Exploring Work Engagement and Its Associated Factors among Supervising Pharmacists in Japan

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Given the growing shortage of healthcare and welfare professionals in Japan, enhancing work engagement among pharmacists is critical to improve productivity and prevent turnover. Addressing these issues is particularly important for pharmacists providing local healthcare services. Supervising pharmacists were exclusively targeted due to their pivotal role as gatekeepers between organizational leadership and frontline staff, as well as the potential for a crossover effect, where their engagement influences that of their subordinates Methods A cross-sectional survey was conducted among supervising pharmacists from major insurance pharmacy companies between August 2023 and September 2024. Participants completed a web-based questionnaire assessing demographic data, occupational stress (The Brief Job Stress Questionnaire), and work engagement (The Utrecht Work Engagement Scale; UWES-17). The association between work engagement and the potential associated factors were evaluated using bivariate and multivariate logistic regression analysis. Results Data from 973 participants (response rate: 88.9%) were analyzed. The median UWES-17 score was 2.82 (mean ± standard deviation: 2.80 ± 0.98). Among the three dimensions of work engagement, "dedication" scored the highest. Significant predictors of higher UWES-17 scores included perceived “meaningfulness of work,” “job control,” “suitable jobs,” “age group (≥ 50 years),” “coworker support,” “poor physical environment stress,” and “quantitative job overload.” Conclusions This study suggests that the distinct roles and workplace environments of supervising pharmacists shape their work engagement. Balancing job resources and demands is therefore critical for sustaining engagement and, by extension, for maintaining workforce stability and service quality in community pharmacies. Targeted interventions that may strengthen self-awareness, peer collaboration, and career development within structured practice communities could potentially reinforce these gains. Trail registration: Not applicable. Work engagement Supervising pharmacists Occupational stress JD-R model Career education UWES-17 Background In recent years, "work engagement" has attracted industry attention because of its association with worker motivation and productivity. Work engagement is no longer just an industry concern; the 2023 G7 Kurashiki Labour and Employment Ministers’ Meeting elevated it to a policy priority by listing “Enhancing work engagement and promoting decent work” among its three main agenda items and highlighting the need to upgrade care‑related jobs. ( 1 ). This positions high engagement in people‑intensive health sectors—pharmacy practice included—as a key lever for service quality and productivity. These developments suggest that policy discussions are paying growing attention to the potential value of promoting work engagement among health professionals-pharmacists included. Work engagement is defined as a positive and fulfilling work-related state of mind characterized by vigor (high levels of energy and perseverance when faced with difficulties), dedication (experiencing a strong sense of fulfillment, inspiration, pride, and challenge), and absorption (being completely focused on and immersed in one’s work) ( 2 ) ( 3 ). This is not a temporary state directed at a specific object, event, individual, or action but a sustained and generalized emotion and cognition directed at work ( 2 , 4 – 6 ) and is considered the conceptual opposite of burnout ( 2 , 4 , 7 ). The positive outcomes of enhancing work engagement include reduced turnover rates; improved health; increased job performance; stronger organizational commitment; and enhanced proactivity, innovation, and creativity ( 5 , 7 ). The Job Demands–Resources (JD-R) model identifies “job demands,” “job resources,” and “personal resources” as key factors influencing work engagement ( 5 , 8 , 9 ). “Job demands” include job pressure, emotional demands in interpersonal interactions, and mental and physical strain and require sustained effort. They are associated with psychological costs, which, if not adequately managed, can diminish work engagement ( 5 , 8 – 10 ). “Job resources,” such as autonomy, performance feedback, support from supervisors and coworkers, and career development opportunities, interact with “personal resources”, such as self-efficacy, optimism, resilience, and hope, to enhance work engagement ( 5 , 8 – 10 ). The Ministry of Health, Labour and Welfare positions work engagement as a crucial concept for simultaneously promoting workers' health and improving job performance ( 11 ). Furthermore, with the progression of aging in Japan, a significant shortage of professionals and service workers in the medical and welfare sectors in local communities has become a pressing issue identified as a major challenge leading to reduced labor productivity and a decline in workers' job satisfaction and motivation. Efforts to maintain and improve work engagement are recommended as to address this issue. ( 11 ) The pharmacy industry is at a critical turning point for improving the quality of local healthcare services. The Ministry of Health, Labour and Welfare's action plan for pharmacists' activities in the community includes enhancing interpersonal services, streamlining material services, promoting pharmacists' digital transformation, and expanding pharmacists' roles in the community, particularly targeting the pharmacy industry ( 12 ). In addition, according to the pharmacist supply–demand projections (draft), the number of prescriptions is expected to peak in 2035, leading to an eventual surplus of pharmacists ( 13 ). However, there is currently a chronic shortage of personnel in the industry, and the demand for pharmacists is expected to increase with the expansion of home-based services and health-support functions in pharmacy ( 13 ). In this context, supervising pharmacists serve as gatekeepers connecting organizations and the field, supporting the work engagement of store staff. Work engagement has been reported to exhibit a crossover phenomenon, where it spreads between individuals in the same environment, such as supervisors and subordinates, such that one person's emotions and attitudes can "transfer" to another person in the same environment ( 4 , 6 , 14 ). Employees construct the meaning of their work by referencing social signals from others in the workplace ( 17 ), suggesting that managers with high engagement can shape the engagement of their subordinates through daily interactions. In other words, improving the work engagement of managing pharmacists will help prevent pharmacist turnover and improve labor productivity. This is an important and timely issue for the pharmacy industry. Extensive scholarship has examined work engagement within medical settings—particularly among nurses ( 15 , 16 ) ,yet no multicompany investigation has profiled the engagement of supervising pharmacists working in community pharmacies.Building on this insight, clarifying supervising pharmacists’ work engagement, identifying its associated factors, and devising organisationwide measures to foster it constitute pressing priorities for the profession. Therefore, the purpose of this study was to evaluate the work engagement of supervising pharmacists working at insurance pharmacies and to explore the factors associated with it. Methods This study was conducted as a cross-sectional survey of supervising pharmacists—many of whom concurrently serve as pharmacy managers — at major insurance pharmacy companies between August 2023 and September 2024. These large insurancepharmacy chains were chosen because they employ substantial pharmacist workforces, proactively align with national policy, and thus provide a robust sample for capturing sectorwide trends within a defined timeframe. Their organisational scale and operational infrastructure also mean they are likely to shape future communitypharmacy practice, making them a pertinent focus for this study. Specific companies were chosen based on a comprehensive consideration of factors, including the number of pharmacists and the number of stores. Supervising pharmacists working in stores more with at least two staff members were included. Specific details regarding the number of pharmacies surveyed, and the exact number of pharmacists and other employees per establishment, cannot be disclosed due to the protection of participant privacy and compliance with ethical guidelines. This represents a limitation regarding data availability. The survey was conducted using a web-based questionnaire collected anonymously with unique research IDs assigned without correspondence tables. Regarding informed consent, an explanation was provided on the questionnaire form, and the participants were deemed to have consented by responding to the questions. The system was designed not to proceed if consent was not obtained. Exclusion criteria included withdrawal requests from participants, unidentified gender, and mismatched IDs between questionnaires. The survey items has included basic attributes of participants, including gender; years of employment; years of professional experience since obtaining a pharmacist’s license; duration in the current managerial position; allocation of work hours to dispensing, interpersonal, and managerial work; marital status; presence of children; job title; perceived workload during normal and busy periods; and occupational stress. Allocation of work hours to dispensing, interpersonal, and managerial work was evaluated using a 10-point scale, where participants assigned points to each task, totaling 10 points. Perceived workload during normal and busy periods was assessed using a 5-point scale, ranging from 1 ('not burdensome at all') to 5 ('extremely burdensome'). Occupational stress was measured using the Brief Job Stress Questionnaire provided by the Ministry of Health, Labour, and Welfare ( 18 ). This questionnaire consists of 19 scales (57 items) categorized into three factors: nine scales related to stress sources, six concerning physical and mental responses to stress, and four reflecting other factors influencing stress responses. Responses to each item were converted into scores on a five-point scale according to a raw score conversion table with higher stress levels corresponding to lower scores (1 point at the lowest) and lower stress levels to higher scores (5 points at the highest). Work engagement was assessed using the original Utrecht Work Engagement Scale (UWES-17) developed by Schaufeli et al., which has been validated for reliability and validity in Japan in the form of the UWES-J ( 2 ) ( 19 ). According to the UWES Manual, the sum of scores for all items divided by the number of items ( 17 ) was used to present scores for the subscales of vigor, dedication, and absorption. Descriptive statistics were used to determine the proportions of basic attributes, including gender and age. The fundamental trends of the three UWES-17 subscales (vigor, dedication, and absorption) were examined by calculating medians, means, and standard deviations and comparing UWES-17 scores by attributes. In Japan, a simplified version (UWES-9) is widely used because of its simplicity and practical applicability ( 19 ). However, this study adopted the original version, the UWES-17, since the aim was to grasp and analyze the current state of work engagement among supervising pharmacists in depth and to explore the associated factors work engagement using statistical methods in a comprehensive manner. Relationships between the UWES-17 and other factors were examined using bivariate and multivariate analyses in JMP® 18.0.1. For bivariate analysis, the UWES-17 scores and basic attributes were set as the dependent and explanatory variables, respectively. For occupational stress analysis, five-point scale scores for the three stress-related categories were aggregated and used as explanatory variables. Each of the 19 scales was scored on a five-point scale (1 = highest stress, 5 = lowest stress), using a MHLW’s score conversion table. For multivariate analysis, the responses to each scale were treated as ordinal variables ranging from level 1 to level 5. Pairwise comparisons were conducted between adjacent score levels (e.g., level 3 vs 2, level 5 vs 3) to examine the relative impact of incremental differences in perceived stress or related conditions. In this context, higher levels indicate lower levels of perceived stress or more favorable psychosocial work conditions. These comparisons were designed to detect potential threshold effects within each scale. Spearman’s rank correlation coefficient and the Kruskal-Wallis test were used for continuous and nominal scales, respectively, among the dependent variables. Post-hoc pairwise comparisons following the Kruskal-Wallis test were conducted using Dunn’s test. For all statistical analyses, the significance level was set to 5%. The interpretation of correlation coefficients in this study followed psychological research conventions;absolute values of Spearman’s rank correlation coefficient were classified into "no correlation" (0), "weak correlation" (0.1–0.3), "moderate correlation" (0.4–0.6), "strong correlation" (0.7–0.9), and "perfect correlation" ( 1 ) ( 20 ). For multivariate analysis, binary logistic regression was conducted, and odds ratios were confirmed for significant factors. First, the quartile ranges of the total UWES-17 scores were calculated with the upper and lower 25% quartiles set as 1 and 0, respectively, as dependent variables. To determine the explanatory variables included in the logistic regression model, bivariate correlations were first examined among all survey variables. When strong correlations were identified, one variable from each highly correlated pair was retained to avoid multicollinearity. In addition, some items in the occupational stress measures were found to conceptually overlap with aspects of work engagement. Therefore, careful discussions were held among the research team to ensure that the selected variables appropriately reflected the objectives of the present study without redundancy. These procedures were directly reflected in the final set of variables included in the logistic regression model. Multicollinearity was considered in setting the explanatory variables for occupational stress, including quantitative and qualitative job overload, perceived physical demands, interpersonal conflict, poor physical environment stress, job control, skill utilization, suitable jobs, meaningfulness of work, supervisor support, coworker support, and support from family and friends. Gender and age, which are found to be related to work engagement in several studies, were added and forcibly entered into the model as control variables. The overall model was tested using the likelihood ratio test at a 5% significance level. The model fit was evaluated comprehensively based on the local outlier factor, Nagelkerke R², Akaike information criterion (AIC), and Bayesian information criterion (BIC). AI-based tools, including ChatGPT (OpenAI), were employed to support the translation and proofreading of this manuscript and enhance its readability and clarity. These tools were used strictly as supplementary aids. The authors carefully reviewed, revised, and finalized the text to ensure accuracy and consistency. This study has been approved by the Ethics Review Committee of the Nippon Pharmaceutical University (Nippon-Rin 5–7) Results The survey received valid responses from 973 of the 1,095 targeted supervising pharmacists (response rate: 88.9%). Of these, 489 were women, and 484 were men. Table 1 shows the gender-specific age distribution; years of employment; years of professional experience since obtaining a pharmacist’s license; duration in the current managerial position; allocation of work hours to dispensing, interpersonal, and managerial work; marital status; presence of children; job titles; and perceived workload during both normal and busy periods. For age distribution, 49.4% of participants were in their 30s (the highest proportion) followed by 23.1% in their 40s, 12.4% in their 20s, 11.8% in their 50s, and 3.2% aged 60 and above. The gender distribution was nearly equal with 50.3% female and 49.7% male. For age groups according to gender, the highest proportion was those in their 30s for both genders (24.3% of women, 25.2% of men). The median length of continuous employment was 88.0 months (89.0 for women, 76.0 for men). The median length of professional experience after obtaining a pharmacist’s license was 136.5 months (164.5 for women, 130.0 for men). The median duration in the current managerial position was 36.5 months (33.0 for women, 47.0 for men). When evaluating work effort on a 10-point scale, both genders had a median score of 3.0 for allocation to dispensing work. The median score for allocation to interpersonal work was 4.0 points and was similar across all age groups and genders. The median scores for allocation to managerial work ranged from 2.0 to 3.0 points for both genders. The proportion of participants with spouses was 54.6% overall (47.4% of women, 61.9% of men). The proportion of participants with children was 39.1% (30.3% of women, 47.9% of men). Regarding positions, 68.9% of the participants held managerial roles equivalent to store managers or higher (67.7% of women, 70.0% of men). By age group, the proportion was highest among participants in their 40s (73.3%). The median perceived workload during normal periods was 3.0 on a five-point scale with no significant differences between genders or age groups. During busy periods, the median score was 4.0 except for among men in their 50s, who scored 3.0. Occupational stress analysis revealed that men reported high stress levels in “quantitative job overload” and “fatigue,” while women reported high stress levels in “quantitative job overload and qualitative job overload” with over 25% of respondents in these categories classified as having high stress (Table 2 ; Additional files1 ). Regarding workplace support, the proportion of high stress ratings was relatively low. The proportions of high stress related to support from supervisors were 4.1% for men and 1.2% for women. The proportions of support from colleagues were 7.0% for men and 1.8% for women. The proportions of support from family and friends were 7.9% for men and 3.3% for women. The results of the UWES-17 are presented in Table 3 . The median total score on the UWES-17 was 2.82 (mean ± SD: 2.80 ± 0.98). Men had a median score of 2.74 (mean ± standard deviation [SD]: 2.68 ± 1.00), and women had a median score of 2.94 (mean ± SD: 2.92 ± 0.93). Among the three factors (vigor, dedication, and absorption), “dedication” was highest, followed by “absorption” and “vigor.” Regarding dedication, the overall median was 3.00 (mean ± SD: 3.00 ± 1.14). For women, the median was 3.20 (mean ± SD: 3.16 ± 1.09), and for men, the median was 2.80 (mean ± SD: 2.84 ± 1.17). Regarding absorption, the overall median was 2.83 (mean ± SD: 2.78 ± 1.05). For women, the median was 2.83 (mean ± SD: 2.90 ± 1.01), and for men, the median was 2.67 (mean ± SD: 2.65 ± 1.09). Regarding vigor, the overall median was 2.67 (mean ± SD: 2.66 ± 1.03). For women, the median was 2.67 (mean ± SD: 2.74 ± 1.00), and for men, the median was 2.50 (mean ± SD: 2.58 ± 1.06). The relationships between the UWES-17 scores and the basic attributes are shown in Additional files 2–5 . Analysis of the UWES-17 scores and occupational stress revealed significant correlations across all items. Analysis by age group showed that participants in their 50s and those aged 60 and above had significantly higher work engagement than those in their 20s–40s. An analysis of perceived workload during normal and busy periods revealed significant differences in work engagement between groups reporting a “very high workload” [5] and other groups [1–3]. Participants with spouses showed significantly higher work engagement overall, and those with children exhibited significantly higher scores across all subscales of the UWES-17. The results of the binary logistic regression analysis are presented in Table 4 . For the logistic regression analysis, the quartile distribution of the total UWES-17 scores was calculated to define the binary outcome variable. The median score was 48.0, with the first quartile (Q1) at 37.0 and the third quartile (Q3) at 58.0, indicating an interquartile range of 21.0. Participants whose total scores were above the third quartile (Q3 > 58.0) were classified into the high engagement group (n = 236), while those with scores below the first quartile (Q1 < 37.0) were classified into the low engagement group (n = 258). These groups were assigned values of 1 and 0, respectively, and used as the dependent variable in the logistic regression model. “Meaningfulness of work,” “job control,” “suitable jobs,” and “age group (≥ 50 years)” were identified as significant factors that increased the likelihood of being in the upper quartile of UWES-17 scores. For “meaningfulness of work,” the odds were 15.4 times higher ( p < 0.0001) when the score increased from 2 to 3 and 15.6 times higher ( p < 0.0001) when it increased from 3 to 5. For “suitable jobs,” an increase from 2 to 3 raised the odds by 4.1 times ( p = 0.0003); for "job control," the same increase raised the odds by 3.5 times ( p = 0.0037). Participants aged 50 years and above had 3.7-times-higher odds ( p = 0.0031) compared with those under 50 years. Supplementary factors included “coworker support,” “poor physical environment stress,” and “quantitative job overload.” The model fit indicators were R² (0.509), AIC (444.0), and BIC (635.4). Discussion This study clarified the actual state of work engagement among supervising pharmacists in major insurance pharmacy companies and identified the associated factors. First, the work engagement of supervising pharmacists was examined based on previous studies conducted in other industries. The median UWES-17 score of supervising pharmacists was 2.82. According to Shimazu and other previous studies, the UWES-9 score for general Japanese workers is estimated to be approximately 2.8 to 2.9 ( 4 ) ( 16 ) ( 21 ). Comparative research across 16 countries, including Japan, found that Japanese workers scored significantly lower than workers from 15 other countries ( 21 ). In healthcare professions, general nurses have reported scores ranging from 2.2 to 2.7 ( 15 ) ( 22 ) ( 23 ) ( 24 ). A study across 16 facilities reported that general nurses had a median score of 2.4, while nurse managers had a median score of 3.0, suggesting that higher positions tended to have higher scores ( 24 ). Although direct comparisons were not possible, the work engagement of supervising pharmacists was similar to that of general Japanese workers and nurse managers. Among the three-factor structure of the UWES (vigor, dedication, and absorption), "dedication" was the highest, while "vigor" was the lowest. “Dedication” is characterized by a sense of significance, enthusiasm, inspiration, pride, and challenge ( 2 ). The following outlines the primary reasons for the highest level of “dedication”. Systematic data on the professional pride of supervising pharmacists in Japan are still lacking, nevertheless, Japanese pharmacists including supervising pharmacists are nationally licensed professionals, a status that confers social recognition of their role ( 25 ), and is considered to foster a sense of pride and meaning in their work. In a recent survey, “Pride in work” was identified as a quality indicator in a survey of community pharmacists in Japan ( 26 ).Supervising pharmacists engage in direct dialogue with patients through interpersonal work and follow-up during medication periods. Among other healthcare workers, a study of nurses found that recognizing patients’ expressions of gratitude enhances the meaningfulness of their work and, in turn, improves their innovative performance ( 27 ). Expressions of gratitude have been cited as a factor that can enhance work engagement ( 4 ). “Pride in work”, coupled with gratitude gained through direct patient interactions, may enhance “dedication” component of work engagement. “Vigor” is characterized by high levels of energy and mental resilience while working, a willingness to invest effort in one’s work, and persistence even in the face of difficulties ( 2 ). Previous studies have emphasized the importance of vigor as a motivational concept for enhancing work engagement. 5 In the current VUCA (Volatile, Uncertain, Complex, Ambiguous) era, the pharmacy industry also requires resilience to adapt flexibly to changes, making it especially important to enhance "vigor" as a component of work engagement. Next, based on the results and the JD-R model, the roles and work environments unique to supervising pharmacists were examined in terms of their impact on work engagement and potential countermeasures. The JD-R model elucidates the mechanisms underlying work engagement and identifies three pivotal factors that influence the development of work engagement: “job demands,” “job resources,” and “personal resources.” ( 5 ) ( 8 ) ( 9 ) “Job demands” such as job pressure, emotional demands in interpersonal interactions, and mental and physical strain require sustained effort and are associated with psychological costs that, if not adequately managed, can diminish work engagement ( 5 ) ( 8 ) ( 9 ) ( 10 ). “Job resources,” such as autonomy, performance feedback, support from supervisors and coworkers, and career development opportunities, along with “personal resources,” such as self-efficacy, optimism, resilience, and hope, interact to enhance work engagement ( 5 ) ( 8 ) ( 9 ) ( 10 ). The JD-R model highlights the importance of enhancing job resources as they contribute not only to improving work engagement but also to reducing stress reactions ( 4 ) ( 5 ) ( 9 ) ( 10 ). According to the JD-R model, high job demands, when combined with insufficient job resources such as lack of support, increase stress levels, which, in turn, diminish work engagement ( 8 ) ( 10 ). Supervising pharmacists supervise employees, manage pharmaceuticals, and provide information to ensure their proper use ( 28 ). Amid chronic staffing shortages caused by pharmacy expansion and regional disparities, supervising pharmacists must juggle players and managerial roles and handle a wide range of pharmacy operations, which cause high job demands. In this study, over 25% of the participants were identified as experiencing high stress due to “quantitative job overload.” Strengthening systems that utilize job resources and enhance support for supervising pharmacists is essential to reduce stress reactions and improve work engagement (Table 2 ). The binary logistic regression analysis identified seven factors that significantly influenced work engagement: “meaningfulness of work,” “suitable jobs,” “age group,” “job control,” “coworker support,” “poor physical environment stress,” and “quantitative job overload” (Table 4 ). These factors highlight the challenges in the roles and work environments unique to supervising pharmacists, as framed by the JD-R model. “Suitable jobs,” “job control,” “coworker support,” and “poor physical environment stress” fall under the job resources category of the JD-R model. Major insurance pharmacy companies, with their nationwide unified management policies, facilitate efficient operations and ensure the stability of “suitable jobs” and “job control.” In contrast, Kato et al. highlighted that management policies restricting the unique decision-making and coordination roles of supervising pharmacists in store operations result in a decline in the autonomy of pharmaceutical tasks and hinder the full utilization of individual pharmacists' abilities ( 29 ). These limitations raise challenges in areas such as “suitable jobs” and “job control.” Regarding “coworker support”, recent studies have underscored that leaders themselves need backing: managers’ work engagement and psychological wellbeing are strongly shaped by the support they receive from their own coworlers and supervisors ( 30 ). Consistently, a 16facility study of nurses and nurse managers found that staff who perceive strong coworker support report significantly higher engagement ( 24 ). Yet chronic staffing shortages in community pharmacies leave supervising pharmacists—who are expected to coordinate and support others—with few opportunities for allhands meetings or informal conversation, making it hard for them to obtain adequate coworker support. Consequently, organisationwide measures are required to ensure that supervising pharmacists receive the support they need. Many pharmacies lack well-equipped back-office spaces, forcing employees to work long hours in confined areas, potentially contributing to “poor physical environment stress.” “Quantitative job overload” is categorized as job demands in the JD-R model. Although addressing diverse tasks can be an opportunity for growth, this study suggests that a high workload contributes to stress. “Meaningfulness of work” was observed in supervising pharmacists belonging to the top group. When “meaningfulness of work” is regarded as meaningful work, it has been examined in relation to both job and personal resources ( 31 ) ( 32 ). Engaging in meaningful work is known to enhance personal resources in the JD-R model, such as “self-efficacy” and “optimism” ( 32 ), which are considered critical for improving work engagement. These findings suggest that the distinctive managerial roles of supervising pharmacists-alongside the overall pharmacy work environment shared by all staff- exert an important influence on their work engagement. Tailored measures such as support for self-awareness and addressing various challenges are necessary to enhance work engagement. Future human resource education must focus on developing “communities of practice” that not only excel in specialized skills but also facilitate effective teamwork. Foundational to this approach is self-and mutual understanding along with knowledge of organizational roles and cognitive diversity, which are essential for fostering organizational climates in which individuals and teams can thrive and find purpose in their work. This study provides significant insights by presenting reliable foundational data through a largescale cross-sectional survey in a field with limited evidence on pharmacists' work engagement. This study also provides concrete proposals regarding the direction of human resources and career training during this transitional period. These findings contribute to the sustainable growth of the pharmacy industry and to efforts to enhance work engagement, including supervising pharmacists Our sample was drawn from four large insurance‑pharmacy chains, excluding the small‑ and medium‑sized pharmacies that account for most outlets nationwide; the findings should therefore be extrapolated only with caution. Because organisational programmes designed to foster work engagement were not assessed, their potential influence could not be modelled, and future studies should measure and adjust for these initiatives. Moreover, individual attributes that may shape engagement—such as income level and specialized credentials—were not captured and merit examination in subsequent research. A plausible explanation is that older pharmacists tend to possess richer job resources-greater autonomy, skill utilisation and person-job fit-than their younger colleagues. Empirical studies show that these resources increase with age and, in turn, predict higher levels of work engagement among employees. Conclusions This crosssectional survey of 973 supervising pharmacists in four large insurancepharmacy chains recorded a median UWES-17 score of 2.82, with dedication the strongest dimension. Major pharmacy chains address chronic staffing shortages by delegating dispensing tasks to clerical staff and dietitians and by reducing the burden of material tasks through the adoption of dispensing equipment and information technology tools. In recent years, they have also actively worked on improving workplace factors such as enhancing labor productivity through the introduction of AI. However, despite having various support systems in place, efforts to alleviate the mental burden of supervising pharmacists, establish support structures that enable individuals to experience personal growth and meaningfulness of work, promote self-awareness and mutual understanding to leverage individuality and diversity in human resource development, and develop career-education programs remain at a nascent stage. The Ministry of Health, Labour and Welfare also suggests a positive correlation between higher implementation rates of human resource development and work engagement ( 11 ). Accordingly, organisational humanresource strategies should deliberately incorporate measures that preserve and strengthen the work engagement of supervising pharmacists. In addition to these empirical findings, this study contributes by providing a reliable data baseline in a field with limited prior evidence and by proposing directions for human resource and career development during this transitional phase in the pharmacy sector. Abbreviations BJSQ Brief Job Stress Questionnaire JD-R Job Demands–Resources UWES-17 Utrecht Work Engagement Scale 17-item version Declarations Authors' information Authors and Affiliations Ethics approval and consent to participate This study was conducted in accordance with Ethical Guidelines for Medical and Health Research Involving Human Subjects in Japan. This study was approved by the Research Ethics Committee for Human Subjects at Nippon Pharmaceutical University (Approval No: Nippon-Rin 5–7; Date of approval: August 22, 2023). Participation in the survey was entirely voluntary, and informed consent was implied by completing and submitting the questionnaire. Respondents were explicitly informed that collected data would be anonymized to protect their privacy and would not be used for any purposes other than statistical analysis. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding Not applicable. Author Contribution All authors participated in meetings related to the study (e.g., study design and manuscript review). YI conceived the study and drafted the manuscript. HS contributed significantly to manuscript preparation by frequently reviewing and suggesting revisions. TY contributed to the preparation of the research plan and advised on manuscript preparation. SO contributed to the survey and statistical analyses and provided advice on manuscript preparation. TH supervised study implementation, reviewed the manuscript, and provided guidance on its interpretation. Acknowledgement We express our deepest gratitude to Qol Co., Ltd.; AIN HOLDINGS, INC.; I&H Co., Ltd.; and Sugi Pharmacy Co., Ltd., for their invaluable support. Data availability Research data will not be made publicly available to protect the participants’ privacy and to comply with ethical guidelines. Moreover, informed consent obtained from the participants did not include permission for data sharing. References Ministry of Health LaW, Overview. G7 Kurashiki Labour and Employment Ministers' Meeting in Okayama Tokyo: Ministry of Health, Labour and Welfare; 2023 [Available from: https://www.mhlw.go.jp/seisakunitsuite/bunya/hokabunya/kokusai/g8/g7labour2023_en/overview.html#agenda Schaufeli WB, Salanova M, González-romá V, Bakker AB. The Measurement of Engagement and Burnout: A Two Sample Confirmatory Factor Analytic Approach. J Happiness Stud. 2002;3(1):71–92. 10.1023/A:1015630930326 . Bakker AB, Schaufeli WB, Leiter MP, Taris TW. Work engagement: An emerging concept in occupational health psychology. Work Stress. 2008;22(3):187–200. 10.1080/02678370802393649 . Shimazu A. Revised Work Engagement: Achieving a Vibrant Life with Positive Mental Health. Tokyo:Labour Research Council; 2014. Schaufeli WB, Bakker AB. Job demands, job resources, and their relationship with burnout and engagement: a multi-sample study. J Organizational Behav. 2004;25(3):293–315. 10.1002/job.248 . Bakker AB, Leiter MP. Work Engagement: A Handbook of Essential Theory and Research.Tokyo. Tokyo: Seiwa Shoten; 2014. Shimazu A. Shokugyōsei sutoresu to wāku engeijimento. Sutoresu kagaku kenkyū. (in Japanese). 2010;25:1–6. 10.5058/stresskagakukenkyu.25.1 . Bakker AB, Demerouti E. The Job Demands-Resources model: state of the art. J Managerial Psychol. 2007;22(3):309–28. 10.1108/02683940710733115 . Galanakis MD, Tsitouri E. Positive psychology in the working environment. Job demands-resources theory, work engagement and burnout: A systematic literature review. Front Psychol. 2022;13. 10.3389/fpsyg.2022.1022102 . Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB. The job demands-resources model of burnout. J Appl Psychol. 2001;86(3):499–512. Ministry of Health Labour and Welfare. Reiwa Gannenban Rōdō Keizai no Bunseki - Hito Te Busoku no Moto de no. Hatarakikata o Meguru Kadai ni Tsuite (in Japanese). Published 2019. Accessed January 8, 2025. Available from: https://www.mhlw.go.jp/stf/wp/hakusyo/roudou/19/19-1.html Ministry of Health Labour and Welfare. Yakkyoku yakuzaishi no gyōmu oyobi yakkyoku no kinō ni kansuru wākingu gurūpu torimatome -Yakuzaishi ga chiiki de katsuyaku suru tame no akushon puran- (in Japanese). Published 2022. Accessed January 8. 2025. Available from: https://www.mhlw.go.jp/stf/newpage_26701.html Ministry of Health Labour and Welfare. Yakuzaishi no jukyū suikei (an) (in Japanese). Published 2021. Accessed January 8, 2025. Bakker AB, Demerouti E. The crossover of work engagement between working couples. J Managerial Psychol. 2009;24(3):220–36. 10.1108/02683940910939313 . Ishitsuka M, Miki A. Byōin kangoshi ni okeru shigoto no shigen・kojin shigen to wāku engeijimento to no kanren (in Japanese). J Japan Acad Occup Health Nurs. 2016;3(1):1–7. 10.32271/jaohn.3.1_1 . Mukae R. A literature review for practical interventions to improve work engagement. Japanese Assoc Indust Org Psychol J. 2018;32(1):55–78. 10.32222/jaiop.32.1_55 . Wrzesniewski A, Dutton JE, Debebe G, INTERPERSONAL SENSEMAKING AND, THE MEANING OF WORK. Res Organizational Behav. 2003;25:93–135. Ministry of Health LaW. Manual for understanding current stress status using the Brief Job Stress Questionnaire (BJSQ) [in Japanese] Tokyo: Ministry of Health, Labour and Welfare. 2005. Available from: https://www.mhlw.go.jp/file/05-Shingikai-11201000-Roudoukijunkyoku-Soumuka/0000050920.pdf Shimazu A, Schaufeli WB, Kosugi S, Suzuki A, Nashiwa H, Kato A, et al. Work Engagement in Japan: Validation of the Japanese Version of the Utrecht Work Engagement Scale. Appl Psychol. 2008;57(3):510–23. 10.1111/j.1464-0597.2008.00333.x . Akoglu H. User's guide to correlation coefficients. Turk J Emerg Med. 2018;18(3):91–3. 10.1016/j.tjem.2018.08.001 . Shimazu A, Schaufeli W, Miyanaka D, Iwata N. Why Japanese workers show low work engagement: An Item Response Theory analysis of the Utrecht Work Engagement Scale. Biopsychosoc Med. 2010;4:17. 10.1186/1751-0759-4-17 . Kagata S, Inoue A, Kubota K, Shimazu A. Byōtō kangoshi ni okeru kanjō rōdō to wāku engeijimento oyobi sutoresu hannō to no kanren (in Japanese). Japan J Behav Med. 2015;21(2):83–90. 10.11331/jjbm.21.83 . Matsuzaki S, Iwanaga E, Somakawa M, et al. An examination of factors affecting the work engagement among nurses. Health Sci Res. 2023;36:1–8. Takaya S, Ambo H. Relationship between work engagement of hospital nursing staff and social support from head nurses and colleagues. J Japan Acad Nurs Sci. 2022;42:168–75. 10.5630/jans.42.168 . Arakawa N. The future of pharmacists in Japan: considerations based on international survey activities. Yakugaku. 2015;75(3):137–9. 10.14843/jpstj.75.137 . Japanese.doi:. Kato Y, Sekiya T, Ishii R, Hirako Y, Satoh H, Kimura H. Quality of work life (QWL) of community pharmacists and its association with subjective evaluations of pharmaceutical services. Exploratory Res Clin Social Pharm. 2024;14:100458. https://doi.org/10.1016/j.rcsop.2024.100458 . Liu B, Liu M, Wang H, Yang Y, Ma Y, Wei X. Can patient gratitude expression boost innovative performance? The role of work meaningfulness and supervisory support. Front Psychol. 2022;13–2022. 10.3389/fpsyg.2022.1024211 . Ministry of Health. Labour and Welfare. Kanri yakuzaishi-tō no sekimu no naiyō ni tsuite: Dai 4-kai Kōsei Kagaku Shingikai Iyakuin Hanbai Seido Kaisei Kentō Bukai, Shiryō 2–3; Heisei 16-nen 7-gatsu 21-nichi (in Japanese). Published 2004. Accessed January 8. 2025. Available from: https://www.mhlw.go.jp/shingi/2004/07/s0721-6d.html Kato Y, Kirino Y, Kimra H. Iyakubungyō ni okeru yakkyoku・yakuzaishi no shakaiteki igi to shokuiki kakudai no kanōsei (in Japanese). Institute for Future Initiatives The University of Tokyo. Published; 2023. Report No.: No.27. Available from: https://ifi.u-tokyo.ac.jp/wp/wp-content/uploads/2023/09/WP027.pdf Wittmers A, Maier GW. Leaders’ mental health in times of crisis: work intensification, emotional demands and the moderating role of organizational support and self-efficacy. Front Psychol. 2023;14. 10.3389/fpsyg.2023.1122881 . Steger MF, Dik BJ, Duffy RD. Measuring meaningful work: The Work and Meaning Inventory (WAMI). J Career Assess. 2012;20(3):322–37. 10.1177/1069072711436160 . Allan BA, Batz-Barbarich C, Sterling HM, Tay L. Outcomes of meaningful work: A meta-analysis. Journal of Management Studies. 2019;56(3):500 – 28.dol: 10.1111/joms.12406 Tables Table 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table14JPHCSRE.docx Table 1 Basic Data by Gender and Age Group This table presents baseline survey results, including years of employment, managerial positions, and perceived workload, categorized by gender and age group. No notable differences were observed in the overall male-to-female ratio. Table 2 Gender-Specific Results of the Brief Job Stress Questionnaire (BJSQ) This table presents the gender-specific results of the Brief Job Stress Questionnaire, focusing on job demands, psychological stress reactions, and workgroup-level job resources. Data are categorized into five levels (1–5) with proportions of high-stress levels (%) reported for each category. Among men, more than 25% were classified as experiencing high stress related to Quantitative Job Overload and Fatigue. Among women, over 25% experienced high stress in both Quantitative and Qualitative Job Overload with nearly half classified as experiencing high stress in Qualitative Job Overload. Additionally, lower levels of supervisor and coworker support were associated with higher stress levels, particularly in men (4.1% and 7.0%, respectively) compared to women (1.2% and 1.8%, respectively). Table 3 Distribution of UWES-17 Scores by Gender and Age Group This table presents the distribution of UWES-17 scores by gender and age group, focusing on work engagement scores per item and total scores. The data include median, mean, and standard deviation (SD) values for each category. The median total work engagement score was 2.82 (mean ± SD: 2.80 ± 0.98). For men, the median score was 2.74 (mean ± SD: 2.68 ± 1.00), while women showed a higher median score of 2.94 (mean ± SD: 2.92 ± 0.93). Among the three components of work engagement, dedication had the highest scores, followed by absorption and vigor. Table 4 Predictors Influencing High Work Engagement: A Logistic Regression Analysis This table presents the results of the binary logistic regression analysis, highlighting the statistically significant factors influencing high work engagement. The predictors, excluding the age group variable, were treated as ordinal variables with five levels. The overall model fit indices (pseudo R² = 0.509, AIC = 444, BIC = 635.4) and the model's global significance (p < 0.0001) indicate that the model adequately explains the dependent variable. The intercept (β = −37.35, p = 0.9876) and parameters excluded from the table were not statistically significant. The instability of the intercept does not affect the interpretation of the explanatory variables. While the predictors "Coworker Support," "Poor physical environment stress," and "Quantitative job overload" were not significant overall, specific pairwise comparisons within these variables demonstrated statistically significant effects on the outcome. p < .05 was considered statistically significant. In this table, 'Comparison (Level)' indicates the specific comparison between levels of each predictor variable used in the logistic regression analysis. For example, '3 vs 2' refers to level 3 being compared to level 2 as the reference category, and '5 vs 3' refers to level 5 being compared to level 3. AdditionalfilesJPHCS.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7276046","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496161851,"identity":"f6b6eed4-0f4e-415f-99f8-86a5c3f89006","order_by":0,"name":"Yukari Ito","email":"","orcid":"","institution":"Hoshi University","correspondingAuthor":false,"prefix":"","firstName":"Yukari","middleName":"","lastName":"Ito","suffix":""},{"id":496161852,"identity":"d556cb54-7437-4629-bd50-33709f446e7d","order_by":1,"name":"Hiroko Suzuki","email":"","orcid":"","institution":"Nihon Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Hiroko","middleName":"","lastName":"Suzuki","suffix":""},{"id":496161853,"identity":"89dec20a-3596-4fca-9891-152743333a85","order_by":2,"name":"Tetsuro Yumoto","email":"","orcid":"","institution":"Shonan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tetsuro","middleName":"","lastName":"Yumoto","suffix":""},{"id":496161854,"identity":"06bf59fc-8a46-4bfb-a9da-a7d71ef979fc","order_by":3,"name":"Sachiko Ohta","email":"","orcid":"","institution":"Nihon Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Sachiko","middleName":"","lastName":"Ohta","suffix":""},{"id":496161855,"identity":"6578c7d7-bba8-4f50-abd8-d870ab734c74","order_by":4,"name":"Tomoo Hosoe","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACAzBZcYCBQYKxAcRkJlLLGZK1MLaBtBDrMHP29ocPPs67Iyc/u7mB4UcNA7s5IS2WPWeMDWdue2ZscOdgA2PPMQZmywZCDruRwybNu+1w4gaJxAYG3gYGZoMDBLWkP5P+O+dw4vwZiQ2Mf4nTkmAmzdhwOLHhRmIDM3G2nAH6pefYYWMDoJbDMsckiPDLcWCI/ag5LCc/I/3hwzc1NskEQwwFAJ0kkWxAkhYQsCNdyygYBaNgFAx3AAAO40P5R4OJlwAAAABJRU5ErkJggg==","orcid":"","institution":"Hoshi University","correspondingAuthor":true,"prefix":"","firstName":"Tomoo","middleName":"","lastName":"Hosoe","suffix":""}],"badges":[],"createdAt":"2025-08-02 06:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7276046/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7276046/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90540364,"identity":"29cced96-78e9-4980-b4d1-5e8a08fcb3ef","added_by":"auto","created_at":"2025-09-03 23:38:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":491299,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7276046/v1/a3c2b628-721c-4de3-82d5-bdf41f98d997.pdf"},{"id":88608501,"identity":"384affae-8832-4d85-8a8b-27633ec0699c","added_by":"auto","created_at":"2025-08-08 09:14:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":310936,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1 \u003c/strong\u003eBasic Data by Gender and Age Group\u003c/p\u003e\n\u003cp\u003eThis table presents baseline survey results, including years of employment, managerial positions, and perceived workload, categorized by gender and age group. No notable differences were observed in the overall male-to-female ratio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Gender-Specific Results of the Brief Job Stress Questionnaire (BJSQ)\u003c/p\u003e\n\u003cp\u003eThis table presents the gender-specific results of the Brief Job Stress Questionnaire, focusing on job demands, psychological stress reactions, and workgroup-level job resources. Data are categorized into five levels (1–5) with proportions of high-stress levels (%) reported for each category. Among men, more than 25% were classified as experiencing high stress related to Quantitative Job Overload and Fatigue. Among women, over 25% experienced high stress in both Quantitative and Qualitative Job Overload with nearly half classified as experiencing high stress in Qualitative Job Overload. Additionally, lower levels of supervisor and coworker support were associated with higher stress levels, particularly in men (4.1% and 7.0%, respectively) compared to women (1.2% and 1.8%, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Distribution of UWES-17 Scores by Gender and Age Group\u003c/p\u003e\n\u003cp\u003eThis table presents the distribution of UWES-17 scores by gender and age group, focusing on work engagement scores per item and total scores. The data include median, mean, and standard deviation (SD) values for each category. The median total work engagement score was 2.82 (mean ± SD: 2.80 ± 0.98). For men, the median score was 2.74 (mean ± SD: 2.68 ± 1.00), while women showed a higher median score of 2.94 (mean ± SD: 2.92 ± 0.93). Among the three components of work engagement, dedication had the highest scores, followed by absorption and vigor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 \u003c/strong\u003ePredictors Influencing High Work Engagement: A Logistic Regression Analysis\u003c/p\u003e\n\u003cp\u003eThis table presents the results of the binary logistic regression analysis, highlighting the statistically significant factors influencing high work engagement. The predictors, excluding the age group variable, were treated as ordinal variables with five levels. The overall model fit indices (pseudo R² = 0.509, AIC = 444, BIC = 635.4) and the model's global significance (p \u0026lt; 0.0001) indicate that the model adequately explains the dependent variable. The intercept (β = −37.35, p = 0.9876) and parameters excluded from the table were not statistically significant. The instability of the intercept does not affect the interpretation of the explanatory variables. While the predictors \"Coworker Support,\" \"Poor physical environment stress,\" and \"Quantitative job overload\" were not significant overall, specific pairwise comparisons within these variables demonstrated statistically significant effects on the outcome. p \u0026lt; .05 was considered statistically significant. In this table, 'Comparison (Level)' indicates the specific comparison between levels of each predictor variable used in the logistic regression analysis. For example, '3 vs 2' refers to level 3 being compared to level 2 as the reference category, and '5 vs 3' refers to level 5 being compared to level 3.\u003c/p\u003e","description":"","filename":"Table14JPHCSRE.docx","url":"https://assets-eu.researchsquare.com/files/rs-7276046/v1/927ffcb18d9fe8ce1c7378ef.docx"},{"id":88607419,"identity":"059e1283-73eb-4443-80a0-1cc5e016b035","added_by":"auto","created_at":"2025-08-08 09:06:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":397873,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalfilesJPHCS.docx","url":"https://assets-eu.researchsquare.com/files/rs-7276046/v1/d39dd7b7bfbb6c3b691a470b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Work Engagement and Its Associated Factors among Supervising Pharmacists in Japan","fulltext":[{"header":"Background","content":"\u003cp\u003eIn recent years, \"work engagement\" has attracted industry attention because of its association with worker motivation and productivity. Work engagement is no longer just an industry concern; the 2023 G7 Kurashiki Labour and Employment Ministers’ Meeting elevated it to a policy priority by listing “Enhancing work engagement and promoting decent work” among its three main agenda items and highlighting the need to upgrade care‑related jobs. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This positions high engagement in people‑intensive health sectors—pharmacy practice included—as a key lever for service quality and productivity. These developments suggest that policy discussions are paying growing attention to the potential value of promoting work engagement among health professionals-pharmacists included.\u003c/p\u003e\u003cp\u003eWork engagement is defined as a positive and fulfilling work-related state of mind characterized by vigor (high levels of energy and perseverance when faced with difficulties), dedication (experiencing a strong sense of fulfillment, inspiration, pride, and challenge), and absorption (being completely focused on and immersed in one’s work) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). This is not a temporary state directed at a specific object, event, individual, or action but a sustained and generalized emotion and cognition directed at work (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and is considered the conceptual opposite of burnout (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003csup\u003e \u003c/sup\u003eThe positive outcomes of enhancing work engagement include reduced turnover rates; improved health; increased job performance; stronger organizational commitment; and enhanced proactivity, innovation, and creativity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Job Demands–Resources (JD-R) model identifies “job demands,” “job resources,” and “personal resources” as key factors influencing work engagement (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). “Job demands” include job pressure, emotional demands in interpersonal interactions, and mental and physical strain and require sustained effort. They are associated with psychological costs, which, if not adequately managed, can diminish work engagement (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). “Job resources,” such as autonomy, performance feedback, support from supervisors and coworkers, and career development opportunities, interact with “personal resources”, such as self-efficacy, optimism, resilience, and hope, to enhance work engagement (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Ministry of Health, Labour and Welfare positions work engagement as a crucial concept for simultaneously promoting workers' health and improving job performance (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Furthermore, with the progression of aging in Japan, a significant shortage of professionals and service workers in the medical and welfare sectors in local communities has become a pressing issue identified as a major challenge leading to reduced labor productivity and a decline in workers' job satisfaction and motivation. Efforts to maintain and improve work engagement are recommended as to address this issue. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe pharmacy industry is at a critical turning point for improving the quality of local healthcare services. The Ministry of Health, Labour and Welfare's action plan for pharmacists' activities in the community includes enhancing interpersonal services, streamlining material services, promoting pharmacists' digital transformation, and expanding pharmacists' roles in the community, particularly targeting the pharmacy industry (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In addition, according to the pharmacist supply–demand projections (draft), the number of prescriptions is expected to peak in 2035, leading to an eventual surplus of pharmacists (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, there is currently a chronic shortage of personnel in the industry, and the demand for pharmacists is expected to increase with the expansion of home-based services and health-support functions in pharmacy (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In this context, supervising pharmacists serve as gatekeepers connecting organizations and the field, supporting the work engagement of store staff. Work engagement has been reported to exhibit a crossover phenomenon, where it spreads between individuals in the same environment, such as supervisors and subordinates, such that one person's emotions and attitudes can \"transfer\" to another person in the same environment (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Employees construct the meaning of their work by referencing social signals from others in the workplace (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), suggesting that managers with high engagement can shape the engagement of their subordinates through daily interactions. In other words, improving the work engagement of managing pharmacists will help prevent pharmacist turnover and improve labor productivity. This is an important and timely issue for the pharmacy industry.\u003c/p\u003e\u003cp\u003eExtensive scholarship has examined work engagement within medical settings—particularly among nurses (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) ,yet no multicompany investigation has profiled the engagement of supervising pharmacists working in community pharmacies.Building on this insight, clarifying supervising pharmacists’ work engagement, identifying its associated factors, and devising organisationwide measures to foster it constitute pressing priorities for the profession. Therefore, the purpose of this study was to evaluate the work engagement of supervising pharmacists working at insurance pharmacies and to explore the factors associated with it.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study was conducted as a cross-sectional survey of supervising pharmacists—many of whom concurrently serve as pharmacy managers — at major insurance pharmacy companies between August 2023 and September 2024.\u003c/p\u003e\u003cp\u003eThese large insurancepharmacy chains were chosen because they employ substantial pharmacist workforces, proactively align with national policy, and thus provide a robust sample for capturing sectorwide trends within a defined timeframe. Their organisational scale and operational infrastructure also mean they are likely to shape future communitypharmacy practice, making them a pertinent focus for this study. Specific companies were chosen based on a comprehensive consideration of factors, including the number of pharmacists and the number of stores. Supervising pharmacists working in stores more with at least two staff members were included. Specific details regarding the number of pharmacies surveyed, and the exact number of pharmacists and other employees per establishment, cannot be disclosed due to the protection of participant privacy and compliance with ethical guidelines. This represents a limitation regarding data availability. The survey was conducted using a web-based questionnaire collected anonymously with unique research IDs assigned without correspondence tables. Regarding informed consent, an explanation was provided on the questionnaire form, and the participants were deemed to have consented by responding to the questions. The system was designed not to proceed if consent was not obtained. Exclusion criteria included withdrawal requests from participants, unidentified gender, and mismatched IDs between questionnaires.\u003c/p\u003e\u003cp\u003eThe survey items has included basic attributes of participants, including gender; years of employment; years of professional experience since obtaining a pharmacist’s license; duration in the current managerial position; allocation of work hours to dispensing, interpersonal, and managerial work; marital status; presence of children; job title; perceived workload during normal and busy periods; and occupational stress. Allocation of work hours to dispensing, interpersonal, and managerial work was evaluated using a 10-point scale, where participants assigned points to each task, totaling 10 points. Perceived workload during normal and busy periods was assessed using a 5-point scale, ranging from 1 ('not burdensome at all') to 5 ('extremely burdensome'). Occupational stress was measured using the Brief Job Stress Questionnaire provided by the Ministry of Health, Labour, and Welfare (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). This questionnaire consists of 19 scales (57 items) categorized into three factors: nine scales related to stress sources, six concerning physical and mental responses to stress, and four reflecting other factors influencing stress responses. Responses to each item were converted into scores on a five-point scale according to a raw score conversion table with higher stress levels corresponding to lower scores (1 point at the lowest) and lower stress levels to higher scores (5 points at the highest).\u003c/p\u003e\u003cp\u003eWork engagement was assessed using the original Utrecht Work Engagement Scale (UWES-17) developed by Schaufeli et al., which has been validated for reliability and validity in Japan in the form of the UWES-J (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). According to the UWES Manual, the sum of scores for all items divided by the number of items (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) was used to present scores for the subscales of vigor, dedication, and absorption. Descriptive statistics were used to determine the proportions of basic attributes, including gender and age. The fundamental trends of the three UWES-17 subscales (vigor, dedication, and absorption) were examined by calculating medians, means, and standard deviations and comparing UWES-17 scores by attributes. In Japan, a simplified version (UWES-9) is widely used because of its simplicity and practical applicability (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). However, this study adopted the original version, the UWES-17, since the aim was to grasp and analyze the current state of work engagement among supervising pharmacists in depth and to explore the associated factors work engagement using statistical methods in a comprehensive manner.\u003c/p\u003e\u003cp\u003eRelationships between the UWES-17 and other factors were examined using bivariate and multivariate analyses in JMP® 18.0.1. For bivariate analysis, the UWES-17 scores and basic attributes were set as the dependent and explanatory variables, respectively. For occupational stress analysis, five-point scale scores for the three stress-related categories were aggregated and used as explanatory variables. Each of the 19 scales was scored on a five-point scale (1 = highest stress, 5 = lowest stress), using a MHLW’s score conversion table. For multivariate analysis, the responses to each scale were treated as ordinal variables ranging from level 1 to level 5. Pairwise comparisons were conducted between adjacent score levels (e.g., level 3 vs 2, level 5 vs 3) to examine the relative impact of incremental differences in perceived stress or related conditions. In this context, higher levels indicate lower levels of perceived stress or more favorable psychosocial work conditions. These comparisons were designed to detect potential threshold effects within each scale. Spearman’s rank correlation coefficient and the Kruskal-Wallis test were used for continuous and nominal scales, respectively, among the dependent variables. Post-hoc pairwise comparisons following the Kruskal-Wallis test were conducted using Dunn’s test. For all statistical analyses, the significance level was set to 5%. The interpretation of correlation coefficients in this study followed psychological research conventions;absolute values of Spearman’s rank correlation coefficient were classified into \"no correlation\" (0), \"weak correlation\" (0.1–0.3), \"moderate correlation\" (0.4–0.6), \"strong correlation\" (0.7–0.9), and \"perfect correlation\" (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor multivariate analysis, binary logistic regression was conducted, and odds ratios were confirmed for significant factors. First, the quartile ranges of the total UWES-17 scores were calculated with the upper and lower 25% quartiles set as 1 and 0, respectively, as dependent variables. To determine the explanatory variables included in the logistic regression model, bivariate correlations were first examined among all survey variables. When strong correlations were identified, one variable from each highly correlated pair was retained to avoid multicollinearity. In addition, some items in the occupational stress measures were found to conceptually overlap with aspects of work engagement. Therefore, careful discussions were held among the research team to ensure that the selected variables appropriately reflected the objectives of the present study without redundancy. These procedures were directly reflected in the final set of variables included in the logistic regression model. Multicollinearity was considered in setting the explanatory variables for occupational stress, including quantitative and qualitative job overload, perceived physical demands, interpersonal conflict, poor physical environment stress, job control, skill utilization, suitable jobs, meaningfulness of work, supervisor support, coworker support, and support from family and friends. Gender and age, which are found to be related to work engagement in several studies, were added and forcibly entered into the model as control variables. The overall model was tested using the likelihood ratio test at a 5% significance level. The model fit was evaluated comprehensively based on the local outlier factor, Nagelkerke R², Akaike information criterion (AIC), and Bayesian information criterion (BIC).\u003c/p\u003e\u003cp\u003eAI-based tools, including ChatGPT (OpenAI), were employed to support the translation and proofreading of this manuscript and enhance its readability and clarity. These tools were used strictly as supplementary aids. The authors carefully reviewed, revised, and finalized the text to ensure accuracy and consistency.\u003c/p\u003e\u003cp\u003e This study has been approved by the Ethics Review Committee of the Nippon Pharmaceutical University (Nippon-Rin 5–7)\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe survey received valid responses from 973 of the 1,095 targeted supervising pharmacists (response rate: 88.9%). Of these, 489 were women, and 484 were men. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the gender-specific age distribution; years of employment; years of professional experience since obtaining a pharmacist\u0026rsquo;s license; duration in the current managerial position; allocation of work hours to dispensing, interpersonal, and managerial work; marital status; presence of children; job titles; and perceived workload during both normal and busy periods.\u003c/p\u003e\n\u003cp\u003eFor age distribution, 49.4% of participants were in their 30s (the highest proportion) followed by 23.1% in their 40s, 12.4% in their 20s, 11.8% in their 50s, and 3.2% aged 60 and above. The gender distribution was nearly equal with 50.3% female and 49.7% male. For age groups according to gender, the highest proportion was those in their 30s for both genders (24.3% of women, 25.2% of men). The median length of continuous employment was 88.0 months (89.0 for women, 76.0 for men). The median length of professional experience after obtaining a pharmacist\u0026rsquo;s license was 136.5 months (164.5 for women, 130.0 for men). The median duration in the current managerial position was 36.5 months (33.0 for women, 47.0 for men).\u003c/p\u003e\n\u003cp\u003eWhen evaluating work effort on a 10-point scale, both genders had a median score of 3.0 for allocation to dispensing work. The median score for allocation to interpersonal work was 4.0 points and was similar across all age groups and genders. The median scores for allocation to managerial work ranged from 2.0 to 3.0 points for both genders. The proportion of participants with spouses was 54.6% overall (47.4% of women, 61.9% of men). The proportion of participants with children was 39.1% (30.3% of women, 47.9% of men). Regarding positions, 68.9% of the participants held managerial roles equivalent to store managers or higher (67.7% of women, 70.0% of men). By age group, the proportion was highest among participants in their 40s (73.3%). The median perceived workload during normal periods was 3.0 on a five-point scale with no significant differences between genders or age groups. During busy periods, the median score was 4.0 except for among men in their 50s, who scored 3.0.\u003c/p\u003e\n\u003cp\u003eOccupational stress analysis revealed that men reported high stress levels in \u0026ldquo;quantitative job overload\u0026rdquo; and \u0026ldquo;fatigue,\u0026rdquo; while women reported high stress levels in \u0026ldquo;quantitative job overload and qualitative job overload\u0026rdquo; with over 25% of respondents in these categories classified as having high stress (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e;\u003cstrong\u003eAdditional files1\u003c/strong\u003e). Regarding workplace support, the proportion of high stress ratings was relatively low. The proportions of high stress related to support from supervisors were 4.1% for men and 1.2% for women. The proportions of support from colleagues were 7.0% for men and 1.8% for women. The proportions of support from family and friends were 7.9% for men and 3.3% for women.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe results of the UWES-17 are presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The median total score on the UWES-17 was 2.82 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98). Men had a median score of 2.74 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation [SD]: 2.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00), and women had a median score of 2.94 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93). Among the three factors (vigor, dedication, and absorption), \u0026ldquo;dedication\u0026rdquo; was highest, followed by \u0026ldquo;absorption\u0026rdquo; and \u0026ldquo;vigor.\u0026rdquo; Regarding dedication, the overall median was 3.00 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14). For women, the median was 3.20 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09), and for men, the median was 2.80 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17). Regarding absorption, the overall median was 2.83 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05). For women, the median was 2.83 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01), and for men, the median was 2.67 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09). Regarding vigor, the overall median was 2.67 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03). For women, the median was 2.67 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00), and for men, the median was 2.50 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06).\u003c/p\u003e\n\u003cp\u003eThe relationships between the UWES-17 scores and the basic attributes are shown in \u003cstrong\u003eAdditional files 2\u0026ndash;5\u003c/strong\u003e. Analysis of the UWES-17 scores and occupational stress revealed significant correlations across all items. Analysis by age group showed that participants in their 50s and those aged 60 and above had significantly higher work engagement than those in their 20s\u0026ndash;40s. An analysis of perceived workload during normal and busy periods revealed significant differences in work engagement between groups reporting a \u0026ldquo;very high workload\u0026rdquo; [5] and other groups [1\u0026ndash;3]. Participants with spouses showed significantly higher work engagement overall, and those with children exhibited significantly higher scores across all subscales of the UWES-17.\u003c/p\u003e\n\u003cp\u003eThe results of the binary logistic regression analysis are presented in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. For the logistic regression analysis, the quartile distribution of the total UWES-17 scores was calculated to define the binary outcome variable. The median score was 48.0, with the first quartile (Q1) at 37.0 and the third quartile (Q3) at 58.0, indicating an interquartile range of 21.0. Participants whose total scores were above the third quartile (Q3\u0026thinsp;\u0026gt;\u0026thinsp;58.0) were classified into the high engagement group (n\u0026thinsp;=\u0026thinsp;236), while those with scores below the first quartile (Q1\u0026thinsp;\u0026lt;\u0026thinsp;37.0) were classified into the low engagement group (n\u0026thinsp;=\u0026thinsp;258). These groups were assigned values of 1 and 0, respectively, and used as the dependent variable in the logistic regression model. \u0026ldquo;Meaningfulness of work,\u0026rdquo; \u0026ldquo;job control,\u0026rdquo; \u0026ldquo;suitable jobs,\u0026rdquo; and \u0026ldquo;age group (\u0026ge;\u0026thinsp;50 years)\u0026rdquo; were identified as significant factors that increased the likelihood of being in the upper quartile of UWES-17 scores. For \u0026ldquo;meaningfulness of work,\u0026rdquo; the odds were 15.4 times higher (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) when the score increased from 2 to 3 and 15.6 times higher (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) when it increased from 3 to 5. For \u0026ldquo;suitable jobs,\u0026rdquo; an increase from 2 to 3 raised the odds by 4.1 times (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0003); for \u0026quot;job control,\u0026quot; the same increase raised the odds by 3.5 times (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0037). Participants aged 50 years and above had 3.7-times-higher odds (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0031) compared with those under 50 years. Supplementary factors included \u0026ldquo;coworker support,\u0026rdquo; \u0026ldquo;poor physical environment stress,\u0026rdquo; and \u0026ldquo;quantitative job overload.\u0026rdquo; The model fit indicators were R\u0026sup2; (0.509), AIC (444.0), and BIC (635.4).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study clarified the actual state of work engagement among supervising pharmacists in major insurance pharmacy companies and identified the associated factors. First, the work engagement of supervising pharmacists was examined based on previous studies conducted in other industries. The median UWES-17 score of supervising pharmacists was 2.82. According to Shimazu and other previous studies, the UWES-9 score for general Japanese workers is estimated to be approximately 2.8 to 2.9 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Comparative research across 16 countries, including Japan, found that Japanese workers scored significantly lower than workers from 15 other countries (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In healthcare professions, general nurses have reported scores ranging from 2.2 to 2.7 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). A study across 16 facilities reported that general nurses had a median score of 2.4, while nurse managers had a median score of 3.0, suggesting that higher positions tended to have higher scores (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Although direct comparisons were not possible, the work engagement of supervising pharmacists was similar to that of general Japanese workers and nurse managers.\u003c/p\u003e\u003cp\u003eAmong the three-factor structure of the UWES (vigor, dedication, and absorption), \"dedication\" was the highest, while \"vigor\" was the lowest. \u0026ldquo;Dedication\u0026rdquo; is characterized by a sense of significance, enthusiasm, inspiration, pride, and challenge (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The following outlines the primary reasons for the highest level of \u0026ldquo;dedication\u0026rdquo;. Systematic data on the professional pride of supervising pharmacists in Japan are still lacking, nevertheless, Japanese pharmacists including supervising pharmacists are nationally licensed professionals, a status that confers social recognition of their role (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and is considered to foster a sense of pride and meaning in their work. In a recent survey, \u0026ldquo;Pride in work\u0026rdquo; was identified as a quality indicator in a survey of community pharmacists in Japan (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).Supervising pharmacists engage in direct dialogue with patients through interpersonal work and follow-up during medication periods. Among other healthcare workers, a study of nurses found that recognizing patients\u0026rsquo; expressions of gratitude enhances the meaningfulness of their work and, in turn, improves their innovative performance (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Expressions of gratitude have been cited as a factor that can enhance work engagement (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). \u0026ldquo;Pride in work\u0026rdquo;, coupled with gratitude gained through direct patient interactions, may enhance \u0026ldquo;dedication\u0026rdquo; component of work engagement.\u003c/p\u003e\u003cp\u003e\u0026ldquo;Vigor\u0026rdquo; is characterized by high levels of energy and mental resilience while working, a willingness to invest effort in one\u0026rsquo;s work, and persistence even in the face of difficulties (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Previous studies have emphasized the importance of vigor as a motivational concept for enhancing work engagement.\u003csup\u003e5\u003c/sup\u003e In the current VUCA (Volatile, Uncertain, Complex, Ambiguous) era, the pharmacy industry also requires resilience to adapt flexibly to changes, making it especially important to enhance \"vigor\" as a component of work engagement.\u003c/p\u003e\u003cp\u003eNext, based on the results and the JD-R model, the roles and work environments unique to supervising pharmacists were examined in terms of their impact on work engagement and potential countermeasures. The JD-R model elucidates the mechanisms underlying work engagement and identifies three pivotal factors that influence the development of work engagement: \u0026ldquo;job demands,\u0026rdquo; \u0026ldquo;job resources,\u0026rdquo; and \u0026ldquo;personal resources.\u0026rdquo; (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) \u0026ldquo;Job demands\u0026rdquo; such as job pressure, emotional demands in interpersonal interactions, and mental and physical strain require sustained effort and are associated with psychological costs that, if not adequately managed, can diminish work engagement (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). \u0026ldquo;Job resources,\u0026rdquo; such as autonomy, performance feedback, support from supervisors and coworkers, and career development opportunities, along with \u0026ldquo;personal resources,\u0026rdquo; such as self-efficacy, optimism, resilience, and hope, interact to enhance work engagement (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The JD-R model highlights the importance of enhancing job resources as they contribute not only to improving work engagement but also to reducing stress reactions (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). According to the JD-R model, high job demands, when combined with insufficient job resources such as lack of support, increase stress levels, which, in turn, diminish work engagement (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSupervising pharmacists supervise employees, manage pharmaceuticals, and provide information to ensure their proper use (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Amid chronic staffing shortages caused by pharmacy expansion and regional disparities, supervising pharmacists must juggle players and managerial roles and handle a wide range of pharmacy operations, which cause high job demands. In this study, over 25% of the participants were identified as experiencing high stress due to \u0026ldquo;quantitative job overload.\u0026rdquo; Strengthening systems that utilize job resources and enhance support for supervising pharmacists is essential to reduce stress reactions and improve work engagement (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe binary logistic regression analysis identified seven factors that significantly influenced work engagement: \u0026ldquo;meaningfulness of work,\u0026rdquo; \u0026ldquo;suitable jobs,\u0026rdquo; \u0026ldquo;age group,\u0026rdquo; \u0026ldquo;job control,\u0026rdquo; \u0026ldquo;coworker support,\u0026rdquo; \u0026ldquo;poor physical environment stress,\u0026rdquo; and \u0026ldquo;quantitative job overload\u0026rdquo; (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These factors highlight the challenges in the roles and work environments unique to supervising pharmacists, as framed by the JD-R model.\u003c/p\u003e\u003cp\u003e\u0026ldquo;Suitable jobs,\u0026rdquo; \u0026ldquo;job control,\u0026rdquo; \u0026ldquo;coworker support,\u0026rdquo; and \u0026ldquo;poor physical environment stress\u0026rdquo; fall under the job resources category of the JD-R model. Major insurance pharmacy companies, with their nationwide unified management policies, facilitate efficient operations and ensure the stability of \u0026ldquo;suitable jobs\u0026rdquo; and \u0026ldquo;job control.\u0026rdquo; In contrast, Kato et al. highlighted that management policies restricting the unique decision-making and coordination roles of supervising pharmacists in store operations result in a decline in the autonomy of pharmaceutical tasks and hinder the full utilization of individual pharmacists' abilities (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). These limitations raise challenges in areas such as \u0026ldquo;suitable jobs\u0026rdquo; and \u0026ldquo;job control.\u0026rdquo;\u003c/p\u003e\u003cp\u003eRegarding \u0026ldquo;coworker support\u0026rdquo;, recent studies have underscored that leaders themselves need backing: managers\u0026rsquo; work engagement and psychological wellbeing are strongly shaped by the support they receive from their own coworlers and supervisors (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Consistently, a 16facility study of nurses and nurse managers found that staff who perceive strong coworker support report significantly higher engagement (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Yet chronic staffing shortages in community pharmacies leave supervising pharmacists\u0026mdash;who are expected to coordinate and support others\u0026mdash;with few opportunities for allhands meetings or informal conversation, making it hard for them to obtain adequate coworker support. Consequently, organisationwide measures are required to ensure that supervising pharmacists receive the support they need.\u003c/p\u003e\u003cp\u003eMany pharmacies lack well-equipped back-office spaces, forcing employees to work long hours in confined areas, potentially contributing to \u0026ldquo;poor physical environment stress.\u0026rdquo;\u003c/p\u003e\u003cp\u003e\u0026ldquo;Quantitative job overload\u0026rdquo; is categorized as job demands in the JD-R model. Although addressing diverse tasks can be an opportunity for growth, this study suggests that a high workload contributes to stress. \u0026ldquo;Meaningfulness of work\u0026rdquo; was observed in supervising pharmacists belonging to the top group. When \u0026ldquo;meaningfulness of work\u0026rdquo; is regarded as meaningful work, it has been examined in relation to both job and personal resources (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Engaging in meaningful work is known to enhance personal resources in the JD-R model, such as \u0026ldquo;self-efficacy\u0026rdquo; and \u0026ldquo;optimism\u0026rdquo; (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), which are considered critical for improving work engagement.\u003c/p\u003e\u003cp\u003eThese findings suggest that the distinctive managerial roles of supervising pharmacists-alongside the overall pharmacy work environment shared by all staff- exert an important influence on their work engagement. Tailored measures such as support for self-awareness and addressing various challenges are necessary to enhance work engagement. Future human resource education must focus on developing \u0026ldquo;communities of practice\u0026rdquo; that not only excel in specialized skills but also facilitate effective teamwork. Foundational to this approach is self-and mutual understanding along with knowledge of organizational roles and cognitive diversity, which are essential for fostering organizational climates in which individuals and teams can thrive and find purpose in their work.\u003c/p\u003e\u003cp\u003eThis study provides significant insights by presenting reliable foundational data through a largescale cross-sectional survey in a field with limited evidence on pharmacists' work engagement. This study also provides concrete proposals regarding the direction of human resources and career training during this transitional period. These findings contribute to the sustainable growth of the pharmacy industry and to efforts to enhance work engagement, including supervising pharmacists\u003c/p\u003e\u003cp\u003eOur sample was drawn from four large insurance‑pharmacy chains, excluding the small‑ and medium‑sized pharmacies that account for most outlets nationwide; the findings should therefore be extrapolated only with caution. Because organisational programmes designed to foster work engagement were not assessed, their potential influence could not be modelled, and future studies should measure and adjust for these initiatives. Moreover, individual attributes that may shape engagement\u0026mdash;such as income level and specialized credentials\u0026mdash;were not captured and merit examination in subsequent research.\u003c/p\u003e\u003cp\u003eA plausible explanation is that older pharmacists tend to possess richer job resources-greater autonomy, skill utilisation and person-job fit-than their younger colleagues. Empirical studies show that these resources increase with age and, in turn, predict higher levels of work engagement among employees.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis crosssectional survey of 973 supervising pharmacists in four large insurancepharmacy chains recorded a median UWES-17 score of 2.82, with \u003cem\u003ededication\u003c/em\u003e the strongest dimension.\u003c/p\u003e\u003cp\u003eMajor pharmacy chains address chronic staffing shortages by delegating dispensing tasks to clerical staff and dietitians and by reducing the burden of material tasks through the adoption of dispensing equipment and information technology tools. In recent years, they have also actively worked on improving workplace factors such as enhancing labor productivity through the introduction of AI. However, despite having various support systems in place, efforts to alleviate the mental burden of supervising pharmacists, establish support structures that enable individuals to experience personal growth and meaningfulness of work, promote self-awareness and mutual understanding to leverage individuality and diversity in human resource development, and develop career-education programs remain at a nascent stage. The Ministry of Health, Labour and Welfare also suggests a positive correlation between higher implementation rates of human resource development and work engagement (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Accordingly, organisational humanresource strategies should deliberately incorporate measures that preserve and strengthen the work engagement of supervising pharmacists.\u003c/p\u003e\u003cp\u003eIn addition to these empirical findings, this study contributes by providing a reliable data baseline in a field with limited prior evidence and by proposing directions for human resource and career development during this transitional phase in the pharmacy sector.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBJSQ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBrief Job Stress Questionnaire\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eJD-R\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eJob Demands\u0026ndash;Resources\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUWES-17\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUtrecht Work Engagement Scale 17-item version\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAuthors\u0026apos; information\u003c/h3\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with Ethical Guidelines for Medical and Health Research Involving Human Subjects in Japan. This study was approved by the Research Ethics Committee for Human Subjects at Nippon Pharmaceutical University (Approval No: Nippon-Rin 5\u0026ndash;7; Date of approval: August 22, 2023). Participation in the survey was entirely voluntary, and informed consent was implied by completing and submitting the questionnaire. Respondents were explicitly informed that collected data would be anonymized to protect their privacy and would not be used for any purposes other than statistical analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors participated in meetings related to the study (e.g., study design and manuscript review). YI conceived the study and drafted the manuscript. HS contributed significantly to manuscript preparation by frequently reviewing and suggesting revisions. TY contributed to the preparation of the research plan and advised on manuscript preparation. SO contributed to the survey and statistical analyses and provided advice on manuscript preparation. TH supervised study implementation, reviewed the manuscript, and provided guidance on its interpretation.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe express our deepest gratitude to Qol Co., Ltd.; AIN HOLDINGS, INC.; I\u0026amp;H Co., Ltd.; and Sugi Pharmacy Co., Ltd., for their invaluable support.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eResearch data will not be made publicly available to protect the participants\u0026rsquo; privacy and to comply with ethical guidelines. Moreover, informed consent obtained from the participants did not include permission for data sharing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMinistry of Health LaW, Overview. 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Journal of Management Studies. 2019;56(3):500\u0026thinsp;\u0026ndash;\u0026thinsp;28.dol: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/joms.12406\u003c/span\u003e\u003cspan address=\"10.1111/joms.12406\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Work engagement, Supervising pharmacists, Occupational stress, JD-R model, Career education, UWES-17","lastPublishedDoi":"10.21203/rs.3.rs-7276046/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7276046/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study investigated the work engagement of supervising pharmacists and sought to identify factors contributing to high work engagement. Given the growing shortage of healthcare and welfare professionals in Japan, enhancing work engagement among pharmacists is critical to improve productivity and prevent turnover. Addressing these issues is particularly important for pharmacists providing local healthcare services. Supervising pharmacists were exclusively targeted due to their pivotal role as gatekeepers between organizational leadership and frontline staff, as well as the potential for a crossover effect, where their engagement influences that of their subordinates\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional survey was conducted among supervising pharmacists from major insurance pharmacy companies between August 2023 and September 2024. Participants completed a web-based questionnaire assessing demographic data, occupational stress (The Brief Job Stress Questionnaire), and work engagement (The Utrecht Work Engagement Scale; UWES-17). The association between work engagement and the potential associated factors were evaluated using bivariate and multivariate logistic regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from 973 participants (response rate: 88.9%) were analyzed. The median UWES-17 score was 2.82 (mean ± standard deviation: 2.80 ± 0.98). Among the three dimensions of work engagement, \"dedication\" scored the highest. Significant predictors of higher UWES-17 scores included perceived “meaningfulness of work,” “job control,” “suitable jobs,” “age group (≥ 50 years),” “coworker support,” “poor physical environment stress,” and “quantitative job overload.”\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study suggests that the distinct roles and workplace environments of supervising pharmacists shape their work engagement. Balancing job resources and demands is therefore critical for sustaining engagement and, by extension, for maintaining workforce stability and service quality in community pharmacies. Targeted interventions that may strengthen self-awareness, peer collaboration, and career development within structured practice communities could potentially reinforce these gains.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrail registration: \u003c/strong\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Exploring Work Engagement and Its Associated Factors among Supervising Pharmacists in Japan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-08 09:06:01","doi":"10.21203/rs.3.rs-7276046/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"784c88cf-4601-48b4-b9b9-77b7b9523af7","owner":[],"postedDate":"August 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-26T05:23:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-08 09:06:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7276046","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7276046","identity":"rs-7276046","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}