Comparison of Communication Channels for Large-Scale Type 2 Diabetes Risk Screening and Intervention Recruitment: Empirical Study
Bibliographic record
Abstract
BACKGROUND: Clinical trials have shown that type 2 diabetes (T2D) is preventable through lifestyle interventions targeting high-risk people. Nevertheless, large-scale implementation of risk identification followed by preventive interventions has proven to be challenging. Specifically, recruitment of participants into preventive interventions is an important but often overlooked part of the intervention. OBJECTIVE: This study aims to compare the reach and yield of different communication channels to engage people at increased risk of T2D to fill in a digital screening questionnaire, with emphasis on reaching those at most risk. The participants expressing their willingness to participate is the final step in the risk screening test, and we aim to determine which channels had the most participants reach this step. METHODS: We established a stepwise web-based T2D risk screening tool with automated feedback according to the T2D risk level and, for those who were eligible, an invitation to participate in the StopDia prevention intervention study conducted in a primary health care setting. The risk estimate was based on the Finnish Diabetes Risk Score; history of repeatedly measured high blood glucose concentration; or, among women, previous gestational diabetes. We used several channels to invite people to the StopDia web-based screening tool, and respondents were classified into 11 categories based on the channel through which they reported having learned about StopDia. The demographics of respondents reached via different communication channels were compared using variance analysis. Logistic regression was used to study the respondents' likelihood of progressing through risk screening steps. RESULTS: A total of 33,399 persons started filling the StopDia screening tool. Of these, 86.13% (28,768/33,399) completed the test and named at least one communication channel as the source of information about StopDia. Altogether, 26,167 persons filled in sufficient information to obtain risk estimates. Of them, 53.22% (13,925/26,167) were at increased risk, 30.06% (7866/26,167) were men, and 39.77% (10,136/25,485) had low or middle education levels. Most frequently mentioned channels were workplace (n=6817), social media or the internet (n=6712), and newspapers (n=4784). The proportion of individuals at increased risk was highest among those reached via community pharmacies (415/608, 68.3%) and health care (1631/2535, 64.33%). The communication channel reaching the largest percentage of interested and eligible men (1353/3979, 34%) was relatives or friends. Health care (578/1069, 54.07%) and radio or television (225/487, 46.2%) accounted for the largest proportion of people with lower education. CONCLUSIONS: Communication channels reaching a large number of people, such as social media and newspapers, were the most effective channels for identifying at-risk people. Personalized approaches increased the engagement of men and less-educated people. Community pharmacies and health care services reached people with a particularly high T2D risk. Thus, communication and recruitment channels should be selected and modified based on the intended target group. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-019-6574-y.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".