What's trust got to do with it? Revisiting opioid contracts
Bibliographic record
Abstract
Prescription opioid abuse (POA) is an escalating clinical and public health problem. Physician worries about iatrogenic addiction and whether patients are 'drug seeking', 'abusing' and 'diverting' prescription opioids exist against a backdrop of professional and legal consequences of prescribing that have created a climate of distrust in chronic pain management. One attempt to circumvent these worries is the use of opioid contracts that outline conditions patients must agree to in order to receive opioids. Opioid contracts have received some scholarly attention, with trust and trustworthiness identified as key values and virtues. However, few articles have provided a critical account of trust and trustworthiness in this context, particularly when there exists disagreement about their role in terms of enhancing or detracting from the patient-physician relationship. This paper argues that opioid contracts represent a misleading appeal to patient-physician trust. Assuming the patient is untrustworthy may wrongfully undermine the credibility of the patient's testimony, which may exacerbate certain vulnerabilities of the person in pain. However, misplaced trust in certain patients may render the physician vulnerable to the potential harms of POA. If patients distrust their physician, or feel distrusted by them, this may destabilise the therapeutic relationship and compromise care. A process of epistemic humility may help cultivate mutual patient-physician trust. Epistemic humility is a collaborative effort between physicians and patients that recognises the role of patients' subjective knowledge in enhancing physicians' self-understanding of their theoretical and practice frameworks, values and assumptions about the motivations of certain patients who report chronic pain.
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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 | 0.053 | 0.153 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.053 |
| Scholarly communication | 0.017 | 0.037 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".