Association Between Care Modality and Use With Treatment Response Among Members Accessing Virtual Mental Health Services: Real-world Observational Study
Bibliographic record
Abstract
BACKGROUND: There is a growing bottleneck in mental health care, as the demand for services has outpaced the availability of mental health professionals. Consequently, many health systems have shifted to teletherapy as a scalable approach to increasing accessibility to care. Within these care models, various treatment modalities (eg, coaching and clinical care) are used to deliver support for anxiety and depression. However, more research is needed to better understand the differences in treatment responses. OBJECTIVE: The purpose of this study was to examine the association between different care modalities and the levels of use with symptom score changes for members seeking virtual care services. METHODS: We conducted an observational study of 4219 members who accessed Ginger, an on-demand mental health service, between September 2020 and September 2021. Using a mobile app, members can access text-based behavioral health coaching and virtual clinical services. This study focused on members with clinically elevated depression or anxiety levels at baseline. Logistic regressions were used to assess the association between care modalities and the levels of use with treatment response in depression and anxiety, using the Patient Health Questionnaire and Generalized Anxiety Disorder Assessment, respectively. RESULTS: Of the 4219 members, 1623 (38.47%) demonstrated a full response to depression, and 1684 (39.91%) demonstrated a full response to anxiety. Members who completed care (ie, text-based coaching, virtual clinical therapy, hybrid of coaching, and clinical care) beyond the introductory session showed significantly increased odds of a full response compared with those who completed only limited care. Members who completed a hybrid of care had the highest odds of improvement; the odds of showing a full response in depression were 2.31 times higher (95% CI 1.91-2.80; P<.001) and in anxiety were 2.23 times higher (95% CI 1.84-2.70; P<.001) compared with members who completed limited care. For members who completed only coaching or clinical care, the largest effects were observed among those with high use. For members who completed a hybrid care program, we observed similar treatment responses across all levels of use. CONCLUSIONS: Our real-world study found that members who completed text-based coaching achieved full treatment responses at similar rates compared with members who completed virtual clinical care and members who completed a hybrid of care. There were no significant differences in the predicted probabilities of full treatment response between coaching and clinical care. Generally, the odds for a full response were highest among members with high use within each care modality; however, there were no differences in full-response treatment odds across levels of use with hybrid care. The results support the utility of digital behavioral health interventions and further highlight text-based coaching protocols as an accessible and suitable option when considering virtual care for treating anxiety and depression.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".