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This article was published in Psychology and Psychotherapy Theory Research
and Practice
Reference: Varese, F., Mansell, W. and Tai, S. J. (2017), What is distressing about auditory verbal hallucinations? The contribution of goal interference and goal facilitation. Psychol Psychother Theory Res Pract. doi:10.1111/papt.12135
Abstract
Objectives: Distressing as well as pleasant/positive voices (auditory verbal
hallucinations) are common in both clinical and non-clinical voice-hearers.
Identifying factors that contribute to emotional reactions to voices is essential for
developing effective psychological interventions. Several theories propose that
facilitation and interference with personal goals are important predictors of distress
and well-being. This study examined whether voice-related distress is related to the
degree to which voices interfere with personal goals, and whether pleasantness of
voices is influenced by the extent to which they facilitate goals.
Design: Cross-sectional with clinical and non-clinical voice-hears
Method: 22 clinical and 18 non-clinical voice-hearers completed interviews and
self-report measures assessing (i) personal goals, (ii) content, characteristics and
affective reactions to voices, and (iii) ratings of the extent to which voices facilitated
and/or interfered with achievement of important personal goals.
Results: Affective reactions were strongly correlated with measures of goal
interference and goal facilitation. Regression analyses revealed these associations
remained significant when controlling for important covariates (e.g. participant
1
grouping; content, frequency and duration of voices). Goal interference was
specifically associated with distress, whereas goal facilitation specifically predicted
perceived pleasantness of voices.
Conclusions: This study provides a novel perspective on the factors that might
contribute to distress in people who hear voices. The findings suggest that perceived
impact of voices on valued personal goals may be an important contributor of voice-
related distress. We propose that clinical assessments, formulations and interventions
could benefit from the careful analysis of the perceived impact of voices on goals.
Practitioner points:
These findings suggest that variability in voice-related distress is closely
linked to the perceived impact of voices on personal goals.
These strong effects observed highlight the importance of considering the
role of personal goals in future research on the psychological mechanisms
leading to distress associated with voice-hearing.
Psychological assessments may benefit from the careful exploration of the
impact of voice hearing on valued goals, and interventions promoting control
over personal goals may be explored as treatment options for clients with
distressing voices.
2
Hearing voices is frequently regarded as characteristic symptoms of
schizophrenia-spectrum disorders, but are also relatively common amongst
individuals with other diagnoses such as bipolar disorder, post-traumatic stress
disorder, depression, and personality disorders (for reviews of prevalence studies,
see Aleman & Larøi, 2008; McCarthy-Jones, 2012). Furthermore, a sizable minority
of individuals in the general population without mental health difficulties also
experience voices (e.g. Beavan, Read, & Cartwright, 2011; Johns, Nazroo,
Bebbington, & Kuipers, 2002). Comparisons of clinical and non-clinical voice-
hearers suggest that non-clinical voices are characterised by lower levels of negative
content and distress (e.g. Daalman et al., 2010; Daalman & Diederen, 2013; Hill &
Linden, 2012; Hill, Varese, Jackson, & Linden, 2012). However, voices described by
psychiatric patients are not always experienced as distressing (Oorschot et al., 2012).
Previous studies indicate that positive/pleasant voices are relatively common
amongst clinical voice-hearers and often associated with the person’s desire to
“preserve” and engage with voices (e.g. Jenner, Rutten, Beuckens, Boonstra, &
Sytema, 2008; Miller, O'Connor, & DiPasquale, 1993; Sanjuan, Gonzalez, Aguilar,
Leal, & Van Os, 2004). The reasons for such variability in emotional responses are
unclear, with the majority of previous research focusing primarily on the ways in
which voices are idiosyncratically appraised individuals (Chadwick, Lees, &
Birchwood, 2000; Morrison, Nothard, Bowe, & Wells, 2004; Peters, Williams,
Cooke, & Kuipers, 2012)
Personal goals are a psychological construct that may provide an integrative
perspective on the apparent variability in the affective reactions to voices. Goals are
defined as ‘internal representations of desired states, where states are broadly
construed as outcomes, events or processes’ (Austin & Vancouver, 1996, p. 338).
3
Goals can convey both information facilitating an individual in progressing toward
or maintaining desirable outcomes (e.g. to be successful), and also inhibiting
undesirable ones (e.g. to avoid failure; Dickson & MacLeod, 2004; Elliot & Sheldon,
1998; Elliot, Sheldon, & Church, 1997). Several theories propose that goals are
internally organised within hierarchical structures of interrelated internal standards,
ranging from innate or gene-driven needs and predispositions (e.g. the range of
optimal blood sugar levels, hunger, need for affiliation) to more complex desired
states formed from past perceptual experiences and sociocultural influences (e.g. a
desired body shape, the person’s self-concept; Austin & Vancouver, 1996). Implicit
to this hierarchical organisation is the notion that lower-order, concrete goals (e.g. to
call a sick relative) can be “traced” to more abstract and general higher order goals
(to be a loving person).
Within several control theory accounts of human behaviour and cognition
(e.g. Perceptual Control Theory, PCT; Powers, 1973, 2005; Powers, Clark, &
McFarland, 1960a, 1960b) the processes through which goals are achieved and
maintained has been often defined in terms of negative feedback control (e.g. Ashby,
1952; Wiener, 1948). In this context, control is defined as a process which reduces
the discrepancy between a desired state (a goal) and the person’s current experience,
leading to a process of continuous dynamic corrections to achieve and maintain
certain desired states. Previous research has demonstrated that successful pursuit of
personally valued goals (in other words, successful control over one’s goals) is
related to positive affect and subjective well-being (Diener, 1984; Emmons, 1986;
Oishi, Diener, Suh, & Lucas, 1999). In contrast, when important personal goals are
threatened and remain unachieved, negative affect and distress may be experienced,
especially when goals that are particularly valued or fundamental to the individual
4
remain in a state of error (Emmons, 1986; Martin, Tesser, & McIntosh, 1993;
McIntosh, Harlow, & Martin, 1995; Srull & Wyer, 1986).
These goals- and control-based theories provide a number of hypotheses
regarding the mechanisms leading to different affective reactions to voices. As
distress is the manifestation of reduced or lost perceived control over desired states,
and in line with findings suggesting that positive and negative affect are experienced
when individuals are successful or unsuccessful in attaining/progressing towards
valued goals (e.g. Emmons, 1986), it is predicted that different affective reactions to
voices depends on the extent to which voices either facilitate or interfere with
important personal goals. In the current study, we tested several hypotheses
consistent with this prediction. First, we examined whether voice-related distress is
associated with the degree to which voices interfere with goals attainment, and
whether perceived pleasantness of voices is related by the extent to which voices
facilitate goal attainment. Second, using regression methods, we tested whether these
hypothesised associations remained significant after accounting for other
determinants of affective reactions to voices (including the amount of negative voice
content, frequency frequency and duration of voices, and the amount of “disruption”
to daily functioning caused by the voices; Haddock, McCarron, Tarrier, & Faragher,
1999; Morrison et al., 2004; Varese et al., under review). Third, we examined the
related hypothesis that clinical voice-hearers (i.e. individuals generally characterised
by heightened levels of voice-related distress, despite considerable individual
variability) would present higher levels of goal interference and lower levels of goal
facilitation when compared to non-clinical voice-hearers.
5
Method
Participants
Forty voice-hearers were recruited for this study. In line with symptom-
specific approaches to the study of psychotic experiences (e.g. Bentall, 2003), no
restriction was placed on eligible psychiatric diagnoses. All participants met the
following eligibility criteria: (i) aged above 16-years-old, (ii) had experienced voices
in the two weeks prior to participating in the study, (iii) history of voice-hearing had
a minimum of six months duration, (iv) the experience of voices was not due to
organic illness (e.g. traumatic brain injury), hypnagogic/ hypnopompic states, sleep
disorders (e.g. sleep paralysis), or alcohol/ drugs intoxication. Demographic
characteristics for the sample are reported in Table 1.
[Insert Table 1 approximately here]
For the purpose of some of the analyses included in the present paper, two
participant subgroups were created: a non-clinical voice-hearers group (n = 18),
comprising individuals with no current or past mental health difficulties requiring
contact with mental health services and/or formal psychiatric diagnoses, and a
clinical voice-hearers group (n = 22), comprising individuals who disclosed having
received a psychiatric diagnosis and/or present or past use of inpatient and/or
outpatient mental health services. Group allocation was informed by self-reported
information provided as part of a short structured interview adapted from the
“Demographic Data”, “Education and Work History” and “Treatment and
Hospitalization History” sections of the Overview module of the Structural Clinical
Interview for DSM-IV-TR; Axis I Disorder (First, Spitzer, M., & Williams, 2002;
see Appendix A). Demographic and clinical characteristics for the sample are
6
reported in Table 1. The two groups were comparable in terms of age, gender and
ethnicity (White Caucasian vs other ethnicity).
Measures
Content and characteristics of voices. A semi-structured interview was
used to assess voice characteristics. Firstly, the interview schedule included the
auditory hallucinations subscale of the Psychotic Symptoms Rating Scale
(PSYRATS-AH; Haddock et al., 1999), a multi-dimensional semi-structured
interview assessing cognitive, affective and “physical” (e.g. loudness, location)
dimensions of voices on 5-point scales (0 to 4). The PSYRATS-AH has
demonstrated good validity and reliability in previous studies, including samples
comprising clinical and non-clinical voice-hearers (e.g. Sommer et al., 2010). For
the present analyses, three separate PSYRATS-AH scores were computed based on
previous factor analytic findings (e.g. Steel et al., 2007; Varese et al., 2016): a total
distress score, defined as the combination of the PSYRATS-AH amount and
intensity of distress items (Spearman-Brown reliability = 0.96 in this sample); a total
negative content score, defined as the amount and degree of negative content items
(Spearman-Brown reliability = 0.94), and a total score comprising the PSYRATS-
AH frequency and duration items (Spearman-Brown reliability = 0.76). We also used
the PSTRATS-AH single-item disruption scale, assessing the impact of voices on the
hearer’s daily living functioning. Furthermore, as the PSYRATS-AH only provides
measures of voice-related distress, but not other affective responses to voices,
participants were asked to provide self-reported ratings of voice pleasantness (“On a
scale from 0 to 10, how pleasant are the voices?”; 0 = “Not at all”, 10 = “Very much
so”). A similar item assessing voice-related distress (“On a scale from 0 to 10, how
7
distressing are the voices?”) was also included to ensure that similar measures of
distress and pleasantness were available for statistical analysis.
Voice facilitation and interference with goals. Participants completed a
series of procedures to generate personally salient “higher-order” (i.e. cross-
situational and/or self-descriptive) goals, followed by a set of questions exploring
further the extent to which their voices influenced their perceived ability to achieve
these goals. An adapted version of the Goal Task (Dickson & MacLeod, 2004) was
used to assess personal goals. This task was modified following piloting work with
two clinical and three non-clinical pilot participants, with the aim of adapting the
procedure to match current study aims and participant population. The task involved
two separate stages. Firstly, participants were asked to describe as many goals that
came to mind within a 3-minute period (i.e. goals were described to participants as
experiences that individuals typically try to accomplish or avoid), and rate the
perceived importance of each goal on a 11-point scale (i.e. “How important is for
you to accomplish this goal?”; 0 = “Not at all”, 10 = “Very much so”). Secondly, as
pilot work indicated that the goals generated using the above procedure were often
“concrete” (context- or activity-specific e.g. “Finish my nursing degree by
September”), an additional component was included to encourage participants to
generate more abstract and general goals. This involved the participants being asked
a series of “why questions” (a questioning style used in several goal constructs
approaches to demonstrate the hierarchical nature of goals; Carey, 2006; Mansell,
Carey, & Tai, 2012) inquiring why they considered important achieving a certain
goal. This was repeated until the participant identified a general cross-situational or
self-definitional goal (e.g. “Being a helpful person”) that underpinned the more
8
concrete goal previously generated (e.g. “Finish my nursing degree by September”).
This procedure was limited to the three goals rated as the most important by the
participant, and follow-up questions were used to ensure that the information
provided during this procedure were indeed regarded as salient goals by the
participant (“Is being an helpful person one of your goals?, “How important is for
you to accomplish this goal on a scale from 0 to 10”). Finally, participants rated how
much voices facilitated and/or hindered their achievement of goals. Separate
facilitation and interference ratings were provided for the three abstract/general goals
identified in the modified Goal Task (e.g. “How much do the voices help with
achieving this goal?” and “How much do the voices interfere with achieving this
goal?”; 0 = not at all, 10 = very much so). Ratings were averaged to provide two
separate summary scores for goal facilitation and goal interference. Both scores
presented good internal consistency in the present study (Cronbach’s αs = 0.89 and
0.91, respectively).
Emotional distress. The short Depression, Anxiety and Stress Scales
(DASS-21; Lovibond & Lovibond, 1995)is a questionnaire assessing emotional
distress. This measure was included to increase comparability of our findings with
those of previous studies which have included measures of emotional symptoms in
addition to or instead of voice-related distress, (e.g. Peters et al., 2012). The DASS-
21 requires participants to rate the extent to which they experienced 21 different
symptoms of anxiety, depression and stress in the previous week on a 4-point scale
(0 to 3). In this study, the DASS-21 presented excellent internal consistency
(Chronbach’s α = 0.96).
9
Procedure
After receiving NHS Ethics and R&D approval, prospective participants were
recruited in the Greater Manchester region between June 2013 and April 2014.
Participants were approached through (i) liaison with mental health services, mental
health charities and Hearing Voices Network groups, (ii) display of poster adverts on
University of Manchester premises, GP surgeries and public venues (e.g. libraries,
community notice boards), (iii) liaison with local Spiritualist churches (given
previous findings suggesting high prevalence of non-clinical voice-hearers in these
communities; e.g. Hill & Linden, 2012; Hill et al., 2012), (iv) adverts on social
network groups, specialist websites and through local patient and public
involvements initiatives. Testing took place in locations convenient to participants,
including University premises, hospitals, community mental health centres, Spiritual
churches and the participants’ homes. After providing informed consent, participants
were asked to complete the demographic and clinical history interview and the
battery of research measures. Participants were then fully debriefed, and received £7
reimbursement.
Data Analysis
Group differences were examined using bootstrap for independent sample
tests (with 1000 bootstrap samples) to test for differences between clinical and non-
clinical voice-hearers on voice characteristics and test for the hypothesized
differences on measures of goal interference and facilitation between clinical and
non-clinical voice-hearers. Non-parametric correlational analyses (Spearman’s rho)
were carried out to test whether goal interference scores were positively associated
10
with measures of distress (PSYRATS-AH distress, self-reported voice-related
distress, and DASS-21 scores), and negatively related to voice pleasantness; and
whether goal facilitation scores positively associated with voice-pleasantness but
negatively related to distress measures. Hierarchical regression analyses were
employed to examine whether goal interference/facilitation ratings significantly
predicted distress and voice pleasantness when controlling for participant group and
other characteristics of voices that might influence affective reactions to voices (i.e.
PSYRATS-AH measures of frequency/duration of voices, measures of negative
content and the amount of disruption to life functioning). All correlational analyses
were carried out both within the entire participant sample and separately within the
clinical and non-clinical groups in order to examine consistent and divergent patterns
of findings between groups. Furthermore, all regression analyses controlled for
participant grouping (by including the dichotomous predictor “group”; 0 = clinical, 1
= non-clinical) to ensure that the findings reported were unbiased by possible group-
differences (Fox, 2008). All statistical analyses were carried out using SPSS version
20.
Results
Differences Between Clinical and Non-clinical Participants
The results of group comparisons between clinical and non-clinical voice-
hearers are reported in Table 1. Clinical voice-hearers scored significantly higher on
the PSYRATS-AH measures of distress, voice frequency/duration, negative voice
content, and disruption to daily life caused by the voices. They also presented
significantly higher DASS-21 and self-reported voice-related distress scores. There
11
was a trend towards significance for the analysis of voice pleasantness, suggestive of
lower pleasantness scores amongst clinical voice-hearers. Consistent with our
hypotheses, clinical participants presented significantly higher interference scores,
and lower facilitation scores compared to non-clinical voice-hearers.
Goal Interference/Facilitation Scores Are Associated with Voice-Related
Distress and Pleasantness
Non-parametric correlational analyses (Spearman’s rho) for associations
between between goal interference/facilitation scores, distress measures (PSYRATS
distress, self-reported voice-related distress, and DASS-21 scores) and the self-
reported measures of voice pleasantness are reported in Table 2. To examine whether
these associations were consistent in both clinical and the non-clinical participants,
separate analyses were carried out within the two participant groups and the Fisher’s
procedure for comparing independent correlation coefficients (Fisher, 1921) was
used to identify any significantly difference in findings obtained from these two
subgroup analyses.
[Insert Table 2 approximately here]
Goal interference and facilitation ratings were significantly associated for the
whole sample (rs = -.72, p = .001) and within subgroup analyses (rs = -.56, p = .021
in clinical and rs = -.73, p = .001 in non-clinical participants). For the total sample,
the associations between interference scores and the distress measures (DASS-21
12
scores, PSYRATS distress, and self-reported voice-related distress ratings) were all
robust and significant. Conversely, significant inverse relationships were found
between goal facilitation and all distress measures. Analyses also revealed that
perceived pleasantness of voices was inversely related to interference ratings,
whereas a large positive association was observed between voice pleasantness and
goal facilitation scores. Subgroup analyses for the clinical and the non-clinical
groups are also displayed in Table 2. Fisher’s z test indicated that the association
between goal facilitation and voice pleasantness was significantly larger in the non-
clinical group compared to the clinical group (z = 3.60, p = .001). All remaining
analyses were non-significant (all zs < 1.96, all ps > .05), indicating that the effects
observed in the two groups were comparable in magnitude.
Two separate hierarchical multiple regression analyses were then used to test
whether goal interference and facilitation scores were significant predictors of: (i)
self-reported voice-related distress ratings when controlling for the effect of other
voice characteristics (frequency/duration, negative content and amount of disruption
to life) and the dichotomous predictor “group” (0 = clinical, 1 = non-clinical), and of
(ii) voice pleasantness when controlling for the same covariates. Interference and
facilitation ratings were included as separate predictors as their bivariate association,
although large, was not of a magnitude that may create spurious findings due to
perfect or quasi-perfect collinearity (r ≥ .80 or .90; Field 2009). For both models
there was no evidence of violations of the assumption of independence of errors
(Durbin-Watson test = 1.80 for both analyses), linearity, homoscedasticity and
normally distributed errors (examined through visual inspection of standardised
residuals). Inspection of collinearity diagnostics found no evidence of
multicollinearity amongst the predictors in the regression models (i.e. all Variance
13
Inflation Factor statistics were < 10; all Tollerance statistics were > .10; Field,
2009).
Results of regression analyses are displayed in Table 3. For voice-related
distress, with participant group and other voice-characteristic (frequency/duration,
negative content and disruption) included in the first step of the analysis, the adjusted
R2 was estimated at .85, indicating that the predictors explained 85% of the variance
in distress. In the first step of the analysis, negative voice content and disruption to
life caused by the voices significantly predicted distress. At step 2, the inclusion of
goal interference and facilitation scores significantly improved the prediction of
distress scores, explaining an additional 4% of the observed variance (R2 = .89,
significance of R2change p = .017). In the final model, goal interference, but not goal
facilitation, significantly predicted distress when controlling for the other variables
included in the model. The effects of negative content and voice disruption were also
significant, whereas frequency/duration of voices and group were not associated with
distress.
[Insert Table 3 approximately here]
A similar hierarchical regression model was estimated with voice
pleasantness as the dependent variable. After the inclusion group and other voice-
characteristic at step 1, the adjusted R2 was estimates at .39, indicating that the model
accounted for 39% of the observed variance in voice pleasantness. In the first step of
the analysis only negative voice content significantly predicted pleasantness scores.
The inclusion of goal facilitation and in reference ratings at step 2 largely improved
the prediction of pleasantness scores, and accounted for an additional 38% of the
14
observed variance (R2 = .77, significance of R2change p < .001). In the final step of
the analysis, goal facilitation was the only significant predictor of pleasantness.
Discussion
The current study examined whether affective reactions to voices (voice-
related distress and pleasantness) are linked to the extent to which hearing voices
interfere or facilitate the persons’ ability to achieve important personal goals. Our
results revealed that goal interference was significantly associated with higher
distress and lower perceived voice pleasantness, whereas goal facilitation was
significantly associated with higher pleasantness and lower voice-related distress.
Subsequent regression analyses revealed that goal interference specifically predicted
distress, whereas goal facilitation was specifically associated with perceived
pleasantness of voices. These analyses found that the extent to which voices
facilitate or hider personal goals are strongly predictive of affective reactions to
voices. Furthermore, these effects remained statistically significant event after
accounting for several covariates that might influence affective reactions to voices
(i.e. voice frequency/duration, amount and degree of negative content of voices,
amount of disruption to daily life caused by the voices, and the participants’ clinical
or non-clinical status).
The current study suggests that goals, and the extent to which individuals
experience voices as facilitating or interfering with personally meaningful goals,
may play a central role in determining whether voices are perceived as distressing or
as pleasant experiences. In contrast with previous investigations which often
15
assessed the impact of hearing voices using arbitrarily defined measures of
psychosocial and occupational functioning (e.g. Hall, 1995) or disruption to daily
life activities (Haddock et al., 1999), the present study employed a more
“idiographic” approach where the impact of voices was subjectively measured in
relation to self-generated and personally meaningful goals. This can be regarded as a
relative strength, in accordance with recommendations of employing
subjective/idiographic methods to understand the idiosyncratic nature of psychotic
experiences (e.g. Haddock et al., 2011; Pitt, Kilbride, Nothard, Welford, &
Morrison, 2007).
Our findings provide a novel perspective on processes that might contribute
to distress in people who hear voices. Within PCT, psychological distress is
experienced whenever control over personally meaningful and salient goals is
disrupted (e.g. Carey, 2006; Mansell et al., 2012; Powers, 1973, 2005). Findings of a
significant relationship between goal interference and distress are therefore in line
with the principles of PCT. Of notable interest, our results compare favourably with
previous investigations of other possible psychological determinants of distress in
voice hearing. For example, the effects on distress observed in the present
investigation were larger in terms of effect sizes than reports from previous studies
focusing on negative beliefs and appraisals of voices (e.g. Chadwick et al., 2000;
Morris, Garety, & Peters, 2014; Morrison et al., 2004; Peters et al., 2012),
maladaptive metacognitive beliefs (e.g. Brett, Johns, Peters, & McGuire, 2009; Hill
et al., 2012), insecure attachment styles (e.g. Berry, Wearden, Barrowclough,
Oakland, & Bradley, 2012; Robson & Mason, 2014) and, to a lesser extent, measures
of the perceived relationship between voice-hearers and their voices (e.g.
Birchwood, Meaden, Trower, Gilbert, & Plaistow, 2000; Vaughan & Fowler, 2004)..
16
Future studies could help to clarify the current findings by examining the possible
interrelationships between other predictors of distress (e.g. negative beliefs and
appraisals of voices) and the goal interference measures considered in the present
study, and the extent to which the constructs considered in this investigation are
independent from other predictors of voice-related distress. It is possible, for
example, that goal interference may represent a more “proximal” predictor of
distress that could mediate the observed association between the way specific voices
are appraised and subsequent distress. Conversely, a reverse association might be
also plausible, with specific positive and negative beliefs/appraisals developing as a
consequence of the perceived impact of voice hearing on personal goals.
The relationship between goal facilitation and voice pleasantness is also of
interest given the paucity of studies investigating the specific determinants of
pleasant hallucinatory experiences, and more generally, possible positive aspects of
psychotic experiences (e.g. Haddock et al., 2011). In both clinical and non-clinical
voice hearers a robust association was observed between the degree to which voices
were perceived as facilitating the ability to achieve personal goals and the extent to
which the voices were experienced as pleasant. This is consistent with previous
surveys suggesting that voices are experienced as useful and constructive events by a
substantial proportion of hearers (e.g. Jenner et al., 2008; Sanjuan et al., 2004).
Furthermore, our comparisons between clinical and non-clinical voice-hearers (in
addition to replicating well-documented differences on several voice-related
variables, e.g. distress, frequency/duration and negative content of voices; Daalman
et al., 2010; Daalman & Diederen, 2013) suggest marked differences in the extent to
which voices are perceived in relation to the ability to progress towards valued goals,
with clinical voice-hearers reporting significantly higher interference, and lower
17
levels of facilitation. The findings of our regression analyses could be interpreted as
evidence that the relative contribution of goal facilitation to pleasantness of voices is
stronger than that of goal interference on distress (the inclusion of step 2 predictors
increases the proportion of explained variance by 38% in models predicting goal
pleasantness, whereas only 4% additional variance is explained in the voice-related
distress analysis). However, it should be noted that these analyses controlled for
covariates that are particularly relevant to the prediction of distress (e.g. amount of
negative voice content assessed using the PSYRATS-AH) rather than pleasantness of
voices. The assessment of “positive” aspects of voices is neglected by the vast
majority of measures focusing on specific dimensions of voice-hearing experiences
like the PSYRATS. Future studies may consider replicating our findings by
controlling for positive voice dimensions that could complement well features of
voices assessed by the PSYRATS (for example “amount of positive voice content”).
A number of caveats should be considered when interpreting the current
findings. As with most psychological investigations relying on voluntary
participation and informed consent, the present study might be vulnerable to
selection bias. The sample consisted primarily of white, British volunteers, which
may limit the generalisability of our findings. The cross-sectional nature of our data
and the modest sample size are also caveats to consider when appraising these
findings. Future investigations considering larger samples of clinical and non-clinical
voice-hearers and/or employing alternative research designs might help to clarify the
nature of the relationships considered in the present study (e.g. experience sampling
methods to examine temporal dynamics amongst the variables considered, and/or
intervention studies considering treatment approaches specifically targeting the
extent to which voices interfere with valued goals). Although it can be argued that
18
self-report measures are unavoidable when investigating phenomena that are
exclusively accessible through introspection, it is recognised that these methods are
vulnerable to several biases (e.g. retrospective reporting, demand characteristics,
social desirability), and may lead to overinflated relationships between the constructs
considered. Several of our research measures were specifically developed to address
the research questions of this study (i.e. goal interference and facilitation ratings) or
adapted following service users consultation to increase their acceptability to the
target population (i.e. the modified Goal Task) which might benefit from further
psychometric evaluation in future studies. The results of this study should be
interpreted in the light of these limitations. Finally, the study did not include a
validated diagnostic tool to assign participants to the clinical and non-clinical groups
and only relied on participant’s self-reported diagnosis and service history. Although
this is not problematic for the symptom-specific approach employed in this instance,
the authors recognise that the lack of such instruments might have introduced bias in
the subgroup analyses reported. Future studies aiming to consider potential effects of
specific diagnoses, or investigate more precisely differences between clinical and
non-clinical voice-hearers may benefit from the use of more detailed diagnostic
assessments.
The study bears a number of clinical implications. The finding that voice-
related distress is closely associated to interference with important goals stresses the
importance of placing individual’s valued goals at the core of any psychological
intervention for distressing voices. The careful exploration of client’s goals, and the
extent to which experiences of voice hearing influence these goals, may allow for
more effective idiographic psychological formulations of clients presenting
difficulty, and the delivery of interventions that may be more acceptable to
19
individual clients. Rather than focusing on symptom reduction, interventions
focusing on promoting the client’s ability to progress towards valued life goals might
represent a meaningful treatment option for individuals with distressing voices. An
example of such approaches is Acceptance and Commitment Therapy interventions
for distressing voices (Shawyer, Thomas, Morris, & Farhall, 2013; Thomas, Morris,
Shawyer, & Farhall, 2013), which have increasingly been used with individuals with
distressing psychotic symptoms, with encouraging preliminary outcomes (Valmaggia
& Morris, 2010). Within PCT and other control theories, psychological distress is
assumed to arise whenever a person experiences loss of control over valued goals,
most commonly resulting from chronic conflict between important strivings and
goals (Carey, Mansell, Tai, & Turkington, 2014), and that long-term distress
resolution can only be achieved when information pertaining to higher-order goals is
accessed. Method of Levels therapy (MoL), a transdiagnostic cognitive therapy
based on PCT (Carey, 2006; Mansell, Carey & Tai, 2012), is a type of therapy,
which specifically aims to shift awareness to higher-level goals and perceptions to
promote long-term resolution of conflict. The application of MoL may therefore
prove beneficial to clients with distressing voices in terms of resolving the possible
distress associated with these experiences (Tai, 2009; Tai & Turkington, 2009).
20
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Table 1: Demographic and clinical characteristics
Whole sample Clinical Non-clinical Group differencep
values(N = 40) (n = 22) (n = 18)
Demographic measures
Age 38.8 (14.5) 37.8 (12.3) 39.9 (16.9) 95% CI [-12.86, 7.52] .70
Gender 17 Males 10 Males 7 Males Fisher's exact test .80
Ethnicity 35 White 19 White 16 White Fisher's exact test .94
Clinical/voice-related measures
PSYRATS-AH frequency/duration 4.5 (2.2) 5.7 (2.1) 3.0 (1.3) 95% CI [0.86, 3.52] .007
PSYRATS-AH negative content 3.7 (2.7) 5.6 (2.3) 2.1 (2.4) 95% CI [1.98, 5.31] .001
PSYRATS-AH disruption 1.0 (1.2) 1.7 (1.2) 0.2 (0.4) 95% CI [1.02, 2.16] .002
PSYRATS-AH distress 3.3 (2.7) 4.7 (2.3) 1.9 (2.4) 95% CI [1.12, 4.46] .004
self-reported distress 4.1 (3.3) 5.9 (2.6) 2.2 (2.8) 95% CI [1.79, 5.75] .001
self-reported pleasantness 4.8 (3.9) 3.6 (3.7) 6.1 (3.7) 95% CI [-5.12, 0.17] .08
DASS-21 24.6 (16.9) 31.1 (17.1) 17.7 (13.7) 95% CI [3.46, 23.97] .02
Goals measures
Facilitation scores 4.2 (3.7) 2.5 (3.1) 5.9 (3.6) 95% CI [-5.70, -0.91] .01
Interference scores 3.8 (3.3) 5.7 (2.7) 1.8 (2.7) 95% CI [1.82, 5.77] .002
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Table 2: Spearman’s rho between goal interference/facilitation scores and the distress and voice pleasantness measures
Whole sample (N = 40) Clinical (n = 22) Non-clinical (n = 18)
Facilitation Interference Facilitation Interferenc
e Facilitation Interference
DASS-21 total -.66 *** .81 *** -.60 ** .84 *** -.77 *** .71 **
PSYRATS distress -.70 *** .89 *** -.65 ** .91 *** -.47 * .79 **
Self-report distress -.71 *** .93 *** -.55 * .93 *** -.72 ** .80 ***
Self-report pleasantness .86 *** -.69 *** .69 ** -.60 ** .94 *** -.72 **
Note: * p < .05; ** p < .01; *** p < .001
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Table 3: Summary of the hierarchical regression analyses
voice-related distress analysis voice pleasantness analysis
Predictor B SE β Predictor B SE β
Step 1 Step 1
Group -1.11 .68 -.17 Group 0.75 1.65 .01
Negative content .81 .11 .72 ** Negative content -1.02 .28 -.77 ***
Disruption 1.01 .30 .39 ** Disruption .13 .72 .04
Frequency/duration .10 .12 .07 Frequency/duration .11 .29 .06
Step 2 Step 2
Group -.99 .61 -.15 Group 1.51 1.03 .20
Negative content .50 .14 .45 ** Negative content -.34 .24 -.26
Disruption .75 .29 .27 * Disruption .51 .49 .16
Frequency/duration -.06 .11 -.04 Frequency/duration .06 .19 .03
Goal facilitation -.07 .08 -.08 Goal facilitation .78 .13 .76 ***
Goal interference .34 .14 .34 * Goal interference -.19 .15 -.15
Note. * p < .05, ** p < .01, *** p < .001
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