Face‐to‐face interviews versus Internet surveys: Comparison of two data collection methods in the Rome foundation global epidemiology study: Implications for population‐based research
Bibliographic record
Abstract
BACKGROUND AND AIMS: The Rome Foundation Global Epidemiology Study (RFGES) assessed the prevalence, burden, and associated factors of Disorders of Gut-Brain Interaction (DGBI) in 33 countries around the world. Achieving worldwide sampling necessitated use of two different surveying methods: In-person household interviews (9 countries) and Internet surveys (26 countries). Two countries, China and Turkey, were surveyed with both methods. This paper examines the differences in the survey results with the two methods, as well as likely reasons for those differences. METHODS: The two RFGES survey methods are described in detail, and differences in DGBI findings summarized for household versus Internet surveys globally, and in more detail for China and Turkey. Logistic regression analysis was used to elucidate factors contributing to these differences. RESULTS: Overall, DGBI were only half as prevalent when assessed with household vs Internet surveys. Similar patterns of methodology-related DGBI differences were seen within both China and Turkey, but prevalence differences between the survey methods were dramatically larger in Turkey. No clear reasons for outcome differences by survey method were identified, although greater relative reduction in bowel and anorectal versus upper gastrointestinal disorders when household versus Internet surveying was used suggests an inhibiting influence of social sensitivity. CONCLUSIONS: The findings strongly indicate that besides affecting data quality, manpower needs and data collection time and costs, the choice of survey method is a substantial determinant of symptom reporting and DGBI prevalence outcomes. This has important implications for future DGBI research and epidemiological research more broadly.
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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 | 0.291 | 0.329 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".