A pilot study of research utilization practices and critical thinking dispositions of Alberta dental hygienists
Bibliographic record
Abstract
UNLABELLED: In order to test interventions for increasing uptake of research findings into dental hygiene practice, we must first identify factors that influence research use. There has been little work on this topic in dental hygiene, but much in other disciplines that can provide exemplars of how others have approached the study of this phenomenon. OBJECTIVES: A pilot study was conducted to determine if protocols used to study research utilization (RU) behaviours and critical thinking dispositions (CTD) in nursing could also be applied to dental hygiene. METHODS: A cross-sectional survey design was used with a random sample of 640 practicing dental hygienists in Alberta, Canada. Three questionnaires were included: one to capture measures of RU including direct, indirect and symbolic RU; the California Critical Thinking Dispositions Inventory (CCTDI) and a demographics questionnaire. RESULTS: Mean responses for the three types of RU were highest for indirect at 3.52 (SD 0.720), followed by direct at 3.13 (SD 0.903) and symbolic 2.86 (SD 0.959). The majority (74.8%) scored between 280 and 350 on the CCTDI (maximum 420). Cronbach's alpha reliability for the RU measures and four of the seven sub-scales were over .7, indicating internal consistency reliability. CONCLUSIONS: The instruments proved reliable for this population, but other challenges, including a low response rate, were identified during the process of using the RU questionnaire in the context of dental hygiene practice. Pilot testing identified the need for improvements to the presentation of scales to reduce cognitive load and improve the response rate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".