Factors associated with provider self‐efficacy in delivery of evidence‐based programs for children, youth, and families
Bibliographic record
Abstract
Abstract Investments in training real‐world behavioral health providers in evidence‐based programs (EBPs) can be costly; thus, it is important to understand which providers may be more or less likely to implement such approaches after training. Provider self‐efficacy is associated with implementation of EBPs, but research on factors associated with provider self‐efficacy is less common. An exploratory, cross‐sectional, quantitative survey examined factors associated with provider self‐efficacy among 150 real‐world service providers who reported delivering EBPs to children, youth, or families in one U.S. state. Factors found to be associated with higher self‐efficacy included profession, workplace support, and extent of training received; difficulty engaging families was associated with lower self‐efficacy. Self‐efficacy was found to be associated with program use but not fidelity. Several organization‐level variables were identified as both facilitators and barriers to implementation of EBPs. Implications for research and practice are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 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".