Home-Based Telemental Health: A Proposed Privacy and Safety Protocol and Tool
Bibliographic record
Abstract
Objectives: To describe the development of a protocol and practical tool for the safe delivery of telemental health (TMH) services to the home. The COVID-19 pandemic forced providers to rapidly transition their outpatient practices to home-based TMH (HB-TMH) without existing protocols or tools to guide them. This experience underscored the need for a standardized privacy and safety tool as HB-TMH is expected to continue as a resource during future crises as well as to become a component of the routine mental health care landscape. Methods: The authors represent a subset of the Child and Adolescent Psychiatry Telemental Health Consortium. They met weekly through videoconferencing to review published safety standards of care, existing TMH guidelines for clinic-based and home-based services, and their own institutional protocols. They agreed on three domains foundational to the delivery of HB-TMH: environmental safety, clinical safety, and disposition planning. Through multiple iterations, they agreed upon a final Privacy and Safety Protocol for HB-TMH. The protocol was then operationalized into the Privacy and Safety Assessment Tool (PSA Tool) based on two keystone medical safety constructs: the World Health Organization (WHO) Surgical Safety Checklist/Time-Out and the Checklist Manifesto. Results: The PSA Tool comprised four modules: (1) Screening for Safety for HB-TMH ; (2) Assessment for Safety During the HB-TMH Initial Visit ; (3) End of the Initial Visit and Disposition Planning; and (4) the TMH Time-Out and Reassessment during subsequent visits. A sample workflow guides implementation. Conclusions: The Privacy and Safety Protocol and PSA Tool aim to prepare providers for the private and safe delivery of HB-TMH. Its modular format can be adapted to each site's resources. Going forward, the PSA Tool should help to facilitate the integration of HB-TMH into the routine mental health care landscape.
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.
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 | 0.236 | 0.154 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".