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Record W2482402567 · doi:10.1186/s12913-016-1577-1

A qualitative study examining healthcare managers and providers’ perspectives on participating in primary care implementation research

2016· article· en· W2482402567 on OpenAlexafffundabout
Lisa Wozniak, Allison Soprovich, Sandra Rees, Steven T. Johnson, Sumit R. Majumdar, Jeffrey Johnson

Bibliographic record

VenueBMC Health Services Research · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsAthabasca UniversityUniversity of Alberta
FundersInstitute of Nutrition, Metabolism and DiabetesCanadian Institutes of Health Research
KeywordsPsychological interventionNursingNursing researchHealth careHealth administrationQualitative researchMedicineHealth informaticsHealth services researchImplementation researchPublic health

Abstract

fetched live from OpenAlex

BACKGROUND: Primary care reforms should be supported by high-quality evidence across the entire life cycle of research. Front-line healthcare providers play an increasing role in implementation research. We recently evaluated two interventions for people with type 2 diabetes (T2D) in partnership with four Primary Care Networks (PCNs) in Alberta, Canada. Here, we report healthcare professionals perspectives on participating in primary care implementation research. METHODS: Guided by the RE-AIM framework, we collected qualitative data before, during, and after both interventions. We conducted 34 in-person or telephone interviews with 17 individual PCN professionals. We used content analysis to identify emerging codes and concepts. RESULTS: Two major themes emerged from the data. First, healthcare managers were eager to conduct implementation research in a primary care setting. Second, regardless of willingness to conduct research, there were challenges to implementing experimental study designs for both interventions. PCN professionals presumed the interventions were better than usual care, expressed role conflict, and reported administrative burdens related to research participation. Perceptions of patient vulnerability and an obligation to intervene exacerbated these issues. CONCLUSIONS: Healthcare professionals with limited practical research experience might not foresee the challenges in implementing experimental study designs in primary care settings to generate high-quality evidence. These issues are intensified when healthcare professionals perceive target patient populations as vulnerable and in need of intervention based on the presenting illness. Possible solutions include further research training, involving healthcare professionals in study design development, and using non-clinical staff to conduct research activities, particularly among acutely unwell patient populations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.054
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.077
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0150.012
Scholarly communication0.0050.005
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.808
GPT teacher head0.780
Teacher spread0.029 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
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

Citations10
Published2016
Admission routes3
Has abstractyes

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