Exploring the management of type 2 diabetes in the Caribbean
Bibliographic record
Abstract
Introduction \nType 2 diabetes mellitus (T2DM) is a chronic metabolic disorder with a prevalence that has been increasing steadily and rapidly across the world, including the Caribbean region. It has negatively impacted individuals health and wellbeing, and in addition, it has increased the economic and social burden on the countries. T2DM management is an integral part of positive health outcomes, however, it has been poor in the Caribbean and is resulting in an alarming number of complications. The best way to reduce the negative outcomes associated with T2DM is to ensure that the disease is managed correctly. To do this, issues associated with poor T2DM management must be identified and disseminated to the public. \n \nAim \nThis thesis aims to highlight and raise awareness of the disparities impacting T2DM management in the Caribbean region to assist with future research, developmental plans and strategies. From the main aim two study objectives were developed. The first objective was to compare the content and quality of the Caribbean and international clinical guidelines for managing T2DM. The second objective was to summarise the barriers and facilitators to T2DM management in the Caribbean region. \n \nMethods \nTo address the aim of this research a formative research approach was used, this is to ensure that the Caribbean government, healthcare professionals and researchers are provided with some of the necessary data needed to plan and develop interventions. This formative research included two separate studies and methods, one to address each aim. The first study appraised T2DM management guidelines including the Caribbean guideline which compared the content and quality of guidelines using the AGREE II tool. The second study was a systematic review which summarised the barriers and facilitators to T2DM management in the Caribbean region. \n \nResults \nFrom the appraisal, the Caribbean clinical guideline was found to contain similar levels of T2DM management topics compared to six guidelines (one international and five country-specific guidelines) and contained higher content levels than the remaining three guidelines (two international and one country-specific). Three country-specific guidelines (Canada, England and Wales and Scotland) met the criteria of high-quality and could be recommended for current use in clinical practice. Four were only eligible for use in practice with modifications (two international and two country-specific). However, the country-specific guideline from the Caribbean as well as two additional guidelines (one international and one country-specific) were of low-quality and therefore, they were not recommended for use in practice. \n \nThe systematic review included eight studies, all of which focused on the patients’ perspective. There were six synthesized findings which included barriers and facilitators of T2DM management. These include, From the participants perspective sociocultural norms, demands and pressures were found to impact self-management and general care of T2DM (moderate certainty evidence); From the participants perspective environmental context and resources were found to impact the management of T2DM (high certainty evidence); From a patients perspective support systems were influential on the general management of T2DM (high certainty evidence); From the participants perspective personal background and circumstances can encourage and limit good self-management and general management of T2DM (high certainty evidence); From the participants perspective emotional factors were found to influence patients’ actions towards management of T2DM (high certainty evidence); and from the participants perspective psychological factors were found to influence patients’ adherence to T2DM management (moderate certainty evidence). \n \nSummary \nWith the aim of reducing the number of cases and deaths associated with T2DM, this research successfully addresses knowledge gaps by determining and presenting the quality of published clinical guidelines for T2DM management used by healthcare professionals. It also assesses the information being provided and summarizes the factors that hinder the promotion of good T2DM management in the Caribbean. The findings from these studies provide evidence that the Caribbean islands can use to make informed decisions on future interventions or research to assist in the fight against T2DM.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".