Perceived control as a predictor of medication adherence in people with Parkinson’s: a large-scale cross-sectional study
Bibliographic record
Abstract
PURPOSE: Medication adherence is a multi-faceted construct associated with several positive consequences in people with chronic conditions. However, non-adherence currently represents a major issue in Parkinson's, potentially due to low perceptions of control. This study investigated the predictive ability of several aspects of perceived control on adherence in people with Parkinson's, while accounting for previously established predictors such as depression and medication variables. MATERIALS AND METHODS: An online cross-sectional survey was carried out with 1210 adults with Parkinson's from 15 English-speaking countries. Demographic and clinical questions, as well as measures of depression, aspects of perceived control, and medication adherence were included. Pearson's correlations and a 4-block hierarchical regression analysis were performed to assess the relationship between the variables. RESULTS: Perceived control explained a slightly higher amount of variance in medication adherence compared to medication variables when entered in the last block. Unexpectedly, depression was not significantly related with adherence. Internal locus of control was an independent negative predictor of adherence, while external dimensions of locus of control emerged as independent positive predictors. CONCLUSIONS: In people with Parkinson's, perceptions of control may have a larger impact on adherence compared to medication variables. Implications for clinical practice and future research are discussed.Implications for RehabilitationPerceived control and depression are considered important constructs for medication adherence in Parkinson's, which in turn is often problematic for affected individuals.The specific predictive value of different aspects of perceived control on medication adherence in Parkinson's is currently unclear.This large-scale study found that perceptions of control may have a larger impact on adherence compared to medication variables, while depression was unrelated to it.A need for psychologically-informed interventions, person-centred approaches to medication management, and Parkinson-specific measures of adherence are highlighted.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".