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Record W3169726931 · doi:10.1186/s12913-021-06583-1

Advancing discussion of ethics in mixed methods health services research

2021· article· en· W3169726931 on OpenAlexaff
Nicole A. Stadnick, Cheryl Poth, Timothy C. Guetterman, Joseph J. Gallo

Bibliographic record

VenueBMC Health Services Research · 2021
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of Alberta
FundersOffice of Behavioral and Social Sciences ResearchNational Institute of Mental Health
KeywordsConfidentialityResearch ethicsInformed consentEthical issuesNursing researchMedicineHealth services researchEthical codeBioethicsMedical educationPublic healthPsychologyEngineering ethicsPublic relationsNursingAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: To describe the ethical issues and experiences of scientists conducting mixed methods health services research and to advance empirical and conceptual discussion on ethical integrity in mixed methods health research. METHODS: The study was conducted with 64 scholars, faculty and consultants from the NIH-funded Mixed Methods Research Training Program (MMRTP) for the Health Sciences. This was a cross-sectional study. Survey results were analyzed using descriptive statistics to characterize responses and open coding to summarize strategies about eight ethical mixed methods research issues. Respondents completed an online survey to elicit experiences related to eight ethical issues (informed consent, confidentiality, data management, burden, safety, equitable recruitment, communication, and dissemination) and strategies for addressing them. RESULTS: Only about one-third of respondents thought their research ethics training helped them plan, conduct, or report mixed methods research. The most frequently occurring ethical issues were participant burden, dissemination and equitable recruitment (> 70% endorsement). Despite occurring frequently, < 50% of respondents rated each ethical issue as challenging. The most challenging ethical issues were related to managing participant burden, communication, and dissemination. Strategies reported to address ethical issues were largely not specific or unique to mixed methods with the exception of strategies to mitigate participant burden and, to a lesser degree, to facilitate equitable recruitment and promote dissemination of project results. CONCLUSIONS: Mixed methods health researchers reported encountering ethical issues often yet varying levels of difficulty and effectiveness in the strategies used to mitigate ethical issues. This study highlights some of the unique challenges faced by mixed methods researchers to plan for and appropriately respond to arising ethical issues such as managing participant burden and confidentiality across data sources and utilizing effective communication and dissemination strategies particularly when working with a multidisciplinary research team. As one of the first empirical studies to examine mixed methods research ethics, our findings highlight the need for greater attention to ethics in health services mixed methods research and training.

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 imitation

Not 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.

metaresearch head score (Codex)0.244
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2440.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.008
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0010.020
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.589
GPT teacher head0.737
Teacher spread0.148 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2021
Admission routes1
Has abstractyes

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