Beliefs about Healthy Sleep Habits in Adults with Diabetes Compared to Adults without Diabetes: A Reasoned Action Approach Elicitation Study
Bibliographic record
Abstract
Abstract Objective Sleep is part of a healthy lifestyle and in adults with diabetes, inadequate sleep is associated with risks of developing complications. The objective was to compare beliefs about healthy sleep habits (HSHs) in adults with versus without diabetes based on the Reasoned Action Approach. Methods A total of 56 adults with and 98 without diabetes answered open-ended questions regarding their beliefs about: avoiding screen use in bed; having a regular sleep schedule; or avoiding caffeine, alcohol, and cigarettes before bedtime. A qualitative content analysis was used to identify the most important beliefs, similarities, and differences between both groups. Results Both groups reported that adopting HSHs could improve sleep. Having a regular sleep schedule was perceived to facilitate diabetes management in adults with diabetes. Negative consequences specific to adopting each HSH were identified in both groups. Adopting HSHs was associated with mainly negative emotions (e.g., stress, anxiety, fear) in both groups. Avoiding screen use in bed was associated with anxiety of not knowing blood glucose levels at night in adults with diabetes. Partners, parents, and friends were considered the most important individuals who would approve of adopting HSHs, but they were often perceived as unlikely to adopt HSHs themselves in both groups. Adults with diabetes perceived more barriers to adopting HSHs. Facilitating factors for both groups included removing triggers of unhealthy sleep habits, behavior substitution, using reminders, time management, and social support. Discussion These beliefs can guide the development of behavioral sleep interventions, including interventions specifically for adults with diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".