Modeling the Reduction of Attrition in Campus Mental Health Services: A Discrete Choice Conjoint Experiment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A significant percentage of college students discontinue mental health treatment prematurely. Using a discrete choice experiment, 909 students chose between experimentally manipulated descriptions of mental health services, selecting the option that would encourage them to stay in treatment. Latent class analysis identified three groups. The community class (36.7%) would remain in treatment at community walk-in clinics. The campus class (27.3%) would be more likely to remain in an on-campus student health service. The residence class, 36.0% of participants, would be most likely to remain in treatments at their residence. All classes would be more likely to remain in services including the option of medication, psychotherapy, or alternative treatments such as diet and exercise. Simulations predicted that most students would trade individual treatment for more cost-effective groups if students who had experienced mental health problems recommended these services and access to text messages and telephone help was included.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it