Motive-Oriented, Personalized, Internet-Based Interventions for Depression: Nonclinical Experimental Study
Bibliographic record
Abstract
BACKGROUND: The low level of adherence in internet-based self-help interventions for depression suggests that in many existing programs, the motivational fit between the program and the user is unsatisfactory (eg, the user seeks autonomy, but the program provides directive guidance). Personalized, motive-oriented, self-help interventions could enable participants who interact with a program and its contents to have more engaging and less aversive experiences and thus increase adherence. OBJECTIVE: In an experimental study with a nonclinical analogue sample, we aimed to test the hypotheses that a better motivational person-program fit is linked with higher anticipated adherence, working alliance, and satisfaction with the program. METHODS: Motivational person-program fit was examined with respect to the 2 contrasting motives being autonomous and being supported. The hypotheses were tested by specifically varying the motivational person-program fit in a nonclinical sample (N=55), where participants were asked to work on, and subsequently evaluate, a limited set of individual pages of a self-help program with guidance (in the form of text messages) for depression. The sections of the self-help program were redesigned to either particularly address the autonomy motive or the support motive. For the quasi-experimental variation of the motivational person-program characteristics, we divided the 55 participants into 2 groups (autonomy group: n=27, 49%; support group: n=28, 51%) by screening method (using the Inventory of Approach and Avoidance Motivation), corresponding to the 2 motives. Both groups evaluated (in randomized order) 2 excerpts of the program-one that matched their motive (fit) and one that was contrary to it (no fit). Immediately after the evaluation of each excerpt, anticipated adherence, working alliance, and treatment satisfaction were assessed. RESULTS: =2.86; P=.008) than a noncongruent fit. However, a similar impact could not be found for the motive being autonomous. Several correlations were found that supported our hypotheses (eg, for the congruent person-program fit autonomy motive and autonomy group, support satisfaction negatively correlated with optimal anticipated adherence). CONCLUSIONS: This first experimental study gives reason to assume that motive orientation may have a positive influence on adherence, working alliance, and satisfaction in internet-based self-help interventions for depression and other mental disorders. Future studies should conduct randomized controlled trials with clinical samples and assess clinical outcomes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".