Health Care Sciences Research Articles

Advancing scaling science in health and social care: a scoping review and appraisal of scaling frameworks

BackgroundScaling is typically discussed as a way to amplify or expand a health innovation. However, there is limited knowledge about the specific techniques that can enhance access to or improve the quality of innovations, aiming to increase their positive impacts for the public good. We sought to identify, compare, and contrast scaling frameworks to advance the science and practice of scaling.MethodsUsing a scoping review we asked: 1) What are the attributes of scaling frameworks for innovations that support health outcomes? and 2) What are the similarities and differences of these attributes? Inclusion criteria were 1) primary studies or review articles, 2) a primary focus on scaling innovations for health and social care, 3) articles that developed a framework, and 4) articles were concerned with a health outcome. Starting from an umbrella review, we identified relevant studies and extracted data about the characteristics of the articles, attributes of framework development, attributes of framework components, transferability, and the framework’s underlying ethical lens. Grey literature was included through expert consultation. Data were summarized using frequencies and qualitative description.ResultsFrom 94 potentially eligible articles, we identified 9 unique frameworks and included 4 additional frameworks from the grey literature, resulting in a total of 13 frameworks. Seven frameworks include a definition of scaling, and eight are designed for public health settings. Five of the frameworks were developed for the US/Canada/UK and Australia. Six of the lead authors’ primary institutional affiliation are from North America. Framework developers involved diverse stakeholders in a number of ways to develop their framework. Eight frameworks were developed, but not yet tested or applied, while the remaining frameworks were in the process of being applied or had already been applied to cases. All frameworks use a consequentialist-utilitarian ethical lens. Lastly, a comparison between frameworks found in the grey or published literature show important differences.ConclusionMuch may be learned through further support for, and development of, scaling frameworks by primary authors affiliated with the Global South. Important aspects of framework development were identified, especially understanding the nuances of diverse stakeholder involvement in development.

Comparing self-regulation strategies among adult learners from Poland, Serbia, Slovakia, and the Czech Republic

An active and constructive process whereby individuals possess the ability to develop, implement, and flexibly maintain planned behavior in order to achieve a desired achievement goal is referred to as self-regulation. The aim of the present study is to examine the factorial structure and psychometric properties of the Self-Regulation Questionnaire, validated in the Czech educational context (SRQ-CZ). The other target is to identify any usage of self-regulation strategies which may differ as nationality, gender, age, education, and internal motivation to learn come into play. A total of 1,711 adult learners from Poland, Serbia, Slovakia, and the Czech Republic who were enrolled in a formal secondary or higher education system pursuing professions in the field of humanities, social and health care sciences participated in this study. A measurement-invariant four-factor model was obtained across all countries (min. CFI, TLI = 0.918, and 0.902, max. RMSEA = 0.059; ω between 0.625 and 0.838, and Cronbach’s α between 0.622 and 0.837), including the Impulse Control, Goal Orientation, Self-Direction, and Decision Making subscales. Generally, the study confirmed a gradual increase in scores that measure positive self-regulatory qualities (Goal Orientation and Decision Making) and a decrease in unfavorable self-regulatory qualities (Impulse Control and Self-Direction) with higher age, education, and motivation, with no gender differences reported within countries. Moreover, scores on Goal Orientation and Decision Making dominated between countries. In conclusion, the SRQ-CZ demonstrated its suitability for cross-national comparisons, and personal characteristics appear to be important factors that distinguish those with high and low self-regulation.

Knowledge and perception of physiotherapy among healthcare science students at the Maldives National University

IntroductionPhysiotherapy is a crucial profession of interdisciplinary medical team, in which healthcare professionals need to comprehend the duties of other members in the team to offer a holistic management to the patients. Healthcare professionals who uphold negative beliefs and perceptions about other healthcare professions can be a barrier to ‘patient- centered’ approach. Nevertheless, there is a paucity of research on knowledge and awareness of physiotherapy by healthcare professionals or students. There has been no study conducted in the Maldives to investigate the knowledge and perception of physiotherapy by healthcare students. Therefore, the aim of the study was to explore the knowledge and perceptions among healthcare science students at The Maldives National University (MNU). MethodsA cross-sectional study was conducted at the Faculty of Health Sciences (FHS), School of Nursing (SN), and School of Medicine (SM). A stratified random sampling method was adopted to recruit the participants. A self-administered questionnaire was used to obtain the data from the participants. The data was analyzed using the SPSS version 25.ResultsA total of 318 students from three different schools and faculties of MNU participated in the study. The mean age of the respondents was 23 ± 4, with 89.9% being female. The overall K-score of 12 indicated poor knowledge, whereas the P-score of 10 reflected a positive perception among the participants, with no significant difference observed between genders. The Kruska-Wallis test indicated a significant difference in K-score across courses and years of study enrolled.ConclusionThis study’s findings revealed a disparity between healthcare students’ positive perception towards physiotherapy and their lack of knowledge regarding the profession, indicating barriers to knowledge acquisition. Significant differences were found between different healthcare courses and years of study.

Evolutionary Game Theory: A General Review

This article explores the Evolutionary Game Theory (now EGT), encompassing its historical underpinnings, recent advancements, and future potential. Originating in the 1970s through the pioneering work of John Maynard Smith and George R. Price, EGT leverages game-theoretic concepts to elucidate the evolution of strategies within various populations across biological, economic, and social domains. Notably, recent progress has seen the integration of advanced large language models (LLMs) such as GPT-3.5 and GPT-4 into agent-based simulations, thereby enriching the authenticity and intricacy of strategic interactions. Additionally, the study addresses the complexities associated with modeling diverse behaviors and bridging the insights derived from LLMs to practical applications in fields like biology, healthcare, education, and social sciences. Furthermore, it underscores the significance of interdisciplinary collaboration and innovative methodologies in addressing the multifaceted challenges within EGT. Finally, the article contemplates the potential avenues for future research, emphasizing the fusion of EGT with real-world applications and the necessity for comprehensive models that encompass the complexities of evolutionary dynamics in adaptive systems.

Causal discovery from nonstationary time series

AbstractThis paper introduces a new causal structure learning method for nonstationary time series data, a common data type found in fields such as finance, economics, healthcare, and environmental science. Our work builds upon the constraint-based causal discovery from nonstationary data algorithm (CD-NOD). We introduce a refined version (CD-NOTS) which is designed specifically to account for lagged dependencies in time series data. We compare the performance of different algorithmic choices, such as the type of conditional independence test and the significance level, to help select the best hyperparameters given various scenarios of sample size, problem dimensionality, and availability of computational resources. Using the results from the simulated data, we apply CD-NOTS to a broad range of real-world financial applications in order to identify causal connections among nonstationary time series data, thereby illustrating applications in factor-based investing, portfolio diversification, and comprehension of market dynamics.

Bibliometric analysis of citizen science in global healthcare: Current trends, challenges, and future directions

With the development of information technologies such as big data, cloud computing, and artificial intelligence, the application scenarios of citizen science worldwide are no longer limited to natural science research. A large number of application cases have emerged in the field of medical health, which suggests that the development of citizen science may bring new impetus to medical health. This study employs CiteSpace for a bibliometric analysis to evaluate the current status, objectives, and methodologies of citizen science in global healthcare. An analysis of 248 articles from the Web of Science Core Collection reveals that citizen science is predominantly implemented in high-income countries, including the United States, the United Kingdom, Germany, and the Netherlands, with significant applications in public health, chronic disease management, infectious disease surveillance, and digital health. The COVID-19 pandemic has further catalyzed the integration of citizen science into health surveillance and public health responses. Conversely, in low- and middle-income countries (LMICs), the development and implementation of citizen science remain nascent, primarily concentrated in traditional domains such as environmental science, ecology, and biodiversity conservation, with limited penetration into the healthcare sector. Several structural barriers, including inadequate technological infrastructure, insufficient policy support, limited public engagement, and constrained resource allocation, have impeded the broader adoption of citizen science in these regions. To mitigate these challenges, this study proposes targeted strategies, these interventions are anticipated to facilitate the expansion of citizen sciences role in global health governance, ultimately contributing to improved public health outcomes and social welfare.

Updating the critical steps of the quality implementation framework: a protocol for an umbrella review of reviews

IntroductionImplementation science focuses on improving the dissemination, uptake and adoption of evidence into practice. Over the last decade, implementation science research has proliferated, particularly in healthcare and social science. The...

From Data Analysis to Creative Arts: The Ubiquity and Impact of Artificial Intelligence in Academia

Integrating Artificial Intelligence in academia has revolutionized various fields with new opportunities for innovation, research, and learning. The capability of AI to analyze enormous amounts of data at such incredibly short times contributes to research advancement across natural sciences, humanities, social sciences, engineering, and healthcare sciences. For instance, in natural sciences, AI algorithms support various types of data analysis and simulation, helping to make new discoveries and provide methods and new approaches to look at existing research methods. AI advances in social sciences employ prediction modeling and machine learning to enhance economic models and other behavioral analyses. AI has presented humanities advancements in text analysis and interpretation of history work, augmenting the research based on historical data with data analysis. In engineering and technology, AI's role is twofold: enhancing physical security and, at the same time, posing new threats in the form of complex cyber threats. In a related context, AI’s application for diagnosis and treatment planning has been observed in the healthcare sector. It has shown the potential capability of improving the care of patients far beyond any imagined capabilities. Nevertheless, the application of AI in academia comes with some challenges. Privacy, protection, ethical views, and prejudice enhancement are some of the most significant issues that should be considered. Despite these challenges, AI creates multi-professional collaboration and advances in knowledge and performance in various scientific disciplines. AI continues to thrive in the future of academia, as future advancement holds possible new research horizons, educational improvement, and world problem-solving. With the rapid evolution of AI, its incorporation into academia and its abuses, biases, and risks need to be constantly reviewed

Gait Speed and Task-Specificity in Predicting Lower-Limb Kinematics: A Deep Learning Approach Using Inertial Sensors

ObjectiveTo develop a deep-learning framework to predict lower-limb joint kinematics from IMU data across multiple gait tasks (walking, jogging, and running) and evaluate the impact of dynamic time warping (DTW) on reducing prediction errors. Patients and MethodsData were collected from 18 participants fitted with IMUs and an optical motion capture (OMC) system between May 25, 2023, to May 30, 2023. A long-short-term memory (LSTM) autoencoder supervised regression model was developed. The model consisted of multiple LSTM and convolution layers. Acceleration and gyroscope data from the IMUs in three axes and their magnitude for the proximal and distal sensors of each joint (hip, knee, ankle) were inputs to the model. OMC kinematics were considered ground truth and used as an output to train the prediction model. ResultsThe deep-learning models achieved a root mean square error (RMSE) of less than 6° for hip, knee, and ankle joint sagittal plane angles, with the ankle showing the lowest error (5.1°). Task-specific models demonstrated enhanced performance during certain gait phases, such as knee flexion during running. The application of DTW significantly reduced RMSE across all tasks by at least 3-4°. External validation of independent data confirmed the model’s generalizability. ConclusionOur findings underscore the potential of IMU-based deep-learning models for joint kinematic predictions, offering a practical solution for remote and continuous biomechanical assessments in healthcare and sports science.

Toward a tipping point in federated learning in healthcare and life sciences

We discuss the real-world application of federated learning (FL) in the healthcare and life sciences industry, noting a tipping point in its adoption beyond academia. Sharing our experiences with multi-hospital and multi-pharma collaborations, we highlight the importance of involving key stakeholders to develop production-grade FL solutions that are fully compliant with stringent privacy and security standards.

Bridging The Gap: Promoting Faculty Diversity to Align With Student Demographics

In many kinesiology and health care science departments in the United States, there is a mismatch between the demographic composition of the student population and the faculty cohort. That is, although student populations are more diverse, the faculty cohort does not reflect this same diversity. The purpose of this paper is threefold: (a) Provide background information on the faculty–student mismatch, (b) discuss reactive strategies to increase diversity among a faculty cohort, and (c) discuss proactive strategies to increase diversity among a faculty cohort. Our approach is pragmatic and concise, which will give the reader various strategies they can incorporate to increase diversity in their faculty cohort.

Nutrient profile models for front-of-pack nutrition labelling: a systematic review

BackgroundFront-of-pack nutrition labelling (FOPNL) is a key policy to tackle diet-related non-communicable diseases. All types of FOPNL require an underlying nutrient profile model (NPM). Nutrient profiling is a scientific method for classifying foods according to their nutritional composition. This review aimed to identify all NPMs developed and/or used for FOPNL, to assist with the selection of appropriate NPMs to underpin nutrition policies, namely supporting the WHO Regional Office for Europe developing template NPMs for FOPNL. MethodsWe searched peer-reviewed databases (MEDLINE, CAB Abstracts, OvidSP, and Scopus) and grey literature (Overton and Google). Searches were limited to articles published in English, Spanish or Portuguese, and published between Jan 1, 2016, and May 4, 2023, building on a comparable review conducted by Labonté et al. in 2016. To be eligible for inclusion, NPMs developed for FOPNL had to allow for the classification or ranking of individual foods, be developed or endorsed by governmental or inter- governmental organisations and have a publicly available algorithm. FindingsFrom the 957 publications retrieved in the searches, 39 NPMs were included: 13 for warning labels, 12 for nutrient-specific systems (including ‘traffic-light’ labelling), 10 for health endorsements and four for graded summary indicators. Of these, 26 NPMs have been developed and four models updated since 2016. The WHO Region with highest number of models was the Americas (n=13, 33%), followed by the European Region (n=9, 23%) and the Western-Pacific Region (n=7, 18%). InterpretationThere has been a proliferation of new NPMs for FOPNL posing a potential challenge for policymakers in the selection of appropriate models for FOPNL policies. This systematic review facilitates the comparison of these models, demonstrating considerable heterogeneity in the NPMs underlying FOPNL, indicating there is little consensus in what constitutes the most appropriate model and reinforcing the need for more guidance and regional alignment. FundingMSB's DPhil is supported by the Nuffield Department of Population Health and St Cross College Joint Scholarship, as well as by the Saven European Scholarship. JAR is funded by the ESRC (SALIENT: Food System Trials for Healthier People and Planet project, Award ID/ref: ES/Y00311X/1). AK is funded by the Nuffield Department of Primary Care Health Sciences, University of Oxford, the Wellcome Trust (SHIFT (Sustainable Healthy Interventions for Food Transition, Award ID: 227132/Z/23/Z), and the NIHR PHR (COPPER: CO-designing for healthy People and Planet: food Economic policy Research. Award ID: NIHR133887). MJR is funded by the Nuffield Department of Population Health, University of Oxford.

How much digital public health is taught in German public health programs? A qualitative analysis

Abstract Background Digital public health (DiPH) professionals are crucial for a successful digital transformation in social and health care. However, the extent to which academic professionals are taught DiPH-related content in their public health studies in Germany remains unclear. Methods We used a systematic module handbook analysis to assess accredited full-time public health-oriented degree programs at German Universities for DiPH-related modules. Programs were identified through the Hochschulkompass platform and among the German Public Health Association member programs. We used MAXQDA for the content analysis of the included module handbooks. Results We identified 79 public health programs. Of these, 10 Bachelor’s and 6 Master’s offered at least one DiPH module, all being highly heterogeneous in their overall addressed public health subfields. Regarding DiPH, 6 programs lectured on the ethics of digitalizing health and data protection, 5 programs each offered modules on DiPH in health policy, on data science in healthcare and software used for eHealth, or on the digital determinants of health. 4 programs each included modules on digital health promotion and alternative evaluation methods. 3 programs each addressed digital science communication and health technology assessment. Finally, 2 programs had modules on digital epidemiology. We found differences between the common understanding of DiPH in academia and the content in the module handbooks. The content identified in the analysis focused mainly on technical areas. Social and health science content was only marginally present. Conclusions The diverse DiPH study programs allow academic public health specialists in Germany to develop specific profiles. There is a need for further development of modules with relevance to the respective degree program to achieve comprehensive competencies in DiPH. We encourage the uptake of our analysis to develop a core curriculum in DiPH among European public health programs. Key messages • Digitalization affects all areas of life, including healthcare systems and public health. Preparing the future workforce already during their training is crucial to enable them to lead the change. • German public health programs are not fit to prepare students for their professions. Developing DiPH curricula with pre-defined and updated competencies will strengthen programs in Germany and beyond.

What Are the Most Popular Articles in Urogynecology and Who Is Disseminating Them

Importance This research describes which articles published in Urogynecology are garnering the most attention online. Understanding which articles are having the largest impact in the online community has become increasingly important due to the exponential increase in the use of social media on the internet. Objective The Altmetric Attention Score (AAS) is a quantitative and qualitative measure of the articles’ online attention in social media and news outlets, blogs, and reference managers. The aim of this study was to provide an analysis of those accessing and sharing the 100 most popular articles published in Urogynecology. Study Design This was a retrospective descriptive analysis. Using Dimensions, a “linked research knowledge system,” data about each article’s demographics on Twitter and other media sources was extracted from each of the articles within Urogynecology with the highest AAS. No articles were excluded. The articles were categorized by topic and metrics of online sharing were compared among categories. Results Fifteen categories were created. Sexual health and education articles had the highest average Altmetric scores per article and reached the highest impressions per article and had the highest average follower count per Twitter user. On average, social justice in medicine had the highest number of tweets per article. Tweets were most often composed by members of the public (58%) compared with health care practitioners (14%), researchers (13%), and science communicators (12%). Conclusions Sexual health and education articles had the highest average AAS and impressions on Twitter. We observed a difference in which articles are being shared most among the general public and health care professionals. The general public comprised a majority of those sharing articles online regardless of category. Additionally, there may be a disparity in research, its funding, and online scientific communications within the field of urogynecology.

Exploring the Need for Medical Futures Studies: Insights From a Scoping Review of Health Care Foresight.

The historical development and contemporary instances of futures studies, an interdisciplinary field that focuses on exploring and formulating alternative futures, exemplify the increasing significance of using futures methods in shaping the health care domain. Despite the wide array of these methodologies, there have been limited endeavors to employ them within the medical community thus far. We undertook the first scoping review to date about the application of futures methodologies and published foresight projects in health care. Through the use of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) method, we identified 59 studies that were subsequently categorized into the following 5 distinct themes: national strategies (n=19), strategic health care foresight (n=15), health care policy and workforce dynamics (n=6), pandemic preparedness and response (n=7), and specialized medical domains (n=12). Our scoping review revealed that the application of futures methods and foresight has been successfully demonstrated in a wide range of fields, including national strategies, policy formulation, global threat preparedness, and technological advancements. The results of our review indicate that a total of 8 futures methods have already been used in medicine and health care, while there are more than 50 futures methods available. It may underscore the notion that the field is unexploited. Furthermore, the absence of structured methodologies and principles for employing foresight and futures techniques in the health care domain warrants the creation of medical futures studies as a separate scientific subfield within the broad domains of health care, medicine, and life sciences. This subfield would focus on the analysis of emerging technological trends, the evaluation of policy implications, and the proactive anticipation and mitigation of potential challenges. Futures studies can significantly enhance medical science by addressing a crucial deficiency in the promotion of democratic participation, facilitating interdisciplinary dialogue, and shaping alternative futures. To further contribute to the development of a new research community in medical futures studies, it is recommended to establish a specialized scientific journal. Additionally, appointing dedicated futurists in decision-making and national strategy, and incorporating futures methods into the medical curriculum could be beneficial.

A landmark federal interagency collaboration to promote data science in health care: Million Veteran Program-Computational Health Analytics for Medical Precision to Improve Outcomes Now.

In 2016, the Department of Veterans Affairs (VA) and the Department of Energy (DOE) established an Interagency Agreement (IAA), the Million Veteran Program-Computational Health Analytics for Medical Precision to Improve Outcomes Now (MVP-CHAMPION) research collaboration. Oversight fell under the VA Office of Research Development (VA ORD) and DOE headquarters. An Executive Committee and 2 senior scientific liaisons work with VA and DOE leadership to optimize efforts in the service of shared scientific goals. The program supported centralized data management and genomic analysis including creation of a scalable approach to cataloging phenotypes. Cross-cutting methods including natural language processing, image processing, and reusable code were developed. The 79.6 million dollar collaboration has supported centralized data management and genomic analysis including a scalable approach to cataloging phenotypes and launched over 10 collaborative scientific projects in health conditions highly prevalent in veterans. A ground-breaking analysis on the Summit and Andes supercomputers at the Oak Ridge National Laboratory (ORNL) of the genetic underpinnings of over 2000 health conditions across 44 million genetic variants which resulted in the identification of 38270 independent genetic variants associating with one or more health traits. Of these, over 2000 identified associations were unique to non-European ancestry. Cross-cutting methods have advanced state-of-the-art artificial intelligence (AI) including large language natural language processing and a system biology study focused on opioid addiction awarded the 2018 Gordon Bell Prize for outstanding achievement in high-performance computing. The collaboration has completed work in prostate cancer, suicide prevention, and cardiovascular disease, and cross-cutting data science. Predictive models developed in these projects are being tested for application in clinical management. Eight new projects were launched in 2023, taking advantage of the momentum generated by the previous collaboration. A major challenge has been limitations in the scope of appropriated funds at DOE which cannot currently be used for health research. Extensive multidisciplinary interactions take time to establish and are essential to continued progress. New funding models for maintaining high-performance computing infrastructure at the ORNL and for supporting continued collaboration by joint VA-DOE research teams are needed.

The Level of Perceived Stress and Affecting Factors due to Current Economic Crisis Among Undergraduates in Faculty of Health-Care Sciences, Eastern University Sri Lanka

Abstract In 2021, the Sri Lankan government officially declared the worst economic crisis in the country. The ongoing economic crisis in Sri Lanka has been affecting the whole sector of the country. The undergraduate students who stayed in hostels had to suffer a lot due to restrictions of family income. The parents face difficulties in affording all expenses required by their children as university students. As a result, students had to cut down their daily expenditures. Due to this crisis, the students had to be affected by various levels of stress leading to disruptions in both physical and mental health. It also caused poor academic performance. Some students had to quit their studies. Stress is an emotional feeling affecting all ages and it appears at any time of the life cycle. The purpose of this study was to identify the level of perceived stress and affecting factors due to the current economic crisis among undergraduates in the Faculty of Health-Care Sciences (FHCS), Eastern University Sri Lanka (EUSL). A cross-sectional descriptive study was conducted using a self-administered online questionnaire to gather information and a complete enumeration was done. The Perceived Stress Scale (PSS) instrument was used to assess the severity of the undergraduate perceived level of stress-related current economic crisis. Demographic variables and affecting factors due to the current economic crisis were considered. The overall mean stress score in the study population was 22.91(SD=5.386). The majority of undergraduates reported moderate stress 70.8% (N=240). A multiple linear regression analysis was applied, Pearson correlation was used, and all necessary tests were performed. There was a statistically significant, positive correlation between the level of perceived stress and their family income per month (p=0.000). The contributing factors correlated with perceived stress were unable to enjoy meeting people, unable to frequently visit home, unable to take meals from outside and instead of cooking, trying to save extra expenditure money, unable to frequent shopping for dresses, cosmetics, jewelry. The level of perceived stress reported by the majority of the students was moderate. Mainly their family income per month contributed to stress among them. Policymakers and the university administration have to consider more about the stress levels of the students and plan suitable programs like scholarships to manage stress.

Advancing health equity and the role of digital health technologies: a scoping review protocol

IntroductionHealthcare systems around the world exhibit inherent systemic inequities that disproportionately impact marginalised populations. Digital health technologies (DHTs) hold promising potential to address these inequities and to play a pivotal...

Prospective healthcare students' perspectives and attitudes on pharmacy as a chosen career path

BackgroundWith the national increase in the number of colleges and schools of pharmacy as well as the decreased pharmacy school applicant pool in recent years, pharmacy school enrollment challenges are at the forefront of issues facing pharmacy programs today. Factors that can influence a candidate's likelihood to pursue pharmacy school are important to evaluate. Recent studies assessing factors that motivate potential pre-health candidates to pursue pharmacy school or other healthcare careers are limited. ObjectiveTo describe prospective candidates' perspectives and attitudes toward pharmacy as a career pathway and assess factors that motivate or deter them from pursuing pharmacy as a career and from considering a specific pharmacy school. MethodThe study was cross-sectional and used an online data collection form distributed via the Qualtrics platform from October 4, 2022 through October 12, 2022 using the social media platform Reddit. Reddit has hundreds of subcommunities known as subreddits, that allow for exchange of ideas and discussion regarding various topics. This social media platform is commonly used by pre-health students to discuss career options. The survey consisted of 28 items and two domains, demographics and prospective healthcare students' understanding of responsibilities of pharmacists and their overall perspective on pharmacy as a profession. The survey was targeted toward anyone with an intention of pursuing a health science degree or career. ResultFour hundred participants completed the survey. Participants were mainly Caucasian, male, and with a mean age of 25 years. This study assessed prospective candidates' perspectives and attitudes toward pharmacy as a career pathway, appealing and unappealing characteristics about pursuing a career in the field of pharmacy, and factors that motivate or deter candidates from pursuing pharmacy. While 68 % of the participants had heard that career choices are vast and vary in the field of pharmacy, most still had concerns about the pharmacy field being heavily saturated and lack of job opportunities after graduation. Almost 60 % of responders gained information about pharmacy programs through social media platforms. The North American Pharmacist Licensure Examination pass rate, postgraduate residencies/fellowships, program duration and program reputation were among the top factors in choosing a pharmacy program. ConclusionMany survey participants had heard that there are a variety of job opportunities in the field of pharmacy, but the majority had heard that the pharmacy field is heavily saturated and that there are lack of opportunities after graduation. Most responders gained information through social media platforms. For prospective pharmacy school candidates, NAPLEX pass rate, number of graduates matched with PGY1 residencies and fellowships, and duration and reputation of the program seems to be among the most important factors in choosing a pharmacy program. Factors that prospective candidates consider when selecting a pharmacy program and the means they use to research about programs can be important considerations for pharmacy programs recruitment. Awareness of the preferences and baseline knowledge of candidates about the field of pharmacy can aid in developing targeted recruitment strategies and informing decision-making in pharmacy programs and recruitment efforts.

Institutional Culture of Belonging and Attrition Risk Among Women Health Care Professionals.

Objective: Attrition of women health care professionals is high, threatening patient care and advances in health care sciences. Women health care professionals have often reported experiencing challenges in the workplace that lower their sense of belonging and may precipitate their attrition. The current study sought to identify dimensions of workplace belonging in women health care professionals and to determine the relative strength of association of these belonging dimensions with intent to leave (ITL) their institution. Methods: Attendees of a continuing education course on women's leadership skills in health care were surveyed about their ITL and workplace belonging experiences. Dimensions of workplace belonging were identified by factor analysis. The strength of association between ITL and each workplace belonging dimension, as well as their relative strengths of association, were assessed in ordinal regression analyses. Results: Women comprised 99% of survey participants. Three dimensions of workplace belonging were identified: "institutional culture," "interactions with supervisor," and "interpersonal relationships." More frequent experiences of support in any of the three belonging dimensions associated strongly with lower ITL. When all three belonging dimensions were considered simultaneously, ITL remained strongly related with experiences of a supportive "institutional culture" (odds ratio 0.41, p < 0.0001), while it became much less strongly related with supportive experiences in the other two dimensions. Conclusions: These findings suggest a dominant role of institutional culture in attrition risk in women health care professionals. Interventions that foster an institutional culture of diversity, opportunities for career advancement, and inclusivity might be effective in improving retention of women health care professionals.