epubs.surrey.ac.ukepubs.surrey.ac.uk/842244/1/Clinical Training Protfolio.do… · Web viewWord Count: Exercise during ... carried out a systematic review and meta-analysis to determine

The Effect of Exercise during Pregnancy on Mood 1

The Effect of Exercise during Pregnancy on Mood

Emma Burgess

Submitted for the Degree of

Doctor of Psychology(Clinical Psychology)

School of PsychologyFaculty of Health and Medical Sciences

University of SurreyGuildford, SurreyUnited KingdomSeptember 2017

1


Statement of Originality

This thesis and the work to which it refers are the results of my own efforts. Any

ideas, data, images, or text resulting from the work of others (whether published or

unpublished) are fully identified as such within the work and attributed to their

originator in the text. This thesis has not been submitted in whole or in part for any

other academic degree or professional qualification.

Emma Burgess

2


Overview

This thesis (comprised of the literature review and empirical paper) aimed to explore

the correlation between physical activity and mood in pregnant women. The

literature review of this portfolio presents a narrative review of the research

exploring the correlation between physical activity and mood in the general pregnant

population. The findings of the review suggest that physical activity improves mood

in this population. The empirical paper investigates the correlation between physical

activity and mood over the duration of pregnancy. The findings suggest that

increased physical activity from before pregnancy to the second trimester improves

mood. The Summary of Clinical Experience is an outline of my experiences on 4

different clinical placements. The Table of Assessments outlines the titles of all

assessments completed whilst on the clinical training programme.

3


Table of Contents

Part 1 – Literature Review……………………………………………………..6

Part 2 – Empirical Paper……………………………………………………….52

Part 3 – Summary of Clinical Experience……………………………………..127

Part 4 – Table of Assessments Completed During Training…………………..130

4


Acknowledgements

I would like to thank my thesis supervisors, Professor Chris Fife-Schaw of the

University of Surrey and Dr. Hayley Mills of Canterbury Christchurch University,

for their support with my main research project.

I would also like to thank my Clinical Tutor Dr Eli Joubert for his ongoing support

and advice around my clinical placements and my personal and professional

development as a Clinical Psychologist.

5


Research Part 1 – Literature Review

Exercise during pregnancy and mood in the general pregnant

population: A Review of the Literature

Emma Burgess

Professor Chris Fife-Schaw

Department of Psychology, University of Surrey, UK

Dr Hayley Mills

Section of Sport and Exercise Sciences, School of Human and Life Sciences,

Canterbury Christ Church University, Canterbury, UK

Address for Correspondence for Emma Burgess (corresponding author) & Prof Fife-

Schaw: Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK,

GU2 7XH, 01483 68 6873

Address for Correspondence for Dr Mills: Section of Sport and Exercise Sciences,

School of Human and Life Sciences, Canterbury Christ Church University,

Canterbury, Kent, CT1 1QU, 01227 767700 ext: 3294

Email: [email protected]; [email protected];

[email protected]

Word Count:

6


Exercise during pregnancy and mood in the general pregnant population: A

Review of the Literature

Abstract

Background Antenatal low mood can be harmful to mother and foetus.

Physical activity may help improve mood.

Objectives This paper reviews studies exploring whether physical

activity affects mood in the general pregnant population.to identify gaps

in the literature and directions for future research.

Search strategy Searches using electronic databases from PsycInfo,

Psycharticles and PubMed were conducted.

Methods Study quality is assessed using the NICE screening tools

Results 22 papers met the inclusion criteria and are a mixture of cross

sectional, longitudinal and intervention studies. Subjects were in the

non-clinically depressed pregnant population.

Conclusions This review found some evidence that physical activity

improves mood in the general pregnant population. This conclusion is

based on a small number of heterogeneous low-moderate quality

studies.

Keywords: Antenatal, depression, exercise, physical activity.

7


Introduction

Antenatal depression, defined as a depressive episode during pregnancy, has

a high prevalence in different countries (Previti, Pawlby, Chowdhury, Aguglia, &

Pariante, 2014) and may have a negative effect on the well-being of both mother and

fetus (Glover, 1997). Antenatal depression is a risk factor for postnatal depression

(Heron, O’Connor, Evans, Golding & Glover, 2004). There is therefore need for

prenatal interventions for depressed symptoms.

Current interventions for antenatal depression include antidepressant

medication and psychological therapy (Field et al., 2009; Wipfli, Rethorst &

Landers, 2009). There is evidence to suggest that antidepressant medication may

have adverse effects on neonatal development (Field, 2010) and therapy can be

difficult to access due to long waiting lists (Butler, Chapman, Forman & Beck,

2006). Physical activity may offer an alternative treatment option. The Royal College

of Obstetricians and Gynecologists (RCOG) in the UK recommends 30 minutes of

daily aerobic exercise during pregnancy in the absence of medical or obstetric

complications (RCOG, 2006). NICE (2007) suggest exercise during pregnancy can

be used to manage antenatal depression.

However, despite numerous studies examining the effect of physical activity

on mood in the general population, research into the pregnant population is limited.

There are four recent review papers which investigated the effect of physical activity

on mood in the pregnant population. Two of these review papers are of high quality,

in accordance with the NICE (2012) review screening tool. Daley et al. (2015)

conducted a meta-analysis to establish whether there is sufficient evidence to

conclude that exercise is an effective intervention for preventing and treating

antenatal depression.

8


Gong et al. (2015) carried out a systematic review and meta-analysis to

determine the effectiveness of yoga as an intervention in the management of prenatal

depression. Both these reviews included only randomised controlled trials (RCT’s);

Daley et al. included those which compared any type of exercise intervention with

any comparator in pregnant women and Gong et al. included those which compared a

yoga intervention with any comparator group in pregnant women. Both reviews

identified six papers each; participants were depressed or non-depressed at baseline.

From the six studies identified by Dayley et al., only one used the non-clinically

depressed population. The control groups differed, some studies used standard

prenatal care, others a suitably matched intervention, such as education. The

intervention type also varied in aerobic intensity and duration. The Center for

Epidemiologic Studies Depression Scale (CES-D) was the primary outcome measure

used by the majority of trials, though some studies used other measures such as the

Hospital Anxiety and Depression Scale (HADS). Both meta-analyses revealed a

significant reduction for depression scores for exercise and yoga interventions

relative to comparator groups. The authors report that these findings need to be

considered within the context of the meta-analyses including only a small number of

low-moderate quality trials with significant heterogeneity and wide confidence

intervals.

The other two review papers identified, Shivakumar et al. (2011) and Davis

(2012) are of low quality in accordance with the NICE (2012) review screening tool.

Shivakumar et al. conducted a review which aimed to investigate the potential

benefits of exercise upon pregnant women such as maternal emotional well-being,

depressive symptoms and obstetric outcomes. The authors did not publish their

exclusion and inclusion criteria for the six papers they identified, which were a

9


mixture of cohort and case controlled studies. The papers were described and given a

quality score but statistics and p-values were only provided for two of the studies.

Furthermore, one of the studies used self-esteem as a primary outcome rather than

mood. The authors suggest that more systematic studies are needed to assess exercise

as a treatment alternative for depression during pregnancy.

Davis (2012) aimed to examine the relationship between physical activity and

mood across the perinatal period. The authors published their search terms and

included 16 papers which met their inclusion criteria. The papers are a mixture of

longitudinal studies, cohort studies and RCT’s. Davis describes the findings of the

papers and reports that 14 of the papers identified significant findings that depression

was reduced in pregnant women who engaged in physical activity. Two of the papers

identified reported results which did not reach significance. However, the author did

not synthesize or analyse the findings from the papers identified.

Therefore, although there are two recent high quality meta-analyses exploring

the relationship between mood and physical activity in the general pregnant

population (Daley et al., 2015 and Gong et al., 2015) these review papers only

include RCT’s. Recent review papers which also include correlational and

longitudinal studies (Shivakumar et al., 2011 and Davis, 2012) are of low quality.

Therefore, there is a need for a high quality literature review in this field. With this in

mind, this study aims to:

- Review the available evidence on the effect of exercise during pregnancy on

mood in the general pregnant population.

10


This study will address its aims by reviewing the available evidence from

randomised controlled trials (RCTs), longitudinal and correlational studies on the

effectiveness of exercise on mood in the general pregnant population.

Methods

Search strategy for identification of studies

Searches were conducted by searching four electronic databases;

PsychArticles, Web of Science, Scopus and Medline between 8 th and 12th December

2015. All searches used the following combination of keywords: Exercise OR

physical activity AND Pregnan* AND Depress* OR low mood OR mental

wellbeing. All searches were limited to papers published between the years 2000 and

2015, owing to the large number of journals identified by the searches.

Inclusion/exclusion criteria

Include ExcludeStudies published in English Studies not published in EnglishJournal articles Peer reviewed articles

Book ChaptersDissertations

Published between 2000 and 2015 Not published between 2000 and 2015Pregnant participants Non pregnant participantsMental wellbeing as primary outcome Other primary outcome e.g. eating

behaviour, weight loss, obesity not mental wellbeing

Some measure of physical activity (PA) levels or intervention to manipulate PA levels.

Participants have a physical condition where exercise is prevented e.g. diabetes

Participants are the general pregnant population

Participants are subsections of pregnant population e.g. obese pregnant population, smokers

Study does not use psychiatric samples Psychiatric samplesAny type of review paper where the subject of the review is exercise during pregnancy and wellbeing, including descriptive reviews, systematic reviews and meta-analyses.

Procedure

11


Initially 641 records were identified; 256 from search 1, where PsycArticles

was the database used, 185 from search 2, where Web of Science was the database,

11 from search 3, with Scopus as the database and 189 from search 4, with Medline

as the database. There were a total of 31 duplicates across all searches, with 11 from

search 2, 2 from search 3 and 18 from search 4, giving a total of 610 records

identified. The titles and/or abstracts of these records were screened against the

inclusion/exclusion criteria and 28 studies were identified as meeting the criteria; 21

from search 1, 4 from search 2, 1 from search 3 and 2 from search 4. On looking at

the identified studies in more detail, a further 11 papers were excluded; 8 from search

1, 1 from search 2, 1 from search 3 and 1 from search 4, leaving a total of 17 papers.

Of the 11 excluded papers, 7 were excluded as they used the clinical population, 2 as

there were not written in English, one as the primary outcome was postnatal

depression and one as a mindfulness intervention was used. The bibliographies of

studies were also searched to identify additional studies. This resulted in an

additional 5 papers being identified. Thus, in total, 22 studies were identified as

relevant to this review. The full method is represented within a flowchart as shown

below:

12


13

Potentially eligible records identified through database searches (N=641):

Search 1 PsychArticles (N=256)Search 2 Web of Science (N=185)Search 3 Scopus (N=11)Search 4 Medline (N=189)

Exclusion of duplicate records within searches (N = 31):Search 1 N = 0Search 2 N = 11Search 3 N = 2Search 4 N= 18

Potentially eligible records (N = 610):Search 1 N = 256Search 2 N = 174Search 3 N = 9Search 4 N = 171

Additional potentially relevant articles (N = 5)

Excluded–did not meet criteria (N=582)Search 1 N = 235Search 2 N = 170Search 3 N= 8Search 4 N= 169

Full text articles assessed for eligibility (N = 28):Additional Articles = 5Search 1 N = 21Search 2 N = 4Search 3 N = 1Search 4 N = 2

Exclusion of articles after screening (N = 11):Search 1 N = 8Search 2 N = 1Search 3 N = 1 Search 4 N = 1

Reasons for Exclusion:Used clinical population (7)Not available in English language (2)Primary outcome postnatal depression (1)Mindfulness intervention used (1)

Articles included in the review (N = 22)


Assessment of study quality

The selected studies were classified into two categories; intervention studies

and quantitative studies reporting either correlations or associations, which were

either longitudinal or cross sectional by design.

Intervention Studies. The methodological quality of each intervention study

was assessed using the Quality appraisal checklist for quantitative intervention

studies (NICE, 2012). It enables a reviewer to appraise a study's internal and external

validity after addressing the following key aspects of study design; characteristics of

study participants, definition of, and allocation to, intervention and control

conditions, outcomes assessed over different time periods and methods of analyses.

Quantitative studies reporting correlations or associations. The

methodological quality of each study reporting a correlation or association was

assessed using the Quality appraisal checklist (NICE, 2012). This checklist enables a

reviewer to appraise a study's internal and external validity after addressing the

following key aspects of study design: characteristics of study participants;

definition of independent variables; outcomes assessed and methods of analyses.

Data Synthesis and Data Analysis

Intervention Studies and Studies reporting correlations and associations.

Both quality appraisal checklists are comprised of five sections which are answered

with ‘++’ ‘+’, ‘-’, NR or NA. A ‘++’ indicates that for that particular aspect of study

design, the study has been designed or conducted in such a way as to minimise the

risk of bias. A ‘+’ indicates that either the answer to the checklist question is not

14


clear from the way the study is reported, or that the study may not have addressed all

potential sources of bias for that particular aspect of study design. A ‘-’ is reserved

for those aspects of the study design in which significant sources of bias may persist.

Not reported (NR) is reserved for those aspects in which the study under review fails

to report how they have (or might have) been considered. Not applicable (NA) is

reserved for those study design aspects that are not applicable given the study design

under review (for example, allocation concealment would not be applicable for

case–control studies). For intervention and correlation studies, two overall quality

ratings are given, taking into account all the information gathered. These are an

overall rating for quality and external validity. These are given a score of -, + or ++.

All papers and overall quality scores are presented in Table 3. An example of the

individual checklists used for assessing study quality is presented in Appendices 2

and 3. Quality scores were assimilated to gather an overall picture of the research

findings.

Results

The results are presented in Tables 1, 2 and 3. Each table is presented in 2

sections; correlational and association studies and intervention studies, which include

RCTs. The correlational studies and intervention studies are formatted in accordance

with tables outlined in the NICE guidelines (NICE, 2012).

15


Table 1.

Description of study details

Study Study Aim Method ParticipantsMean age and (SD)

Quantitative studies reporting correlations or associations1. Downs et al. (2008) Determinants of pregnancy and postpartum depression: Prospective influences of depressive symptoms, body image satisfaction, and exercise behavior.

To examine the associations between and the extent to which depressive symptoms (DS), body image satisfaction (BIS), and exercise behaviour (EB) prospectively explains trimester-specific and postpartum depression

Ppts allocated to one of 3 EB groups based on self-reported pre-pregnancy PA; (1) Active (≥120 mins weekly activity), (2) Somewhat Active (30-120 mins weekly activity), (3) Not Active (no weekly activity).Ppts completed self-reported measures midway through their 1st, 2nd & 3rd trimesters and at 6-weeks postpartum

N = 230 (96 in Group 1, 113 in Group 2, 11 in Group 3, 10 excluded due to missing data)Age: mean=30.05, SD=4.13, Range=18-43Setting: Outpatient (Private Clinic Pennsylvania)Other: Sample mostly Caucasian, married, educated to graduate level, family income ≥ $40,000, overweight

2. Orr et al. (2006). Exercise participation before and during pregnancy among low-income, urban, black women: The Baltimore Preterm Birth Study.

To explore the correlation between various psychosocial and behavioural factors with exercise during pregnancy

Ppts completed measures before and during pregnancy. Classified as those that participated only in strenuous activities; those that participated only in non-strenuous activities; and those that participated in both strenuous and nonstrenuous activities based on self-report

N = 922 pregnant black womenAge: Over 18Setting: women recruited at 1st prenatal visit to one of 5 hospital based prenatal clinics located in Baltimore between 1993 & 1995.

3. Watts et al. (2013) ). Depressive symptoms during pregnancy: Exploring the role of sitting. Mental Health and Physical Activity

To explore the relationship between sitting behaviour and depressive symptoms in a population of pregnant Australian women.

Interviews conducted both in-person at the hospital and via telephone approximately one week after recruitment.

N = 81Age: N/RSetting: antenatal clinic of a large Brisbane public hospital (Queensland, Australia).Other: Under-represented indigenous women, women >36 & low income households. Over represented trimester 2.

4. Takahasi et al. (2013) To investigate the Women completed questionnaire and N = 1,447

16


Mental health and physical inactivity during pregnancy: a cross-sectional study nested in the BRISA cohort study.

association between mental health and physical inactivity in pregnant women in the 2nd trimester of pregnancy.

interviewWomen classified into 3 PA categories: high, medium, low

Age: N/RSetting: women in 2nd trimester attending private and public hospitals in São Luís, State of Maranhão, Northeast Brazil between March 2010 and June 2011Other: convenience sample

5. Loprinzi et al. (2012) Physical activity and depression symptoms among pregnant women from the National Health and Nutrition Examination Survey 2005–2006.

To examine the association between objectively measured physical activity and depression symptoms among a nationally representative sample of pregnant women

Ppts were interviewed in their homes and subsequently examined in mobile examination centers (MEC) across numerous U.S. geographic locations.

N = 141Age: N/RSetting: Ppts from the National Health and Nutrition Examination Survey (NHANES) 2005–2006Other: The NHANES employs a representative sample of noninstitutionalized U.S. civilians, selected by a complex, multistage probability design.

6. Poudevigne & O'Connor (2005) Physical activity and mood during pregnancy.

To compare 3 PA measures in pregnant women and examine mood correlates of PA changes during pregnancy

Once monthly, for 7 consecutive months, total weekly energy expenditure (TWEE) was assessed using a physical activity diary (PAD) and a recall interview (PAR). Accelerometers were worn for 3 days each month. Mood also assessed.

N = 12 (matched with 12 non-pregnant women)Age: 18-40Setting: Ppts self-selected through adverts in GeorgiaOther: Ppts mostly Caucasian, middle class

7. Goodwin et al (2000) Body image and psychological well-being in pregnancy: a comparison of exercisers and non-exercisers.

To compare the perceptions of body image and psychological well-being between exercising and non-exercising pregnant women

Data collected at 2 intervals during the pregnancy, 17 weeks and 30 weeks gestation. Retrospective data relating to the prepregnancy period was collected on entry into the studyAfter the second data collection session the women were allocated to 3 groups by self-selection, based on the frequency, duration and intensity level of their recreational exercise participation.

N = 72Age: 20-40 yearsSetting: Convenience sample recruited recruited from community and hospital based pre-natal classes in AustraliaOther: Ppts mostly Caucasian, well educated, self-selected

8. Da Costa et al. (2003). Self-reported leisure-time physical activity during pregnancy and relationship

1) To examine self-reported LTPA patterns during each trimester of pregnancy.

Ppts put into 2 groups = exercisers and non-exercisers based on answering yes or no to whether they have participated inLeisure-time physical activity (LTPA) in

N = 180Age: 19-40Setting: Recruited from 5 obsetrics/ gynecology units in Montreal, Canada.

17


to psychological well-being. 2) To determine the relationship between LTPA and psychological well-being during each trimester of pregnancy.

the last month.Participants completed 3 structured interviews at each trimester.

Other: Women in 1st trimester

9. Tendais et al. (2011). Physical activity, health-related quality of life and depression during pregnancy.

To examine PA patterns of women from pre-pregnancyto the 2nd trimester of pregnancy, and the relationship between PA status based on PA guidelines and HRQoL and depression changes over pregnancy

Ppts completed questionnaires at 2 time points: 10-15 weeks (also asked about 3 months before pregnancy) and 19-24 weeksWomen were classified as active or low active pre-pregnancy based on guidelines

N = 78Age: 18-40Setting: Ppts attending 1 of 4 private obstetric clinics in Porto, PortugalOther: Ppts in 1st or 2nd trimesters

10. Gjestland et al. (2013). Do pregnant women follow exercise guidelines? Prevalence data among 3482 women, and prediction of low-back pain, pelvic girdle pain and depression.

1) describe exercise-level mid-pregnancy; (2) examine sociodemographic variables associated with exercise & (3) analyse association between exercise in mid pregnancy and low-back pain, pelvic girdle pain & depression in pregnancy week 32

Questionnaires completed about exercise, sociodemographic variables, low-back pain, pelvic girdle pain and depression at pregnancy weeks 17–21 and 32

N = 3751Age: N/RSetting: Ppts recruited from Akershus Birth Cohort study at Akershus University Hospital Norway at pregnancy week 17 from Nov 2008 to April 2010

11. Demissie et al. (2011). Associations between physical activity and postpartum depressive symptoms

To expand previous research and examine the association between overall and domain-specific moderate-to-vigorous physical activity(MVPA) and depressive symptoms during pregnancy

Women asked to participate in two research clinic visits (at <20 and 24–29 weeks' gestation) in order to obtain biological samples, 2 telephone interviews (at 17–22 and 27–30 weeks' gestation), and 2 self-administered questionnaires given at each of the clinic visits and mailed back to study staff.

N = 1220Age: >16Setting: Ppts recruited between January 2001 and June 2005 from prenatal clinics at the University of North Carolina (UNC) Hospitals.Other: Ppts ≤20 weeks gestation

Intervention Studies

18


12. Gaston & Prapavessis (2013) Tired, moody and pregnant? Exercise may be the answer.

To examine whether engaging in a short (4 week) exercise intervention programme would be associated with improvements in a wide range of psychological well-being constructs in previously inactive pregnant women.

Ppts completed 7-day baseline assessment before being randomized into 1 or 3 experimental groups; (1) information only based on protection motivation theory (PMT),(2) PMT based intervention + action planning,(3) PMT intervention + action planning + coping planning.

N = 56Age: N/RSetting: Ppts responded to promotion of study through newspaper article, an online parenting group & midwifery clinic in Canada between June 2010 & May 2011

13. Ji & Han (2010). The effects of Qi exercise on maternal fetal interaction and maternal well-being during pregnancy.

To investigate the effects of Qi exercise on healthy pregnant women.

Intervention group: 2x90 minute weekly Qi exercise sessions for 12 weeks. Control group: TAU3 month follow up

N = 80Age: N/RSetting: Convenience sample recruited from a women’s wellness center and a women’s health clinic in Seoul, KoreaOther: Gestational age > 18 weeks

14. Robledo-Colonia et al. (2012). Aerobic exercise training during pregnancy reduces depressive symptoms in nulliparous women: a randomised trial.

To determine whether a 3-month supervised aerobic exercise program decreases depressive symptoms in nulliparous pregnant women.

Ppts randomly allocated into 2 groups: aerobic exercise plus usual prenatal care, or usual prenatal care only.PA group: 3x60min exercise classes per week for 3 months (16-20 weeks gestation). Control group did not attend classes.

N = 80Age: 16-30Setting: Ppts recruited from prenatal care at 1 of 3 tertiary hospitals in Cali, ColombiaOther: Ppts between 16 & 20 weeks gestation

15. Satyapriya et al. (2013) Effect of integrated yoga on anxiety, depression & well being in normal pregnancy.

To study the effect of integrated yoga on pregnancy experience, anxiety, and depression in normal pregnancy.

Yoga group (n = 51) practiced integrated yoga and control group (n = 45) did standard antenatal exercises, one hour daily, from 20th to 36th week of gestation.

N = 96Age: 20-35Setting: Ppts recruited from a pool of 200 who had registered for antenatal care at Maiya multispecialty hospital in Bengaluru, IndiaOther: Ppts between 18 & 20 weeks gestation

16. Lox & Treasure (2001) Changes in Feeling States Following Aquatic Exercise During Pregnancy

To investigate (a)changes in acute exercise-induced feeling states following a single bout of exercise (b changes in feeling states

45 min of aquatic aerobic exercise, 2 weekly classes for 6-weeksNo randomisation, no control group.

N = 44Age: N/RSetting: Ppts self-registered for prenatal aquatics exercise classes at a large hospital located in a Chicago suburb community.

19


generally experienced during the present pregnancy (prior to participating in exercise program) compared to feeling states generally experienced during 6-week exercise program

Other: Ppts were middle-to-upper-income Caucasian women

17. Polman et al. (2007). Effect of a single bout of exercise on the mood of pregnant women.

To investigate the influence of a single bout of exercise of the mood of pregnant women participating in an aqua or studio based exercise class compared to parentcraft and a control group

4 conditions; an aqua class, gym studio class, parentcraft class and control.Single session pre-/post-exercise mood-state evaluation

N = 66Age: N/RSetting: Ppts recruited from local gym/fitness establishments, hospital parental classes and local GP surgeries in Leeds, UK.Other: Ppts in 2nd or 3rd trimester.

18. Guszkowska et al. (2013). Influence of a single physical exercise class on mood states of pregnant women.

To define the influence of a single physical exercise class on mood states of pregnant women and to establish the socio-demographic and personality predictors of mood changes.

Intervention group (n=62) attended exercise classes. Conducted in groups of 6-10 ppts.Control group (n=47) participated in traditional childbirth education classes

N = 109Age: 19-37 yearsSetting: Recruitment for the study was conducted during registration for 8 prenatal courses in Warsaw and lasted for 8 months.Other: Ppts were between the 17th and 32nd weeks of their gestation

19. Guszkowska et al. (2013).Influence of a relaxation session and an exercise class on emotional states in pregnant women.

To compare changes in state anxiety and mood dimensions in pregnant women after a session of physical exercise and relaxation

Volunteers chose the supplementary classes according to their preferences.Both groups n=46, 8 weeks (2 classes). Exercise/relaxation + usual birthing classes. Relaxation – 30-50 minutes, Exercise – 50 minutes.Emotional state of ppts measured immediately before and after class.

N = 92Age: 22-38 yearsSetting: WarsawOther: Ppts enrolled into the study were between the 24th and 33rd weeks of their pregnancies

20. Kieffer et al. (2013). Effect of the healthy MOMs lifestyle intervention on

To examine the effectiveness of a culturally & linguistically tailored,

Ppts randomized to the Healthy MOMs Healthy Lifestyle Intervention (MOMs) or the Healthy Pregnancy Education

N = 275Age: was ≥18 yearsSetting: Ppts recruited at CHASS,

20


reducing depressive symptoms among pregnant Latinas. American journal of community psychology,

social support-based, healthy lifestyle intervention led by trained community health workers in reducing depressive symptoms among pregnant and early postpartum Latinas.

(control) group.Measures were collected at three time points: pre-intervention (baseline), immediately after the intervention during pregnancy (follow-up), and approximately 6 weeks postpartum.

Supplemental Nutrition Program for Women, Infants, and Children (WIC) clinics, and through posters and flyers distributed to community organizations and in public settings in Southwest Detroit.Other: Ppts were <20 weeks gestational at the eligibility screening; all ppts were Latinas

21. Perales et al. (2015) Exercise During Pregnancy Attenuates Prenatal Depression A Randomized Controlled Trial.

To examine whether a supervised exercise program (EP) reduces depressive symptoms in pregnant women.

Ppts randomized into exercise group (EG) or control group (CG).EG: 55-60 mins sessions per week that began between 9 & 12 weeks of gestation and continued until the end of the 3rd trimester

N = 166 (90 in EG, 77 in CG)Age: N/RSetting: Ppts living in Madrid, Spain, and who underwent ultrasound examination at limit 12 weeks of pregnancy were invited to participate.Other: Ppts excluded if partaking in PA

22. Newham et al. (2014) Effects of antenatal yoga on maternal anxiety and depression: a randomized controlled trial.

To test the efficacy of yoga as an intervention for reducing maternal anxiety during pregnancy.

Ppts randomized to Yoga Group (8-week course of antenatal yoga in groups of 10-11) or TAU.Measures taken after recruitment & after 8 weeks

N = 59 (31 in yoga group, 28 in TAU)Age: ≥ 18 yearsSetting: Ppts identified by sonographers or midwives at their 20-week ultrasound or 24-week routine appointment in Manchester, UK.Other: Ppts in 2nd or early 3rd trimester

21


Table 2.

Measures and Results of included studies

StudyQuantitative studies reporting correlations or associations

Measures Analysis Results Limitations

1. Downs et al. (2008) Determinants of pregnancy and postpartum depression: Prospective influences of depressive symptoms, body image satisfaction, and exercise behavior

Personal History Questionnaire; The Centers for Epidemiological Studies-Depression (CES-D) Scale;Body Areas Satisfaction Scale (BASS); Leisure-Time Exercise Questionnaire (LTEQ)

Four hierarchical regression analyses (HRA) were used to examine the contributions of DS, BIS, and EB for predicting depression across the study time periods

DS, BIS, and EB were associated across the 3 pregnancy time points and postpartum; DS and BIS were main determinants of later depression in pregnancy and postpartum; the moderating influence of pre-pregnancy EB was evident in early pregnancy

Lacks generalizabilitySelf-report measuresProspective study does not provide information on causal mechanisms

2. Orr et al. (2006). Exercise participation before and during pregnancy among low-income, urban, black women: The Baltimore Preterm Birth Study.

Self-report of EB; 41-item Prenatal Social Environment Inventory (PSEI) used to assess exposure to stressors; CES-D; John Henryism Active Coping Scale (JHAC 12) used to measure propensity to cope actively with environmental stressors.Medical records checked for drug and alcohol behavior

Bivariate associations were evaluated for statistical significance by using the chi-square statistic.

1) Increased coping correlated with increased EB)2) Increased EB correlated with decreased depression. 3) Exposure to stressors and behavioural factors not associated with exercise participation before or during pregnancy

Lacks generalizability

3. Watts et al. (2013) ). Depressive symptoms during pregnancy: Exploring the role of sitting. Mental Health and Physical Activity

Depressive symptoms were measured using the Hospital Anxiety and Depression Scale (HADS).Sitting behaviour was measured using the Australian

Linear regression analyses were used to explore the relationship between sitting and depressive symptoms, whilst controlling for known covariates.

The model investigating “total sitting time” showed no association with depressive symptoms (F= .77, p = 0.38). The model investigating

Use of convenience sample which overrepresented ppts in trimester 2.Self-report measure of sitting time used.Underpowered.

22


Women’s Activity Survey (AWAS). Several potential covariates were also assessed.

“planned leisure sitting time” was statistically significant (F = 4.42, p =0.04): significant contributors to the model variance were HADS anxiety score (p = 0.003) and number of existing children (p = 0.02).

4. Takahasi et al. (2013)Mental health and physical inactivity during pregnancy: a cross-sectional study nested in the BRISA cohort study.

Short version of the International Physical Activity Questionnaire (self-report)Symptoms of depression and anxiety, and stress levels were assessed using CES-D, the Beck Anxiety Inventory and the Perceived Stress Scale, respectively

Unadjusted and adjusted analysis of the factors associated with physical inactivity was conducted using robust Poisson regression adopting a significance level of 0.05

Association found between physical inactivity and not living with a partner (OR = 1.28), having a manual occupation (OR = 0.71) and normal and low levels of anxiety (OR = 1.46 & OR = 1.44, respectively). No association observed between physical inactivity and symptoms of severe depression and perceived stress.

Self-report measure for PA. Measures for low mood may not be most suitable for use in pregnant population.Given the cross-sectional nature of the data, caution must be taken in the interpretation of causal relationships between variables.Use of a convenience sample limits generalizability.

5. Loprinzi et al. (2012) Physical activity and depression symptoms among pregnant women from the National Health and Nutrition Examination Survey 2005–2006.

Participants wore an ActiGraph accelerometer for 7 days following their examination and completed the Patient Health Questionnaire-9 (PHQ-9) to assess depression status.

A logistic regression was used to examine the association between mean duration of MVPA and depression status, as well as percent meeting physical activity guidelines

Women classified as not having depression symptoms(n=114) spent significantly more time in MVPA than those classified as having some depression symptoms

Cross-sectional study precludes making any causal inferences between objectively measured physical activity and depression symptoms.Relatively low internal consistency of PHQ-9.

6. Poudevigne & O'Connor (2005) Physical activity and mood during pregnancy

PA measured with the Bouchard diary extended to 7 days, the 7-day recall from

A two-factor mixed-model ANOVA was used to analyse the data (2 groups

Changes in PA were not correlated to changes in mood in either group

Small sampleSelf-selectedLacks generalizability

23


Blair and the MTI accelerometer each gestational month from weeks 12 to 36. Scores on the depression and anxiety scales from the POMS were reported from weeks 12 to 36.

[pregnant women vs non pregnant women] 7 times across pregnancy

7. Goodwin et al (2000) Body image and psychological well-being in pregnancy: a comparison of exercisers and non-exercisers.

A self-report exercise history questionnaire and a 10 item Body Cathexis Scale were completed at both time points. The General Health Questionnaire (GHQ-28) was administered at 2nd time point.

The t-test and two-factor repeated measures ANOVA used for analysis of parametric data. Chi-square and Mann Whitney U used for non-parametric data. Regression analyses used to predict relationships between independent variables and the dependent variable.

When the exercise group was compared with the non-exercise group at late pregnancy, a significant difference was found for overall psychological well-being and for sub-scales somatic symptoms, and anxiety and insomnia (unpaired t-test, p< 0.05).

GHQ measure only used at 2nd time pointSelf-selection of participantsLacks generalizability.

8. Da Costa et al. (2003). Self-reported leisure-time physical activity during pregnancy and relationship to psychological well-being.

Leisure-time physical activity (LTPA); Depression measure (DACL), Pregnancy Experiences Questionnaire (PEQ), state-trait anxiety inventory (STAI), Hassles Scale

Independent samples t-tests comparing exercisers and non-exercisers in each trimester

A significantly greater number of women who were not exercising in the 1st trimester were depressed (33.1%; n = 42) compared to exercisers (15.1%, n = 8; x' (1) = 6.02, p = 0.02). Similar group differences were shown in the 2nd trimester. No group differences were shown for the 3rd trimester.

Self-report measure of PAFindings suggest an association, but not necessarily a causal link between regular LTPA and enhanced psychological well-being.Lacks generalizability.

9. Tendais et al. (2011). Physical activity, health-related quality of life and depression during pregnancy.

HRQoL was assessed with the 36-Item Short Form Health Survey (SF-36). PA data was collected by the Global Physical Activity

Repeated-measures ANOVA carried out to determine changes in modes and intensities of PA over time. Similar analyses

Significant group (active or low active) differences were noted in mental health [F(2,46) = 4.06, p = 0.024] mean scores. Low active

PA examined using indirect methodSmall number of pregnant women included and multiple comparisons made

24


Questionnaire (GPAQ). Depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS)

performed to test for differences between active and low active groups in HRQoL dimensions & depression scores.

women before and during 1st trimester of pregnancy had higher mental health at 9-24 weeks than active women that became low active at 10-15 weeks of pregnancy (p = 0.015)

Lacks generalizability.

10. Gjestland et al. (2013). Do pregnant women follow exercise guidelines? Prevalence data among 3482 women, and prediction of low-back pain, pelvic girdle pain and depression.

Ppts asked 3 questions about frequency, intensity & duration of PA. Categorized exercise by frequency into 3 groups <once a week (never+<once a week), 1-2 times a week and ≥ 3 times a week.Depression measured using The Edinburgh Postnatal Depression Scale (EDPS)

Results were analysed by logistic regression and are presented as crude (cOR) and adjusted OR (aOR) with 95% CI

Women exercising 1–2 times a week were less likely to report depression (aOR: 0.66, 95% CI 0.48 to 0.91). However, the results did not reach statistical significance among participants exercising ≥3 times a week.

No clinical assessment to diagnose low-back pain, pelvic girdle pain and depression.Self-reporting of PANot generalizable to non-Scandinavian ethnic groups.

11. Demissie et al. (2011). Associations between physical activity and postpartum depressive symptoms

Physical Activity Questionnaire (PAQ)CES-DLife Experiences Survey (LES)

Logistic regression modelling was utilized to calculate odds ratios (OR) and 95% confidence intervals (CI).

Active women with ≤2.67 h/week of total MVPA had almost half the odds of having high depressive symptoms as compared to women with no MVPA

CES-D is a self-report measureMultiple tests carried out and not adjusted forPA only assessed over past weekLimited generalizabilityPpts excluded may differ in characteristics from those included.

Intervention Studies12. Gaston & Prapavessis (2013) Tired, moody and pregnant? Exercise may be the answer.

Mood measures:Profile of Mood States–Short Form (POMS-SF)State Trait Anxiety Scale-Trait version (STAI-T)Behavioural Measures: Exercise was assessed using

Two (group: meeting vs. not meeting guidelines) by 2 (time: baseline vs. follow-up) repeated measures ANOVAs were computed for POMS-SF and STAI-T variables

Factorial repeatedmeasures ANOVAs demonstrated that ppts who met Canadian guidelinesfor exercise during pregnancy at week 4 experienced significant decreases in depression,

Self-selection biasLimited generalizabilityNo true control groupInvestigator delivering the intervention was not blinded to group assignment

25


accelerometers anger, tension, fatigue, trait anxiety & increases in vigour compared to those who were not meeting guidelines.

13. Ji & Han (2010). The effects of Qi exercise on maternal fetal interaction and maternal well-being during pregnancy.

Intrapersonal Communication Questionnaire (Talking to Your Baby), Zung’s Self-rating Depression Scale (ZSDS), State Trait Anxiety Inventory (STAI) & Pregnancy Mild Discomfort Index

ANCOVA used to test the effects of Qi exercise on study outcomes

At 3-month follow-up, women in Qi exercise group showed significantly higher levels of maternal/fetal interaction& lower levels of maternal depressive symptoms &physical discomfort than control group. No significant between-group difference in anxiety.

Qi exercise sessions – varied in duration and group size.Quasi experimental design-small nPpts self-selectedLacks generalizabilitySelf-report of pregnancy-related symptoms & discomforts.Difficult to determine which Qi exercise intervention component contributed more or less to improving study outcomes

14. Robledo-Colonia et al. (2012). Aerobic exercise training during pregnancy reduces depressive symptoms in nulliparous women: a randomised trial.

CES-D Unpaired t-test used to estimate between-group difference in CES-D scores. Significance level set at <0.05

Experimental group reduced their depressive symptoms on the CES-D questionnaire by 4 points (95% CI 1 to 7) more than the control group

Therapists and participants not blinded.Participants already exercised.Data reported for completers only

15. Satyapriya et al. (2013) Effect of integrated yoga on anxiety, depression & well- being in normal pregnancy.

Pregnancy related experience (PEQ), State (STAI I) anxiety, Trait (STAI II) anxiety and Depression (HADS)

Independent samples ‘t’ test used for baseline comparisons & mean differences within groups. As the data were not normally distributed, Mann Whitney test (between groups) and Wilcoxon’s test (within groups) were used.

There was significant difference between groups (Mann Whitney p < 0.001) in all variables.PEQ, STAI I, STAI II & HADS decreased in intervention group relative to control group.

Possible interaction between the groups could not be avoided.Requests for shift from control to yoga group due to popularity of yoga through the media led to unexpected number of drop outs.Not generalizable

16. Lox & Treasure (2001) Changes in Feeling States Following Aquatic Exercise

Pre-pregnancy PA (3 categories: regular, occasional or non-exerciser).

Repeated measures MANOVA

Significant main effect for time, F(3, 33) = 9.82, p < .0001, indicating

Sample was composed of self-selected, middle-to-upper-income Caucasian females and, thus,

26


During Pregnancy Subjective Exercise Experiences Scale SEES – completed weekly after exercise class weeks 2-5 & at beginning and end of programme (weeks 1 & 6)SEES has 3 subscales: positive well-being (PWB), psychological distress (PD) & fatigue (FA)

significant differences existed between pre- and post-exercise feeling states. PWB was higher (d = 0.93) and PD and FA were lower (d = -0.74 and -0.68, respectively) following acute exercise bout, as compared to the pre-exercise assessment.

findings may not generalize to other populations.Cannot be certain as to the mechanisms of the changes reported in this paper, largely because of the lack of an “attention” control group in the study design.

17. Polman et al. (2007). Effect of a single bout of exercise on the mood of pregnant women.

POMS ANOVAS (one and 2 way) used.

Condition main effect for vigour, significant interaction between vigour and total mood. Post hoc comparisons - no differences between 3 conditions, both exercise classes increased vigour from pre to post exercise (P<0.01).Post hoc comparisons for depression show significant decrease in depression score for aqua condition (P <0.05)

Non-random allocation.Exercise conditions – ppts already exercised and therefore may be predisposed to enjoy the exercise experience.

18. Guszkowska et al. (2013).Influence of a single physical exercise class on mood states of pregnant women.

Emotional states were assessed with the UWIST Mood Adjective Checklist-tense arousal (TA), energetic arousal (EA) & hedonic tone (HT); Personality traits were measured with the NEO-FFI, LOT-R and STAI; socio-demographic data also

2 way ANOVA After a single class, the 2 groups differed significantly in 2 dimensions (EA & TA.) Ppts in the experimental condition had more energy, were less tense, and were more relaxed. The HT was higher in the group of exercising women.

Lacks generalizabilityAssignment of ppts to the groups did not meet the conditions of randomization, as the respondents chose the group according to their preferences.Women in earlier stages of pregnancy, more physically active prior to pregnancy, and who rated their own health better took part in

27


collected by survey developed by researchers

the PA program.

19. Guszkowska et al. (2013).Influence of a relaxation session and an exercise class on emotional states in pregnant women.

Emotional states were assessed with the UWIST Mood Adjective Checklist and State–Trait Anxiety Inventory.

ANOVAS The main time effect was observed in all emotional states assessed: the level of state anxiety and tension arousal decreased and the level of hedonic tone and energetic arousal increased. The main group effect was significant only for energetic arousal (higher level in the exercise group).

Lacks generalizablityAssignment of ppts to the groups did not meet the conditions of randomisation, because the respondents chose the group according to their personal preference.Women in the physical exercise group had slightly higher energetic arousal before the classes than women in the relaxation group

20. Kieffer et al. (2013). Effect of the healthy MOMs lifestyle intervention on reducing depressive symptoms among pregnant Latinas. American journal of community psychology,

Depressive symptoms within the past week were measured with the CES-D.

Linear mixed models used to estimate mean CES-D score with 95% CI’s & to make comparisons between the MOMs intervention & control groups at baseline, follow-up & postpartum time points.

The MOMs group had a significantly greater decrease in CES-D score from baseline to follow-up than the control group (mean difference in change score = -1.83 points; 95% CI: -3.59, -0.07; p = 0.042).

Lacks ecological validity as study heavily funded.Lacks generalizability to other ethnicitiesSmall nUnclear of clinical significance, as did not use a measure of clinical depression.

21. Perales et al. (2015) Exercise During Pregnancy Attenuates Prenatal Depression A Randomized Controlled Trial.

CES-D Student’s paired t-test was used to assess the effect of the EP. Unpaired t-test used to examine differences in descriptive characteristics, pregnancy outcomes & CES-D scores between 2 groups.

Significant differences found between groups at end of study in CES-D scores (EG: 7.67 ± 6.30 vs. CG: 11.34 ± 9.74), & in percentages of women depressed (EG: n= 11/12.2% vs. CG: n= 19/24.7%, p = .04).

Exercise group very well described. Control group not described at all. Unsure whether the control was TAU/no intervention.Generalisability not reported.Unsure if population representative of local pregnant population.

22. Newham et al. (2014) Effects of antenatal yoga on maternal anxiety and depression: a randomized

EDPSState (STAI S) anxietyTrait (STAI T) anxiety

Comparisons of linear data for TAU vs. yoga group made using the Mann Whitney U test, whereas Chi-square test or Fisher’s

There was no significant difference in the STAI-S, STAI-T, or EPDS scores recorded at the two time points in the TAU or yoga

Some women in the TAU group participated in alternative yoga classes affecting the fidelity of the comparison groups.Program’s educational element

28


controlled trial. Exact Test used to analyze categorical data. Within-group comparisons of baseline & follow-up mood outcome scores and of pre- and post-class assessment of STAI-S scores & salivary cortisol levels made using Wilcoxon signed rank test

group. might influence the mood of the participants in the yoga group.Potential effect of receiving attention from the instructor and also the subject-expectancy effect could contribute to findings Women’s prior beliefs about effects of yoga could influence mood.Homogeneity of group restricts generalizability.

Table 3.

29


Methodological Quality

Study Quality Score External Validity Score

1. Downs et al. (2008) ++ +2. Orr et al. (2006) + -3. Watts et al. (2013) + -4. Takahasi et al. (2013) ++ -5. Loprinzi et al. (2012) ++ ++6. Poudevigne & O'Connor (2005) - -7. Goodwin et al (2000) - -8. Da Costa et al. (2003) + +9. Tendais et al. (2011) + +10. Gjestland et al. (2013) + -11. Demissie et al. (2011) ++ -Intervention Studies12. Gaston & Prapavessis (2013) + -13. Ji & Han (2010) - -14. Robledo-Colonia et al. (2012) ++ +15. Satyapriya et al. (2013) + -16. Lox & Treasure (2001) - -17. Polman et al. (2007) - -18. Guszkowska et al. (2013) - -19. Guszkowska et al. (2013) - -20. Kieffer et al. (2013) ++ ++21. Perales et al. (2015) + +22. Newham et al. (2014) + +

30


Methodological Quality

Studies reporting correlations and associations. The search identified

eleven papers which looked at correlations and associations. Four studies

achieved a quality score of ++, five a score of + and two a score of -. For the

external validity ratings, one study gained a score of ++, three a score of + and

seven a score of -. The populations used varied across studies, with four using a

Caucasian American population, two an Australian population, one study used

women from Canada, one used women in Norway, one used women from Brazil

and one, women from Portugal. The majority of studies therefore used a

Caucasian, well educated, financially stable, married, middle class population,

limiting generalizability to women of different ethnic and socioeconomic

backgrounds. However, Or et al (2006) used a cohort of black, low income

women and found that proportionately more women with lower levels of

depressive symptoms engaged in exercise during pregnancy (65.9%) than those

with higher levels of depressive symptoms (51.8%). Takahsi et al. (2013) used

Brazilian women and found no association between physical activity and

depression. Loprinzi et al. (2012) used a racially ethnically diverse sample of US

pregnant women and found women classified as not having depression symptoms

spent significantly more time being physically active than those classified as

having some depression symptoms. Using participants of a particular population

limits the generalizability of studies to pregnant women of different populations

and thus impacts the external validity score and overall quality of the papers.

The overall quality score of studies was affected by the number of

participants used, and thus the statistical power achieved. Three of the eleven

31


papers were underpowered due to a small number of participants; Watts et al.

(2013), Poudevigne and O’Connor (2005) and Tendais et al. (2011). One paper,

Tendais et al., also used multiple comparisons in their statistical analyses without

correcting for Type 1 error rate, which further impacts on the statistical power of

the paper.

Several studies, such as Demissie et al. (2011), did not analyse the data

from excluded participants or those who dropped out during the study, to see

whether they differed across any characteristics from the participants included.

This limits the overall quality rating of these studies.

Studies used different reliable and valid measures to record mood levels

such as the Edinburgh Postnatal Depression Scale (EPDS), The Centers for

Epidemiological Studies-Depression (CES-D) Scale and the Patient Health

Questionnaire-9 (PHQ-9). A variety of measures were used to record physical

activity, mainly in the form of self-report questionnaires which are validated and

have good reliability. Examples of these self-report questionnaires include the

Global Physical Activity Questionnaire (GPAQ) and the International Physical

Activity Questionnaire. Many of the studies also took other measures, all of which

were reliable and valid, such as the General Health Questionnaire (GHQ-28), the

Prenatal Social Environment Inventory (PSEI) and the Short Form Health Survey

(SF-36). The use of reliable and valid outcome measures across studies improves

the overall quality score of these studies.

However, the wide use of different measures makes it difficult to compare

findings across studies. Furthermore, there are potential problems with the

measures themselves. For example the PHQ-9, which measures mood, has a

relatively low internal consistency, suggesting that the measure may need

32


additional development work to be reliable in this population (Loprinzi et al.,

2012). Several studies used the CES-D or the SCID to assess pregnant women’s

depression. However, this may not the best choice due to misinterpretation of

somatic symptoms of pregnancy for certain items (e.g., tiredness, lack of energy).

Some studies used a higher cut off point for the presence of symptoms of

depression in order to address this problem and minimize bias (Radloff, 1977).

Some studies used the Edinburgh Postnatal Depression Scale (EPDS), which may

be a better choice for use in this population. Other studies utilised the Profile of

Mood States (POMS), which has been criticised because the test was initially

validated for use in clinical populations and includes only one positive mood

dimension (see LaFontaine et al., 1992). In the light of these and other criticisms,

future reliance on the POMS as the primary measure of mood state in exercise

research must be questioned.

In terms of measuring physical activity levels, all except one study used

only self-report measures of physical activity. Self-report rather than objective

measures make data vulnerable to over- or under-reporting (Prince et al., 2008).

However, the self-report instruments used are validated, and as such the results

are comparable to other studies using the same self-report measures (Watts et al.

2013). Although some studies have found self-reported physical activity to

correlate with objective measures of physical fitness (Da Costa et al., 2003) and

some measures, such as the GPAQ have been validated against accelerometers

(Tendais et al., 2011), the level of correlation with objective measures is far from

being good. Self-report measures are often used because they are cheap and they

impose little on the participants. However, if research was ideally resourced,

objective measures would be preferable.

33


Intervention studies. The review identified eleven intervention studies.

Only two studies achieved a quality score of ++, with four achieving a score of +

and five a score of -. In terms of external validity, one study gained a rating of ++,

three a rating of + and seven a score of -. Participants were recruited from various

settings and countries, including Korea, Detroit, Spain, India, Poland, Canada and

Chicago. Only two studies recruited participants from the same country; Newham

et al. (2014) used women from hospital in Manchester in the UK whilst Polman et

al. (2007) recruited participants from gyms, hospital parental classes and local

doctors surgeries in Leeds, also in the UK. The fact that these studies recruited

participants from particular populations limits their generalizability.

The quality score of studies was affected by the method of allocation into

intervention or comparison groups. Several studies did not randomly allocate

participants into a group. Guszkowska et al. (2013) selected participants based on

their preference of treatment or control group and Satapriya et al. (2013) allowed

participants to move from the control group into the yoga (intervention) group,

thus cross-contaminating the groups and meaning participants were not blind to

details about the study. Polman et al. (2007) also did not randomly allocate

participants into groups. In one study, Newham et al. (2014), participants in the

control group participated in yoga classes whilst taking part in the study, affecting

any comparisons made with the yoga intervention group and reducing the study

quality.

Some studies, such as Lox and Treasure (2001), did not have a true control

group and thus their study can be deemed a quasi-experiment. Where true control

groups were used, some authors did not describe the nature of the control group in

34


any detail. Although Perales et al. (2015) thoroughly described the intervention

group, enabling this aspect of the study to be replicated, they provided no details

about the nature of the control group. Some studies did not provide sufficient

details about the nature of the intervention group. For example, Ji and Han (2010)

used an intervention based on “Qi exercise” but did not describe this in sufficient

detail to allow for replication.

The overall quality of the studies was also affected by the fact that often

the investigators and the participants were not blinded to condition. It is difficult

to blind researchers and participants to group allocation, where an exercise

component to the group is easily detectable.

Study quality was enhanced by the use of reliable and valid outcome

measures, which were relevant for the concepts investigated. Outcome measures

for mood included the EDPS, POMS, UWIST mood adjective checklist, Zung’s

self-rating depression scale (ZSDS), CES-D and HADS. Some studies took

additional measures such as the pregnancy experience questionnaire (PEQ) and

the pregnancy mild discomfort index.

Some studies, such as Kieffer et al. (2013) used a small number of

participants, limiting the power of the study and thus reducing its quality score.

Some studies used follow-up times which did not enable long-term benefits or

adverse effects of the intervention to be detected. Guszkowska et al. (2013)

looked at differences in emotional states immediately following a single exercise

class and did not collect any follow-up measures.

35


Results and Main Findings reported by Studies

Studies reporting correlations and associations. Nine of the eleven

studies in this category found a significant association between physical activity

and mood. These nine studies found that increased physical activity levels

correlated with decreased levels of depression. For example, Loprinzi et al.

(2012) found that women classified as not having depression symptoms spent

significantly more time exercising that those who reported depressive symptoms

and Demissie et al. (2011) found that active women had almost half the odds of

having high depressive symptoms compared with those who did not exercise.

The results of two studies did not reach significance. Takahasi et al. (2013)

found no association between physical inactivity and symptoms of depression and

Poudevigne and O’Connor (2005) found that changes in PA were not correlated

with changes in mood. For Poudevigne and O’Connor, this difference in findings

may be due to generally small changes in physical activity and mood preventing a

strong test of the hypothesized relationships. Additionally, the sample size did not

eliminate the possibilities for small sample bias in the results or Type II errors

associated with multiple contrasts. For Takahasi et al. (2013), in addition to no

association being found between physical inactivity and low mood, results

indicated the contradictory finding of an association between lower anxiety levels

and increased physical activity. The authors suggest it is possible that most

physical activity reported was related to domestic chores and work activities,

which in turn could be associated with increased anxiety levels.

Intervention studies. Ten of the studies found that participants in the

intervention group experienced significantly lower scores in measures of

36


depression when compared with participants in the control group. For example, Ji

and Han (2010) found that subjects in the Qi exercise group had lower levels of

depression compared with subjects in the control group. Only one study did not

show a significant difference between depression scores between intervention and

control conditions. Newham et al. (2014) found no significant difference on EPDS

scores between the yoga and ‘treatment as usual’ groups after the eight week

intervention.

Discussion

Findings from this review found preliminary evidence which suggests that

exercise may be effective in reducing low mood during pregnancy. Nine of the

eleven studies reporting correlations and associations found a significant

association between physical activity and mood. Ten of the eleven intervention

studies found a significant reduction in mood in the physical activity condition

relative to comparison groups. Findings from the intervention studies are in line

with those of previous reviews. Meta-analyses carried out by Dayley et al. (2015)

and Gong et al. (2015) revealed a significant reduction for depression scores for

exercise and yoga interventions relative to comparator groups. Overall findings of

this review from papers reporting correlations and associations also align with

findings from the low quality reviews conducted by Shivakumar et al (2011) and

Davis (2012). Both these reviews considered cohort and case controlled studies

exploring the relationship between physical activity and mood across the perinatal

period and found that most of the studies identified presented significant findings

that depression was reduced in pregnant women who engaged in physical activity.

37


This review has a number of limitations. Firstly, the journals identified are

limited by both the search terms and the databases used. The exclusion criteria, in

particular the fact that articles written before 2000 were not included, further

limits this review. This exclusion criterion was decided upon due to time

constraints. However, the review may be more thorough if articles published prior

to this date were included.

The current review is also limited by my own personal judgements about

which papers met the inclusion criteria and thus should be included. This bias

could be reduced with the use of other researchers carrying out the same searches

in order to improve inter-rater reliability. In common with systematic reviews in

general, there is also an overall publication bias towards significant findings.

Trials with negative results are less likely to be published and thus this review is

likely to be equally biased towards statistically significant findings.

Overall findings of this review highlight the poor quality of many of the

studies in this field. In assessing the quality of studies, there are a number of

themes which emerged across trials. Firstly, the majority of studies used a

Caucasian, well educated, financially stable, married, middle class population,

limiting generalizability to women of different ethnic and socioeconomic

backgrounds. Several of the studies also had self-selection bias, whereby women

decided from advertisements or by attending medical appointments to take part in

the research thus resulting in a sample who were interested in participating, which

may not be representative of the general population in that area.

Another theme which emerged across studies was the wide use of different

measurements to record low mood and physical activity levels, making it difficult

to compare findings across studies. Some measures used have low internal

38


consistency, other measures were used on the non-clinical population where they

had been previously validated in the clinical population. Physical activity levels

were measured using self-report questionnaires, which make data vulnerable to

over- or under-reporting (Prince et al., 2008).

Another theme which emerged is that measures were taken at different

time points over the course of pregnancy, making it difficult to make direct

comparisons across studies. As energy levels, tiredness and other physical

symptoms change over the course of pregnancy, this may affect scores on mood

and physical activity questionnaires.

Many of the studies used a small sample size and were thus underpowered,

increasing the risk of Type I error; that is falsely reporting statistically significant

effects. Analysis involving multiple testing, conducted by several studies, further

augments this problem.

In terms of the studies which looked at associations, significant findings

reveal a correlation between physical activity and mood rather than indicate the

direction of causation. Authors of these studies hypothesise that pregnant women

engaging in physical activity experience improved mood. However, it may be the

case that women with better mood are more motivated to engage in physical

activity. It is important for studies to address this.

Furthermore, there are many potential confounding factors, only some of

which studies measured and subsequently controlled for. Until further research is

carried out in this field, it is difficult to detect which variables affect mood and

activity during pregnancy, how they may interact and to what extent. One

important interacting factor is pre-pregnancy exercise levels. This is likely to

affect exercise levels during pregnancy and response to exercise based

39


interventions. Some studies tested and controlled for pre-pregnancy exercise

levels (Downs et al., 2008), others selected participants who had similar exercise

behaviour prior to the study (Gaston & Prapavessis, 2013). However, the majority

of the studies reported in this review did not account for this factor.

In terms of intervention studies, it is difficult to make comparisons across

studies, as different interventions were used in different studies. Exercise ranged

from yoga, to “Qi exercise”, to aerobic based exercise classes. It is difficult to

detect which particular component of the activity has an effect on mood. The

effect may be something related to the intervention that is not the physical effect

of physical activity such as a chance to get out of the house or peer support. As it

is not possible to blind participants to the condition, it is impossible to rule out

expectation effects. Several studies did not publish or make clear the specific

details of the intervention, making it very difficult to replicate studies.

Furthermore, the use and nature of control groups differed across trials, ranging

from treatment as usual to education sessions. Some studies did not use a control

group. Studies may also lack ecological validity, for example in the case of the

MoM intervention grant funds supported the transportation and on-site childcare

that made participation feasible for participants. Such supports may not be

available in many clinic or community settings under usual care (Kieffer er al.,

2013).

This review shows some preliminary evidence that physical activity

reduces low mood in the general pregnant population. However, a greater number

of high quality trials are required to add weight to this hypothesis. In particular:

Studies need to be sufficiently powered to detect an effect

Multiple testing needs to be minimized

40


More studies with participants of different socioeconomic

backgrounds and cultures are required

Consistent measures for mood and activity levels, which are

reliable and valid for use in this population, need to be utilised

Possible confounding factors need to be identified and

subsequently controlled for.

Interventions need to be well outlined and studies replicate

41


References

Butler, A.C., Chapman, J.E., Forman, E.M., & Beck A,T. (2006). The empirical

status of cognitive-behavioural therapy: a review of meta-analyses. Clinical

Psychology Review, 26, 17–31.

Da Costa, D., Rippen, N., Drista, M., & Ring, A. (2003). Self-reported leisure-

time physical activity during pregnancy and relationship to psychological well-

being. Journal of Psychosomatic Obstetrics & Gynaecology., 24(2), 111–9.

Daley, A.J., Foster, L., Long, G., Palmer, C., Robinson, O., Walmsley, H., &

Ward, R. (2015). The effectiveness of exercise for the prevention and treatment of

antenatal depression: systematic review with meta-analysis. International Journal

of Obstetrics & Gynaecology, 122(1), 1471-0528. doi: 10.1111/1471-0528.12909.

Davis, K., & Dimidjian, S. (2012). The relationship between physical activity and

mood across the perinatal period: A review of naturalistic and clinical research to

guide future investigation of physical activity–based interventions for perinatal

depression. Clinical Psychology: Science and Practice, 19(1), 27-48.

Demissie, Z., Siega-Riz, A., Evenson, K. R., Herring, A. H., Dole, N., & Gaynes,

B. N. (2011). Associations between physical activity and postpartum depressive

symptoms. Journal of Women's Health, 20(7), 1025-1034.

Downs, D. S., DiNallo, J. M., & Kirner, T. L. (2008). Determinants of pregnancy

and postpartum depression: Prospective influences of depressive symptoms, body

image satisfaction, and exercise behavior. Annals of Behavioral Medicine, 36(1),

54-63.

Field, T., Deeds, O., Diego, M., Hernandez-Reif, M., Gauler, A., Sullivan, S. et al.

(2009). Benefits of combining massage therapy with group interpersonal

42


psychotherapy in prenatally depressed women. Journal of Bodywork and

Movement Therapies, 13, 297–303.

Field, T. (2010). Prenatal depression and selective serotonin reuptake inhibitors.

International Journal of Neuroscience, 120, 163–7

Gaston, A., & Prapavessis, H. (2013). Tired, moody and pregnant? Exercise may

be the answer. Psychology & Health, 28(12), 1353-1369.

doi:10.1080/08870446.2013.809084

Gjestland, K., Bø, K., Owe, K.M., Eberhard-Gran, M. (2013). Do pregnant

women follow exercise guidelines? Prevalence data among 3482 women, and

prediction of low-back pain, pelvic girdle pain and depression. British Journal of

Sports Medicine, bjsports-2012

Glover, V. (1997). Maternal stress or anxiety in pregnancy and emotional

development of the child. British Journal of Psychiatry, 171, 105–6

Gong, H., Ni, C., Shen, X., Wu, T., & Jiang, C. (2015). Yoga for prenatal

depression: a systematic review and meta-analysis. BMC psychiatry, 15(1), 14.

Goodwin, A., Astbury, J., & McMeeken, J. (2000). Body image and psychological

well-being in pregnancy: a comparison of exercisers and non-exercisers. Aust NZ

J Obstet Gynaecol, 43(1), 41-45.

Guszkowska, M., Langwald, M., & Sempolska, K. (2013). Influence of a

relaxation session and an exercise class on emotional states in pregnant women.

Journal of Reproductive and Infant Psychology, 31(2), 121-133.

43


Guszkowska, M., Langwald, M., Dudziak, D., & Zaremba, A. (2013). Influence

of a single physical exercise class on mood states of pregnant women. Journal of

Psychosomatic Obstetrics & Gynecology, 34(2), 98-104.

Heron, J., O’Connor, T.G., Evans, J., Golding, J., & Glover, V. (2004). The

course of anxiety and depression through pregnancy and the postpartum in a

community sample. Journal of affective disorders, 80(1), 65–73.

Ji, E. S., & Han, H. (2010). The effects of Qi exercise on maternal fetal interaction

and maternal well-being during pregnancy. Journal of Obstetric, Gynecologic, &

Neonatal Nursing: Clinical Scholarship for the Care of Women, Childbearing

Families, & Newborns, 39(3), 310-318.

Kieffer, E. C., Caldwell, C. H., Welmerink, D. B., Welch, K. B., Sinco, B. R., &

Guzmán, J. R. (2013). Effect of the healthy MOMs lifestyle intervention on

reducing depressive symptoms among pregnant Latinas. American journal of

community psychology, 51(1-2), 76-89.

LaFontaine, T.P., DiLorenzo, T.M., Frensch, P.A., et al. (1992). Aerobic exercise

and mood. Sports Medicine, 13(3), 160–70.

Loprinzi, P. D., Fitzgerald, E. M., & Cardinal, B. J. (2012). Physical activity and

depression symptoms among pregnant women from the National Health and

Nutrition Examination Survey 2005–2006. Journal of Obstetric, Gynecologic, &

Neonatal Nursing: Clinical Scholarship for the Care of Women, Childbearing

Families, & Newborns, 41(2), 227-235.

44


Lox, C.L., & Treasure, D.C. (2000). Changes in Feeling States Following Aquatic

Exercise During Pregnancy. Journal of Applied Social Psychology, 30(3), 518–

527.

National Institute of Health and Care Excellence. (2006). Antenatal and Postnatal

Mental Health. Clinical Management and Service Guidance. CG45. London:

National Institute for Health and Care Excellence.

Newham, J. J., Wittkowski, A., Hurley, J., Aplin, J. D., & Westwood, M. (2014).

Effects of antenatal yoga on maternal anxiety and depression: a randomized

controlled trial. Depression and anxiety, 31(8), 631-640.

NICE (2012). Methods for the development of NICE public health guidance (third

edition). Retrieved from https://www.nice.org.uk/article/pmg4/chapter/Appendix-

J-Process-for-using-review-level-material-in-exceptional-circumstances

Orr, S.T., James, S.A., Garry, J., & Newton, E. (2006). Exercise participation

before and during pregnancy among low-income, urban, Black women: The

Baltimore Preterm Birth Study. Ethnicity & Disease, 16, 909– 913.

Perales, M., Refoyo, I., Coteron, J., Bacchi, M., & Barakat, R. (2015). Exercise

during pregnancy attenuates prenatal depression: a randomized controlled

trial. Evaluation & the health professions, 38(1), 59-72.

Polman, R., Kaiseler, M., & Borkoles, E. (2007). Effect of a single bout of

exercise on the mood of pregnant women. Journal of sports medicine and

physical fitness, 47(1), 103.

Poudevigne, M. S., & O'connor, P. J. (2005). Physical activity and mood during

pregnancy. Medicine & Science in Sports & Exercise, 37(8), 1374-1380.

45


Previti, G., Pawlby, S., Chowdhury, S., Aguglia, E., & Pariante, C. M. (2014).

Neurodevelopmental outcome for offspring of women treated for antenatal

depression: a systematic review. Archives of women's mental health, 17(6), 471-

483.

Prince, S. A., Adamo, K. B., Hamel, M. E., Hardt, J., Gorber, S. C., & Tremblay,

M. (2008). A comparison of direct versus self-report measures for assessing

physical activity in adults: a systematic review. International Journal of

Behavioral Nutrition and Physical Activity, 5(1), 56.

Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for

research in the general population. Applied psychological measurement, 1(3), 385-

401.

Robledo-Colonia, A. F., Sandoval-Restrepo, N., Mosquera-Valderrama, Y. F.,

Escobar-Hurtado, C., & Ramírez-Vélez, R. (2012). Aerobic exercise training

during pregnancy reduces depressive symptoms in nulliparous women: a

randomised trial. Journal of physiotherapy, 58(1), 9-15.

Royal College of Obstetricians and Gynaecologists. (2006). Exercise in

Pregnancy. Statement No. 4. London: RCOG.

Satyapriya, M., Nagarathna, R., Padmalatha, V., & Nagendra, H. R. (2013). Effect

of integrated yoga on anxiety, depression & well being in normal

pregnancy. Complementary therapies in clinical practice, 19(4), 230-236.

Shivakumar, G., Brandon, A. R., Snell, P. G., Santiago-Muñoz, P., Johnson, N. L.,

Trivedi, M. H., & Freeman, M. P. (2011). Antenatal depression: A rationale for

studying exercise. Depression and Anxiety, 28(3), 234-242.

46


Takahasi, E. H. M., Alves, M. T. S. S. D., Alves, G. S., Silva, A. A. M. D.,

Batista, R. F. L., Simões, V. M. F., Del-Ben, C.M. & Barbieri, M. A. (2013).

Mental health and physical inactivity during pregnancy: a cross-sectional study

nested in the BRISA cohort study. Cadernos de Saúde Pública, 29(8), 1583-1594.

Tendais, I., Figueiredo, B., Mota, J., & Conde, A. (2011). Physical activity,

health-related quality of life and depression during pregnancy. Cadernos de saude

publica, 27(2), 219-228.

Watts, J. N., Miller, Y. D., & Marshall, A. L. (2013). Depressive symptoms

during pregnancy: Exploring the role of sitting. Mental Health and Physical

Activity, 6(1), 36-42.

Wipfli, B. M., Rethorst, C. D., & Landers, D. M. (2008). The anxiolytic effects of

exercise: a meta-analysis of randomized trials and dose–response

analysis. Journal of Sport and Exercise Psychology, 30(4), 392-410.

47


Appendix 1: Checklist for intervention/correlation & association studies

Study identification: (Include full citation details)

Study design:Refer to the glossary of study designs (appendix D) and the algorithm for classifying experimental and observational study designs (appendix E) to best describe the paper's underpinning study design

Guidance topic:Assessed by:Section 1: Population1.1 Is the source population or source area well described?

Was the country (e.g. developed or non-developed, type of healthcare system), setting (primary schools, community centres etc.), location (urban, rural), population demographics etc. adequately described?

+++−NRNA

Comments:

1.2 Is the eligible population or area representative of the source population or area?

1.3 Was the recruitment of individuals, clusters or areas well defined (e.g. advertisement, birth register)?

Was the eligible population representative of the source? Were important groups under-represented?

+++−NRNA

Comments:

1.4 Do the selected participants or areas represent the eligible population or area?

Was the method of selection of participants from the eligible population well described?What % of selected individuals or clusters agreed to participate? Were there any sources of bias?Were the inclusion or exclusion criteria explicit and appropriate?

+++−NRNA

Comments:

Section 2: Method of allocation to intervention (or comparison)2.1 Allocation to intervention (or comparison). How was selection bias minimised? Was allocation to exposure and comparison randomised? Was it truly random ++ or pseudo-randomised + (e.g. consecutive admissions)?If not randomised, was significant confounding likely (−) or not (+)? If a cross-over, was order of intervention randomised?

+++−NRNA

Comments:

2.2 Were interventions (and comparisons) well described and appropriate? Were interventions and comparisons described in sufficient detail (i.e. enough for study to be replicated)? Was comparisons appropriate (e.g. usual practice rather than no intervention)?

+++−NRNA

Comments:

2.3 Was the allocation concealed? Could the person(s) determining allocation of participants or clusters to intervention or comparison groups have influenced the allocation?Adequate allocation concealment (++) would include centralised allocation or computerised allocation systems.

+++−NRNA

Comments:

48


2.4 Were participants or investigators blind to exposure and comparison? Were participants and investigators – those delivering or assessing the intervention kept blind to intervention allocation? (Triple or double blinding score ++)If lack of blinding is likely to cause important bias, score −.

+++−NRNA

Comments:

2.5 Was the exposure to the intervention and comparison adequate?Is reduced exposure to intervention or control related to the intervention(e.g. adverse effects leading to reduced compliance) or fidelity of implementation (e.g. reduced adherence to protocol)?Was lack of exposure sufficient to cause important bias?

+++−NRNA

Comments:

2.6 Was contamination acceptably low? Did any in the comparison group receive the intervention or vice versa?If so, was it sufficient to cause important bias?If a cross-over trial, was there a sufficient wash-out period between interventions?

+++−NRNA

Comments:

2.7 Were other interventions similar in both groups?Did either group receive additional interventions or have services provided in a different manner?Were the groups treated equally by researchers or other professionals?Was this sufficient to cause important bias?

+++−NRNA

Comments:

2.8 Were all participants accounted for at study conclusion?Were those lost-to-follow-up (i.e. dropped or lost pre-,during or postintervention) acceptably low (i.e. typically <20%)?Did the proportion dropped differ by group? For example, were drop-outs related to the adverse effects of the intervention?

+++−NRNA

Comments:

2.9 Did the setting reflect usual UK practice?Did the setting in which the intervention or comparison was delivered differ significantly from usual practice in the UK? For example, did participants receive intervention (or comparison) condition in a hospital rather than a community-based setting?

+++−NRNA

Comments:

2.10 Did the intervention or control comparison reflect usual UK practice?Did the intervention or comparison differ significantly from usual practice in the UK? For example, did participants receive intervention (or comparison) delivered by specialists rather than GPs? Were participants monitored more closely?

+++−NRNA

Comments:

Section 3: Outcomes3.1 Were outcome measures reliable?Were outcome measures subjective or objective (e.g. biochemically validated nicotine levels ++ vs self-reported smoking −)?How reliable were outcome measures (e.g. inter- or intra-rater reliability scores)?Was there any indication that measures had been validated (e.g. validated against a gold standard measure or assessed for content validity)?

+++−NRNA

Comments:

3.2 Were all outcome measurements complete?Were all or most study participants who met the defined study outcome definitions likely to have been identified?

+++−NRNA

Comments:

3.3 Were all important outcomes assessed? ++ Comments:

49


Were all important benefits and harms assessed?Was it possible to determine the overall balance of benefits and harms of the intervention versus comparison?

+−NRNA

3.4 Were outcomes relevant?Where surrogate outcome measures were used, did they measure what they set out to measure? (e.g. a study to assess impact on physical activity assesses gym membership – a potentially objective outcome measure – but is it a reliable predictor of physical activity?)

+++−NRNA

Comments:

3.5 Were there similar follow-up times in exposure and comparison groups?If groups are followed for different lengths of time, then more events are likely to occur in the group followed-up for longer distorting the comparison.Analyses can be adjusted to allow for differences in length of follow-up(e.g. using person-years)

+++−NRNA

Comments:

3.6 Was follow-up time meaningful?Was follow-up long enough to assess long-term benefits or harms?Was it too long, e.g. participants lost to follow-up?

+++−NRNA

Comments:

Section 4: Analyses4.1 Were exposure and comparison groups similar at baseline? If not, were these adjusted?Were there any differences between groups in important confounders at baseline?If so, were these adjusted for in the analyses (e.g. multivariate analyses or stratification).Were there likely to be any residual differences of relevance?

+++−NRNA

Comments:

4.2 Was intention to treat (ITT) analysis conducted?Were all participants (including those that dropped out or did not fully complete the intervention course) analysed in the groups (i.e. intervention or comparison) to which they were originally allocated?

+++−NRNA

Comments:

4.3 Was the study sufficiently powered to detect an intervention effect (if one exists)?A power of 0.8 (that is, it is likely to see an effect of a given size if one exists, 80% of the time) is the conventionally accepted standard.Is a power calculation presented? If not, what is the expected effect size?Is the sample size adequate?

+++−NRNA

Comments:

4.4 Were the estimates of effect size given or calculable?Were effect estimates (e.g. relative risks, absolute risks) given or possible to calculate?

+++−NRNA

Comments:

4.5 Were the analytical methods appropriate?Were important differences in follow-up time and likely confounders adjusted for?If a cluster design, were analyses of sample size (and power), and effect size performed on clusters (and not individuals)?

+++−NRNA

Comments:

50


Were subgroup analyses pre-specified?4.6 Was the precision of intervention effects given or calculable?Were they meaningful?Were confidence intervals or p values for effect estimates given or possible to calculate?Were CI's wide or were they sufficiently precise to aid decision-making? If precision is lacking, is this because the study is under-powered?

+++−NRNA

Comments:

Section 5: Summary5.1 Are the study results internally valid (i.e. unbiased)?How well did the study minimise sources of bias (i.e. adjusting for potential confounders)?Were there significant flaws in the study design?

+++−NRNA

Comments:

5.2 Are the findings generalisable to the source population (i.e. externally valid)?Are there sufficient details given about the study to determine if the findings are generalisable to the source population? Consider: participants, interventions and comparisons, outcomes, resource and policy implications.

+++−NRNA

Comments:

51


Research Part 2 – Empirical Paper with Appendices


By

Emma Burgess

Submitted in partial fulfillment of the degree of Doctor of Psychology (Clinical Psychology)

School of PsychologyFaculty of Health and Medical Sciences

University of Surrey 2017

© Emma Clare Mary Burgess 2017

52


Abstract

Objective

The study aims to explore the relationship between physical activity (PA) during

pregnancy and mood. Pregnant women are vulnerable to low mood; pregnancy

can be seen as a “teachable moment” when changes in attitude are possible.

Establishing the value of PA in pregnancy is important in optimising mood and

well-being.

Design

The study is a longitudinal follow-up survey using online questionnaires.

Participants completed questionnaires measuring mood and physical activity at

second trimester (T2) and third trimester (T3). At T2 participants were also asked

about their pre-pregnancy (T1) physical activity levels. Measures at T3 are

compared with T2 and T1.

Participants

Participants were 76 women aged between 25 and 42 who were in their second

trimester of pregnancy at the point of completing the first questionnaire.

Participants were recruited through advertising on social media and posters.

Results

Three groups defined by changes in PA were created using a tertile split.

ANOVA’s showed that mood and physical health were significantly better in the

group where PA increased from T1 to T3 compared with the group where PA

decreased. All other ANOVA’s comparing changes in PA and mood, physical

health and mental health scores across other time points in the study were not

significant.

Conclusions

53


The findings suggest that an increase in physical activity levels over the course of

pregnancy improves mood and physical health.

Introduction

Physical activity is defined as any bodily movement produced by skeletal

muscles that results in energy expenditure beyond resting expenditure. Exercise is

a subset of physical activity that is planned, structured, repetitive, and purposeful

in the sense that improvement or maintenance of physical fitness is the objective

(Thompson et al, 2016). Regular physical activity results in cardiovascular

adaptations that increase exercise capacity, endurance and skeletal muscle

strength. Physical activity has been shown to have many benefits for the health of

women including a reduction in weight, body mass index, blood pressure and an

increase in serum high-density lipoprotein (HDL) cholesterol (Yeung, 1996), thus

improving their cardiovascular risk profile. There is also a wide body of evidence

indicating that women who exercise have a reduced risk of developing breast

cancer, colon cancer and osteoporosis (Petruzzello, Landersm Hatfield Kubitz &

Salazar, 1991). In addition to physical and medical benefits, being physically

active has also been shown to improve wellbeing and reduce depressive

symptoms (Teychenne, Ball & Salmon, 2008).

Pregnancy is characterized by major changes in physical, social, and

emotional health (Armstrong & Edwards, 2004) and can make women particularly

vulnerable to the onset or return of depressive symptoms (National Institute of

Mental Health [NIMH] 2008; Bennett et al. 2004). Clinical depression is

experienced when low mood persists for two weeks and has an impact on

functioning (National Institute of Mental Health, 2015).

54


Fifteen percent of women experience their initial onset of depression

during pregnancy and 18.4% of women experience depression during pregnancy

(Gaynes et al., 2005). Pregnant women who have depression are more likely to

experience postpartum depression (Field, 2011), more likely to engage in risky

health behaviours, less likely to follow medical recommendations and have an

increased likelihood of having negative birth outcomes such as premature delivery

and low birth weight infants (Grote et al., 2010). There is also evidence that the

children of mothers who are depressed during pregnancy have higher cortisol

levels at birth and adolescence, impaired cognitive skills and a greater risk of

developmental and mental disorders (Brennan et al., 2008; LeWinn et al., 2009).

The etiology of depression during pregnancy is thought to be a complex

interplay of social, psychological and biological factors (Goldberg, 2006). To

date, the majority of research into treatment options for depression during

pregnancy has focused on psychological therapy and pharmacological treatments

(Dennis, Ross & Grigoriadis, 2007). Although medication has been shown to be

an effective treatment (Freeman, 2007), it has associated problems such as an

increased risk of miscarriage, low birth weight and negative neurobehavioural

outcomes (Dennis et al., 2007). For these reasons, many women do not wish to

take medication during pregnancy (Austin, 2003). Therapeutic approaches such as

counseling require skilled professionals, resources and time, and are not available

in some settings (Dennis et al., 2007). Due to the difficulties in pharmacological

and therapeutic interventions for treating depression during pregnancy, it is useful

to explore alternatives which are more cost effective, safer and more acceptable to

pregnant women. In particular, modifying lifestyle behaviours may be particularly

feasible and helpful, if they are shown to be effective (Dennis et al, 2007).

55


Research in non-pregnant populations indicates that being physically

active improves wellbeing and reduces depressive symptoms (Teychenne et al.

2008). Physical activity has been shown to be as effective as both medication and

therapy as a treatment for depression (Dunn, Trivedi, Kampert, Clark &

Chambliss, 2005; Craft & Perna 2004; Martinsen 2008).

Participating in moderate intensity physical activity whilst pregnant is

considered to have several health benefits for mother and foetus (Pivarnik et al.

2006) and is considered to be of low risk. Both the National Institute for Health

and Care Excellence (NICE) and Royal College of Obstetricians and

Gynaecologists (RCOG) recommend 30 minutes of moderate physical activity, at

least four times per week, for women with uncomplicated pregnancies, in all

trimesters (Atkinson et al., 2014). Despite these recommendations, a recent survey

of UK women who were currently pregnant or had been pregnant in the last 3

years demonstrated that many are unaware of the recommended levels of physical

activity in pregnancy and may fail to meet recommendations through exercise.

Despite no evidence of risk, women are concerned that exercise contributes to

miscarriage. Tiredness, aches and pains and morning sickness were cited as

common reasons to avoid exercise (Atkinson, Parsona & Jackson, 2014). There is

reason to hypothesize that women suffering from depression will have an

increased tendency to avoid exercise or meet the government guidelines, with

tiredness (American Psychological Society, 2015) and aches and pains

(Demyttenaere et al., 2006) also common symptoms of low mood.

To date, there have been many studies of the general population examining

the effect of physical activity on mood, suggesting a positive correlation between

the two; broadly speaking, exercise improves mood. In reviewing the literature on

56


exercise during pregnancy and mood in the general pregnant population,

preliminary evidence suggests a similar correlation can be found during

pregnancy. However, finding are mixed; in some studies, participation in physical

activity is associated with lower levels of depressive symptoms (Pottinger et al.

2009; Orr et al. 2006; Haas et al. 2004, Da Costa et al. 2003; Koniak-Griffin

1994) whilst other studies have found no associations between total or

recreational physical activity and depressive symptoms (Goodwin et al. 2000;

Poudevigne and O'Connor 2005; Downs et al. 2008).

In assessing the quality of studies, there are a number of themes which

emerge across trials. Firstly, studies use different populations, limiting their

generalisability. The majority of studies use a Caucasian, well educated,

financially stable, married, middle class population, limiting generalisability to

women of different ethnic and socioeconomic backgrounds.

Another theme present across studies is the wide use of different

measurements to record low mood and physical activity levels, making it difficult

to compare findings across studies. Several studies use the Center for

Epidemiological Studies Depression Scale (CES-D) or the Structured Clinical

Interview for DSM-IV (SCID) to assess pregnant women’s depression. However,

this may not the best choice due to misinterpretation of somatic symptoms of

pregnancy for certain items (e.g., tiredness, lack of energy). Some studies used a

higher cut off point for the presence of symptoms of depression in order to

address this problem and minimize bias (Radloff, 1977). Some studies used the

Edinburgh Postnatal Depression Scale (EPDS), which may be a better choice for

use in this population. Some studies utilised the Profile of Mood States (POMS),

which has been criticised because the test was initially validated for use in clinical

57


populations and includes only one positive mood dimension (see LaFontaine et

al., 1992). In the light of these and other criticisms, future reliance on the POMS

as the primary measure of mood state in exercise research must be questioned.

Studies use a wide range of measures to record physical activity, which

can make comparisons across studies difficult, though measures are more

comparable than those for mood. Some studies have made use of movement

sensors, such as accelerometers. While accelerometers provide objective

measurements, they have some limitations, such as not informing on body posture

and missing upper body movement (Lee & Shiroma, 2014). The majority of

studies use self-report measures of physical activity (Prince et al., 2008) which are

validated, and as such the results are comparable to other studies using the same

self-report measures (Watts et al. 2013). Self-reported physical activity has in

some studies been found to correlate well with objective measures of physical

fitness (Da Costa et al., 2003) and some measures, such as the Global Physical

Activity Questionnaire (GPAQ) have been validated against accelerometers

(Tendais et al., 2011).

Another theme which emerges is that measures are taken at different time

points over the course of pregnancy, making it difficult to make direct

comparisons across studies. As energy levels, tiredness and other physical

symptoms change over the course of pregnancy, this may affect scores on mood

and physical activity questionnaires.

Many of the selected studies use a small sample size and are thus

underpowered, increasing the risk of Type II error; that is falsely reporting

statistically significant effects. Analysis involving multiple testing, conducted by

several studies, further augments this problem.

58


In terms of studies which look at associations, significant findings reveal a

correlation between physical activity and mood rather than causation. There are

many other potential confounding factors, only some of which studies measure

and subsequently control for. Until further research is carried out in this field, it is

difficult to detect which variables affect mood and activity during pregnancy, how

they may interact and to what extent. One important interacting factor is pre-

pregnancy exercise levels. This is likely to affect exercise levels during pregnancy

and response to exercise based interventions. Some studies have tested and

controlled for pre-pregnancy exercise levels (Downs et al., 2008), others have

selected participants who had similar exercise behaviour prior to the study

(Gaston & Prapavessis, 2013).

In terms of intervention studies, it is difficult to make comparisons across

studies, as different interventions are used by different studies. Exercise ranges

from yoga, to “Qi exercise”, to aerobic based exercise classes. It is difficult to

detect which particular component of the activity has an effect on mood. The

effect may be something about the activity that is not the activity itself, such as

relaxation, socializing or getting away from daily problems. As it is not possible

to blind participants to the condition they are in in trials of PA, it is impossible to

rule out expectation effects. Several studies have failed to publish or make clear

the specific details of the intervention, making it very difficult to replicate studies.

Furthermore, the use and nature of control groups differ across trials, ranging

from treatment as usual to education sessions. Some studies do not use a control

group. Studies may also lack ecological validity, for example in the case of one

particular intervention study, grant funds supported the transportation and on-site

childcare that made participation feasible for participants. Such support may not

59


be available in many clinic or community settings under usual care (Kieffer et al.,

2013).

There is also an overall publication bias towards significant findings. In

terms of review papers, trials with negative results are less likely to be published

and more likely to be excluded from systematic review, which biases the literature

towards positive findings (Gong et al., 2015). Similarly, correlational and

association studies, and intervention studies, suffer from publication bias.

In summary, there is some preliminary evidence that physical activity

reduces low mood in the general pregnant population. However, a greater number

of high quality studies are required to explore this further. This study aims to

address methodological gaps in the following ways:

By achieving sufficient power to detect an effect

By minimizing multiple testing

By utilising consistent measures for mood and activity levels,

which are reliable and valid for use in this population.

By identifying and controlling for possible confounding factors.

By taking measures for physical activity and mood at different time

points over the course of pregnancy (pre-pregnancy, at first

trimester and at second trimester).

Objectives

This study aims to explore the relationship between physical activity and

depression in the general pregnant population. It aims to do this by measuring low

mood, physical activity, and other potential confounding factors such as social

60


support, general health, age, level of education and marital status in pregnant

women across two different time points, their second trimester and their third

trimester. At the first time point, pregnant women are also asked about their pre-

pregnancy physical activity levels.

Research Questions

Is physical activity participation during pregnancy related to mood?

Do changes in physical activity levels before and during pregnancy relate

to changes in mood?

Hypotheses

1) A change in PA levels over the course of pregnancy will be significantly

associated with a change in mood.

2) Levels of PA are expected to decrease over the course of pregnancy. As

PA decreases, it is expected that levels of mood will decrease.

Definition of Terms

Physical Activity. This study uses the term physical activity as defined by

Caspersen, Powell & Christenson (1985). It refers to any activity which expends

energy, including planned exercise, leisure activities and household and work

tasks.

Depression. Current studies measure low mood or depression in various

ways, often using the two terms interchangeably. This study uses “depression” to

mean low mood. The Patient Health Questionnaire is used as a measure, as its 9

61


questions follow the criteria for depression as outlined by the DSM-IV (Kroenke,

Spitzer & Williams, 2001).

Contribution to clinical theory and practice

In establishing the relationship between depression and activity in the

general pregnant population, insight will be gained as to whether physical activity

during pregnancy improves mood. This may indicate that physical activity can be

a protective factor against antenatal depression. It is important to establish the link

between activity and depression in this population, as they are at high risk of low

mood, both during and post pregnancy. Pregnancy can be seen as a ‘teachable

moment’ (Phelan, 2010) or a ‘window of opportunity’ when women are a little

more able to consider a change in lifestyle as they want to do what is best for

baby, so changes in attitude at this time might be possible. Findings may also have

implications for the clinically depressed pregnant population. An exercise

intervention may prove an effective alternative to therapeutic or pharmacological

interventions.

This could also be relevant for clinical psychologists in their individual

work with pregnant women; for example when working with pregnant women

experiencing low mood, clinical psychologists should be aware that they may

benefit from increasing their level of physical activity.

62


Methods

Design

The study is a longitudinal follow-up survey using online questionnaires

presented using the Qualtrics software (Qualtrics, 2017). Within and between

participant measures were collected at two data collection points. At the first data

collection point, information was obtained about activity levels before pregnancy.

The first data collection point was at the second trimester of pregnancy. The

retrospective data about pre-pregnancy activity levels is considered as time point 1

(T1). The data collected about activity levels during the second trimester is

classified as time point 2 (T2). The second data collection point was at the third

trimester and is classified as time point 3 (T3). The time points are summarised

below:

T1: Participants completed a measure at data collection point 1 which asked

retrospectively about their pre-pregnancy physical activity levels. This is

classified as time point 1 (T1).

T2: Participants completed measures at data collection point 1 during their second

trimester (pregnancy week 13-28). This is classified as time point 2 (T2).

T3: Participants completed measures at data collection point 2 during their third

trimester (pregnancy week 29-40). This is classified as time point 3 (T3).

Measures at T3 are compared with T2 and T1 within and between individuals.

Participants

63


Description of Sample. Participants were recruited through posters

distributed at a University campus and doctors surgeries in South London and

South East England, social media, advertising on Mumsnet and through National

Childbirth Trust (NCT) groups. Participants self-selected and completed an online

survey.

448 participants accessed the link to the online survey. An initial screening

question ensured only participants who were currently in their second trimester of

pregnancy were able to proceed with the remaining questionnaires. Those

participants who were not in their second trimester were taken to a study

information page. Of the 448 participants who accessed the link, 201 were in their

second trimester and therefore completed the first part of the survey. Participants

were contacted by email during their third trimester and invited to complete the

second part of the survey. Of the 201 participants who were contacted, 135

completed the second part of the survey.

Power Calculation. Gjestland et al (2013) carried out a study which

addressed a similar topic to the current study. This study was used to inform the

desired sample size of the current study. The authors found that women exercising

1-2 times per week were less likely to report depression. The adjusted odds ratio

was 0.66. This corresponds to a value of -0.2291 for Cohen’s d and an r value of

0.1138 (Borenstein, Hedges, Higgins & Rothstein, 2009). Assuming a desired

power of 0.8 to detect an effect size of this value and a 1-tailed test with alpha

0.05 using logistic regression an a priori calculation using G*Power 3.1.7. (Faul,

Erdfelder, Lang, & Buchner, 2007) suggested a sample of 234 is required.

Inclusion/Exclusion Criteria

Inclusion Exclusion

64


16-20 weeks gestation at consenting Medical conditions which could interfere with participation

Aged 18-49 years Illicit drug useAble to speak and read EnglishLive foetus at routine ultrasound scanSingleton pregnancy

Measures

Participants completed two online questionnaires using the Qualtrics

software, the first during their second trimester (T2) and the second, during their

third trimester (T3).

Questionnaire 1 (Completed at T2). The first questionnaire took

approximately 20-25 minutes to complete. Participants were asked their age,

marital status, ethnicity, employment history, history of mental health difficulties,

religion, level of education, whether they have had previous pregnancies, and

whether they have previously engaged in physical activity. Participants then

answered the following questionnaires:

To measure depression:

The Patient Health Questionnaire (PHQ-9) (Kroenke, Spitzer & Williams, 2001).

This is a 9-item self-reported questionnaire designed to evaluate the presence and

severity of depressive symptoms during the prior 2 weeks. Each of the 9 items

asks for each of the DSM-IV diagnostic criteria. Scores can range from 0 (absence

of depressive symptoms) to 27 (severe depressive symptoms). Scores are

calculated using a Likert Scale from 0 (not at all) to 3 (nearly every day). As a

diagnostic measure, major depression is diagnosed if 5 or more of the 9 depressive

symptom criteria have been present at least “more than half the days” (a score of

2) in the past 2 weeks, and one of the symptoms is depressed mood or anhedonia.

65


The PHQ-9 has been shown to be a reliable and valid questionnaire; test-retest

reliability (0.84), internal reliability (Cronbach’s α = 0.89).

To measure exercise levels during T2:

The Pregnancy Physical Activity Questionnaire (PAQ) (Chasan-Taber, Schmidt,

Roberts et al., 2004) This is a 36 item self-administered questionnaire to measure

physical activity levels. The questionnaire asks participants to select the category

that best approximates the amount of time spent in 32 activities including

household/caregiving, occupational, sports/exercise, and inactivity during the

current trimester. The PAQ also has an open-ended section which allows the

respondent to add activities not already listed. The participant responds using a 6-

item Lickert Scale ranging from “none” to “3/6 hours per day/week” depending

upon the nature of the activity asked about. The duration of time spent in each

activity is multiplied by its intensity to arrive at a measure of average weekly

energy expenditure (MET-h·week-1) attributable to each activity. The sum total

of these scores gives a measure of total weekly activity. Higher scores indicate

higher levels of PA. Intraclass correlation coefficients used to measure

reproducibility of the PPAQ were 0.78 for total activity, 0.82 for moderate

activity, 0.81 for vigorous activity, and ranged from 0.83 for sports/exercise to

0.93 for occupational activity. Spearman correlations between the PPAQ and three

published cut points used to classify actigraph data ranged from 0.08 to 0.43 for

total activity, 0.25 to 0.34 for vigorous activity, 0.20 to 0.49 for moderate activity,

and 0.08 to 0.22 for light-intensity activity (Chasan-Taber et al., 2004).

To measure exercise levels before pregnancy:

66


Pre-pregnancy Physical Activity Questionnaire (PPAQ); an adjusted version of

the PAQ to measure activity before pregnancy. The wording was adjusted to ask

about “the 12 months before pregnancy”. The questionnaire is scored as above

and has the same psychometric properties.

To measure other factors:

Multidimensional Scale of Perceived Social Support (MPSS) (Zimet, Dahlem,

Zimet & Farley, 1988). This measure assesses an individual’s perceptions of

support from 3 different groups; friends, family and significant others. The scale

is comprised of a total of 12 items, with 4 items for each subscale. Items are rated

on a 7-point Likert-scale ranging from 1 (very strongly disagree) to 7 (very

strongly agree). Responses to items within each of the subscales are summed to

derive a total subscale score. A high observed total mean score on any specific

subscale indicates high levels of perceived social support from that source. Scores

on all 12 items are summed to obtain a composite MSPSS scale score (i.e., global

perceived social support). Scores range from 12 to 84 with higher scores

indicating increased global perceived social support. This scale has been shown

by other studies to have good reliability and validity (Cronbach’s α, 0.88; test-

retest reliability, 0.85.)

A measure for social support was included as research has shown that lack of

social support constitutes an important risk factor for maternal well-being

(Elsenbruch et al., 2006). It is likely that social support has an impact on mood

and thus may contribute to the proposed relationship between mood and PA.

To measure health status:

67


12-Item Short-Form Health Survey (SF-12) (Jenkinson & Layte, 1997). This is a

shortened version of the 36-itemed questionnaire (SF-36) It is a generic measure

for health status, assessing physical and psychological aspects of quality of life.

The SF-12 is comprised of a physical (PCS-12) and mental (MCS-12) component

summary scales. In this study, mental health was measured using the Mental

Composite Score (MCS) and physical health using the Physical Composite Score

(PCS). The PCS and MCS are scored using norm-based methods. Physical and

mental regression weights and a constant for both measures come from the

general U.S. population. The scoring procedure is detailed in Ware, Kosinski &

Keller (1996). Higher scores indicate better health. Test-retest reliability is 0.88

for PCS and 0.78 for MCS; Cronbach’s α 0.67 for PCS and 0.97 for MCS (Ware

et al., 1996). A measure for health status was included, as research has shown that

elevated depressive symptoms during pregnancy are associated with diminished

health (Orr, Blazer, James & Reiter, 2007). Poor health has been cited as a barrier

to women’s engagement in physical activity (Trost, Owen, Bauman, Sallis &

Brown, 2002). It may be that health status contributes to the proposed relationship

between mood and PA.

Questionnaire 2 (completed at T3). The second questionnaire took

approximately 10-15 minutes to complete and included the PHQ-9, MPSS, SF-12

and PAQ.

(For copies of questionnaires, see Appendix 3).

Procedure

Participants self-selected to participate in the study from advertising

through social media and posters. A prize of £50 of Amazon vouchers for one

68


randomly selected participant was offered as an incentive for completing both

parts of the survey.

Participants consented into the study and completed the first questionnaire

during their second trimester (T2). During their third trimester (T3), participants

were contacted by email and invited to complete the second part of the

questionnaire. Participants questionnaires completed at T2 were linked with their

questionnaires completed at T3 by matching their email addresses.

Ethical Considerations

Consent. Potential participants were provided with an online information

sheet presented on Qualtrics giving details relating to confidentiality (McLeod,

2015), the purpose of the research, possible discomforts, the research procedure

and possible benefits of taking part.

Participants were provided with contact details for the researchers should

they wish to ask further questions and, if they wished to proceed, were asked to

click to continue with the survey, thus giving their consent to take part.

Data Protection. All personal data relating to participants were handled

in accordance with the Data Protection Act (1998).

Results

Data Cleaning

Data were screened for outliers. Of the 135 participants who had

completed the questionnaire at both time points (T2 and T3), 59 participants had

incomplete data. The data was primarily missing from the PAQ and PPAQ across

all 3 time points.

69


Little’s MCAR test was conducted for the PAQ and PPAQ data

(completed at T1, T2 and T3) and was not found to be significant (X² = 4.716 (df =

4785; p=1.000), indicating that the missing data are missing at random.

It was decided to remove all incomplete data from the analysis. As more

than 20% of the data were missing, expectation maximization and multiple

imputation were not used (Lee & Huber, 2011). It was also decided not to use

pairwise deletion because the total score for these questionnaires was used for the

purposes of analysis. As such, even if one of the 36 items was missing from the

questionnaire, this would impact on the total score for that participant.

Furthermore, items 30 and 31 of the PAQ and PPAQ require the participant to

name an activity they do for fun or pleasure. In calculating the total score,

activities are given an intensity rating using compendium based MET values.

Given the fact that participants could name any activity, it seems theoretically

unsound to predict these activities, and assign intensity values to them. Since 76

participants had complete scores for their PAQ and PPAQ data, these participants

alone were used for the analysis.

116 of the 135 participants had completed the first 25 questions of the 36-

itemed PAQ and PPAQ. A secondary analysis was conducted on this dataset and a

similar pattern of findings emerged (see Appendix 2 for output from the

secondary analysis).

Findings are presented for the analysis using the full PAQ and PPAQ

scores, as these represent a participants’ profile of PA more fully.

Sample Characteristics

70


Participants were 76 pregnant women who completed the online survey

during their second and third trimester. The demographic data from the sample

and the missing data are presented in tables 1 and 2.

Chi-squared tests of independence were conducted to determine whether

characteristics from the sample and missing data come from the same population

(Table 3). Marital status, employment and education were significant whilst

religion was approaching significance. Previous pregnancy, previous physical

activity, ethnicity and previous mental health difficulties were not found to be

significant. However, these findings should be approached with caution, as there

were several groups with a size of less than 5 which had to be collapsed in order

to perform the tests.

Overall, it seems that the demographic characteristics for the sample and

missing data are broadly similar.

71


Table 1: Demographics data for full dataset (N=76)

Age Range

Previous Pregnancy Previous PA Marital Status Ethnic Group Employment Previous Mental Health History

Education Religion

25-42 Yes 31 (40.79%)

Yes 22 (28.95%)

Married 64 (84.21%)

White British 70 (92.11%)

Employed 66 (86.84%)

Yes 19 (25%) A-level 5 (6.58%)

Christian 36 (47.37%)

No 44 (57.89%)

No 9 (11.84%)

With partner

12 (15.79%)

Any other white background

4 (5.26%)

Homemaker 4 (5.26%)

No 56 (73.68%)

Bachelor’s Degree

42 (55.29%)

No religion

37 (48.68%)

Pref not to say

1 (1.32%) N/A 45 (59.21%)

Any other mixed/multiple ethnic background

1 (1.32%)

Any other employment

6 (7.89%)

Pref not to say

1 (1.32%)

Doctoral Degree

6 (7.89%)

Buddhist 1 (1.32%)

Any other ethnic group

1 (1.32%)

GCSE or Equivalent

2 (2.63%)

Jewish 1 (1.32%)

Master’s Degree

21 (27.63%)

Pref not to say

1 (1.32%)

Table 2. Demographic data for missing data (N=59)

Age Range

Previous Pregnancy Previous PA Marital Status Ethnic Group Employment Previous Mental Health History

Education Religion

20-43 Yes 31 (53.45%)

Yes 18(31.03%)

Married 36 (62.07%)

White British 43 (74.14%)

Employed 37 (63.79%)

Yes 12 (20.69%)

A-level 12 (20.69%)

Christian 25 (43.10%)

No 22 (37.93%)

No 13(22.41%)

With partner

15 (25.86%)

Any other white background

8 (13.79%)

Homemaker 10 (17.24%)

No 41 (70.69%)

Bachelor’s Degree

23 (39.66%)

No religion

25 (43.10%)

Pref not to say

3 (5.17%) N/A 27(46.55%)

Single 1 (1.72%)

Any other mixed/multiple ethnic background

1 (1.72%)

Any other employment

6 (10.34%)

N/A 5 (8.62%)

Doctoral Degree

1 (1.72%) Jewish 1 (1.72%)

N/A 2 (3.45%) Any other marital status

1 (1.72%)

N/A 6 (10.34%)

N/A 5 (8.62%)

GCSE or Equivalent

5 (8.62%) Pref not to say

2 (3.45%)

N/A 5 (8.72%)

Master’s Degree

12 (20.69%)

N/A 5 (8.62%)

N/A 5 (8.62%)

72


73


Table 3Summary of Chi-Square tests of independence

Variables df Pearson p Chi-SquarePrevious pregnancy

Previous Physical Activity

Marital Status

Ethnicity

Employment

Previous Mental Health

Education

Religion

1

2

1

1

2

1

1

1

3.660

3.268

3.383

2.644

6.854

0.123

10.780

0.000

0.56

0.195

0.066*

0.104

0.032*

0.726

0.001*

0.082**

p<*p <0.05 **Approaching significance

74


Table 4Pearson Correlation Matrix

PHQ9TOTALT2

PHQ9TOTALT3

SF12T2PCSTOTAL

SF12T2MCSTOTAL

SF12T3PCSTOTAL

SF12T3MCSTOTAL

MPSSTOTALMEANT2

MPSSTOTALMEANT3

PAQT2ALL36

PPALL36

PAQT3ALL36

PHQ9TOTALT2 .568** -.453** -0.599** -.193 -.202 -.381** -.424** .018 .280* .040

PHQ9TOTALT3 -.373** -.264* -.415** -.504** -.349** -.436** -.010 .292* -.102

SF12T2PCSTOTAL

.036 .420** .208 .246* .247* .019 -.123 .049

SF12T2MCSTOTAL

.129 .241* .304** .307** .059 -.122 .013

SF12T3PCSTOTAL

.077 .057 .246* -.028 -.111 .162

SF12T3MCSTOTAL

.218 .282* -.009 -.173 .067

MPSSTOTALMEANT2

.707** -.112 -.285* -.104

MPSSTOTALMEANT3

-.097 -.299**

-.085

PAQT2ALL36 .819** .861**

PPALL36 .698**

PAQT3ALL36

**correlation is significant at the 0.01 level (2-tailed); *correlation is significant at the 0.05 level (2-tailed)

75


Analytic Approach

The correlation matrix (Table 4) shows that the dependent variables

(PHQ9TOTAL, SF12PCSTOTAL and SF12MCSTOTAL) are highly correlated, as

conceptually they are measuring the related constructs of mood, mental health and

physical health. It is also clear from the correlation matrix that physical activity

scores for pre-pregnancy (T1), trimester 2 (T2) and trimester 3 (T3) are highly

correlated.

Data from the PPAQ, measuring pre-pregnancy physical activity (PA) levels

(T1) and the PAQ, measuring activity levels at the first trimester (T2) and the second

trimester (T3) show that over the course of pregnancy, some participants increased in

PA levels, others decreased in PA levels, and others reported PA levels which

remained the same.

It was therefore decided that change scores would be developed to assess how

an increase, a decrease or no change in physical activity levels over the course of

pregnancy affects mood, physical health and mental health.

Change scores were developed for differences in PA levels between T1 and

T2, T2 and T3 and T1 and T3 as follows:

1. Change in PA between T2 and T3 = PA at T2 – PA at T3

2. Change in PA between T1 and T2 = PA at T1 – PA at T2

3. Change in PA between T1 and T3 = PA at T1 = PA at T3

The change scores were distributed normally and a tertile split was used to

create 3 levels of change.

76


Level 1 - PA levels reduced (change scores fell between the minimum change

in PA score and the score at 33% cut off)

Level 2 – PA levels remained the same (change scores fell between the 33%

and 66% cut offs)

Level 3- PA levels increased (change scores fell between the 66% cut off an

the maximum change in PA score)

These 3 levels of change were applied to each of the three time points, i.e. for changes in PA

levels between T2 and T3, T1 and T2 and T1 and T3.

Analysis for changes in PA levels between T2 and T3

Table 5Summary of ANOVA’s for T3-T2

DV – dependent variabledf – degrees of freedom

PHQ9 – Patient Health Questionnaire 9MCS – Mental Composite Score on the 12-Item Short-Form Health Survey (SF-12)PCS – Physical Composite Score on the 12-Item Short-Form Health Survey (SF-12)

One-way analysis of variance (ANOVA) was used to compare the effect of a

reduction in PA, no change in PA and an increase in PA conditions on participants’

mood, mental health and physical during their third trimester of pregnancy. All

ANOVA’s were not significant (Table 5).



77

DV df (total) F Effect size pPHQ9 74 .947 .026 .393MCS 74 1.234 .033 .297PCS 74 1.184 .032 .312


DV – dependent variabledf – degrees of freedomPHQ9 – Patient Health Questionnaire 9MCS – Mental Composite Score on the 12-Item Short-Form Health Survey (SF-12)PCS – Physical Composite Score on the 12-Item Short-Form Health Survey (SF-12)



mood, mental health and physical during their second trimester of pregnancy. All

ANOVA’s were not significant (Table 6).



*p<0.05DV – dependent variabledf – degrees of freedomPHQ9 – Patient Health Questionnaire 9MCS – Mental Composite Score on the 12-Item Short-Form Health Survey (SF-12)PCS – Physical Composite Score on the 12-Item Short-Form Health Survey (SF-12)



mood, mental health and physical during their third trimester of pregnancy. The

effect of PA level on mood and physical health were found to be significant. The

effect of PA level on mental health was not found to be significant (see table 7).

The effect of PA on mood

78

DV df (total) F Effect size pPHQ9 73 1.340 .036 .268MCS* 73 2.884 .050 .068PCS 73 0.666 .136 .517

DV df (total) F Effect size pPHQ9 73 4.131 .101 .020*MCS 73 1.954 .051 .149PCS 73 3.917 .097 .024*


Post hoc comparisons using the Tukey HSD test indicated that the mean score

for the reduction in PA levels condition (M=6.64, SD=4.21) was significantly

different from the increase in PA levels condition (M=3.68, SD=2.75). However, the

no change in PA levels condition (M=5.38, SD=3.84) did not significantly differ

from the reduction in PA levels condition or the increase in PA levels condition).

(See Table 8 for descriptive statistics and Table 9 for Tukey test output).

Table 8Descriptive Statistics for PHQ9 scores for different levels of PA

T Table 9

Tukey HSD Comparison for mood 95% Confidence Interval

I J Mean Diff (I-J) Std Error Lower Bound Upper Bound

1 23

1.255382.96000*

1.023881.03387

-1.1942.4865

3.70495.4335

2 13

-1.255381.70462

1.023881.02388

-3.7049-.7449

1.19424.1542

3 12

-2.96000*-1.70462

1.033871.02388

-5.4335-4.1542

-5.4335-4.1542

*The mean difference is significant at the 0.05 level

79

Minimum Maximum Mean Standard Deviation

1 1 17 6.6400 4.211892 0 16 5.3846 3.837473 0 10 3.6800 72.74955


1 2 30

1

2

3

4

5

6

7

Level of PA

Mea

n PH

Q9

Figure 1. Graph showing significant decrease in PHQ9 score (indicating improved mood) when there is an increase in PA levels between “pre-pregnancy” and third trimester (condition3) compared with a decrease in PA levels.

The effect of PA on physical health

Post hoc comparisons using the Tukey HSD test indicated that the mean PW score for

the reduction in PA levels condition (M=31.97, SD=10.09) was significantly different from

the increase in PA levels condition (M=39.78, SD=7.45). However, the no change in PA

levels condition (M=35.75, SD=11.554) did not significantly differ from the reduction in PA

levels condition or the increase in PA levels condition). (See Table 10 for descriptive

statistics and Table 11 for Tukey test output).

Table 10Descriptive Statistics for PCS scores for different levels of PA

PPCS – Physical Composite Score on the 12-Item Short-Form Health Survey (SF-12)

PA – Physical Activity

Table 11

80

Minimum Maximum Mean Standard Deviation

1 8.16 51.42 31.9742 10.090662 10.36 54.60 35.7493 11.537973 23.66 54.29 39.7826 7.45424


Tukey HSD Comparison for physical health 95% Confidence Interval

I J Mean Diff (I-J) Std Error Lower Bound

Upper Bound

1 23

-3.77512-7.80846*

2.763512.79048

-10.3866-14.4845

2.8364-1.324xplaining

2 13

3.77512-4.03334

2.762512.76251

-2.8364-10.6449

10.38662.5782

3 12

7.80846*4.03334

2.790482.76251

1.1324-2.5782

14.484510.6449

*The mean difference is significant at the 0.05 level

Figure 2. Graph showing significant increase in physical health scores when PA levels increased from “pre-pregnancy” to trimester 3 (condition 1) compared with condition 2, where PA levels decreased from “pre-pregnancy” to third trimester.

81

1 2 30

5

10

15

20

25

30

35

40

45

Level of PA

Mea

n PC

S


Discussion

Analysis asked whether changes in physical activity over the course of pregnancy

changed mood, mental health and physical health. It was hypothesized that a drop in physical

activity between the second and third trimesters (T2 and T3) and from “pre-pregnancy” (T1)

to trimesters 2 and 3 would result in lower mood, mental health and physical health scores.

Results partially supported this hypothesis; a one-way analysis of variance (ANOVA)

comparing the effect of a drop in PA, no change in PA and an increase in PA from “pre-

pregnancy” to trimester 3 conditions on participants’ mood during their third trimester of

pregnancy was significant. Post hoc comparisons using the Tukey HSD test indicated that the

mean low mood score for the “drop in PA levels” condition was significantly greater than the

mean low mood score in the “increase in PA levels” condition. In other words, participants

who reduced their levels of activity over the course of pregnancy experienced greater levels

of low mood compared with participants who increased their activity levels.

A one-way analysis of variance (ANOVA) comparing the effect of a drop in PA, no

change in PA and an increase in PA from “pre-pregnancy” to trimester 3 conditions on

participants’ physical health during their third trimester of pregnancy was also significant.

Post hoc comparisons using the Tukey HSD test indicated that the mean physical health score

for the “drop in PA levels” condition was significantly lower than the “increase in PA levels”

condition. In other words, participants who reduced their activity levels over the course of

pregnancy experienced poorer physical health compared with those who increased their

activity levels.

The data did not show that a reduction in activity levels between “pre-pregnancy” and

the third trimester of pregnancy resulted in a reduction in mental health compared with

participants who increased their activity levels or those whose activity levels remained the

same.

82


This hypothesis was also partially unsupported; the data did not show that a reduction

in activity levels between the second and third trimesters of pregnancy resulted in a reduction

in mood, physical health or mental health compared with participants who increased their

activity levels or those whose activity levels remained the same. The data also did not show

that a reduction in activity levels between “pre-pregnancy” and the second trimester of

pregnancy resulted in a reduction in mood, physical health or mental health compared with

participants who increased their activity levels or those whose activity levels remained the

same.

The data in part suggests that an increase in physical activity levels over the course of

pregnancy improves mood and physical health. However, it is important to note that this was

only the case when comparing physical activity levels before pregnancy with those during the

third trimester. This finding is in line with research findings. Orr et al. (2006) looked at

exercise patterns of a cohort of low income, pregnant black women before and during

pregnancy and found that proportionately more women with lower levels of depressive

symptoms engaged in exercise during pregnancy (65.9%) than those with higher levels of

depressive symptoms (51.8%). Da Costa et al. (2003) interviewed 180 Canadian pregnant

women at each trimester of their pregnancy and found that more women who were not

exercising during their first trimester were depressed compared with exercisers. This pattern

was also shown in the second trimester, but not at the third. Pottinger et al. (2009) conducted

a prospective longitudinal study where they gathered self-reports of depression using the

Edinburgh Postnatal Depression Scale (EPDS) over three trimesters. The authors found

exercise to be a protective factor for having a depressive disorder. In a series of telephone

surveys, Haas et al. (2004) found that women who did not exercise prior to pregnancy were

more than twice as likely to report poor health, poor physical function and depressive

symptoms compared with women who exercised at least two hours per week. Koniak-Griffin

83


(1994) examined the effects of participation in a six-week aerobic exercise programme (AEP)

on pregnant adolescents and found that those in the AEP group experienced a significant

decrease in depressive symptoms over time and an increase in self-esteem. Those in the

comparison group reported a significant increase in physical discomforts associated with

pregnancy.

However, the findings from this study need to be approached with caution and within

the context of the limitations in study design, population and outcome measured used. It is

also important to consider the hypotheses which were supported within the context of the

other hypotheses, where results were not significant.

Firstly, there are limitations with the outcome measures used in the study. In terms of

participants’ scores on the PHQ-9, the mean score was 5.1 at second trimester, indicating

low, subclinical levels of depression. The standard deviation was 3.5, indicating that scores

did not vary much between participants. Further, there was not much variation between

scores taken at trimesters 2 and 3. The mean score at trimester 3 was 5.2 and the standard

deviation 3.8. It may have been more useful to use a more sensitive measure of mood such as

the Positive and Negative Affect Scale (PANAS) (Tellegen, 1988) to allow for a wider range

of scores between and within participants.

The Pregnancy Physical Activity Questionnaire (PAQ) is a self-administered series of

questions which asks respondents to report the time spent participating in 32 activities

including household/caregiving, occupational, sports/exercise, transportation, and inactivity.

The PAQ has been shown by some studies to be a reliable instrument and a reasonably

accurate measure of a broad range of physical activities during pregnancy (Chasan-Taber et

al., 2004). However, Shanna Wilson (2015) compared PAQ-measured PA to directly

measured PA using omniaxial Actical® accelerometers during the second trimester of

pregnancy and found the PAQ to overestimate moderate to vigorous physical activity.

84


Garriguet and Colley (2014) and Prince et al. (2008) also found evidence that self-reporting

of PA has poor reliability. However, for the purposes of this study, where participants

completed measures online, self-report of physical activity appears to be the most appropriate

means of measuring PA amongst this population. Taking into account the resources available,

it was not possible to collect data using accelorometers for large numbers of participants.

Furthermore, the majority of studies within the literature use self-reported measures of

activity, enabling this study to be comparable to other similar research papers.

At the second trimester (T2), where participants first completed the online survey,

they were asked to complete the PAQ for that trimester. Additionally, they were asked to

complete the PPAQ for “pre-pregnancy” exercise levels. This involved completing the PAQ

retrospectively to account for the “twelve months before their pregnancy”. As this survey

involved completing many questions about physical activity, respondents may have become

fatigued, thus affecting the accuracy of responses. Participants then had to complete the

questionnaire again during their third trimester, when they completed the second survey. The

number of questions about activity levels may explain why only 76 participants of the 135

who completed both surveys had complete data for all parts of the PAQ. There were large

chunks of the questionnaire missing, mainly from the later stages of the questionnaires. It

may have been helpful to use the option on the Qualtrics software whereby participants

cannot move onto the next question without completing all parts of the questionnaire, to

ensure all parts of all questionnaires were completed. However, setting Qualtrics to “force”

completion of items has ethical implications.

It is also worth noting that measuring “pre-pregnancy” exercise levels retrospectively

may not be accurate. There are numerous sources of bias that threaten the validity of

retrospective reports (Schwarz & Sudman, 1994). Furthermore, participants self-selected to

take part in the study, which may make them more influenced by the social desirability of

85


reporting particular behaviours. In general, people tend to over-report physical activity and

underestimate sedentary pursuits such as watching television (Klesges, Eck, Mellon et al.

(1990).

Taking this into account, it may have been useful to use a shorter measure for physical

activity, such as the Godin Leisure-time exercise questionnaire (Godin & Shephard, 1997),

which is comprised of only nine questions, compared with the PPAQ’s 32. This measure has

good test-retest reliability 0.62, p<0.05 (Jacobs, Ainsworth, Hartman & Leon.,1993) and

good relationships with other activity measures (Sallis, Buono. Roby et al., 1993).

The small sample size of only 76 participants further limits the power of the study.

From early power calculations, the desired sample size was 243 but this was not achieved.

This is largely due to participants dropping out between the first and second questionnaire

and due to large chucks on incomplete data, mainly from the PAQ.

The majority of participants are white Caucasian, highly educated women with a high

socioeconomic status and high levels of social support living in the UK and aged between 25

and 42. This limits the generalizability of the study to women from different cultural and

social backgrounds. Participants self-selected from social media and through NCT groups and

parenting forums such as “Mumsnet”. This may mean they have more of an interest in

physical activity and general health and well-being. In looking at responses to questionnaires,

it seems that women had low levels of depression and high levels of physical activity

compared with the general pregnant population. There is not much variability, in that the

majority of participants are clustered in their responses towards the lower end of scores of the

PHQ-9 (indicating sub-clinical, low levels of depression) and the higher end of scores on the

PAQ (indicating higher levels of physical activity).

Furthermore, although the participants who did not complete all aspects of the PAQ

questionnaire and thus were discounted from the analysis had broadly similar demographic

86


characteristics, they may have differed in other characteristics which were not measured, or

could have showed differences in their mood or activity levels. This further limits the dataset

used.

There are a number of potential factors which may influence physical activity levels

within this population which were not taken into account in the study. These include smoking

behavior, which is known to reduce engagement in physical activity during pregnancy (Ning

et al., 2003).

Overall, this study suggests that decreasing physical activity levels from before

pregnancy to the third trimester leads to a lower mood and reduced physical health, which is

in keeping with research findings and in line with the hypotheses. Lack of power in the

sample size may explain why a significant effect was only found between the “pre-

pregnancy” time point and the third trimester, and only comparing the condition where

physical activity reduced and the condition where physical activity increased. This

comparison likely resulted in the greatest difference in scores, making significant findings

more detectable.

It certainly seems that this topic area is welcome in the pregnant community, shown

by the positive response received by participants. Future research should use a larger sample

size, and perhaps a shorter less time intensive measure of physical activity. It may be helpful

to use an unobtrusive objective measure like accelerometry to supplement the self-report

measures, thus providing a more complete picture of activity levels. It would also be useful to

ask about further possible confounding factors, such as smoking.

Findings suggesting that increased physical activity during pregnancy improves mood

do not provide any information about the mechanism of change. This has been addressed

within the literature (Bryan, Hutchison, Seals & Allen, 2007) but is important to explore

further in future research. It would be useful to investigate whether the same mechanism

87


applies in the pregnant and in the non-pregnant population. It would also be useful to

examine whether the mood of pregnant women who already engaged in physical activity

prior to pregnancy changes in line with reduced or increased PA over the course of pregnancy

to the same extent as women who did not engage in pre-pregnancy PA.

Establishing a link between increased levels of physical activity during pregnancy and

improved mood is important for this population, who are at high risk of depression (Bennett

et al., 2004). Exercise may serve as a protective factor against antenatal and postnatal

depression. Given the difficulties with taking antidepressant medication during pregnancy

and the lack of resources in provision of psychological therapy, physical activity may be an

alternative intervention which is cost effective, safe and more acceptable to pregnant women.

Furthermore, pregnancy can be seen as a ‘teachable moment’ (Phelan, 2010) or a ‘window of

opportunity’ when women are a little more able to consider a change in lifestyle as they want

to do what is best for baby, so changes in attitude at this time might be possible.

It is also important that future research explores the mechanism by which physical

activity improves mood during pregnancy, so that effective interventions and clinical

recommendations may be established. Additionally, barriers to physical activity in this

population should be established, so that they may be addressed and thought about. As a

clinical psychologist, exercise may be a useful recommendation for pregnant women

experiencing low mood. Supporting patients to engage in physical activity before and during

this critical time may prove important as part of their care package.

88


References

Armstrong, K., & Edwards, H. (2004). The effectiveness of a pram‐walking exercise

programme in reducing depressive symptomatology for postnatal women. International

journal of nursing practice, 10(4), 177-194.

Atkinson, L., Parsons, J., & Jackson, B. R. (2014). Exercise in pregnancy–UK women’s

views and experiences: results of an online survey. Pregnancy Hypertension: An

International Journal of Women's Cardiovascular Health, 4(3), 231.

American Psychiatric Association (2015). Diagnostic and statistical manual of mental

disorders (5th ed.) Washington, DC.

Austin, M. P. (2003). Psychosocial assessment and management of depression and anxiety in

pregnancy. Key aspects of antenatal care for general practice. Australian family

physician, 32(3), 119.

Bennett, H. A., Einarson, A., Taddio, A., Koren, G., & Einarson, T. R. (2004). Prevalence of

depression during pregnancy: systematic review. Obstetrics & Gynecology, 103(4), 698-709.

Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to

Meta-Analysis. New York, John Wiley & Sons.

Brennan, P. A., Pargas, R., Walker, E. F., Green, P., Jeffrey Newport, D., & Stowe, Z.

(2008). Maternal depression and infant cortisol: influences of timing, comorbidity and

treatment. Journal of Child Psychology and Psychiatry, 49(10), 1099-1107.

Bryan, A., Hutchison, K. E., Seals, D. R., & Allen, D. L. (2007). A transdisciplinary model

integrating genetic, physiological, and psychological correlates of voluntary exercise. Health

Psychology, 26(1), 30.

89


Caspersen, C. J., Powell, K. E., & Christenson, G. M. (1985). Physical activity, exercise, and

physical fitness: definitions and distinctions for health-related research. Public health reports,

100(2), 126.

Chasan-Taber, L., Schmidt, M. D., Roberts, D. E., Hosmer, D., Markenson, G. L. E. N. N., &

Freedson, P. S. (2004). Development and validation of a pregnancy physical activity

questionnaire. Medicine and science in sports and exercise, 36, 1750-1760.

Craft, L. L., & Perna, F. M. (2004). The benefits of exercise for the clinically

depressed. Primary care companion to the Journal of clinical psychiatry, 6(3), 104.

Costa, D. D., Rippen, N., Dritsa, M., & Ring, A. (2003). Self-reported leisure-time physical

activity during pregnancy and relationship to psychological well-being. Journal of

Psychosomatic Obstetrics & Gynecology, 24(2), 111-119.

Demyttenaere, K., Bonnewyn, A., Bruffaerts, R., Brugha, T., De Graaf, R., & Alonso, J.

(2006). Comorbid painful physical symptoms and depression: prevalence, work loss, and help

seeking. Journal of affective disorders, 92(2), 185-193.

Dennis, C. L., Ross, L. E., & Grigoriadis, S. (2007). Psychosocial and psychological

interventions for treating antenatal depression. The Cochrane Library.

Downs, D. S., DiNallo, J. M., & Kirner, T. L. (2008). Determinants of pregnancy and

postpartum depression: Prospective influences of depressive symptoms, body image

satisfaction, and exercise behavior. Annals of Behavioral Medicine, 36(1), 54-63.

90


Dunn, A. L., Trivedi, M. H., Kampert, J. B., Clark, C. G., & Chambliss, H. O. (2005).

Exercise treatment for depression: efficacy and dose response. American journal of

preventive medicine, 28(1), 1-8.

Elsenbruch, S., Benson, S., Rücke, M., Rose, M., Dudenhausen, J., Pincus-Knackstedt, M.

K., ... & Arck, P. C. (2006). Social support during pregnancy: effects on maternal depressive

symptoms, smoking and pregnancy outcome. Human reproduction, 22(3), 869-877.

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical

power analysis for the social, behavioral, and biomedical sciences. Behavior Research

Methods, 39, 175-191.

Field, T. (2011). Prenatal depression effects on early development: A review. Infant Behavior

and Development, 34, 1–14

Freeman, M. P. (2007). Antenatal depression: navigating the treatment dilemmas. American

Journal of Psychiatry, 164(8), 1162-1165.

Gaston, A., & Prapavessis, H. (2013). Tired, moody and pregnant? Exercise may be the

answer. Psychology & Health, 28(12), 1353-1369. doi:10.1080/08870446.2013.809084

Garriguet, D., & Colley, R. C. (2014). A comparison of self-reported leisure-time physical

activity and measured moderate-to-vigorous physical activity in adolescents and

adults. Health reports, 25(7), 3.

Gaynes, B.N., Gavin, N., Meltzer-Brody, S., Lohr, K.N., Swinson, T., Gartlehner, G., Brody,

S., & Miller, W.C. (2005). Perinatal Depression: Prevalence, Screening Accuracy, and

91


Screening Outcomes: Summary. In: AHRQ Evidence Report Summaries. Rockville (MD):

Agency for Healthcare Research and Quality (US); 1998-2005. 119. Available from:

https://www.ncbi.nlm.nih.gov/books/NBK11838/

Gjestland, K., Bø, K., Owe, K. M., & Eberhard-Gran, M. (2012). Do pregnant women follow

exercise guidelines? Prevalence data among 3482 women, and prediction of low-back pain,

pelvic girdle pain and depression. British journal of sports medicine, bjsports-2012.

Godin, G., & Shephard, R. J. (1997). Godin leisure-time exercise questionnaire. Medicine

and Science in Sports and Exercise, 29(6), 36-38.

Goldberg, D. (2006). The aetiology of depression. Psychological Medicine, 36(10), 1341-

1347.

Gong, H., Ni, C., Shen, X., Wu, T., & Jiang, C. (2015). Yoga for prenatal depression: a

systematic review and meta-analysis. BMC psychiatry, 15(1), 14.

Goodwin, A., Astbury, J., & McMeeken, J. (2000). Body image and psychological well‐being

in pregnancy. A comparison of exercisers and non‐exercisers. Australian and New Zealand

journal of obstetrics and gynaecology, 40(4), 442-447.

Grote, N. K., Bridge, J. A., Gavin, A. R., Melville, J. L., Iyengar, S., & Katon, W. J. (2010).

A meta-analysis of depression during pregnancy and the risk of preterm birth, low birth

weight, and intrauterine growth restriction. Archives of general psychiatry, 67(10), 1012-

1024.

92


Haas, J. S., Jackson, R. A., Fuentes‐Afflick, E., Stewart, A. L., Dean, M. L., Brawarsky, P., &

Escobar, G. J. (2005). Changes in the health status of women during and after

pregnancy. Journal of general internal medicine, 20(1), 45-51.

Jacobs Jr, D. R., Ainsworth, B. E., Hartman, T. J., & Leon, A. S. (1993). A simultaneous

evaluation of 10 commonly used physical activity questionnaires. Medicine and science in

sports and exercise, 25(1), 81-91.

Jenkinson, C., & Layte, R. (1997). Development and testing of the UK SF-12. Journal of

Health Services Research, 2(1), 14-18.

Klesges, R.C., Eck, L.H., Mellon, M.W., Fulliton, W., Somes, G.W., et al. (1990). The

accuracy of self-reports of physical activity. Medicine & Science in Sports & Exercise, 22,

690–697.

Kieffer, E. C., Caldwell, C. H., Welmerink, D. B., Welch, K. B., Sinco, B. R., & Guzmán, J.

R. (2013). Effect of the healthy MOMs lifestyle intervention on reducing depressive

symptoms among pregnant Latinas. American journal of community psychology, 51(1-2), 76-

89.

Koniak‐Griffin, D. (1994). Aerobic exercise, psychological well‐being, and physical

discomforts during adolescent pregnancy. Research in nursing & health, 17(4), 253-263.

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The Phq‐9. Journal of general internal

medicine, 16(9), 606-613.

93


Kroenke, K. & Spitzer, R.L. (2002). The PHQ-9: A new depression and diagnostic severity

measure. Psychiatric Annals, 32, 509-521.

Kroenke, K., Strine, T. W., Spitzer, R. L., Williams, J. B., Berry, J. T., & Mokdad, A. H.

(2009). The PHQ-8 as a measure of current depression in the general population. Journal of

Affective Disorders, 114(1-3), 163-173. doi: 10.1016/j.jad.2008.06.026

LaFontaine, T. P., DiLorenzo, T. M., Frensch, P. A., Stucky-Ropp, R. C., Bargman, E. P., &

McDonald, D. G. (1992). Aerobic exercise and mood. Sports Medicine, 13(3), 160-170.

Lee, J. H., & Huber Jr, J. (2011, September). Multiple imputation with large proportions of

missing data: How much is too much?. In United Kingdom Stata Users' Group Meetings

2011 (No. 23). Stata Users Group.

Lee, I. M., & Shiroma, E. J. (2014). Using accelerometers to measure physical activity in

large-scale epidemiological studies: issues and challenges. British journal of sports medicine,

48(3), 197-201.

Legislation.gov.uk. (2015). Data Protection Act 1998. [online] Available at:

http://www.legislation.gov.uk/ukpga/1998/29/contents [Accessed 15 Jan. 2017].

LeWinn, K. Z., Stroud, L. R., Molnar, B. E., Ware, J. H., Koenen, K. C., & Buka, S. L.

(2009). Elevated maternal cortisol levels during pregnancy are associated with reduced

childhood IQ. International Journal of Epidemiology, 38, 1700–1710.

doi:10.1093/ije/dyp200

94


Martinsen, E. W. (2008). Physical activity in the prevention and treatment of anxiety and

depression. Nordic journal of psychiatry, 62(sup47), 25-29.

McLeod, S.A. (2015). Psychology Research Ethics. Retrieved June 19, 2015, from

http://www.simplypsychology.org/Ethics.html

National Institute of Mental Health. (2008). Women and depression: discovering hope. U.S.

Department of Health & Human Services, National Institutes of Health, National Institute of

Mental Health; Bethesda, MD: 2008.

Ning, Y., Williams, M. A., Dempsey, J. C., Sorensen, T. K., Frederick, I. O., & Luthy, D. A.

(2003). Correlates of recreational physical activity in early pregnancy. The Journal of

Maternal-Fetal & Neonatal Medicine, 13(6), 385-393.

Orr, S. T., James, S. A., Garry, J., & Newton, E. (2006). Exercise participation before and

during pregnancy among low-income, urban, Black women: The Baltimore Preterm Birth

Study. Ethnicity and Disease, 16(4), 909.

Orr, S. T., Blazer, D. G., James, S. A., & Reiter, J. P. (2007). Depressive symptoms and

indicators of maternal health status during pregnancy. Journal of women's health, 16(4), 535-

542.

Petruzzello, S. J., Landers, D. M., Hatfield, B. D., Kubitz, K. A., & Salazar, W. (1991). A

meta-analysis on the anxiety-reducing effects of acute and chronic exercise. Sports

medicine, 11(3), 143-182.

Phelan, S. (2010). Pregnancy: a “teachable moment” for weight control and obesity

prevention. American journal of obstetrics and gynecology, 202(2), 135-e1.

95


Pivarnik, J. M., Chambliss, H. O., Clapp, J. F., Dugan, S. A., Hatch, M. C., Lovelady, C.

A., ... & Williams, M. A. (2006). Impact of physical activity during pregnancy and

postpartum on chronic disease risk. Medicine & Science in Sports & Exercise, 38(5), 989-

1006.

Pottinger, A. M., Trotman-Edwards, H., & Younger, N. (2009). Detecting depression during

pregnancy and associated lifestyle practices and concerns among women in a hospital-based

obstetric clinic in Jamaica. General hospital psychiatry, 31(3), 254-261.

Poudevigne, M. S., & O'connor, P. J. (2005). Physical activity and mood during

pregnancy. Medicine & Science in Sports & Exercise, 37(8), 1374-1380.

Poudevigne, M., & O'Connor, P. J. (2006). A Review of Physical Activity Patterns in

Pregnant Women and Their Relationship to Psychological Health. Sports Medicine, 36(1),

19-38.

Prince, S. A., Adamo, K. B., Hamel, M. E., Hardt, J., Gorber, S. C., & Tremblay, M. (2008).

A comparison of direct versus self-report measures for assessing physical activity in adults: a

systematic review. International Journal of Behavioural Nutrition and Physical Activity,

5(1), 56. doi: http://dx.doi.org/10.1186/1479-5868-5-56

Qualtrics (2017). Qualtrics Version: March 2016-Feb 2017. Provo, UT: Qualtrics.

Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the

general population. Applied psychological measurement, 1(3), 385-401.

96


Sallis J.F., Buono M.J., Roby J.J., Micale F.G., & Nelson J.A. (1993) Seven-day recall and

other physical activity self-reports in children and adolescents. Medicine & Science in Sports

& Exercise 25(1), 99-108

Schwarz, N., & Sudman, S. (1996). Answering questions: Methodology for determining

cognitive and communicative processes in survey research. San Francisco: Jossey-Bass.

Shanna Wilson BSc, M. B. N. F. (2015). Self-report pregnancy physical activity

questionnaire overestimates physical activity. Canadian Journal of Public Health, 106(5),

E297.

Tendais, I., Figueiredo, B., Mota, J., & Conde, A. (2011). Physical activity, health-related

quality of life and depression during pregnancy. Cadernos de saude publica, 27(2), 219-228.

Tellegen, A. (1988). Development and Validation of Brief Measures of Positive and Negative

Affect: The PANAS Scales. Journal of Personality and Social Psychology, 54(6), 1063-1070.

Teychenne, M., Ball, K., & Salmon, J. (2008). Physical activity and likelihood of depression

in adults: a review. Preventive medicine, 46(5), 397-411.

Thompson, P. D., Buchner, D., Piña, I. L., Balady, G. J., Williams, M. A., Marcus, B. H., ...

& Fletcher, G. F. (2003). Exercise and Physical Activity in the Prevention and Treatment of

Atherosclerotic Cardiovascular Disease. Circulation, 107, 3109-3116.

97


Trost, S. G., Owen, N., Bauman, A. E., Sallis, J. F., & Brown, W. (2002). Correlates of

adults’ participation in physical activity: review and update. Medicine & Science in Sports &

Exercise, 34(12), 1996-2001.

U.S. Department of Health and Human Services, National Institutes of Health, National

Institute of Mental Health. (2015). Depression (NIH Publication No. 15-3561). Bethesda,

MD: U.S. Government Printing Office.

Ware Jr, J. E., Kosinski, M., & Keller, S. D. (1996). A 12-Item Short-Form Health Survey:

construction of scales and preliminary tests of reliability and validity. Medical care, 34(3),

220-233.

Watts, J. N., Miller, Y. D., & Marshall, A. L. (2013). Depressive symptoms during

pregnancy: Exploring the role of sitting. Mental Health and Physical Activity, 6(1), 36-42.

Yeung, R. R. (1996). The acute effects of exercise on mood state. Journal of psychosomatic

research, 40(2), 123-141.

Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional

scale of perceived social support. Journal of personality assessment, 52(1), 30-41.

98


Appendix 1: Support Data for the Analysis

Question 1

Does a drop in physical activity levels between trimester 2 (T2) and trimester 3 (T3) result in

a drop in mood, mental health or physical health?

Table of descriptives used in creating the change score for Question 1

Normality plot for the change score for Question 1

ANOVA 1.1: PHQ9 as Dependent Variable (DV)

Table of descriptives from ANOVA 1.1

99


Output from Levene’s Test of Homogeneity from ANOVA 1.1

ANOVA 1.2 – SF12MCS as DV



ANOVA 1.3: SF12PCS as DV


100


Output from

Levene’s Test of Homogeneity from ANOVA 1.3

Question 2

Does a drop in physical activity levels between “pre-pregnancy” and trimester 2 (T2) result in



101



ANOVA 2.1: PHQ9 as DV


102



ANOVA 2.2: SF12MCS as DV e



103


Adjusted F statistic based on violation of Leven’s Test




104


Question 3





105


ANOVA 3.1: PHQ9 as DV


Test of Homogeneity of Variances

PHQ9TOTALT3

Levene Statistic df1 df2 Sig.

1.062 2 73 .351

ANOVA 3.2: SF12MCS as DV



106





Appendix 2: Output from Analysis on Dataset using PAQ score from questions 1-25

1. Does a drop in physical activity levels between trimester 2 (T2) and trimester 3 (T3)

result in a drop in mood, mental health or physical health?

107





ANOVA

PHQ9TOTALT3

Sum of Squares Df Mean Square F Sig.

Between Groups 81.171 2 40.585 2.750 .068

Within Groups 1667.691 113 14.758

108


Total 1748.862 115




ANOVA

SF12T3MWTOTALCONST


Between Groups 161.137 2 80.568 .907 .407

Within Groups 10035.403 113 88.809

109


Total

10196.540 115




ANOVA

SF12T3PWTOTALCONST


Between Groups 233.813 2 116.906 .949 .390

Within Groups 13914.882 113 123.141

Total 14148.694 115

110




Question 2




StatisticsCHANGEPAQT2ANDPP

N Valid 116

Missing 0

Std. Deviation 56.33312

Variance 3173.421

111


Minimum -390.48

Maximum 130.58

Percentiles 25 -18.0750

33.3333 -13.8250

50 -1.8625

66.6666 3.7000

75 11.8562




112


Output from Levene’s Test of Homogeneity from ANOVA 2.

Adjusted ANOVA




Adjusted ANOVA

113



ANOVA

SF12T2PWTOTALCONST


Between Groups 219.367 2 109.684 1.729 .182

Within Groups 7166.690 113 63.422

Total 7386.057 115



Question 3

114








115



Adjusted ANOVA

Tukey Test Output

ANOVA 3.2: SF12MCS as Dependent Variable (DV)

ANOVA

SF12T3MWTOTALCONST


Between Groups 190.294 2 95.147 1.074 .345

Within Groups 10006.246 113 88.551

Total 10196.540 115

116




ANOVA 3.3: SF12PCS as Dependent Variable (DV)

ANOVA

SF12T3PWTOTALCONST


Between Groups 441.906 2 220.953 1.822 .166

Within Groups 13706.788 113 121.299

Total 14148.694 115


117



The questionnaires have been removed due to copyright issues.

118

Appendix 3: Outcome Measures


Bio

Name: Emma BurgessJob: Trainee Clinical PsychologistFrom: University of SurreyResearch Interest: Exercise, Pregnancy & Well-beingCurrent Clinical Role: Trainee Psychologist in Chronic Pain Service,St Georges Hospital, LondonContact Details: [email protected]

Does activity affect your mood and feeling of well-being when you are pregnant? Can this vary with time? My research aims to looks at the effects of physical activity (or lack of it!) during those life changing nine months.

Why is this important?If we can understand the connection between physical activity and mood in pregnant women, then we can support women more effectively during their pregnancy journey.

A bit of background into the research.Pregnancy is characterised by major changes in physical, social, and emotional health and can make women particularly vulnerable to the onset or return of depressive symptoms. 15% of women experience their initial onset of depression during pregnancy and 18.4% of women experience depression during pregnancy.

Although antidepressant medication has been shown to be effective, it has associated problems such as an increased risk of miscarriage and low birth weight. For these reasons, many women do not wish to take medication during pregnancy. Research already shows

that being physically active improves wellbeing and reduces depressive symptoms for women who are not pregnant. So what about the women who are pregnant? Research on this is limited and it has been difficult to draw conclusions from previous studies. We need

to know more.

My Study

119

Appendix 4: Article for local NCT Group Newsletter


My study aims to look into the effects of physical activity during pregnancy on mood and well-being. Participants are required to complete two online surveys, one during their second trimester and one during their third. Questions are about activity levels, mood and other things which may affect well-being, like the support people have.

How can you enter?It really couldn’t be easier! You can contribute to this important research and be automatically entered into our prize draw for just a few minutes of your time.If you are in your second trimester of pregnancy you can complete the first part of the survey by clicking the link below. It will take you around 10 minutes. I shall then send you the second part in a few months’ time. By entering, you will have a chance to win £50 in Amazon vouchers and contribute to this valuable research.

http://surveys.fahs.surrey.ac.uk/Pregnancy_Lifestyle_Factors/

120


121

Appendix 5: Poster advertising the study


122

Appendix 6: Ethical Approval Document


Appendix 7: Information Sheet for Participants displayed on Qualtrics

Lifestyle Factors during PregnancyInformation Sheet

PLEASE CLICK HERE TO START THE SURVEY

My name is Emma Burgess and I am a research student at the University of Surrey. I am carrying out a study about lifestyle factors during pregnancy.

Before you decide to take part, it is important for you to fully understand what the study involves and all relevant information. Please take time to read the following sheet carefully.

1. What is the purpose of the study?Specifically, I am interested in learning about lifestyle factors such as physical activity, social support, health and wellbeing and how they may affect the pregnancy experience.

2. What will the study involve?If you decide to take part, I will ask you to complete two identical online surveys, one during your second trimester (pregnancy week 13-28) and one during your third trimester (pregnancy week 29-40). Each survey will include some questionnaires about lifestyle factors which are a multiple choice format, where you will be asked to choose which answer option best applies to you. Each questionnaire will take around 10-15 minutes to complete. You will receive an email reminder prompting you to fill out the second questionnaire 10 – 16 weeks after you have filled out the first. Further information about the study will be provided at the end of the questionnaire.

123


3. Who will see my information?Nobody except for myself and my supervisors will be allowed to see your answers. You will be known only by number so your answers will remain completely confidential. If the results of this study are published, any information you give will not be identifiable as yours.If you decide to take part in the study, you will be asked to provide your email address at the end of the study. This address will be used to send you a reminder about completing the second questionnaire. Your email address will not be shared with anyone else.

4. Do I have to take part?It is up to you to decide to take part. If you do decide to take part in the study you will be asked to complete an online consent form to agree that you have read and understood the study information.

5. Can I withdraw from the study?If you decide to take part you may withdraw at any time without having to give a reason. You can also ask for your data to be destroyed. If you are a student at the University of Surrey, your decision about whether or not to take part will not affect your education in any way.

6. What are the incentives to complete the study?Prize drawYour participation in both parts of the study will entitle you to enter a prize draw, where you will have the opportunity to win £50 in vouchers. If you wish to be entered into the prize draw, please check the box at the end of the second questionnaire, sent 10 - 16 weeks after you have completed the first. You will also have the opportunity to receive information about the results of the study. If you are interested in hearing about the results and conclusions of the study, please inform the principal researcher via email who will send you a summary once the research is complete. Your email address will only be used for these purposes.

7. What are the possible disadvantages and risks of taking part? There are no known disadvantages or risks to participating in this study. However, if you do feel worse after taking part in the study and you feel you need some support to help with difficult emotions, please inform the principal researcher via email (see point 11 for details).

If you would like urgent support, you can contact the Samaritans on 08457 90 90 90 or [email protected]. For general information and support about mental health issues, you can also visit MIND, www.mind.org.uk.

8. What will happen to the results of the research study? The research study will be written up and submitted in partial fulfilment of the requirements of the Doctorate in Clinical Psychology. It is also proposed that the findings of the study will be written up and submitted to a peer-reviewed journal. If you are interested in hearing about the results

124


and conclusions of the study, please inform the principal researcher via email who will send you a summary once the research is complete.

9. Who has reviewed the study? This study has been reviewed and approved by the Psychology department's internal ethical procedure at the University of Surrey.

10. Who is organizing the funding of the research? The research is a requirement of my doctoral thesis as part of my training in Clinical Psychology. My training is funded by Surrey and Borders Mental Health and Social Care Trust.

11. What should I do if I would like to find out more?If you wish to discuss any aspect of the research with me, please email me at [email protected]. My study is being supervised by Professor Chris Fife-Schaw, University of Surrey and Dr Hayley Mills, Canterbury Christchurch University. If you would like to discuss any aspect of the research with them, you can contact them by email at [email protected]@canterbury.ac.uk.

Alternatively, you can use the postal addresses or telephone numbers provided below:

Emma Burgess&Professor Chris Fife-SchawFaculty of Health and Medical SciencesUniversity of SurreyGuildfordSurrey, UKGU2 7XH01483 68 6873

Dr Hayley Mills, CPsycholSenior Lecturer in Exercise Psychology.Section of Sport and Exercise Sciences,School of Human and Life Sciences,Canterbury Christ Church University,Canterbury,Kent,CT1 1QU01227 767700 ext: 3294

Appendix 8: Information participants receive after completing the study or if they choose to discontinue the online survey

125


Lifestyle Factors During Pregnancy Thank you for your participation in the first part of this study.You will receive an email when you reach your third trimester with a link to the second survey. This will have identical questions to the first survey and will take 15-20 minutes to complete.Pregnancy can be a difficult time, and sometime thinking about topics such as your health and the support you have can give rise to difficult emotions. If you felt uncomfortable or distressed and would like to access some support for this, or you would like some information on psychological well-being, details of organisations where you will be able to access this support are listed below:

Improving Access to Psychological Therapies (IAPT) is a national NHS programme that provides support for depression and anxiety disorders. You can find your local IAPT service at www.iapt.nhs.uk

NHS Choices provides information from the NHS on a range of

conditions, treatments, local services and healthy living. You can access this online at www.nhs.uk

The Samaritans are available 24 hours a day to provide confidential

emotional support for people who are experiencing feelings of distress, despair or suicidal thoughts. They can be reached in a number of ways. For the fastest response, it is best to telephone them. Tel: 08457 90 90 90; Email: [email protected]; Web: www.samaritans.org.

Your GP is able to provide information and support as well as make

referrals to other organisations for specialist support.

If you are a student at The University of Surrey, the university centre

for well-being offer counselling sessions. You can arrange an appointment by calling them on 01483 689498 or emailing them at [email protected]. Alternatively, you can go to the well-being centre Monday-Friday 9am-5pm to arrange an appointment in person.

126


IN AN EMERGENCY, for example, if you feel you are at risk of

harming yourself or you are experiencing suicidal thoughts, please visit your local Accident & Emergency department.

Should you have any further questions or concerns, or wish to discuss any aspect of the study please email me at [email protected]. My study is being supervised by Professor Chris Fife-Schaw, University of Surrey and Dr Hayley Mills, Canterbury Christchurch University. If you would like to discuss any aspect of the research with them, you can contact them by email at [email protected] / [email protected], you can use the postal addresses or telephone numbers provided below: Emma BurgessFaculty of Health and Medical SciencesUniversity of SurreyGuildford Surrey, UKGU2 7XH01483 68 6873 Professor Chris Fife-SchawFaculty of Health and Medical SciencesUniversity of SurreyGuildfordSurrey, UKGU2 7XH01483 68 6873 Dr Hayley Mills, CPsycholSenior Lecturer in Exercise Psychology.Section of Sport and Exercise Sciences,School of Human and Life Sciences,Canterbury Christ Church University,Canterbury,Kent,CT1 1QU01227 767700 ext: 3294

127


Part 3 – Summary of Clinical Experience

Adult Placement: Community Mental Health Team (CMHT)

I spent one year in a CMHT where I gained experience working with working age

adults presenting with a wide range of mental health difficulties. The primary treatment

model used was Cognitive Behavioural Therapy, though systemic and psychodynamic

models also informed work and formulation. On this placement, I worked with clients from

diverse ethnic and sociocultural backgrounds and used an interpreter for work with one

family. I also co-facilitated a Systems Training for Emotional Predictability and Problem

Solving (STEPPS) group for people with a diagnosis of Borderline Personality Disorder

(BPD). Whilst on this placement, I was also able to complete a full neuropsychological

assessment of intellectual functioning and memory, using the Wechsler Adult Intelligence

Scale (WAIS IV) and Wechsler Memory Scale (WMS IV) respectively.

Older Adult Placement: Community Mental Health Team for Older People

I spent six months based in a CMHT for older people. I gained further experience in

administering neuropsychological assessments. I worked alongside my supervisor in

delivering supervision and teaching to members of the multidisciplinary team around

administering and interpreting the Addenbrooke’s Cognitive Examination III (ACE III). I

gained experience in delivering dementia assessments and testing for executive function.

Whilst on this placement, I co-facilitated a Dementia Information Group for older adults with

dementia and their family members. The group comprised of a series of talks given by

different professionals about living with dementia. I led one of the talks which focused on the

psychological aspects of dementia, including adjusting to a diagnosis and managing difficult

emotions. Individual work on this placement included working with clients on managing

depression, anxiety and agoraphobia. I gained experience using narrative and Cognitive

128


Analytic Therapy (CAT) techniques. I also supervised a Community Nurse Practitioner in

using a Cognitive Behavioural approach to work with clients.

Child and Adolescent Placement: Tier 3 CAMHS and Behaviour and Learning Support

Service

For this six month placement, my time was split between a Behaviour and Learning

Support Service (BLSS) based in a Pupil Referral Unit (PRU) and a Tier 3 CAMHS

outpatient service. Work at the BLSS involved school observations, systemic work with

families and teachers to support children experiencing behavioural difficulties, and cognitive

assessments to identify learning needs. My supervisor on this placement used psychodynamic

and systemic approaches to inform the work. Whilst on this placement, I attended a

conference “Ameliorating the effects of childhood complex trauma in schools and families.”.

I presented material from this conference to the Tier 3 CAMHS service during their weekly

multidisciplinary team (MDT) meeting. Work at the Tier 3 CAMHS service involved

individual and systemic work with clients of different ages with various presentations. I

regularly attended MDT meetings to discuss cases and worked jointly with a wide range of

different professionals. Whist on this placement, I had an opportunity to link in with the

Service User Liaison Coordinator to deliver a presentation to school children about staying

well. This involved a morning of creative activities, discussion and group work at a

community theatre.

Specialist Placement: Chronic Pain Service

This six month placement involved working as part of a Chronic Pain Self-

Management Team (CPSMT). I was involved in multidisciplinary team assessments of

clients’ needs and in the co-facilitation of the Pain Management Programme (PMP). This is

an intense three week course and each programme has up to nine members who experience

persistent pain. The primary models used by the CPSMT are CBT, Mindfulness and

129


Acceptance and Commitment Therapy (ACT). During my time on this placement, I was able

to observe all the sessions on a full group programme. I then co-facilitated psychology-based

sessions for three complete programmes and was able to be involved in the one month follow

up session for one of these. I was also able to observe some three month follow-up sessions

from previous programmes, enabling me to get a full overview of a clients’ journey through

the service. Whilst on this placement, I was able to observe the Pain Consultants’ work in the

pain clinic and attend referral meetings with the CPSMT and the consultants. During this

placement, I gave a presentation to the team about using the Leeds Clinical and Reliable

Change Index to compare patients’ scores over the course of the programme.

Learning Disability Placement: Mental Health and Learning Disability Team

This six month placement involved working with clients with a diagnosis of a mental

health difficulty and a learning disability. Work took place in residential settings, the

community and in an outpatient clinic. Individual work with clients included working with

bereavement, anger, self-esteem and anxiety in addition to exploring areas such as identity

and stigma. I was able to use an integrative approach, drawing upon psychodynamic,

cognitive behavioural and attachment models. I worked systemically and indirectly with

members of a clients’ network around issues of challenging behavior. Whilst on this

placement, I co-facilitated a Client and Carers Group with a Well-being Navigator. This

group ran for six weeks and enabled people with a learning disability and their family

members to share their experiences, support one another and challenge stigma. I also further

developed my skills in administering neuropsychological assessments. I assessed a client with

Down Syndrome for signs of early onset dementia. I also assessed a client for memory and

executive problems. My skills were enhanced by two further assessments using all the core

subtests of the Weschler Adult Intelligence Scale IV (WAIS-IV).

130


Part 4 – Table of Assessments Completed During Training

PSYCHD CLINICAL PROGAMMETABLE OF ASSESSMENTS COMPLETED DURING TRAINING

Year I AssessmentsASSESSMENT TITLE

WAIS WAIS Interpretation (online assessment)Practice Report of Clinical Activity

Assessment and formulation of an 18 year old lady presenting with Obsessive Compulsive Disorder (OCD) with self-harm.

Audio Recording of Clinical Activity with Critical Appraisal

Audio Recording of Clinical Activity with Critical Appraisal

Report of Clinical Activity N=1

A Cognitive Behavioural Model for a 30 year old male with a diagnosis of Body Dysmorphic Disorder presenting with social anxiety symptoms.

Major Research Project Literature Survey

Exercise during pregnancy and depressionA survey of the literature

Major Research Project Proposal


Service-Related Project Evaluation of Systems Training for Emotional Predictability and Problem Solving (STEPPS) Group

Year II AssessmentsASSESSMENT TITLE

Report of Clinical Activity/Report of Clinical Activity – Formal Assessment

A Neuropsychological Assessment for a male in his 70s to assess for cognitive decline and establish executive functioning.

PPLD Process Account The Experience of being part of a Personal and Professional Learning Discussion Group: Reflections on the self, group processes and personal and professional change

Presentation of Clinical Activity

Presentation of Clinical Activity for a 10 year old boy experiencing separation anxiety.

Year III Assessments ASSESSMENT TITLE

Major Research Project Literature Review

Exercise during pregnancy and mood in the general pregnant population: A Review of the Literature

Major Research Project Empirical Paper


Final Reflective Account

On becoming a clinical psychologist: A retrospective, developmental, reflective account of the experience of training

Report of Clinical Activity/Report of

Report of Clinical Activity for a Pain Self-Management Group

131


Clinical Activity – Formal Assessment

132

Documents

epubs.surrey.ac.ukepubs.surrey.ac.uk/842244/1/Clinical Training Protfolio.do… · Web viewWord Count: Exercise during ... carried out a systematic review and meta-analysis to determine