Quality of life, recovery and decision-making: a mixed methods study of mental health recovery in social care

Abstract

Purpose
Mental health care is a complex system that includes social care organisations providing support for people with continuing needs. The relationship over time between decisional conflict, social support, quality of life and recovery outcomes across two time periods for people experiencing mental health problems in receipt of social care was investigated.

Methods
This is a mixed methods study comprised of a quantitative survey at two time points using measures of decisional conflict, social support, recovery and quality of life in a random sample (n = 122) using social care services in Wales, UK. In addition, 16 qualitative case studies were developed from data collected from individuals, a supportive other and a care worker (n = 41) to investigate trajectories of care. Survey responses were statistically analysed using SPSS and case study data were thematically analysed.

Results
Participants reported increasing decisional conflict and decreasing social support, recovery and quality of life over the two time points. Linear regression indicated that higher recovery scores predict better quality of life ratings and as ratings for social support decline this is associated with lower quality of life. Correlational analysis indicated that lower decisional conflict is associated with higher quality of life. Thematic analysis indicated that ‘connectedness and recovery’ is a product of ‘navigating the system of care’ and the experience of ‘choice and involvement’ achieved by individuals seeking help.

Conclusions
These results indicate that quality of life for people experiencing mental health difficulties is positively associated with social support and recovery and negatively associated with decisional delay.

Full text

Vol.:(0123456789)
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Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
https://doi.org/10.1007/s00127-018-1635-6
ORIGINAL PAPER
Quality oflife, recovery anddecision-making: amixed methods study
ofmental health recovery insocial care
MichaelCoey1 · BenHannigan2· AlanMeudell3· MariJones4· JulianHunt1· DebFitzsimmons4
Received: 26 March 2018 / Accepted: 17 November 2018 / Published online: 23 November 2018
© The Author(s) 2018
Abstract
Purpose Mental health care is a complex system that includes social care organisations providing support for people with
continuing needs. The relationship over time between decisional conflict, social support, quality of life and recovery out-
comes across two time periods for people experiencing mental health problems in receipt of social care was investigated.
Methods This is a mixed methods study comprised of a quantitative survey at two time points using measures of decisional
conflict, social support, recovery and quality of life in a random sample (n = 122) using social care services in Wales, UK.
In addition, 16 qualitative case studies were developed from data collected from individuals, a supportive other and a care
worker (n = 41) to investigate trajectories of care. Survey responses were statistically analysed using SPSS and case study
data were thematically analysed.
Results Participants reported increasing decisional conflict and decreasing social support, recovery and quality of life over
the two time points. Linear regression indicated that higher recovery scores predict better quality of life ratings and as ratings
for social support decline this is associated with lower quality of life. Correlational analysis indicated that lower decisional
conflict is associated with higher quality of life. Thematic analysis indicated that ‘connectedness and recovery’ is a product
of ‘navigating the system of care’ and the experience of ‘choice and involvement’ achieved by individuals seeking help.
Conclusions These results indicate that quality of life for people experiencing mental health difficulties is positively associ-
ated with social support and recovery and negatively associated with decisional delay.
Keywords Mental health care· Shared decision-making· Quality of life· Mixed methods· Recovery
Introduction
The move from institutionalised mental health care has seen
the advent of community-based provision in modern socie-
ties [1]. However, the relationship between key factors such
as social support, involvement in decisions, recovery and
quality of life (QoL) has received limited attention. Recov-
ery is defined as “regaining mental health to the maximum
extent possible and achieving the best possible quality of
life, lived as independently as possible” [2]. While there
appears to be overlap between the concepts of recovery
and quality of life, the direction of the relationship is not
clearly established [3]. Enhancing social support from mul-
tiple sources (family, peers and community) may influence
recovery and is a potential target for intervention [4]. Shared
decision-making (SDM) as one means to achieve consensus
on treatment goals [5] involves collaborative efforts to aid
recovery and may reduce patient distress, improve func-
tional status, improve satisfaction with services and achieve
Michael Coffey, Ben Hannigan and Alan Meudell contributed
equally to this work.
Mari Jones and Deb Fitzsimmons contributed quantitative analysis
expertise to this work.
Julian Hunt contributed to data collection.
* Michael Coffey
m.j.coffey@swansea.ac.uk
1 Department ofPublic Health, Policy andSocial Sciences,
Swansea University, Wales, UK
2 Cardiff University, Wales, UK
3 Caerphilly Mind, Wales, UK
4 Swansea Centre forHealth Economics, Swansea University,
Wales, UK
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716 Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
1 3
a greater sense of control [6]. Systematic review evidence
indicates that control over aspects of one’s life and building
social connectedness are important in recovery [7]. How-
ever, collaborative and shared involvement in care is incon-
sistent with many service users uncertain about aspects of
their care [8] and reporting high levels of decisional conflict
[9]. Decisional conflict refers to uncertainty in a course of
action such as making decisions related to one’s care and is a
potential measure of readiness for, or alternatively delaying,
involvement in shared decision-making [10].
To address the knowledge gaps identified above, a mixed
methods study of recovery, quality of life, social support
and shared decision-making was conducted with a popula-
tion of people using social care mental health services in
Wales. The central premise of mixed methods is that the
combination of approaches provides a better understand-
ing of research problems than either method alone [11]. For
the quantitative part of this study, it was hypothesised that
involvement in decisions will lead over time to improved
QoL and recovery outcomes for people with mental health
problems. It was further hypothesised that there would be
a positive association between recovery, involvement, size
and depth of social networks and QoL. For the qualitative
part of the study, participant accounts were examined for
experiences of uncertainty in making decisions about care
and access to social support, recovery and quality of life to
develop a richer account of these experiences.
Design andmethods
The project protocol has been previously published [12]. A
mixed methods study was conducted using a random sam-
ple of people using social care mental health services in
Wales, which consists of a survey using standardised meas-
ures over two time points with additional qualitative case
study interviews. The aim was to provide a rich account of
contemporary recovery-focused social care via an integrated
exploratory analysis [11, 13]. Ethics approval for this study
was received from West of Scotland Research Ethics Service
on 18th March 2014 (REC ref: 14/WS/0063).
The study was conducted at a time of financial upheaval
and sustained reductions in the provision of mental health
care due to austerity [14]. The setting was a national chari-
table provider of a range of local recovery-focused daytime
social activities including drop-in groups, gardening groups,
one-to-one support and activities such as art classes. People
attending activities had prior or continuing experience of
secondary mental health care for a range of enduring condi-
tions and required opportunities to develop new skills and
establish or maintain social contacts. Activities occurred in
urban and rural settings across Wales.
A random sample of people using these services was
drawn from existing anonymised databases of the charitable
organisation for the survey. Random selection of survey par-
ticipants was conducted by administrative staff at the char-
ity. Staff were instructed to select every fourth entry on the
database for inclusion in the survey; therefore, the research
team had no details of potential participants thus achiev-
ing allocation concealment [15]. This simple randomisation
approach complied with the requirements of the charity and
meant that the team was blinded to the sampling procedure.
A potential bias is that individuals in any particular region
of Wales could have been proportionately under- or over-
sampled without the study team’s knowledge.
Potential participants were sent a booklet containing
the participant information sheet, four standardised survey
measures detailed below and information on how to com-
plete each. Consent was sought from participants for the
research team to access National Health Service (NHS) case
records for the purposes of completing a measure of case
complexity. Permissions and access to these records were
negotiated with NHS organisations. Researchers trained in
using the measure read patient records to complete scores
for case complexity.
Case study participants were purposively sampled from
attendees at social care projects. Our aim was to select a
sample representing the range of people engaged in recov-
ery from mental health problems. Our inclusion criteria
were adults of working age, who have been in receipt of
mental health care, including recent (< 2years) and more
established contact (> 2years). Receipt of mental health
included any primary, secondary, tertiary and/or social
mental health services. Exclusion criteria included people
identified by staff as being in current crisis and those who
were in hospital.
Data collection
Data were collected in two overlapping stages which con-
sist of a survey using standardised measures followed by a
case study stage involving interviews with service users, a
significant other and a nominated project worker. Data from
case notes were collected following consent from survey
participants.
A survey questionnaire pack was sent to participants at
entry to the study (time point 1) and where possible, com-
pleted again 6–8months (time point 2) later by telephone.
This consisted of an information sheet on the study and the
following measures:
1. Lubben Social Network Scale (LSNS) [16]—a 12-item
scale measuring size, closeness and frequency of contact
with friends, family and neighbours.
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717Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
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2. Decision Conflict Scale [10]—a 16-item measure assess-
ing the decision-maker’s uncertainty in making a choice,
modifiable factors contributing to uncertainty (lack of
information, unclear values, and inadequate social sup-
port) and perceived effective decision-making.
3. The Process of Recovery Questionnaire (QPR) [17]—a
22-item scale which measures both intrapersonal and
interpersonal tasks involved in recovery.
4. Manchester Short Assessment of Quality of Life Scale
(Mansa) [18]—a brief operational measure of QoL
across eight domains.
The Matching Resources to Care (MARC2) scale was
used to measure complexity of needs. This is a multi-
dimensional measure of mental health problems incor-
porating social situation, illness severity, risk and social
exclusion components [19] completed using data collected
from patient records by trained researchers. MARC2 scores
helped to describe complexity so that results could be inter-
preted more broadly in relation to sample similarity (or oth-
erwise) with other studies.
Participation in case studies involved individual qualita-
tive one-to-one audio-recorded interviews with the person,
their worker and significant others nominated by the per-
son. Utilising data from up to three participants per case
study, this aimed to build as complete a picture as possible
based upon a multiple-perspective approach [20] by exam-
ining differing accounts of recovery. Interview schedules
were designed in relation to issues identified in the relevant
literature and precise wording and sequence of questions
were agreed in consultation with a Lived Experience Advi-
sory Panel (described below). Interview schedules (see sup-
plementary file) covered experiences of involvement, social
networks and recovery so that they matched the focus of
the standardised measures; for example, ‘Can you tell me
about times when you feel professionals have successfully
involved you in discussions about your care?’ The interview
schedules were similar for all participant groups with minor
word changes to recognise individual roles, e.g. staff or fam-
ily member.
Public andpatient involvement andstudy oversight
This study was supported by two advisory panels. The main
project advisory panel included colleagues from voluntary
sector organisations, service users, and academic staff [21].
Its role was to provide advice and to act as a critical friend
to support the project team. The second panel consisted of
a five-member Lived Experience Advisory Panel (LEAP)
recruited through the Involving People network. This pro-
vided advice related to question formulation, wording,
sequencing, participant recruitment and user-related issues
such as concerns about welfare. The project team included
a mental health service user researcher (AM) who con-
tributed to the study design, data collection, analysis and
dissemination.
Data analysis
Each measure was scored using published guidelines. Quan-
titative data from the standardised measures were entered
into SPSS v22. For the cross-sectional analysis of time point
1 and 2 data (6–8months follow-up), descriptive and infer-
ential statistics were produced, using parametric or non-par-
ametric techniques (as appropriate, dependent on the nature
and distribution of the data) to describe changes in primary
and secondary outcomes at each time point. The null hypoth-
esis at p values less than 0.05 was rejected.
A linear regression was conducted to investigate the rela-
tionship between quality of life as measured by the Mansa
questionnaire and the other ‘Total’ score variables (i.e. QPR,
DCS and Lubben) at both time points (1 and 2), and the
overall change between the two points. The Mansa Overall
score was set as the dependent variable, with the other scores
set as potential predictors.
Research interviews were transcribed verbatim with all
identifiers removed. Data were managed and analysed with
the aid of the software package, NVivo v10. Inductive and
deductive codes were created and used to identify and link
segments of data and to generate themes [22, 23]. Both
within-case (i.e. single trajectory) and across-case analyses
[24] were conducted to describe experiences of recovery in
rich detail.
Results
A random sample of 900 people were sent survey booklets
with n = 122 agreeing to participate, giving a response rate
of 13%. The follow-up phase involved a sample of n = 50.
Case records for n = 73 participants were identified for the
purpose of completing the case complexity measure.
Case study recruitment achieved a sample of n = 16 peo-
ple using services plus n = 11 significant others and n = 14
nominated workers giving a total case study sample of
n = 41. One potential participant did not keep appointments
on two occasions and was deemed to have withdrawn from
the study.
More men (n = 66, range 20–66years, mean 42.6years
sd = 12.5) than women (n = 55, range 20–76years, mean
46.8years sd = 13.9) participated in the survey. No statistical
differences between male and female participants were found
in an independent samples t test (or a Mann–Whitney test
in the case of the non-parametric general MANSA score).
Case complexity [19] (Table1) data indicated that concerns
about risk were prominently reported in written records and
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718 Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
1 3
that needs for medication monitoring and living alone con-
tributed towards severity scores.
Standardised measures
Descriptive results for decisional conflict on DCS total scale
are reported in Table2 for both time points. Decisional con-
flict centred on medication and therapy for more than half
the sample, fewer conflicts related to social issues such as
housing. The DCS threshold for decisional delay is a score
of 37.5 or higher. At time point 1, 26.3% of the sample had
scores below the threshold on the DCS and 37.9% had scores
above the threshold indicating decisional delay. However, at
time point 2, 6.3% of the sample had below threshold scores
on the DCS and 62.5% had above threshold scores indicating
they were experiencing decisional delay.
Distributional analysis indicates that only the total score
variable was normally distributed (for the first time point,
the Kolmogorov–Smirnov test has a p value of 0.053, for the
second time point p > 0.2). Therefore, the matched-pair t test
was conducted for the total score, and the Wilcoxon signed
rank test for the other subscores (uncertainty, informed,
clarity, support and effective). The total score, and each of
the subscores increased significantly over time (all p val-
ues < = 0.001). The increase in scores for decisional conflict
on the DCS indicates that participants experienced more
decisional delay over time indicating difficulty in engaging
in shared decision-making.
A score of 24 or less on the LSNS-R indicates isolation
from social support. Social support scores on the LSNS-R
suggest that participants were not socially isolated (> 24) (see
Table2). However, 34% (n = 35) completing the measure at
time point 1 were at or below the threshold for social isola-
tion indicating some heterogeneity. The survey at time point
2 found that 42% (n = 21) were below the threshold for social
isolation. Distributional analysis indicates that both the total
and family subscores on the Lubben Social Network Scale
are normally distributed for the first and second time points
(p > 0.2 for all). The friend subscore is not normally distributed
Table 1 Main severity scores on MARC2 for n = 73 of 122 partici-
pants
MARC2_severity_score (n = 73) Mean Std. dev
Lives alone 0.34 0.48
Past or present risk of self-neglect 0.53 0.50
Past or present serious suicidal risk 0.66 0.48
Needs medication monitoring 0.34 0.48
Previous compulsory admissions 0.32 0.47
Past or present risk of violence to family 0.18 0.39
Past or present risk of violence to others 0.36 0.48
Overall severity score 0.22 0.15
Table 2 Scores for standardised measures at time points 1 and 2
DCS1
total
DCS2
total
Lub-
ben
score
1
Lub-
ben
score
2
Fam-
ily
score
1
Fam-
ily
score
2
Friendship
score 1
Friend-
ship
score 2
QPR score 1 QPR score 2 Overall
MANSA 1
Overall
MANSA
2
General QOL
MANSA 1
General
QOL
MANSA 2
Mean 30.31 41.07 30.87 27.76 14.93 13.5 15.93 14.26 51.26 42.24 4.42 4.12 4.14 3.74
Median 29.69 39.06 30.00 28.00 15 14.5 17.50 16.00 53 43 4.53 4.19 4 4
St dev 18.28 14.96 10.93 10.98 7.37 7.28 6.57 6.46 17.23 14.27 0.97 0.94 1.51 1.42
Min 0 15.63 10 0 0 0 0 0 11 11 2.88 2.69 1 11
Max 81.25 82.81 50 46 28 25 27 23 88 69 6.63 6 7 6
IQR 18.75 23.44 15 17 10 11.25 9 9 21 22.5 1.48 1.61 1.63 2.13
P value P < 0.001 P = 0.002 P = 0.019 P < 0.001 P < 0.001 P < 0.001 P = 0.002
Test Matched-pair
t test
Matched-pair
t test
Matched-pair
t test
Wilcoxon signed rank
test
Matched-pair t test Matched-pair t test Wilcoxon signed rank test
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719Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
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at the second time point (p = 0.012). Therefore, the matched-
pair t test was conducted for the total score and the family sub-
score, and the Wilcoxon signed rank test was completed for the
friend subscore. The total, family subscore and friend subscore
are all significant at the 95% level (p = 0.002, p = 0.019 and
p < 0.001, respectively) indicating that there was a significant
decrease in LSNS-R score over time suggesting that individu-
als became more isolated.
Although there are no threshold points on the QPR, it was
noted that scores for mental health recovery indicated 29.1%
(n = 30) of the sample scored lower than the midway point
(< = 44) at time point 1 suggesting recoveries that are yet to
establish. At time point 2, 59.1% (n = 26) scored lower than
the midway point on the QPR scale. Distributional analysis
(Table2) identified that the total QPR score is normally dis-
tributed. The matched-pair t test (for total score) indicated that
there was a significant decrease in these scores as time pro-
gressed demonstrating diminished recovery.
What are themain factors thataffect initial quality
oflife?
The assumptions of linear regression were satisfied with the
dependent variable initial overall quality of life (MANSA over-
all one) and the independent variables total score variables, age
and gender. A stepwise linear regression model that maximises
R2 was generated and the final model is shown below. Regres-
sion analysis was undertaken on the raw scoring variables and
the standardised variables to be able to quantify the relative
impact of each of the scoring variables.
Raw scores
The regression model tested is significant (p < 0.001) and,
therefore, closer inspection of each individual independent
variable was completed. Using the stepwise method, the vari-
ables are included which maximises R2 (a measure of fit of
the model) and gives the best model when all independent
variables are treated equally. The final model generated in the
linear regression is
This model produces an R2 value of 0.409 implying that
40.9% of the variation in the original data is accounted for by
the model. This means that for a unit increase in QPR score,
if all other variables are kept the same, MANSA 1 would
increase by 0.028.
Standardised scores
Variables on quality of life using the above coefficients cannot
be compared for impact since they are measured on different
MANSA 1
=
1.81
+
0.028
∗
TOTAL QPR SCORE
+
0.038
∗TOTAL LUBBEN SCORE
.
scales. It was necessary to rerun the regression on standard-
ised variables and then compare each of the coefficients.
The model now becomes
This analysis indicates that mental health recovery (QPR
score) has a bigger impact on the quality of life (MANSA
score) than social support (Lubben score). Finally, by cor-
relating quality of life (overall MANSA score) and the total
scoring variables (Pearson correlation coefficients are quoted
as these variables are normally distributed) all the correla-
tion coefficients show a moderate association between the
variables and quality of life (Table3). The DCS score is
negatively associated with quality of life whereas the other
variables are positively associated with quality of life. This
means that if DCS scores were high and results indicate
increased decisional conflict, QoL scores would be expected
to be lower.
Case study analysis
Anonymised details of case study participants are provided
in Table4. Analysis of qualitative data generated three broad
themes which were ‘navigating the systems of care’, ‘choices
and involvement’ and ‘connectedness and recovery’.
Theme 1: navigating thesystem ofcare
A mental health system has been defined as all the activi-
ties whose primary purpose is to promote, restore or main-
tain mental health [25]. For the person needing to use it,
this system can present itself as an exquisitely complex
MANSA overall =4.393 +0.457 ∗QPR score (standardised)
+
0.403
∗LUBBENscore(standardised)
.
Table 3 Pearson correlation coefficient for quality of life (MANSA
score) against total scoring variables
MANSA score
(quality of life)
Total DCS score
Pearson correlation −0.459
p value P < 0.000
N79
Total Lubben score
Pearson correlation 0.485
p value P < 0.000
N84
Total QPR score
Pearson correlation 0.526
p value P < 0.000
N86
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720 Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
1 3
one. Having input in how services are delivered and deci-
sions about one’s own care is crucial and offers a form of
reciprocity and a sense of epistemic justice [26].
For service users, medication was one area of conten-
tion. Decisions relating to medication were reported as
imposed rather than reached by mutual agreement. For
example, Sadie said,
“They’ve changed it quite a lot in the last 6months
and none of it has worked, and I’ve said to them, I
don’t want that medication, so I’ve stopped taking it.
Then I get told off for stopping taking it. Then I’m
like, but it was making me worse. It was making me
snappy, or horrible, and I’m not that person.” [Ser-
vice user, Case study 15].
Sadie positioned herself as attempting to resist the use
of medications which were unhelpful but felt scolded for
taking an autonomous decision. Treatment led changes to
personal identity, therefore, made it critical to have her
voice heard. Involvement in decisions can provide the
opportunity to help people engage, recover and find their
way through the system of care.
Participants told us of substantial variance in care and
treatment planning. Workers from social care services
reported that service users were often unsure if they had a
care plan and in some cases were wary of discussing these
with healthcare professionals.
Lisa, a care worker for a mental health charity, said,
“You ask any service-user, have you got a care and
treatment plan? First of all, they look at you and they
will think, I’m not sure. Then, when you give them a
bit more information, they might say, Yes, he asked
me to sign that. That is not always the fault of the
CPN [Community Psychiatric Nurse]. Quite often,
service-users don’t want to.” [Worker, Case study 6].
When people were engaged in co-producing their care
plan, a feeling of being involved and having ownership
was reported. Navigating and accessing the system of care,
however, remained difficult. For example, Abigail, who is
Dave’s daughter, talked about variance in cover arrange-
ments at their local general practice, making referral back
to a psychiatrist problematic,
“….That’s another thing that puts my dad off. The
locum can’t refer to the psychiatrist.” [Family mem-
ber, Case study 1].
Navigating the system of care was a task made more
complex as provision diversified and became less consistent.
Theme 2: choices andinvolvement incare
An integral element of meaningful choice is access to qual-
ity information on which to base decisions. Participants
provided examples of lack of choice, of decisions imposed
or care plans drafted with little input from the person
themselves.
Table 4 Anonymised details of case study participants
Key: no key worker or relative identified is signalled by inclusion of the symbol –
Case study
number
Service user Living situation Significant other Case worker
1Dave Semi-rural, independent with wife Abigail (daughter) Sonia (project worker)
2 Derek Urban, independent with family – Beverly (project worker and nurse)
3 Ellen Semi-rural, independent alone – –
4 Frank Urban, independent with wife Vanessa (wife) Bruce (project worker)
5 Gwen Urban, supported housing alone Cameron (housing support worker) Daphne (social worker)
6 Joe Semi-rural, independent alone Tony (launderette owner) Lisa (project worker)
7 Lillian Urban, independent with partner – Chloe (project worker)
8 Melvin Urban, supported housing with partner – –
9 Nicola Semi-rural, independent with child Rita (grandmother) Sally (CPN)
10 Nina Rural, independent with family Jeremy (husband) Paula (CPN)
11 Norma
Douglas
(husband)
Urban, independent with family Marilyn (friend) Jane (project worker)
12 Patrick Urban, independent alone Mary (mother) Nicholas (project worker)
13 Pete Urban, supported housing alone Daniel (housing support worker) Ralph (CPN)
14 Rohan Urban, independent with parents Lorna (mother) Penny (project worker)
15 Sadie Rural, independent with child – Samantha (advocacy worker)
16 Tommy Rural, independent with parents Lynne (mother) Rachel (project worker)
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721Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
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Interviewer: With the care plan, do you feel you had
more of a say in some things than other things?
Tommy: I’ll tell you what, I think, no, because the care
plan was very restrictive. I accept that I wasn’t allowed
to drink, fair enough, or allowed to use illegal drugs,
again, which I didn’t do. I wanted to go on holiday, they
were against that. Anything that I wanted to do was
stretched out and became difficult to do and it became
more of a burden. So what things I wanted to do were
less listened to and so forth, but with them their ideas
were what we do. [Service user, Case study 16].
Tommy appeared to accept that services would be
paternal at times and this was for his longer term benefit.
There was evidence that service users and family members
accepted the need for services to step in and take control
when needed. However, a more common experience was
professionals neglecting to relinquish control over relatively
mundane elements of the person’s life.
Participating in decisions and having those decisions
respected enables a semblance of control over one’s life.
Getting involved in decisions was not a straightforward pro-
cess as Derek intimated in the data extract below.
“As a service user—well, sometimes you’re too scared
to say anything, which makes it harder to know. If they
gave you a leaflet to say what they were actually going
to do, if they gave you like a forward planning chart, to
say, “On this date we’re going to try and do this with
you,” then I’d have a better understanding. … So then
I’d know, I’d be prepared.” [Service user, Case study 2].
For many participants their experience of involvement in
decisions was inconsistent and dependent largely upon indi-
vidual mental health workers. Derek noted that this created
uncertainty and wariness about contributing.
Theme 3: connectedness andrecovery
Recovery was described as individual, achieved by the per-
son but contextualised in relation to wider society. Differ-
ent sources of social support in recovery were revealed. For
example, one participant mentioned art classes for women
only with each woman assigned a mentor. Participants drew
contrasts with others who were constructed as less able to
assert their wishes. The availability of social support was
proposed by one family member, Lynne, herself a mental
health service user, as a potential advocate for achieving
preferred outcomes.
I fear for the people who have no family. Who have no
support because I know, how can I say? They’ve got
nobody who can stick up for them. [Family member,
Case study 16].
Close family members were often the first to identify
signs associated with deterioration and the onset of a crisis.
They initiated contact with services and took on the role of
supporter for the individual and their rights. It was often
family and friends who identified and articulated progress
too, thus motivating the person. Frank noted:
You don’t notice your recovery, until someone else
tells you ... To think, I couldn’t do that last week or six
months ago but I can now. I know that recovery is a
long, drawn out process. It’s not an overnight thing. It
doesn’t recover one specific problem at a time, it’s dif-
ferent things. Different amount of time but something
is happening. Slowly or whatever. But it’s my family
and friends. They’ll tell me more about it than myself.
[Service user, Case study 4].
Frank spoke of family and friends serving an impor-
tant function as an external source of reference for making
judgements about progress. This contribution implicates
prior knowledge of the individual before they were unwell.
Shared long-term relationships may lead to more complex
understandings of the identity performances of the person.
Participants also report that relationships with professionals
were highly valued where workers showed empathy, respect,
trust and positioned the individual as a person beyond the ill-
ness. The willingness of professionals to engage the person
in their own care appeared to create an atmosphere of trust
and the opportunity for sharing decisions.
Discussion
This study assessed the relationship between social support,
decisional conflict, recovery and quality of life in a mixed
but reducing economy of provision. Accomplishing recovery
in a system that is complex and organisationally fragmented
is a significant challenge.
Survey data indicated that participants were reluctant to
engage in decisions about their care and that this decisional
conflict increased over time. These results suggest a concern
about influence in decisions on treatment. It has been previ-
ously reported that forms of leverage are brought to bear in
consultations between people using services and those pro-
viding them [27]. The results indicate that decisional delay
is experienced by individuals meaning they were unable to
participate in shared decision-making. Correlational analy-
sis indicated that increased decisional conflict was signifi-
cantly associated with lower quality of life scores. In half of
these responses, the decision under question was related to
medical treatment and diagnosis. Qualitative case study data
indicated participants were positive about being involved in
decisions. Conversely participants also provided examples
related to their medical care where choice was limited, and
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722 Social Psychiatry and Psychiatric Epidemiology (2019) 54:715–723
1 3
decisions pressured or prescribed. Shared decision-making
was mixed and consistent with findings elsewhere [9].
Case study data suggested that the role of familial rela-
tionships in supporting and establishing external social con-
nections was important to some but for others, family was
positioned as a source of their troubles. Connectedness was
also an attribute associated with relationships with workers,
though not in every circumstance. Stability in service provi-
sion appeared to be an important criterion for the achieve-
ment of recovery outcomes. Qualitative case study data sug-
gesting participants unable to nominate a significant other
converged with results from the quantitative measures on
social support which found 35% of participants at or below
the threshold for social isolation. These individuals appear
reliant upon small networks and data indicating that social
support was worsening over time are perhaps an indication
of the delicate nature of this support. The results suggest a
need for interventions to widen social participation to (re)
build social capital [4].
Recovery for individuals in the study was an inconsist-
ent experience with advances and retreats along the road
towards this destination. Where recovery was scored highly
there was a positive relationship with higher quality of life
scores. The case studies revealed that recovery required
real involvement in decisions on care and treatment and
more directly in decisions about medication. Recovery and
quality of life scores in the population studied were lower
than reference studies [17, 28–30] suggesting this group
had complex needs. These results, nevertheless, indicate
new evidence that quality of life for people experiencing
mental health difficulties is positively associated with social
support and recovery and negatively associated with deci-
sional delay.
The study reported here indicates the benefit of examin-
ing real-world experiences of recovery and quality of life.
Individuals participating in this study were everyday users
of mental health services and as such are similar to usual
clinical populations. The combining of methods allowed
experiences of attempting to achieve mental health recov-
ery using standardised measures to be displayed alongside
rich qualitative data.
Limitations in this study include that, to comply with
local requirements, no direct access to the sampling frame
was allowed. It is possible, therefore, that some under- or
over-sampling of participants from specific regions of Wales
occurred limiting claims of representativeness of this sam-
ple. Difficulties were encountered in locating National
Health Service records for all participants and in some cases
this information was incomplete. This means that the case
complexity data should be considered with caution. Finally,
follow-up of all participants was limited by incomplete or
absent contact details; therefore, time point 2 data were
recorded for less than half the original sample.
Conclusions
The results indicate that better recovery scores predict better
quality of life. However, participants achieved lower scores
than found in other studies and the data indicated that this
was a group with complex needs. One explanation for lower
recovery and quality of life scores is that this study meas-
ured recovery, social support, decisional delay and quality
of life in naturally occurring settings which consist of mixed
mental health service provision. As such, the findings may
represent a baseline assessment of the experience of peo-
ple navigating complex service provision, while living with
difficult and persistent effects of mental ill health. The con-
clusion drawn is that mental health services appear largely
resistive to shared decision-making and this may, therefore,
limit opportunities to improve recovery and quality of life.
The current mix of statutory and charitable provision is not
achieving improved recovery outcomes and targeted service
improvements that fully engage individuals and their com-
munities in developing solutions is needed.
Acknowledgements The authors thank Ioan Humphreys and Angela
Farr at SCHE for work on early analysis not used in this paper. Thanks
are due to Peter Martin, Christine Wilson and colleagues at Hafal for
facilitating access for data collection.
Funding This study was funded by the National Institute for Social
Care and Health Research (NISCHR) in Wales (now known as Health
and Care Research Wales) grant number SC-12-03.
Compliance with ethical standards
Conflict of interest On behalf of all authors, the corresponding author
states that there is no conflict of interest.
Ethics statement This study has been approved by the appropriate
ethics committee (West of Scotland Research Ethics Service on 18th
March 2014 REC ref: 14/WS/0063) and has, therefore, been performed
in accordance with the ethical standards laid down in the 1964 Declara-
tion of Helsinki and its later amendments.
Open Access This article is distributed under the terms of the Crea-
tive Commons Attribution 4.0 International License (http://creat iveco
mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribu-
tion, and reproduction in any medium, provided you give appropriate
credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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