An Assessment of the Effect of Education, In-Service Training (IST) and Tenure on Healthcare Performance: A Cost-Optimizing Perspective

Abstract

Healthcare institutions, governments and other stakeholders have over the years used employee education, in-service training and tenure prolongation to enhance the job performance of health professionals, which is termed healthcare performance in this study. The lack of adequate financial resources may however leave employers with the sole option of applying only one of these methods. This study attempts to identify the best predictor of healthcare performance that can be prioritized in cost-optimizing situations. Self-reported and supervisor-or superior-reported questionnaires were used to collect data from 1,163 health professionals in Accra North, who were selected using random sampling methods. Confirmatory Factor Analysis was used to test the study's hypotheses. The resulting model is of good fit at 5% significance level [Chi-square (χ 2 ) = 1.492; p = 0.222], with training found to be the ultimate method applicable if the need to use a single method arises. Nonetheless, the role of training as the ultimate applicable method is driven by tenure prolongation. The study concludes that in-service training is the ultimate method applicable for enhancing healthcare performance. Nevertheless, simultaneous application of training and tenure prolongation in non-financial or costoptimizing terms is recommended.

Psychometric Properties of a New Scale Measuring Neglect and Abuse of Older Adults in the Community: Implications for Social Activity

“…These statistics confirm convergent and discriminant validity based on the criteria MSV<AVE and ASV<MSV, respectively. 29,40,42,45 Our data met these requirements, an outcome that confirms that the new scale is appreciably valid. It is worth mentioning that some studies 35,41 that have produced good scales used today used less robust statistical procedures to confirm the internal consistency and validity of their scales.…”

“…Multivariate normality of the data, which is a requirement for confirmatory factor analysis, was met based on criteria established in the literature. [38][39][40] Pearson's correlation test was used to run bivariate correlations, whereas multiple linear regression analysis was used to assess the association between each domain of the scale and social activity. In interpreting bivariate correlations, a standard criterion (r < .3 ¼ small, .3 r .5 ¼ medium, and r !…”

The Influence of Community-Level Built Environment Factors on Active Social Network Size in Older Adults: Social Activity as a Moderator

“…Multivariate normality of the data, which is a requirement for confirmatory factor analysis, was met based on criteria established in the literature. 8,18,24 Pearson's correlation test was used to run bivariate correlations, and four regression models were built to examine relevant associations. The first of the models tested the influence of ABEFs on ASNS while adjusting for the demographic variables.…”

“….7 and factor loadings !0.5 for each factor and the overall scale. 24,26 Both criteria were met for social activity and ABEFs in Tables 1 and 2. Convergent validity was assessed with average variance extracted (AVE), maximum shared variance (MSV), and average shared variance (ASV), and the general rules of thumb applied in harmony with the literature are AVE !0.5 (for convergent validity) and MSV<AVE/ASV<MSV (for discriminant validity).…”