Perceptions of diabetes distress during pregnancy in women with type 1 and type 2 diabetes: a qualitative interpretive description study
Bibliographic record
Abstract
BACKGROUND: Diabetes distress is commonly seen in adults with pre-existing diabetes and is associated with worsened glycemic management and self-management practices. While a majority of women report increased stress during pregnancy, it is unknown how women with type 1 or type 2 diabetes experience diabetes distress during this unique and transitional time. PURPOSE: This study aimed to understand the experiences and perceptions of diabetes distress in women with pre-existing diabetes during pregnancy. METHODS: A qualitative study using an interpretive description approach was conducted. In-depth, one to one interviewing was used to capture rich descriptions of the pregnancy experience. Nested, stratified, and theoretical sampling was used to recruit 18 participants with type 1 and type 2 diabetes from the quantitative strand of this mixed methods study. Constant comparative analysis was used to inductively analyze the data and develop themes. FINDINGS: Four themes, each with several subthemes, emerged under the main finding of "Diabetes Distress": 1) Worry for Baby's Health - "What's this going to do to the baby?"' 2) Feeling Overwhelmed with Diabetes Management-"It just seemed unattainable"; 3) Living with Diabetes - "There's no way out" and 4) Cycle of Diabetes Distress. CONCLUSIONS: The findings from this study identify the sources and experiences of diabetes distress during pregnancy in women with pre-existing diabetes. Diabetes distress often presents as cyclical and multifaceted during pregnancy, with elements of fear for the unborn baby, difficulties with diabetes management, and having negative lived experiences of diabetes. Further work is needed to develop appropriate screening tools for pregnancy and interventions to mitigate diabetes distress. Diabetes educators are well-positioned provide emotional support and person-centred self-management education to individuals with diabetes.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".