Which comment would most likely positively influence a student with weak self-efficacy

Am J Pharm Educ. 2016 Aug 25; 80[6]: 95.

Abstract

Objective. To develop and test a conceptual model that hypothesized student intention to undertake a higher degree in pharmacy practice research [PPR] would be increased by self-efficacy, outcome expectancy, and the social influence of faculty members.

Methods. Cross-sectional surveys were completed by 387 final-year pharmacy undergraduates enrolled in 2012 and 2013. Structural equation modeling was used to explore relationships between variables and intention.

Results. Fit indices were good. The model explained 55% of the variation in intention. As hypothesized, faculty social influence increased self-efficacy and indirectly increased outcome expectancy and intention.

Conclusion. To increase pharmacy students’ orientation towards a career in PPR, faculty members could use their social influence by highlighting PPR in their teaching.

Keywords: Students, pharmacy, practice research, self-confidence, social norms, psychosocial

INTRODUCTION

Ever since Hepler and Strand’s seminal work advocating for the provision of pharmaceutical care,1 nontraditional services in pharmacy practice have increased throughout the world. This expansion of the of pharmacist’s role has been accompanied by increasing inclusion of social and administrative pharmacy content embedded in pharmacy curriculum.2 Along with the need for students to learn social and administrative pharmacy content is the need for them to develop research skills in preparation for emerging roles and those in clinical pharmacy.3

Training in pharmacy practice research [PPR] is an accepted component of professional pharmacy degrees in Australia and New Zealand,4 the United States,5 the United Kingdom,6 and Canada.7 Further, the Australian Pharmacy Council stipulates that each college or school of pharmacy must actively promote and support research and scholarship.4 Commentary from the United States further supports the need for the inclusion of research skills training in professional [doctoral] pharmacy programs.8 There may be a high level of diversity in the breadth and depth of PPR skills training offered by professional degree programs. Whether students are exposed to sufficient training for PPR is questioned in the United States9 and Arabic-speaking countries.10 While further research is needed to determine the effectiveness of PPR training [in terms of academic outcomes], this paper deals with students’ subjective experiences of PPR and their career goals.

Research and innovation are drivers for change and moulded the evidenced-based practice paradigm. Without practice research, the profession would stagnate and patients might not experience the potential benefits of expanded pharmacy services and standards of care. Research is needed to understand how best to design, implement, and evaluate outcomes of expanded services. Furthermore, as the profession expands and pharmacists pursue the opportunity to practice at an advanced level, research skills will become increasingly pertinent.11 In Australia, a new framework for the recognition of advanced practice has been developed, which states that advanced pharmacy practitioners will need to demonstrate research skill competencies.12 While it specifically assumes, for example, that all pharmacists need to be able to interpret research findings and integrate them into their practice,4 advanced pharmacy practitioners, akin to the medical model, will be required to actively participate in PPR.12 Advanced practitioners may be expected to, for example, conduct prescribing practice audits, implement the results of trial data into local practice procedures, and develop evidence-based treatment guidelines, protocols, or standards of practice at a local or national level.13

The number of Australian pharmacists working in roles that include a large component of research is probably not high. Health Workforce Australia [HWA], a statutory authority charged with building a sustainable health workforce, reported that, in 2012-2013, less than 3% of registered pharmacists were employed in academia or research.14 The report also suggested, however, that the recent increase in supply of pharmacists should be seen as “an opportunity to further pursue changing models of care and work settings, and opportunities for expanded scope of practice for pharmacists.”14 As opportunities for PPR expand, there will be a need for more pharmacy practice researchers.

In Australia, there is some discussion as to whether sufficient numbers of students enroll in higher research degrees across all disciplines.15 A concern is that there may be insufficient academic workforce in the near future as retiring academics leave their posts. Compounding the concern for pharmacy practice academia in Australia is the recent expansion in number of pharmacy schools and of students enrolled in the professional degrees. Therefore, there is a need for research to be conducted within pharmacy schools aimed at understanding how to facilitate students’ interest in pursuing a career in PPR.

It is to be expected that student experience during undergraduate curriculum would have a notable effect on final-year students’ career expectations and goals. This expectation is supported by Wilson et al’s study conducted in the United Kingdom, where final-year pharmacy students’ perceptions of the main influence on their career choice were ranked in the following order: course content, hospital pharmacy visits and placements, and pharmacy practice lecturers.16 However, students enrolled in professional degree program at The University of Sydney reported that they had limited opportunities to actively participate in PPR during the curriculum or on placement.17 Within that degree, students can gain specific research training through the honors program [around 15%], and approximately half of the students conduct projects related to pharmacy practice. However, pharmacy practice topics are delivered in depth during the third and fourth years where research-led teaching is intended to introduce students to the concepts around the design, conduct, and critical evaluation of PPR findings. Therefore, many students may be exposed to the concept of PPR through interactions with pharmacy practice academics, particularly toward the end of the degree. A major focus of this paper is, therefore, the social learning about PPR that occurs as a consequence of students’ formal and informal contact with PPR educators and that runs in tandem with the delivery of curriculum.

Kritikos and colleagues explored students’ perceptions of PPR in a 4-year undergraduate pharmacy degree in a research-intensive pharmacy school.17 Their research was designed to develop and validate the measurement of these perceptions at various stages of students’ progression through the curriculum. While this research explored students’ perceptions, it did not attempt to relate these perceptions to final-year students’ career goals in PPR. This study builds on previous research to explore the relationship between; students’ perceptions of the extent to which faculty members portray favorable attitudes towards PPR and their career goals centered on PPR.17

Bandura’s social cognitive theory [SCT] was used as a framework for the present study because it recognizes that an individual’s thoughts and behaviors have a social context.18 These thoughts and behaviors are impacted by a combination of observation and direct experience. Further, SCT has been used as a framework to develop an educational theory of how social learning influences graduate students’ career intentions.19 The theory holds that goal systems play an important role in the self-regulation of behavior.20 In the context of career-related goals, making decisions to apply for or accept a particular position is the most specific goal. Other goal-setting activities occur earlier in the process and include holding aspirations, developing career plans, and formulating [and stating] intentions. Turning to the present study, if Australian final-year pharmacy students wished to pursue a career in PPR, the most logical and salient step for them would be to consider undertaking a higher degree in PPR, at some stage after graduation. It could be argued that students may consider a career in PPR without undertaking a higher degree. However, the authors believe that the most conceptually accessible step towards achieving this career goal would be to do a higher degree. Therefore, the aim of the research was to develop and test a model, based on SCT, of final-year students’ intention to undertake a higher degree in PPR after graduation.

METHODS

In essence, SCT posits that whether a person is motivated to undertake a particular activity may be influenced by their expectations of their capacity to undertake the activity [self-efficacy] and their expectations about the outcome of participating in the activity [outcome expectancy].18 A diagram of the hypothesis generated from this model is provided in Figure 1. In the present case, self-efficacy may be described as students’ perception of their ability to conduct PPR. To undertake PPR after graduation, consistent with SCT, students would benefit from self-confidence in their understanding of how to design, conduct, and evaluate the findings of PPR in the context of clinical practice. It was hypothesized that having high self-efficacy would positively influence intention. In the theory, self-efficacy is thought to influence a person’s intention to act both directly and indirectly by increasing outcome expectancy.20 In this context, outcome expectancy may be described as students’ expectations of whether conducting PPR research after graduation would be enjoyable and beneficial for them and their career. We hypothesized that having high positive outcome expectancy would positively influence intention.

Conceptual Model of Final-year Students’ Intention to Undertake a Higher Degree in Pharmacy Practice Research

An essential element of SCT is the social influence that others have on our thoughts and feelings about our goal behavior, which occurs during our vicarious learning experiences.21 Social influence, which is an element of persuasion, occurs when individuals are led or mentored by persons whom they believe have the capability to perform the task of interest. Self-efficacy may be markedly influenced by the modeling behavior and verbal persuasion of such individuals.21 In the present context, “faculty social influence” is defined as students’ perceptions of the extent to which their PPR teachers discuss and emphasize PPR in the undergraduate teaching environment. We hypothesized that high levels of faculty social influence would have a positive effect on self-efficacy and a direct or indirect effect on outcome expectancy.

Our vicarious learning experiences of research should be more salient and influential if we are actually exposed to the processes of conducting research. Assuming that learning experiences about research were positive, consistent with SCT, its effect would be to increase self-efficacy and outcome expectancy. Exposure to research could occur during the course of the bachelor of pharmacy [BPharm] degree program, and this was named “academic exposure to research.” Exposure to research could also occur through experiences unrelated to formal education, such as contact with family and friends, which was named “social exposure to research.”

This was a cross-sectional study using the analytical method of structural equation modeling [SEM], chosen because it allows researchers to test hypotheses between latent variables, or unobserved variables. Latent variables are typically psycho-social constructs and in the present study were self-efficacy, outcome expectancy, faculty social influence, and intention. While latent variables cannot be measured directly, they may be estimated by modeling relationships between observed variables and the latent variable. The advantage of SEM is that it enables researchers to test hypotheses while simultaneously providing evidence of the reliability of the relationship between the observed variables and the latent variables.22 The SEM techniques were performed and reported in accordance with Schreiber.23

Respondents were eligible for inclusion in this study if they were enrolled in the final year of the 4-year pharmacy undergraduate program at the University of Sydney in Australia. To provide sufficient sample size the survey was conducted in 2012 and repeated in 2013.

The questionnaire was adapted from Winans and Madhavan.24 It contained 25 psycho-social items, 16 providing demographic and educational background information, and five allowing for free-text responses [not reported in the present study]. The demographic information collected in the questionnaires included age, gender, and whether the respondent was born in Australia. Other information relevant to educational background was probed using responses to yes/no questions such as whether the student had received a scholarship to study or had an educational loan to repay. The small numbers of students enrolled in the honors program were not identified to ensure anonymity among respondents.

Measuring whether students perceived academic and social exposure to research to be a positive experience would require generating new measurement scales, which was beyond the scope of the study. Exposure to research was conceptualized as either exposed or not. Academic exposure to research was measured by asking respondents a single question “Have you been exposed to or involved in any research during your education” with a yes/no response [1=yes, 0=no]. There were four items designed to determine the level to which a student had been exposed to [any] research through social contact with family or friends: “Are any immediate family members involved in research? Are any other family members involved in research? Are any of your friends involved in research? Do you have a mentor involved in research?” An index of social exposure to research was formed by summing the responses to the four yes/no questions [1=yes, 0=no]. Thus, the index score could theoretically range from zero to 4.

For all the other items used in the SEM, respondents provided their level of agreement with statements on a 5-point Likert scale. Following the guidance of Rossiter, a single item was selected for the dependent variable because intention to undertake a higher degree in PPR [intention] is a relatively concrete attribute.25 Respondents were asked to provide their level of agreement to the statement “I am likely to pursue a pharmacy practice research degree [eg, PhD/MPhil] in the future.” Faculty social influence, outcome expectancy, and self-efficacy were eliciting attributes,25 which required the use of multiple items to ensure the measures probe the set of beliefs that comprise the construct. Therefore, the remaining items were those used in Winans’ and Madhavan’s study.24 The psychometric properties of the measurement scales were subsequently explored in research conducted by Kritikos et al, among 853 University of Sydney students across the four years of the undergraduate program.17 Self-efficacy was measured with three items. In Kritikos et al’s research, this construct was called “confidence to do PPR” and had acceptable reliability [Cronbach alpha=0.77].17 Outcome expectancy was measured with seven items. In Kritikos et al’s research, three items were removed from this scale to reduce cross-loadings, leaving just four items. In the present study, all seven items were included because the three deleted items explored students’ perceptions regarding the benefit of doing PPR in relation to employment goals. Inclusion of these items was in keeping with the original meaning of outcome expectancy as defined by Bandura. Faculty social influence was measured with three items. In the research of Kritikos et al, this construct was called “faculty involvement of students in PPR” and had acceptable reliability [Cronbach alpha=0.70].

All enrolled students were invited to complete the voluntary, anonymous survey during tutorial time in the final week of the last semester. Completion of the survey instrument implied informed consent. No incentives were offered to respondents. Approval for the project was given by the University of Sydney Human Ethics Committee.

For descriptive statistical analyses and exploratory factor analysis [EFA], SPPS 21.0.0.0 [SPSS Inc., Chicago, IL] was used. Confirmatory factor analysis [CFA] and structural equation modeling [SEM] were performed with AMOS 21.0.0 [SPSS Inc., Chicago, IL] using a maximum likelihood [ML] estimator.17 Structural equation modeling with ML estimation requires the presence of multivariate normality for dependent variables. Therefore, prior to performing the CFA, items intended to be used as dependent variables in the structural model were examined for evidence of skewness and kurtosis. Prior to using the multi-item measurement scales for CFA or SEM, a maximum likelihood EFA with oblique rotation was performed on the data from the sample of 2012 in order to test whether the scales were unidimensional. Since there was only one indicator for the dependent variable, a latent variable was created in which the error term for the indicator was fixed at [1-reliability] x observed variance, where the reliability was estimated to be 0.85.

Convergent validity of the multi-item scales was assessed by inspection of the results from CFA. Standardized factor loadings should exceed 0.50 with significance to demonstrate high convergence on a common point.26 In addition, the average variance extracted should equal or exceed 50%.26 The composite reliability [CR] of these scales was computed using the formula suggested by Fornell and Larcker,27 where values equal to or greater than 0.7 indicate that the construct of the model is reliable.26 Discriminant validity was assessed using the paired construct method of Anderson and Gerbing.22 The technique of factorial invariance was employed to search for consistency in factor structure for each of the two groups of students [2012, 2013].28 According to Wu et al, data from different groups may be considered essentially equivalent and therefore pooled when strict invariance is demonstrated.29 Using the method of Westlund,30 with four latent constructs and 14 indicators [including the dependent variable], a sample size of more than 313 was deemed necessary to detect a minimum effect size of 0.20 with a power of 0.8 and p