biostudies-literatureUnknown10Krakowczyk JB<h4>Background</h4>Make It Training is an e-mental health intervention designed for individuals with cancer that aims to reduce psychological distress and improve disease-related coping and quality of life.<h4>Objective</h4>This study evaluated the experienced usefulness and usability of the web-based Make It Training intervention using a qualitative approach.<h4>Methods</h4>In this study, semistructured interviews were conducted with participants at different cancer stages and with different cancer entities. All participants had previously taken part in the Reduct trial, a randomized controlled trial that assessed the efficacy of the Make It Training intervention. The data were coded deductively by 2 independent researchers and analyzed iteratively using thematic codebook analysis.<h4>ResJMIR cancere53117https://www.ebi.ac.uk/biostudies/studies/S-EPMC11040444biostudies-literatureEvaluation of the e-Mental Health Intervention Make It Training From Patients' Perspectives: Qualitative Analysis Within the Reduct Trial.PMC11040444Heinen JKrakowczyk JBGraf JTruijens FSchug CLalgi TErim YTeufel MPantforder MBauerle AfalseEvaluation of the e-Mental Health Intervention Make It Training From Patients' Perspectives: Qualitative Analysis Within the Reduct Trial.<h4>Background</h4>Make It Training is an e-mental health intervention designed for individuals with cancer that aims to reduce psychological distress and improve disease-related coping and quality of life.<h4>Objective</h4>This study evaluated the experienced usefulness and usability of the web-based Make It Training intervention using a qualitative approach.<h4>Methods</h4>In this study, semistructured interviews were conducted with participants at different cancer stages and with different cancer entities. All participants had previously taken part in the Reduct trial, a randomized controlled trial that assessed the efficacy of the Make It Training intervention. The data were coded deductively by 2 independent researchers and analyzed iteratively using thematic codebook analysis.<h4>Res2024-01-01T00:00:00Z2024 Apr2025-04-22T20:44:57.491Z2025-04-06T03:11:57.092ZS-EPMC110404443859276410.2196/53117