Bibliographic record
Abstract
Calls for innovations and research echo in the latest reviews and meta-analyses of methods to enhance compliance (Haynes, McDonald, Garg, & Montague, 2003; Pekkala & Merinder, 2002; Peterson, Takiya, & Finley, 2003). In spite of effective therapy emerging daily from medical research, non-compliance appears at disappointing rates. Over the past 25 years, the gap is widening between what we could achieve with available and emerging health care and what we are currently achieving. This lack of compliance with proven therapy thwarts health outcomes and adds to the growing health care costs. In Canada, direct and indirect costs resulting from non-compliance with therapies amount to 7 to 9 billion dollars per year (Coambes, Jensen, Hao Her, Ferguson, Jarry, Wong, & Abrahamsohn, 1995; Coambs, 1997; Tamblyn & Perreault., 1997). Many stakeholders play a role in the complex compliance equation. The physician plays a key role. Supporting physician maintenance of competence are continuing health educators. Together, the physicians and educators seek to employ the latest evidence in their practices to enhance compliance. Explicating the thinking that guides their medical and educational practices helps researchers and educators to understand problems in current approaches to compliance. It is argued that prior knowledge is the basis for learning (Limon & Mason, 2002). Understanding current knowledge and behavior of a learner establishes the baseline to build effective educational activities that will impact targeted outcomes. Further, education designed by using learner's prior knowledge is the scaffold for future learning (Alexander, 1996). This survey research examines the thinking and behavior of a randomized sample of Canadian physicians and networking sample of educators. Quantitative and qualitative analysis of participant thinking and interventions reveal different perspectives and mental models that guide their clinical and educational decisions. The findings reveal important differences with current clinical recommendations. The study identifies important variables that explain the differences and lack of progress in this area. Directions for future education and research are forwarded. The recommendations, based in theories of change and cognition, offer important insights and opportunities to make advances toward enhancing current rates of compliance.
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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 | 0.141 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.018 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".