Exploring the Experiences and Needs of Patients With Type 2 Diabetes Mellitus in Sleman Regency, Yogyakarta, Indonesia: Protocol for a Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic disease that can cause adverse effects if not managed effectively. The prevalence of T2DM will continue to rise every year, and data from the International Diabetes Federation show that the number of patients diagnosed with T2DM in Indonesia is predicted to increase from 10.3 million in 2017 to 16.7 million in 2045. Managing T2DM properly is a challenge for the patients because they need to implement lifestyle changes that involve the self-monitoring of blood glucose, consuming prescribed medication properly, maintaining a healthy diet, getting sufficient physical training, keeping a healthy sleeping pattern, managing stress properly, and consulting medical professionals regularly. The worldwide intervention for T2DM focuses on self-management education. The varied results in studies about interventions show that no particular intervention method can be regarded as the most effective. In Indonesia, there are limited studies on educational interventions to improve the quality of life and health of patients with T2DM. OBJECTIVE: This study aims to explore the experiences and needs of patients with T2DM in Sleman Regency, Yogyakarta, Indonesia, to develop effective self-management education. METHODS: The study will use the phenomenology method with purposive sampling to collect data. The inclusion criteria are patients in the Chronic Disease Self-Management Program at the Sleman Regency Public Health Center who are aged ≥18 years, diagnosed with T2DM for more than a year, with hemoglobin A1c levels ≤7.5% and >7.5%, capable of communicating verbally and literate in the Indonesian language, not deaf, and willing to participate. The data collection is based on the Social Cognitive Theory, which involves selecting assessment targets and analyzing personal factors, environment, and behavior that determine the knowledge, attitude, and adherence of persons with T2DM. Researchers will collect the data through in-depth, face-to-face interviews to learn about knowledge, self-efficacy, outcome expectancy, outcome experience, worry, illness belief, treatment belief, diet, physical activity, medicine intake, treatment pattern, support system, as well as ethnic and cultural influences. The results will be taken from unstructured and open-ended questions written in Indonesian according to the interview guidelines. The data analysis process will go through several stages: reading the data thoroughly; coding; sorting the categories; creating the themes; making general descriptions; and presenting the data in charts, narratives, and recorded quotations from the interviews. RESULTS: This study received a grant in May 2021 and gained permission from the Medical and Health Research Ethics Committee of Universitas Gadjah Mada, Indonesia, on July 1, 2021. Data collection started on August 12, 2021, and the results are expected to be published in 2022. CONCLUSIONS: The results of this study will be used to design an educational intervention model to improve the knowledge, attitude, and adherence of patients with T2DM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37528.
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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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".