BACKGROUND The demand for mental health treatment is increasing, while the availability of treatment offered remains insufficient to meet rising demand. Alternative solutions need to be explored to enable access to care for patients who cannot participate in traditional psychotherapeutic settings due to common barriers like place of residence, professional obligations, or physical limitations. OBJECTIVE This study aimed to investigate attitudes towards digital psychotherapy, specifically within a digital inpatient-like therapy setting, among psychology and medical students. These students represent the future generation of therapists and possess the educational background necessary to develop innovative ideas to benefit a digital psychotherapeutic setting. METHODS We conducted qualitative, semi-structured interviews with 20 participants (10 psychology students and 10 medical students). The data were analyzed using an inductive, thematic analysis according to the methodology outlined by Braun and Clark. RESULTS The thematic analysis led to a codebook including four overarching categories: (1) evolution of digitalisation in medical practice, (2) future directions for digital psychotherapy, (3) technical framework, and (4) artificial intelligence (AI)-based psychotherapy. CONCLUSIONS In the context of mental health, digital psychotherapy is accepted as a viable option when conventional face-to-face therapy is not possible. The primary concerns were potential impairments in the therapeutic relationship and interaction. AI was rejected as standalone therapy, but considered acceptable as a supplementary tool. Technical problems represent a major obstacle for the consistent and reliable implementation of digital psychotherapy. A successful digital psychotherapeutic concept for inpatient and outpatient settings need to enable a sufficient interpersonal therapeutic relationship situated in a reliable technical framework.
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Rebekka Robitzsch
Tania Lalgi
Alexander Diel
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Robitzsch et al. (Fri,) studied this question.
www.synapsesocial.com/papers/68af59d7ad7bf08b1eade48b — DOI: https://doi.org/10.2196/preprints.82830
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