Participant Adherence and Contact Behavior in a Guided Internet Intervention for Depressive Symptoms: Exploratory Study
Bibliographic record
Abstract
Background: The number of studies on internet-based guided self-help has rapidly increased during the last 2 decades. Guided self-help comprises 2 components: a self-help program that patients work through and usually weekly guidance from therapists who support patients using the self-management program. Little is known about participants' behavior patterns while interacting with therapists and their use of self-help programs in relation to intervention outcomes. Objective: This exploratory study aimed to investigate whether the number of messages sent to the therapist (ie, contact behavior) is an indicator of the outcome, that is, a reduction in depressive symptoms. Furthermore, we investigated whether adherence was associated with outcome. Most importantly, we investigated whether different combinations of adherence and contact behavior were associated with outcome. Methods: Drawing on a completer sample (n=113) from a randomized full factorial trial, participants were categorized into 4 groups. The groups were based on median splits of 2 variables, that is, the number of messages sent to therapists (low: groups 1 and 2; high: groups 3 and 4) and adherence (low: groups 1 and 3; high: groups 2 and 4). The 4 groups were compared in terms of change in depressive symptoms (measured with the Patient Health Questionnaire-9) from pre- to posttreatment and pretreatment to follow-up, respectively. Results: On average, participants sent 4.5 (SD 3.7) messages to their therapist and completed 18.2 (SD 5.2) pages of the program in 6.39 (SD 5.39) hours. Overall, analyses revealed no main effect for participants' messages (H1=0.18, P=.67) but a significant main effect for adherence on changes in depressive symptoms from pre- to posttreatment (H1=5.10, P=.02). The combined consideration of adherence and messages sent to the therapist revealed group differences from pre- to posttreatment (H3=8.26, P=.04). Group 3 showed a significantly smaller improvement in symptoms compared with group 4 (Z=-2.84, P=.002). Furthermore, there were group differences from pretreatment to follow-up (H3=8.90, P=.03). Again, group 3 showed a significantly smaller improvement in symptoms compared with group 4 (Z=-2.62, P=.004) and group 2 (Z=-2.47, P=.007). All other group comparisons did not yield significant differences. Conclusions: This exploratory study suggests that participants characterized by low adherence and frequent messaging do not improve their symptoms as much as other participants. These participants might require more personalized support beyond the scope of guided internet interventions. The paper underscores the importance of considering individual differences in contact behavior when tailoring interventions. The results should be interpreted with caution and further investigated in future studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".