Prevalence and Correlates of Diabetes Distress in Pregnant Individuals With Preexisting Diabetes: A Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE Managing preexisting diabetes during pregnancy requires considerable self-management skills to achieve recommended glycemic targets and reduce fetal and obstetrical risks. Given the demands during this time, many individuals may experience diabetes distress. This study aimed to determine the prevalence of diabetes distress and associated clinical factors of diabetes distress during pregnancy. RESEARCH DESIGN AND METHODS A cross-sectional study was conducted involving 36 pregnant participants with type 1 diabetes and 40 pregnant participants with type 2 diabetes. Assessments of diabetes distress, the primary outcome, were performed, along with assessments of depressive symptoms, self-efficacy, self-management, and patient care satisfaction. Linear and logistic regression analyses were conducted to determine predictors of diabetes distress scores and positive diabetes distress. RESULTS The prevalence of diabetes distress was 22.4%. Age ≥35 years of age and higher education levels were significantly associated with scores on the Problem Areas in Diabetes (PAID) scale, which measures diabetes-related emotional distress (decreases of 10.18 and 11.77 points, respectively, P = 0.04). Living with others was associated with a reduction in PAID score by 21.56 points (P = 0.05) and the Patient Assessment of Chronic Illness (PACIC) total score as well as PACIC Goal-Setting, and Problem-Solving/Contextual Counseling subscale scores were each associated with a decrease of ∼4 points in PAID score (P <0.05). Having a common-law partner or spouse, comorbid depression, depressive symptoms, and depression scores were all significantly associated with increased PAID scores (P <0.05). CONCLUSION The prevalence of diabetes distress in pregnancy is similar to estimates for nonpregnant adults with type 1 or type 2 diabetes, based on limited pregnancy literature. Further research is needed to establish diabetes distress rates using a validated tool for pregnancy to understand whether diabetes distress affects obstetrical and fetal outcomes and how diabetes distress levels can be alleviated in this population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".