British South Asian Patients’ Perspectives on the Relevance and Acceptability of Mobile Health Text Messaging to Support Medication Adherence for Type 2 Diabetes: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The prevalence of type 2 diabetes (T2D) is greater in South Asian populations and health outcomes are poorer compared with other ethnic groups. British South Asians are up to six times more likely to have T2D than the general population, to develop the condition at a younger age, and to experience diabetes-related complications. Interventions to support people in managing their condition can potentially reduce debilitating complications. Evidence to support the use of digital devices in T2D management, including mobile phones, has shown positive impacts on glycemic control. There is increasing recognition that health interventions that are culturally adapted to the needs of specific groups are more likely to be relevant and acceptable, but evidence to support the effectiveness of adapted interventions is limited and inconclusive. OBJECTIVE: This formative study aimed to explore the perceptions and views of British South Asian patients with T2D on mobile health SMS text messaging to support medication adherence, aimed at the general UK population. METHODS: Eight exploratory focus groups were conducted in Leicester, the United Kingdom, between September 2017 and March 2018. A diverse sample of 67 adults took part. RESULTS: British South Asian people with T2D who use digital devices, including mobile phones, felt that short messages to support medication adherence would be acceptable and relevant, but they also wanted messages that would support other aspects of self-management too. Participants were particularly interested in content that met their information needs, including information about South Asian foods, commonly used herbs and spices, natural and herbal approaches used in the United Kingdom and in South Asia, and religious fasting. Short messages delivered in English were perceived to be acceptable, often because family members could translate for those unable to read or understand the messages. Suggestions to support patients unable to understand short messages in English included having them available in different formats, and disseminated in face-to-face groups for those who did not use digital devices. CONCLUSIONS: Exploring the views of British South Asian patients about SMS text messaging aimed at the general UK population is important in maximizing the potential of such an intervention. For such a digital system to meet the needs of UK South Asian populations, it may also have to include culturally relevant messages sent to those who opt to receive them. It is equally important to consider how to disseminate message content to patients who do not use digital devices to help reduce health inequalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".