Patient and Therapist Expectations for a Blended Cognitive Behavioral Therapy Program for Depression: Qualitative Exploratory Study
Bibliographic record
Abstract
BACKGROUND: Blended cognitive behavioral therapy (bCBT)-the combination of digital elements and face-to-face psychotherapy-has been proposed to alleviate challenges that patients and therapists face in conventional cognitive behavioral therapy. There is growing evidence that adding digital elements to face-to-face psychotherapy can contribute to better treatment outcomes. However, bCBT programs still show considerable shortcomings, and knowledge on how to improve digital apps using a bCBT protocol is limited. OBJECTIVE: This study aimed to inductively identify functions and qualities that are expected from a bCBT treatment for depression in the eyes of patients and psychotherapists who were not currently receiving or practicing bCBT treatment. METHODS: We used a qualitative exploratory study design and conducted 3 focus group interviews (n=6 in each) and 5 semistructured in-depth interviews with therapists as well as 11 individual interviews with patients with a primary diagnosis of depression and currently undergoing cognitive behavioral therapy treatment in Germany. Themes and categories were established inductively from transcribed interview records based on a rigorous coding method. RESULTS: Both therapists and patients expected a digital app to provide patients with the opportunity to track their mood, work on therapeutic homework activities, easily access an intervention set for harder moments, and efficiently facilitate administrative tasks. The desire to be able to customize bCBT protocols to individual patient circumstances was evident in both patient and therapist interviews. Patients differed with respect to what content and the amount of material the app should focus on as well as the method of recording experiences. Therapists viewed digital apps as potentially aiding in their documentation work outside of sessions. Different attitudes surfaced on the topic of data security, with patients not as concerned as therapists. CONCLUSIONS: Both patients and therapists had substantially positive attitudes toward the option of an integrated bCBT treatment. Our study presents novel findings on the expectations and attitudes of patients and therapists.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".