Interventions to Increase the Reachability of Migrants in Germany With Health Interview Surveys: Mixed-Mode Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Germany is a popular destination for immigrants, and migration has increased in recent years. It is therefore important to collect reliable data on migrants' health. The Robert Koch Institute, Berlin, Germany, has launched the Improving Health Monitoring in Migrant Populations (IMIRA) project to sustainably integrate migrant populations into health monitoring in Germany. OBJECTIVE: One of IMIRA's objectives is to implement a feasibility study (the IMIRA survey) that focuses on testing various interventions to increase the reachability of migrants with health interview surveys. Possible causes of nonresponse should be identified so as to increase participation in future surveys. METHODS: The survey target populations were Turkish, Polish, Romanian, Syrian, and Croatian migrants, who represent the biggest migrant groups living in Germany. We used probability sampling, using data from the registration offices in 2 states (Berlin and Brandenburg); we randomly selected 9068 persons by nationality in 7 sample points. We applied age (3 categories: 18-44, 45-64, and ≥65 years) and sex strata. Modes and methods used to test their usability were culturally sensitive materials, online questionnaires, telephone interviews, personal contact, and personal interviews, using multilingual materials and interviewers. To evaluate the effectiveness of the interventions, we used an intervention group (group A) and a control group (group B). There were also focus groups with the interviewers to get more information about the participants' motivation. We used the European Health Interview Survey, with additional instruments on religious affiliation, experience of discrimination, and subjective social status. We evaluated results according to their final contact result (disposition code). RESULTS: We collected data from January to May 2018 in Berlin and Brandenburg, Germany. The survey had an overall response rate of 15.88% (1190/7494). However, final disposition codes varied greatly with regard to citizenship. In addition to the quantitative results, interviewers reported in the focus groups a "feeling of connectedness" to the participants due to the multilingual interventions. The interviewers were particularly positive about the home visits, because "if you are standing at the front door, you will be let in for sure." CONCLUSIONS: The IMIRA survey appraised the usability of mixed-mode or mixed-method approaches among migrant groups with a probability sample in 2 German states. When conducting the survey, we were confronted with issues regarding the translation of the questionnaire, as well as the validity of some instruments in the survey languages. A major result was that personal face-to-face contact was the most effective intervention to recruit our participants. We will implement the findings in the upcoming health monitoring study at the Robert Koch Institute.
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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 | 0.040 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".