This review aimed to assess the impact of behavioural therapy for insomnia administered alone (BT-I) or in combination with cognitive techniques (cognitive-behavioural therapy for insomnia, CBT-I) on depressive and fatigue symptoms using network meta-analysis. PubMed, Scopus and Web of Science were searched from 1986 to May 2015. Studies were included if they incorporated sleep restriction, a core technique of BT-I treatment, and an adult insomnia sample, a control group and a standardised measure of depressive and/or fatigue symptoms. Face-to-face, group, self-help and internet therapies were all considered. Forty-seven studies were included in the meta-analysis. Eleven classes of treatment or control conditions were identified in the network. Cohen’s d at 95% confidence interval (CI) was calculated to assess the effect sizes of each treatment class as compared with placebo. Results showed significant effects for individual face-to-face CBT-I on depressive (d= 0.34, 95% CI: 0.06 - 0.63) but not on fatigue symptoms, with high heterogeneity between studies. The source of heterogeneity was not identified even after including sex, age, comorbidity and risk of bias in sensitivity analyses. Findings highlight the need to reduce variability between study methodologies and suggest potential effects of individual face-to-face CBT-I on daytime symptoms.

The effectiveness of behavioural and cognitive behavioural therapies for insomnia on depressive and fatigue symptoms: a systematic review and network meta-analysis / Ballesio, Andrea; Aquino, Maria Raisa Jessica; Feige, Bernd; Johann, Anna; Kyle, Simon D; Spiegelhalder, Kai; Lombardo, Caterina; Rücker, Gerta; Riemann, Dieter; Baglioni, Chiara. - In: SLEEP MEDICINE REVIEWS. - ISSN 1087-0792. - STAMPA. - 37:(2018), pp. 114-129. [10.1016/j.smrv.2017.01.006]

The effectiveness of behavioural and cognitive behavioural therapies for insomnia on depressive and fatigue symptoms: a systematic review and network meta-analysis

BALLESIO, ANDREA;LOMBARDO, Caterina;
2018

Abstract

This review aimed to assess the impact of behavioural therapy for insomnia administered alone (BT-I) or in combination with cognitive techniques (cognitive-behavioural therapy for insomnia, CBT-I) on depressive and fatigue symptoms using network meta-analysis. PubMed, Scopus and Web of Science were searched from 1986 to May 2015. Studies were included if they incorporated sleep restriction, a core technique of BT-I treatment, and an adult insomnia sample, a control group and a standardised measure of depressive and/or fatigue symptoms. Face-to-face, group, self-help and internet therapies were all considered. Forty-seven studies were included in the meta-analysis. Eleven classes of treatment or control conditions were identified in the network. Cohen’s d at 95% confidence interval (CI) was calculated to assess the effect sizes of each treatment class as compared with placebo. Results showed significant effects for individual face-to-face CBT-I on depressive (d= 0.34, 95% CI: 0.06 - 0.63) but not on fatigue symptoms, with high heterogeneity between studies. The source of heterogeneity was not identified even after including sex, age, comorbidity and risk of bias in sensitivity analyses. Findings highlight the need to reduce variability between study methodologies and suggest potential effects of individual face-to-face CBT-I on daytime symptoms.
2018
insomnia; depression; fatigue; CBT; network meta-analysis
01 Pubblicazione su rivista::01a Articolo in rivista
The effectiveness of behavioural and cognitive behavioural therapies for insomnia on depressive and fatigue symptoms: a systematic review and network meta-analysis / Ballesio, Andrea; Aquino, Maria Raisa Jessica; Feige, Bernd; Johann, Anna; Kyle, Simon D; Spiegelhalder, Kai; Lombardo, Caterina; Rücker, Gerta; Riemann, Dieter; Baglioni, Chiara. - In: SLEEP MEDICINE REVIEWS. - ISSN 1087-0792. - STAMPA. - 37:(2018), pp. 114-129. [10.1016/j.smrv.2017.01.006]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/935744
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