Tarnai, Kathryn A; Miller, Christopher B; Magill, Nicholas; Emsley, Richard; Robinson, Will; Kyle, Simon D; McGrath, Emer R; Espie, Colin A; Henry, Alasdair L; (2025) Efficacy of digital cognitive behavioral therapy for treating insomnia in adults aged 65 and older: a secondary analysis using individual participant data from three randomized controlled trials. Aging & mental health. pp. 1-7. ISSN 1360-7863 DOI: https://doi.org/10.1080/13607863.2025.2480124 (In Press)
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Abstract
Objectives: Insomnia prevalence increases with age. Although cognitive behavioral therapy (CBT) for insomnia is the first-line treatment, limited accessibility leaves many older adults with few effective treatment options. This study assessed the efficacy of digital CBT (dCBT) for treating insomnia, anxiety, and depression symptoms in adults aged 65 and older. Method: Data from three published randomized controlled trials of dCBT for insomnia (Sleepio) versus controls were combined for those aged 65+ with insomnia disorder (N = 315). Insomnia, anxiety, and depression scores were standardized into z-scores for comparison. Mixed-effects models estimated the treatment effect on insomnia, depression, and anxiety outcomes at post-treatment (8–10 wk) and follow-up (24 wk). Chi-squared tests of Sleep Condition Indicator (SCI-8) scores evaluated post-treatment insomnia remission rates between groups. Results: Compared with controls, dCBT generated significantly greater improvements at post-treatment and follow-up in insomnia (gs ≤ −1.88, ps < 0.001) and depression (gs ≤ −0.44, ps ≤ 0.001) and significantly greater improvements in anxiety at post-treatment (g = −0.33, p < 0.001). dCBT generated higher post-treatment insomnia remission rates (60% vs. 16%, p < 0.001). Conclusion: dCBT can effectively improve symptoms of insomnia, anxiety, and depression in adults aged 65+. Digital CBT may serve as an accessible means for older adults to receive guideline-concordant treatment at scale and avoid adverse side effects from common pharmacologic interventions.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Medical Statistics |
Elements ID | 239778 |
Official URL | https://doi.org/10.1080/13607863.2025.2480124 |
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