"Pretty radical from what I've known": The dissonance and distance underlying patients' cognitive engagement with educational health information
Bibliographic record
Abstract
Patient education often aims to activate behaviours for health management. Assumptions of a fundamental desire for information and learning as a pre-requisite for self-management are countered by the fact that some patients refuse or selectively attend to health information. The complex and emotional context surrounding illness and disease may reduce the patient’s openness or willingness to engage with information. Perceptions of a non-compliant, resistant or difficult patient are accompanied with little understanding of the underlying factors. The goal of this research was to explore the cognitive and emotional factors underlying the patient’s readiness to learn or cognitively engage with information regarding diabetes management. This study was conducted using Interpretative Phenomenological Analysis, which draws from the educational experiences of patients with diabetes and interprets their narratives within the context of existing research and theory. A maximum variation sample of 19 adults with Type II diabetes from a primary care clinic and a tertiary care hemodialysis unit participated in an interview. Three main themes emerged: underlying incongruence in knowledge, thoughts and beliefs; relational talking; and negotiating control. Themes converged on the essence of ‘distance’ between the patient’s lifeworld and the disease and its management. When considered in relation to cognitive dissonance and psychological distance theories, psychological adjustment and relational challenges were revealed. Adjustment involved reconciling difference and dissonance at various points during diabetes management. Distance also threatened the adjustment process and in some cases generated defensive reactions. Adjustment and relational challenges have a bearing on the early stages of the learning process. Differentiating the message according to concrete and abstract information may be more conducive to a staged learning process and offer a more tangible understanding of ‘finding common ground’ within patient-centered communication. These factors underlying readiness to learn have been reported by patients with diabetes and require further consideration for tailoring communication and education to support person-centred care and self-management.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".