Commentary on Brown <scp>CE</scp> , Ecoff L, Kim <scp>SC</scp> , Wickline <scp>MA</scp> , <scp>R</scp> ose <scp>B</scp> , <scp>K</scp> limpel <scp>K</scp> and <scp>G</scp> laser <scp>D</scp> (2010) Multi‐institutional study of barriers to research utilisation and evidence‐based practice among hospital nurses. <i> <scp>J</scp> ournal of Clinical Nursing </i> 19, 1944–1951
Bibliographic record
Abstract
Twenty years ago, Funk et al. (1991) published the instrument Barriers to research utilisation scale, the BARRIERS scale. The numbers of researcher world-wide using the scale are impressive (Kajermo et al. 2010). The scale measures the nurse's perceptions of barriers to research utilisation. Because of different versions, the scale consists of 29 or 28 items that are divided in four subscales labelled Nurse – the characteristics of the adopter; Setting – the characteristics of the organisation; Research – the characteristics of the innovation; and Presentation – the characteristics of the communication. The factors are proposed to parallel major concepts in Rogers’ Diffusion of Innovation theory (Funk et al. 1991). In 2010, we published a systematic review of studies using the BARRIERS scale (Kajermo et al. 2010). We identified 63 studies in nursing populations of which the majority was conducted in English-speaking countries; however, the spread to non-English speaking countries had escalated during the last decade. One finding was that nurses perceived the setting/organisation and the presentation of research findings/communication as the main barriers to research utilisation. Somewhat surprisingly, the results in the studies remained the same over time, across countries and languages. Just six of the 63 included studies had examined associations between reported research use and perceptions of barriers to research utilisation, mostly using bivariate analyses. Few associations were identified and none of the studies reported statistically significant associations between nurses’ research use and barriers related to the setting/organisation. We therefore appreciate Baker et al. (2010) study as they examined the relationships between perceived barriers and adoption of evidence-based practice (EBP) among nurses in four hospitals using hierarchical multiple regression analyses. As in the majority of the studies using the BARRIERS scale, the nurses in the study by Brown et al. perceived the setting/organisation as the main barrier to research utilisation. Three of the four factors were significantly associated with EBP though explaining only 2·7% of the variance. The setting/organisation factor was not associated with EBP. The Baker et al. (2010) study supports our questioning of the validity of the BARRIERS scale. One problem with the scale is that the items represent general and non-specific barriers that represent information that is difficult to use for developing adequate interventions. Furthermore, as the scale was developed in the 1980s, there have been changes in healthcare. For example, remarkable development in information technology has increased the access to research findings and relevant evidence, an aspect that is not represented in the BARRIERS scale. As our review was published, we have identified at least ten additional publications using the BARRIERS scale in nursing populations, revealing the ongoing popularity and spread of the scale. On the basis of the study by Brown et al., the review by Carlson and Plonczynski (2008) and our review, our continued recommendation is that no more descriptive studies should be undertaken using the Barriers scale. Future research efforts should instead focus on addressing locally identified barriers as tailored interventions to overcome identified barriers appear to be an effective strategy to get evidence into practice (Baker et al. 2010). The authors declare they have no conflict of interest.
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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 | 0.010 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.039 | 0.042 |
| Insufficient payload (model declined to judge) | 0.027 | 0.020 |
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".