Subjective Rationalities of Nonadherence to Treatment and Vaccination in Healthcare Decision-Making
Bibliographic record
Abstract
Objective: In this short report contributing to the literature on treatment and vaccination adherence, nonadherence was examined from the perspective of decision-making (DM) practice in healthcare. The objective of this study was to survey the rationalities given for treatment nonadherence and their association with DM practice. Methods: The Ottawa decision Support Framework was used as a theoretical background for the study. Multiple choice and open-text responses indicating nonadherence were drawn from vignette survey data. The results have been analyzed and reported as descriptive statistics and findings of data-driven content analysis. The number of observatory units was 1032 in the within-subject study design. Results: DM practice was predominantly associated with nonadherence to vaccination, whereas nonadherence to treatment was consistently associated with attitudinal reasons independent of DM practice. Nonadherence to vaccination was most often rationalized by prior negative experiences in simple DM scenarios. After other DM practices, nonadherence was rationalized by uncertainty and criticism about the benefits of the recommended vaccine. Mistrust toward healthcare providers stood out, first in treatment nonadherence generally and, second, in vaccination nonadherence after simple DM where the final decision was left to the patient. Conclusion: In medical DM, adherence to treatment and vaccination may be achieved through a recognition of patients’ previous healthcare encounters and potential trust-related concerns, which could pose a risk for nonadherence. To be able to observe these risks, patient engagement and mutual trust should be priorities in decision support in healthcare. Plain Language Summary: Research on treatment and vaccination adherence aim at increasing knowledge about improving adherence and treatment outcomes. This study examined explanations given for not adhering to treatment and an association between the explanations and medical decision-making practices. Decision-making practices are known to impact patient–physician interaction and the patients’ motivation to have an active role at the appointment. In a shared decision-making (SDM) practice, patients’ participation is encouraged. SDM is built on both medical expertise of the practitioner and individual views, values and preferences of the patient. As opposed to SDM, authoritarian decision-making refers to a practice in which decisions are made solely by the physician. In guided decision-making, the physician shares information with the patient but makes the final decision. In simple decision-making, the final decision is left to the patient after consultation. This empirical study used illustrated vignette survey data from Finland. Out of the 1935 respondents, 64% were female with an average age of 68. In the study design, nonadherence was presumed to depend on a decision-making practice presented. Primary findings showed that nonadherence to treatment is most correlated with attitudinal predetermination of the patient and mistrust toward healthcare providers. Nonadherence to vaccination had a stronger association with decision-making practices. After simple decision-making, declining vaccination was most often explained by prior negative experiences and mistrust toward healthcare providers. After other decision-making practices, explanations for declining included uncertainty and criticism about the benefits of the recommended vaccine. This study underscores the pivotal role of trust in the patient-physician interaction. Keywords: decision-making, interaction, treatment adherence, trust, vaccination
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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 | 0.000 | 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".