Medication beliefs and depression in Black individuals with diabetes and mild cognitive impairment
Bibliographic record
Abstract
Depression and impaired cognition occur frequently in older patients with diabetes, and may influence beliefs about diabetes medications.1, 2 These beliefs, when not shared by clinicians, may engender mistrust and reduce medication adherence. Thus, the relationship between depression, cognition, and medication beliefs is important, especially because treating depression may improve cognition and reverse depressive symptoms (e.g., pessimism, loss of interest, and hopelessness) that compromise medication adherence. In this study, we examined relationships between beliefs about diabetes medications, depression, and cognition in older Black individuals with type 2 diabetes and mild cognitive impairment (MCI). The results may guide ways to optimize diabetes treatment in this high-risk population. This was a cross-sectional analysis of baseline data (N = 289) from two clinical trials testing the efficacy of two different behavioral interventions in older Black primary care patients with type 2 diabetes and MCI to improve glycemic control. Previous publications describe the two studies (Study 1; N = 144 and Study 2; N = 145).3, 4 Institutional Review Board (IRB) approval was obtained, and all participants provided informed consent. Baseline data in both studies included age, sex, and education; hemoglobin A1c level; Patient Health Questionnaire-9 (PHQ-9); participants with PHQ-9 scores ≥10 were considered to have clinically significant depression5; and Beliefs About Medicines Questionnaire (BMQ), which rates medication beliefs from 1 ("strongly disagree") to 5 ("strongly agree").6 Beliefs that were agreed to or strongly agreed to were considered present. To assess cognition, we used the Mini-Mental Status Examination (MMSE)7 in Study 1, and the Montreal Cognitive Assessment (MoCA)8 in Study 2. Statistical tests included one-way analysis of variance (ANOVA) for continuous data and chi-squares for categorical variables. Among 289 participants, 89 (30.8%) met criteria for clinically significant depression. Depressed and nondepressed participants were similar in age, sex, education, and hemoglobin A1c levels (Table 1). In the Study 1 sample, depressed and nondepressed participants had comparable MMSE scores; in the Study 2 sample, depressed participants had lower MoCA scores than nondepressed participants (Table 1). Depressed participants were significantly more likely to endorse negative medication beliefs than nondepressed participants (Figure 1). Many participants held negative beliefs about physicians' medication prescribing (i.e., "doctors use too many medicines"; "doctors place too much trust on medicines"; and "if doctors had more time with patients, they would prescribe fewer medicines") but rates were higher in depressed than nondepressed participants. We found that negative beliefs about diabetes medications were related to depression in older Black patients with type 2 diabetes and MCI. Although depression may induce negative health beliefs (e.g., worry, disruption, and misunderstanding), both depressed and nondepressed participants held many negative medication beliefs, particularly concerning physicians. These findings are important because depression, health beliefs, medication adherence, glycemic control, and diabetes complications are interrelated.9, 10 In this study, all participants had impaired cognition, which can compromise insight and shape health beliefs. Medication beliefs, however, appeared more related to depression than cognition, notwithstanding the somewhat lower MoCA scores in depressed versus nondepressed participants in Study 2. This study has a number of limitations, including uncertain generalizability, absence of data on medication beliefs among individuals with normal cognition, and uncertainty about whether treating depression can modify health beliefs. Despite these limitations, this study suggests that discussing medication beliefs with patients may identify those at risk of medication nonadherence, depression, and impaired cognition. Moreover, such discussions can provide an opportunity to promote positive attitudes about treatment and trust in physicians, and thereby optimize care for older Black individuals, in whom rates of diabetes, depression, and impaired cognition are high. Concept and design: Both authors. Acquisition, analysis, or interpretation of data: Both authors. Drafting of the manuscript: Barry W. Rovner, Robin J. Casten. Statistical analysis: Robin J. Casten. Obtained funding: Barry W. Rovner. The authors have no conflicts of interest to disclose. The sponsors had no role in the study design, data collection, in the analysis and interpretation of data, in the writing of this manuscript, or the decision to submit this manuscript for publication. This study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK; grant R01 DK102609-01) and the National Institute on Aging (R01AG065467).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".