Support Strategies to Enhance Adherence in a Prescription Digital Therapeutic for Erectile Dysfunction: Retrospective Quasi-Experimental Cohort Study. (Preprint)
Bibliographic record
Abstract
BACKGROUND: Sustained engagement is a central challenge for digital therapeutics. In routine operations, inactivity-triggered supports (eg, SMS reminders and telephone follow-up) are used to nudge patients back after lapses, but evidence in digital erectile dysfunction (ED) therapy is limited. OBJECTIVE: This study aims to evaluate whether low-threshold support in the form of SMS reminders and structured telephone outreach, both triggered after 7 or more days of inactivity, improves engagement and patient-centered outcomes in a certified German digital health application (Digitale Gesundheitsanwendung [DiGA]) for ED. METHODS: In a pragmatic, calendar-time (rotating-week) quasi-experimental allocation, 470 men with physician-diagnosed ED entered 1 of 3 groups: control (no additional support), SMS (automated reminders), or call (structured telephone contact). Analyses were conducted as assigned. The primary end point was active weeks (number of weeks with ≥1 completed session) during the 12-week study period, derived from app logs with built-in completion rules. A prespecified mechanistic end point captured any reactivation after an inactive week (yes or no). Secondary end points included Clinical Global Impression-Improvement (CGI-I), week-12 5-item International Index of Erectile Function (IIEF-5), intention to continue therapy, and documented continuation ("conversion") within 3 months. Covariate-adjusted models included age, BMI, smoking, and baseline pharmacotherapy; calendar-week sensitivity was planned. RESULTS: Participants completed a mean of 6.34 (SD 4.44) active weeks. Unadjusted means favored both support groups (control: 5.79; call: 6.57; SMS: 6.80); the prespecified SMS-vs-control contrast was nominally significant (P=.049, small effect). In covariate-adjusted models, planned pairwise contrasts were not significant. In a calendar-adjusted sensitivity model, the omnibus group term reached significance, but adjusted pairwise contrasts remained nonsignificant; stricter adherence definitions led to the same overall inference. By contrast, any reactivation after inactivity was more common in the intervention groups than in the control group (omnibus chi-square test P=.008), consistent with the intended mechanism of breaking inactivity spells. The call group showed a higher intention to continue therapy (49% vs 38% in the control arm; P=.04); conversion did not differ. CGI-I and IIEF-5 showed no arm-wise differences over 12 weeks; follow-up availability was limited in routine care. CONCLUSIONS: Inactivity-triggered supports in a real-world ED DiGA reactivated use after lapses, and telephone outreach increased motivation to continue, while effects on weekly dose were small and not significant after adjustment, and clinical outcomes did not differ over 12 weeks. Programs may consider a stepped approach (SMS first-line nudge and call as escalation) and target system bottlenecks that decouple motivation from realized continuation. Further work should test longer-term outcomes, targeting, and generalizability.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".