A modified random walk door-to-door recruitment strategy for collecting social and biological data relating to mental health, substance use/addictions and violence problems in a Canadian community
Bibliographic record
Abstract
Flynn, A., Tremblay, P. F., Rehm, J., & Wells, S. (2013). A modified random walk door-to-door recruitment strategy for collecting social and biological data relating to mental health, substance use, addiction, and violence problems in a Canadian community. International Journal of Alcohol and Drug Research, 2(2), 7-16. doi: 10.7895/ijadr.v2i2.143 (http://dx.doi.org/10.7895/ijadr.v2i2.143)Aims: To describe a modified “random walk” door-to-door recruitment strategy used to obtain a random community sample for participation in a study relating to mental health, substance use, addiction, and violence (MSAV) problems and involving the collection of both self-report and biological (hair and saliva) data. This paper describes study protocols, response rates for the study and for the provision of biological data, and possible further applications for this data collection method.Design: A two-stage cluster sample was derived from the 2006 Canadian census sampling frame for a small Ontario community, based on the random selection of city blocks as the primary sampling units and households as the secondary sampling units.Setting: A small city in Ontario, Canada.Participants: A general population sample of 92 participants selected randomly from households using Kish tables.Measures: A computerized questionnaire was administered to obtain self-report data on MSAV problems. Saliva was collected to study genetic vulnerabilities to MSAV problems, and hair was collected to examine stress levels (via the hormone cortisol) as they relate to MSAV problems.Findings: The study showed a response rate of 50% and a high rate of provision of biological samples (over 95%).Conclusions: Modified random walk methodologies involving face-to-face recruitment may represent a useful approach for obtaining general population samples for studies of MSAV problems, particularly those involving the collection of biological samples. Further studies are needed to assess whether this approach leads to better response rates and improved estimates compared to other survey methods used in research on substance use.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".