The Development and Pilot Testing of a Fidelity Checklist for a Family-Centered Telehealth Intervention for Parents of Children with Motor Delay
Bibliographic record
Abstract
This multi-methods study describes the development of a pediatric rehabilitation telehealth intervention fidelity checklist, estimates its inter-rater reliability, and documents raters' implementation experience. A literature scan and expert consultation identified eighteen key behaviors and categorized them into three subdomains, measured using a 5-point measurement system. To estimate the checklist's inter-rater reliability, three raters scored 33 video recordings. A Shrout and Fleiss Class 1,1 intraclass correlation (ICC)) and 95% confidence intervals (CI) calculated ICCs = 0.5 (CI: 0, 0.9) for both the Therapist and the Parent-Therapists subdomains, and the Parent subdomain an ICC = 0.3 (CI: 0, 0.8). In the implementation surveys, raters reported high levels of satisfaction (100%), ease of use (84% to 88%), and confidence in their video ratings (87% to 100%). Changes in procedures and scoring were recommended. Capturing raters' implementation experiences is crucial in the early evaluation of the fidelity checklists for telehealth.
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 | 0.034 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".