Structural barriers to coping with type 1 diabetes mellitus in Ghana: experiences of diabetic youth and their families.
Bibliographic record
Abstract
OBJECTIVE: To explore the structural barriers faced by families coping with type 1 diabetes mellitus (T1DM) in Ghana, and to provide insight for policy development. METHODS: Qualitative study conducted with families with a child with T1DM, receiving care in the greater Accra area. Total of 17 individuals were interviewed using individual and dyadic approaches: 7 youth with T1DM, 9 parents of children with T1DM, and one medical doctor. FINDINGS: 5 key barriers emerged from the data: primary care, schools, financial burden, lack of formal support, and access to information. Participants expressed concern over the misdiagnosis of T1DM at primary care facilities, resulting in some of the children going into a diabetic coma before receiving proper care. Children and parents noted discrimination and poor care at school. Financial burden was due to the high costs of medications and appliances needed for proper diabetes management. A lack of formal support was credited by participants to be the result of the lethargy of advocacy groups or resource centers. Finally, there was a lack of readily available and accessible information for children and parents on T1DM. CONCLUSION: Awareness of T1DM needs to be increased, by incorporating lessons on recognition into already existing campaigns for type 2 diabetes mellitus (T2DM). Schools need to be more engaged with their responsibility for children with diabetes. Pressuring policy makers and pharmaceutical companies to make diabetes supplies more affordable and accessible could ease the financial burden. Social support networks need to be explored and strengthened. Study into the experiences of youth with T1DM in rural settings and other parts of Ghana, as well as, youth from low socioeconomic backgrounds is necessary.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".