The acceptability of digital cognitive behavioural therapy for insomnia interventions: A mixed methods systematic review

Digital cognitive behavioural therapy for insomnia (dCBT-I) is a promising solution to the widely recognised lack of access to CBT-I treatments. Although dCBT-I has been found to be effective, it is unclear how acceptable it is by recipients. This mixed-methods systematic review aimed to explore the acceptability of dCBT-I interventions by integrating a range of acceptability data from across quantitative, qualitative and mixed-methods studies. PsycINFO, EMBASE, MEDLINE, CINAHL Plus and CENTRAL were systematically searched, yielding 2347 unique citations from which 68 studies were included in the review. Thirty-three studies only reported proxy measures of acceptability, the results of which were extremely varied across studies. Six interrelated themes were identified from acceptability data extracted from the remaining 35 studies, derived from n = 2497 participants: general acceptability, perceived helpfulness, individualised needs, congruence with personal life, functionality, and design. There was a trend towards acceptability across several of the identified themes with evidence showing that dCBT-I interventions are not always congruent with recipients' personal experiences nor allow for tailoring to their individualised needs. Methodological issues with the way acceptability is defined and measured in the literature suggests that improvements are needed to future research design before we can be confident in these findings.

Authors

Institutions

Publication Details

Journal
Sleep Medicine Reviews
Published
2026-03-11
DOI
https://doi.org/10.1016/j.smrv.2026.102279
Primary Topic
Sleep and related disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The acceptability of digital cognitive behavioural therapy for insomnia interventions: A mixed methods systematic review

Breda Cullen, Maria Gardani, Michaela Gilarova, Joseph Lawrence et al.
Sleep Medicine Reviews
Sleep and related disorders
article

The acceptability of digital cognitive behavioural therapy for insomnia interventions: A mixed methods systematic review

Breda Cullen, Maria Gardani, Michaela Gilarova, Joseph Lawrence, Nikki Thomson
article en

Abstract

Digital cognitive behavioural therapy for insomnia (dCBT-I) is a promising solution to the widely recognised lack of access to CBT-I treatments. Although dCBT-I has been found to be effective, it is unclear how acceptable it is by recipients. This mixed-methods systematic review aimed to explore the acceptability of dCBT-I interventions by integrating a range of acceptability data from across quantitative, qualitative and mixed-methods studies. PsycINFO, EMBASE, MEDLINE, CINAHL Plus and CENTRAL were systematically searched, yielding 2347 unique citations from which 68 studies were included in the review. Thirty-three studies only reported proxy measures of acceptability, the results of which were extremely varied across studies. Six interrelated themes were identified from acceptability data extracted from the remaining 35 studies, derived from n = 2497 participants: general acceptability, perceived helpfulness, individualised needs, congruence with personal life, functionality, and design. There was a trend towards acceptability across several of the identified themes with evidence showing that dCBT-I interventions are not always congruent with recipients' personal experiences nor allow for tailoring to their individualised needs. Methodological issues with the way acceptability is defined and measured in the literature suggests that improvements are needed to future research design before we can be confident in these findings.

Sleep Medicine ReviewsVol. 87
Universidad Mariana (CO), Advanced Manufacturing Research Centre (GB), University of Glasgow (GB)
Openalex Percentile: Top 31%
Sleep and related disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.