An Ontological Model of Behaviour Theory to Generate Personalized Action Plans to Modify Behaviours
Bibliographic record
Abstract
Behavior change approaches aim to assist patients in achieving self-efficacy in managing their condition. Social cognitive theory (SCT) stipulates self-efficacy as a central element to behavior change and provides constructs to achieve self-efficacy guided by person-specific action plans. In our work, to administer behaviour change in patient with chronic conditions, our approach entails the computerization of SCT-based self-efficacy constructs in order to generate personalized action plans that are suitable to an individual's current care scenario. We have taken a knowledge management approach, whereby we have computerized the SCT-based self-efficacy constructs in terms of a high-level SCT knowledge model that can be operationalized to generate personalized behaviour change action plans. We have collected and computerized behavior change content targeting healthy living and physical activity. Semantic web technologies have been used to develop the SCT knowledge model, represented in terms of an ontology and SWRL rules. The ontological SCT model can inferred to generate personalized self-management action plans for a given patient profile. We present formative evaluation of the clinical correctness and relevance of the generated personalized action plans for a range of test patient profiles.
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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 | 0.000 |
| 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".