•Journal•ISSN: 2152-7180
Psychology
Scientific Research Publishing
About: Psychology is an academic journal published by Scientific Research Publishing. The journal publishes majorly in the area(s): Mental health & Population. It has an ISSN identifier of 2152-7180. It is also open access. Over the lifetime, 2262 publications have been published receiving 20246 citations.
Topics: Mental health, Population, Anxiety, Personality, Coping (psychology)
Papers published on a yearly basis
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TL;DR: Leiter et al. as mentioned in this paper used the job-demands-Resources model to predict work engagement and found that the model can be used to predict engagement and burnout, Demerouti, Cropanzano, and Bakker.
Abstract: Leiter, Bakker, Work Engagement: State of the Art. Schaufeli, Bakker, Defining and Measuring Work Engagement: Bringing Clarity to the Concept. Sonnentag, Dormann, Demerouti, Not All Days are Created Equal: The Concept of State Work Engagement. Taris, Schaufeli, Shimazu, The Push and Pull of Work: The Differences between Workaholism and Work Engagement. Sweetman, Lutgans, The Power of Positive Psychology: Psychological Capital and Work Engagement. Shirom, Feeling Energetic at Work: On Vigor's Antecendents. Hakanen, Roodt, Using the Job-Demands-Resources Model to Predict Engagement: Analysing a Conceptual Model. Halbesleben, A Meta-analysis of Work Engagement: Relationships with Burnout, Demands, Resources and Consequences. Salanova, Schaufeli, Xanthopoulou, Bakker, The Gain Spiral of Resources and Work Engagement: Sustaining a Positive Worklife. Spreitzer, Lam, Fritz, Engagement and Human Thriving: Complementary Perspectives on Energy and Connections to Work. Demerouti, Cropanzano, From Thought to Action: Employee Work Engagement And Job Performance. Leiter, Maslach, Building Engagement: The Design and Evaluation of Interventions. Bakker, Leiter, Where To Go From Here: Integration and Future Research on Work Engagement.
1,024 citations
TL;DR: In this article, the issue of what sample size and sample power the researcher should have in the EFA, CFA, and SEM study is reviewed. But, the existing literature provides limited and sometimes conflicting guidance on this issue.
Abstract: Adequate statistical power contributes to observing true relationships in a dataset. With a thoughtful power analysis, the adequate but not excessive sample could be detected. Therefore, this paper reviews the issue of what sample size and sample power the researcher should have in the EFA, CFA, and SEM study. Statistical power is the estimation of the sample size that is appropriate for an analysis. In any study, four parameters related to power analysis are Alpha, Beta, statistical power and Effect size. They are prerequisites for a priori sample size determination. Scale development in general and Factor Analysis (EFA, CFA) and SEM are large sample size methods because sample affects precision and replicability of the results. However, the existing literature provides limited and sometimes conflicting guidance on this issue. Generally, for EFA the stronger the data, the smaller the sample can be for an accurate analysis. In CFA and SEM parameter estimates, chi-square tests and goodness of fit indices are equally sensitive to sample size. So the statistical power and precision of CFA/SEM parameter estimates are also influenced by sample size. In this work after reviewing existing sample power analysis rules along with more elaborated methods (like Monte Carlo simulation), we conclude with suggestions for small samples in factor analysis found in literature.
568 citations
TL;DR: This article reviewed the literature on tolerance of ambiguity and related concepts since a previous review (Furnham & Ribchester, 1995) and made recommendations for the use of these tests in research.
Abstract: This review paper attempts to update the literature on tolerance of ambiguity (TA) and related concepts since a previous review (Furnham & Ribchester, 1995). Various related concepts like Uncertainly Avoidance and In/Tolerance of Uncertainly are reviewed. Both correlational and experimental studies of TA are reviewed and tabulated. Further, an attempt was made to identify and critique various different questionnaires design to measure TA. Recommendations for the use of these tests in research are made. The reasons for progress and lack of progress in this field are highlighted.
244 citations
TL;DR: In this paper, the authors investigated the relationship of demographic factors (age and job tenure) and job satisfaction facets with organizational commitment and found that a moderate significant positive relationship was found among job satisfaction, demographic factors, and organizational commitment.
Abstract: This study investigated the nature of relationships of demographic factors (age and job tenure) and job satisfaction facets with organizational commitment. The study also sought to determine the impact of demographic factors and job satisfaction facets on organizational commitment. A sample consists of 128 employees from service industry selected randomly. Employees were given a Job Descriptive Index (JDI) questionnaire and the Organizational Commitment questionnaire (OCQ). Pearson’s product moment correlation coefficient and multiple regression analyses were used to analyze the data. The Results of the study show that the mean values of job satisfaction and organizational commitment are at moderate side. A moderate significant positive relationship was found among job satisfaction facets, demographic factors, and organizational commitment. Supervision, pay, overall job satisfaction, age, and job tenure were the significant predictors of organizational commitment.
144 citations