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Development and Validation of a Derived Measure of Research Utilization by Nurses

2006· article· en· W2034086719 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Research · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsContext (archaeology)VariablesVariable (mathematics)Linear regressionRegression analysisStatisticsMeasure (data warehouse)PsychologyComputer scienceApplied psychologyMathematicsData mining

Abstract

fetched live from OpenAlex

BACKGROUND: Theoretical models are needed to guide strategies for the implementation of research into clinical practice. To develop and test such models, including analyses of complex theoretical constructs and causal relationships, rich datasets are needed. Working with existing datasets may mean that important variables are lacking. OBJECTIVE: The aim of this study was to derive a nursing research utilization variable and validate it using the Promoting Action on Research Implementation in Health Services (PARIHS) conceptual framework on research implementation. METHODS: This study was based on data from two surveys of registered nurses. The first survey (1996; N = 600) contained robust research utilization variables but few organizational variables. The second (1998; N = 6,526) was rich in organizational variables but contained no research utilization variables. A linear regression model with predictors common to both datasets was used to derive a research utilization variable in the 1998 dataset. To validate these scores, four separate procedures based on the hypothesis of a positive relationship between context and research utilization were completed. Mutually exclusive groups reflecting various levels of context were created to accomplish these procedures. RESULTS: The derived research utilization variable was successfully mapped onto the cases in the 1998 dataset. The derived scores ranged from 0.21 to 21.40, with a mean of 10.85 (SD = 3.23). The mean score per subgroup ranged from 8.28 for the lowest context group to 12.75 for the highest context group. One of the validation procedures showed that significant differences in mean research utilization existed only among four conceptually unique context groups (p < .001). These groups showed a positive incremental relationship in research utilization (p < .001; the better the context, the higher the research utilization score). The validity of the derived variable was supported by using the three remaining validation procedures. DISCUSSION: The successful creation and validation of a derived research utilization variable will enable advanced modeling of the relationships between research utilization and individual and organizational characteristics. The findings also support the construct validity of the context element of the PARIHS theoretical framework.

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.

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)0.013
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.532
GPT teacher head0.631
Teacher spread0.099 · 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