Revisiting the internal consistency and factorial validity of the 8-item Morisky Medication Adherence Scale
Bibliographic record
Abstract
OBJECTIVE: To assess the internal consistency and factorial validity of the adapted French 8-item Morisky Medication Adherence Scale in assessing adherence to noninsulin antidiabetic drug treatment. STUDY DESIGN AND SETTING: In a cross-sectional web survey of individuals with type 2 diabetes of the Canadian province of Quebec, self-reported adherence to the antidiabetes drug treatment was measured using the Morisky Medication Adherence Scale-8. We assessed the internal consistency of the Morisky Medication Adherence Scale-8 with Cronbach's alpha, and factorial validity was assessed by identifying the underlying factors using exploratory factor analyses. RESULTS: A total of 901 individuals completed the survey. Cronbach's alpha was 0.60. Two factors were identified. One factor comprised five items: stopping medication when diabetes is under control, stopping when feeling worse, feeling hassled about sticking to the prescription, reasons other than forgetting and a cross-loading item (i.e. taking drugs the day before). The second factor comprised three other items that were all related to forgetfulness in addition to the cross-loading item. CONCLUSION: Cronbach's alpha of the adapted French Morisky Medication Adherence Scale-8 was below the acceptable value of 0.70. This observed low internal consistency of the scale is probably related to the causal nature of the items of the scale but not necessarily a lack of reliability. The results suggest that the adapted French Morisky Medication Adherence Scale-8 is a two-factor scale assessing intentional (first factor) and unintentional (second factor) non-adherence to the noninsulin antidiabetes drug treatment. The scale could be used to separately identify these outcomes using scores obtained on each of the sub-scales.
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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 | 0.023 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".