Implementing participation‐focused services: A study to develop the Method for using Audit and Feedback in Participation Implementation (MAPi)
Bibliographic record
Abstract
BACKGROUND: It is widely agreed that children's services should use participation-focused practice, but that implementation is challenging. This paper describes a method for using audit and feedback, an evidence-based knowledge translation strategy, to support implementation of participation-focused practice in front-line services, to identify barriers to implementation, and to enable international benchmarking of implementation and barriers. METHOD: Best-practice guidelines for using audit and feedback were followed. For audit, participation-focused practice was specified as clinicians' three observable behaviours: (a) targets participation outcomes; (b) involves child/parent in setting participation outcomes; and (c) measures progress towards participation outcomes. For barrier identification, the Theoretical Domains Framework Questionnaire (TDFQ) of known implementation barriers was used. A cycle of audit and barrier identification was piloted in three services (n = 25 clinicians) in a large U.K. healthcare trust. From each clinician, up to five randomly sampled case note sets were audited (total n = 122), and the clinicians were invited to complete the TDFQ. For feedback, data on the behaviours and barriers were shared visually and verbally with managers and clinicians to inform action planning. RESULTS: A Method for using Audit and feedback for Participation implementation (MAPi) was developed. The MAPi audit template captured clinicians' practices: Clinicians targeted participation in 37/122 (30.3%) of the sampled cases; involved child/parent in 16/122 (13.1%); and measured progress in 24/122 (19.7%). Barriers identified from the TDFQ and fed back to managers and clinicians included clinicians' skills in participation-focused behaviours (median = 3.00-5.00, interquartile range [IQR] = 2.25-6.00), social processes (median = 4.00, IQR = 3.00-5.00), and behavioural regulation (median = 4.00-5.00, IQR = 3.00-6.00). CONCLUSIONS: MAPi provides a practical, off-the-shelf method for front-line services to investigate and support their implementation of participation-focused practice. Furthermore, as a shared, consistent template, MAPi provides a method for generating cumulative and comparable, across-services evidence about levels and trends of implementation and about enduring barriers to implementation, to inform future implementation strategies.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".