Introduction
Self-efficacy is defined as an individual’s level of confidence to exert control over their own behavior and, in the context of research skills, is often measured to understand what factors influence how trainees perceive their own abilities and comfort in performing certain experiments or skills.1 The Clinical Research Appraisal Inventory (CRAI) and its shortened version, the CRAI-12, are previously validated instruments for documenting the self-confidence and self-efficacy of physicians in performing activities associated with several important domains in clinical research: study design and data collection; reporting, interpreting and presenting; conceptualizing and collaborating; planning; funding; and research subject protections.2,3 These assessment tools are based on self-efficacy theory and social cognitive career theory and have been previously shown to correlate with future involvement in clinical research activities and scholarly productivity in physicians.2,3
In response to a strong demand for veterinary clinical disease models to be incorporated into the translational research enterprise,4–6 there has been a substantial increase in focus on the design and implementation of veterinary clinical studies7–9; however, the level of confidence of veterinary academic clinicians in their ability to design and conduct clinical research has not been previously reported. The goal of the present study was to document domain-specific confidence of academic veterinary clinicians in the various tasks associated with research design, conduct, and dissemination to help inform future training initiatives by use of a veterinary-specific modification of the CRAI-12 for identifying areas of current strength and areas where targeted clinician-development initiatives should be implemented. We hypothesized that previous participation in a formal research training program and increased years of experience would enhance self-efficacy in clinical research conduct and that years of experience in the field of academic veterinary medicine would lead to enhanced self-efficacy in experiential tasks such as project management.
Methods
This study was reviewed and found to be exempt by The Ohio State Institutional Review Board prior to initiation (study No. 2021E1022). An electronic survey containing a modified version of the CRAI-12, along with a set of demographic questions, was composed in Qualtrics and disseminated to veterinary clinicians working in US academic veterinary institutions during a 4-week period in the fall of 2021 along with an introductory email explaining the nature of the project. Minor adjustments were made to the wording of tasks related to regulatory approvals and research subject protections to ensure applicability to veterinary medicine, and several tasks not relevant to veterinary clinical research were removed. Ultimately, a modified veterinary CRAI (mvCRAI) was used in the present study and contained 10 domains: conceptualizing a study; designing a study; collaborating with others; funding a study; planning and managing a study; protecting research subjects and responsible conduct of research; collecting, recording, and analyzing data; interpreting data; reporting a study; and presenting a study (Supplementary Material S1). An invitation to complete the survey was distributed to all faculty members subscribed to the Clinical and Translational Science Award One Health Alliance listserv, and email invitations were sent directly to Associate Deans of Research and clinical department heads at all colleges of veterinary medicine with on-site teaching hospitals. Administrators were requested and encouraged to forward the invitation to clinicians at their institutions. Reminders were emailed 2 weeks into the survey window and 48 hours prior to close of the survey. In total, 31 academic veterinary institutions were contacted (Table 1). In addition to mvCRAI instrument questions, demographic information about respondents was gathered, including previous research training, academic rank, duration of time in role, and previous experience with veterinary clinical research. Respondents were asked whether they currently held a faculty appointment at a US academic veterinary institution. Only those answering yes were able to move on to the questions assessing clinical research self-efficacy. For items relating to the mvCRAI, questions were presented as radio buttons across a scale in which respondents were asked to rank their confidence in performing a range of clinical research tasks from 0 to 10, where 0 indicated no confidence and 10 indicated total confidence.
A list of US academic veterinary institutions contacted as part of the survey-distribution process assessing self-efficacy in veterinary clinical research.
Auburn University | The Ohio State University |
Colorado State University | Tufts University |
Cornell University | Tuskegee University |
Iowa State University | University of California-Davis |
Kansas State University | University of Florida |
Lincoln Memorial University | University of Georgia |
Louisiana State University | University of Illinois |
Michigan State University | University of Minnesota |
Midwestern University | University of Missouri |
Mississippi State University | University of Pennsylvania |
North Carolina State University | University of Tennessee |
Oklahoma State University | University of Wisconsin |
Oregon State University | Virginia-Maryland |
Purdue University | Regional College |
Texas A&M University | Washington State University |
Texas Tech University | Western University |
Summary statistics were used to present results of individual survey questions, and modified mvCRAI confidence levels were presented as median (range) scores for the group. The relationship between the completion of formal training in clinical research and reported clinical research self-efficacy across specific tasks and domains was assessed with a ranked ANOVA, with effect size calculated with Cohen’s f. The relationship between years of experience and research self-efficacy was calculated with a Pearson χ2 test with effect size calculated with Cramér’s V. Correction for multiple comparisons was not applied since the work was considered exploratory in nature with a goal of generating new hypotheses for future studies. Results for all analyses were considered statistically significant at P < .05.
Results
General demographics
A total of 182 responses from US veterinary academic clinicians were received (Tables 2 and 3). Of the 182 respondents, 146 completed all domains of the mvCRAI. Individuals who provided partial survey responses were included in analysis only for the domains for which they responded. Eighty nine percent of respondents indicated they had served as a principal investigator, coinvestigator, or supporting personnel on a veterinary clinical research study at least once in the last 5 years, and 89% identified themselves as having a general interest in veterinary clinical research. Thirty-nine percent of respondents reported having served as a principal investigator on a veterinary clinical study within the past 5 years. Respondents were predominantly junior to midcareer faculty, with 53% having spent ≤ 15 years in academic veterinary practice.
Demographics of respondents to a survey assessing self-efficacy of academic veterinary clinicians in clinical research; 174 responses were received for demographics information.
Variable | Response | |
---|---|---|
Frequency | Percent | |
Gender | ||
Male | 53 | 31 |
Female | 117 | 67 |
Prefer not to answer | 4 | 2 |
Other | 0 | 0 |
Age (y) | ||
31–34 | 10 | 6 |
35–40 | 36 | 21 |
41–45 | 26 | 15 |
46–50 | 35 | 20 |
51–55 | 26 | 15 |
56–60 | 19 | 11 |
61–65 | 16 | 9 |
> 65 | 6 | 3 |
Ethnicity | ||
African American/Black | 2 | 1 |
Asian American/Asian | 5 | 3 |
White | 161 | 90 |
Other | 4 | 3 |
Prefer not to answer | 6 | 3 |
Academic background of respondents to a survey assessing self-efficacy of academic veterinary clinicians in clinical research; 174 responses were received for academic background information.
Variable | Response | |
---|---|---|
Frequency | Percent | |
Degree | ||
DVM | 16 | 9 |
DVM/MS | 9 | 5 |
DVM/PhD | 16 | 9 |
DVM/specialty diplomate | 40 | 22 |
DVM/MS/specialty diplomate | 33 | 19 |
DVM/MPH/specialty diplomate | 1 | 1 |
DVM/PhD/specialty diplomate | 47 | 27 |
Current position | ||
Fellow/postresidency scholar | 1 | 1 |
Assistant professor—clinical | 31 | 18 |
Assistant professor—tenure track | 22 | 13 |
Associate professor—clinical | 31 | 18 |
Associate professor—tenure track | 30 | 17 |
Professor—clinical | 16 | 9 |
Professor—tenure track | 37 | 21 |
Other | 6 | 3 |
Total years in academic veterinary practice | ||
0–5 | 33 | 19 |
6–10 | 34 | 20 |
11–15 | 25 | 14 |
16–20 | 27 | 16 |
21–25 | 27 | 16 |
26–30 | 12 | 6 |
> 30 | 16 | 9 |
Education and training
When asked about educational degrees held, the most common responses were DVM and specialty diplomate status (22%); DVM, MS, and specialty diplomate (19%); or DVM, PhD, and specialty diplomate (27%). Most respondents (52%) indicated not having completed any formal training or education in the design and conduct of clinical research. Those who indicated they had received formal training in this area were further asked to specify the type via a text box format, and responses ranged from “during PhD program” to “Good Clinical Practice or other formal training courses” to “2-day seminar on clinical research.”
Career status and total years in the field
Survey respondents listed their role at their current institution as postresidency fellow (1%), assistant professor—clinical (18%), assistant professor—tenure track (13%), associate professor—clinical (18%), associate professor—tenure (17%), professor—clinical (9%), professor—tenure (21%), and other, such as adjunct, locum, or research track (3%). Respondents indicated the number of years they had spent in academic veterinary medical practice as 0 to 5 years (19%), 6 to 10 years (20%), 11 to 15 years (14%), 16 to 20 years (16%), 21 to 25 years (16%), 26 to 30 years (6%), or > 30 years (9%).
Modified veterinary CRAI domain responses
In general, domains and associated tasks that focused on conceptualizing a study and collaboration received higher self-efficacy scores than domains and associated tasks such as funding a study, research subject protections/responsible conduct of research, and collecting and analyzing data. Respondents indicated the highest confidence in the following specific tasks: identifying experts in their area of interest (9; 0 to 10); consulting senior researchers for ideas (9; 0 to 10); organizing a research report for a journal according to an appropriate professional forma and standards (9; 1 to 10); writing a methods section that conveys sufficient methodological detail to permit subsequent replication of your work by others (9; 1 to 10); writing the results section of a research paper that clearly summarizes and describes the results, free of interpretative comments (9; 1 to 10); and reporting results in both narrative and graphic form (9; 1 to 10). A complete summary of respondent confidence in all tasks listed across the 10 domains covered in the survey is provided in Supplementary Table S1.
Respondents indicated the lowest confidence in performing advanced statistical analysis in one’s research area such as discriminant analysis, principal component analysis, multiple logistic analysis, survival analysis, or time series analysis (3; 0 to 10; Table 4). Other factors for which respondents reported relatively low confidence included the following: design a study using qualitative methods, such as ethnography, grounded theory, or phenomenology (4; 0 to 10); terminate a collaboration that isn’t working (5; 0 to 10); describe a major funding agency’s (eg, NIH, National Science Foundation, or other foundation) proposal-review and award process (5; 0 to 10); establish a sufficient timeline for a grant application (5; 0 to 10); establish collaborator and consultant agreements for a grant application (5; 0 to 10); ask staff to leave the project team when necessary (5; 0 to 10); and explain the historical events that had significant impact on the federal regulations for the regulation of animal use in research (5; 0 to 10).
Survey responses regarding self-efficacy for tasks associated with the 10 domains covered in the modified veterinary Clinical Research Appraisal Inventory (CRAI) and for which self-efficacy was rated as low (≤ 5). Data are presented as median response (range), where 0 indicates no level of confidence and 10 indicates complete confidence.
Domain | Median (range) |
---|---|
Designing a study | |
Design a study using qualitative methods (eg, ethnography, grounded theory, or phenomenology) | 4 (0–10) |
Collaborating with others | |
Terminate a collaboration that isn’t working | 5 (0–10) |
Funding a study | |
Describe a major funding agency’s (eg, NIH, National Science Foundation, or foundation) proposal-review and award process | 5 (0–10) |
Establish a sufficient timeline for a grant application | 5 (0–10) |
Establish collaborator and consultant agreements for a grant application | 5 (0–10) |
Planning and managing a study | |
Ask staff to leave the project team when necessary | 5 (0–10) |
Protecting research subjects and responsible conduct of research | |
Explain the historical events that had significant impact on the federal regulations for the regulation of animal use in research | 5 (0–10) |
Collecting, recording, and analyzing data | |
Perform more advanced statistical tests used in one’s research area, such as discriminant analysis, principal components analysis, multiple logistic analysis, survival analysis, or time series analysis | 3 (0–10) |
Influence of a formal research training program
There was a strong statistical relationship between the completion of a formal research training program and self-efficacy in many of the tasks assessed by the mvCRAI (Table 5). The impact of a formal research training program was apparent in tasks across 9 of the 10 domains assessed, with the largest effect sizes noted in domains and specific tasks that involved statistical techniques/quantitative methods and approaches to study design. For those tasks not specifically reported in Table 5, there was no statistical difference in self-efficacy between those who had and those who had not completed a formal research training program. Domains for which no individual tasks were impacted by formal research training included collaborating with others, protecting research subjects/responsible conduct of research, and presenting a study.
Modified veterinary CRAI domains and tasks for which there was a statistically significant relationship (P < .05) between higher reported confidence and the completion of a formal research training program.
Domain | P value | Effect size |
---|---|---|
Conceptualizing a study | ||
Refine a problem so it can be investigated | < .001 | 0.514 |
Relate specific questions of interest to underlying theory | .005 | 0.505 |
Explain (in a general way) the importance of theory to research | .047 | 0.503 |
Select a suitable topic area for study | .029 | 0.483 |
Develop a logical rationale for a particular research idea | .044 | 0.479 |
Articulate a clear purpose for the research | .042 | 0.386 |
Organize your proposed research ideas in writing | .031 | 0.467 |
Place one’s study in the context of existing research and justify how it contributes to important questions in the area | .032 | 0.463 |
Designing a study | ||
Determine the universe, population, and appropriate sample for a given study | .023 | 0.620 |
Design a study using quantitative methods (eg, experimental, quasi-experimental designs, or clinical trials) | .002 | 0.557 |
Design the best data analysis strategy for your study | .001 | 0.534 |
State the purpose, strengths, and limitations of each study design | .002 | 0.502 |
Choose an appropriate research design that will answer a set of research questions and/or test a set of hypotheses | .009 | 0.440 |
Funding a study | ||
Prepare a research proposal suitable for submission in one’s research area | .012 | 0.443 |
Describe a major funding agency’s (eg NIH, National Science Foundation, or foundation) proposal-review and award process | .015 | 0.441 |
Establish a sufficient timeline for a grant application | .036 | 0.451 |
Identify appropriate funding sources (local, state, national) to support a study | .011 | 0.432 |
Write a competitive grant application | .046 | 0.406 |
Collecting, recording, and analyzing data | ||
Evaluate the reliability and validity of a given measurement | .003 | 0.582 |
Use computer software to generate graphic images, such as flow charts or theoretical models | .005 | 0.536 |
Provide direction to computer specialists or statisticians on how to handle missing data | < .001 | 0.532 |
State the relationship between the chosen research design, type of data collected, and necessary statistical techniques | .043 | 0.517 |
Perform commonly used statistical tests, such as χ2 test, t test, ANOVA, correlations, and multiple regression | .008 | 0.492 |
Interpreting data | ||
Explain the outcome of given analysis in terms of the originally stated hypotheses or research questions | .010 | 0.470 |
Planning and managing your research study | ||
Prepare and submit required reports, budget requests, and other documents to institutional agency administrators and funding agencies | .001 | 0.563 |
Recruit and screen research project staff | .02 | 0.414 |
Reporting a study | ||
Report results in both narrative and graphic form | < .001 | 0.526 |
Influence of years of experience
Number of years of experience was significantly associated with self-efficacy in several areas, where confidence increased with total years in academic veterinary practice (Table 6). An impact of years of experience was apparent in 7 of the 10 domains assessed by the instrument, with the largest effect sizes noted in tasks that involved project management, interpersonal interactions, and selecting a journal for manuscript submission. Domains for which no specific tasks were impacted by years of experience as an academic faculty member included collecting, recording, and analyzing data; interpreting data; and presenting a study.
Modified veterinary CRAI domains and tasks for which there was a statistically significant relationship (P < .05) between higher reported confidence and increased total years of experience in academic veterinary medicine.
Domain | P value | Effect size |
---|---|---|
Conceptualizing a study | ||
Organize your proposed research ideas in writing | .022 | 0.302 |
Refine a problem so it can be investigated | .023 | 0.287 |
Designing a study | ||
State the purpose, strengths, and limitations of each study design | .03 | 0.302 |
Funding a study | ||
Speak with a person at the funding agency regarding your project or project idea | .002 | 0.348 |
Planning and managing your research | ||
Train assistants to collect data | .042 | 0.319 |
Collaborating with others | ||
Sustain effective collaborations | .045 | 0.288 |
Protecting research subjects and responsible conduct of research | ||
Identify the responsibilities of research institutions and regulatory agencies in conducting research | .048 | 0.322 |
Reporting a study | ||
Select a journal for manuscript submission | .006 | 0.324 |
Write a discussion section for a research paper that articulates the importance of your findings relative to other studies in the field | .016 | 0.315 |
Discussion
To our knowledge, this study represents the first published data assessing clinical research self-efficacy in academic veterinary clinicians. Understanding clinician confidence in their ability to conduct various aspects of clinical research is important as clinical research becomes a larger focus at academic veterinary medical centers, both for improving veterinary health and as a tool for conducting translational studies. While 89% of academic veterinary clinicians in the present study reported serving as a member of a clinical study team over the previous 5 years, most reported having received no formal training in research. Documenting self-identified knowledge gaps can highlight opportunities for targeted training and institutional support. Institutional support has been previously identified as an important predicter of research self-efficacy in other professions in health sciences,10 and training opportunities in veterinary clinical research can support career growth for veterinary clinicians with research interests. Median self-efficacy scores for most items in the present survey were high; however, self-efficacy for almost all tasks ranged from 0 to 10, indicating vast differences in confidence between clinicians, regardless of career stage and academic rank. This finding suggests that opportunities for clinician development exist in all domains covered by the mvCRAI, even those where most individuals rated themselves as comfortable.
Exposure to a formalized research training program was associated with higher levels of confidence in many domains of our mvCRAI, suggesting that, unsurprisingly, formal training enhances veterinary clinician-scientist comfort with research activities. However, a strict definition of “formal research training program” was not provided in the survey, and respondents were asked to provide examples of what they considered formal training. Examples ranged from 2-day training seminars to more intensive graduate coursework including PhD training programs. Lack of a standard definition of formal research training was a limitation of the study. However, on the basis of the number of individuals reporting completion of master’s or PhD programs, these likely account for most but not all of the formal programs referenced. Some respondents also reported more limited or discrete training opportunities, suggesting that even smaller-scale opportunities to provide research training, such as retreats and short courses, could have substantial positive impact on clinician self-efficacy in research. This finding is important because it is highly actionable for individual institutions, specialty colleges, and other professional organizations positioned to offer continuing education opportunities in clinical research to their membership.
The task with the lowest reported self-efficacy in the present study related to performing advanced statistical methods. Formal research training did enhance comfort with statistical analysis in general. While this finding suggests that additional statistical training could be helpful to veterinary clinician-scientists, it also serves as a reminder that academic clinicians will benefit from reliable access to biostatisticians who can provide advanced support in this domain, as advanced training in methods beyond routine comparisons is likely outside the scope of what would be considered a relevant skill set for most veterinary clinicians.
Tasks related to funding a study, including speaking with a funding agency about a potential project, establishing a sufficient timeline for a grant application, establishing collaborator and consultant agreements for a grant application, and writing a competitive grant application, also received relatively low self-efficacy scores compared to other tasks. These tasks represent important areas where clinician-development opportunities could focus by helping to improve familiarity with grant application processes, assisting clinicians to make connections with funding agencies, and providing support for grant writing and preparation of supporting documents. Self-efficacy was improved for many tasks associated with obtaining funding when individuals had completed a formal research training, while only self-efficacy in the task of “speaking with a person at the funding agency regarding your project or project idea” was improved with increased years in academic practice.
Respondents in the present study also reported low self-efficacy in conducting qualitative studies, and comfort in this area did not increase with formal research training or years of experience. This likely reflects the focus on quantitative study designs classically emphasized across the health science landscape, but it does suggest an area of opportunity for veterinary clinician development. Qualitative studies can be highly valuable for describing complex phenomena, generating hypotheses, explaining behavioral patterns, and more deeply investigating data generated by quantitative research. Many important topics in veterinary medicine can be studied via qualitative methods; for example, the scholarship of teaching and learning, research on drivers of medical errors, or factors that impact pet owner acceptance of specific treatment recommendations. Lack of familiarity with qualitative methods could prevent faculty from pursuing studies focused on important knowledge gaps that would be best filled by these types of study designs.
Other tasks with relatively low overall confidence were interpersonal in nature, including terminating a collaboration that isn’t working and asking a staff member to leave a project. In these areas, there was no apparent influence of formal research training on self-efficacy; however, improved self-efficacy was associated with increased number of years in an academic faculty position. Respondents with an increasing number of years in role also reported enhanced self-efficacy in speaking with a person at a funding agency about their project, training assistants to collect data, sustaining effective collaborations, project management, and journal selection for publication. These findings suggest an important role for faculty mentoring committees, in addition to formal training opportunities, in areas for which self-efficacy appears to be developed experientially over the course of a career.
A limitation of this study was that all data were self-reported. While this is the nature of approaches that gather measures of self-efficacy, self-efficacy cannot be directly equated to competency or expertise. The literature does support that enhanced self-efficacy results in enhanced participation in clinical research by clinicians and measures that improve self-efficacy also improve research participation.10 Enhanced participation itself is an important outcome for academic veterinary clinicians given the ever-growing landscape of clinical study opportunities and the growing importance of supporting veterinary healthcare advances through impactful and innovative research activities. Further, most respondents in the present study indicated that participating as a member of a clinical study team is or has been a task that fell within their job as an academic clinician in the last 5 years. Increased self-efficacy in job-related tasks has been shown to enhance worker engagement, reduce burnout, and lead to overall higher levels of job satisfaction in both healthcare- and non–healthcare-focused career domains.11–13 These considerations are particularly important, given the potential for selection bias in the population of clinicians responding to this survey toward research-motivated individuals, suggesting that self-efficacy in the present study is more likely to be an overestimation of confidence for the general population of academic clinicians rather than an underestimation.
This study highlights the need for developing targeted training opportunities and other resources for academic veterinary clinicians in biostatistical support, qualitative study design methods, and aspects of communication and interpersonal skills that are important for developing and leading effective research teams, including forming effective collaborations, terminating ineffective ones, and training laboratory members. Additionally, confidence in many areas differs substantially across clinicians, suggesting that opportunities for clinician development in all domains covered by the mvCRAI will improve self-efficacy for a segment of academic clinicians. Future studies should focus on the impact of formal training sessions on various domains of self-efficacy and on the role of mentoring committees in supporting confidence in more experiential learning domains.
Supplementary Materials
Supplementary materials are posted online at the journal website: avmajournals.avma.org.
Acknowledgments
None reported.
Disclosures
The authors have nothing to disclose. No AI-assisted technologies were used in the generation of this manuscript.
Funding
The authors have nothing to disclose.
ORCID
S. Moore https://orcid.org/0000-0002-4311-6199
A. O’Kell https://orcid.org/0000-0002-3412-0575
References
- 1.↑
Lachance K, Heustis RJ, Loparo JJ, Venkatesh MJ. Self-efficacy and performance of research skills among first-semester bioscience doctoral students. CBE Life Sci Educ. Published online July 28, 2020. doi:10.1187/cbe.19-07-0142
- 2.↑
Mullikin EA, Bakken LL, Betz NE. Assessing research self-efficacy in physician-scientists: the Clinical Research APPraisal Inventory. J Career Assess. 2007;15(3):367-387. doi:10.1177/1069072707301232
- 3.↑
Robinson GFWB, Switzer GE, Cohen ED, et al. A shortened version of the Clinical Research Appraisal Inventory: CRAI-12. Acad Med. 2013;88(9):1340-1345. doi:10.1097/ACM.0b013e31829e75e5
- 4.↑
Gardner HL, Fenger JM, London CA. Dogs as a model for cancer. Annu Rev Anim Biosci. 2016;4(1):199-222. doi:10.1146/annurev-animal-022114-110911
- 5.
Nardone R, Höller Y, Taylor AC, et al. Canine degenerative myelopathy: a model of human amyotrophic lateral sclerosis. Zoology (Jena). 2016;119(1):64-73. doi:10.1016/j.zool.2015.09.003
- 6.↑
Hubbard ME, Arnold S, Bin Zahid A, et al. Naturally occurring canine glioma as a model for novel therapeutics. Cancer Invest. 2018;36(8):415-423. doi:10.1080/07357907.2018.1514622
- 7.↑
Bertout JA, Baneux PJR, Robertson-Plouch CK. Recommendations for ethical review of veterinary clinical trials. Front Vet Sci. 2021;8:715926. doi:10.3389/fvets.2021.715926
- 8.
Moore SA, O’Kell A, Borghese H, Garabed R, O’Meara H, Baneux P; CTSA One Health Alliance. A CTSA One Health Alliance guidance on institutional review of veterinary clinical studies. BMC Vet Res. 2021;17(1):83. doi:10.1186/s12917-021-02790-4
- 9.↑
Moore SA, McCleary-Wheeler A, Coates JR, Olby N, London C. A CTSA One Health Alliance (COHA) survey of clinical trial infrastructure in North American veterinary institutions. BMC Vet Res. 2021;17(1):90. doi:10.1186/s12917-021-02795-z
- 10.↑
Lynch MT, Zhang L, Korr WS. Research training, institutional support, and self-efficacy: their impact on research activity of social workers. Adv Soc Work. 2009;10(2):193-210. doi:10.18060/219
- 11.↑
Ortan F, Simut C, Simut R. Self-efficacy, job satisfaction and teacher well-being in the K-12 educational system. Int J Environ Res Public Health. 2021;18(23):12763. doi:10.3390/ijerph182312763
- 12.
Bernales-Turpo D, Quispe-Velasquez R, Flores-Ticona D, et al. Burnout, professional self-efficacy, and life satisfaction as predictors of job performance in health care workers: the mediating role of work engagement. J Prim Care Community Health. 2022;13:21501319221101845. doi:10.1177/21501319221101845
- 13.↑
Alshammari MH, Alenezi A. Nursing workforce competencies and job satisfaction: the role of technology integration, self-efficacy, social support, and prior experience. BMC Nurs. 2023;22(1):308. doi:10.1186/s12912-023-01474-8