Development of a Workplace Health Initiatives Checklist for Women and its cross-sectional associations with burnout, productivity, and satisfaction

The WHIC‑W was conceptualized as a formative implementation index: each item reflects a distinct workplace action, not manifestations of a single latent construct. Thus, internal-consistency coefficients and factor analysis were not used as primary evaluations. We assessed content validity via a multistage expert and Patient and Public Involvement (PPI) review and evaluated construct validity by testing hypothesized cross-sectional associations between WHIC‑W scores and burnout, productivity, and job satisfaction. To establish content validity, we first referred to the 38-item workplace checklist developed by the Japan Society for Occupational Health in 2008, 26 created by 10-20 occupational health experts, including physicians, nurses, and industrial hygienists. It covers hazardous environments, disability prevention, and harmful exposures. The team has been updated regularly since 2008. Amid Japan’s declining birthrate, government policies have increasingly focused on women’s health, including menstrual and menopausal symptoms, infertility treatment (insured since 2022), work–childcare balance, and breast cancer. A 2017 survey by the Ministry of Economy, Trade and Industry revealed limited corporate action. 27 Against this backdrop, we aimed to create a checklist for working women. Between 2020 and 2022, a multidisciplinary team drafted a 56-item checklist. A PPI Committee, comprising representatives from women’s health and femtech companies, corporate leaders, health insurers, managers, and human resources, reviewed and refined it to 34 items. We further excluded 8 items that were primarily directed at employers, including items related to education and promotion opportunities for female employees, parental leave uptake among male employees, and acquisition of the Kurumin mark, a certification system evaluating corporate efforts to support the balance between work and childcare. Ultimately, a final 26-item “WHIC-W” was established ( Table S1 ). This checklist consists of 2 domains: Domain 1, “Improvement of the Workplace Environment” (15 items), and Domain 2, “Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work” (11 items). Each item of the “WHIC-W” was assessed by asking participants, “Does your workplace implement the following initiative?” Responses were coded as 1 for “yes” and 0 for “no” or “don’t know,” and summed to generate a total score. A higher total score indicated that a greater number of workplace initiatives addressing women’s health were being implemented. This study employed a cross-sectional web-based survey conducted from October 13 to 16, 2023, targeting female respondents aged 20 to 69 years who were registered as monitors with GMO RESEARCH & AI, an internet research company based in Japan ( https://gmo-research.ai/ ). A total of 128 184 individuals met the inclusion criteria—(i) being a Japanese woman and (ii) being in paid employment—and were eligible to receive survey invitations. Of these, 22 014 were invited to participate, and 3799 accessed the survey page. Ultimately, 3395 responses were collected. Following data cleaning, 52 cases were excluded, resulting in a final analytical sample of 3343 respondents. The survey was closed once the target of approximately 3000 responses was exceeded, yielding an estimated response rate of approximately 10%. The survey was administered online. Participants were informed of the study’s purpose and the intended use of the data via an on-screen explanation. Only those who provided informed consent were permitted to proceed. All personal data were securely stored within the research company’s protected infrastructure, and the anonymized survey results were provided by the company. This study was approved by the Ethics Committee of Akita University Graduate School of Medicine (No. 2999, approved June 12, 2023) and was conducted in accordance with the principles of the Declaration of Helsinki. The outcomes of the developed checklist included the Copenhagen Burnout Inventory (CBI), work productivity, intention to resign, and job satisfaction. Supportive workplace initiatives addressing women’s health are expected to reduce chronic work-related stress and role strain, while facilitating sustained work ability and work engagement, which have been consistently linked to burnout, productivity, and job satisfaction in occupational health research. Given that higher total scores represent a greater extent of workplace initiatives for women’s health, our research hypothesis was that higher scores would be associated with reduced levels of burnout and intention to resign, while enhancing work productivity and job satisfaction. The CBI, developed in Denmark, is a validated tool for assessing burnout. It comprises 3 subscales: personal burnout (PBO, 6 items), work-related burnout (WBO, 7 items), and client-related burnout (CBO, 7 items), and was used to measure mental fatigue. 28 PBO assesses general exhaustion, WBO targets work-related stress, and CBO captures fatigue from client interactions. Items were rated on a 5-point Likert scale (eg, “To what extent do you feel tired?”). Each item was converted to a score between 0 and 100, where “Always/To a very high degree” equaled 100 points and “Not at all/Hardly at all/To a very low degree” equaled 0 points. The mean score was then calculated. Respondents were considered nonrespondents if they answered fewer than 3 questions on the personal and customer-related scales or fewer than 4 questions on the work-related scale. The work-related scale included 1 reverse-scored item, which was incorporated into the average score after reversal. A higher overall score indicates a greater degree of burnout syndrome. Absolute presenteeism was measured using the WHO Health and Work Performance Questionnaire (HPQ; short form, Japanese edition). Productivity loss due to presenteeism was assessed via 2 items: Q1 rated typical performance of peers (0 = worst, 10 = best), and Q2 rated self-performance over the past 4 weeks. Responses ranged from 0 (severely affected) to 10 (unaffected). Absolute presenteeism was calculated as Q2 × 10 (range: 0-100; higher scores = less decline). 29 , 30 Absenteeism was operationalized as the number of full days absent from work for health-related reasons. Participants were asked: “In the past four weeks (28 days), how many full days did you take off work for health reasons (excluding leisure days)?” Individuals reporting 1 or more days of absence were considered to have experienced absenteeism, as the overall prevalence of work absence in this population was relatively low, making it necessary to apply a sensitive threshold. The level of satisfaction was calculated using a visual analog scale (VAS), with scores ranging from 0 (not satisfied at all) to 10 (very satisfied), based on the question, “How satisfied are you with your current workplace?” Those who answered 6 or more were considered to be satisfied, as relatively few respondents reported very high satisfaction, necessitating a moderate cutoff to ensure sufficient variability and analytic power. Intention to resign was measured on a 5-point scale (strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, strongly agree) in response to the questions, “Do you want to change departments (job rotation) within the next year?” and “Do you want to leave within the next year?” Participants who responded “somewhat agree” or “strongly agree” to either question were classified as having the intention to resign; all others were classified as not having the intention to resign. Information was collected on participants’ age, marital status (single/married), presence of children, provision of family care, employment status (regular/nonregular, including part-time/self-employed or small office or home office/other), occupation , 31 and industry. 32 For continuous outcomes, linear regression was used to estimate regression coefficients (β) and 95% CIs for associations between domain scores of the 26-item checklist and PBO, WBO, CBO, and absolute presenteeism. For categorical outcomes, logistic regression estimated odds ratios (ORs) and 95% CIs for associations with absenteeism, satisfaction, and intention to resign. All models were adjusted for age, marital status, presence of children, family care, and employment status. Analyses were conducted using SAS (Statistical Analysis System, version 9.4), with 2-sided significance set at P  < .05.

Table 1 presents the participants’ characteristics. The average age of the survey respondents was 45 years, with 54.4% being single ( n  = 1820), 43% having at least 1 child ( n  = 1427), and 6.9% providing family care for family members ( n  = 232). Among the employees, 40.6% were regular employees ( n  = 1357), and 49.8% were nonregular employees ( n  = 1665) including contract, dispatched, and part-time workers. The highest occupational category was clerical workers (36%), followed by service workers (23%), professionals and engineering workers (11%), and sales workers (9%). The top industry type was wholesale and retail trade (15%), followed by medicine, health care, welfare (14%), services (13%), and manufacturing (10%). Participant characteristics. Abbreviations: CBO, client-related burnout; IQR, interquartile range; PBO, personal burnout; WBO, work-related burnout. The median (interquartile range, IQR) CBI scores were 29 (17-50) for PBO, 36 (21-50) for WBO, and 33 (17-46) for CBO. Compared with previous studies that investigated hospital nurses and the academic faculty of a university, the burnout values were low for this group. 33 , 34 For work productivity, the median (IQR) absolute presenteeism rate was 60% (50%-70%), and the absenteeism rate was 1 (0-8 days) per 4 weeks. The median (IQR) satisfaction level was 6 (5-8) on the VAS. Intention to resign was observed in 702 participants (21%). Table 2 shows the scores for the WHIC-W. For the 26-item checklist, the median total score (IQR) was 3 (1-9), indicating that few workplaces had implemented initiatives to support women. The median score for Domain 1, “Improvement of the Workplace Environment,” was 2 out of 15, while that for Domain 2, “Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work,” was 0 out of 11. WHIC-W total and domain scores. Abbreviation: WHIC-W, Workplace Health Initiatives Checklist for Women. a Domain 1: Improvement of the Workplace Environment. b Domain 2: Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work. In the univariate analysis of PBO ( Table 3 , Figure 1 ), the following variables were significantly associated with PBO scores: Domain 1 “Improvement of the Workplace Environment” ( P  < .0001), Domain 2 “Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work” ( P  = .0018), total checklist ( P  < .0001), age ( P  < .0001), single (compared with married; P  < .0001), presence of children (compared with no children; P  < .0001), and provision of family care (compared with no provision; P  = .0154). General linear regression model for the effect of checklist items on Copenhagen Burnout Inventory and absolute presenteeism (forest plot). Domain 1: Improvement of the Workplace Environment. Domain 2: Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work. * Adjusted for age, marital status, presence or absence of children, family care availability, and employment status. Abbreviations: CBO, client-related burnout; PBO, personal burnout; WBO, work-related burnout. General linear regression model for the effect of checklist items on Copenhagen Burnout Inventory and absolute presenteeism. Abbreviations: CBO, client-related burnout; PBO, personal burnout; WBO, work-related burnout. a Adjusted for, age, marital status, presence or absence of children, family care availability, employment status. In multivariate analysis, PBO was negatively correlated with Domain 1 (β = −0.71, 95% CI: −1.035 to −0.388) and total checklist score (β = −0.32, 95% CI: −0.435 to −0.196). In addition, PBO was negatively correlated with age (β = −0.44, 95% CI: −0.504 to −0.373) and compared with nonregular employment status (contract employees, commissioned employees, and part-time), other employment status (β = −2.65, 95% CI: −4.349 to −0.949). On the other hand, a positive correlation with PBO was found for single (compared with married; β = 3.32, 95% CI: 1.357-5.290), for people without children (compared with people with children; β = 2.82, 95% CI: 0.707-4.939), and for those who provide family care (compared with those who do not provide family care; β = 8.87, 95% CI: 5.611-12.127). In the univariate analysis, significant associations were observed in Domain 1 ( P  < .0001), Domain 2 ( P  < .0001), total checklist ( P  < .0001), age ( P  < .0001), single (compared with married; P  < .0001), presence of children (compared with no children; P  < .0001), and other employment status (compared with nonregular; P  < .0001) ( Table 3 , Figure 1 ). In multivariate analysis, WBO was negatively correlated with Domain 1 (β = −0.57, 95% CI: −0.823 to −0.316) and the total checklist (β = −0.30, 95% CI: −0.395 to −0.207), and age (β = −0.39, 95% CI: −0.443 to −0.340). On the other hand, a positive correlation with WBO was found for single (compared with married; β = 3.41, 95% CI: 1.874-4.956), for people without children (compared with people with children; β = 2.45, 95% CI: 0.790-4.106), and for those who provide family care (compared with those who do not provide family care; β = 6.48, 95% CI: 3.926-9.031). The following variables were significantly associated with CBO in the univariate analysis: Domain 1 ( P  = .0049), total checklist ( P  = .0281), age ( P  < .0001), single (compared with married) ( P  < .0001), presence of children (compared with no children; P  < .0001), providing family care (compared with not providing; P  = .0246), and other employment status (compared with nonregular; P  < .0001) ( Table 3 , Figure 1 ). In multivariate analysis, CBO was negatively correlated with Domain 1 (β = −0.59, 95% CI: −0.878 to −0.307) and the total checklist (β = −0.17, 95% CI: −0.276 to −0.065), and age (β = −0.27, 95% CI: −0.331 to −0.215). On the other hand, CBO was positively correlated with Domain 2 (β = 0.36, 95% CI: 0.010-0.712). In addition, a positive correlation with CBO was found for single (compared with married; β = 2.70, 95% CI: 0.960-4.433), for people without children (compared with people with children; β = 2.49, 95% CI: 0.618-4.355), and for those who provide family care (compared with those who do not provide family care; β = 6.25, 95% CI: 3.372-9.127). In the univariate analysis of absolute presenteeism, there were significant associations with Domain 1 ( P  < .0001), Domain 2 ( P  < .0001), total checklist ( P  < .0001), age ( P  < .0001), single (compared with married; P  < .0001), and the presence of children (compared with no children; P  < .0001) ( Table 3 , Figure 1 ). In multivariate analysis, absolute presenteeism was positively correlated with Domain 1 (β = 0.62, 95% CI: 0.377-0.862) and the total checklist (β = 0.43, 95% CI: 0.336-0.516) and, age (β = 0.14, 95% CI: 0.088-0.186). On the other hand, absolute presenteeism was negatively correlated with single (compared with married; β = −1.94, 95% CI: −3.418 to −0.471). In the univariate analysis of absenteeism, significant associations were observed in Domain 1 “Improvement of Work Environment” ( P  = .0134), Domain 2 “Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work” ( P  = .0023), total checklist ( P  = .0039), age ( P  < .0001), and providing family care (compared with no provision; P  = .0023) ( Table 4 and Figure 2 ). Logistic regression model for the effect of checklist items on intention to resign, satisfaction, and absenteeism (forest plot). Domain 1: Improvement of the Workplace Environment. Domain 2: Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Illness and Work. * Adjusted for, age, marital status, presence or absence of children, family care availability, employment status. Logistic regression model for the effect of checklist items on intention to resign, satisfaction and absenteeism. a Adjusted for age, marital status, presence or absence of children, family care availability, employment status. In the multivariate analysis, higher total checklist scores (OR = 1.01, 95% CI: 1.001-1.021) were associated with increased absenteeism. In addition, those who provide family care (OR = 1.63, 95% CI: 1.225-2.157) were associated with increased absenteeism. In contrast, age (OR = 0.99, 95% CI: 0.983-0.994) was associated with decreased absenteeism. In the univariate analysis, there were significant associations of satisfaction with the following variables: Domain 1 ( P  < .0001), Domain 2 ( P  < .0001), total checklist ( P  < .0001), age ( P  < .0001), being single (compared with married; P  < .0001), presence of children (compared with no children; P  < .0001), and other employment status (compared with nonregular; P  = .0048) ( Table 4 and Figure 2 ). In the multivariate analysis, higher Domain 1 (OR = 1.10, 95% CI: 1.064-1.127) and total checklist scores (OR = 1.07, 95% CI: 1.055-1.079) were associated with increased satisfaction. In addition, age (OR = 1.01, 95% CI: 1.006-1.018) was associated with increased satisfaction. In contrast, single (compared with married; OR = 0.79, 95% CI: 0.664-0.931), and those without children (compared with people with children; OR = 0.81, 95% CI: 0.671-0.965) were associated with decreased satisfaction. In the univariate analysis of intention to resign, age ( P  < .0001), single (compared with married; P  = .0003), presence of children (compared with no children; P  < .0001), and other employment status (compared with nonregular; P  = .0093) were significant factors ( Table 4 and Figure 2 ). The multivariate analysis showed no significant relationship between checklist scores and intention to resign. Age (OR = 0.98, 95% CI: 0.968-0.982) was associated with decreased intention to resign. On the other hand, those who provided family care (OR = 1.72, 95% CI: 1.248-2.356) were associated with increased intention to resign compared with those who did not provide family care.

This study provides initial construct validity evidence supporting the WHIC-W as a formative checklist indexing workplace initiatives for women’s health. The observed cross-sectional associations between WHIC-W scores and burnout, productivity, and job satisfaction were consistent with a priori hypotheses, thereby supporting construct validity without implying causal relationships. Our survey showed that the average score for the WHIC-W was very low (3 out of a total of 26 points). This suggests that there may be a lack of or significant delay in workplace initiatives to promote and maintain women’s health in the workplaces of Japanese survey participants. This is consistent with the findings of the Japanese government, which reported that initiatives related to women’s health, such as campaigns on menstrual symptoms and infertility treatment, have not received as much attention as initiatives to promote work–life balance. Another reason for the very low median checklist score may be that the respondents were unaware of the existing initiatives for the health of working women in their workplaces. In this study, the checklist validation was generally as expected for the total score of Domain 1 or Domains 1 and 2 of “Improving the Work Environment” and “Support for Pregnancy, Childbirth, Childcare, Nursing Care, and Balancing Work With Illness,” but Domain 2 was not consistently significantly related to the results of the study. When the score for Domain 1 or the total score for Domains 1 and 2 was high, PBO, WBO, and CBO were significantly reversed, and the absolute presenteeism and satisfaction showed a positive correlation. This suggests that health promotion in the workplace is associated with a decrease in the risk of burnout, and that it is associated with an increase in satisfaction and absolute presenteeism. These findings imply that by implementing adequate measures, companies may enhance the retention of female employees, increase job satisfaction, and improve labor productivity. In contrast to Domain 1, Domain 2—which captures workplace support for pregnancy, childbirth, childcare, nursing care, and balancing illness and work—was not consistently associated with burnout or work productivity outcomes in this study. One plausible explanation relates to the demographic characteristics of the sample. More than half of the respondents were single, fewer than half had children, and the median Domain 2 score was zero, indicating that many participants had not experienced or required these forms of support at the time of the survey. Because the initiatives included in Domain 2 are primarily relevant to specific life stages or health conditions, their potential benefits may only become apparent among subgroups of women who are actively facing pregnancy, childcare responsibilities, caregiving, or medical treatment. In a sample where the proportion of such individuals is limited, both the exposure to Domain 2 initiatives and the variability of outcomes are reduced, making statistically significant associations less likely to be detected. This conditional nature of Domain 2 initiatives may therefore explain the weaker and less consistent associations observed in the present cross-sectional analysis. Regarding absenteeism and intention to resign, the total scores for Domains 1 and 2 were statistically related to absenteeism, but the effect size was small (OR = 1.01, 95% CI: 1.001-1.021). In addition, neither Domain 1 nor Domain 2 was statistically related to the intention to resign. This may be due to the fact that a modest 21% of the respondents expressed an intention to resign (18.3% leave, 9.6% job rotation), and the median number of absentee days was only 1 day. Moreover, the median score for Domain 2 was 0, which may explain this insignificance. Factors not captured by the checklist may also be involved. In contrast, the median satisfaction score was 6 out of 10, suggesting that robust results were likely to be obtained. Satisfaction is related to burnout and a decline in self-esteem and is thought to be related to the health of working women. 35 The strengths of our study are that the checklist was created by forming a task force and incorporating various items, including multiple rounds of face validity verification over several years by a group of experts, expert opinions, a questionnaire survey of large-scale employers and employees conducted by the Ministry of Economy, Trade, and Industry, and health coverage for infertility treatment against the backdrop of the recent decline in birthrate. Through these processes, we were able to confirm that the WHIC-W had a positive impact on women’s satisfaction, as well as on the reduction of presenteeism and burnout. This is thought to be a significant contribution to the working style of Japanese female workers, given that more than half of those work part-time. Traditionally, Japanese women tend to leave their jobs when faced with life events such as marriage, child-rearing, or caregiving for family members. 36 Reports indicate that only one-third of mothers who were employed full-time prior to childbirth remain in full-time employment 18 months after giving birth. 37 With nonregular employment, there are very few opportunities for promotion or pay disparities compared with male counterparts. 38 Furthermore, even if a mother returns to work after her child grows, job opportunities in large companies are typically limited. Consequently, these structural challenges within Japanese industries have forced many women into part-time employment, often in retail sectors such as supermarkets or in support positions within the medical field. 39 There are several limitations to this study that should be acknowledged. First, the generalizability of the findings is limited, as all respondents were Japanese; thus, the impact on working women from other ethnic and cultural backgrounds was not considered. Japan has a large gender gap, ranking 118th of 148 countries in the World Economic Forum’s annual Gender Equality Index. 1 For this reason, problems such as harassment and the difficulty of balancing work with life events are major stumbling blocks for working women, but in countries such as Iceland, where the government supports childcare and men can take paternity leave in the same way as women, 40 a completely different approach to supporting women may be necessary, and in the first place, it may not be necessary to support women at all. Second, the checklist should be flexible enough to evolve in accordance with emerging health issues and societal trends. For example, in Japan, infertility treatment was suddenly covered by the national health insurance system in 2022 as a response to the declining birthrate. Furthermore, the environment for working women is evolving due to changes in the way we work following the coronavirus pandemic, new ways of working, and government-led reforms. Third, as this was a cross-sectional study, the responses reflected a single point in time, and it was not possible to clarify causal relationships. To clarify causal relationships and investigate medium- to long-term effects, longitudinal surveys with more valid and concrete outcomes, such as the number of women who actually resigned or were promoted to higher positions, are needed.

This study provides initial evidence supporting WHIC‑W as a formative checklist indexing workplace initiatives for women’s health. WHIC‑W scores were consistently associated with lower burnout and higher productivity and job satisfaction, supporting construct validity. The 26‑item checklist enables employers, workplace managers, and employees to objectively assess the work environment and may serve as an indicator for maintaining and improving working women’s health.

According to the Global Gender Gap 2025 report by the World Economic Forum, Japan ranked 118th out of 148 countries, reflecting low female social participation. 1 Although the Equal Employment Opportunity Act was enacted in 1985 and women’s work opportunities have gradually improved, the proportion of female managers in Japan remains low by international standards, at 14.5%. 2 This persistent gap highlights the need for broader workplace reforms beyond managerial representation. Building on this broader demographic and economic context, Japan’s Ministry of Economy, Trade and Industry (METI) introduced the certified “KENKO (Health) Investment for Health” system in 2016 as part of a national strategy to address structural challenges such as the shrinking labor force and aging workforce, and to enhance corporate productivity through improved employee health. 3 Although the program was conceived as a broad workforce policy instrument rather than a measure specifically targeting women’s employment, gender‑specific support was not sufficiently incorporated at that time. Relatedly, the Ministry of Health, Labour and Welfare has operated the “Kurumin” certification since 2007 to recognize companies that support work–childcare balance 4 ; however, this labor policy instrument does not substitute for gender‑responsive measures within economic policy. Women’s health initiatives were added as an evaluation component of the certified “KENKO (Health) Investment for Health” system in 2019. 5 However, the certification framework does not specify concrete implementation items or operational definitions for workplace initiatives addressing women’s health. As a result, employers and occupational health practitioners face uncertainty regarding what specific measures should be implemented in practice. 6 Working women in Japan face a wide range of interrelated challenges, including gender-based role expectations, insufficient workplace support during major life events, and limited implementation of health-related workplace initiatives. These challenges arise from a combination of workplace-level factors (such as organizational policies, education, and support systems), broader societal norms, and individual-level health literacy. Clarifying which issues can be addressed at the workplace level is therefore essential for effective intervention. To address these challenges, this study sought to develop a formative implementation checklist for workplace initiatives supporting women’s health. Among health challenges that can be addressed through workplace initiatives, menstrual-related symptoms represent a prominent and well-documented example. Although the Labor Standards Act permits menstrual leave, 7 only 0.9% of eligible women utilize this leave. 8 Tanaka et al 9 in 2013 estimated the annual economic burden of menstrual symptoms in Japan at ¥682.8 billion, of which 72% was attributable to productivity loss due to presenteeism, defined as reduced work performance while working despite ill health. 10 These findings underscore the importance of workplace initiatives that extend beyond the mere existence of formal policies and focus on creating environments in which such measures can be practically utilized. In addition to menstrual health, workplace support related to harassment prevention, pregnancy, childbirth, and childcare remains insufficient. 11 Although legislative frameworks mandate employer action against power harassment and discrimination related to pregnancy and childcare, awareness and implementation at the workplace level remain limited. This gap between policy frameworks and workplace implementation constitutes a major barrier preventing working women from receiving adequate support during critical life events. Another critical issue refers to balancing work with pregnancy, childcare, and nursing care, which is a key concern for working women. Many women continue employment after pregnancy due to childcare leave and related measures. However, employment type shows disparity: 83.4% of full-time workers remain employed after their first child, versus 40.3% of part-time, dispatched, and other fixed-term workers. 12 As over half of Japanese women are in nonregular jobs, 13 improving workplace conditions is vital. To support pregnant workers, the government introduced the “Maternal Health Management and Guidance Card,” which shares medical information between obstetrician and gynecologist and workplace doctors to prompt employer support. 14 Yet, 57.4% of women are unaware of this card, and only 8.2% have used it. 15 Furthermore, working women face challenges in balancing employment and medical treatment. In Japan, where birthrates are low and the population is aging, infertility treatment has been covered by insurance since 2022. 16 Still, many struggle to remain employed due to difficulties in managing treatment and work . 17 , 18 Workplace education and support systems are needed to improve understanding of infertility treatment. 19 Uterine and breast cancers, common among women, are especially prevalent in working-age groups . 20 , 21 Breast cancer, in particular, significantly affects employment, including income reduction. 22 Support in the workplace is essential during the early stages of cancer diagnosis. 23 In Japan, cancer screening uptake rates for cervical and breast cancer are both lower than 50%, which is lower than in many other countries . 24 , 25 These health concerns are underrecognized by working women and occupational health staff and require prompt intervention, underscoring the need for structured workplace initiatives that directly address women’s health. Given this background and the recent inclusion of women’s health in the certified “KENKO (Health) Investment for Health” criteria, clarifying workplace initiatives that support women’s long-term employment is essential. Such initiatives are also expected to influence key work-related outcomes, including employee well-being and performance. Therefore, the aim of this study was to develop a formative implementation checklist for workplace initiatives supporting women’s health—the Workplace Health Initiatives Checklist for Women (WHIC-W). In addition, we sought to provide initial validity evidence by examining its hypothesized cross-sectional associations with burnout, productivity, and job satisfaction.