Development of an observational measure of therapy engagement for pediatric rehabilitation
Bibliographic record
Abstract
PURPOSE: The Pediatric Rehabilitation Intervention Measure of Engagement-Observation (PRIME-O) version was designed to capture signs of affective, cognitive and behavioral involvement for clients and service providers and in the client-provider interaction. METHODS: Phase 1 examined interrater consensus and construct validity of a pilot version, using observer ratings of engagement indicators made while viewing videos of therapy sessions differing in high and low engagement (Sample 1). Phase 2 examined these properties in a 10-item version (Samples 2 and 3). Phase 3 examined the content validity of the 10-item version, using observed signs of child, youth and parent engagement, as reported in an interview study involving 10 service providers. RESULTS: There was excellent interrater consensus for both versions and ratings significantly discriminated between videos differing in high and low engagement, providing evidence for construct validity. Content validity was demonstrated by service provider reports of engagement signs. More behavioral signs were reported for children and more cognitive signs were reported for youth and parents, providing evidence for the developmental appropriateness of the PRIME-O. CONCLUSIONS: The PRIME-O provides a multifaceted view of affective, cognitive and behavioral components of engagement in pediatric rehabilitation. The PRIME-O has potential utility for research, clinical practice and continuing education. Implications for Rehabilitation Measures of engagement in therapy are needed to identify factors associated with successful therapy sessions and positive client outcomes. The PRIME-O is an observational measure that captures indicators of affective, cognitive and behavioral components of engagement for both clients and service providers. The PRIME-O may further help in understanding of the strategies service providers can use to facilitate an optimal state of engagement within a therapy session. Clinical practice may be enhanced by attending to the client's signals of engagement in therapy. The PRIME-O can help service providers to more accurately identify signs of engagement and disengagement, monitor their own success in creating an engaging intervention atmosphere, and instigate strategies to optimize engagement.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".