Evaluating a Family Capacity-Building Service: Are We Doing More Good Than Harm?
Bibliographic record
Abstract
Background. Parents of children with special needs are more likely to experience stress and have health-related problems. Pediatric occupational therapy interventions that build parents’ capacity are often considered to be effective. It remains unclear how they can be offered without overburdening parents. Purpose. The purpose of this article is to share the findings from the evaluation of a flexible capacity-building occupational therapy service with seven families. Method. A convergent parallel mixed methods design was used to document parents’ and occupational therapists’ perspectives on the services, including outcomes, strengths, weaknesses, opportunities, and threats. Findings. Parents reported understanding their children better, having more positive attitudes toward the challenges experienced, feeling more confident that they could help them, and having more satisfactory family routines. The importance for therapists to develop nonjudgmental collaborative relationships, to be flexible and to use the time available to help families with what matters the most in their daily lives came out particularly loudly. Conclusion. This study provides a concrete example of how it is possible to build families’ capacities without overburdening them. It also provides guidance to establishments wishing to take a step back to think about how they build families’ capacities.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".