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Record W2171576473 · doi:10.1186/1748-5908-5-32

The BARRIERS scale -- the barriers to research utilization scale: A systematic review

2010· review· en· W2171576473 on OpenAlexafffund
Kerstin Nilsson Kajermo, Anne‐Marie Boström, D. Scott Thompson, Alison M. Hutchinson, Carole A. Estabrooks, Lars Wallin

Bibliographic record

VenueImplementation Science · 2010
Typereview
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsNOSM UniversityUniversity of Alberta
FundersCanadian Institutes of Health ResearchMacEwan UniversityKarolinska InstitutetAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche MédicaleUniversity of Alberta
KeywordsNursing researchMedicineScale (ratio)Psychological interventionHealth services researchMEDLINEHealth informaticsDescriptive statisticsSystematic reviewSample size determinationFamily medicineNursingPublic health

Abstract

fetched live from OpenAlex

BACKGROUND: A commonly recommended strategy for increasing research use in clinical practice is to identify barriers to change and then tailor interventions to overcome the identified barriers. In nursing, the BARRIERS scale has been used extensively to identify barriers to research utilization. AIM AND OBJECTIVES: The aim of this systematic review was to examine the state of knowledge resulting from use of the BARRIERS scale and to make recommendations about future use of the scale. The following objectives were addressed: To examine how the scale has been modified, to examine its psychometric properties, to determine the main barriers (and whether they varied over time and geographic locations), and to identify associations between nurses' reported barriers and reported research use. METHODS: Medline (1991 to September 2009) and CINHAL (1991 to September 2009) were searched for published research, and ProQuest(R) digital dissertations were searched for unpublished dissertations using the BARRIERS scale. Inclusion criteria were: studies using the BARRIERS scale in its entirety and where the sample was nurses. Two authors independently assessed the study quality and extracted the data. Descriptive and inferential statistics were used. RESULTS: Sixty-three studies were included, with most using a cross-sectional design. Not one study used the scale for tailoring interventions to overcome identified barriers. The main barriers reported were related to the setting, and the presentation of research findings. Overall, identified barriers were consistent over time and across geographic locations, despite varying sample size, response rate, study setting, and assessment of study quality. Few studies reported associations between reported research use and perceptions of barriers to research utilization. CONCLUSIONS: The BARRIERS scale is a nonspecific tool for identifying general barriers to research utilization. The scale is reliable as reflected in assessments of internal consistency. The validity of the scale, however, is doubtful. There is no evidence that it is a useful tool for planning implementation interventions. We recommend that no further descriptive studies using the BARRIERS scale be undertaken. Barriers need to be measured specific to the particular context of implementation and the intended evidence to be implemented.

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)0.048
metaresearch head score (Gemma)0.132
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.048
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.132
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0100.010
Bibliometrics0.0250.024
Science and technology studies0.0020.002
Scholarly communication0.0040.007
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.573
GPT teacher head0.720
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations296
Published2010
Admission routes2
Has abstractyes

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