Influence of the expertise, collaborative efforts and trustworthiness of pharmacists on the prescribing decisions of physicians

The relationship between the pharmacist's role, patient understanding and satisfaction during the provision of a cost-effective pharmacist-led intervention

RATIONALE, AIMS AND OBJECTIVES

This study aimed to investigate the relationship between the pharmacist's role, patient understanding and satisfaction during the provision of a cost-effective pharmacist-led intervention using structural equation modelling (SEM). SEM is a group of statistical techniques used in different disciplines to model latent variables and evaluate theories.

METHODS

A validated questionnaire was used to gather patient views on a pharmacist-led intervention. A conceptual model was developed to test the statistical significance of the relationship between patient understanding and satisfaction, the pharmacist's role and patient understanding, the pharmacist's role and patient satisfaction. In addition, the study evaluated the model's in-sample and out-of-sample predictive power. The analysis tested fours hypotheses (H): 1) There was no significant relationship between patient understanding and patient satisfaction; 2) There was no significant relationship between the pharmacist's role and patient understanding; 3) There was no significant relationship between the pharmacist's role and patient satisfaction; 4) The in-sample and out-of-sample predictive power of the model. Data were analysed using Smart-PLS software version 3.2.8.

RESULTS

Two hundred and forty-six patients returned the questionnaire. Construct reliability, validity (Cronbach's alpha〉0.70, ⍴A>0.70, ⍴C>0.70), average extracted variance (AVE〉0.50) and discriminant validity (HTMT<0.85) were confirmed. The structural model and hypothesis testing results showed that all hypotheses were supported in this study. Path coefficients and effect sizes suggested that the pharmacist's role played a significant part in patient understanding (H2, β=0.650, f² =0.730, p<0.001), which then influenced patient satisfaction (H1, β=0.474, f² =0.222, p<0.001). The in-sample and out-of-sample predictive powers were moderate.

CONCLUSIONS

Patient satisfaction is becoming an integral component in healthcare provision and evaluation of healthcare quality. The results support using structural equation modelling to assess the link between the pharmacist's role and patient understanding and satisfaction when delivering cost-effective pharmacist-led interventions.

A conceptual model for students' satisfaction with team-based learning using partial least squares structural equation modelling in a faculty of life sciences, in the United Kingdom

PURPOSE

Students' satisfaction is an essential element in higher education. This study aimed to identify paths and predictive power of students' satisfaction during team-based learning (TBL) activities in the faculty of life sciences using partial least squares structural equation modelling (PLS-SEM).

METHODS

In 2018-2019, at the University of Sussex (Falmer, UK), 180 life science students exposed to TBL were invited to participate in the study. Team-Based-Learning-Student-Assessment-Instrument was used. A conceptual model was developed for testing six hypotheses. H1: What was the effect of TBL on student satisfaction? H2: What was the effect of lectures on student satisfaction? H3: What was the effect of TBL on accountability? H4: What was the effect of lectures on accountability? H5: What was the effect of accountability on student satisfaction? H6: What were the in-sample and out-of-sample predictive power of the model? The analysis was conducted using the PLS-SEM approach.

RESULTS

Ninety-nine students participated in the study giving a 55% response rate. Confirmatory tetrad analysis suggested a reflective model. Construct reliability, validity, average extracted variance, and discriminant validity were confirmed. All path coefficients were positive, and 5 were statistically significant (H1: β=0.587, P<0:001; H2: β=0.262, P<0.001; H3: β=0.532, P<0.001; H4: β=0.063, P=0.546; H5: β=0.200, P=0.002). The in-sample predictive power was weak for Accountability, (R2=0.303; 95% confidence interval [CI], 0.117-0.428; P<0.001) and substantial for Student Satisfaction (R2=0.678; 95% CI, 0.498-0.777; P<0.001). The out-of-sample predictive power was moderate.

CONCLUSION

The results have demonstrated the possibility of developing and testing a TBL conceptual model using PLS-SEM for the evaluation of path coefficients and predictive power relative to students' satisfaction.