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Record W2010077987 · doi:10.1258/1355819053559029

Contested ground: how should qualitative evidence inform the conduct of a community intervention trial?

2005· article· en· W2010077987 on OpenAlexaff
Therese Riley, Penelope Hawe, Alan Shiell

Bibliographic record

VenueJournal of Health Services Research & Policy · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIntervention (counseling)Qualitative researchReflexivityLegitimacyResearch ethicsRelevance (law)Cluster randomised controlled trialRandomized controlled trialRigourPsychological interventionPsychologyPublic relationsQualitative propertyNarrativeSociologyApplied psychologyMedicineNursingPolitical scienceSocial scienceEpistemologyLawComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

This paper presents issues which arose in the conduct of qualitative evaluation research within a cluster-randomized, community-level, preventive intervention trial. The research involved the collection of narratives of practice regarding the intervention by community development officers working in eight communities over a two-year period. The community development officers were largely responsible for implementing the intervention. We discuss the challenges associated with the collection of data as the intervention unfolded, in particular, the disputes over cues to revise and adjust the intervention (i.e. to use the early data formatively). We explore the ethical uncertainties that arise when multiple parties have different views on the legitimacy of types of knowledge and the appropriate role of research and theory in various trial stages. These issues are discussed drawing on the fields of ethnography, community psychology, epidemiology, qualitative methodology and notions of research reflexivity. We conclude by arguing that, in addition to the usual practice of having an outcome data-monitoring committee, community intervention trials also require a process data-monitoring committee as a forum for debate and decision-making. Without such a forum, the relevance, ethics and position of qualitative evaluation research within randomized controlled trials are destined to be a point of contention rather than a source of insight.

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)0.121
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1210.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.002
Open science0.0020.000
Research integrity0.0000.004
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 head0.931
GPT teacher head0.807
Teacher spread0.125 · 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 designQualitative
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

Citations42
Published2005
Admission routes1
Has abstractyes

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