Rethinking evidence-based practice for children’s mental 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
“Efficiency is concerned with doing things right. Effectiveness is doing the right things.” Drucker, 1993 Typically, evidence-based practice (EBP) refers to health practitioners applying the best currently available research evidence in the provision of health services. In other words, EBP challenges practitioners to “do things right” and to “do the right things”. EBP originated in medicine, where an estimated 10 000 new randomised controlled trials (RCTs) are published every year but where an estimated 20%–40% of services still do not reflect the best research evidence.1 Related disciplines such as psychology have also embraced the EBP movement to bridge research and practice in order to improve outcomes for people with mental disorders.2 In children’s mental health, high levels of unmet service need suggest a strong role for EBP. At any given time 14% of children experience mental disorders that cause significant distress and impair their functioning, yet only 25% of these children receive specialised mental health treatment services.3 It is also clear that children’s mental health services often fail to reflect the best available research evidence, leading researchers to argue that EBP is an ethical imperative if we are to improve children’s mental health.4,5 Despite being widely advocated, EBP has nevertheless proved difficult to implement. To some extent implementation barriers are a result of a restricted focus on interventions designed to change simple behaviours performed by individual practitioners, such as prescribing by physicians. These interventions have had only modest effects and need to be integrated with larger organisational and system changes that support EBP.1 However, a greater challenge may be posed by controversies about EBP’s narrow definitions of “evidence,” particularly when applied in mental health.6 Here, we discuss the controversies with regard to implementing EBP in children’s mental health. We illustrate the issues based …
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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 | 0.025 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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