Purpose: Expressing opinions and ideas in the workplace is an important aspect of organizational development and employee well-being. However, employee voice intention, which refers to an employee's willingness to share their opinions or ideas, is an area that has received limited attention in research. Therefore, the aim of this study was to develop and validate a reliable measurement tool for employee voice intention.
Methods: The study followed a three-stage process. First, in-depth interviews were conducted with managers and employees from Chinese companies, resulting in 38 qualitative data points. Second, the employee voice intention scale was developed and validated through two surveys. Exploratory factor analysis (N=264) and confirmatory factor analysis (N=260) were performed, respectively. Third, the predictive validity of the scale was assessed by collecting 366 valid responses across three rounds of questionnaires, using voice efficacy and employee voice behavior as correlational calibration criteria.
Results: The study employed grounded theory methodology to analyze the qualitative data collected, resulting in the development of a robust conceptual framework of employee voice intention. This framework is composed of two dimensions: perceived desirability and perceived feasibility, which together capture the key factors that influence whether an employee will express their opinions or ideas within an organizational context. A corresponding measurement scale was developed, consisting of nine measurement items that underwent rigorous testing to ensure their reliability and validity. Furthermore, the results of the empirical study showed that employee voice intention mediated the positive effect of voice efficacy on voice behavior, supporting the scale's predictive validity.
Conclusion: This study provides valuable insights into the dimensions of employee voice intention and contributes significantly to the existing literature on this topic by introducing a reliable and valid measurement tool. Furthermore, it advances our understanding of the underlying dimensions associated with this construct.
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http://dx.doi.org/10.2147/PRBM.S414623 | DOI Listing |
Trials
December 2024
School of Medicine Depts of Pediatrics, Neurology and Pharmacology, Children's Hospital Colorado/University of Colorado, 12800 E 19th, MS8102, Aurora, CO, 80045, USA.
Introduction: The clinical, research and advocacy communities for Rett syndrome are striving to achieve clinical trial readiness, including having fit-for-purpose clinical outcome assessments. This study aimed to (1) describe psychometric properties of clinical outcome assessment for Rett syndrome and (2) identify what is needed to ensure that fit-for-purpose clinical outcome assessments are available for clinical trials.
Methods: Clinical outcome assessments for the top 10 priority domains identified in the Voice of the Patient Report for Rett syndrome were compiled and available psychometric data were extracted.
Prim Health Care Res Dev
December 2024
Department of Pharmacy and Pharmacology, University of Bath, Claverton Down, Bath and Northeast Somerset, UK.
Aim: We aimed to explore participant perspectives on social prescribing (SP) for mental health and well-being and the acceptability of community pharmacists (CP) as members of SP pathways that support people with mild to moderate depression and anxiety.
Background: SP aims to support people with poor health related to socio-demographic determinants. Positive effects of SP on self-belief, mood, well-being, and health are well documented, including a return to work for long-term unemployed.
Lancet Digit Health
December 2024
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK; Centre for Patient Reported Outcomes Research, School of Health Sciences, College of Medical and Dental Sciences, Birmingham, UK; University of Birmingham, Birmingham, UK. Electronic address:
Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups.
View Article and Find Full Text PDFRespir Res
December 2024
MSD, Puteaux, France.
Introduction: Recurrent respiratory papillomatosis (RRP) is a chronic disease caused by human papillomavirus (HPV), characterized by recurrent papillomas in the respiratory tract. Presenting as either juvenile-onset RRP (JoRRP) or adult-onset RRP (AoRRP), the severity of the disease is subjective and unpredictable. Lack of curative therapies necessitates disease management involving repeated surgical removal of lesions.
View Article and Find Full Text PDFBMC Public Health
December 2024
Health Management and Policy School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Background: Lack of accountability within healthcare systems contributes to suboptimal healthcare quality and ultimately poor health outcomes, especially in low-income countries. In Uganda, our research team implemented a pilot project of quarterly health accountability meetings between community members and their local political leaders to discuss healthcare needs and strategies for quality improvement. In this study, we examine the community members' understanding and perceptions of the health accountability meetings, as well as the perceived impact of the meetings on local healthcare services and community life.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!