Psychosocial well-being after stroke
education, work status, caring responsibilities, social support,
previous illnesses and rehabilitation services. Data collectors
with healthcare backgrounds (RN or OT) administered the in-
struments using a personal interview format. The assessors read
the questions to the respondent and recorded the respondent’s
answers in a web-based secure questionnaire using a tablet. At
6 months post-stroke (T2), a data collector who was blinded to
the group allocation repeated the outcome measurements. Any
changes in the patient’s living situation or health status since
the first assessment were recorded.
The term psychosocial refers to the interrelation between so-
cial factors and individual thoughts and behaviours. Well-being
generally refers to emotional reactions and subjective evalua-
tions in response to events and includes a greater prevalence of
positive than negative emotions and moods, satisfaction with
life, sense of fulfilment, and positive relationships (21, 22). The
primary outcome to evaluate psychosocial well-being was the
General Health Questionnaire-28 (GHQ-28) (23). The GHQ-
28 has been translated into Norwegian (24) and evaluated as
an appropriate tool for research purposes in studies to capture
emotional stress (25). The GHQ-28 consists of the following
4 subscales addressing aspects of psychosocial well-being:
somatic symptoms, anxiety and insomnia, social dysfunction
and severe depression (23). Higher score on the GHQ-28 in-
dicates higher distress levels. The continuous GHQ-28 score
was calculated based on a Likert scoring of 0, 1, 2, 3, resulting
in a scale of 0–84. The dichotomized GHQ-28 score was based
on a case scoring of 0, 0, 1, 1, resulting in a scale of 0–28. Ba-
sed on a comparable study (11) the cut-off was set at 5 in the
dichotomized GHQ-28 variable. Scores <5 indicated a normal
mood, and scores ≥5 indicated a low mood.
Three secondary outcomes were explored. The Yale-Brown
single-item questionnaire (Yale) measures the individual’s pre-
sence or absence of depression (26). The Stroke and Aphasia
Quality of Life Scale-39 (SAQOL-39g) addresses dimensions
of stroke-specific health-related quality of life and is adjusted
for people with aphasia (27). SAQOL-39g items are scored on
a scale from 1 to 5, and mean scores are calculated for each
dimension and for the total sum score. Higher scores indicate a
higher quality of life. The SOC-13 measures the main concepts
of SOC theory (16). In this study, the SOC-13 items were sco-
red on a scale from 1 to 5. The total sum score was calculated
after reversing the scores of the reversely formulated items,
resulting in a scale from 13–65. Higher scores indicate higher
levels of comprehensibility, manageability, and experiences of
meaningfulness in life.
The fatigue questionnaire (FQ-2), Lee’s fatigue scale (LFS-5)
(28) and the Ullevaal Aphasia Screening test (UAS) (29) were
included to describe the sample.
Sample size calculations
Sample size was determined based on the primary outcome
measurement. With the power set at 80% and the significance
level (α) at 0.05, the estimated sample size was 300 patients
(150 per group). The calculations were based on a repeated
measures logistic regression model of the output variable
“normal mood” (GHQ-28). In this study, the power of finding
a statistically significant difference between groups was 80%
for an OR of 1.9 or higher.
Randomization and blinding
A computer-generated block randomization procedure was used
to allocate the patients into either the intervention or control arm.
559
Participants were randomly assigned in blocks of 10, stratified by
the recruiting centre with an allocation ratio of 5:5. An assistant
independent of the research group prepared opaque randomization
envelopes with 5-digit patient identification numbers printed on
the outside and a note specifying intervention or control on the
inside. Two regional study coordinators performed the randomiza-
tion. Group allocations were communicated solely to the patient
and the IP delivering the intervention. To maintain blinding during
follow-up, a text message was sent from the study coordinator
to the participants before the data collector contacted them with
a reminder not to reveal their group allocation.
Statistical methods
The data were analysed using the Statistical Package for the
Social Sciences (SPSS), version 25.0, for Windows (IBM Corp.,
Armonk, NY, USA) . All statistical tests were intention-to-treat
analyses performed as 2-sided tests with a significance level of
a=0.05. Missing data were imputed using multiple imputation
by chained equations (MICE) in SPSS (30), and all reported
results from the statistical analyses were combined results across
5 imputations based on Rubin’s rule (31).
A logistic regression with time points (T1 vs T2) as the single
independent variable was used to assess the odds of a normal
mood (GHQ-28<5) and not having depression (Yale) from T1 to
T2 separately per treatment group. The changes in mean scores
on the SAQOL-39g and SOC-13 from T1 to T2 were examined
for each treatment group using paired-sample t-tests.
Logistic regression analyses were used to analyse the effects
of the intervention on mood (GHQ-28) and depression (Yale)
at 6 months. Multiple linear regression analysis was applied to
determine whether participating in the intervention was statisti-
cally significantly associated with the participants’ scores on the
SAQOL-39g. Based on conceptual and theoretical assumptions,
the following baseline characteristics were controlled for in the
regression models in each analysis: group allocation, sex, age at
admission, rehabilitation services at baseline, care responsibility,
living arrangements, comorbidity, stroke severity (NIHSS),
stroke aetiology, stroke symptom localization, depression,
fatigue and SOC (SOC-13). The baseline value of the outcome
measurement analysed was also added as a covariate because
the results of the by-group analyses showed significant changes
between time points. A variable of recruitment centre was in
addition included in the logistic regression analysis of GHQ-28
to control for a potential effect of recruitment centre.
The SAQOL-39g was analysed for both the original and log-
transformed (2**) variables because of the non-normal distribu-
tion of the data. The results were compared, and no significant
differences were found. To simplify interpreting the results, only
outcomes from the original data analysis are presented herein.
Independent-samples t-tests were used to test for statistically
significant differences in the mean scores on the SOC-13 bet-
ween the intervention and control groups.
Ethics
The ethical approval of the study was provided by the Regional
Committee for Ethics in Medical Research (REC) (2013/2047)
and the Data Protection Authorities (2014/1026). The study fol-
lowed the guidelines of the Declaration of Helsinki.
When invited to participate, eligible participants received oral
and written information about the study from trained clinical
staff who also obtained informed consent.
If patients showed signs of severe emotional distress during
the interviews or intervention, the interviewer/intervention
J Rehabil Med 51, 2019