The Challenges of Conducting Research in Rural Populations: A Feasibility Study
Bibliographic record
Abstract
Purpose: Chronic stress related to health disparities results in negative health outcomes for mothers and infants. The brain-gut-immune axis plays a significant role in perinatal health outcomes. Researchers have not focused on the effects of rural living on the maternal/infant gut microbiome. The purpose of our study was to validate recruitment protocols, data and specimen collection protocols, participant feedback, and participant retention strategies for future studies in a rural Nebraska population of mother/infant dyads. Sample: Mother/infant dyads living in Nebraska counties with a rural-urban commuting area (RUCA) code of three or greater (n = 17 dyads, n = 1 triad). Methods: We conducted a cross-sectional pilot feasibility study by collecting stool samples, actigraph data, sleep diaries, and health and lifestyle questionnaires from mother/infant dyads living in rural Nebraska counties. Findings: Retrospective review of this pilot study identified the main feasibility findings were primarily related to distance: 1) relying on virtual recruiting methods was cost-effective; 2) stool sample shelf-life created participant inconvenience; 3) shipping carrier delays affected collection timing of actigraph data; 4) participant access to shipping carrier drop-offs increased cost and inconvenience. Conclusion: Rural locations create barriers to research, but none are insurmountable. When working with rural populations, it is important to consider the potential adaptation of participant recruitment methods and protocol procedures, including careful attention to shipping and related time constraints that may impact data collection. DOI: https://doi.org/10.14574/ojrnhc.v23i2.740
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".