Barriers and Facilitators to Research Use Among Allied Health Practitioners: A Mixed-Method Approach to Assessment
Bibliographic record
Abstract
Objectives – The disparity between what is known to be effective and what is done in practice points to barriers to research use among health practitioners. Library and information services (LIS) collect, organize and disseminate published research findings so they may be uniquely positioned to be of influence. This study aimed to identify barriers and facilitators to research use among allied health practitioners working in the alcohol and other drugs (AOD) field in Ireland, and to explore the services, strategies, and resources that may help alleviate these issues. Methods – Three focus groups were held with AOD practitioners. A survey questionnaire was then sent by post to 175 counsellors. The survey included the Barriers to Research Utilization Scale (Barriers Scale) (Funk et al. 1991), which assessed potential barriers from four factors: practitioner, setting, qualities of the research, and communication. Results – The number of responses was 71 (41%). All communication-related Barriers Scale items, and some items associated with the setting and practitioner, were perceived to be a moderate or great barrier by the majority of survey respondents. Similar issues were also raised in focus groups, where language, presentation, and time to engage with research were considered significant influences. Qualitative aspects of the study also revealed scepticism about research application and relevance. All proposed LIS were rated as moderate or great facilitators by the majority of respondents who expressed an opinion (those who choose “no opinion” or did not respond, 6–8%, were excluded). Conclusions – The high incidence of communication-related issues among top barriers and the enthusiasm expressed about proposed library services and training reveals the key role that LIS personnel can play in enabling practitioners to use research in practice. The addition of setting and practitioner factors indicates that a holistic, collaborative approach to promoting the effective use of research collections and resources is required. Mixed-method data collection (focus group and survey) provided a rich source of information, and may offer a useful approach for future study.
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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 | 0.069 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".