Pilot Study of Impact of Medical-Legal Partnership Services on Patients’ Perceived Stress and Wellbeing
Bibliographic record
Abstract
UNLABELLED: Medical-legal partnerships (MLPs) bring legal services into health care settings to address patients' unmet legal needs. This pilot project examined whether MLP services impact patients' perceptions of stress and wellbeing. METHODS: Providers referred patients with legal concerns to the Tucson Family Advocacy Program (TFAP), an MLP within a family medicine clinic. Stress levels and wellbeing were assessed before and after legal services using self-administered 10-item Perceived Stress Scale (PSS-10) and Measure Yourself Concerns and Wellbeing (MYCaW) instruments. RESULTS: Sixty-seven participants completed pre- and post-service questionnaires. Within this group, the mean PSS-10 score decreased 8.1 points. Wellbeing scores improved by 1.8 points. Individual changes in perceived stress were strongly related to participants' level of concern regarding the particular legal issues addressed. CONCLUSIONS: Services in patient-centered medical homes to address unmet legal needs have the potential to reduce perceived stress and improve overall wellbeing. Additional studies concerning MLPs and patient outcomes are needed.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".