DATA COLLECTION VIA PHONE IN MULTICENTRIC RESEARCH ON NURSING CARE IN THE FACE OF COVID-19
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Objective: to report data collection via telephone carried out in multicenter research on nursing care assessment during the COVID-19 pandemic. Method: this is an experience report on using the telephone to collect quantitative and qualitative data with participants from ten Brazilian university hospitals from October 2020 to December 2021. The experience was presented in stages: 1) Operationalization of data collection via telephone; 2) Interviewing team training; 3) Monitoring and adjustments to data collection; and 4) Results of telephone contact with patients. Results: data collection planning and organization involved creating guidance manuals to guide the collectors, which were validated for clarity and agreement. For monitoring and adjustments, a weekly meeting was held with the interviewers in charge and researchers. Data from 539 respondents from the Patient Measure of Safety instrument, 643 from the Care Transitions Measure instrument and 56 from open interviews were included. Conclusion: using guidance manuals for data collection via telephone, training and follow-up meetings are strategies that can enhance this strategy in multicenter research when in-person data collection is impossible.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it