The Effect of a Mobile Application-Based Work Scheduling Program on the Perceived Quality of Work Life Among Operating Room Nurses in a Tertiary Hospital

Main Article Content

Sataya Panthuen
Phechnoy Singchungchai
Netchanok Sritoomma

Abstract

Introduction: This quasi-experimental study employed a two-group pretest–posttest design with non-random allocation of the experimental and control groups at the hospital level. It compared perceived quality of work life among operating room nurses between a group receiving a mobile application-based scheduling program and a control group and compared pretest and posttest scores within the experimental group. Materials and methods: The sample consisted of 42 operating room nurses from two hospitals, selected through purposive sampling, with 21 nurses in each group. The research instruments were the mobile application-based scheduling program and a perceived quality of work life questionnaire (S-CVI/Ave = .86; Cronbach's alpha = .91). Data were analyzed using independent-samples and paired-samples t-tests, with the level of statistical significance set at .05. Results: The results showed that, after receiving the program, the experimental group had an overall quality of work life score at a high level ( equation = 4.04, SD = .13), significantly higher than the control group, which was at a moderate level ( equation = 3.39, SD = .20), and significantly higher than its own pre-intervention score ( equation = 3.29, SD = .34), with a between-group mean difference of 0.65 (95% CI 0.55–0.76, Cohen’s d = 3.97) and a within-group pre-post mean difference of 0.76 (95% CI 0.61–0.90, Cohen’s dz = 2.31). Conclusion: These preliminary findings therefore suggest that the program may be associated with enhanced quality of work life among operating room nurses. However, because allocation was conducted at the hospital level with only one hospital per group, the results cannot yet fully separate the program’s effect from institution-specific factors. Nursing administrators may therefore consider applying this approach in settings with similar contexts and further evaluating its outcomes before wider implementation.

Downloads

Download data is not yet available.

Article Details

How to Cite
1.
Panthuen S, Singchungchai P, Sritoomma N. The Effect of a Mobile Application-Based Work Scheduling Program on the Perceived Quality of Work Life Among Operating Room Nurses in a Tertiary Hospital. RTA Med. J. [internet]. 2026 Sep. 30 [cited 2026 Oct. 19];79(3):255-73. available from: https://he02.tci-thaijo.org/index.php/rtamedj/article/view/284176
Section
Original Article

References

World Health Organization. State of the world’s nursing 2025: investing in education, jobs, leadership and service delivery. Geneva: World Health Organization; 2025.

Shin S, Park JH, Bae SH. Nurse staffing and nurse outcomes: a systematic review and meta-analysis. Nurs Outlook. 2018;66(3):273-82. doi:10.1016/j.outlook.2017.12.002.

Lasater KB, Muir KJ, Sloane DM, McHugh MD, Aiken LH. Alternative models of nurse staffing may be dangerous in high-stakes hospital care. Med Care. 2024;62(7):434-40. doi:10.1097/MLR.0000000000001990.

TCIJ Editorial Board. [Rocket Media Lab: Thailand’s nursing crisis: understaffing, heavy workloads, high resignation rates, and insufficient numbers of newly trained nurses] [Internet]. Chiang Mai: Thai Civil Rights and Investigative Journalism; 2026 Apr 3 [cited 2026 Jul 17]. Available from: https://www.tcijthai.com/news/2026/4/scoop/14965. Thai.

Dall’Ora C, Ball J, Recio-Saucedo A, Griffiths P. Characteristics of shift work and their impact on employee performance and wellbeing: a literature review. Int J Nurs Stud. 2016;57:12-27. doi:10.1016/j.ijnurstu.2016.01.007.

Li Y, Xiang D, Jiang Y, Gu S. Understanding burnout among operating room nurses: a qualitative study. Front Public Health. 2025;13:1604631. doi:10.3389/fpubh.2025.1604631.

Association of periOperative Registered Nurses. Guidelines for perioperative practice. Denver (CO): AORN, Inc.; 2021.

Brooks BA, Anderson MA. Defining quality of nursing work life. Nurs Econ. 2005;23(6):319-26, 279.

Bureau of Digital Health, Office of the Permanent Secretary, Ministry of Public Health. [Smart hospital assessment manual for fiscal year 2026]. Nonthaburi: Office of the Permanent Secretary, Ministry of Public Health; 2026. Thai.

Epstein M, Arakelian E, Tucker P, Dahlgren A. Managing sustainable working hours within participatory working time scheduling for nurses and assistant nurses: a qualitative interview study with managers and staffing assistants. J Nurs Manag. 2023;2023:8096034. doi:10.1155/2023/8096034.

Sinprasit P. [The development of nursing staffing in internal medicine unit using smartphone application, Somdech Phra Pinklao Hospital] [master’s thesis]. Bangkok: Chulalongkorn University; 2023. doi:10.58837/CHULA.THE.2023.158.Thai.

Aksu M, Dinç L. Designing and piloting a mobile application for fair and objective nurse scheduling: a design-based study. BMC Nurs. 2025;24:784. doi:10.1186/s12912-025-03370-9.

Inchingolo AD, Inchingolo AM, Fatone MC, Ferrante L, Casamassima L, Trilli I, et al. Guidelines for reducing the adverse effects of shift work on nursing staff: a systematic review. Healthcare (Basel). 2025;13(17):2148. doi:10.3390/healthcare13172148.

Dall’Ora C, Saville C, Rubbo B, Turner L, Jones J, Griffiths P. Nurse staffing levels and patient outcomes: a systematic review of longitudinal studies. Int J Nurs Stud. 2022;134:104311. doi:10.1016/j.ijnurstu.2022.104311.

Bärnighausen T, Røttingen JA, Rockers P, Shemilt I, Tugwell P. Quasi-experimental study designs series-paper 1: introduction: two historical lineages. J Clin Epidemiol. 2017;89:4-11. doi:10.1016/j.jclinepi.2017.02.020.

Shadish WR, Cook TD, Campbell DT. Experimental and quasi-experimental designs for generalized causal inference. Boston (MA): Houghton Mifflin; 2002.

Whiting-O’Keefe QE, Henke C, Simborg DW. Choosing the correct unit of analysis in medical care experiments. Med Care. 1984;22(12):1101-14. doi:10.1097/00005650-198412000-00005.

Donner A, Klar N. Design and analysis of cluster randomization trials in health research. London: Arnold; 2000.

Reeves BC, Wells GA, Waddington H. Quasi-experimental study designs series-paper 5: a checklist for classifying studies evaluating the effects on health interventions-a taxonomy without labels. J Clin Epidemiol. 2017;89:30-42. doi:10.1016/j.jclinepi.2017.02.016.

Haynes AB, Haukoos JS, Dimick JB. TREND reporting guidelines for nonrandomized/quasi-experimental study designs. JAMA Surg. 2021;156(9):879-80. doi:10.1001/jamasurg.2021.0552.

Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149-60. doi:10.3758/BRM.41.4.1149.

Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates; 1988.

Gupta KK, Attri JP, Singh A, Kaur H, Kaur G. Basic concepts for sample size calculation: critical step for any clinical trials! Saudi J Anaesth. 2016;10(3):328-31. doi:10.4103/1658-354X.174918.

Thailand Nursing and Midwifery Council. [Announcement of the Thailand Nursing and Midwifery Council on the policy on nurses’ working hours for patient safety]. Bangkok: Thailand Nursing and Midwifery Council; 2017. Thai.

Nursing Division, Office of the Permanent Secretary, Ministry of Public Health. [Standards and quality assessment of perioperative nursing services]. Nonthaburi: Nursing Division, Office of the Permanent Secretary, Ministry of Public Health; 2025. Thai.

Likert R. A technique for the measurement of attitudes. Arch Psychol. 1932;22(140):1-55.

Best JW, Kahn JV. Research in education. 10th ed. Harlow (UK): Pearson Education Limited; 2014.

Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health. 2007;30(4):459-67. doi:10.1002/nur.20199.

Killip S, Mahfoud Z, Pearce K. What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. Ann Fam Med. 2004;2(3):204-8. doi:10.1370/afm.141.

Leyrat C, Morgan KE, Leurent B, Kahan BC. Cluster randomized trials with a small number of clusters: which analyses should be used? Int J Epidemiol. 2018;47(1):321-31. doi:10.1093/ije/dyx169.

Adams G, Gulliford MC, Ukoumunne OC, Eldridge S, Chinn S, Campbell MJ. Patterns of intra-cluster correlation from primary care research to inform study design and analysis. J Clin Epidemiol. 2004;57(8):785-94. doi:10.1016/j.jclinepi.2003.12.013.

Shiri R, Karhula K, Turunen J, Koskinen A, Ropponen A, Ervasti J, et al. The effect of using participatory working time scheduling software on employee well-being and workability: a cohort study analysed as a pseudo-experiment. Healthcare (Basel). 2021;9(10):1385. doi:10.3390/healthcare9101385.

Gerlach M, Renggli FJ, Bieri JS, Sariyar M, Golz C. Exploring nurse perspectives on AI-based shift scheduling for fairness, transparency, and work-life balance. BMC Nurs. 2025;24:1161. doi:10.1186/s12912-025-03808-0.

Peršolja M. Effects of nurses’ schedule characteristics on fatigue: an integrative review. Nurs Manage. 2023;54(4):28-37. doi:10.1097/01.NUMA.0000921904.11222.11.