Using network intervention analysis to explore associations between participant expectations of and difficulties with cognitive behavioural therapy for insomnia and clinical outcome: A proof of principle study. (April 2022)

• Record Type: Journal Article
• Authors: Scott, Jan; Vedaa, Øystein; Sivertsen, Børge; Langsrud, Knut; Kallestad, Havard
• Is Part Of: Journal of psychiatric research. Volume 148(2022)
• Page Start: 73
• Page End: 83
• Publication Date: 2022-04
• Subjects: CBT-I -- Response -- Predictors -- Network analysis -- Expectations -- Sleep restriction -- Components -- Dismantling -- Digital; Psychiatry -- Periodicals; Mental Disorders -- Periodicals; Maladies mentales -- Périodiques; Psychiatry; Electronic journals; Periodicals; 616.89005
• DOI: 10.1016/j.jpsychires.2022.01.054
• Languages: English
• ISSNs: 0022-3956

Abstract

Abstract: Background: Research about predictors of response to cognitive behaviour therapy for insomnia (CBT-I) is ongoing. We examined any whether pre-intervention expectations or post-intervention appraisals of difficulties in utilizing face to face (FtF) or digital (dCBT-I) versions of the therapy were associated with outcome. Methods: Self-rating data were extracted on 101 adult participants in a recent randomized controlled trial of FtF versus dCBT-I. Network intervention analyses were used to explore any associations between expectations of CBT-I at response at 9 weeks and between post-intervention ratings of difficulties, modality of therapy and response at 9-weeks and at 6-months. Results: Anticipated and actual difficulties in employing sleep restriction techniques predicted response in all network models. Modality of therapy played a more overt role in the 9-week outcome network, with FtF therapy more robustly associated with response. However, the direct association between FtF therapy and response was not found in the 6-month outcome network. Notable predictors of poor outcome at 9-weeks and 6-month follow-up were difficulties in accommodating CBT-I into work and daily routines and applying the rules of CBT-I. Conclusions: This network intervention analysis highlights that self-confidence and ability in undertaking sleep restriction is a key active ingredient of CBT-I. Also, benefits and gains from access to the FtF version of this multi-component therapy were more apparent in the short than the longer term. However, it is important that findings from this proof of principle study are confirmed in further studies. Highlights: Dynamic analytic models may shed light on the active ingredients of multi-component therapies. We employed network intervention analysis to examine self-rated expectations and difficulties with using cognitive behaviour therapy for insomnia (CBT-I). We identified that expectations and difficulties in using sleep restriction techniques were related to response to CBT-I. Individuals receiving face to face rather than digital CBT-I self-reported fewer difficulties in following therapy rules.