Daily mindfulness is associated with recovery processes

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Pawsey, F., Wong, J H., Kenttä, G., Näswall, K. (2021)Daily Mindfulness Is Associated With Recovery Processes Among Coaches: A 4-WeekDiary StudyInternational Sport Coaching Journal, 8: 371-381https://doi.org/10.1123/iscj.2020-0045

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Daily mindfulness is associated with coaches’ recovery processes

Daily mindfulness is associated with recovery processes among coaches – a 4 week diary

study

Authors:

Fleur Pawsey, School of Psychology, Speech and Hearing, University of Canterbury, Private

Bag 4800, Christchurch 8140, New Zealand (corresponding author)

Jennifer Hoi Ki Wong, School of Psychology, Speech and Hearing, University of

Canterbury, Private Bag 4800, Christchurch 8140, New Zealand

Göran Kenttä, The Swedish School of Sport and Health Sciences, Stockholm, Sweden

Katharina Näswall, School of Psychology, Speech and Hearing, University of

Canterbury, Private Bag 4800, Christchurch 8140, New Zealand

1


2

Daily mindfulness is associated with recovery processes among coaches – a 4 3

week diary study 4

Sport coaching is a profession which is often demanding, and one in which 5

psychological burnout is problematic. Recovery from work demands is known to important in 6

preventing burnout, but research to date has paid little attention to short term recovery for 7

coaches. The present study therefore focuses on day to day recovery. Specifically, we 8

investigated the role of mindfulness in recovery, given previously established empirical 9

relationships between mindfulness and recovery processes. We used an intensive diary study 10

design to gather daily data from a sample of 46 sport coaches, over a period of 28 consecutive 11

days. Multilevel modelling allowed data analysis at the intra-individual level, providing 12

insights into daily recovery processes for individual coaches. Results showed that increases in 13

daily mindfulness, relative to coaches’ individual mean levels, were predictive of higher 14

levels of recovery related variables (energy, mood) through mechanisms of reduced 15

rumination and improved sleep. The present study highlights mindfulness as a potential path 16

to daily recovery, and prevention of burnout, amongst coaches. The study lays groundwork 17

for the investigation of mindfulness training as a recovery promoting intervention for 18

coaches, potentially through easily accessible means such as app-based training delivery and 19

the incorporation of informal mindfulness practice into daily activities. 20

Keywords: Stress, burnout, rumination, energy, mood 21

Introduction 22

Coaching in competitive sports is a profession which has the potential to be rewarding 23

and stimulating, but also one which is known for its pressures. Coaches typically face a number 24

of varied demands, associated not only with the technical nature of sport performance but also 25


to management, administration, and organizational stressors (Norris et al., 2017). Additionally, 26

many coaches work on a part time basis, and must fit the multiple tasks and responsibilities of 27

their coaching work around their primary or other employment (Potts et al., 2019). On top of 28

these demands, many coaches feel pressure to produce results, and often, in high competition. 29

It has been argued that this pressure becomes most obvious and demanding at the highest 30

competitive level (Giges et al., 2004). However, even at levels where competition is less 31

important, such as child and youth sports, coaches must deal with performance expectations, 32

either from external sources or internal sources such as high personal standards (Durand-Bush 33

et al., 2012). 34

Given these many and varied challenges, it is perhaps unsurprising that stress is a 35

common experience amongst coaches (Fletcher & Scott, 2010; Norris, et al., 2017). Drawing 36

on transactional theory (Folkman & Lazarus, 1984), stress can be explained as the result of an 37

appraisal process; a weighing up of perceived demands or threats against available coping 38

resources. Where demands exceed resources, feelings of stress are the likely outcome. It is 39

important to note that stress is not necessarily harmful, especially when stressful episodes are 40

short lived, and in the coaching context some coaches have even reported a certain amount of 41

stress as being invigorating, boosting energy and motivation (Olusoga et al., 2010; Olusoga et 42

al., 2019). Stress, however, is problematic if it is ongoing and chronic without adequate 43

recovery; in this form stress has been found to act as a precursor to a state of burnout (Fletcher 44

& Scott, 2010). 45

Burnout has been identified as a serious issue for coaches, from high performance right 46

through to volunteer and community levels (Engelberg-Moston et al., 2009; Olusoga et al., 47

2019), and therefore presents a cause for concern for the coaching profession (McNeill et al., 48

2017; O'Connor & Bennie, 2006; Olusoga et al., 2019). Symptoms of coach burnout include 49

depressed mood and low energy levels, sleep disturbances, and ruminative thought patterns 50


(Bentzen et al., 2014), as well as feelings of cynicism toward and disengagement from athletes 51

(Lundkvist et al., 2012; Madigan et al., 2019), and a desire to withdraw from coaching 52

(Hassmén et al., 2019). Clearly, burnout has a negative impact on affected coaches, but it also 53

affects the athletes and sports participants they work with. Given the negative impact of burnout 54

on coaches and those around them, understanding how to prevent coach burnout is of 55

importance. 56

Kallus & Kellmann (2000) conceptualise coach burnout as an end state resulting from 57

an imbalance between stress and recovery over a period of time. Recovery refers to the process 58

that takes place when work demands or stressors cease, and workers have the opportunity to 59

rebuild and restore those resources expended during the working day (Sonnentag, 2001). If 60

stress and recovery are determinants of burnout, it follows that one strategy to reduce the 61

likelihood of coach burnout, in a profession that is inherently demanding and stressful, is to 62

focus on day-to-day recovery (Bentzen et al., 2017; Bentzen et al., 2016; Kellmann et al., 2016). 63

Consistent with this reasoning, a growing body of research in the general (i.e. non coach 64

specific) work stress literature emphasises the importance of recovery, in terms of maintaining 65

worker wellbeing in the face of high work demands and associated stress (e.g. Rook & Zijlstra, 66

2006; Sonnentag, 2001; Sonnentag et al., 2008; Zijlstra, & Sonnentag, 2006). 67

A range of different activities are thought to contribute to recovery, so long as they do 68

not draw on the same resources that are called on at work (Sonnentag et al., 2008). However, 69

in professions such as coaching, where mental effort is involved, recovery can be difficult to 70

achieve. Work-related activity easily extends beyond work hours per se (Querstret et al., 2017), 71

because simply thinking about work challenges or problems can draw on the same mental 72

resources used during the working day thus limiting opportunities for good recovery 73

(Sonnentag, 2001, Rook & Zijlstra, 2006). This challenge is highly relevant to coaching in 74

sports, which is often described as a profession without boundaries that is difficult to mentally 75


disengage from (McNeill et al., 2017). Furthermore, coaches report that they find it hard to 76

stop thinking about work after hours, in addition to a tendency to engage in ruminative thought 77

patterns (e.g. Lundkvist et al., 2012; Tashman et al., 2010; Donahue et al., 2012). Ruminative 78

thoughts, which are intrusive, repetitive, and usually negative, are particularly detrimental to 79

recovery because they can form psychological representations of either past or future stressors 80

at work, prolonging the experience of work demands and the associated stress response 81

(Brosschot et al., 2010). Ruminative thought may be a precursor to, as well as a sign of, coach 82

burnout. In the present research, we therefore examine rumination on day to day basis and how 83

it is associated to the recovery processes, in order to understand more about how coach burnout 84

can be prevented. More specifically, we examine the role of mindfulness, a psychological state 85

that may act as an antidote to rumination and help facilitate better recovery. 86

Mindfulness and Recovery 87

Mindfulness is a state of consciousness involving a ‘receptive attention to and awareness of 88

present events and experience’ (Brown et al., 2007; p122), which has been related to a range 89

of positive outcomes including positive emotional states, and declines in mood disturbance and 90

stress (Brown & Ryan, 2003 Chiesa & Serrett; 2009; Sharma & Rush, 2014). Everyone has the 91

capacity to experience mindfulness (Tuckey et al., 2018), but some people tend to do so more 92

frequently and consistently than others. Mindfulness, therefore, varies between people, but can 93

also fluctuate within individuals. For example, someone who has a naturally high level of 94

mindfulness will still have moments or days when they are less aware of the present moment, 95

and when they end up completing tasks on autopilot (Siegel, 2009). Mindfulness can therefore 96

be considered trait-like (i.e., dispositional mindfulness) but also as a state of consciousness 97

which can vary somewhat from day-to-day within individuals (i.e., state mindfulness). 98

Over the last two decades mindfulness based interventions have been increasingly used 99

in sports settings, and have been found effective in enhancing performance as well as overall 100


wellbeing of athletes (Gardner & Moore, 2017). More recently, coach specific interventions 101

have been developed and tested. Longshore and Sachs (2015) found that coaches who 102

participated in mindfulness training reported less anxiety and greater emotional stability 103

following the intervention, while participants in an applied mindfulness intervention 104

(Lundqvist et al., 2018) experienced greater psychological flexibility and lower perceived 105

stress after completing mindfulness training. Importantly, those coaches also reported 106

improved sleep quality and reduced rumination. 107

We build on the findings of Lundqvist et al., (2018) in the present research, further 108

investigating the relationship between mindfulness and rumination amongst coaches, to 109

understand more about determinants of coach recovery. Previous research has demonstrated 110

that individuals who are higher in mindfulness are less likely to engage in ruminative patterns 111

of thinking (Josefsson et al., 2017; Jury & Jose, 2019; Querstret et al., 2017). There are several 112

possible explanations for this relationship. Firstly, mindfulness implies acceptance of events 113

and experiences, whereas rumination has been described as a maladaptive cognitive strategy 114

employed by individuals to avoid, rather than face up to, unwanted emotional states (Liverant 115

et al., 2011). Rumination, therefore, indicates a lack of acceptance (Ciesla et al., 2012; Liverant 116

et al., 2011), a mental or emotional state which seems incompatible with a state of mindfulness. 117

Additionally, as a cognitive response to events or experiences, rumination is automatic 118

rather than intentional. Mindfulness, on the other hand, is associated with decreased 119

automaticity of thoughts and emotions. Mindfulness is described as involving a shift in 120

perspective, referred to as decentering (Brown et al., 2007; Piet & Hougaard, 2011) or re-121

perceiving (Shapiro et al., 2006), in which thoughts and emotions are acknowledged simply as 122

temporary mental events rather than reflections of reality (Bishop et al., 2004; Wolkin, 2015). 123

Decentering therefore involves a separation of self from emotion, and this appears to reduce 124

automatic response patterns such as rumination. 125


In addition, mindfulness may also be associated with recovery because it appears to 126

promote sleep quality (Howell et al., 2010; Hülsheger et al., 2015). Sleep is fundamental to 127

recovery (Berset et al., 2011; Zijlstra & Sonnentag, 2006), bringing total disengagement from 128

work related activity, thought and effort (Hulsheger et al., 2015). On the other hand, lack of 129

sleep, or impaired sleep quality, can result in accumulated fatigue, and there are well 130

established links between impaired sleep and burnout in non-clinical populations (Grossi et al., 131

2015). When people are more mindful they may experience better quality sleep, and therefore 132

have greater opportunity for recovery. 133

The present research 134

The arguments presented so far suggest that individuals who are higher in dispositional 135

mindfulness are less likely to engage in ruminative thought, and more likely to experience 136

better quality sleep, in contrast to their counterparts who might be lower in mindfulness. Less 137

rumination, and better sleep quality, are thought to predict recovery from work demands. In 138

the present research we examined these relationships on a day to day basis, for individual 139

coaches. We proposed a an investigative model where daily mindfulness is indirectly related 140

to recovery indicators (mood and energy) through two potential explanatory variables; namely, 141

evening rumination and evening sleep quality. Mood and energy were chosen as outcomes 142

because they strongly associated to recovery: sufficient recovery is experienced by way of 143

feeling mentally and physically refreshed with an associated improvement in mood (Binnewies 144

et al., 2009; Sonnentag & Kruel, 2006). We expected that where participants were more 145

mindful than usual, they would report lower rumination and better sleep that evening, and 146

higher mood and energy levels the following day. 147

Research hypotheses follow: 148


Hypothesis 1: At the within person level, daytime mindfulness is: a) negatively related to 149

evening work-related rumination, and b) positively related to evening sleep quality. 150

Hypothesis 2: At the within person level, daytime mindfulness is positively related to mood 151

and energy ratings the following day, via the mechanisms of a) reduced evening rumination, 152

and b) improved sleep quality. 153

The purpose of the current research was to test the two hypotheses, and we did this by 154

using a diary design, with participants providing repeated daily measures of the same variables 155

over a period of 28 consecutive days. Each day, the data collection gathered information on 156

recovery related outcomes that day, as well as on recovery processes, which unfolded the 157

previous evening. This repeated measure design gave the ability to examine varying states 158

within individual participants (Gunthert & Wenze, 2012; Hamaker, 2012), and therefore to 159

understand more about individual participant’s recovery processes. 160

Methods 161

Participants 162

Participants were recruited through convenience sampling, via two different methods. 163

Some study participants were recruited through their participation in a previous coaching study 164

carried out by the lead author (while responses in that cross-sectional survey were anonymous, 165

some respondents provide an email address so that they might be contacted regarding future 166

research). Others responded to emails sent to their sporting organisations or governing bodies, 167

providing information on the present study and calling for participants. Eligibility was limited 168

to people over 18 years of age, actively working as a sport coach (either on a full time or part 169

time basis) and based in New Zealand. As an incentive, participants were offered the 170

opportunity to go in a draw for a $250 shopping voucher, provided they remained in the study 171

for the 28-day duration. 172


A total of 50 sport coaches began the study. Four were excluded from the analyses 173

because they had completed less than 50% of the daily surveys, leaving a remaining sample of 174

n = 46 (30 males, 65%). This sample size was deemed appropriate for the planned multilevel 175

analysis, where a sample of size of 30 or more is sufficiently large to not bias results (Ohly et 176

al., 2010). Participants ranged in age; the youngest participant identified as being in the 18-20 177

age bracket, while 15 participants (32%) were aged 50 years and over. Ten participants (21%) 178

were aged between 21 and 30 years, 7 (15%) were aged between 31 and 40 years, and 13 (28%) 179

were aged between 41 and 50 years. The majority of participants (29) had more than 10 years 180

coaching experience; only 7 participants had less than 5 years coaching experience. The other 181

10 coaches had between 5 and 10 years of experience. Approximately one third of participants 182

(n = 16, 36%) were full-time coaches, and the remainder coached part-time as well as being 183

employed elsewhere. Hours per week spent coaching ranged from 7 hours per week for a part-184

time coach who worked in other full-time employment, to 60 hours per week for a professional 185

rugby coach. Coaches came from a wide range of sports, including mainstream codes such as 186

rugby, netball, athletics and rowing, as well as lesser known sports such including archery, 187

equestrian, and multisport. The diversity in terms of age, experience, and sports means that it 188

is likely that participants had a range of pathways into their coaching positions; some may have 189

had formal training while others are likely to have learned ‘on the job.’ 190

Daily survey procedures 191

Data collection took place over a four-month period, and coaches were given the option 192

of participating in one of four separate rounds. Each round began on the first Tuesday of the 193

month and continued for 28 consecutive days. Coaches were asked to self-select the month in 194

which they would complete surveys, based on availability and their sporting season (coaches 195

were asked to only participate if they were in their competitive season, and therefore to choose 196

a month where this was the case). Data collection ran from August to November 2017, a time 197


period which captured the competitive season for winter and summer sports in New Zealand. 198

Prior to the beginning of data collection, the survey was piloted for seven days amongst a post-199

graduate research lab group and a small group of volunteers from a range of backgrounds and 200

occupations. Additionally, human ethics approval was obtained from the University of 201

Canterbury. 202

In the study itself, daily surveys were emailed to participants each evening for 28 203

consecutive days. Basic demographic information was captured in the initial survey. The 204

remaining 27 surveys contained the same questions each day, although the order of questions 205

was randomized to minimise habitual responding. Daily surveys were brief and took around 206

two minutes to complete. The text introducing and concluding the survey was consistent across 207

participants but different every day, both to keep participants interested and engaged and to 208

show interest and commitment on the part of the researchers. Participants were also given the 209

option to request weekly summaries of their survey scores, to further boost engagement. All 210

surveys and accompanying emails were friendly, informal and encouraging in tone, offering 211

opportunities for participants to provide feedback or to contact the researchers with any 212

questions or concerns. Every survey ended with an expression of thanks and appreciation to 213

the participants for their time and effort. 214

Participants were asked to provide an email address for an account they could access 215

either from home, or on their mobile device, and surveys were emailed via the Qualtrics survey 216

platform (Qualtrics, Provo, Utah, USA) at 7pm each evening. Participants were asked and 217

encouraged to complete each survey on the night it was sent. After 15 hours the survey was 218

made inaccessible, thus preventing late responses. Participants were strongly encouraged to 219

complete all 28 surveys but given the feasibility of an intensive daily diary study, missing a 220

survey on occasion would not impact their inclusion in the study. Of the 1288 possible surveys 221

over the course of the study, 1131 were completed with a mean of 24.64 (SD 3.34) of diary 222


entries per participant and a range of 17 – 28 entries. 41 participants completed 20 or more 223

surveys, with 8 participants completing all 28 entries. The highest number of missing surveys 224

for a single participant was 11. Friday and Saturday were the days on which surveys were least 225

likely to be completed. Missing data analysis showed that, at a within-person level, lagged 226

study variables were not significantly associated with the missed days of entry the next day. 227

Measures 228

Mindfulness 229

Daily mindfulness was measured using the state version of the Mindful Attention and 230

Awareness Scale (MAAS). This version of the MAAS has been used in similar diary research 231

(Hülsheger et al., 2014) and is a five-item scale which is designed to measure mindfulness as 232

a naturally occurring state, even in those without any prior mindfulness meditation training or 233

experience. Participants were asked to think back on the day they had just had and indicate the 234

extent to which they agreed with the scale items, an example of which is “I rushed through 235

activities without being really attentive to them.” Responses were given on a seven-point 236

Likert-type scale, where 1 = strongly disagree and 7 = strongly agree. Scores were reverse 237

coded prior to analyses, so that a high score would indicate higher levels of mindfulness. 238

Rumination 239

A five-item scale was adapted from the ‘affective rumination’ component of the Work-Related 240

Rumination Questionnaire (Querstret & Cropley, 2012). Items were slightly adjusted to refer 241

specifically to coaching work. The five adjusted items included in the scale were as follows: 242

“1. I became tense when I thought about coaching related issues during my free time; 2. I got 243

annoyed by thinking about coaching related issues when not at work; 3. I became irritated by 244

coaching issues when not at work; 4. I felt fatigued by thinking about coaching-related issues 245

during my free time; 5. I was troubled by coaching-related issues when not at work”. 246


Participants were asked to think back on the previous evening when responding, and responses 247

were provided on a 7-point Likert-type scale where 1 = strongly disagree and 7 = strongly 248

agree. 249

Sleep quality 250

Participants were asked to ‘please rate, out of ten, the overall quality of your sleep last night’, 251

using a visual analogue scale with anchor points at each end (0 = extremely poor and 10 = 252

extremely good). This single-item measure has been used in previous diary studies and 253

correlates highly with total scores on the Pittsburgh Sleep Quality Index (Pow et al., 2017), 254

while the visual analogue format was used by Arnetz et al. (2008) in their Brief Fatigue 255

Syndrome Scale. 256

Energy 257

Energy was measured using a single-item measure; participants were asked ‘please rate your 258

energy levels today,’ again using a visual analogue scale with anchor points at each of 0 = 259

extremely poor and 10 = extremely good (Fisher et al., 2016). This question was taken from 260

the Brief Fatigue Syndrome Scale (Arnetz et al., 2008), a validated scale containing three 261

single-item measures to measure three aspects of fatigue. The wording was adjusted slightly to 262

reflect the daily nature of the present study and different anchor points were used to ensure 263

consistency with the other single-item measures. 264

Mood 265

A single item measure was used for mood: participants were asked participants to ‘please rate 266

your overall mood today,’ using a visual analogue scale with anchor points at each end of 0 = 267

extremely poor and 10 = extremely good. Mood has been measured in previous recovery-268

related diary research using a similar single item (Fuller et al., 2003). 269


Reliability analysis 270

Reliability for the multi-item scales, in terms of measuring within person change, was 271

assessed following recommendations from Bolger and Laurenceau (2013). Coefficient omegas 272

for each scale were calculated based on the estimated factor loadings and variances from the 273

within person component of a multilevel confirmatory factor analysis (Bolger & Laurenceau, 274

2013). The resulting coefficient omegas of .85 for the mindfulness scale and .87 for rumination 275

indicated good reliability. 276

Statistical analyses 277

As the daily measures were nested within participants, multilevel modelling was 278

appropriate. All analyses were carried out using MPlus Version 8 (Muthén & Muthén, 2019). 279

The analyses utilised a lower level or 1-1-1 mediation model (Kenny et al., 2003) 280

reflecting the fact that all the study variables were measured at the lower (day) level. Following 281

recommendations from Preacher and colleagues (Preacher et al., 2011; Preacher et al., 2010) 282

an unconflated approach was taken, meaning that that the variance of the day-level variables 283

was separated into within- and between-level components. This approach allows for the 284

possibility that relationships between study variables will differ at the within- and between-285

levels. Additionally, each day-level predictor variable was centered on the person mean. 286

Centering in this way makes it possible to investigate how individuals’ daily deviations from 287

their own mean on a predictor variable relate to the outcome variable (Hülsheger et al., 2018), 288

and enables the study of intra-individual processes. 289

Although measures were collected at the same time each day, they related to different 290

points in time. On any given day, the survey measured mindfulness on that day, energy and 291

mood on that same day, and rumination and sleep the previous evening. The area of focus, and 292

research interest, was the temporal relationship between mindfulness on any day, rumination 293


and sleep that same evening, and energy and mood the following day. Therefore, prior to 294

analysis the mindfulness variable was lagged by one day in the dataset to allow this temporal 295

relationship to be assessed (Bolger & Laurenceau, 2013). For example, data collected on a 296

Tuesday evening related to mindfulness, energy, and mood on Tuesday, and rumination and 297

sleep on Monday evening. Lagging the mindfulness variable by one day meant that the Monday 298

mindfulness score could be used to predict Monday evening rumination and sleep, and Tuesday 299

daytime energy and mood. 300

Before testing the study hypotheses, several different elements of the data were 301

inspected. First, the intra-class correlation (ICC) was checked. This indicates the proportion of 302

variation that exists between people, compared with the total variation in the model (Finch & 303

Bolin, 2017). ICCs ranged from 0.32 to 0.48, indicating that a large amount of variation in the 304

model was at the within person level, and therefore that multilevel modelling was an 305

appropriate approach. Next, the data was visually inspected via the creation of individual panel 306

plots for each participant. This allowed for observation of variables across time, to check for 307

any evidence of systematic change. While none was apparent, recommendations from Bolger 308

and Laurenceau (2013) were nonetheless followed and time was included in the final model as 309

a predictor of the mediator and outcome variables. 310

Results 311

Tables 1 shows means, standard deviations, and intercorrelations for all study variables. Tables 312

2 and 3 display results of the multilevel mediation analysis, for the outcome variables energy 313

and mood respectively. It should be noted at this point that mediation analysis was used not to 314

explain any direct relationship between the predictor and outcome variables, but rather to 315

investigate the hypothesized indirect relationships between those variables, via the 316

hypothesized explanatory mechanisms (Agler & De Boeck, 2017). 317


Table 1: Descriptive statistics and correlations for study variables at within and between person level

Variable (within person) M SD 1 2 3 4 1 Mindfulness 5.19 1.34 - 2 Rumination 2.53 1.40 -.14* - 3 Sleep 6.66 2.25 .10* -.13* - 4 Mood 7.57 1.60 .08 -.23* .34* - 5 Energy 6.91 1.98 .06 -.15* .40* .53* Variable (between person) M SD 1 2 3 4 1 Mindfulness 5.19 1.28 - 2 Rumination 2.53 0.94 -.82* - 3 Sleep 6.70 1.28 .43* -.28 - 4 Mood 7.62 1.16 .73* -.69* .56* - 5 Energy 6.97 1.31 .62* -.55* .75* .73*

*significant at 0.05 level

At the within-subject level mindfulness was negatively related to rumination, meaning 318

that on days where individuals reported higher mindfulness during the day, they were less likely 319

to experience coaching-related ruminative thoughts that evening. Similarly, mindfulness 320

during the day was positively related to sleep quality that evening. Thus, Hypotheses 1a and 321

1b were supported. Regarding Hypothesis 2a, results showed a significant indirect relationship 322

between mindfulness and energy, via both rumination and sleep, supporting our predictions 323

(Figure 1). Similarly, Hypothesis 2b was supported, with mindfulness and mood indirectly 324

related, via both rumination and sleep. (Refer to Figure 1 for a conceptual model, including 325

results). 326

In terms of the relative effect of different variables in the model, standardized 327

regression coefficients showed that at the individual level mindfulness had a stronger effect on 328

rumination (-0.14, p = 0.000) than on sleep (0.09, p = 0.000). The effect of sleep on mood 329

(0.29, p = 0.00) was stronger than the effect of rumination on mood (-0.18, p = 0.00). Similarly, 330

the effect of sleep on energy (0.38, p=0.000) was stronger than the effect of rumination on 331

energy (-0.10, p = 0.003). Contrast tests, however, showed that neither rumination nor sleep 332

was more important than the other, in terms of their explanatory roles in the model. 333


Table 2: Results of mediation analysis for outcome variable Energy

Mediation Pathway Estimate SE P value LLCI ULCI Within Level Mindfulness Rumination -0.16* 0.06 0.006 -0.25 -0.06 Mindfulness Sleep 0.17* 0.07 0.011 0.06 0.27 Rumination Energy -0.15* 0.04 0.001 -0.22 -0.08 Sleep Energy 0.30* 0.07 0.000 0.19 0.41 Mindfulness Energy -0.02 0.04 0.698 -0.08 0.05 Indirect Effects

MindfulnessRuminationEnergy 0.02* 0.01 0.030 0.00 0.04 Mindfulness Sleep Energy 0.05* 0.02 0.044 0.01 0.09 Residual variance outcome 1.82* 0.39 0.000 1.17 2.46 Residual variance rumination 1.15* 0.13 0.000 0.94 1.36 Residual variance sleep 3.38* 0.39 0.000 2.33 4.43

Between Level Mindfulness Rumination -0.76* 0.11 0.000 -0.94 -0.59 Mindfulness Sleep 0.49* 0.19 0.009 0.18 0.79 Rumination Energy -0.35 0.19 0.075 -0.67 -0.03 Sleep Energy 0.61* 0.14 0.000 0.38 0.85 Mindfulness Energy 0.2 0.17 0.056 -0.08 0.49 Indirect Effects

MindfulnessRuminationEnergy 0.26 0.15 0.070 0.02 0.50 Mindfulness Sleep Energy 0.30* 0.14 0.030 0.07 0.53 Residual variance outcome 0.58* 0.2 0.003 0.26 0.90 Residual variance rumination 0.35* 0.06 0.000 0.24 0.45 Residual variance sleep 1.41* 0.24 0.000 1.02 1.81 *Significant at 0.05 level

334


Table 3: Results of mediation analysis for outcome variable Mood

Mediation Pathway Estimate SE P Value LLCI ULCI Within Level Mindfulness Rumination -0.16* 0.06 0.006 -0.25 -0.06 Mindfulness Sleep 0.17* 0.07 0.011 0.06 0.27 Rumination Mood -0.20* 0.04 0.000 -0.27 -0.14 Sleep Mood 0.20* 0.04 0.000 0.12 0.27 Mindfulness Mood 0.02 0.05 0.747 -0.06 0.09 Indirect Effects

MindfulnessRuminationMood 0.03* 0.01 0.013 0.01 0.05 Mindfulness Sleep Mood 0.03* 0.02 0.030 0.01 0.06 Residual variance outcome 1.32* 0.14 0.000 1.09 1.56 Residual variance rumination 1.15* 0.13 0.000 0.94 1.34 Residual variance sleep 0.28* 0.11 0.000 2.33 4.43

Between Level Mindfulness Rumination -0.76* 0.11 0.000 -0.94 -0.59 Mindfulness Sleep 0.49* 0.19 0.000 0.18 0.79 Rumination Mood -0.43* 0.21 0.035 -0.77 -0.09 Sleep Mood 0.28* 0.11 0.009 0.11 0.46 Mindfulness Mood 0.35 0.18 0.058 0.05 0.65 Indirect Effects

MindfulnessRuminationMood 0.33 0.17 0.055 0.05 0.61 Mindfulness Sleep Mood 0.14 0.08 0.096 0.00 0.05 Residual variance outcome 0.44* 0.11 0.000 0.26 0.61 Residual variance rumination 0.35* 0.06 0.000 0.24 0.45 Residual variance sleep 1.41* 0.24 0.000 1.02 1.81 *Significant at 0.05 level

335

Relationships at the between-person level were not hypothesized, because the focus of 336

the study was the within-person process of recovery. Tests for those relationships were, 337

however, included in the analysis. Results, displayed in Tables 2-3, show a similar pattern to 338

results at the within-subject level. Mindfulness was related to rumination and sleep, 339

indicating that those coaches who across the course of the study reported higher mindfulness 340

levels also reported less rumination and better-quality sleep. Consistent with the within-341


person analyses, there were significant indirect effects between mindfulness and both 342

outcome variables through rumination and sleep. 343

344

Figure 1: Results model showing relationships between study variables 345

Discussion 346

The 28-day diary study provided a rich body of data and with it the ability to investigate 347

within-person fluctuations in mindfulness, consequent changes in evening recovery processes, 348

and recovery-related outcomes the day after, for participating coaches. Examining daily 349

processes over an extended time period, at the individual level, is relatively unique in the 350

literature and therefore the present research contributes to a more in depth understanding of 351

daily recovery processes. Results provided support for both of the study hypotheses. Firstly, 352

and consistent with existing research (e.g., Josefsson et al., 2017; Querstret et al., 2017), a 353

negative relationship was found between mindfulness and subsequent rumination. Secondly, 354

results supported the hypothesis that there would be a positive relationship between daily 355

mindfulness and sleep that same evening, providing further evidence that a mindful attitude 356

promotes sleep quality (Howell et al., 2010). Finally, support was found for the hypothesized 357

model. Results showed an indirect relationship between coach mindfulness on a given day and 358

mood and energy the following day, through rumination and sleep quality on the given evening. 359

Specifically, on days where coaches reported higher mindfulness (relative to their own mean), 360


they also reported less coaching-related rumination and better sleep quality that evening, and 361

higher mood and energy ratings the following day. Altogether, this represents a recovery 362

process facilitated by state mindfulness. The use of within person lagged analysis in the present 363

study gives an indication of the temporal order of the variables. Intuitively it seems possible 364

that mindfulness, and consequent effects on rumination and sleep, might be outcomes rather 365

than predictors of positive mood. Previous research has suggested that when people are 366

experiencing better psychological wellbeing, they may be more likely to be mindful (Bishop, 367

2002), or that mindfulness levels and mood have a mutual influence on one another (Baer et 368

al., 2012). Past study designs, however, have not adequately allowed for examination of the 369

causal order of variables (Snippe et al., 2015). In the present study there was no significant 370

correlation between mindfulness and mood, but rather an indirect relationship via the 371

explanatory mechanisms of rumination and sleep, suggesting that increased mindfulness is 372

indeed a precursor to better mood. This is consistent with the findings of Snippe et al., (2015) 373

who examined within-person changes in mindfulness and mood following a Mindfulness 374

Based Stress Reduction intervention. Their findings indicated that changes in mindfulness 375

predicted changes in positive affect the following day, but changes in affect did not predict 376

next-day mindfulness. Mindfulness, they argued, was not simply a ‘side-effect’ of a good mood 377

(Snippe et al., 2015). While not yet conclusive, evidence, including that in the present study, 378

does suggest that mindfulness promotes positive affect rather than the other way around. 379

Sleep is an important part of any overnight recovery process, because of the opportunity 380

it provides for total disengagement from work related demands, as well as the replenishment 381

of resources. The present study expected, and found, mindfulness to be positively related to 382

sleep quality. This hypothesis was based on prior research suggesting that mindfulness 383

promotes better awareness and regulation of sleep behaviour (Howell et al., 2008; Hülsheger 384

et al., 2015). It is possible, however, that improved sleep is a result of decreased rumination 385


(Berset et al., 2011; Demsky et al., 2018), and that the two recovery processes proposed in the 386

present study (lower rumination, higher sleep quality) are interdependent. Future research, with 387

survey questions more targeted on different aspects of sleep quality, as well as a design that 388

would better support serial mediation and causal inferences (e.g. collection of data about post-389

work rumination with a brief survey in the evening, and collecting data on sleep quality the 390

following morning), could investigate this potential relationship more fully. 391

The present study contributes to the coach burnout literature by identifying the state of 392

mindfulness as a factor which might facilitate recovery and help coaches restore personal 393

resources so that they may continue to meet the demands of their work. Work-related thought 394

outside of work time can act as a continuation of work demands, therefore impeding recovery. 395

Negative rumination is considered particularly detrimental, because dwelling on work 396

problems and stressors may prolong the physiological stress response, and prevent restoration 397

of resources (e.g., energy, and positive affect). Contemplation of work challenges which is 398

positive in tone, however, appears to be less detrimental to recovery (Querstret & Cropley, 399

2012). The experience of positive events is known to build personal resources (Fredrickson, 400

2001) so it is possible that reflections on good things that have taken place at work add to rather 401

than deplete work-related resources. Taken together, these findings signal a need to identify 402

factors which affect the content and valence of work-related thought and may therefore 403

facilitate recovery. Results from the present study, particularly the negative relationship 404

between mindfulness and rumination, suggest that mindfulness is one such factor. 405

Many coaches are motivated to work because of a genuine interest in their chosen sport, 406

and in the development of sportspeople. They find a sense of purpose, meaning, and identity 407

in their work (McNeill et al., 2017). This motivation, amongst workers in an occupation known 408

for unusual work hours and high integration between work and non-work lives, means that 409

work-related thought often extends beyond work hours. Persistent and negative thoughts about 410


work issues are known to impede recovery from work demands. However, results of the present 411

study indicate that negative ruminative thought is less likely to occur when one is in a mindful 412

state. Given that the consistency and frequency with which individuals experience state 413

mindfulness (Creswell, 2017) can be increased through education and training, the study 414

highlights a potential direction for recovery promoting interventions for coaches. Given the 415

prevalence of burnout in coaching (e.g. Engelberg-Moston et al., 2009; Olusoga et al., 2019), 416

and the role of recovery in preventing burnout, results of the present study make a significant 417

contribution to the coach burnout literature. 418

Methodological considerations 419

A strength of the present study is the longitudinal design and daily data collection, as 420

there is limited research on actual day to day recovery processes amongst coaches. In addition, 421

little is known how mindfulness varies across workdays and how this might affect wellbeing 422

related outcomes. Almost all investigations of mindfulness in the work context look at trait 423

mindfulness, or the impact of mindfulness interventions (Tuckey et al., 2018). Results of the 424

present study, which show that varying levels of mindfulness predict variation in rumination 425

and sleep and are indirectly related to recovery, add to the literature on how, rather than 426

whether, mindfulness is related to a recovery process that facilitates coach wellbeing. 427

Mindfulness appears to help coaches regulate the content of work-related thought outside of 428

work time, reducing work-related rumination and thus allowing for more effective recovery 429

from the mental demands of work. Through this process, mindfulness may help to protect 430

against the risk of under-recovery and eventual burnout amongst coaches, ultimately enhancing 431

sustainability. 432

While the longitudinal design is one of the strongest features of the study, it also 433

presented challenges. Data collection took place over a relatively long timeframe, in order to 434


gain meaningful information on the overnight recovery process within individuals. 435

Administering daily surveys over 28 consecutive days, however, carried the risk of participant 436

boredom and disengagement. The survey was therefore deliberately brief, capturing only the 437

variables which were considered fundamental to the study. Future research into the relationship 438

between daily mindfulness and overnight recovery from work could include other variables 439

which potentially influence recovery. For example, daily measures of objective work demands 440

might influence the amount of recovery required each evening. Daily measures of perceived 441

work-related stress could provide some indication of the extent to which mindfulness predict 442

more benign stress appraisals and more adaptive coping strategies, reducing the likelihood of 443

ruminative thought. 444

In an effort to keep the daily surveys brief, single-item measures rather than multi-item 445

scales were used to measure some of the study variables. Multi-item scales are usually 446

considered more appropriate in survey research, as they allow for assessment of psychometric 447

properties, but single items are suitable in some circumstances (Van Hooff et al., 2007). In 448

daily diary studies where constructs are measured frequently and repeatedly, use of single-item 449

measures can help minimise the risk of participant boredom, disengagement, and dropout 450

(Fuchs & Diamantopoulos, 2009). Additionally, when a construct is familiar and unambiguous 451

to a participant, the use of a single item may be appropriate and even have higher face validity 452

than repetitive multiple items (Van Hooff et al., 2007). This was considered to be the case with 453

the constructs of mood, energy, and sleep, which were likely to be clear and familiar to 454

participants. Further, because the data of interest was within person fluctuations in mood and 455

energy, rather than absolute values, it was more important to measure according to each 456

individual’s understanding of the construct, rather than considering every possible aspect 457

(Gilbert & Kelloway, 2014). In the case of mindfulness and rumination, brief scales were 458


considered more appropriate than single items, as the constructs are very abstract in nature and 459

may not have been familiar to or easily conceptualised by participants. 460

Study variables were all measured using self-report, which does bring the risk of 461

common method variance. However, as part of the analysis the independent and mediator 462

variables were centered on the person mean, effectively eliminating any between-person 463

variance attributable to the response tendencies of individual participants (Niks et al., 2017). 464

In addition, the lagging of the data meant that there was a time delay between completion of 465

the mindfulness and rumination scales for each day. From a practical perspective, self-report 466

is the only way to measure constructs which are attitudinal or perceptual, such as rumination, 467

energy, and mood (Fisher et al., 2016; Schmitt, 1994). However, future research on the daily 468

within-person recovery process could explore the use of objective and physiological measures. 469

Steps have been taken toward development of an objective measure of mindfulness (e.g., Wong 470

et al., 2018), and sleep quality and quantity can feasibly be measured using heart rate 471

monitoring technology, as can physiological recovery from work demands. These measures 472

would require considerably more time, effort and commitment from participants, and were not 473

feasible for 28-day daily diary design of the present study where data was easily accessible via 474

self-report measures. 475

Practical implications 476

Mindfulness training is gradually receiving attention in sport coaching literature; a limited 477

number of studies have demonstrated the promise of formal mindfulness based interventions 478

in assisting coaches to maintain wellbeing (e.g. Longshore & Sachs, 2015; Lundqvist et al., 479

2018). However, in considering the impact of day to day fluctuations in mindfulness, the 480

present study makes a novel contribution with important practical implications. In addition, it 481

responds to the recent call by Cropley et al. (2020) for more research into self-care strategies 482


that may be taken by coaches. Specifically, results from the present study suggest that even 483

small shifts in mindfulness, relative to one’s daily norm, can have an effect on both rumination 484

and sleep, and therefore may impact the degree to people can recovery from work demands. 485

These findings suggest it could be worthwhile for coaches to take even very small steps that 486

help them to be more mindful, more often. As Creswell (2017) suggests, mindfulness training 487

could viewed in a similar vein to physical training that strives to improve aerobic or muscular 488

capacity; while it might be true that there are optimum training levels in terms of volume and 489

intensity, where this levels are not realistic consistently doing some training is certainly better 490

than none. This should be encouraging for coaches, many of whom may consider the time and 491

commitment requirements of formal mindfulness training programmes a major deterrent. 492

Today, there are practical and accessible ways in which coaches might bring more mindfulness 493

into their daily lives. 494

One option which could feasibly be explored by coaches, and the coaching profession, is digital 495

mindfulness training. Over the last decade mindfulness apps have provided mindfulness 496

instruction to millions of people in different settings (Mrazek et al, 2019). This form of delivery 497

makes mindfulness instruction highly accessible, and even very brief interventions (for 498

example, 10 sessions of 10 minutes each, taking at time and setting of participants’ choice) 499

have been found to have a positive impact on aspects of participants’ wellbeing (Campillo et 500

al., 2018). Critics point out that the plethora of available apps do vary in their content, quality 501

and effectiveness, and the extent to which they teach mindfulness or simply offer guided 502

meditation (Mani et al., 2015). Indeed, to continue with the physical training analogy, any 503

coach will agree that a program well designed, evidence based and specific to the population 504

is preferable. The same is true for mindfulness training (Baltzell et al., 2014). So perhaps while 505

a readily available ‘off the shelf’ app may be a good start, there is potential and need for the 506


development for online, app based mindfulness resources specifically targeted toward sport 507

coaches. 508

Additionally, mindfulness can be built and maintained through informal as well as formal 509

practice (Hindman et al., 2015). Informal practice simply means incorporating mindfulness 510

into everyday tasks and existing routines, such as eating mindfully, completing household 511

chores mindfully, or simply engaging in mindful moments. Using such activities as an 512

opportunity to be mindful can increase state mindfulness (Hanley et al., 2015), and as shown 513

in the present study even small increases in state mindfulness may have an impact on wellbeing. 514

Coaches, therefore, could benefit from being taught and encouraged to cultivate moments of 515

mindfulness in their day to day activities; a practice that could be in addition to or instead of 516

formal mindfulness practice. It is suggested that coach education programs could include and 517

promote both formal and informal mindfulness practises, with an emphasis that it will enhance 518

well-being and sustainability in the coaching profession. 519

Conclusions 520

Many sport coaches are faced with high demands, making regular and sufficient 521

recovery important for sustained wellbeing and performance. In showing that variations in 522

daily mindfulness are predictive of changes in rumination levels and sleep quality, which in 523

turn predict changes in recovery related outcomes, the present study highlights a potential 524

path to daily recovery. Groundwork is laid for the investigation of mindfulness training as a 525

recovery promoting intervention, potentially through easily accessible means such as app 526

based training delivery and the incorporation of informal mindfulness practice into day to day 527

activities. 528

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Daily mindfulness is associated with recovery processes