Susanne Edelbluth, Jan Philipp Klein, Brian Schwartz, Miriam Hehlmann, Alice Arndt, Julian Rubel, Danilo Moggia, Thomas Berger, Björn Meyer, Steffen Moritz, Johanna Schröder, Wolfgang Lutz
{"title":"早期改变模式的长影:使用网络干预轻度至中度抑郁症状后的 3 年随访。","authors":"Susanne Edelbluth, Jan Philipp Klein, Brian Schwartz, Miriam Hehlmann, Alice Arndt, Julian Rubel, Danilo Moggia, Thomas Berger, Björn Meyer, Steffen Moritz, Johanna Schröder, Wolfgang Lutz","doi":"10.1080/16506073.2024.2368520","DOIUrl":null,"url":null,"abstract":"<p><p>Web-based interventions can be effective in treating depressive symptoms. Patients with risk not responding to treatment have been identified by early change patterns. This study aims to examine whether early changes are superior to baseline parameters in predicting long-term outcome. In a randomized clinical trial with 409 individuals experiencing mild to moderate depressive symptoms using the web-based intervention deprexis, three latent classes were identified (early response after registration, early response after screening and early deterioration) based on early change in the first four weeks of the intervention. Baseline variables and these classes were included in a Stepwise Cox Proportional Hazard Multiple Regression to identify predictors associated with the onset of remission over 36-months. Early change class was a significant predictor of remission over 36 months. Compared to early deterioration after screening, both early response after registration and after screening were associated with a higher likelihood of remission. In sensitivity and secondary analyses, only change class consistently emerged as a predictor of long-term outcome. Early improvement in depression symptoms predicted long-term outcome and those showing early improvement had a higher likelihood of long-term remission. These findings suggest that early changes might be a robust predictor for long-term outcome beyond baseline parameters.</p>","PeriodicalId":10535,"journal":{"name":"Cognitive Behaviour Therapy","volume":" ","pages":"681-700"},"PeriodicalIF":4.3000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The long shadow of early-change patterns: a 3-year follow-up after the use of a web-based intervention for mild to moderate depressive symptoms.\",\"authors\":\"Susanne Edelbluth, Jan Philipp Klein, Brian Schwartz, Miriam Hehlmann, Alice Arndt, Julian Rubel, Danilo Moggia, Thomas Berger, Björn Meyer, Steffen Moritz, Johanna Schröder, Wolfgang Lutz\",\"doi\":\"10.1080/16506073.2024.2368520\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Web-based interventions can be effective in treating depressive symptoms. Patients with risk not responding to treatment have been identified by early change patterns. This study aims to examine whether early changes are superior to baseline parameters in predicting long-term outcome. In a randomized clinical trial with 409 individuals experiencing mild to moderate depressive symptoms using the web-based intervention deprexis, three latent classes were identified (early response after registration, early response after screening and early deterioration) based on early change in the first four weeks of the intervention. Baseline variables and these classes were included in a Stepwise Cox Proportional Hazard Multiple Regression to identify predictors associated with the onset of remission over 36-months. Early change class was a significant predictor of remission over 36 months. Compared to early deterioration after screening, both early response after registration and after screening were associated with a higher likelihood of remission. In sensitivity and secondary analyses, only change class consistently emerged as a predictor of long-term outcome. Early improvement in depression symptoms predicted long-term outcome and those showing early improvement had a higher likelihood of long-term remission. 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The long shadow of early-change patterns: a 3-year follow-up after the use of a web-based intervention for mild to moderate depressive symptoms.
Web-based interventions can be effective in treating depressive symptoms. Patients with risk not responding to treatment have been identified by early change patterns. This study aims to examine whether early changes are superior to baseline parameters in predicting long-term outcome. In a randomized clinical trial with 409 individuals experiencing mild to moderate depressive symptoms using the web-based intervention deprexis, three latent classes were identified (early response after registration, early response after screening and early deterioration) based on early change in the first four weeks of the intervention. Baseline variables and these classes were included in a Stepwise Cox Proportional Hazard Multiple Regression to identify predictors associated with the onset of remission over 36-months. Early change class was a significant predictor of remission over 36 months. Compared to early deterioration after screening, both early response after registration and after screening were associated with a higher likelihood of remission. In sensitivity and secondary analyses, only change class consistently emerged as a predictor of long-term outcome. Early improvement in depression symptoms predicted long-term outcome and those showing early improvement had a higher likelihood of long-term remission. These findings suggest that early changes might be a robust predictor for long-term outcome beyond baseline parameters.
期刊介绍:
Cognitive Behaviour Therapy is a peer reviewed, multidisciplinary journal devoted to the application of behavioural and cognitive sciences to clinical psychology and psychotherapy. The journal publishes state-of-the-art scientific articles within: - clinical and health psychology - psychopathology - behavioural medicine - assessment - treatment - theoretical issues pertinent to behavioural, cognitive and combined cognitive behavioural therapies With the number of high quality contributions increasing, the journal has been able to maintain a rapid publication schedule, providing readers with the latest research in the field.