Exploring the experiences of mothers of children with type 1 diabetes in Northern Alberta: a qualitative descriptive study
Bibliographic record
Abstract
OBJECTIVES: Canada has one of the highest rates of Type 1 diabetes in children. Management of their diabetes and prevention of poor health outcomes often falls on mothers who are often the primary caregiver. The caregiving demands can result in substantial responsibility and stress. Mothers report career sacrifices, sleep deprivation, stress, grief, anxiety, and low mood. While globally Canada has a high rate of type 1 diabetes, studies on the caregiving experience within a Canadian context have not been conducted. This study explored the experiences of mothers of children with type 1 diabetes in northern Alberta, Canada. METHODS: Utilizing a qualitative descriptive approach, we interviewed 16 mothers (average age = 37.1 ± 6) with children with type 1 diabetes who were under the age of 18. We also drew upon a caregiver engagement in research approach to create a Community Advisory Committee of three mothers of children with diabetes. Advisory members collaborated with us and offered invaluable insight and feedback throughout the study. RESULTS: Using reflexive thematic analysis, six interrelated themes were identified: (a) "I am the organ": a sense of constant vigilance, (b) accepting a new normal, (c) grief underlying a rollercoaster of emotions, (d) caregiving as an isolating experience, (e) the continuous glucose monitor is a champion, and (f) finding the positives. Mothers face constant vigilance and anxiety, often feeling like their child's "organ" for survival. They view caregiving as an isolating experience with limited understanding and assumptions from people without children with type 1 diabetes. Grief persists several years post diagnosis, intertwined with concerns and worries for the health and future of their children. New routines revolved around caretaking duties result in the acceptance of lifestyle changes and shifts in priorities. CONCLUSIONS: Caring for a child with type 1 diabetes presents many stressors for mothers. Over time, mothers gain confidence about their abilities as caregivers. They find relief in online networks and access to continuous glucose monitors, which alleviate some anxiety and sleep deprivation but also present challenges. Our findings highlight the importance of improving access to affordable technology, psychological support, and respite care to improve loss of personal time and the need for constant vigilance.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".