February marked an important milestone for the CIHR Institute of Aging (IA) as we held our 50th Institute Advisory Board (IAB) meeting and welcomed two new members to our Board – Dr. Carole Estabrooks from the University of Alberta and Dr. Amine Choukou from the University of Manitoba. Dr. Estabrooks is a health services researcher who holds a Canada Research Chair in Knowledge Translation with an emphasis on the care of older adults in residential long-term care (LTC) settings.
The Ontario government has established the Staffing Supply Accelerator Group to help implement one of the largest health care recruitment and training programs in Ontario history. The group will support the objectives of A Better Place to Live, A Better Place to Work: Ontario’s Long-Term Care Staffing Plan.
Sigma Theta Tau International Honor Society of Nursing (Sigma) will induct 20 world-renowned nurse researchers into the International Nurse Researcher Hall of Fame at Sigma’s 32nd International Nursing Research Congress
Belita E, Yost J, Squires JE, Ganann R, Dobbins M.
PLoS One 2021 Mar 10;16(3):e0248330.
There are professional expectations for public health nurses to develop competencies in evidence-informed decision-making (EIDM) due to its potential for improved client outcomes. Robust tools to assess EIDM competence can encourage increased EIDM engagement and uptake. This study aimed to develop and validate the content of a measure to assess EIDM competence among public health nurses. A four-stage process, based on measure development principles and the Standards for Educational and Psychological Testing, was used to develop and refine items for a new EIDM competence measure: a) content coverage assessment of existing measures; b) identification of existing measures for use and development of items; c) validity assessment based on content; d) validity assessment based on response process. An EIDM competence measurement tool consisting of EIDM knowledge, skills, attitudes/beliefs, and behaviour items was developed using conceptual literature and existing measures (Evidence-Based Practice Competency Tool and Evidence-Based Practice Beliefs Scale) to address limitations of existing EIDM tools identified from the content coverage assessment. Item content validity index ratings ranged from 0.64-1.00. Qualitative themes from validity assessment based on content and response process included word changes to improve clarity, reducing item redundancy, separating multi-component items, and ensuring items reflect nursing role expectations. Upon determining its reliability and validity, there is potential for the EIDM competence measure to be used in: public health nursing practice to identify competence gaps and strengths to facilitate professional development activities; in research to support development of strategies to build EIDM capacity; and for curriculum planning and development across nursing education programs.
Saltaji H, Armijo-Olivo S, Cummings GG, Amin M, Major PW, da Costa BR, et al.
Journal of Evidence Based Dental Practice 2021 03/10:101544.
Background In this meta-epidemiological study, we aimed to examine associations between treatment effect size estimates and sponsorship bias in oral health randomized clinical trials. Methods We selected oral health related meta-analyses that included a minimum of five randomized controlled trials. We extracted data, in duplicate, related to influence of sponsorship bias. We quantified the extent of bias associated with influence of sponsorship on the magnitude of effect size estimates of continuous variables using a two-level meta-meta-analytic approach with random-effects models to allow for intra- and inter-meta-analysis heterogeneity. Results We initially identified 540 randomized trials included in 64 meta-analyses. Risk of sponsorship bias was judged as being “unclear” in 72.8% (n=393) of the trials, while it was assessed as “low” in 16.7% (n=90) and as “high” in 10.6% (n=57) of the trials. Using a meta-epidemiological analysis (37 meta-analyses, including 328 trials that analyzed 85,934 patients), we identified statistically significant larger treatment effect size estimates in trials that had ”high or unclear” risk of sponsorship bias (difference in treatment effect size estimates=0.10; 95% confidence intervals: 0.02 to 0.19) than in trials that had “low” risk of sponsorship bias. Conclusions We identified significant differences in treatment effect size estimates between dental trials based on sponsorship bias. Treatment effect size estimates were 0.10 larger in trials with “high or unclear” risk of sponsorship bias. Practical Implications Clinicians should have an adequate knowledge of sponsorship bias in a clinical trial and be able to estimate the degree to which the conclusions of a systematic review are synthesized and interpreted, based on trials with low risk of sponsorship bias.
