Background The digital transformation of obesity therapy introduces new demands on exercise therapists. Yet, the therefore required competences remain mostly unassessed, hindering effective implementation. To address this gap, valid instruments are needed to identify competences to plan and implement digital obesity exercise therapy and inform targeted professional training programs. The DigCompThExO model provides a conceptual framework and accompanying questionnaire but has not yet been validated. Therefore, this study examines the factorial structure and psychometric properties to enable its diagnostic use. Methods To address the research gap, two consecutive studies were conducted. Study 1 assessed content validity through cognitive interviews with German-speaking digital obesity exercise therapists, using Tourangeau-based probing. Study 2 evaluated structural validity via confirmatory factor analysis (CFA) based on revised questionnaire data from a separate sample within the same target group. Model fit (CFI, TLI, RMSEA, SRMR), validity (AVE, HTMT), reliability (CR), and measurement invariance were evaluated. Results Study 1 involved ten therapists (Age: M = 39.3, SD = 10.67, 50% female) in cognitive interviews. Based on results, one dimension and one item were removed; scaling and wording were refined. In Study 2, 205 therapists (Age: M = 32.34, SD = 5.9, 47.3% female, 0.5% divers) completed the revised questionnaire. CFA revealed four latent factors, with good model fit CFI = .964; TLI = .953; RMSEA = .070, 90% CI (.049;.090); SRMR = .051. Regarding validity and reliability, measurement invariance was confirmed (RMSEA .069), along with convergent validity (AVE .50), discriminant validity (HTMT .85), and internal consistencies (all CR .70). Conclusion Cognitive interviews and CFA confirm reliability, construct validity, and practical relevance of the DigCompThExO for digital obesity exercise therapy. It enables the assessment of existing and required digital competences and may guide the development of tailored training programs. If embedded in institutional medical education (e.g., university), this could enhance quality and effectiveness of digital obesity exercise therapy. Further research should explore the tool's applicability in other domains of obesity therapy (e.g., nutrition, behavior) or chronic conditions (e.g., diabetes) to promote digital, location-independent healthcare.
Pawellek et al. (Mon,) studied this question.