Psychological Associations of Poststroke Fatigue
A Systematic Review and Meta-Analysis
Simiao Wu, MSc; Amanda Barugh, MRCP; Malcolm Macleod, FRCP; Gillian Mead, FRCP
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Background and Purpose—Fatigue is common after stroke but has no effective treatments. Psychological interventions
improve fatigue in other conditions by targeting psychological factors such as mood. If psychological factors correlate
with fatigue in stroke, this would justify the development of similar interventions for poststroke fatigue (PSF). We used
systematic review and meta-analysis to determine psychological associations of PSF.
Methods—We systematically searched for studies that reported psychological associations of PSF. We used odds ratios
(ORs) to estimate the strength of associations and random-effects modeling to calculate summary estimates of ORs.
We used stratified meta-analysis to investigate the impact of study design and conducted sensitivity analyses limited to
studies that excluded patients with clinical depression and to studies that used depression scales without fatigue items.
Results—Thirty-five studies (n=9268) reported the association between PSF and ≥1 psychological factor. For PSF and
depressive symptoms, we identified 19 studies (n=6712; pooled OR=4.14; 95% confidence interval, 2.73–6.27); this
association existed in patients without clinical depression (pooled OR=1.39; 95% confidence interval, 1.27–1.53) and in
studies using depression scales without fatigue items (pooled OR=5.41; 95% confidence interval, 1.54–18.93). For PSF
and anxiety, we identified 4 studies (n=3884; pooled OR=2.34; 95% confidence interval, 0.98–5.58). Two studies (n=123)
found an association with poor coping styles and 1 study (n=167) with loss of control. Six studies (n=1978) reported other
emotional or behavioral associations.
Conclusions—PSF is associated with depressive symptoms, anxiety, poor coping, loss of control, emotional, and behavioral
symptoms. These factors are potential targets for treatment of PSF. (Stroke. 2014;45:1778-1783.)
Key Words: behavior ◼ fatigue ◼ rehabilitation ◼ stroke
P
used meta-analysis to estimate the strength of associations.
Thus, we need more evidence about the nature of the association between PSF and psychological factors, including, but
not limited to, depressive symptoms, anxiety, sense of control,
and coping styles.
This systematic review and meta-analysis aimed to determine whether PSF is associated with psychological factors
that could be targets for a psychological intervention.
oststroke fatigue (PSF) is a distressing symptom that affects
more than a third of stroke survivors.1 Currently, there is
insufficient evidence to guide treatment.2 Psychological interventions improve fatigue in cancer, multiple sclerosis, and
chronic fatigue syndrome by targeting thoughts, mood, and
behavior. To determine whether to develop and test similar
interventions for PSF, we need evidence about associations
between PSF and those factors that could be targeted as part
of a psychological intervention.
Although several narrative reviews have reported psychological factors associated with PSF,1,3–10 their results are
conflicting, for example, 3 reviews concluded that PSF was
associated with depression1,5,9 and 6 reported that PSF could
occur independently of depression.3,4,6–8,10 Three reviews
reported that PSF was associated with anxiety1,3,9 and 1 review
reported no association.4 One review reported that fatigue was
associated with lower expectations for self-efficacy in performing physical activity.11 Importantly, none of these reviews
Methods
We systematically searched electronic databases (MEDLINE,
EMBASE, CINAHL Plus, AMED, and PsycINFO) using key words
stroke and fatigue and their synonyms adapted from a Cochrane review of interventions for PSF.2
One author (S.W.) screened all titles and abstracts on 2 separate
occasions (to ensure that eligible studies were not missed) and obtained full texts of potentially eligible studies. S.W. read all full
texts and 2 authors (G.M., A.B.) each read half of the full texts,
independently of the first author. Any disagreement was discussed
Received December 20, 2013; final revision received March 18, 2014; accepted March 27, 2014.
From the Centre for Clinical Brain Sciences (S.W., M.M., G.M.) and Department of Geriatric Medicine (A.B., G.M.), University of Edinburgh,
Edinburgh, United Kingdom; and Department of Neurology, West China Hospital, Sichuan University, Chengdu, China (S.W.).
Guest Editor for this article was Eric E. Smith, MD, MPH.
Presented in part at the UK Stroke Forum, North Yorkshire, England, December 3–5, 2013, and published in abstract form (Int J Stroke. 2013;8[S3]:71).
Correspondence to Gillian Mead, FRCP, Department of Geriatric Medicine, University of Edinburgh, Room s1642, Royal Infirmary of Edinburgh,
Edinburgh EH16 4SA, United Kingdom. E-mail [email protected]
© 2014 American Heart Association, Inc.
Stroke is available at http://stroke.ahajournals.org
DOI: 10.1161/STROKEAHA.113.004584
1778
Wu et al Psychological Associations of PSF 1779
between authors. Reference lists of included articles and previous reviews were screened, and potentially relevant full texts were
obtained.
We included observational studies reporting measures of both PSF
and ≥1 psychological factor either as dichotomous variables (eg, the
presence or absence of depressive symptoms) or as a continuous variable (eg, depression scales). For studies in which only qualitative data
for the association were available, we included studies in the review
but not in the meta-analysis. Studies were excluded if they (1) contained insufficient data to allow reporting of any association, (2) included any patients aged <18 years, (3) used unstructured assessment
for PSF, or (4) provided data for patients with stroke that could not be
disaggregated from other types of patients.
Two authors (S.W., A.B.) independently extracted data on demographics, presence of prestroke fatigue, how PSF and psychological
factors were assessed, whether patients with a clinical diagnosis of
depression were included or excluded, and statistics for associations. They independently applied the Strengthening the Reporting
of Observational Studies in Epidemiology checklist12 to assess study
quality.
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Statistical Analysis
For each study in which raw data were provided, odds ratios (ORs)
and 95% confidence intervals (95% CIs) were calculated for associations between PSF and each psychological factor. ORs reported by
study authors were accepted if raw data were unavailable. If studies
reported only correlation coefficient, we used established methods to
convert to ORs.13 If ORs could not be obtained by these methods, we
summarized these studies qualitatively not quantitatively. Publication
bias was assessed by funnel plotting.13
For associations of PSF with depressive symptoms and with anxiety, we determined summary estimates of ORs using random-effects
modeling.14 Between-study heterogeneity was assessed using the
Cochran Q statistic,13 in which P<0.05 implies significant heterogeneity. We had intended to perform meta-analysis for psychological associations other than mood, but this was not possible because
these studies only reported regression coefficients and P values for
the associations.
We used partitioning of heterogeneity13 to compare studies that reported adjusted ORs with those that reported unadjusted ORs. For
the association with depressive symptoms, only 3 studies reported
adjusted ORs by controlling for potential confounders (age, sex, lesion site, and dependence in daily life) for PSF in multiple logistic regression, whereas the remaining 16 studies reported unadjusted ORs
(Figure 1). We conducted sensitivity analyses (1) for studies that had
excluded people with a clinical diagnosis of depression and (2) by
excluding studies that had used a depression measure that contained
an item of fatigue.
Results
A total of 5863 citations were identified, and 288 full texts
were retrieved. Three studies (2 conference abstracts and 1
not published in English)15–17 were excluded because they
contained insufficient data for analysis and study authors did
not provide further data on our request. Thirty-five studies fulfilled inclusion criteria (Figure 1).
Mean age of patients ranged from 5118 to 75 years.19 The
proportion of women ranged from 19%18 to 67%.20 Five studies recruited patients with ischemic stroke,21–25 2 with subarachnoid hemorrhage,26,27 18 studies included both ischemic
and hemorrhagic stroke,18–20,28–42 and the other 10 studies did
not specify stroke type.43–52
The median number of Strengthening the Reporting of
Observational Studies in Epidemiology checklist items scored
(out of 22) was 19 (interquartile range, 18–20). No study provided sample size calculations. Other common weaknesses
included not describing details of recruitment, not addressing
potential bias, or not declaring sources of funding.
Depressive Symptoms
Overall Meta-Analysis
Of 31 studies that provided data on the association between
PSF and depressive symptoms, ORs could be obtained, and
used in meta-analysis, from 19 studies; from these we calculated ORs from raw data of 7 studies,20,36,37,39,43,44,49 extracted
ORs from 4 studies,19,23,24,33 and converted ORs from correlation coefficients from 8 studies.22,25,30,32,34,45,47,48 Summary
estimate of OR was 4.14 (95% CI, 2.73–6.27; Figure 2),
with no significant between-study heterogeneity (Q=15.58;
df=18; P=0.62).
Stratified Meta-Analysis
The use of adjusted ORs or unadjusted ORs explained a significant portion of heterogeneity between studies (Q=4.91;
df=1; P=0.03). The strength of the association in 16
Figure 1. Electronic search, study selection, and data analysis. ORs indicates
odds ratios.
1780 Stroke June 2014
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Figure 2. Random-effects meta-analysis for the association between poststroke fatigue and depressive symptoms. The horizontal axis is
the odds ratio (OR) comparing the occurrence of depressive symptoms in patients with and without fatigue after stroke. Horizontal error
bars represent the 95% confidence interval (CI) of OR in individual studies, and vertical gray bar represents the 95% CI of the summary
estimate of OR. Symbol size represents the log of the number of participants in that study. *The upper limit of the 95% CI of OR beyond
34 did not show in the plot.
studies of unadjusted ORs (n=6171; pooled OR=5.46; 95% CI,
3.58–8.32) was higher (P<0.01) than the association in 3
studies in which ORs were adjusted (541 patients; pooled
OR=1.36; 95% CI, 1.26–1.46). This heterogeneity might have
contributed to an asymmetrical funnel plot (Figure 3) because
the 3 studies reporting adjusted ORs were located in the upper
­left-hand corner of the plot away from the other 16 studies.
Figure 3. Funnel plot for publication bias. The horizontal axis
represents the log odds ratios (ORs) for the association between
poststroke fatigue and depressive symptoms, and the vertical
axis represents the inverse SE. The vertical bar represents the
pooled estimate of ORs.
Sensitivity Analyses
Of the 19 studies included in meta-analysis, one study (n=334)
excluded patients with major depression at recruitment24
and another study (n=99) provided data for patients without
depression33; pooled estimate of these 2 adjusted ORs was
1.39 (95% CI, 1.27–1.53, which was not statistically different
from the summary estimate of all 3 adjusted ORs; P=0.91).
The other 17 studies did not specify whether they had distinguished patients with current clinical depression.
Thirteen studies assessed depression using a measure that
contained a single item for fatigue,19,22,24,25,30,32–34,36,43,45,48,49 and
2 of them also assessed fatigue using this fatigue item of the
depression measure.22,49 For the remaining 6 studies (n=4554)
that used depression measures without any fatigue item, the
pooled OR was 5.41 (95% CI, 1.54–18.93), which was not
significantly different from either the summary estimate for
the other 13 studies (pooled OR=3.45; 95% CI, 1.82–6.57;
P=0.53) or from that of the total 19 studies (pooled OR=4.14;
95% CI, 2.73–6.27; P=0.84).
Qualitative Analysis
Twelve studies did not report sufficient data to be included
in meta-analysis. Nine studies (n=1043) reported an association between PSF and depression,18,21,28,31,38,41,42,51,52 whereas one
study (n=32) reported no significant difference in depression
scores between fatigued and nonfatigued groups35; another study
(n=100) reported that depressive symptoms were associated with
mental fatigue but not with other fatigue domains50; and one further study (n=88) used 2 measures for PSF and 2 measures for
depression, but reported 4 conflicting results of the association.29
Wu et al Psychological Associations of PSF 1781
Anxiety
Seven studies reported the association between PSF and
anxiety,23,29,31,33,39,44,52 and data from 4 studies (n=3934)23,33,39,44
could be included in meta-analysis. The summary estimate
of the OR was 2.34 (95% CI, 0.98–5.58) with no significant between-study heterogeneity (Q=2.36; df=3; P=0.50).
Stratified meta-analysis indicated that the strength of association between PSF and anxiety in 2 studies23,33 not controlling
the effect of depression (n=217; pooled OR=5.34; 95% CI,
4.70–6.07) was higher (P<0.01) than that in the other 2 studies39,44 having controlled the effect of depression (n=3717;
pooled OR=1.25; 95% CI, 1.14–1.38).
Of the 3 studies that provided insufficient data to be
included in the meta-analysis, 2 (n=90) reported a significant
association between fatigue and anxiety,31,52 whereas 1 (n=88)
excluded patients with depression at recruitment and found a
nonsignificant association between PSF and anxiety.29
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Sense of Control and Coping Styles
One study (n=167) reported that patients who were not confident in their own ability to control their health had more severe
fatigue (P=0.002).47 Associations between PSF and coping
styles were investigated by 2 studies. One (n=50) reported that
patients focusing on personal emotions and self-blame were
more likely to have a higher level of PSF (P<0.01).30 Another
study (n=73) found that maladaptive coping (eg, denial and
self-distraction) was the main cause of post-traumatic stress
disorder (P<0.0001), and the latter was associated with PSF
(P<0.0001).27
Other Psychological Factors
Six studies reported other psychological associations of PSF.
Three studies (n=1527) assessed mental health and emotional role by Short Form-36, and all reported that poor outcomes of mental or emotional subscales were associated with
PSF.25,40,46 Such an association was also reported by another
study (n=141) using the emotional subscale of stroke-specific
quality of life.26 PSF was also associated with inappropriate
laughing (1 study, n=220)43 and alertness behavior (measured
by Sickness Impact Scale in 1 study, n=90).51
Discussion
This is, to our knowledge, the first meta-analysis to report
associations between PSF and mood or other psychological factors. We found a statistically significant association
between PSF and depressive symptoms and a trend toward an
association between PSF and anxiety. Two studies reported
associations with inadequate coping styles, 1 study with loss of
control, and 6 studies with emotional or behavioral symptoms.
The named psychological factors, that is, depressive symptoms, anxiety, locus of control and coping, have already been
targeted by psychological interventions for fatigue in other
conditions such as cancer and multiple sclerosis. This review
provides the necessary evidence to justify the development of
a similar intervention for fatigue in stroke survivors. However,
our findings should be interpreted with caution because only
a small number of studies investigated each factor except for
depressive symptoms. Also, there are some weaknesses in the
quality of the included studies in that most of them did not
report how patients were recruited and how study size was
achieved; thus, it is difficult to determine whether the sample
is representative of the entire stroke population.
PSF is associated with depressive symptoms, even in
patients not meeting clinical criteria for depression. A previous study reported the presence of depressive symptoms in
patients with stroke without clinical depression, where 41%
of the patients reported depressed mood but only half of them
met clinical criteria for depression.53 This suggests that clinicians should be aware of depressive symptoms in patients with
stroke and screen for them in patients with PSF, even in those
without a clinical depression. We also noticed that some of
the included studies had measured depression by using scales
or criteria that contain a single item of fatigue. We therefore
performed a sensitivity analysis to determine whether this
might result in an overestimation of the strength of association
between fatigue and depression. The result indicated that this
association remained significant even after excluding studies
that had used a depression measure containing a fatigue item.
In fact, in these depression measures, fatigue only contributes
a small proportion to the total score of depression (from 1/9 to
1/66). Thus, the association that we identified was not because
of the overlap between fatigue and depression measures.
In some of the included studies, age, sex, lesion site, and
dependence in daily life were considered as confounders for
the association between PSF and depressive symptoms. Based
on the current data, however, we could not analyze the effect
of each individual factor on the association. Previous studies
reported that age and sex are associated with fatigue40 but not
with depression.54 There is insufficient evidence for the association between lesion site and either fatigue55 or depression.56
The association between PSF and dependence has been widely
reported in the studies included in this review. Dependence
was also reported to be associated with poststroke depression.57 Future research is expected to investigate the effect of
these confounders.
There is a trend toward an association between PSF and
anxiety, but the association was weaker after controlling the
effect of depressive symptoms. One study (included in our
systematic review but not in meta-analysis) that had excluded
patients with depression reported no significant association between PSF and anxiety.29 It is reported that anxiety is
strongly correlated with depression after stroke.58 To better
clarify whether depressive symptoms are confounders, the
association between PSF and anxiety needs to be compared
between patients with stroke with and without depressive
symptoms.
Our study has several strengths. It is the first systematic review to pool the results from studies that reported
the associations between PSF and depressive symptoms or
anxiety. We performed a comprehensive search, had a prespecified protocol, and used a well-established statistical
approach. We also used a funnel plot to detect publication
bias, in which the asymmetrical plot might indicate certain
publication bias caused by the missing studies in the bottom
left-hand corner of the plot. These studies are likely to be
of small sample size and reported less significant results.
1782 Stroke June 2014
A possible source for this publication bias might be the
exclusion of conference abstracts and studies not published
in English, although we have attempted to obtain further
data by contacting the study authors but did not get a reply.
One limitation of our study is that only 1 author read all the
abstracts to identify potentially eligible studies. However,
this was done on 2 separate occasions to reduce the possibility of missing any relevant studies.
Conclusions
This review provides robust evidence for the association
between PSF and depressive symptoms. This implies the
screening and treatment of PSF in patients with stroke needs
to integrate strategies targeting mood. PSF is also associated,
either directly or indirectly, with anxiety, loss of control, poor
coping styles, emotional, and behavioral symptoms; these factors are potential targets for treatment of PSF.
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Sources of Funding
S. Wu was funded by the China Scholarship Council/University of
Edinburgh Joint Scholarship. A. Barugh was supported by the Dunhill
Medical Trust (grant No. RTF17/0111).
Disclosures
None.
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Psychological Associations of Poststroke Fatigue: A Systematic Review and Meta-Analysis
Simiao Wu, Amanda Barugh, Malcolm Macleod and Gillian Mead
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Stroke. 2014;45:1778-1783; originally published online April 29, 2014;
doi: 10.1161/STROKEAHA.113.004584
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