A Lexicon of Assessment and Outcome Measures for Telemental Health
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
BACKGROUND: The purpose of this document is to provide initial recommendations to telemental health (TMH) professionals for the selection of assessment and outcome measures that best reflect the impacts of mental health treatments delivered via live interactive videoconferencing. MATERIALS AND METHODS: The guidance provided here was created through an expert consensus process and is in the form of a lexicon focused on identified key TMH outcomes. RESULTS: Each lexical item is elucidated by a definition, recommendations for assessment/measurement, and additional commentary on important considerations. The lexicon is not intended as a current literature review of the field, but rather as a resource to foster increased dialogue, critical analysis, and the development of the science of TMH assessment and evaluation. The intent of this lexicon is to better unify the TMH field by providing a resource to researchers, program managers, funders, regulators and others for assessing outcomes. CONCLUSIONS: This document provides overall context for the key aspects of the lexicon.
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 | 0.006 | 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 it