Enhancing feedback by health coaching: The Effectiveness of Mixed Methods Approach to Long-Term Physical Activity Changes in Nurses. An Intervention Study

Enhancing feedback by health coaching: The Effectiveness of Mixed Methods Approach to Long-Term Physical Activity Changes in Nurses. 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An Intervention Study Agnieszka Nerek, Katarzyna Wesołowska-Górniak, Bożena Czarkowska-Pączek This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2934300/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Mar, 2024 Read the published version in BMC Nursing → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Although knowledge of the barriers and motivators to physical activity participation among nurses is increasing, the factors influencing motivation methods’ effectiveness are not completely defined. This study aimed to identify the sociodemographic, occupational, and health-related factors that influence the effectiveness of motivation methods in increasing the level of daily physical activity among nurses . Methods: This study was based on an intervention study protocol. All registered nurses in clinical settings were invited to participate in the study. The study involved 71 professionally active nurses. A self-reported questionnaire was used to collect sociodemographic and employment data. The level of physical activity was assessed using the International Physical Activity Questionnaire, and the daily number of steps was assessed using a pedometer. Body composition was measured using a bioimpedance method, and the 5-year risk of cardiovascular events was assessed using the Harvard Score. The intervention included self-monitoring daily steps using a pedometer and completing a diary daily for one month. Additionally, a few-minute speech was sent to each participant via email on the intervention’s 7th, 14th, and 21st days. Results: The analysis revealed a higher value of physical activity recorded in the follow-up compared to the initial and final measurement in the Recreation domain [Met] (p < 0.001) and a higher value of daily steps in the follow-up compared to the final measurement (p = 0.005). Participants with a higher Harvard Score were more likely to increase their daily number of steps (OR = 6.025; 95% CI = 1.70-21.41), and nurses working in hospital wards were less likely to do so (OR = 0.002; 95% CI = 0.00-0.41). Conclusions: Recommendations for physical activity in the nursing population should focus on increasing leisure time physical activity and regular risk assessment of cardiovascular events. A mixed methods approach, such as feedback enhanced by health coaching, effectively achieves long-term physical activity changes in nurses. Daily Number of Steps Health Coaching Health-promoting Behaviours Long-Term Changes Nursing Staff Physical Activity Figures Figure 1 Figure 2 Background The benefits of regular physical activity are well-documented and include improved cardiovascular function and musculoskeletal strength, reduced morbidity and mortality risk due to chronic disease, and decreased risk of mental health problems (1,2). Additionally, performing physical activity can reduce work-related stress and incidence of burnout (3–5) and positively affect emotional intelligence and resilience (6,7). These benefits are increasingly emphasized in research on healthcare worker populations (8). Furthermore, a positive relationship has been found between stressful work conditions and obesity in nurses (9). Despite being aware of the benefits, many nurses have low levels of physical activity (10–13), placing them at an increased risk for chronic diseases (14). Over 30% of registered nurses are overweight or obese (10,15,16) leading to increased absences and decreased work capacity, potentially increasing the workload for other nurses on the unit (17,18). Although nurses have the highest rates of obesity and overweight, they have the lowest participation in workplace health promotion activities among all healthcare professional groups working in hospitals (19). As such, nurses should be a target group for health promotion initiatives (20). Several methods have been identified to promote physical activity, but the results of interventions regarding physical activity promotion in nurses, especially workplace initiatives, are inconsistent (14). Effective methods in increasing nurses’ physical activity include self-monitoring using the accelerometer or physical activity challenges, but the rate of change decreases over time (5,21), Visual triggers and health coaching with texting have also increased physical activity levels (22). Based on replicable behavior change techniques, self-monitoring behavior and subsequent feedback are typically an effective combination of methods to improve nurses’ physical activity (23). One recommendation to increase the level of physical activity is to remove barriers that discourage or prevent nurses from engaging in physical activity. These barriers include lack of time, excessive work, irregular shifts, stress, exhaustion, and fear of pain after exercise, which results from the physically demanding nature of the nursing profession (24–26). The workplace is an ideal setting to implement health promotion initiatives to reduce noncommunicable disease risk factors, according to the World Health Organization (27). However, the quality of studies assessing the impact of such interventions among nurses is mostly low to moderate, and results should be interpreted cautiously (14). Many authors report the necessity to investigate personal and occupational factors that could help nurses sustain physical activity levels in the long term (20,21). This study aims to identify sociodemographic, occupational, and health-related factors influencing the effectiveness of motivation methods in increasing daily physical activity. Methods Design and Settings This study was based on an intervention study protocol, and data were collected over 10 months, from September 2021 to June 2022. The inclusion process was continuous and intentionally included different seasons to account for the variability of the daily number of steps depending on the season, which is confirmed in the literature (28). All registered nurses in clinical settings were invited to participate in the study. Detailed information about the study was disseminated in hospitals and outpatient clinics in Warsaw, and a full list of participating institutions is included in Appendix 1. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement was used to report data (29), along with the Page et al. statement about improving the reporting of therapeutic exercise interventions in rehabilitation research (30). Sample The inclusion criteria for this study were being a professionally active nurse working in a clinical setting, being able to walk unassisted, being willing to wear a monitoring device on the wrist, and having access to the Internet and an email address. Criteria for exclusion from participation in the study were dysfunction or disability affecting gait locomotion, pregnancy, medical contraindications to exercise, or implanted pacemakers or other devices contraindicated for body composition assessment using the bioimpedance method. Sample size analysis was performed using G*Power 3.1.9.4 software. Based on analysis of variance (ANOVA) results for a moderate effect size (f = 0.25), alpha = 0.05, and test power at 0.95, the sample size required was 43 participants for repeated measures. Data Sources and Measurements The study was divided into three phases: inclusion, intervention with final assessment, and follow-up measurements. During the inclusion process, all participants consented to participate in the study. A self-reported questionnaire was used to collect sociodemographic data such as sex, age, and place of residence, as well as professional activity-related data such as education, clinical specialization, management position, number and type of workplace(s), total monthly workload, type of shift, and work experience. Body composition, including Body Mass Index (BMI) [kg/m 2 ], the absolute value of Fat Mass (Fat) in kg, and the absolute value of Free Fat Mass (FFM) in kg, was measured using a bioimpedance method (Body Composition Analyzer Maltron Bioscan 920, UK). The measurement was taken during rest in the supine position after measuring the participant’s body weight in kg. Blood pressure was measured once in the supine position using an upper arm automatic blood pressure monitor (Omron M4). On average, each examination lasted up to 10 min for each person. The 5-year risk of cardiovascular events was assessed using the Harvard Score (Score), a non-laboratory method shown to predict cardiovascular events as accurately as the Framingham Coronary Heart Disease Risk Score, which requires laboratory-based values. The Harvard Score utilized non-laboratory-based risk factors such as age, sex, diabetes status (no diabetes or diabetes), current smoking status (non-smoker or smoker), systolic blood pressure, and Body Mass Index to determine 5-year cardiovascular disease risk categories: 10–20% (moderate), > 20–30% (high), or > 30% (high). Cardiovascular risk scores were not calculated for participants younger than 35 (Gaziano et al., 2008). The level of daily physical activity was assessed using a Polish version of the long form of the International Physical Activity Questionnaire (IPAQ). The questionnaire was structured to provide separate domain-specific scores for walking (total walking MET), moderate-intensity activity (total moderate MET), and vigorous-intensity activity (total vigorous MET) within each of the work (Occupational activity [MET]), active transportation (Active locomotion [MET]), domestic chores (Domestic chores [MET]), and leisure-time domains (Recreation [MET]). Total time engaged in walking, moderate physical activity, and vigorous physical activity, as well as the total level of weekly activity (total physical activity score - TPAS), were computed according to the guidelines (Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire, 2005). The average daily number of steps was measured using a pedometer Health Manager App Beurer AS 80 (model 2016/2017) for 7 consecutive days. The nurses were instructed to wear the activity monitor from waking to bedtime (except during water activities) and to complete a diary of their daily number of steps. A flow chart depicting the measures taken in each study phase is presented in Fig. 1. Figure 1A flow chart depicting the measures taken in each study phase. Intervention All participants wore the pedometer for one month and had to complete a diary of their daily number of steps. In addition, on the intervention’s 7th, 14th, and 21st days, motivation for physical activity participation was enhanced through a few-minute speech recorded and sent to each participant’s email. The speeches covered topics such as guidelines for daily physical activity, the impact of physical activity on health, the health effects of physical inactivity, and tips on gradually increasing daily physical activity. During the speeches, participants were encouraged to achieve the goal of 10,000 steps per day, but goal achievement was not the purpose of the study. At the end of the intervention phase, final measurements were conducted, including the level of daily physical activity measure, the average daily number of steps, body composition, and Harvard Score. Follow-up The follow-up assessments were conducted after 3 months of final measurements and included the level of daily physical activity measure and the average daily number of steps. Statistical Methods All data were analyzed using IBM SPSS Statistics, version 28.0. Descriptive statistics were used to assess sample characteristics. The Shapiro-Wilk test was used to assess the consistency of the quantitative variable with a normal distribution. For the comparison of two related samples and quantitative variables, the t-test was performed, and for more than two measurements, the Friedman test or the analysis of variance for repeated measures was used (e.g., comparison of the level of daily physical activity measure and Steps values between each study phase). To determine which of the analyzed variables were predictors of the decrease/increase in the average daily number of steps (Steps), a logistic regression analysis was performed using the backward elimination method with maximum likelihood estimation. The model explained a total of 21.9% of the variance of the dependent variable (Cox and Snell R2 = 0.219) and was well fitted to the data, χ2 (8) = 3.90; p = 0.866 (Hosmer-Lemeshow test). Spearman’s rho correlation analysis determined the relationships between quantitative variables. The significance level was set at α = 0.05.For all research, this must include a final section including details of ethical approval, informed consent and, where relevant registration. Results Participant characteristic A total of 106 professionally active Polish nurses were included in the study, and 71 completed all stages. One participant was excluded during the intervention due to a leg fracture, 11 were excluded due to upper respiratory tract infections, and 23 withdrew without reason. The detailed characteristics of the study participants are summarized in Table 1. Participants were predominantly middle-aged (mean 35.65 ± 10.40 [years]), female (85.9%), residing in a city (91.5%), and had a master’s degree (59.2%) without clinical specialization (69%). Most of the participants were employed in hospital settings (90.1%), working overtime (62%) on mixed shifts (81.7%). The average work experience of participants was 12.3 ± 9.28 [years]. Table 1. The detailed characteristics of the study participants Variables: Statistics: Sociodemographic Variables: Sex, n (%) Woman 61 (85.9) Man 10 (14.1) Age [years], M (± SD) 35.65 (±10.40) Place of residence, n (%) City 65 (91.5) Village to medium-sized town 6 (8.5) Professional activity related variables: Education, n (%) Bachelor of Nursing 29 (40.8) Master of Nursing 42 (59.2) Clinical Specialization, n (%) Yes 22 (31) No 49 (69) Management position, n (%) Yes 5 (7) No 66 (93) Workplace, n (%) Hospital Ward 64 (90.1) Other 7(9.9) Total monthly workload, n (%) Full-time work 27 (38) More than full-time (full-time and overtime) 44 (62) Shift type, n (%) Daily shift 13 (18.3) Rotating shift 58 (81.7) Work experience [years], M (±SD) 12.3(±9.28) M: Mean; ± SD: Standard Deviation; Village to medium-sized town: 100,000 inhabitants; City: >100,000 inhabitants; Daily shift: working during the day; Rotating shift: working both day and night shifts. Physical activity before and after intervention There were no significant differences in the Total Physical Activity Score (TPAS [MET]) assessed by IPAQ between study points, but a detailed analysis revealed significant differences in the Recreation domain [MET]. The follow-up recorded a higher value than the initial and final measurements. However, the differences between the initial and final measurements were not significant. The average daily number of steps (Steps) was significantly higher in the follow-up compared to the final measurement, but there were no differences between the initial and final measurements. The comparisons of the results of IPAQ and Steps between each study phase are presented in Table 2 . Table 2 Comparison the results of IPAQ and Steps between each study phase. Initial measurement (n = 71) Final measurement (n = 71) Follow-up (n = 71) χ2/F p M Me SD M Me SD M Me SD IPAQ: Total Physical Activity Score [MET] 30916.00 25104.00 20762.50 26395.36 20704.00 14222.73 25840.25 23970.00 9053.79 0.20 0.906 IPAQ: Occupational activity [MET] 19102.94 14652.00 14214.43 15943.76 12264.00 10346.49 16099.00 15015.00 6166.47 1.38 0.502 IPAQ: Active locomotion [MET] 4926.06 2772.00 4989.03 3637.19 2916.00 2638.64 3838.65 3465.00 2605.67 3.19 0.202 IPAQ: Domestic chores [MET] 4640.60 3480.00 4649.33 4640.35 4020.00 3532.43 3647.25 3360.00 2051.15 6.33 0.042 IPAQ: Recreation [MET] 2246.40 792.00 3514.89 2165.99 1371.00 3046.46 2240.23 1554.00 2196.21 17.51 < 0.001 Steps 7267.68 7571.00 2066.31 7107.04 6985.00 1763.73 7764.73 8268.00 1571.87 5.43 0.005 M: Mean; ± SD: Standard Deviation; IPAQ: International Physical Activity Questionnaire; Steps: An average daily number of steps; p: p-value. The trend analysis of the Step number revealed that the average daily number of steps was similar during each of the 30 days of the intervention. A slight decrease from the average was observed on the 6th, 14th, 17th, and 20th day of the study, while a higher activity level was observed on the 25th day of the study. The trend of the daily number of steps is presented in Fig. 2. Figure 2. The trend of the daily number of steps during the intervention phase. Body composition and cardiovascular disease risk before and after intervention The study revealed a significant decrease in Body Mass Index and the absolute value of Fat Mass at [kg] in the final measurement compared to the initial measurement (t = 2.09; p = 0.04 and t = 2.22; p = 0.03, respectively). The comparisons of the results of blood pressure, body composition, and Harvard Score between each study phase are summarized in Table 3 . Table 3 Comparisons the results of blood pressure, body composition and Harvard Score between each study phase Initial measurement (n = 71) Final measurement (n = 71) 95% CI M SD M SD t p LL UL Cohens d DBP [mmHg] 75.13 7.81 75.59 7.32 -1.57 0.121 -1.06 0.13 0.19 SBP [mmHg] 119.59 9.03 119.94 8.10 -1.09 0.281 -1.00 0.29 0.13 BMI 24.62 4.70 24.60 4.71 2.09 0.040 0.00 0.04 0.25 Fat [kg] 19.80 8.88 19.63 8.93 2.22 0.030 0.02 0.33 0.26 FFM [kg] 49.38 8.88 50.15 9.24 -1.96 0.054 -1.55 0.01 0.23 M: Mean; ± SD: Standard Deviation; t: t-test; p: p-value; DBP: Diastolic Blood Pressure; SBP: Systolic Blood Pressure; BMI: Body Mass Index; Fat[kg]: absolute value of Fat mass; FFM [kg]: absolute value of Free Fat Mass Factors influencing the increase in the average daily number of steps after the intervention were examined in the present study. The results showed that 43.7% of participants had increased the Steps number at the final measure and 63.4% at the follow-up. Logistic regression analysis revealed that the odds for an increase in the Steps number decreased with higher systolic blood pressure (SBP) [mmHg] (OR = 0.92; 95% CI = 0.85-1.00) and with working in a hospital ward (OR = 0.002; 95% CI = 0.00-0.41). On the other hand, the odds for an increase in the Steps number increased with a higher Harvard Score (OR = 6.025; 95% CI = 1.70-21.41) and Free Fat Mass (FFM) [kg] (OR = 1.451; 95% CI = 1.07–1.96) measures. None of the other variables, including sociodemographic, vocational, or health-related factors, were significant predictors of an increase or decrease in the participants’ number of steps. Discussion The intervention implemented in the study did not influence the Total Physical Activity Score (TPAS [MET]) assessed by IPAQ, but a detailed analysis revealed a significant increase in the Recreation domain [MET], where a significantly higher value was recorded in the follow-up compared to the initial and final measurements. Furthermore, the average daily number of steps was significantly higher in the follow-up compared to the final measurement, suggesting that the intervention had a long-lasting effect that persisted after the completion of the intervention phase. This finding is inconsistent with previous studies that reported short-lived increases in physical activity after web-based interventions providing feedback and physical activity challenges (33). The results suggest that other motivation methods, such as health coaching, should enhance interventions with feedback and physical activity challenges (22). The good match of health coaching applied in the present study, which occurred just after the decrease in the daily number of steps, supports this hypothesis. Drawing on evidence-based behavior change techniques, such as coaching, social support, feedback, barrier identification, follow-up prompts, and health checks may help reinforce long-term physical activity changes (34). Our findings suggest that the Recreation domain of daily physical activity is the most susceptible to change. This aligns with our previous research, which demonstrated that nurses who are more motivated to be active engagement in a higher level of leisure-time physical activity than those who are less motivated (20). Research has also shown that engaging in moderate- to vigorous-intensity physical activity before a morning shift is associated with increased sedentary time and decreased physical activity during work hours (35). Henwood et al. found that nurses who engaged in ≥ 30 minutes/day of moderate workplace activity were not healthier than those who found the same amount of physical activity during their leisure time. They concluded that workplace activity does not positively affect health and well-being (36). Parker et al. suggested that occupational physical activity may not provide the same health benefits as leisure-time physical activity for nurses (37). Furthermore, Richard et al. reported that leisure-time physical activity is inversely associated with all-cause mortality, whereas occupational physical activity does not have clear associations (38). These observations support the effectiveness of intervention programs that promote physical activity, particularly in the leisure-time domain, which is most recommended for health benefits. Providing sufficient time for recovery after work and ensuring compliance with ergonomic principles are crucial to enable nurses to engage in leisure-time physical activity. Our study also revealed a significant change in participants’ Body Mass Index, which may indicate that the motivational strategies employed during the intervention phase influenced other healthy behaviors besides physical activity. Other studies have also confirmed the effectiveness of health coaching in promoting behavior changes for improved health, including body weight loss, increased physical activity, mental health status, enhanced medication adherence, better social support, and improved physical health status, including HbA1c. Health coaching is also a low-cost tool (39). The presented study identified several factors predisposing individuals to increase their daily number of steps. Participants with higher Harvard Scores were likelier to increase their Steps number, which contradicts the belief that fear arousal induced by threat (future punishment) is likely counterproductive when self-efficacy is low (23). This suggests that nurses with higher knowledge about the consequences of chronic diseases may be more motivated to change their health behaviors because of the fear of threat (future punishment), such as the 5-year risk of cardiovascular events. Conversely, participants with higher Free Fat Mass [kg] are more vulnerable to applied motivation, suggesting that naturally active individuals in good physical condition are more willing to engage in physical activity. Nurses who agree that physical activity positively affects their mental and physical condition were more motivated to engage in physical activity and showed a higher level of leisure-time physical activity (20). However, working in a hospital ward harmed the increase in the number of steps after the applied intervention. Although the type of hospital ward was not distinguished in the study, other research has shown that the average number of steps and distance traveled was greatest for nurses working in the emergency room, followed by the intensive care unit, surgical ward, and medical ward (40). Working in a hospital ward and engaging in direct patient care is considered the most demanding (35,41), and nurses not involved in direct patient care are more sedentary (41). Nurses working in rotating shifts showed a significantly higher level of general physical activity than nurses working only in daily shifts (20,42). Furthermore, nurses who are highly active during work hours are less likely to engage in leisure-time physical activity, as confirmed by Chappel et al., who revealed that occupational walking time was associated with lower activity levels during leisure time (35). Although working in a hospital ward is difficult to modify, ensuring appropriate time for recovery and compliance with ergonomic principles is necessary to enable nurses to increase their leisure-time physical activity. Limitations One limitation of the presented study is the possibility that participants may have adopted a healthier lifestyle during the observation period than they normally would have, knowing that their physical activity was being recorded. Therefore, an observer effect cannot be ruled out, a common limitation in similar studies (43). Another limitation is self-selection, meaning nurses not interested in increasing their physical activity may have chosen not to participate in the study. Conclusions To reinforce long-term changes in nurses’ physical activity, mixed methods should be employed. Feedback and physical activity challenges should be supplemented by other motivational techniques, such as health coaching, effectively promoting behavior changes for improved health. It should be highly recommended because leisure-time physical activity is the most susceptible to change according to motivational techniques. Participants with higher Harvard Scores were more likely to increase their daily number of steps; therefore, regular evaluation of this indicator among nurses is warranted. Working in a hospital ward had the most negative impact on increasing the daily number of steps, and this factor is difficult to modify. Therefore, ensuring appropriate time for recovery and compliance with ergonomic principles is necessary to enable nurses to increase their leisure-time physical activity. Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki, and was approved by Ethics Committee of Medical University of Warsaw (reference number: AK-BE/163/2020). Informed consent was obtained from all participants of the study. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests No conflict of interest has been declared by the author(s). Funding This research was as part of the project (grant number: MB/Z/10) implemented from 2020 to 2022 and financed by a subsidy allocated to science from the Medical University of Warsaw. Authors' contributions Agnieszka Nerek: Conceptualization, Data curation, Investigation, Methodology, Writing an original draft; Katarzyna Wesołowska-Górniak: Conceptualization, Funding acquisition, Methodology, Project administration, Writing an original draft, Writing - review and editing; Bożena Czarkowska-Pączek: Conceptualization, Methodology, Project administration, Supervision, Writing—review and editing. Acknowledgements We are grateful to the nurses who participated in this study. References Warburton DER, Bredin SSD. Health benefits of physical activity: a systematic review of current systematic reviews. 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The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495-9. https://doi.org/10.1016/j.ijsu.2014.07.013 Page P, Hoogenboom B, Voight M. IMPROVING THE REPORTING OF THERAPEUTIC EXERCISE INTERVENTIONS IN REHABILITATION RESEARCH. Int J Sports Phys Ther. 2017;12(2):297-304. Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I Follow-up Study cohort. Lancet. 2008;371(9616):923-31. https://doi.org/10.1016/s0140-6736(08)60418-3 Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ) – Short and Long Forms 2005 Reed JL, Cole CA, Ziss MC, Tulloch HE, Brunet J, Sherrard H, et al. The Impact of Web-Based Feedback on Physical Activity and Cardiovascular Health of Nurses Working in a Cardiovascular Setting: A Randomized Trial. Front Physiol. 2018;9:142. https://doi.org/10.3389/fphys.2018.00142 Michie S, Ashford S, Sniehotta FF, Dombrowski SU, Bishop A, French DP. A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: the CALO-RE taxonomy. Psychol Health. 2011;26(11):1479-98. https://doi.org/10.1080/08870446.2010.540664 Chappel SE, Aisbett B, Considine J, Ridgers ND. Bidirectional associations between emergency nurses' occupational and leisure physical activity: An observational study. J Sports Sci. 2021;39(6):705-13. https://doi.org/10.1080/02640414.2020.1841921 Henwood T, Tuckett A, Turner C. What makes a healthier nurse, workplace or leisure physical activity? Informed by the Australian and New Zealand e-Cohort Study. J Clin Nurs. 2012;21(11-12):1746-54. https://doi.org/10.1111/j.1365-2702.2011.03994.x Parker HM, Gallagher R, Duffield C, Ding D, Sibbritt D, Perry L. Occupational and Leisure-Time Physical Activity Have Different Relationships With Health: A Cross-Sectional Survey Study of Working Nurses. J Phys Act Health. 2021;18(12):1495-502. https://doi.org/10.1123/jpah.2020-0415 Richard A, Martin B, Wanner M, Eichholzer M, Rohrmann S. Effects of leisure-time and occupational physical activity on total mortality risk in NHANES III according to sex, ethnicity, central obesity, and age. J Phys Act Health. 2015;12(2):184-92. https://doi.org/10.1123/jpah.2013-0198 Malecki HL, Gollie JM, Scholten J. Physical Activity, Exercise, Whole Health, and Integrative Health Coaching. Phys Med Rehabil Clin N Am. 2020;31(4):649-63. https://doi.org/10.1016/j.pmr.2020.06.001 Chang HE, Cho SH. Nurses' steps, distance traveled, and perceived physical demands in a three-shift schedule. Hum Resour Health. 2022;20(1):72. https://doi.org/10.1186/s12960-022-00768-3 Ross A, Yang L, Wehrlen L, Perez A, Farmer N, Bevans M. Nurses and health-promoting self-care: Do we practice what we preach? J Nurs Manag. 2019;27(3):599-608. https://doi.org/10.1111/jonm.12718 Peplonska B, Bukowska A, Sobala W. Rotating night shift work and physical activity of nurses and midwives in the cross-sectional study in Łódź, Poland. Chronobiol Int. 2014;31(10):1152-9. https://doi.org/10.3109/07420528.2014.957296 Roskoden FC, Krüger J, Vogt LJ, Gärtner S, Hannich HJ, Steveling A, et al. Physical Activity, Energy Expenditure, Nutritional Habits, Quality of Sleep and Stress Levels in Shift-Working Health Care Personnel. PLoS One. 2017;12(1):e0169983. https://doi.org/10.1371/journal.pone.0169983 Additional Declarations No competing interests reported. Supplementary Files Appendix1.docx Cite Share Download PDF Status: Published Journal Publication published 22 Mar, 2024 Read the published version in BMC Nursing → Version 1 posted Editorial decision: Major revision 31 Aug, 2023 Reviews received at journal 30 Aug, 2023 Reviews received at journal 30 Jun, 2023 Reviewers agreed at journal 20 Jun, 2023 Reviewers invited by journal 06 Jun, 2023 Editor assigned by journal 06 Jun, 2023 Editor invited by journal 24 May, 2023 Submission checks completed at journal 24 May, 2023 First submitted to journal 14 May, 2023 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-2934300","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":203548322,"identity":"e74634de-e778-4b75-bd7e-a8192ba58198","order_by":0,"name":"Agnieszka Nerek","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Agnieszka","middleName":"","lastName":"Nerek","suffix":""},{"id":203548323,"identity":"9c1853a2-1342-452e-b345-dedbaa3619b2","order_by":1,"name":"Katarzyna Wesołowska-Górniak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABOUlEQVRIie3SsWqDQBjA8U8EXS64nhzYV7AIIZKUPkiXHoJZapZAcSoHgp1K1kztKzSLzWg5MIvgasfi2qHBRWko1TRQ0Ni5UP9ww93xu+NQgL6+PxhuzEfVkADev2f6YaVBxNYREgjLH9I8tIOI6Bei3ibPubvjM4Wh09fCxZqeRDQ/8/kFyF6AhXWLEGSJaoz4HIfIMFCMDT21OXF87jAUXWMhbhENLFAZ5pSFg4AIPqZBKjPiBBXBV0NcrbSIkokl0zl9CAdPZVmTZON9mDU5eTtKCLYklV1y+ljdAoOahHZEhP0t6ChRl9nQZOGUrriSk/ot56ltm3efU8dH9nxE22/BCc1e2G5M7zc+3RbuRFMXkZEW8dhZyHyVbteTJjnkQeP7wP4nAKCsQ8BN14bQSfr6+vr+T1+57G6zIIfBsQAAAABJRU5ErkJggg==","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Katarzyna","middleName":"","lastName":"Wesołowska-Górniak","suffix":""},{"id":203548324,"identity":"4180c504-cfd2-4116-9bfe-73a26f0f40d1","order_by":2,"name":"Bożena Czarkowska-Pączek","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bożena","middleName":"","lastName":"Czarkowska-Pączek","suffix":""}],"badges":[],"createdAt":"2023-05-14 17:44:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2934300/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2934300/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12912-024-01815-1","type":"published","date":"2024-03-22T15:01:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":37553671,"identity":"46c2e36d-b7d9-493f-82eb-ef399cabc4b8","added_by":"auto","created_at":"2023-05-26 18:58:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23351,"visible":true,"origin":"","legend":"\u003cp\u003eA flow chart depicting the measures taken in each study phase.\u003c/p\u003e","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-2934300/v1/cde4a2ecc77d4d2615346e5e.png"},{"id":37553078,"identity":"79668a98-f8fe-48c9-8e99-f946c82b662e","added_by":"auto","created_at":"2023-05-26 18:50:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57955,"visible":true,"origin":"","legend":"\u003cp\u003eThe trend of the daily number of steps during the intervention phase.\u003c/p\u003e","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-2934300/v1/b2ee9ab6bc94cc66234f74bd.png"},{"id":53404377,"identity":"f4d80b2e-3bf8-44c3-8936-c560d3363a20","added_by":"auto","created_at":"2024-03-25 15:17:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":554231,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2934300/v1/eb5de9ed-478b-4bff-80e1-d6cf31838e56.pdf"},{"id":37553080,"identity":"0776c96a-d860-4358-93ad-d52383456af5","added_by":"auto","created_at":"2023-05-26 18:50:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14296,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2934300/v1/2b959700bbcc654bca71fac3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancing feedback by health coaching: The Effectiveness of Mixed Methods Approach to Long-Term Physical Activity Changes in Nurses. An Intervention Study","fulltext":[{"header":"Background","content":"\u003cp\u003eThe benefits of regular physical activity are well-documented and include improved cardiovascular function and musculoskeletal strength, reduced morbidity and mortality risk due to chronic disease, and decreased risk of mental health problems (1,2). Additionally, performing physical activity can reduce work-related stress and incidence of burnout (3\u0026ndash;5) and positively affect emotional intelligence and resilience (6,7). These benefits are increasingly emphasized in research on healthcare worker populations (8). Furthermore, a positive relationship has been found between stressful work conditions and obesity in nurses (9). Despite being aware of the benefits, many nurses have low levels of physical activity (10\u0026ndash;13), placing them at an increased risk for chronic diseases (14). Over 30% of registered nurses are overweight or obese (10,15,16) leading to increased absences and decreased work capacity, potentially increasing the workload for other nurses on the unit (17,18). Although nurses have the highest rates of obesity and overweight, they have the lowest participation in workplace health promotion activities among all healthcare professional groups working in hospitals (19). As such, nurses should be a target group for health promotion initiatives (20).\u003c/p\u003e \u003cp\u003eSeveral methods have been identified to promote physical activity, but the results of interventions regarding physical activity promotion in nurses, especially workplace initiatives, are inconsistent (14). Effective methods in increasing nurses\u0026rsquo; physical activity include self-monitoring using the accelerometer or physical activity challenges, but the rate of change decreases over time (5,21), Visual triggers and health coaching with texting have also increased physical activity levels (22). Based on replicable behavior change techniques, self-monitoring behavior and subsequent feedback are typically an effective combination of methods to improve nurses\u0026rsquo; physical activity (23). One recommendation to increase the level of physical activity is to remove barriers that discourage or prevent nurses from engaging in physical activity. These barriers include lack of time, excessive work, irregular shifts, stress, exhaustion, and fear of pain after exercise, which results from the physically demanding nature of the nursing profession (24\u0026ndash;26). The workplace is an ideal setting to implement health promotion initiatives to reduce noncommunicable disease risk factors, according to the World Health Organization (27). However, the quality of studies assessing the impact of such interventions among nurses is mostly low to moderate, and results should be interpreted cautiously (14).\u003c/p\u003e \u003cp\u003eMany authors report the necessity to investigate personal and occupational factors that could help nurses sustain physical activity levels in the long term (20,21). This study aims to identify sociodemographic, occupational, and health-related factors influencing the effectiveness of motivation methods in increasing daily physical activity.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eDesign and Settings\u003c/p\u003e \u003cp\u003eThis study was based on an intervention study protocol, and data were collected over 10 months, from September 2021 to June 2022. The inclusion process was continuous and intentionally included different seasons to account for the variability of the daily number of steps depending on the season, which is confirmed in the literature (28). All registered nurses in clinical settings were invited to participate in the study. Detailed information about the study was disseminated in hospitals and outpatient clinics in Warsaw, and a full list of participating institutions is included in Appendix 1. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement was used to report data (29), along with the Page et al. statement about improving the reporting of therapeutic exercise interventions in rehabilitation research (30).\u003c/p\u003e \u003cp\u003eSample\u003c/p\u003e \u003cp\u003eThe inclusion criteria for this study were being a professionally active nurse working in a clinical setting, being able to walk unassisted, being willing to wear a monitoring device on the wrist, and having access to the Internet and an email address. Criteria for exclusion from participation in the study were dysfunction or disability affecting gait locomotion, pregnancy, medical contraindications to exercise, or implanted pacemakers or other devices contraindicated for body composition assessment using the bioimpedance method. Sample size analysis was performed using G*Power 3.1.9.4 software. Based on analysis of variance (ANOVA) results for a moderate effect size (f\u0026thinsp;=\u0026thinsp;0.25), alpha\u0026thinsp;=\u0026thinsp;0.05, and test power at 0.95, the sample size required was 43 participants for repeated measures.\u003c/p\u003e \u003cp\u003eData Sources and Measurements\u003c/p\u003e \u003cp\u003eThe study was divided into three phases: inclusion, intervention with final assessment, and follow-up measurements. During the inclusion process, all participants consented to participate in the study. A self-reported questionnaire was used to collect sociodemographic data such as sex, age, and place of residence, as well as professional activity-related data such as education, clinical specialization, management position, number and type of workplace(s), total monthly workload, type of shift, and work experience.\u003c/p\u003e \u003cp\u003eBody composition, including Body Mass Index (BMI) [kg/m\u003csup\u003e2\u003c/sup\u003e], the absolute value of Fat Mass (Fat) in kg, and the absolute value of Free Fat Mass (FFM) in kg, was measured using a bioimpedance method (Body Composition Analyzer Maltron Bioscan 920, UK). The measurement was taken during rest in the supine position after measuring the participant\u0026rsquo;s body weight in kg. Blood pressure was measured once in the supine position using an upper arm automatic blood pressure monitor (Omron M4). On average, each examination lasted up to 10 min for each person.\u003c/p\u003e \u003cp\u003eThe 5-year risk of cardiovascular events was assessed using the Harvard Score (Score), a non-laboratory method shown to predict cardiovascular events as accurately as the Framingham Coronary Heart Disease Risk Score, which requires laboratory-based values. The Harvard Score utilized non-laboratory-based risk factors such as age, sex, diabetes status (no diabetes or diabetes), current smoking status (non-smoker or smoker), systolic blood pressure, and Body Mass Index to determine 5-year cardiovascular disease risk categories: \u0026lt;5% (low), 5\u0026ndash;10% (low), \u0026gt;\u0026thinsp;10\u0026ndash;20% (moderate), \u0026gt;\u0026thinsp;20\u0026ndash;30% (high), or \u0026gt;\u0026thinsp;30% (high). Cardiovascular risk scores were not calculated for participants younger than 35 (Gaziano et al., 2008).\u003c/p\u003e \u003cp\u003eThe level of daily physical activity was assessed using a Polish version of the long form of the International Physical Activity Questionnaire (IPAQ). The questionnaire was structured to provide separate domain-specific scores for walking (total walking MET), moderate-intensity activity (total moderate MET), and vigorous-intensity activity (total vigorous MET) within each of the work (Occupational activity [MET]), active transportation (Active locomotion [MET]), domestic chores (Domestic chores [MET]), and leisure-time domains (Recreation [MET]). Total time engaged in walking, moderate physical activity, and vigorous physical activity, as well as the total level of weekly activity (total physical activity score - TPAS), were computed according to the guidelines (Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire, 2005).\u003c/p\u003e \u003cp\u003eThe average daily number of steps was measured using a pedometer Health Manager App Beurer AS 80 (model 2016/2017) for 7 consecutive days. The nurses were instructed to wear the activity monitor from waking to bedtime (except during water activities) and to complete a diary of their daily number of steps. A flow chart depicting the measures taken in each study phase is presented in Fig.\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;1A flow chart depicting the measures taken in each study phase.\u003c/p\u003e \u003cp\u003eIntervention\u003c/p\u003e \u003cp\u003eAll participants wore the pedometer for one month and had to complete a diary of their daily number of steps. In addition, on the intervention\u0026rsquo;s 7th, 14th, and 21st days, motivation for physical activity participation was enhanced through a few-minute speech recorded and sent to each participant\u0026rsquo;s email. The speeches covered topics such as guidelines for daily physical activity, the impact of physical activity on health, the health effects of physical inactivity, and tips on gradually increasing daily physical activity. During the speeches, participants were encouraged to achieve the goal of 10,000 steps per day, but goal achievement was not the purpose of the study. At the end of the intervention phase, final measurements were conducted, including the level of daily physical activity measure, the average daily number of steps, body composition, and Harvard Score.\u003c/p\u003e \u003cp\u003eFollow-up\u003c/p\u003e \u003cp\u003eThe follow-up assessments were conducted after 3 months of final measurements and included the level of daily physical activity measure and the average daily number of steps.\u003c/p\u003e \u003cp\u003eStatistical Methods\u003c/p\u003e \u003cp\u003eAll data were analyzed using IBM SPSS Statistics, version 28.0. Descriptive statistics were used to assess sample characteristics. The Shapiro-Wilk test was used to assess the consistency of the quantitative variable with a normal distribution. For the comparison of two related samples and quantitative variables, the t-test was performed, and for more than two measurements, the Friedman test or the analysis of variance for repeated measures was used (e.g., comparison of the level of daily physical activity measure and Steps values between each study phase). To determine which of the analyzed variables were predictors of the decrease/increase in the average daily number of steps (Steps), a logistic regression analysis was performed using the backward elimination method with maximum likelihood estimation. The model explained a total of 21.9% of the variance of the dependent variable (Cox and Snell R2\u0026thinsp;=\u0026thinsp;0.219) and was well fitted to the data, χ2 (8)\u0026thinsp;=\u0026thinsp;3.90; p\u0026thinsp;=\u0026thinsp;0.866 (Hosmer-Lemeshow test). Spearman\u0026rsquo;s rho correlation analysis determined the relationships between quantitative variables. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05.For all research, this must include a final section including details of ethical approval, informed consent and, where relevant registration.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eParticipant characteristic\u003c/p\u003e\n\u003cp\u003eA total of 106 professionally active Polish nurses were included in the study, and 71 completed all stages. One participant was excluded during the intervention due to a leg fracture, 11 were excluded due to upper respiratory tract infections, and 23 withdrew without reason. The detailed characteristics of the study participants are summarized in Table\u0026nbsp;1. Participants were predominantly middle-aged (mean 35.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.40 [years]), female (85.9%), residing in a city (91.5%), and had a master\u0026rsquo;s degree (59.2%) without clinical specialization (69%). Most of the participants were employed in hospital settings (90.1%), working overtime (62%) on mixed shifts (81.7%). The average work experience of participants was 12.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.28 [years].\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"72.77227722772277%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. The detailed characteristics of the study participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistics:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003e\u003cem\u003eSociodemographic Variables:\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eSex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eWoman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e61 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eMan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e10 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eAge [years], M (\u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e35.65 (\u0026plusmn;10.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003ePlace of residence, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eCity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e65 (91.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eVillage to medium-sized town\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e6 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eProfessional activity related variables:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eBachelor of Nursing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e29 (40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eMaster of Nursing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e42 (59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eClinical Specialization, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e22 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e49 (69)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eManagement position, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e5 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e66 (93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eWorkplace, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eHospital Ward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e64 (90.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e7(9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eTotal monthly workload, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eFull-time work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e27 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eMore than full-time (full-time and overtime)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e44 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eShift type, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eDaily shift\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e13 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eRotating shift\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e58 (81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.77227722772277%\"\u003e\n \u003cp\u003eWork experience [years], M (\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22772277227723%\"\u003e\n \u003cp\u003e12.3(\u0026plusmn;9.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eM: Mean; \u0026plusmn; SD: Standard Deviation; Village to medium-sized town: \u0026lt;100,000 inhabitants; City: \u0026gt;100,000 inhabitants; City: \u0026gt;100,000 inhabitants; Daily shift: working during the day; Rotating shift: working both day and night shifts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePhysical activity before and after intervention\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in the Total Physical Activity Score (TPAS [MET]) assessed by IPAQ between study points, but a detailed analysis revealed significant differences in the Recreation domain [MET]. The follow-up recorded a higher value than the initial and final measurements. However, the differences between the initial and final measurements were not significant.\u003c/p\u003e\n\u003cp\u003eThe average daily number of steps (Steps) was significantly higher in the follow-up compared to the final measurement, but there were no differences between the initial and final measurements. The comparisons of the results of IPAQ and Steps between each study phase are presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison the results of IPAQ and Steps between each study phase.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eInitial measurement (n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFinal measurement (n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFollow-up (n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026chi;2/F\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIPAQ: Total Physical Activity Score [MET]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30916.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25104.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20762.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26395.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20704.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14222.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25840.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23970.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9053.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIPAQ: Occupational activity [MET]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19102.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14652.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14214.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15943.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12264.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10346.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16099.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15015.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6166.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIPAQ: Active locomotion [MET]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4926.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2772.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4989.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3637.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2916.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2638.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3838.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3465.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2605.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIPAQ: Domestic chores [MET]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4640.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3480.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4649.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4640.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4020.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3532.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3647.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3360.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2051.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIPAQ: Recreation [MET]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2246.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e792.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3514.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2165.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1371.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3046.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2240.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1554.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2196.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSteps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7267.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7571.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2066.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7107.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6985.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1763.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7764.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8268.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1571.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\"\u003eM: Mean; \u0026plusmn; SD: Standard Deviation; IPAQ: International Physical Activity Questionnaire; Steps: An average daily number of steps; p: p-value.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003eThe trend analysis of the Step number revealed that the average daily number of steps was similar during each of the 30 days of the intervention. A slight decrease from the average was observed on the 6th, 14th, 17th, and 20th day of the study, while a higher activity level was observed on the 25th day of the study. The trend of the daily number of steps is presented in Fig. 2.\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;2. The trend of the daily number of steps during the intervention phase.\u003c/p\u003e\n\u003cp\u003eBody composition and cardiovascular disease risk before and after intervention\u003c/p\u003e\n\u003cp\u003eThe study revealed a significant decrease in Body Mass Index and the absolute value of Fat Mass at [kg] in the final measurement compared to the initial measurement (t\u0026thinsp;=\u0026thinsp;2.09; p\u0026thinsp;=\u0026thinsp;0.04 and t\u0026thinsp;=\u0026thinsp;2.22; p\u0026thinsp;=\u0026thinsp;0.03, respectively). The comparisons of the results of blood pressure, body composition, and Harvard Score between each study phase are summarized in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\" style=\"margin-right: calc(0%); width: 100%;\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparisons the results of blood pressure, body composition and Harvard Score between each study phase\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 5.6912%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" style=\"width: 8.9227%;\"\u003e\n \u003cp\u003eInitial measurement\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" style=\"width: 8.6333%;\"\u003e\n \u003cp\u003eFinal measurement\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 2.6527%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" style=\"width: 2.8456%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" style=\"width: 4.9195%;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 0.1929%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 5.6912%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.3536%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.5691%;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.1607%;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.4726%;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.8456%;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003eLL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.2668%;\"\u003e\n \u003cp\u003eUL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 4.2443%;\"\u003e\n \u003cp\u003eCohens d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 5.6912%;\"\u003e\n \u003cp\u003eDBP [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.3536%;\"\u003e\n \u003cp\u003e75.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.5691%;\"\u003e\n \u003cp\u003e7.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.1607%;\"\u003e\n \u003cp\u003e75.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.4726%;\"\u003e\n \u003cp\u003e7.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.8456%;\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.2668%;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 4.2443%;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 5.6912%;\"\u003e\n \u003cp\u003eSBP [mmHg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.3536%;\"\u003e\n \u003cp\u003e119.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.5691%;\"\u003e\n \u003cp\u003e9.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.1607%;\"\u003e\n \u003cp\u003e119.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.4726%;\"\u003e\n \u003cp\u003e8.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.8456%;\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e-1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.2668%;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 4.2443%;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 5.6912%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.3536%;\"\u003e\n \u003cp\u003e24.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.5691%;\"\u003e\n \u003cp\u003e4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.1607%;\"\u003e\n \u003cp\u003e24.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.4726%;\"\u003e\n \u003cp\u003e4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.8456%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.040\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.2668%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 4.2443%;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 5.6912%;\"\u003e\n \u003cp\u003eFat [kg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.3536%;\"\u003e\n \u003cp\u003e19.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.5691%;\"\u003e\n \u003cp\u003e8.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.1607%;\"\u003e\n \u003cp\u003e19.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.4726%;\"\u003e\n \u003cp\u003e8.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.8456%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.2668%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 4.2443%;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 5.6912%;\"\u003e\n \u003cp\u003eFFM [kg]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.3536%;\"\u003e\n \u003cp\u003e49.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.5691%;\"\u003e\n \u003cp\u003e8.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.1607%;\"\u003e\n \u003cp\u003e50.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 3.4726%;\"\u003e\n \u003cp\u003e9.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e-1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.8456%;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 2.6527%;\"\u003e\n \u003cp\u003e-1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 2.2668%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 4.2443%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 38.5362%;\"\u003eM: Mean; \u0026plusmn; SD: Standard Deviation; t: t-test; p: p-value; DBP: Diastolic Blood Pressure; SBP: Systolic Blood Pressure; BMI: Body Mass Index; Fat[kg]: absolute value of Fat mass; FFM [kg]: absolute value of Free Fat Mass\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003eFactors influencing the increase in the average daily number of steps after the intervention were examined in the present study. The results showed that 43.7% of participants had increased the Steps number at the final measure and 63.4% at the follow-up. Logistic regression analysis revealed that the odds for an increase in the Steps number decreased with higher systolic blood pressure (SBP) [mmHg] (OR\u0026thinsp;=\u0026thinsp;0.92; 95% CI\u0026thinsp;=\u0026thinsp;0.85-1.00) and with working in a hospital ward (OR\u0026thinsp;=\u0026thinsp;0.002; 95% CI\u0026thinsp;=\u0026thinsp;0.00-0.41). On the other hand, the odds for an increase in the Steps number increased with a higher Harvard Score (OR\u0026thinsp;=\u0026thinsp;6.025; 95% CI\u0026thinsp;=\u0026thinsp;1.70-21.41) and Free Fat Mass (FFM) [kg] (OR\u0026thinsp;=\u0026thinsp;1.451; 95% CI\u0026thinsp;=\u0026thinsp;1.07\u0026ndash;1.96) measures. None of the other variables, including sociodemographic, vocational, or health-related factors, were significant predictors of an increase or decrease in the participants\u0026rsquo; number of steps.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe intervention implemented in the study did not influence the Total Physical Activity Score (TPAS [MET]) assessed by IPAQ, but a detailed analysis revealed a significant increase in the Recreation domain [MET], where a significantly higher value was recorded in the follow-up compared to the initial and final measurements. Furthermore, the average daily number of steps was significantly higher in the follow-up compared to the final measurement, suggesting that the intervention had a long-lasting effect that persisted after the completion of the intervention phase. This finding is inconsistent with previous studies that reported short-lived increases in physical activity after web-based interventions providing feedback and physical activity challenges (33). The results suggest that other motivation methods, such as health coaching, should enhance interventions with feedback and physical activity challenges (22). The good match of health coaching applied in the present study, which occurred just after the decrease in the daily number of steps, supports this hypothesis. Drawing on evidence-based behavior change techniques, such as coaching, social support, feedback, barrier identification, follow-up prompts, and health checks may help reinforce long-term physical activity changes (34).\u003c/p\u003e \u003cp\u003eOur findings suggest that the Recreation domain of daily physical activity is the most susceptible to change. This aligns with our previous research, which demonstrated that nurses who are more motivated to be active engagement in a higher level of leisure-time physical activity than those who are less motivated (20). Research has also shown that engaging in moderate- to vigorous-intensity physical activity before a morning shift is associated with increased sedentary time and decreased physical activity during work hours (35). Henwood et al. found that nurses who engaged in \u0026ge;\u0026thinsp;30 minutes/day of moderate workplace activity were not healthier than those who found the same amount of physical activity during their leisure time. They concluded that workplace activity does not positively affect health and well-being (36). Parker et al. suggested that occupational physical activity may not provide the same health benefits as leisure-time physical activity for nurses (37). Furthermore, Richard et al. reported that leisure-time physical activity is inversely associated with all-cause mortality, whereas occupational physical activity does not have clear associations (38). These observations support the effectiveness of intervention programs that promote physical activity, particularly in the leisure-time domain, which is most recommended for health benefits. Providing sufficient time for recovery after work and ensuring compliance with ergonomic principles are crucial to enable nurses to engage in leisure-time physical activity. Our study also revealed a significant change in participants\u0026rsquo; Body Mass Index, which may indicate that the motivational strategies employed during the intervention phase influenced other healthy behaviors besides physical activity. Other studies have also confirmed the effectiveness of health coaching in promoting behavior changes for improved health, including body weight loss, increased physical activity, mental health status, enhanced medication adherence, better social support, and improved physical health status, including HbA1c. Health coaching is also a low-cost tool (39).\u003c/p\u003e \u003cp\u003eThe presented study identified several factors predisposing individuals to increase their daily number of steps. Participants with higher Harvard Scores were likelier to increase their Steps number, which contradicts the belief that fear arousal induced by threat (future punishment) is likely counterproductive when self-efficacy is low (23). This suggests that nurses with higher knowledge about the consequences of chronic diseases may be more motivated to change their health behaviors because of the fear of threat (future punishment), such as the 5-year risk of cardiovascular events. Conversely, participants with higher Free Fat Mass [kg] are more vulnerable to applied motivation, suggesting that naturally active individuals in good physical condition are more willing to engage in physical activity. Nurses who agree that physical activity positively affects their mental and physical condition were more motivated to engage in physical activity and showed a higher level of leisure-time physical activity (20). However, working in a hospital ward harmed the increase in the number of steps after the applied intervention. Although the type of hospital ward was not distinguished in the study, other research has shown that the average number of steps and distance traveled was greatest for nurses working in the emergency room, followed by the intensive care unit, surgical ward, and medical ward (40). Working in a hospital ward and engaging in direct patient care is considered the most demanding (35,41), and nurses not involved in direct patient care are more sedentary (41). Nurses working in rotating shifts showed a significantly higher level of general physical activity than nurses working only in daily shifts (20,42). Furthermore, nurses who are highly active during work hours are less likely to engage in leisure-time physical activity, as confirmed by Chappel et al., who revealed that occupational walking time was associated with lower activity levels during leisure time (35). Although working in a hospital ward is difficult to modify, ensuring appropriate time for recovery and compliance with ergonomic principles is necessary to enable nurses to increase their leisure-time physical activity.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eOne limitation of the presented study is the possibility that participants may have adopted a healthier lifestyle during the observation period than they normally would have, knowing that their physical activity was being recorded. Therefore, an observer effect cannot be ruled out, a common limitation in similar studies (43). Another limitation is self-selection, meaning nurses not interested in increasing their physical activity may have chosen not to participate in the study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eTo reinforce long-term changes in nurses\u0026rsquo; physical activity, mixed methods should be employed. Feedback and physical activity challenges should be supplemented by other motivational techniques, such as health coaching, effectively promoting behavior changes for improved health. It should be highly recommended because leisure-time physical activity is the most susceptible to change according to motivational techniques. Participants with higher Harvard Scores were more likely to increase their daily number of steps; therefore, regular evaluation of this indicator among nurses is warranted. Working in a hospital ward had the most negative impact on increasing the daily number of steps, and this factor is difficult to modify. Therefore, ensuring appropriate time for recovery and compliance with ergonomic principles is necessary to enable nurses to increase their leisure-time physical activity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and was approved by Ethics Committee of Medical University of Warsaw (reference number: AK-BE/163/2020). Informed consent was obtained from all participants of the study.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from\u003c/p\u003e\n\u003cp\u003ethe corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eNo conflict of interest has been declared by the author(s).\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research was as part of the project (grant number: MB/Z/10) implemented from 2020 to 2022 and financed by a subsidy allocated to science from the Medical University of Warsaw.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eAgnieszka Nerek: Conceptualization, Data curation, Investigation, Methodology, Writing an original draft; Katarzyna Wesołowska-G\u0026oacute;rniak: Conceptualization, Funding acquisition, Methodology, Project administration, Writing an original draft, Writing - review and editing; Bożena Czarkowska-Pączek: Conceptualization, Methodology, Project administration, Supervision, Writing\u0026mdash;review and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe are grateful to the nurses who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWarburton DER, Bredin SSD. 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Bidirectional associations between emergency nurses\u0026apos; occupational and leisure physical activity: An observational study. J Sports Sci. 2021;39(6):705-13. https://doi.org/10.1080/02640414.2020.1841921\u003c/li\u003e\n\u003cli\u003eHenwood T, Tuckett A, Turner C. What makes a healthier nurse, workplace or leisure physical activity? Informed by the Australian and New Zealand e-Cohort Study. J Clin Nurs. 2012;21(11-12):1746-54. https://doi.org/10.1111/j.1365-2702.2011.03994.x \u003c/li\u003e\n\u003cli\u003eParker HM, Gallagher R, Duffield C, Ding D, Sibbritt D, Perry L. Occupational and Leisure-Time Physical Activity Have Different Relationships With Health: A Cross-Sectional Survey Study of Working Nurses. J Phys Act Health. 2021;18(12):1495-502. https://doi.org/10.1123/jpah.2020-0415 \u003c/li\u003e\n\u003cli\u003eRichard A, Martin B, Wanner M, Eichholzer M, Rohrmann S. Effects of leisure-time and occupational physical activity on total mortality risk in NHANES III according to sex, ethnicity, central obesity, and age. J Phys Act Health. 2015;12(2):184-92. https://doi.org/10.1123/jpah.2013-0198\u003c/li\u003e\n\u003cli\u003eMalecki HL, Gollie JM, Scholten J. Physical Activity, Exercise, Whole Health, and Integrative Health Coaching. Phys Med Rehabil Clin N Am. 2020;31(4):649-63. https://doi.org/10.1016/j.pmr.2020.06.001\u003c/li\u003e\n\u003cli\u003eChang HE, Cho SH. Nurses\u0026apos; steps, distance traveled, and perceived physical demands in a three-shift schedule. Hum Resour Health. 2022;20(1):72. https://doi.org/10.1186/s12960-022-00768-3\u003c/li\u003e\n\u003cli\u003eRoss A, Yang L, Wehrlen L, Perez A, Farmer N, Bevans M. Nurses and health-promoting self-care: Do we practice what we preach? J Nurs Manag. 2019;27(3):599-608. https://doi.org/10.1111/jonm.12718\u003c/li\u003e\n\u003cli\u003ePeplonska B, Bukowska A, Sobala W. Rotating night shift work and physical activity of nurses and midwives in the cross-sectional study in Ł\u0026oacute;dź, Poland. Chronobiol Int. 2014;31(10):1152-9. https://doi.org/10.3109/07420528.2014.957296\u003c/li\u003e\n\u003cli\u003eRoskoden FC, Kr\u0026uuml;ger J, Vogt LJ, G\u0026auml;rtner S, Hannich HJ, Steveling A, et al. Physical Activity, Energy Expenditure, Nutritional Habits, Quality of Sleep and Stress Levels in Shift-Working Health Care Personnel. PLoS One. 2017;12(1):e0169983. https://doi.org/10.1371/journal.pone.0169983\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Daily Number of Steps, Health Coaching, Health-promoting Behaviours, Long-Term Changes, Nursing Staff, Physical Activity","lastPublishedDoi":"10.21203/rs.3.rs-2934300/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2934300/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAlthough knowledge of the barriers and motivators to physical activity participation among nurses is increasing, the factors influencing motivation methods’ effectiveness are not completely defined. This study aimed to identify the sociodemographic, occupational, and health-related factors that influence the effectiveness of motivation methods in increasing the level of daily physical activity among nurses\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis study was based on an intervention study protocol. All registered nurses in clinical settings were invited to participate in the study.\u003c/p\u003e\n\u003cp\u003eThe study involved 71 professionally active nurses. A self-reported questionnaire was used to collect sociodemographic and employment data. The level of physical activity was assessed using the International Physical Activity Questionnaire, and the daily number of steps was assessed using a pedometer. Body composition was measured using a bioimpedance method, and the 5-year risk of cardiovascular events was assessed using the Harvard Score. The intervention included self-monitoring daily steps using a pedometer and completing a diary daily for one month. Additionally, a few-minute speech was sent to each participant via email on the intervention’s 7th, 14th, and 21st days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe analysis revealed a higher value of physical activity recorded in the follow-up compared to the initial and final measurement in the Recreation domain [Met] (p \u0026lt; 0.001) and a higher value of daily steps in the follow-up compared to the final measurement (p = 0.005). Participants with a higher Harvard Score were more likely to increase their daily number of steps (OR = 6.025; 95% CI = 1.70-21.41), and nurses working in hospital wards were less likely to do so (OR = 0.002; 95% CI = 0.00-0.41).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eRecommendations for physical activity in the nursing population should focus on increasing leisure time physical activity and regular risk assessment of cardiovascular events. A mixed methods approach, such as feedback enhanced by health coaching, effectively achieves long-term physical activity changes in nurses.\u003c/p\u003e","manuscriptTitle":"Enhancing feedback by health coaching: The Effectiveness of Mixed Methods Approach to Long-Term Physical Activity Changes in Nurses. 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