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The effect of nonpharmacological sleep
interventions on depression symptoms: a
metaanalysis of randomised controlled
trials
Article
Accepted Version
Gee, B., Orchard, F., Clarke, E., Joy, A., Clarke, T. and
Reynolds, S. (2019) The effect of nonpharmacological sleep
interventions on depression symptoms: a metaanalysis of
randomised controlled trials. Sleep Medicine Reviews, 43. pp.
118128. ISSN 15322955 doi:
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The Effect of Non-Pharmacological Sleep Interventions on Depression Symptoms: A
Meta-Analysis of Randomised Controlled Trials
Brioney Gee1,2, Faith Orchard3, Emmet Clarke1, Ansu Joy1, Tim Clarke1,2, Shirley Reynolds3
1Norfolk and Suffolk NHS Foundation Trust, UK
2Norwich Medical School, University of East Anglia, UK
3School of Psychology and Clinical Language Sciences, University of Reading, UK
Corresponding Author:
Dr Brioney Gee
Norfolk and Suffolk NHS Foundation Trust
80 St Stephens Road, Norwich, UK.
NR1 3RE
Email: brioney.gee@nsft.nhs.uk Tel: +44 (0)1603 201455
Acknowledgments
We would like to thank Drs Matthew Blake, Kenneth Lichstein and Ron Postuma for sharing
additional data for inclusion in the meta-analysis and the staff of Norfolk and Suffolk NHS
Foundation Trust Frank Curtis Library for their assistance in accessing articles. This review
was not supported by any specific funding. We have no conflicts of interest to declare.
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Summary
Poor sleep is a significant risk factor for depression across the lifespan and sleep
problems
have been hypothesised to contribute to the onset and maintenance of depression symptoms.
However, sleep problems are usually not a direct target of interventions for depression. A
range of non-pharmacological treatments can reduce sleep problems but it is unclear whether
these interventions also reduce other depression symptoms. The aim of this review was to
examine whether non-pharmacological interventions for sleep problems are effective in
reducing symptoms of depression. We carried out a systematic search for randomised
controlled trials of non-pharmacological sleep interventions that measured depression
symptoms as an outcome. Forty-nine trials (n=5908) were included in a random effects meta-
analysis. The pooled standardised mean difference for depression symptoms after treatment
for sleep problems was -0.45 (95% CI: -0.55,-0.36). The size of the effect on depression
symptoms was moderated by the size of the effect on subjective sleep quality. In studies of
participants with mental health problems, sleep interventions had a large effect on depression
symptoms (d=-0.81, 95% CI: -1.13,-0.49). The findings indicate that non-pharmacological
sleep interventions are effective in reducing the severity of depression, particularly in clinical
populations. This suggests that non-pharmacological sleep interventions could be offered as a
treatment for depression, potentially improving access to treatment.
Keywords: depression; mood; sleep; insomnia; intervention; treatment; meta-analysis
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Glossary
Cognitive behavioural therapy for insomnia: A multi-component psychological intervention
comprising a range of strategies designed to target the behavioural and cognitive
underpinnings of insomnia.
Forest plot: Graphical representation of the results of a meta-analysis.
Funnel plot: Used to detect bias in trials included in a meta-analysis. Publication bias will
result in asymmetry in the plot.
Heterogeneity: Variability in observed effect sizes that is greater than would be expected by
chance alone.
Meta-regression: A statistical technique that allows the association between continuous, as
well as categorical, study characteristics and the intervention effects observed to be
investigated.
Paradoxical intention: Instructing the client to stop trying to fall asleep and instead stay
awake for as long as possible in order to lessen anxiety about falling asleep.
Rosenthal’s failsafe N: The number of additional studies in which the intervention effect was
zero that would need to be included in a meta-analysis to increase the P value to above 0.05.
Sleep restriction therapy: Limiting the time spent in bed to the actual time spent sleeping in
order to increase sleep efficiency.
Stimulus control therapy: Providing the client with instructions designed to re-associate the
bed/bedroom with sleep.
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Introduction
Depression is a common mental health problem, with a lifetime prevalence of approximately
15% in high income countries [1]. It is among the leading causes of disability globally [2],
but only a small minority of individuals experiencing depression receive adequate treatment
[3]. More than 65% of adults with major depressive disorder report sleep difficulties [4,5],
including difficulty falling asleep, frequent awakenings during the night, early morning
awakening and non-restorative sleep [6], and around 40% report sleep disturbance severe
enough to warrant a diagnosis of insomnia [7]. Among adolescents with depression, recent
research indicates that up to 90% present with disturbed sleep [8,9]. In both children and
adults, those who experience sleep problems present with more severe depression than
depressed individuals without sleep problems [10,11].
Depression has often been conceptualised as a cause of sleep problems [12], reflected in the
inclusion of sleep disturbance in the diagnostic criteria for depressive disorders in both
commonly used diagnostic manuals (DSM-5 [13] and ICD-10 [14]). However, sleep
problems often predate the onset of depression [15,16], and are among the most commonly
reported residual symptoms after the remission of a depressive disorder [17]. Thus it has been
suggested that, rather than sleep problems being a symptom or consequence of depression,
that depression and sleep disorders may constitute separate syndromes that co-occur as a
result of shared causal pathways [18].
Longitudinal research suggests a bidirectional relationship between depression and sleep,
with sleep disturbances predicting later depressive episodes as well as vice versa [19]. In a
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meta-analysis of longitudinal studies, the risk of non-depressed individuals with
insomnia
subsequently developing depression was found to be twice that of people without sleep
difficulties [20]. Studies examining the prospective role of sleep in the development of
depression have found sleep problems to be a risk factor for subsequent depression across the
lifespan, from adolescence [21] through to older adulthood [22].
Further, there is some evidence to support the hypothesis that poor sleep might play a causal
role in the onset and maintenance of depression symptoms [23,24]. In experimental and
quasi-experimental studies, sleep deprivation has been found to increase negative mood [23],
decrease positive emotional responses to goal-enhancing events [25] and bring about poorer
memory for positively valenced words [26]. In addition, healthy adult volunteers subjected to
six days of sleep curtailment have been found to show electroencephalography abnormalities
and endocrine disturbances usually observed in depression [18]. In adolescents, even modest
sleep restriction over five nights has been found to result in worsened mood, increased
irritability and decreased ability to regulate negative emotions [27].
Given the hypothesis that poor sleep might contribute to the onset and maintenance of
depression, it is plausible that treatments that are successful in improving sleep might also
lead to reductions in symptoms of depression. Pharmacological sleep treatments have been
found to produce short-lived improvements in sleep but are not recommended for longer-term
sleep problems due to poor efficacy [28] and concerns about dependence and other adverse
effects [29].
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Non-pharmacological interventions are effective in improving sleep, both in individuals with
insomnia [30,31], and in those with sleep problems in the context of medical and psychiatric
disorders [32–34]. Insomnia is the most common sleep complaint, both in individuals with
depression [5,11] and in the general population [34]. A range of non-pharmacological
interventions have been found to be effective treatments for insomnia, including stimulus
control therapy, relaxation training, sleep restriction therapy, biofeedback, paradoxical
intention and multicomponent cognitive behavioural therapy for insomnia (CBT-I) [35].
Depression symptoms are often measured as a secondary outcome in trials of non-
pharmacological interventions designed to improve sleep. A number of previous reviews
have included analyses of the effect of interventions targeting sleep problems on depression
symptoms. The results of previous meta-analyses suggest that both internet-delivered [36]
and group-based [37] CBT-I have small but significant effects on depression symptoms,
despite these symptoms not being specifically targeted.
However, a recent network meta-analysis of behavioural and cognitive behavioural
interventions for adults with insomnia [38] found that only individual, face-to-face CBT-I
had a significant effect on depression symptoms when compared to a placebo condition.
Studies were included in this analysis if the trial intervention incorporated sleep restriction,
and depression was measured using a standardised measure. The authors grouped the CBT-I
interventions trialled into six classes according to their treatment components and delivery
mode, and compared each class of intervention to placebo conditions (pills or behavioural
placebo). Significant moderate-sized mean effects were found for individual CBT-I, but no
significant effects were found for other treatment classes. However, the conclusions that
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could be drawn were limited by significant heterogeneity that was not explained by the
clinical, demographic or methodological characteristics examined, which included age, sex,
whether participants with comorbidities were excluded, and risk of bias.
One possible source of heterogeneity in the effect of sleep interventions on depression is
variation in the size of effect on the sleep symptoms directly targeted. The authors of a recent
review of CBT-I in adults with co-morbid major depressive disorder [39] suggest that
improvement in depression following CBT-I may be mediated by improvement in insomnia
symptoms. There are plausible mechanisms through which improvements in sleep might lead
to improvements in depression symptoms. These include the impact of improved sleep on
quality of life, emotion regulation and cognitive functioning [40,41], as well as reductions in
neurobiological abnormalities common to both mood and sleep disturbances [42]. However,
there are also a range of non-specific factors that might account for the effect of sleep-
interventions on depression, for instance increased motivation or hope as a result of
developing a therapeutic relationship or participation in a therapeutic process [43]. As such,
the extent to which improvements in depression symptoms are accounted for by improved
sleep warrants investigation.
The aim of the current review was to identify and synthesise the results of all randomised
controlled trials of non-pharmacological interventions designed to improve sleep that
reported depression symptoms as an outcome. Eligible interventions were designed to
improve the amount, quality or timing of sleep, including but not limited to interventions for
insomnia. The review was not restricted to a particular intervention or client group, and the
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impact of the age of trial participants and presence or absence of mental health comorbidities
was examined.
A secondary goal was to examine whether improvements in symptoms of depression were
moderated by improvements in subjective sleep quality in order to assess whether
heterogeneity in the effect of sleep interventions on depression can be explained by variation
in how effective the intervention is in improving perceived sleep quality. Better
understanding the impact of non-pharmacological sleep interventions on depression
symptoms will be important in enabling us to assess in which cases interventions targeting
sleep might be appropriately harnessed as treatment options for depression.
Methods
Search strategy
The review was conducted in accordance with guidance in the ‘preferred reporting items for
systematic reviews and meta-analyses’ (PRISMA) statement [44]. The protocol was
registered with the PROSPERO registry prior to implementation of the search strategy and
can be accessed at:
http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017054940.
The search strategy aimed to identify all eligible trials reported in the English language in a
peer-reviewed journal. Four electronic databases, PsycINFO, Medline, CINAHL and
CENTRAL, were searched from their inception until 1st May 2018. The following search
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terms were used: (sleep OR insomnia OR “sleep treatment” OR “sleep disorders”) AND
(intervention OR treatment OR therapy OR help OR hygiene OR support OR education)
AND (depressi* OR mood). Limiters were used to narrow the search to clinical trials and
English language publications. We also hand searched the reference lists of eligible articles
and key review papers to identify any eligible articles missed by the electronic search.
Eligibility Criteria
The inclusion criteria employed were as follows: (1) randomised controlled trial; (2) trial
intervention was a non-pharmacological intervention specifically designed to improve sleep
(amount, quality or timing); (3) trial included a control condition not designed to improve
sleep; (4) depression symptoms were measured (as either a primary or secondary outcome)
using a validated instrument; (5) the trial was reported in the English language in a peer
reviewed journal. Studies that met any of the following criteria were excluded: (1) the trial
intervention included a pharmacological component (including traditional/herbal remedies);
(2) all trial arms received an intervention designed to improve sleep (for instance, the only
control condition was a pharmacological sleep aid or sleep hygiene); (3) trial intervention
was designed to treat parasomnias, sleep apnoea or fatigue (as these are thought to have
causal factors distinct from other sleep problems).
Study selection
The titles and abstracts of all retrieved articles were screened by one reviewer (BG). A
subsample of 10% of articles (selected using a random number generator) was screened
independently by a second reviewer (AJ) to check that no potentially eligible articles were
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excluded. The full texts of all articles deemed potentially relevant were obtained and assessed
for eligibility against the inclusion/exclusion criteria by two reviewers independently (BG
and one of FO, EC, AJ, TC or SR). All disagreements regarding eligibility were discussed by
the two reviewers and, if consensus not reached, resolved by a third reviewer. Where multiple
publications describing the same trial were identified, only the article reporting on the larger
sample was included.
Data extraction and quality assessment
Data were extracted independently by two reviewers (BG and EC) and cross-checked to
ensure accuracy. The following information was recorded using a customised data extraction
spreadsheet: study characteristics (authors, title, year of publication), intervention type, age of
sample, psychiatric comorbidities, depression measure used, subjective sleep quality
measure
used, size of intervention and control groups, baseline and outcome data (at first time-point
post-intervention) for depression and sleep quality (means and standard deviations). Where
insufficient outcome data were reported for the study to be included in the meta-analysis, we
contacted corresponding authors to request this data. The methodological quality of included
studies was assessed by one reviewer (AJ) using the Cochrane collaboration’s risk of bias
tool [45]. For a random subsample of 10% of included studies, the risk of bias assessment
was independently verified by a second reviewer (BG) and discrepancies resolved through
discussion.
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Data synthesis
All eligible studies for which sufficient data on depression outcomes were reported or could
be obtained from the corresponding author were included in a random effects meta-analysis.
Review Manager Version 5.3 [46] was used to perform the meta-analysis. Standardised mean
differences of depression scores at post-intervention and their 95% confidence intervals were
calculated for each study, and weighted according to sample size via the random effects
model. Standardised mean differences greater than 0.8 were considered large, 0.5 moderate
and 0.2 small [47].
Where more than one non-pharmacological intervention designed to improve sleep was
included in the trial, data for the most intensive intervention was included in the meta-
analysis. The most intensive intervention was determined by consensus of two reviewers
based on the amount of face-to-face contact the intervention included (so that interventions
delivered in a self-help format were classed as less intensive than therapist-delivered
interventions). A random effects model was selected as we expected there would be
heterogeneity in study effect sizes because of diversity in their target populations and the
specific interventions trialled. Statistical heterogeneity was assessed using the Chi2 and I2
statistics. Significant heterogeneity is indicated by a Chi2 statistic greater than the degrees of
freedom and a p value<0.05; I2 values range from 0% to 100%, with higher values indicating
greater heterogeneity [48]. Publication bias was assessed via construction and visual
inspection of a funnel plot and by calculating Rosenthal’s failsafe N.
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Two planned subgroup analyses were carried out to investigate sources of heterogeneity. The
first divided the studies into those that recruited from populations who had sleep problems in
the context of mental health problems and those that recruited from populations without
clinical mental health problems. Studies were classified as recruiting from a population with
mental health problems if all participants either (a) meet standardised diagnostic criteria for at
least one functional mental disorder (determined via chart review or diagnostic interview) or
(b) scored above the clinical threshold on a validated measure of mental health
symptomatology. The second planned subgroup analysis divided the studies according to the
age range of participants: children/adolescents (aged up to 19), adults (aged 18+), older adults
(aged 50+). Additionally, a post-hoc subgroup analysis was conducted to investigate the
impact of the depression measure employed on the effect size detected. Only trials that
measured depression using an instrument employed by at least two other trials were included
in this analysis.
Finally, a random effects meta-regression was carried out to assess whether the effect of an
intervention on depression symptoms was predicted by its effect on subjective sleep quality.
This was achieved by calculating effect sizes (standardised mean difference) for all studies
that reported subjective sleep quality post-intervention and entering these as covariates in a
meta-regression using Field and Gillett’s SPSS syntax files [49].
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Results
Study selection
The study selection process is illustrated in Figure 1. Sixty-one papers were identified that
met the inclusion criteria, however three were secondary analyses of already included trials
and we were unable to obtain sufficient depression data for inclusion in the meta-analysis
from the published report or by contacting the corresponding author for nine studies.
Therefore data from 49 articles are included in the meta-analysis.
[Inset Figure 1]
Characteristics of included studies
Characteristics of the 49 trials included in the meta-analysis are summarised in Table 1. The
meta-analysis included data on 5908 participants, of whom 2731 were randomised to receive
the trial sleep intervention. The included trials were all of psychological interventions. The
majority (39 out of 48 studies) were described by the study authors as CBT-I or CBT-
informed interventions. Sixteen studies trialled interventions delivered in a self-help format,
online or via a mobile application. The remaining trials were of face-to-face interventions, 27
delivered individually and five delivered in a group format. Control conditions included
active interventions not specifically targeting sleep (e.g. dietary advice, exercise
programmes), and passive controls, such as medical treatment as usual and waitlist.
Most participants were adults; only four studies included young people aged under 18
(n=292) and none included children under 11 years. Many of the studies recruited participants
with physical health problems (e.g. chronic pain, heart failure, cancer), for whom sleep was a
secondary or additional problem. Twenty studies recruited participants with sleep problems
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and no other comorbidity. Half of the included studies excluded participants deemed to have
clinical levels of depression symptoms (defined either as meeting diagnostic criteria for a
depressive disorder or scoring above a specified cut-off on a measure of depression
symptoms). A wide range of measures of depression symptoms were used and included
widely used self-report questionnaires, as well as observer rating scales (e.g. the Hamilton
rating scale for depression). Subjective sleep quality (including self-reported insomnia
severity) was measured by 43 of the 49 included studies. The trials were conducted in high
and upper-middle income countries across four continents (Europe, North America, Asia and
Australasia).
[Insert Table 1]
Risk of bias
The Cochrane collaboration’s risk of bias tool was used to assess the quality of the included
studies and a risk of bias summary graph produced (Figure 2). The majority of studies were
judged to be of high quality, though few studies were able to blind participants and research
personnel, and most papers included insufficient information to be able to determine the risk
of bias due to poor allocation concealment or selective reporting. The measures of depression
used in the studies had sound psychometric properties, and where young people under 18
were included, had been validated for use with adolescents.
[Insert Figure 2]
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Meta-analysis of effect on depression symptoms at post-treatment
The results of the random effects meta-analysis are illustrated in Figure 3. There was a small
to moderate effect of non-pharmacological sleep interventions in reducing depression
symptoms in comparison to control conditions not designed to improve sleep (standardised
mean difference = -0.45, 95% CI -0.55, -0.36, p<0.001, k=49). The statistical heterogeneity
in effect sizes among studies was moderate (I2=56%, χ2=108.8, df=48, p<0.001).
[Inset Figure 3]
Subgroup analyses and meta-regression
Comorbid mental health difficulties
Seven of the included studies recruited from participants with clinical mental health problems
(typically anxiety, depression and PTSD) in addition to sleep difficulties. The subgroup
analyses showed that the pooled effect on depression symptoms for these seven studies was
large (standardised mean difference = -0.81, 95% CI -1.13, -0.49, p<0.001, k=7) and the
statistical heterogeneity among these studies was small (I2=27%, χ2=8.19, df=6, p=0.22). In
comparison, the subgroup of studies that recruited participants without clinical mental health
difficulties (k=42) found a small effect on depression symptoms (standardised mean
difference = -0.41, 95% CI -0.51, -0.31, p<0.001) and these effect sizes were more
heterogeneous (I2=56%, χ2=93.45, df=41, p<0.001).
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Adolescents, adults and older adults
The majority of included studies recruited adults of all ages. Four of the studies recruited
adolescents (all participants under the age of 20) and three recruited only adults over the age
of 50. The four trials in adolescents had the smallest pooled effect on depression
symptoms
(standardised mean difference = -0.27, 95% CI -0.50, -0.04, p=0.02, k=4), with no statistical
heterogeneity (I2=0%, χ2=1.99, df=3, p=0.57). The pooled effect on depression symptoms for
the studies with adult participants was small to moderate (standardised mean difference = –
0.46, 95% CI -0.57, -0.36, p<0.001, k=42) with moderate heterogeneity (I2=59%, χ2=100.75,
df=41, p<0.001). The three studies that recruited adults over the age of 50 had the largest
pooled effect size but wide confidence intervals (standardised mean difference = -0.60, 95%
CI -1.12, -0.08, p=0.02, k=3) and moderate heterogeneity (I2=47%, χ2=3.76, df=2, p=0.15).
Depression measure
The centre for epidemiological studies depression scale (CESD) was the most commonly
used depression measure in the included studies (k=11), followed by the Beck depression
inventory (BDI) (k=10), hospital anxiety and depression scale (HADS) (k=8), nine item
patient health questionnaire (PHQ-9) (k=4) and the Beck depression inventory version II
(BDI-II) (k=3). All other measures were employed in less than three of the included trials.
The standardised mean difference was largest for trials that measured depression using the
PHQ-9 (-0.70, 95% CI -1.00, -0.41, p<0.001), followed by the BDI (-0.56, 95% CI -0.76, -
0.36, p<0.001), the CESD (-0.45 95% CIs -0.67, -0.24, p<0.001), and the HADS (-0.34, 95%
CIs -0.57, -0.11, p=0.003). It was smallest in trials that used the BDI-II (-0.12, 95% CIs –
0.36, 0.13, p=0.34).
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Effect on subjective sleep quality
The standardised mean difference for subjective sleep quality at post-intervention could be
calculated in the case of 40 of the 49 included studies. There was a positive linear
relationship between the standardised mean difference of the sleep interventions on
depression symptoms and the standardised mean difference for subjective sleep quality. The
meta-regression revealed that the size of the effect on subjective sleep quality was a
significant continuous moderator of the effect on depression symptoms (β=0.447, 95% CI
0.29, 0.60, p<0.001). The residual variation was non-significant (χ2=41.89, p=0.306)
suggesting the statistical heterogeneity in the size of the effect of the studied sleep
interventions on depression symptoms can be explained by variation in their effect on
subjective sleep quality.
Publication bias
Inspection of the funnel plot suggested that effect sizes might be slightly inflated in some
smaller studies, with one small study a notable outlier. However, this might be explained by
clinical diversity among the populations studied since trials that recruited participants with
sleep problems in the context of mental health problems tended to find larger effect sizes and
to have smaller samples than the studies that recruited participants without clinical mental
health problems. Rosenthal’s failsafe N was 3593.46, indicating that 3593 studies with zero
effect sizes would be needed to nullify the pooled effect.
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Discussion
We reviewed the evidence of the effect of non-pharmacological interventions designed to
improve sleep on the severity of depression symptoms. The meta-analysis showed that non-
pharmacological sleep interventions reduce the severity of depression symptoms immediately
post-intervention, and this finding was robust to the possibility of publication bias. The
pooled effect on depression severity was in the small to moderate range. This is comparable
to the effect size of targeted non-pharmacological interventions for depression delivered in
primary care [50,51] and to non-pharmacological interventions for depression that is
comorbid with physical health problems [52–54]. The effect is, however, somewhat smaller
than the effect sizes of non-pharmacological interventions for depression delivered to
individuals with major depression disorder [55].
As would be expected given that most eligible trials were of CBT-I, or CBT-informed
interventions for insomnia, the effect on depression symptoms we identified is comparable to
the effects on depression symptoms reported in previous meta-analyses of CBT-I [36–38].
The size of reduction in depression symptoms is also similar to the effect on anxiety
symptoms in a meta-analysis of CBT-I trials [56], suggesting that non-pharmacological sleep
interventions are similarly effective in reducing both depression and anxiety.
Whilst the pooled effect of non-pharmacological sleep interventions on depression symptoms
is small to moderate, there was considerable heterogeneity in the size of effects observed.
This heterogeneity is in line with previous research [38] and unsurprising given the variation
in the participants recruited and the type of interventions trialled by the included studies. For
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participants with mental health problems, sleep interventions had a large effect on symptoms
of depression. Such interventions have previously been found to have large effects on sleep
symptoms in individuals with mental health problems [57]. Therefore, sleep interventions
might be of particular benefit to this group.
The pooled effect size for studies that recruited children and adolescents was small compared
to the effect sizes for those studies that recruited adults and older adults. These relatively
modest effects on depression symptoms are in line with the small effect sizes that have been
found in studies of non-pharmacological therapies directly targeting depression in children
and young people [58,59]. However, none of the studies included in this review investigated
the effect of non-pharmacological sleep interventions on children or adolescents with clinical
level mental health difficulties, including depression, for whom sleep difficulties are both
common and distressing [8,9]. Given the effect of sleep interventions on depression
symptoms was larger in studies that recruited participants with sleep problems in the context
of mental health problems, the small effect on depression in studies of children and
adolescents might be partially accounted for by the lack of trials including young people with
clinical-level mental health problems. Therefore, the potential effects of sleep interventions
for depressed children and adolescents warrants further evaluation.
There was a strong association between the change in subjective sleep quality brought about
by an intervention and its effect on depression symptoms. The statistical heterogeneity in the
effect sizes for depression symptoms was nullified by the introduction of the effect size for
subjective sleep quality as a covariate in the random effects meta-regression, indicating that
the heterogeneity on the effect of the interventions on depression can be explained by
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heterogeneity in their effect on subjective sleep quality. This might support the contention
that changes in the severity of depression symptoms were brought about by changes in
subjective sleep quality.
However, it is also possible that the observed relationship between effects on depression
symptoms and subjective sleep quality is a consequence of non-specific features of the
intervention or study context impacting on both sleep and depression symptoms
independently. Further research is needed to fully understand the nature of the relationship
between the effect of sleep interventions on sleep and their effect on depression. Studies
incorporating objective measurement of sleep variables in addition to self-reported sleep
quality would potentially be informative.
Clinical implications
Currently, only a small minority of individuals experiencing depression receive adequate
treatment [3]. The stigma associated with mental health problems has been identified as an
important barrier to help-seeking and treatment adherence [60]. The effectiveness of non-
pharmacological sleep interventions on depression symptoms suggests that the use of non-
pharmacological interventions that target sleep (and not mental health difficulties) may offer
a relatively low stigma means of reducing depression symptoms in individuals who have both
sleep and mental health difficulties. Offering sleep interventions as a treatment option for
those who report depression symptoms might also be particularly useful for individuals
reluctant to engage in a targeted treatment for depression.
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21
Non-pharmacological sleep interventions can be successfully delivered in a variety of
relatively low-cost formats [28], therefore providing these as a treatment option for people
with depression has the potential to be cost-effective. However, caution should be exercised
in offering non-pharmacological sleep interventions as a standalone intervention for
depression symptoms; residual depression symptoms should be monitored and additional
interventions offered as necessary.
Limitations
A limitation of the current review is that, because diagnostic criteria for depression include
sleep problems as a symptom, measures of depression typically incorporate one or more
items assessing sleep symptoms. Since these items account for only a small proportion of the
total scale score, it is unlikely that changes on these items alone after treatment for sleep
problems could account for the size of the effects observed. However, lack of item level data
meant that it was not possible to isolate the effect of the interventions trialled on non-sleep
depression symptoms. Future trials should use depression measures that do not include items
assessing sleep symptoms or report item-level data to enable the effect of sleep interventions
on non-sleep depression symptoms to be investigated.
A further consideration in interpreting the results of this meta-analysis is that many studies
excluded people who reported elevated symptoms of depression or a history of major
depression. Thus, while we cannot be certain what effect this had on the pooled effect size, it
is possible that relatively low levels of depression before treatment for sleep problems
reduced the overall effect of treatment on depression symptoms. We were also unable to
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
22
assess whether participants in the included trials were offered treatment for depression or
provided with mood management techniques before or after their participation in the sleep
interventions trialled as this was not consistently reported.
The meta-analysis only included trials that reported adequate data on depression symptoms at
post-treatment. We could not include nine trials identified as eligible for inclusion in the
meta-analysis as we were unable to obtain sufficient data on depression outcome to calculate
the standardised mean difference. Also, we focused on outcomes immediately post-
intervention so are unable to comment on the longevity of the effects on depression observed.
Further, we only included trials that measured depression symptoms as an outcome. It is
possible that trials of non-pharmacological sleep interventions that did not measure
depression symptoms as an outcome might have differed from those that did in some fashion
that would impact the size of the effect obtained.
Conclusions
Non-pharmacological interventions designed to improve sleep have a positive impact on
depression symptoms. The size of the effect on depression is moderated by the effect on
subjective sleep quality and is largest for participants experiencing sleep problems in the
context of mental health difficulties. Further research investigating the mechanisms by which
sleep interventions impact depression symptoms is warranted.
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
23
Practice points
1. Available randomised controlled trial evidence indicates that non-pharmacological
interventions designed to improve sleep have a small to moderate effect on depression
symptoms when these are measured as a secondary outcome.
2. The size of the effect on depression symptoms is moderated by the effect of the
intervention on subjective sleep quality.
3. The effect on depression symptoms appears to be larger in adult than in children and
adolescents but this may be an artefact of the participants who were recruited.
4. We found evidence of a large effect for studies that recruited participants experiencing
sleep problems in the context of mental health difficulties. Offering non-
pharmacological sleep interventions to users of mental health services who are
experiencing concomitant mood and sleep problems may lead to significant
improvements in depression symptoms as well as sleep quality.
Research agenda
1. Future trials of sleep interventions should measure depression symptoms as an
outcome and report this data at item level where the depression instrument used
includes an item(s) assessing sleep problems.
2. Future studies should investigate the mechanisms through which sleep interventions
lead to improvements in depression symptoms.
3. The effect of sleep interventions on depression in children and adolescents with
mental health problems should be trialled.
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
24
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Tables
Table 1. Characteristics of studies included in the meta-analysis
Study County Participants Intervention Depression
measure
Sleep
measure
Blake et al. 2016 [61] Australia Adolescents (aged 12–17) with
high anxiety and sleep difficulties
CBT/mindfulness-based
group sleep intervention
CESD PSQI
Casault et al. 2015 [62] Canada Adults diagnosed with cancer
with comorbid insomnia
Self-help CBT-I with
telephone support
HADS ISI
Chang et al. 2016 [63] Taiwan Adults with heart failure Educational supportive care
programme
HADS PSQI
Christensen et al. 2016 [64] Australia Adult internet users
with insomnia
and subclinical depression
Online insomnia self-help
programme
PHQ-9 ISI
Currie et al. 2000 [65] Canada Adults with insomnia secondary
to chronic pain
Group CBT-I
BDI PSQI
Currie et al. 2004 [66] Canada Adult recovering alcoholics with
insomnia
Brief CBT-based insomnia
programme
BDI PSQI
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
34
Dewald-Kaufmann et al.
2014 [67]
Netherlands Adolescents (aged 12-19) with
chronic sleep reduction
Gradual sleep extension and
sleep hygiene advice
CDI CSRQ
Ebert et al. 2015 [68] Germany Adult teachers with sleeping
problems
Online CBT-I based recovery
training programme
CESD PSQI
Edinger et al. 2001 [69] USA Adults with chronic primary
sleep-
maintenance insomnia
Individual CBT-I BDI ISQ
Edinger et al. 2007 [70] USA Adults with primary sleep-
maintenance insomnia
Individual CBT-I BDI ISQ
Freeman et al. 2017 [71] UK Adult university students with
insomnia
Online CBT-I delivered via a
media-rich web application
PHQ-9 ISI
Galovski et al. 2016 [72] USA Adult female interpersonal assault
survivors with sleep impairment
Sleep-directed hypnosis BDI-II PSQI
Gradisar et al. 2011 [73] Australia Adolescents (aged 11-18)
diagnosed with delayed sleep
phase disorder
Individual CBT plus morning
bright light
MFQ None
Ho et al. 2014 [74] China Adult internet users with insomnia Online self-help CBT-I with HADS PSQI
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
35
telephone support
Horsch et al. 2017 [75] Netherlands Adult with insomnia and an
Android mobile phone
CBT-I delivered via an
automated mobile phone app
CESD PSQI
Hou et al. 2014 [76] China Adults with end stage renal
disease and comorbid insomnia
Individual CBT-I SCL-90 PSQI
Irwin et al. 2017 [77] USA Adult survivors of breast cancer
with insomnia
Group CBT-I IDS-C PSQI
Jungquist et al. 2010 [78] UK Adults with insomnia comorbid
with chronic pain
Individual CBT-I
BDI ISI
Kapella et al. 2011 [79] USA Adults with insomnia and chronic
obstructive pulmonary disease
Individual CBT-I POMS-D PSQI
Lancee et al. 2012 [80] Netherlands Adult internet users with insomnia Online self-help CBT-I
CESD SLEEP-50
Lancee et al. 2015 [81] Netherlands Adult internet users with insomnia Online self-help CBT-I
CESD ISI
Lancee et al. 2016 [82] Netherlands Adult internet users with insomnia Online guided CBT-I CESD ISI
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
36
Lancee et al. 2017 [83] Netherlands Adult internet users with insomnia
Attentional bias modification
training
CESD ISI
Lichstein et al. 2000 [84] USA Older adults (aged 58+) with
insomnia secondary to illness
Sleep hygiene, stimulus control
and relaxation
GDS None
Margolies et al. 2013 [85] USA Adult veterans with PTSD and
sleep disturbance
CBT-I combined with imagery
rehearsal therapy
PHQ-9 PSQI
McCurry et al. 1998 [86] USA Older adult (aged 50+) dementia
caregivers with sleep problems
Group educational and
behavioural intervention
CESD PSQI
McCurry et al. 2012 [87] USA Older adults with dementia
resident in small care homes
Sleep education for care-staff CSDD None
Mimeault & Morin 1999
[88]
Canada Adults with primary insomnia Self-help CBT-I with
telephone support
BDI PSQI
Morin et al. 2005 [89] Canada Adults with insomnia symptoms
Self-help CBT-I BDI-II PSQI
Moseley et al. 2009 [90] Australia Adolescent high school students CBT-I-based classroom sleep DASS-21 None
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
37
(aged 15/16) education programme
Nguyen et al. 2017 [91] Australia Adults with
traumatic brain injury
and sleep/fatigue complaints
Individual CBT-I adapted for
traumatic brain injury
HADS PSQI
Pigeon et al. 2012 [92] USA Adults with co-occurring chronic
pain and chronic insomnia
CBT for insomnia and pain CESD ISI
Riedel et al. 1998 [93] USA Adults with insomnia
Individual stimulus control
sessions
BDI None
Rios Romenets et al. 2013
[94]
Canada Adults with Parkinson’s disease
and insomnia
Sleep hygiene training, CBT-I
and bright light therapy
BDI ISI
Ritterband et al. 2012 [95] USA Adult internet users in remission
from cancer with secondary
insomnia
Online CBT-I HADS ISI
Savard et al. 2005 [96] Canada Adult women with insomnia
secondary to breast cancer
Group CBT-I HADS ISI
Savard et al. 2014 [97] Canada Adult women with breast cancer
and insomnia symptoms who
Individual CBT-I HADS ISI
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
38
received radiation therapy
Stremler et al. 2013 [98] Canada Adult women who had recently
given birth for the first time
Sleep education and advice EPDS GSDS
Suzuki et al. 2008 [99] Japan Adult workers with a desire to
improve their sleep quality
Online CBT-based self-help
programme
K6 PSQI
Swift et al. 2012 [100] UK Adults who responded to a flyer
advertising sleep workshops
One-day CBT-I workshop BDI ISI
Talbot et al. 2014 [101] USA Adults with PTSD and insomnia
Individual CBT-I BDI ISI
Tang et al. 2012 [102] UK Adults with chronic pain and
insomnia
Individual hybrid CBT for
insomnia and chronic pain
HADS ISI
Taylor et al. 2014 [103] USA Adult college students with
insomnia
Individual CBT-I QIDS PSQI
Thorndike et al. 2013 [104] USA Adult internet users with insomnia
Online self-help CBT-I BDI-II ISI
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
39
Ulmer et al. 2011 [105] USA Adult veterans meeting criteria for
PTSD and insomnia
Sleep intervention for PTSD
(CBT and imagery rehearsal
therapy)
PHQ-2 PSQI
van Straten et al. 2009
[106]
Netherlands Adults with insomnia symptoms Self-help CBT-I delivered via a
book and television
CESD SEF
van Straten et al. 2014
[107]
Netherlands Adults with insomnia Online CBT-I with support of
online coach
CESD PSQI
Wagley et al. 2013 [108] USA Adult psychiatric outpatients with
low sleep quality and depression
symptoms
Two session individual CBT-I PHQ-9 PSQI
Watanabe et al. 2011 [109] Japan Adult psychiatric outpatients with
depression and insomnia
Individual CBT-I HDRS PSQI
Abbreviations. BDI = Beck depression inventory; CBT-I = cognitive behavioural therapy for insomnia; CDI = children’s depression inventory;
CESD = centre for epidemiological studies depression scale; CSDD = Cornell Scale for Depression in Dementia; CSRQ = chronic sleep
reduction questionnaire; DASS = depression anxiety stress scale; GDS = geriatric depression scale; GSDS = general sleep disturbance scale;
HADS = hospital anxiety and depression scale (depression subscale); HDRS = Hamilton depression rating scale; ISI = insomnia severity index;
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
40
K6 = Kessler psychological distress scale; MFQ = mood and feeling questionnaire; PHQ = patient health questionnaire; POMS-D = profile of
mood states depression subscale; PSQI = Pittsburgh sleep quality inventory; SCI = sleep condition indicator; SCL-90 = symptom checklist
RUNNING HEAD: EFFECT OF NON-PHARMACOLOGICAL SLEEP INTERVENTIONS ON DEPRESSION SYMPTOMS
41
Figure Legends
Figure 1. Flow diagram of study selection process
Figure 2. Risk of bias graph
Figure 3. Forrest plot for meta-analysis of the effect of non-pharmacological sleep
interventions on depression symptoms.
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