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Adaptation and Psychometric Evaluation of the Turkish Version of the Reflective Smartphone Disengagement Scale for Nursing Students

*Nehir Yasan Ak orcid  -  Department of Management Information Systems, Faculty of Social Sciences and Humanities, Akdeniz University, Antalya, Türkiye, Turkey
Kerime Bademli orcid  -  Department of Psychiatric Nursing, Faculty of Nursing, Akdeniz University, Antalya, Türkiye, Turkey
Open Access Copyright (c) 2025 by the Authors, Published by Department of Nursing, Faculty of Medicine, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

Background: Problematic smartphone use among nursing students has been linked to impaired learning and professional performance. While previous research has primarily focused on addictive or compulsive smartphone use, limited attention has been paid to individuals’ intentional and reflective efforts to regulate their smartphone use. Moreover, no validated instrument exists to assess reflective smartphone disengagement among nursing students in the Turkish context.

Purpose: This study aimed to adapt and validate the Turkish version of the Reflective Smartphone Disengagement Scale among undergraduate nursing students.

Methods: A descriptive, cross-sectional design was employed at a nursing faculty in a public university in the southern region of Türkiye. Using convenience sampling, the study included 376 undergraduate nursing students from all grade levels who owned a smartphone and consented to participate. Sample size adequacy was supported by recommended item-to-participant ratios and an acceptable KMO value. Data were collected using a personal information form, the Reflective Smartphone Disengagement Scale, and the Nomophobia Questionnaire. Face, content, construct, and criterion validity procedures were applied for scale adaptation.

Results: Exploratory Factor Analysis (EFA) revealed that the Turkish version of the Reflective Smartphone Disengagement Scale has a two-factor structure with six items, comprising usage moderation (items related to limiting smartphone use across specific times, places, situations, and life balance) and availability management (items related to controlling reachability and intentional disconnection). Internal consistency was acceptable, with Cronbach’s alpha coefficients of .70 and .81, respectively. Confirmatory Factor Analysis indicated a good model fit (CFI = .97, RMSEA = .08).

Conclusion: The Turkish version of the Reflective Smartphone Disengagement Scale is a valid and reliable tool for assessing nursing students’ conscious efforts to manage smartphone use and can be utilized in nursing education to identify students’ self-regulatory behaviors and inform interventions aimed at promoting healthy smartphone use in academic and clinical settings.

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Keywords: Nursing students; psychometrics; scale adaptation; scale validation; smartphone disengagement

Article Metrics:

  1. Al-Balhan, E. M., Khabbache, H., Watfa, A., Re, T. S., Zerbetto, R., & Bragazzi, N. L. (2018)
  2. Psychometric evaluation of the Arabic version of the nomophobia questionnaire: Confirmatory and exploratory factor analysis–implications from a pilot study in Kuwait among university students. Psychology Research and Behavior Management, 471-482. https://doi.org/10.2147/PRBM.S169918
  3. Allen, M. S., Robson, D. A., & Iliescu, D. (2023). Face Validity: A Critical but Ignored
  4. Component of Scale Construction in Psychological Assessment. European Journal of
  5. Psychological Assessment, 39(3), 153–156. https://doi.org/10.1027/1015-5759/a000777
  6. Andrew, D. P. S., Pedersen, P. M., & McEvoy, C. D. (2011). Research methods in sport
  7. management. Champaign: Human Kinetics
  8. Augner, C., Vlasak, T., Aichhorn, W., & Barth, A. (2023). The association between problematic
  9. smartphone use and symptoms of anxiety and depression—a meta-analysis. Journal of Public Health, 45(1), 193-201. https://doi.org/10.1093/pubmed/fdab350
  10. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory
  11. Prentice-Hall
  12. Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and
  13. Human Decision Processes, 50(2), 248–287. https://doi.org/10.1016/07495978(91)90022-L
  14. Baumeister, R. F., & Vohs, K. D. (Eds.). (2004). Handbook of self-regulation: Research, theory,
  15. and applications. Guilford Press
  16. Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000). Guidelines for the process
  17. of cross-cultural adaptation of self-report measures. Spine, 25(24), 3186–3191. https://doi.org/10.1097/00007632-200012150-00014
  18. Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L
  19. (2018). Best practices for developing and validating scales for health, social, and
  20. behavioral research: A primer. Frontiers in Public Health, 6, 149
  21. https://doi.org/10.3389/fpubh.2018.00149
  22. Bruton, A., Conway, J. H., & Holgate, S. T. (2000). Reliability: what is it, and how is it
  23. measured? Physiotherapy, 86(2), 94-99. https://doi.org/10.1016/S0031-9406(05)61211-4
  24. Busch, P. A., & McCarthy, S. (2021). Antecedents and consequences of problematic
  25. smartphone use: A systematic literature review of an emerging research area
  26. Computers in Human Behavior, 114, 106414. https://doi.org/10.1016/j.chb.2020.106414
  27. Chen, Y., Yu, Y., & Zhu, K. (2023). Analysis of Smartphone Addiction Today: A Literature Review. Journal of Education, Humanities and Social Sciences, 8, 921-927. https://doi.org/10.54097/ehss.v8i.4382
  28. Cho, S., & Lee, E. (2015). Development of a brief instrument to measure smartphone addiction among nursing students. CIN: Computers, Informatics, Nursing, 33(5), 216-224. https://doi.org/10.1097/CIN.0000000000000132
  29. Cho, S., & Lee, E. (2016). Distraction by smartphone use during clinical practice and opinions about smartphone restriction policies: A cross-sectional descriptive study of nursing students. Nurse Education Today, 40, 128-133. https://doi.org/10.1016/j.nedt.2016.02.021
  30. Caner-Yıldırım, S., & Yıldırım, Z. (2022). Psychometric properties of Turkish version of
  31. generalized problematic internet use scale-2 and the relationship between internet use patterns and problematic internet use. International Journal of Mental Health and Addiction, 1-23. https://doi.org/10.1007/s11469-022-00819-9
  32. Carmines, E.G. & Zeller, R.A. (1979). Reliability and Validity assessment. Sage. Beverly Hills,
  33. CA
  34. Cohen, R. J., & Swerdlik, M. E. (2018). Psychological testing and assessment: An introduction to tests and measurement (9th ed.). McGraw Hill
  35. Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Practical Assessment Research and Evaluation, 10(7). https://doi.org/10.7275/jyj1-4868
  36. Creswell, J.W. (2012). Education research planning conducting and evaluating quantitative
  37. and qualitative research. Pearson Education
  38. Cudeck, R., & Browne, M. W. (1983). Cross-validation of covariance structures. Multivariate Behavioral Research, 18(2), 147-167. https://doi.org/10.1207/s15327906mbr1802_2
  39. Davis, L. L. (1992). Instrument review: Getting the most from a panel of experts. Applied Nursing Research, 5(4), 194–197. https://doi.org/10.1016/S0897-1897(05)80008-4
  40. Dennison, L., Morrison, L., Conway, G., & Yardley, L. (2013). Opportunities and challenges
  41. for smartphone applications in supporting health behavior change: Qualitative study. Journal of Medical Internet Research, 15(4), 25-83. https://doi.org/10.2196/jmir.2583
  42. Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the
  43. pervasive problem of internal consistency estimation. British Journal of Psychology,
  44. (3), 399–412. https://doi.org/10.1111/bjop.12046
  45. Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use
  46. of exploratory factor analysis in psychological research. Psychological Methods,
  47. (3), 272–299. https://doi.org/10.1037/1082-989X.4.3.272
  48. Fink, A. (2010). Survey research methods. In P. Peterson, E. Baker & B. McGaw(Editors) International Encyclopedia of Education (3rd ed). (pp. 152–160). Amsterdam: Elsevier. https://doi.org/10.1016/B978-0-08-044894-7.00296-7
  49. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with
  50. unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  51. Gao, Y., Dai, H., Jia, G., Liang, C., Tong, T., Zhang, Z., ... & Zhu, Y. (2020). Translation of the
  52. Chinese version of the nomophobia questionnaire and its validation among college students: factor analysis. JMIR mHealth and uHealth, 8(3), e13561. https://doi.org/10.2196/13561
  53. Gomez, R., Brown, T., Watson, S., & Stavropoulos, V. (2022). Confirmatory factor analysis
  54. and exploratory structural equation modeling of the factor structure of the Questionnaire of Cognitive and Affective Empathy (QCAE). PloS one, 17(2), e0261914. https://doi.org/10.1371/journal.pone.0261914
  55. Gutiérrez-Puertas, L., Márquez-Hernández, V. V., & Aguilera-Manrique, G. (2016). Adaptation
  56. and validation of the Spanish version of the nomophobia questionnaire in nursing studies. CIN: Computers, Informatics, Nursing, 34(10), 470-475. https://doi.org/10.1097/CIN.0000000000000268
  57. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis. Cengage
  58. Hayes, A. F., & Coutts, J. J. (2020). Use omega rather than Cronbach’s alpha for estimating
  59. reliability. Communication Methods and Measures, 14(1), 1–24. https://doi.org/10.1080/19312458.2020.1718629
  60. Higher Education Council. (2024). Yükseköğretim Program Atlası (YÖK Atlas) 2024. Yükseköğretim Kurulu. https://yokatlas.yok.gov.tr/
  61. Horwood, S., & Anglim, J. (2019). Problematic smartphone usage and subjective and psychological well-being. Computers in Human Behavior, 97, 44-50. https://doi.org/10.1016/j.chb.2019.02.028
  62. Hu, L. H. & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1), 1-15. https://doi.org/10.1080/10705519909540118
  63. Kırca, K., & Kutlutürkan, S. (2019). Hemşirelik öğrencilerinin akıllı telefon bağımlılık düzeylerinin iletişim becerilerine etkisi. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi, 5(2), 81-85
  64. Kline, R. B. (2011). Convergence of structural equation modeling and multilevel modeling. The
  65. SAGE handbook of innovation in social research methods, 562-589. http://journals.sagepub.com/doi/pdf/10.4135/9781446268261.n31
  66. Lin, Y. H., Lin, Y. C., Lin, S. H., Lee, Y. H., Lin, P. H., Chiang, C. L., ... & Kuo, T. B. J
  67. (2017).To use or not to use? Compulsive behavior and its role in smartphone addiction. Translational Psychiatry, 7(2), e1030-e1030. https://doi.org/10.1038/tp.2017.1
  68. Lukoff, K., Yu, C., Kientz, J., & Hiniker, A. (2018). What makes smartphone use meaningful
  69. or meaningless? Proceedings of the ACM on Interactive, Mobile, Wearable and
  70. Ubiquitous Technologies, 2(1), 1-26. https://doi.org/10.1145/3191754
  71. Ma, J., & Liu, C. (2021). Evaluation of the factor structure of the Chinese version of the
  72. nomophobia questionnaire. Current Psychology, 40, 1367-1373. https://doi.org/10.1007/s12144-018-0071-9
  73. Matthes, J., Karsay, K., Hirsch, M., Stevic, A., & Schmuck, D. (2022). Reflective
  74. smartphone disengagement: Conceptualization, measurement, and validation. Computers in Human Behavior, 128, 107078. https://doi.org/10.1016/j.chb.2021.107078
  75. Matthes, J., Stevic, A., Koban, K., Thomas, M. F., Forrai, M., & Karsay, K. (2023). Fear of Missing Out, Reflective Smartphone Disengagement, and Loneliness in Late Adolescents. Cyberpsychology, Behavior, and Social Networking, 26(10), 731-738. https://doi.org/10.1089/cyber.2023.0014
  76. McNeish, D. (2018). Thanks coefficient alpha, we’ll take it from here. Psychological Methods,
  77. (3), 412–433. https://doi.org/10.1037/met0000144
  78. Meier, A., & Reinecke, L. (2021). Computer-mediated communication, social media, and mental health: A conceptual and empirical meta-review. Communication Research, 48(8), 1182-1209. https://doi.org/10.1177/0093650220958224
  79. Merenda, P. F. (2006). An overview of adapting educational and psychological assessment instruments: Past and present. Psychological Reports, 99, 307–314. https://doi.org/10.2466/pr0.99.2.307-314
  80. Olson, J. A., Veissière, S. P. L., Sandra, D. A., Chmoulevitch, D., & Raz, A. (2023). A nudge-based intervention to reduce problematic smartphone use: Randomised controlled trial. International Journal of Mental Health and Addiction, 21, 3842–3864. https://doi.org/10.1007/s11469-022-00826-w
  81. Osorio-Molina, C., Martos-Cabrera, M. B., Membrive-Jiménez, M. J., Vargas-Roman, K., Suleiman-Martos, N., Ortega-Campos, E., & Gómez-Urquiza, J. L. (2021). Smartphone addiction, risk factors and its adverse effects in nursing students: A systematic review and meta-analysis. Nurse Education Today, 98, 104741. https://doi.org/10.1016/j.nedt.2020.104741
  82. Plichta, S.B. & Kelvin, E.A. (2012). Munro’s Statistical Methods for Health Care Research (Sixth edition). Lippincott Williams & Wilkins, Philadelphia, PA
  83. Polit, D. F., & Beck, C. T. (2006). The content validity index: Are you sure you know what’s being reported? Critique and recommendations. Research in Nursing & Health, 29(5), 489–497. https://doi.org/10.1002/nur.20147
  84. Preacher, K. J., & MacCallum, R. C. (2003). Repairing Tom Swift's electric factor analysis machine. Understanding statistics: Statistical issues in psychology, education, and the social sciences, 2(1), 13-43. https://doi.org/10.1207/S15328031US0201_02
  85. Precht, L. M., Mertens, F., Brickau, D. S., Kramm, R. J., Margraf, J., Stirnberg, J., &
  86. Brailovskaia, J. (2023). Engaging in physical activity instead of (over) using the
  87. smartphone: An experimental investigation of lifestyle interventions to prevent
  88. problematic smartphone use and to promote mental health. Journal of Public
  89. Health, 1-19. https://doi.org/10.1007/s10389-023-01832-5
  90. Ramjan, L. M., Salamonson, Y., Batt, S., Kong, A., McGrath, B., Richards, G., ... & Crawford, R. (2021). The negative impact of smartphone usage on nursing students: An integrative literature review. Nurse Education Today, 102, 104909. https://doi.org/10.1016/j.nedt.2021.104909
  91. Radtke, T., Apel, T., Schenkel, K., Keller, J., & von Lindern, E. (2022). Digital detox: An effective solution in the smartphone era? A systematic literature review. Mobile Media & Communication, 10(2), 190-215. https://doi.org/10.1177/20501579211028647
  92. Ratter, J., Pellekooren, S., Wiertsema, S., van Dongen, J. M., Geleijn, E., de Groot, V., ... & Ostelo, R. W. (2022). Content validity and measurement properties of the Lower Extremity Functional Scale in patients with fractures of the lower extremities: a systematic review. Journal of Patient-Reported Outcomes, 6(1), 1-14. https://doi.org/10.1186/s41687-022-00417-2
  93. Semerci, R., & Kostak, M. A. (2019). Hemşirelik öğrencilerinin akıllı telefon kullanım özelliklerinin belirlenmesi. Sağlık Bilimleri ve Meslekleri Dergisi, 6(1), 8-16
  94. Steven. J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). New York: Taylor & Francis Group
  95. Syvertsen, T., & Enli, G. (2020). Digital detox: Media resistance and the promise of authenticity. Convergence, 26(5-6), 1269-1283. https://doi.org/10.1177/1354856519847325
  96. Tabachnick, B. G., & Fidell, L. S. (2014). Using Multivariate Statistics (6th ed.). Harlow: Pearson Education
  97. Thorkildsen, T. (2010). Validity of measurement. Encyclopedia of Research Design, 1592-
  98. https://thork.people.uic.edu/fair/Validity%20of%20Measurement_2020.pdf
  99. Willis, G. B. (2004). Cognitive interviewing: A tool for improving questionnaire design. Sage Publications
  100. Vaske, J. J., Beaman, J., & Sponarski, C. C. (2017). Rethinking internal consistency in
  101. Cronbach's alpha. Leisure Sciences, 39(2), 163-173. https://doi.org/10.1080/01490400.2015.1127189
  102. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M
  103. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press
  104. Yildirim, C., & Correia, A. P. (2015). Exploring the dimensions of nomophobia: Development
  105. and validation of a selfreported questionnaire. Computers in Human Behavior, 49, 130–137. https://doi.org/10.1016/j.chb.2015.02.059
  106. Yildirim, C., Sumuer, E., Adnan, M., & Yildirim, S. (2016). A growing fear: Prevalence of
  107. nomophobia among Turkish college students. Information Development, 32(5), 1322–1331. https://doi.org/10.1177/0266666915599025
  108. Zhao, H., Deng, S., Liu, Y., Xia, S., Lim, E. T. K., & Tan, C. W. (2022). Promoting users’
  109. smartphone avoidance intention: the role of health beliefs. Industrial Management & Data Systems, 122(4), 963-982. https://www.emerald.com/insight/0263-5577.htm

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