Cognitive behavioral therapy for insomnia as a suicide prevention strategy: a protocol for a systematic review and meta-analysis

Cognitive behavioral therapy for insomnia as a suicide prevention strategy: a protocol for a systematic review and meta-analysis | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Cognitive behavioral therapy for insomnia as a suicide prevention strategy: a protocol for a systematic review and meta-analysis View ORCID Profile Cagdas Türkmen , Carlotta L. Schneider , Yuki Furukawa , Jens H. van Dalfsen , William V. McCall , Wilfred R. Pigeon , Andrew S. Tubbs , Michael L. Perlis , Dieter Riemann , Kai Spiegelhalder , Knut Langsrud , Håvard Kallestad , Elisabeth Hertenstein doi: https://doi.org/10.1101/2025.06.29.25330506 Cagdas Türkmen 1 Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg , Mannheim, Germany MSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Cagdas Türkmen For correspondence: cagdas.tuerkmen{at}zi-mannheim.de Carlotta L. Schneider 2 Faculty of Medicine, Department of Psychiatry, University of Geneva , Geneva, Switzerland MSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yuki Furukawa 3 Technical University of Munich, TUM School of Medicine and Health, Department of Psychiatry and Psychotherapy , Munich, Germany 4 Department of Neuropsychiatry, University of Tokyo Hospital , Tokyo, Japan MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jens H. van Dalfsen 5 Department of Psychiatry, University Medical Center Groningen , Groningen, The Netherlands PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site William V. McCall 6 Department of Psychiatry and Health Behavior, Medical College of Georgia, Augusta University , Augusta, GA, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Wilfred R. Pigeon 7 Department of Psychiatry, University of Rochester Medical Center , Rochester, NY, USA 8 Center of Excellence for Suicide Prevention, U.S. Department of Veterans Affairs , Canandaigua, NY, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew S. Tubbs 9 Department of Psychiatry, Washington University School of Medicine , St. Louis, MO, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael L. Perlis 10 Behavioral Sleep Medicine Program, Department of Psychiatry, The School of Nursing, University of Pennsylvania , Philadelphia, PA, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dieter Riemann 11 Department of Psychiatry and Psychotherapy, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg , Germany 12 Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg , Freiburg, Germany PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kai Spiegelhalder 11 Department of Psychiatry and Psychotherapy, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg , Germany MD, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Knut Langsrud 13 Department of Research and Development, St. Olavs University Hospital , Trondheim, Norway MD, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Håvard Kallestad 13 Department of Research and Development, St. Olavs University Hospital , Trondheim, Norway 14 Department of Mental Health, Norwegian University of Science and Technology , Trondheim, Norway PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elisabeth Hertenstein 2 Faculty of Medicine, Department of Psychiatry, University of Geneva , Geneva, Switzerland PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF ABSTRACT Background Insomnia is a highly prevalent and debilitating sleep-wake disorder, with growing evidence indicating that it is an independent risk factor for suicidal ideation and behaviors. Cognitive behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for chronic insomnia. However, its effect on suicidal ideation and behaviors in those with insomnia has not been well-characterized. Thus, the aim of the planned meta-analysis is to quantify the effects of CBT-I on suicidal ideation, suicidal behaviors and suicide deaths in adults with insomnia with and without comorbidities. Methods The planned study will include randomized controlled trials (RCTs) comparing CBT-I with a control condition with no presumed strong effect on insomnia in individuals with insomnia according to standardized diagnostic criteria or a clinically relevant screening score. Both published and unpublished RCTs will be retrieved through a systematic search in major databases and trial registries. The primary outcomes include 1) suicidal ideation, 2) suicidal behaviors, and 3) suicide deaths, assessed post-treatment and at follow-ups. We will only consider RCTs reporting suicide-related outcomes and/or enrolling participants with suicidal ideation or behaviors. For continuous data, a random-effects meta-analysis will be conducted to estimate (standardized) mean differences. In the case of categorical data, a random-effects logistic regression meta-analysis model will be used. The risk of bias of the primary outcomes will be evaluated using the Cochrane Risk of Bias 2 tool. The certainty of evidence will be assessed using GRADE. All analyses will be conducted in the R software. Discussion The planned meta-analysis will provide a synthesis of the effects of CBT-I on suicide-related outcomes in individuals with insomnia. The findings could have important implications for integrating sleep-focused interventions into suicide prevention strategies and inform clinical practice, particularly for individuals with comorbid insomnia and increased suicide risk. Systematic review registration PROSPERO-ID CRD420250628820 Review question How effective is cognitive behavioral therapy for insomnia (CBT-I) in reducing suicidal ideation, suicidal behaviors and suicide deaths among adults with insomnia with and without comorbidities? Background Insomnia is a highly prevalent and debilitating sleep-wake disorder, affecting approximately 1 in 10 individuals in the general population ( 1 ). It is associated with reduced health-related quality of life ( 2 ), impaired work productivity ( 3 ) and an increased risk of developing psychiatric disorders ( 4 ). Accumulating evidence indicates that insomnia is also a significant risk factor for suicidal ideation and behaviors across various age groups ( 5 – 10 ). Thus, the effective treatment of insomnia is of high public health importance. Cognitive behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for chronic insomnia among adults ( 11 ). Recent meta-analyses have shown that CBT-I is effective for the treatment of insomnia in individuals with comorbid mental health and alcohol use disorders ( 12 – 14 ), where insomnia can exacerbate symptoms and increase the risk of relapse ( 15 , 16 ). While CBT-I may reduce comorbid symptom severity ( 12 ), there is a paucity of evidence synthesis addressing whether CBT-I may also reduce suicidal ideation and behaviors. Since 2010, there has been a call to action to evaluate sleep interventions as a strategy for suicide prevention ( 17 ). There has been a slow but steady response to this call, with initial observational studies suggesting that CBT-I may reduce suicidal ideation ( 18 , 19 ). In recent years, CBT-I has gained momentum through several randomized controlled trials contributing to the evidence base ( 20 – 24 ). Although the latest meta-analysis reported a modest effect of sleep interventions (including behavioral and pharmacological treatments) in reducing suicidal ideation, the findings were limited by substantial variability among the relatively few included studies ( 25 ). The planned meta-analysis aims to expand upon this work by updating the evidence with newly published studies, incorporating unpublished data, and narrowing the focus to CBT-I. Specifically, we aim to quantify the effects of CBT-I, compared with control conditions, on suicidal ideation, suicidal behaviors and suicide deaths among adults with insomnia with and without comorbidities. Methods The information in this protocol is reported in accordance with the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) ( 26 , 27 ). The completed PRISMA-P checklist is provided in Supplement 1 . The protocol was prospectively registered on PROSPERO (CRD420250628820). Study selection and selection criteria Two reviewers will independently screen the titles and abstracts of all studies, and will retrieve and review full-text reports of potentially relevant studies to determine their eligibility. We will include published and unpublished records reporting on randomized controlled trials (RCTs) that compare CBT-I in any delivery format to control conditions with no presumed strong effect on insomnia (i.e., placebo, sleep hygiene, self-help, waitlist, no treatment) in parallel-group designs. CBT-I must include stimulus control or sleep restriction as behavioral components, in accordance with recent network meta-analyses identifying these as critical components ( 28 , 29 ). CBT-I may be combined with other treatments (e.g., specific to a psychiatric disorder), provided that the control group receives the same treatment. We will consider adults (≥ 18 years) of any gender with insomnia with or without comorbidity according to diagnostic criteria (i.e., the Diagnostic and Statistical Manual of Mental Disorders ( 30 , 31 ), the International Classification of Sleep Disorders ( 32 ) or Diseases ( 33 , 34 )), or a validated, clinically meaningful screening score. We will only consider studies reporting suicide-related outcomes and/or enrolling participants with suicidal ideation or behaviors. Disagreements regarding study selection will be resolved by consensus or, if necessary, with the involvement of another member of the review team. Search strategy The following databases and registers were systematically searched to identify records published from inception through 21/03/2025: Medline, Embase, Cochrane Library, PsycInfo and ClinicalTrials.gov. No language restrictions were applied. An RCT filter was applied to all databases except the Cochrane Library. The search will be complemented by screening the reference lists of the included studies and of relevant systematic reviews on this topic ( 25 , 35 ). Additionally, forward citation searches (i.e., identifying studies that have cited the included studies and relevant systematic reviews on this topic) will be performed to capture any further eligible records. Search strings and the number of hits for each database/register are provided in Supplement 2 . Primary and secondary outcomes The primary outcomes include suicidal ideation, suicidal behaviors and suicide deaths, assessed post-treatment and at follow-up(s). The secondary outcomes include insomnia severity, also measured post-treatment and at follow-up(s), as well as depression severity and hopelessness which are key correlates of suicidal ideation, behaviors and suicide deaths ( 36 ). Based on preliminary searches, both the primary and secondary outcomes (with the exception of suicide deaths) are commonly measured using continuous outcome measures. Thus, continuous data will be prioritized over categorical data in the analyses. Record management Records will first be imported into EndNote (Clarivate, Version 21, 2023) ( 37 ) and deduplicated using the software’s built-in functions. The deduplicated records will then be exported from EndNote to an Excel spreadsheet for formal screening. Records will initially be coded as clearly irrelevant (excluded prior to full-text review based on title and/or abstract) or potentially relevant (proceeding to full-text review). Following full-text review, potentially relevant records will be coded as either included or excluded, with reasons documented for each exclusion. Data extraction Two reviewers will independently extract data from all included trials for the following variables: authors, year of publication, number of participants in the CBT-I/control groups at each timepoint, age of participants at baseline, percentage of women at baseline, race/ethnicity, number of follow-up assessments, time between baseline and each follow-up, criteria for insomnia, outcome measures, CBT-I components, number of CBT-I sessions, treatment duration, and details regarding control conditions. This information will be summarized narratively in the text and/or presented in tabular form. Outcome data will be extracted independently by two reviewers using a pre-defined Excel sheet for the meta-analyses. Depending on the frequency of continuous versus categorical data reporting, we may opt to harmonize the data to enhance statistical power and reduce the number of analyses by reaching out to study authors. For instance, if most studies reported continuous data and it is feasible to obtain continuous data from studies that reported categorical data (e.g., those that transformed continuous data into binary outcomes using cut-off scores), we will request these data from the principal investigators. Principal investigators of both unpublished and published studies will be contacted up to three times, with a two-week interval between each attempt, to request unpublished data or address other relevant inquiries. Statistical analysis For pairwise comparisons informed by ≥ 3 RCTs, we will perform a meta-analysis if the RCTs are sufficiently homogeneous with respect to design and comparator. For continuous data, mean differences (MDs) or standardized mean differences (SMDs), along with 95% confidence intervals (CIs), between the CBT-I group versus control groups will be calculated for the outcomes post-treatment and at follow-up(s). MDs will be used when all studies measured an outcome on the same scale, while SMDs will be used when multiple scales are used across studies. In the case of SMDs, Hedges’ g will be used as a measure of effect size. We will rely on post- and (follow-up-) means, instead of a change score between baseline and post-(and follow-up-) means. Based on the assumption that there is a distribution of true effect sizes rather than a single true effect size, a random-effects model will be used when pooling the primary studies, in line with the recommendation by Borenstein et al. (2010) ( 38 ). Forest plots will be presented to visualize the results. The degree of heterogeneity between studies will be assessed using I 2 , which describes the proportion of total variation in estimated effect sizes attributable to differences among the studies. An I 2 value of 50% or higher is commonly considered an indicator of heterogeneity. As an additional measure of heterogeneity and to estimate the range of effect sizes in future studies, corresponding 95% prediction intervals will be calculated ( 39 , 40 ). For categorical data (yes/no), odds ratios (ORs) and 95% CIs will be estimated using a random-effects logistic regression model. Suicide-related outcomes, particularly suicide deaths, are expected to be rare (i.e., low counts). For rare events, the Mantel-Haenszel method will be used, which avoids continuity corrections that might bias results ( 41 , 42 ). To evaluate the robustness of the results, we will compare the results of the inverse variance model (which assumes a common treatment effect) and those of the Mantel-Haenszel method. If notable discrepancies arise between the methods, only the Mantel-Haenszel method will be used. Forest plots will be used for the visualization of the results, applying a 0.5 continuity correction for studies with zero events in one treatment arm. We will report the I 2 statistic, along with its 95% CI, as an indicator of heterogeneity for all analyses. Prediction intervals will be calculated as an additional indicator for the degree of heterogeneity and to estimate the effect size range in future studies ( 39 , 40 ). All analyses will be conducted in R using the meta package ( 43 ). Although we anticipate conducting meta-analyses for the primary and secondary outcomes, we will provide a systematic narrative synthesis if quantitative synthesis is not appropriate (e.g., due to insufficient data). Information will be presented in the text and in tabular form to summarize and explain the characteristics and findings of the included studies. The narrative synthesis will assess the relationships and results within and between the included studies Subgroup analyses Assuming that sufficient data are available, meta-regression will be used to explore potential subgroup differences based on study characteristics, including age group, psychiatric comorbidities, CBT-I delivery format (e.g., in-person vs. digital) and treatment setting (e.g., outpatient vs. inpatient). Sensitivity analyses To assess the robustness of all synthesized results, we will conduct sensitivity analyses excluding studies at high overall risk of bias. Publication bias Provided that ≥ 10 studies are included ( 44 ), the presence of potential publication bias (or ‘small-study effects’) will be assessed by examining asymmetry in a contour-enhanced funnel plot ( 45 ) using the primary outcomes. Risk of bias Two reviewers will independently assess the risk of bias of the primary outcomes in each study using the Cochrane Risk of Bias 2 (RoB 2) tool ( 46 ). The assessment will cover the following domains: bias arising from the randomization process, bias due to deviations from the intended interventions, bias due to missing outcome data, bias in measurement of the outcome, and bias in selection of the reported result. Each domain will be rated as “low risk of bias”, “some concerns”, or “high risk of bias”. The overall risk of bias of each primary outcome will be determined by the least favorable rating among the domains. The assessments will be managed using the RoB 2 Excel tool. Disagreements will be resolved by consensus or, if necessary, with the involvement of another member of the review team. Certainty of evidence Two reviewers will independently assess the certainty of the evidence for the primary outcomes using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach ( 47 ). Based on GRADE guidelines ( 48 ), the following factors will be considered: 1) risk of bias (study limitations), 2) inconsistency of results (heterogeneity in the meta-analysis), 3) indirectness (relevance to the research question), 4) imprecision (small sample sizes, wide CIs), and 5) publication bias. The certainty in the body of evidence will be rated as high, moderate, low or very low. Justifications will be provided for decisions to downgrade or upgrade the certainty of the evidence, as well as for the importance rating of each outcome. Disagreements will be resolved by consensus or, if necessary, with the involvement of another member of the review team. Discussion The planned meta-analysis will offer a synthesis of the current evidence on the effects of CBT-I on suicide-related outcomes in individuals with insomnia. Given the strong and growing evidence linking insomnia with suicidal ideation and behaviors ( 5 – 10 ), the findings could have important implications for clinical practice and suicide prevention strategies. Notably, CBT-I in digitally delivered formats (digital CBT-I) offers a scalable, low-cost, and accessible alternative to face-to-face CBT-I ( 49 ), making it a promising component of broader public health approaches to suicide prevention. However, it is important to acknowledge that RCTs in this specific area of research have only recently begun to emerge ( 20 ), and the current evidence base may still be limited in both size and scope. As such, the planned meta-analysis may also play a critical role in identifying gaps in the literature, highlighting important methodological considerations, and informing the design of future studies. Beyond its clinical relevance, the review could serve as a foundation for advancing research into the mechanisms underlying the relationship between insomnia and suicidal ideation/behaviors, ultimately contributing to the development of more targeted prevention strategies. Data Availability Not applicable. DECLARATIONS Ethics approval and consent to participate The planned review does not require ethical approval or consent to participate. Consent for publication The planned review will not incorporate any individual person’s data in any form. Thus, consent for publication is not required. The findings will be published in a peer-reviewed journal and may be presented at international conferences. Availability of data and materials Not applicable. Competing interests WM s a scientific advisor and receives honoraria or equity options from Idorsia, Haleon, LivaNova, Axon Medical Technologies, AlzaTV, and Carelon. The other authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions CT, the guarantor of the review, conceived the study and wrote the first draft of the protocol. All authors contributed to the study design and provided intellectual input on the first draft. All authors approved the final version of the protocol to be published. Acknowledgements We thank the librarian Dipl.-Bibl. Volker Braun from the Library of the Medical Faculty Mannheim, University of Heidelberg, for his assistance in developing the systematic search strategy and managing the records. We also extend our gratitude to the Central Institute of Mental Health in Mannheim, Germany, for supporting this work through institutional open access funding. 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