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Clinicians face challenges in implementing evidence-based practices due to limited resources and tools that can support their efforts in translating evidence into practice. To address this, JBI developed PACES (Practical Application of Clinical Evidence System), an online tool designed to streamline and support evidence implementation and quality improvement projects.
This paper reports the development of JBI-PACES and presents an evaluation of its usability (usefulness, satisfaction, ease of use) and user recommendations for improvements.
PACES was developed based on the integration of the Donabedian perspective on quality improvement and JBI's process model for evidence implementation, which incorporates context evaluation, facilitation of change, and the evaluation of both process and outcomes. Initially launched in 2004, the system underwent multiple enhancements based on informal user feedback from 2007 to 2017. A significant update, version 0.0.23 Build 1, was re-launched in late 2018. To evaluate its usability, we conducted a cross-sectional study using the Post-Study System Usability Questionnaire (PSSUQ), which also gathered qualitative feedback.
PACES supports evidence implementation by allowing users to conduct audits across multiple sites and over time, enabling data comparisons and insights into clinical practices. Findings from the usability evaluation showed high levels of satisfaction with the system's usefulness and ease of use. However, qualitative data indicated areas where further enhancements could optimize user experience and functionality.
The current study suggests clear benefits of PACES in terms of its utility and value for supporting evidence-based practices. Although the system performs well in usability, ongoing refinements are necessary to optimize user experience and ensure the tool continues to meet the evolving needs of healthcare professionals.
Burnout and mental health concerns are prevalent among healthcare workers. Female physicians, nurses, and healthcare staff are at a higher risk of suicide than the general population. Burnout and depression have been known to coexist with suicidal ideation and behaviors.
To identify what is known about the relationship between burnout and depression in the context of suicide among healthcare workers.
Registered scoping review of English language articles indexed to CINAHL, PubMed, and PsychInfo databases with date of publication prior to March 5, 2024.
The review yielded nine eligible studies, all employing observational or descriptive methodologies. Depression was found to be a predictor of suicidal ideation. While burnout was associated with depressive symptoms and found to coexist with suicidal ideation, it was not predictive of ideation. Emotional exhaustion and depersonalization were key components of burnout linked to depression. No studies were found exploring survivorship factors in healthcare professionals. Suggested prevention strategies that need to be tested include mindfulness and cognitive-behavioral skills training, improved workplace conditions, addressing loneliness, and fostering resilience.
Interventional studies are needed to test strategies addressing burnout, depression, suicidal behaviors, and survivorship of suicide attempts. Depression should be considered and evaluated when healthcare workers exhibit symptoms of burnout. Moreover, the Socio-economic Model of Suicide Prevention (i.e., SESM) can be used to categorize suicide prevention measures in healthcare. Burnout and depression interact to influence mental health outcomes among healthcare professionals, with depression playing a more significant role in predicting suicidal ideation. Despite the demonstrated relationships, critical gaps in knowledge exist in understanding survivorship and in the development and testing of effective interventions. Future interventional multisite research is needed using validated tools to identify best practices in suicide prevention for healthcare professionals.
Childhood obesity is an escalating crisis in the United States. Health policy may impact this epidemic which disproportionally affects underserved populations.
The aim was to use the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework to assess health policy impact on preventing or treating school-aged children (5 > 18 years) with obesity in underserved populations.
A scoping review of 842 articles was conducted. Twenty-four articles met the inclusion criteria and underwent data extraction.
Twelve studies included subgroup analysis, with four suggesting an impact of policy on at-risk groups. None of the 24 studies fully applied the RE-AIM framework. Policies positively impacted childhood obesity in 12 studies across the sample.
Our review revealed inconsistent evidence for the effectiveness of policy on childhood obesity, perhaps due to the lack of focus on the social determinants of health. In addition, many studies did not evaluate the outcomes for underserved populations. Therefore, we propose more attention to social determinants in future legislation and evaluation of policy effectiveness on underserved populations. Findings identify an urgent need for the design, implementation, and evaluation of policies specifically directed to address the inequities of racism, social injustices, and social determinants of health that impact childhood obesity in the United States. Future work needs to identify who was reached by the policy, who benefitted from the policy, and how policies were implemented to address obesity-related health disparities. Nurses should advocate for the evaluation of childhood obesity policies, particularly in underserved populations, to determine effectiveness. Nurses, particularly those trained in population and community health and research, should advocate for policy research that considers inequities rather than controls for these variables. Multi-layered interventions can then be tailored to sub-populations and evaluated more effectively.
The intent of the PICOT (i.e., Population, Intervention, Comparison, Outcome, Time) method is to formulate focused clinical questions to facilitate the discovery of relevant evidence through systematic searching, with the components of the question serving as the foundation for the search. Doctor of Nursing Practice (DNP) graduates use evidence-based practices to institute changes in their organizations' systems and policies, thereby yielding positive effects on both patient and system outcomes. Given that the clinical question is the foundation of the evidence-based practice process, DNP graduates' competence in the PICOT method needs to be better understood.
This analysis aimed to describe how DNP students used the PICOT method to ask clinical questions in their DNP projects.
Project questions were retrieved from a subset (n = 129, 60.56%) of an existing national random sample of publicly available DNP projects spanning the years 2010 to 2021 from Commission on Collegiate Nursing Education-accredited schools (n = 213). Project questions using the PICOT method were further evaluated with a scoring system of 0 = no and 1 = yes for missing elements, formatting, directional outcome, and project purpose. Possible scores ranged from 0 to 8, with higher scores indicating more errors. Discussion among five researchers, until agreement was achieved, yielded consensus.
Although the PICOT method was project author-identified in 66 (31.0%) projects, only four (6%) followed the PICOT method. All 66 (100%) were intervention questions. There were 2.74 (SD 1.55) mean errors, ranging from 0 to 6. No questions were missing P or O. Specific errors included missing I 3 (4.5%) or missing C 37 (56%), poor formatting 34 (51.5%), directional outcome 44 (66.7%), and project purpose 38 (57.6%). Thirty-three (50%) of the questions were missing T; however, T is not used for searching, so researchers recalculated the mean error without T (M = 2.24, SD = 1.28, range 0–5).
Gaps in the accurate use of the PICOT method to construct clinical questions can lead to biased searches, inaccurate clinical problem identification, and, when used as the project purpose, jumping to non-evidence-based solutions. Academic faculty and clinical educators can mitigate these skewed outcomes and enhance their impact on quality outcomes by helping DNP-prepared nurses shore up this foundational skill.
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