Conscientious objection - a cross-sectional, vignette-based, mixed methods exploration of Australian pharmacists' perspectives.

Background: Conscientious objection (CO) in healthcare is a controversial topic. Some perceive CO as freedom of conscience, others believe their professional duty-of-care overrides personal-perspectives. There is a paucity of literature pertaining to pharmacists' perspectives on CO. Aim: To explore Australian pharmacists' decision-making in complex scenarios around CO and reasons for their choices. Method: A cross-sectional, qualitative questionnaire of pharmacists' perspectives on CO. Vignette-based questions were about scenarios related to medical termination, emergency contraception, IVF surrogacy for a same-sex couple and Voluntary Assisted Dying (VAD) Results: Approximately half of participants (n = 223) believed pharmacists have the right to CO and most agreed to supply prescriptions across all vignettes. However, those who chose not to supply (n = 20.9%), believed it justifiable, even at the risk of patients failing to access treatment. Strong self-reported religiosity had a statistically significant relationship with decisions not to supply for 3 of 4 vignettes. Three emergent themes included: ethical considerations, the role of the pharmacist and training and guidance. Conclusion: This exploratory study revealed perspectives of Australian pharmacists about a lack of guidance around CO in pharmacy. Findings highlighted the need for future research to investigate and develop further training and professional frameworks articulating steps to guide pharmacists around CO.

Combinatorially restricted computational design of protein-protein interfaces to produce IgG heterodimers.

Redesigning protein-protein interfaces is an important tool for developing therapeutic strategies. Interfaces can be redesigned by in silico screening, which allows for efficient sampling of a large protein space before experimental validation. However, computational costs limit the number of combinations that can be reasonably sampled. Here, we present combinatorial tyrosine (Y)/serine (S) selection (combYSelect), a computational approach combining in silico determination of the change in binding free energy (ΔΔG) of an interface with a highly restricted library composed of just two amino acids, tyrosine and serine. We used combYSelect to design two immunoglobulin G (IgG) heterodimers-combYSelect1 (L368S/D399Y-K409S/T411Y) and combYSelect2 (D399Y/K447S-K409S/T411Y)-that exhibit near-optimal heterodimerization, without affecting IgG stability or function. We solved the crystal structures of these heterodimers and found that dynamic π-stacking interactions and polar contacts drive preferential heterodimeric interactions. Finally, we demonstrated the utility of our combYSelect heterodimers by engineering both a bispecific antibody and a cytokine trap for two unique therapeutic applications.

The Carer Assessment of MedicaTion Management GuidanCe for People With Dementia at Hospital Discharge (CATCH) Tool: Exploratory Factor Analysis.

PURPOSE: The Carer Assessment of medicaTion management guidanCe for people with dementia at Hospital discharge (CATCH) tool was developed to examine the carer's experiences of medication management guidance delivery at discharge. This study explored its factor structure, characterized carers' experiences at discharge, and identified predictors of carer preparedness to manage medications at discharge. METHODS: A cross-sectional survey of carers across Australia was distributed. Survey responses were analyzed descriptively, and exploratory factor and regression analyses were performed. RESULTS: A total of 185 survey responses were completed. Exploratory factor analysis revealed 2 factors in the CATCH tool: (1) shared and supported decision-making in medication management (16 items loading 0.47 to 0.93); 2) provision of medication management guidance that is easy to understand (4 items loading (0.48 to 0.82). Internal consistency was acceptable (Cronbach alpha >0.8). Almost 18% of participants stated that they were not included in decisions about medications for people with dementia. The carer reported that the measure of how guidance is provided was positively related to their confidence in the management of medications postdischarge and satisfaction ( P < 0.05 for both). CONCLUSIONS: The CATCH tool can give the patient and carer an opportunity to provide feedback on key elements of medication management guidance delivered at discharge.

Resilience and empathy in pharmacy interns: Insights from a three-year cohort study.

Background: Resilience and empathy are important attributes for healthcare professionals to navigate challenging work environments and providing patient-centred care. Knowledge about pharmacists' levels of resilience and empathy, particularly during the early stages of their careers, is limited. Objectives: To explore pharmacy interns' levels of resilience and empathy using the Connor-Davidson-Resilience-Scale-25 (CD-RISC-25) and the Kiersma-Chen-Empathy-Scale (KCES), examine potential associations with demographic characteristics and ascertain what challenges interns' resilience and which support mechanisms they identify. Methods: Hard copies of the surveys were distributed to three cohorts during face-to-face intern pharmacy workshops from 2020 to 2022. Additionally, a qualitative questionnaire explored interns' experiences while completing an accredited internship program during the COVID-19 pandemic. Data were analysed using descriptive and inferential statistics, open-ended questions were analysed through qualitative and quantitative content analysis. Results: Among 134 completed surveys, most respondents were female, aged 18-22, and worked in hospitals. The CD-RISC-25 mean score was 66.6 (SD 11.7) and the KCES mean was 84.3 (SD 9.23) indicative of intermediate levels of resilience and empathy. Resilience and empathy scores did not significantly differ between the three cohorts (p-value > 0.05), and both were not consistently correlated with each other (p-value > 0.05). No significant associations were found between demographic characteristics and resilience scores. However, age and pre-internship employment history showed a statistically significant association with empathy scores (p-value < 0.05), with younger age groups and those who worked part-time during undergraduate studies demonstrating higher levels of empathy. Challenges undermining interns' resilience included the COVID-19 pandemic, internship requirements, and feelings of inadequacy and inexperience. Conclusions: This study showed that resilience and empathy scores among interns were at what can be regarded as intermediate levels, largely unaffected by the COVID-19 pandemic or cohort demographics. It highlights professional aspects and strategies which are professionally sustaining and may assist interns in navigating challenges to their resilience and empathy.

Healthcare data integration using machine learning: A case study evaluation with health information-seeking behavior databases.

BACKGROUND: The amount of data in health care is rapidly rising, leading to multiple datasets generated for any given individual. Data integration involves mapping variables in different datasets together to form a combined dataset which can then be used to conduct different types of analyses. However, with increasing numbers of variables, manual mapping of a dataset can become inefficient. Another approach is to use text classification through machine learning to classify the variables to a schema. OBJECTIVES: Our aim was to create and evaluate the use of machine learning methods for the integration of data from datasets across health information-seeking behavior (HISB) databases. METHODS: Four online databases relevant to the research field were selected for integration. Two experiments were designed for dataset mapping: intra-database mapping using the one data source, and inter-database mapping to map datasets between the four databases. We compared logistic regression (LR), a random forest classifier (RFC), and neural network (NN) models by F1-score for two methods of integration. A third experiment was an ablation study that used all the available data to create a model for classifying HISB variables in a dataset. RESULTS: In intra-database mapping, the mean F1 score for an LR classifier (0.787) was better than the RFC score (0.767) and fully connected NN (0.735). In inter-database mapping, the LR (0.245) scored best, however, this was dependent on which database was used as a training source. Using all the databases, these top three models were able to correctly classify 90-91% of the variables. Removing one dataset improved scores and resulted in a model able to correctly classify 95-96% of the HISB variables. CONCLUSIONS: As part of data integration, a neural network can be used as an approach to map the variables of a dataset. The developed models can be used to classify the HISB terms in a database.

Correction: Predictors of Health Information-Seeking Behavior: Systematic Literature Review and Network Analysis.

[This corrects the article DOI: 10.2196/21680.].

Missing data in surveys: Key concepts, approaches, and applications.

A recent review of missing data in pharmacy literature has highlighted that a low proportion of studies reported how missing data was handled. In this paper we discuss the concept of missing data in survey research, how missing data is classified, common techniques to account for missingness and how to report on missing data. The paper provides guidance to mitigate the occurrence of missing data through planning. Considerations include estimating expected missing data, intended vs unintended missing data, survey length, working with electronic surveys, choosing between standard and filtered form questions, forced responses and straight-lining, as well as responses that can generate missingness like "I don't know" and "Not Applicable". We introduce methods for analysing data with missing values, such as deletion, imputation and likelihood methods. The manuscript provides a framework and flow chart for choosing the appropriate analysis method based on how much missing data is observed and the type of missingness. Special circumstances involving missing data have been discussed, such as in studies with repeated or cohort measures, factor analysis or as part of data integration. Finally, a checklist of questions are provided for researchers to guide the reporting of the missing data when conducting future research.

Predictors of Health Information-Seeking Behavior: Systematic Literature Review and Network Analysis.

BACKGROUND: People engage in health information-seeking behavior to support health outcomes, and being able to predict such behavior can inform the development of interventions to guide effective health information seeking. Obtaining a comprehensive list of the predictors of health information-seeking behavior through a systematic search of the literature and exploring the interrelationship of these predictors are critical first steps in this process. OBJECTIVE: This study aims to identify significant predictors of health information-seeking behavior in the primary literature, develop a common taxonomy for these predictors, and identify the evolution of the concerned research field. METHODS: A systematic search of PsycINFO, Scopus, and PubMed was conducted for all years up to and including December 10, 2019. Quantitative studies identifying significant predictors of health information-seeking behavior were included. Information seeking was broadly defined and not restricted to any source of health information. Data extraction of significant predictors was performed by 2 authors, and network analysis was conducted to observe the relationships between predictors with time. RESULTS: A total of 9549 articles were retrieved, and after the screening, 344 studies were retained for analysis. A total of 1595 significant predictors were identified. These predictors were categorized into 67 predictor categories, with the most central predictors being age, education, gender, health condition, and financial income. With time, the interrelationship of predictors in the network became denser, with the growth of new predictor grouping reaching saturation (1 new predictor identified) in the past 7 years, despite increasing publication rates. CONCLUSIONS: A common taxonomy was developed to classify 67 significant predictors of health information-seeking behavior. A time-aggregated network method was developed to track the evolution of the research field, showing the maturation of new predictor terms and an increase in primary studies reporting multiple significant predictors of health information-seeking behavior. The literature has evolved with a decreased characterization of novel predictors of health information-seeking behavior. In contrast, we identified a parallel increase in the complexity of predicting health information-seeking behavior, with an increase in the literature describing multiple significant predictors.

Use of Visual Dashboards to Enhance Pharmacy Teaching.

Teaching large cohorts of pharmacy students with a team of multiple tutors in a feedback intensive course poses challenges in relation the amount of data generated, data integrity, interpretation of the data and importantly application of the insights gained from the data. The dispensing and counselling course in the third year BPharm at the University of Sydney has implemented the USyd Pharmacy Dashboard, developed to address these challenges following the Technological Pedagogical Content Knowledge Framework (TPACK) to integrate technology into teaching. The dashboard was designed to improve the student experience through more consistent feedback, gain insights to improve teaching delivery and provide efficiencies in maintaining data integrity. The tool has been developed using an action-based research approach whereby ideas are put into practice as the means to further develop the idea and improve practice. Refinement of the USyd Pharmacy Dashboard over three years has shown improvements in teaching delivery as teachers can respond to emerging trends. Student performance and satisfaction scores have increased, mainly due to improved consistency between tutors and improved delivery of feedback. Time involved with administrative tasks such as data maintenance is reduced. Opportunities for further refinements such as real time benchmarking and developing an open learner model have become apparent.

How to measure a latent construct: Psychometric principles for the development and validation of measurement instruments.

Measurement instruments are used to collect data about respondents. In social pharmacy, measurement instruments are often used to measure latent constructs, such as attitudes, among healthcare professionals and patients. This paper aims to describe the fundamental aspects of designing and validating instruments, which aim to measure latent constructs. The main focus of this manuscript is to describe the considerations and processes relating to exploratory and confirmatory factor analyses, when used to develop measures of latent psychosocial constructs. However, it also presents a detailed summary of the current evidence and suggestions for item generation and sample selection, as well as, an in-depth description of approaches to content and face validation. Suggestions for further reading are also provided.

Missing data reporting in clinical pharmacy research.

PURPOSE: This study aimed to document the ways by which missing data were handled in clinical pharmacy research to provide an insight into the amount of attention paid to the importance of missing data in this field of research. METHODS: Our cross-sectional descriptive report evaluated 10 journals affiliated with pharmacy organizations in the United States, Canada, the United Kingdom, and Australia. Randomized controlled trials, cohort studies, case-control studies, and cross-sectional studies published in 2018 were included. The primary outcome measure was the proportion of studies that reported the handling of missing data in their methods or results. RESULTS: A total of 178 studies were included in the analysis. Of these, 19.7% (n = 35) mentioned missing data either in their methods (3.4%, n = 6), results (15.2%, n = 27), or in both sections (1.1%, n = 2). Only 4.5% (n = 8) of the studies mentioned how they handled missing data, the most common method being multiple imputation (n = 3), followed by indicator (n = 2), complete case analysis (n = 2), and simple imputation (n = 1). One study using multiple imputation and both studies using an indicator method also combined other strategies to account for missing data. One study only used complete case analysis for subgroup analysis, and the other study only used this method if a specific baseline variable was missing. CONCLUSIONS: Very few studies in clinical pharmacy literature report any handling of missing data. This has the potential to lead to biased results. We advocate that researchers should report how missing data were handled to increase the transparency of findings and minimize bias.

Validation of a questionnaire for consumers' perception of service quality in community pharmacy.

BACKGROUND: Consumer insights are vital to gain an understanding of service quality and enable its accurate measurement. Our team has previously developed a theory-based, qualitatively and quantitatively-informed service quality questionnaire for Australian community pharmacies with a price-focused marketing strategy (PFMS). The questionnaire assess 6 domains of service quality: Health and Medicines Advice, Non-Prescription Service, Relationship Quality, Technical Quality, Environmental Quality, and Health Outcomes. OBJECTIVE: The aim of this study was to validate the questionnaire through confirmatory factor analysis (CFA) using data from customers attending pharmacies with a service-focused marketing strategy (SFMS). METHODS: A 31 item questionnaire was administered to convenience sample of customers from 3 SFMS pharmacies. The collected data was analysed using CFA. Model parameters were estimated using the full information maximum likelihood (FIML) method. The model was revised on inspection of modification indices and fit statistics and tested for construct validity, construct reliability and measurement invariance. RESULTS: A total of 319 responses were collected for CFA. On examination of the modification indices, 4 items were deleted. The fit statistics for the final model were as follows: Satorra-Bentler scaled χ2 = 211.4, df = 155, CFI = 0.96, TLI = 0.95, RMSEA = 0.031 (90% confidence interval = 0.016-0.042). Construct validity of all constructs was established from positive convergent and discriminant validity tests. The composite reliability values for all constructs were ≥0.7, thus confirming construct reliability. A positive test for strong invariance confirmed that the model constructs are comparable across regional and metropolitan settings, gender, age and education level. CONCLUSIONS: This study has established the validity of the questionnaire as a measure of consumer perceptions of community pharmacy service quality. The tool can be applied in Australian community pharmacies in both metropolitan and regional settings to guide improvements in aspects of service provision.

Development of a questionnaire to measure consumers' perceptions of service quality in community pharmacies.

BACKGROUND: Recent changes within community pharmacy have seen a shift towards some pharmacies providing "value-added" services. However, providing high levels of service is resource intensive yet revenues from dispensing are declining. Of significance therefore, is how consumers perceive service quality (SQ). However, at present there are no validated and reliable instruments to measure consumers' perceptions of SQ in Australian community pharmacies. OBJECTIVES: The aim of this study was to build a theory-grounded model of service quality (SQ) in community pharmacies and to create a valid survey instrument to measure consumers' perceptions of service quality. METHODS: Stage 1 dealt with item generation using theory, prior research and qualitative interviews with pharmacy consumers. Selected items were then subjected to content validity and face validity. Stages 2 and 3 included psychometric testing among English-speaking adult consumers of Australian pharmacies. Exploratory factor analysis was used for item reduction and to explain the domains of SQ. RESULTS: In stage 1, item generation for SQ initially generated 113 items which were then refined, through content and face validity, down to 61 items. In stage 2, after subjecting the questionnaire to psychometric testing on the data from the first pharmacy (n = 374), the use of the primary dimensions of SQ was abandoned leaving 32 items representing 5 domains of SQ. In stage 3, the questionnaire was subject to further testing and item reduction in 3 other pharmacies (n = 320). SQ was best described using 23 items representing 6 domains: 'health and medicines advice', 'relationship quality', 'technical quality', 'environmental quality', 'non-prescription service', and 'health outcomes'. CONCLUSION: This research presents a theoretically-grounded and robust measurement scale developed for consumer perceptions of SQ in a community pharmacy.

Marketing activity in the community pharmacy sector - A scoping review.

BACKGROUND: Community pharmacy ownership requires engaging with marketing strategies to influence consumer behaviour. There is a plethora of information from trade journals, expert opinion, and published discussion surrounding this issue. Despite this, evidence relating to the efficacy of marketing activity within the pharmacy sector is scant. OBJECTIVES: To review how marketing activity has been conceptualised in the community pharmacy sector and to determine the evidence for the effect of marketing activity. METHODS: Seven databases were systematically searched using a scoping review framework with the reporting protocol of PRISMA-P. The search yielded 33 studies that were analysed for year of publication, journal, country of focus, and framework of marketing. RESULTS: The majority of marketing research papers focused on the United States and were published in healthcare journals. These were various marketing strategy elements, including; segmentation, targeting, differentiation, and positioning. Also evident was research regarding marketing mix, which predominately involved the "4Ps" model. Actual marketing activity comprised little of the research. CONCLUSIONS: Research into marketing activity in community pharmacy is limited, and little evidence is available to show the effects of such activities. Future research needs to demonstrate the causality for the effect of marketing activities on consumer behaviour and economic outcomes.