Research Article

Creation and validation of the online self-disclosure via educational platforms scale

Beatrice Hayes 1 * , Lizete Murniece 1
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1 Department of Psychology, Royal Holloway, University of London, Egham, UK* Corresponding Author
Journal of Digital Educational Technology, 4(2), 2024, ep2416,
Published: 09 July 2024
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Globally, higher education (HE) institutions now implement some element of hybrid learning, heightened since the COVID-19 pandemic and temporary shift to online learning. To communicate, online self-disclosure (revealing information about the self) is required. The majority of HE students are aged between 18-24 years, which is considered the developmentally sensitive period of ‘emerging adulthood’. Having only ever known a digitally-connected world, emerging adults self-disclose differently to other generations when communicating via an online environment. Whilst communicating online with HE staff, students may self-disclose in a way that misaligns with the expectations of staff; this may result in miscommunication or over-disclosure (revealing inappropriate information to a misjudged audience). Over-disclosing via online educational platforms (e.g., Moodle, MS Teams, and e-mail) may result in negative feedback from staff and this may impact student experience, engagement and attainment. Problematically, no standardized measure exists that captures student self-disclosure via online educational platforms and so research on this topic is currently limited and theoretically unstable. Via a three-phase study, comprising four studies and 283 participants, we have created and conducted an initial evaluation of the online self-disclosure via educational platforms (OSDEP) scale. The OSDEP scale is the first psychometric tool to specifically measure HE students’ online self-disclosure behaviors specifically within an online educational context. The OSDEP scale can be used for future educational and pedagogical research to further understand HE students’ online self-disclosure behaviors and to what extent these may be associated with topics such as mental health, engagement, attainment, and student experience.


Hayes, B., & Murniece, L. (2024). Creation and validation of the online self-disclosure via educational platforms scale. Journal of Digital Educational Technology, 4(2), ep2416.


  1. Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. (2003). Help seeking and help design in interactive learning environments. Review of Educational Research, 73(3), 277-320.
  2. Antaki, C., Barnes, R., & Leudar, I. (2005). Self-disclosure as a situated interactional practice. British Journal of Social Psychology, 44(2), 181-199.
  3. Arbreton, A. (2012). Student goal orientation and help-seeking strategy use. In S. A. Karabenick (Ed.), Strategic help seeking (pp. 95-116). Routledge.
  4. Bagby, R. M., Taylor, G. J., & Atkinson, L. (1988). Alexithymia: A comparative study of three self-report measures. Journal of Psychosomatic Research, 32, 107-116.
  5. Bates, D. M., Mächler, M., Bolker, B. M., & Walker, S. C. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1-48.
  6. Bjornsen, C. A. (2018). Social media use and emerging adulthood. In M. Zupančič, & M. Puklek Levpušček (Eds.), Prehod v odraslost: Sodobni trendi in raziskave [Emerging adulthood: Current trends and research] (pp. 223-261). Znanstvena Založba Filozofske Fakultete [Scientific Publishing House of the Faculty of Arts].
  7. Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, 149.
  8. Bovill, C. (2019). Student-staff partnerships in learning and teaching: An overview of current practice and discourse. Journal of Geography in Higher Education, 43(4), 385-398.
  9. Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230-258.
  10. Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Lawrence Erlbaum Associates Publishers.
  11. Carlson, K. D., & Herdman, A. O. (2012). Understanding the impact of convergent validity on research results. Organizational Research Methods, 15, 17-32.
  12. Chan, L. L., & Idris, N. (2017). Validity and reliability of the instrument using exploratory factor analysis and Cronbach’s alpha. International Journal of Academic Research in Business and Social Sciences, 7(10), 400-410.
  13. (2022). Global student survey 2022.
  14. Chen, B., & Denoyelles, A. (2013). Exploring students’ mobile learning practices in higher education. Educause Review, 7, 36-43.
  15. Chesney, M. A., Neilands, T. B., Chambers, D. B., Taylor, J. M., & Folkman, S. (2006). A validity and reliability study of the coping self-efficacy scale. British Journal of Health Psychology, 11(3), 421-437.
  16. Cho, S. H. (2007). Effects of motivations and gender on adolescents’ self-disclosure in online chatting. CyberPsychology & Behavior, 10(3), 339-345.
  17. Clouder, D. L., Goodman, S., Bluteau, P., Jackson, A., Davies, B., & Merriman, L. (2011). An investigation of “agreement” in the context of interprofessional discussion online: A “netiquette” of interprofessional learning? Journal of Interprofessional Care, 25(2), 112-118.
  18. Cohen, J. (1988). Set correlation and contingency tables. Applied Psychological Measurement, 12(4), 425-434.
  19. Colbert, C. Y., Brateanu, A., Nowacki, A. S., Prelosky-Leeson, A., & French, J. C. (2021). An examination of resident perspectives on survey participation and methodology: Implications for educational practice and research. Journal of Graduate Medical Education, 13(3), 390-403.
  20. Contena, B., Loscalzo, Y., & Taddei, S. (2015). Surfing on social network sites: A comprehensive instrument to evaluate online self-disclosure and related attitudes. Computers in Human Behavior, 49, 30-37.
  21. Cozby, P. C. (1973). Self-disclosure: A literature review. Psychological Bulletin, 79(2), 73-91.
  22. Er, E., Kopcha, T. J., Orey, M., & Dustman, W. (2015). Exploring college students’ online help-seeking behavior in a flipped classroom with a web-based help-seeking tool. Australasian Journal of Educational Technology, 31(5), 537-555.
  23. Fan, Y. H., & Lin, T. J. (2023). Identifying university students’ online academic help-seeking patterns and their role in Internet self-efficacy. The Internet and Higher Education, 56, 100893.
  24. Ferketich, S. (1991). Focus on psychometrics. Aspects of item analysis. Research in Nursing & Health, 14(2), 165-168.
  25. Flint, A., & Millard, L. (2018). “Interactions with purpose”: Exploring staff understandings of student engagement in a university with an ethos of staff-student partnership. International Journal for Students as Partners, 2(2), 21-38.
  26. Gasman, I., Purper-Ouakil, D., Michel, G., Mouren-Siméoni, M. C., Bouvard, M., Perez-Diaz, F., & Jouvent, R. (2002). Cross-cultural assessment of childhood temperament: A confirmatory factor analysis of the French emotionality activity and sociability (EAS) questionnaire. European Child & Adolescent Psychiatry, 11, 101-107.
  27. Glen, S. (2018). Average inter-item correlation: Definition, example. Statistics How To.
  28. Hayes, B. (2024). Exploring university students’ online self-presentation techniques and self-disclosure behaviors as predictors of staff response. Journal of Digital Educational Technology, 4, ep2405.
  29. Hayton, J. C., Allen, D. G., & Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7(2), 191-205.
  30. HESA. (2015). Staff in higher education 2013/2014.
  31. HESA. (2023). Higher education student statistics: UK, 2021/2022.
  32. Hill, J., Healey, R. L., West, H., & Déry, C. (2021). Pedagogic partnership in higher education: Encountering emotion in learning and enhancing student wellbeing. Journal of Geography in Higher Education, 45(2), 167-185.
  33. Howard, M. C. (2016). A review of exploratory factor analysis decisions and overview of current practices: What we are doing and how can we improve? International Journal of Human-Computer Interaction, 32, 51-62.
  34. Hu, L. T., & 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, 1-55.
  35. Hurley, A. E., Scandura, T. A., Schriesheim, C. A., Brannick, M. T., Seers, A., Vandenberg, R. J., & Williams, L. J. (1997). Exploratory and confirmatory factor analysis: Guidelines, issues, and alternatives. Journal of Organizational Behavior, 18(6), 667-683.<667::AID-JOB874>3.0.CO;2-T
  36. Ignatius, E., & Kokkonen, M. (2007). Factors contributing to verbal self-disclosure. Nordic Psychology, 59(4), 362-391.
  37. Jebbour, M., & Mouaid, F. (2019). The impact of teacher self-disclosure on student participation in the university English language classroom. International Journal of Teaching and Learning in Higher Education, 31(3), 424-436.
  38. Joinson, A. N. (2001). Self-disclosure in computer-mediated communication: The role of self-awareness and visual anonymity. European Journal of Social Psychology, 31(2), 177-192.
  39. Joinson, A. N., & Paine, C. B. (2007). Self-disclosure, privacy and the Internet. The Oxford Handbook of Internet Psychology, 2374252, 237-252.
  40. Jourard, S. M. (1961). Self-disclosure patterns in British and American college females. The Journal of Social Psychology, 54(2), 315-320.
  41. Kassambara, A. (2023). Pipe-friendly framework for basic statistical tests. rstatix.
  42. Khan, K. A., & Rafi, S. T. (2020). Online education & MOOCs: Teacher self-disclosure in online education and a mediating role of social presence. South Asian Journal of Management, 14, 142-158.
  43. Kim, J., & Dindia, K. (2011). Online self-disclosure: A review of research. In K. B. Wright, & L. M. Webb (Eds.), Computer-mediated communication in personal relatinoships (pp. 156-180). Peter Lang Publishing.
  44. Kline, P. (2015). A handbook of test construction (psychology revivals): Introduction to psychometric design. Routledge.
  45. Koc, S., & Liu, X. (2016). An investigation of graduate students’ help-seeking experiences, preferences and attitudes in online learning. Turkish Online Journal of Educational Technology, 15(3), 27-38.
  46. Krasnova, H., & Veltri, N. F. (2011). Behind the curtains of privacy calculus on social networking sites: The study of Germany and the USA. In Proceedings of the 2010 43rd Hawaii International Conference on System Sciences (pp. 1-10). IEEE.
  47. Kyriazos, T. A. (2018). Applied psychometrics: The 3-faced construct validation method, a routine for evaluating a factor structure. Psychology, 9(8), 2044-2072.
  48. Lohnes, S., & Kinzer, C. (2007). Questioning assumptions about students’ expectations for technology in college classrooms. Innovate: Journal of Online Education, 3(5).
  49. Lou, S. (2014). Cross-cultural differences between American and Chinese college students on self-disclosure on social media.
  50. Mercer-Mapstone, L., Dvorakova, S. L., Matthews, K. E., Abbot, S., Cheng, B., Felten, P., Knorr, K., Marquis, E., Shammas, R., & Swaim, K. (2017). A systematic literature review of students as partners in higher education. International Journal for Students as Partners, 1(1), 15-37.
  51. Michikyan, M. (2020). Depression symptoms and negative online disclosure among young adults in college: A mixed-methods approach. Journal of Mental Health, 29(4), 392-400.
  52. Miller, L. C., Berg, J. H., & Archer, R. L. (1983). Openers: Individuals who elicit intimate self-disclosure. Journal of Personality and Social Psychology, 44(6), 1234.
  53. Money, J., Nixon, S., Tracy, F., Hennessy, C., Ball, E., & Dinning, T. (2017). Undergraduate student expectations of university in the United Kingdom: What really matters to them? Cogent Education, 4, 1301855.
  54. Morley, D. A. (2012). Enhancing networking and proactive learning skills in the first year university experience through the use of wikis. Nurse Education Today, 32(3), 261-266.
  55. Nguyen, M., Bin, Y. S., & Campbell, A. (2012). Comparing online and offline self-disclosure: A systematic review. Cyberpsychology, Behavior, and Social Networking, 15(2), 103-111.
  56. Office for National Statistics. (2021). Coronavirus and first year higher education students, England: 4 October to 11 October 2021.
  57. Office for Students. (2022). The office for students annual review 2022.
  58. Orcan, F. (2018). Exploratory and confirmatory factor analysis: Which one to use first? Journal of Measurement and Evaluation in Education and Psychology, 9(4), 414-421.
  59. Ostendorf, S., & Brand, M. (2022). Theoretical conceptualization of online privacy-related decision making–Introducing the tripartite self-disclosure decision model. Frontiers in Psychology, 13, 996512.
  60. Park, J. H. (2010). Differences among university students and faculties in social networking site perception and use: Implications for academic library services. The Electronic Library, 28(3), 417-431.
  61. Puustinen, M., Bernicot, J., Volckaert-Legrier, O., & Baker, M. (2015). Naturally occurring help-seeking exchanges on a homework help forum. Computers & Education, 81, 89-101.
  62. Roberts, P., & Dunworth, K. (2012). Staff and student perceptions of support services for international students in higher education: A case study. Journal of Higher Education Policy and Management, 34(5), 517-528.
  63. Robinson, S. B., & Leonard, K. F. (2018). Designing quality survey questions. SAGE.
  64. Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48, 1-36.
  65. Russell, G., & Topham, P. (2012). The impact of social anxiety on student learning and well-being in higher education. Journal of Mental Health, 21(4), 375-385.
  66. Sawyer, S. M., Azzopardi, P. S., Wickremarathne, D., & Patton, G. C. (2018). The age of adolescence. The Lancet Child & Adolescent Health, 2(3), 223-228.
  67. Schlosser, A. E. (2020). Self-disclosure versus self-presentation on social media. Current Opinion in Psychology, 31, 223-228.
  68. Schouten, A. P., Valkenburg, P. M., & Peter, J. (2007). Precursors and underlying processes of adolescents’ online self-disclosure: Developing and testing an “Internet-attribute-perception” model. Media Psychology, 10(2), 292-315.
  69. Schreiber, J. B. (2021). Issues and recommendations for exploratory factor analysis and principal component analysis. Research in Social and Administrative Pharmacy, 17(5), 1004-1011.
  70. Schunk, D. H., & Zimmerman, B. J. (Eds.). (2012). Motivation and self-regulated learning: Theory, research, and applications. Routledge.
  71. Song, H., Kim, J., & Luo, W. (2016). Teacher–student relationship in online classes: A role of teacher self-disclosure. Computers in Human Behavior, 54, 436-443.
  72. Stockdale, L. A., & Coyne, S. M. (2020). Bored and online: Reasons for using social media, problematic social networking site use, and behavioral outcomes across the transition from adolescence to emerging adulthood. Journal of Adolescence, 79, 173-183.
  73. Suler, J. (2004). The online disinhibition effect. Cyberpsychology & Behavior, 7(3), 321-326.
  74. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2013). Using multivariate statistics. Pearson.
  75. Thurstone, L. L. (1947). Multiple-factor analysis: A development and expansion of “the vectors of mind”. University Chicago Press.
  76. Tidwell, L. C., & Walther, J. B. (2002). Computer-mediated communication effects on disclosure, impressions, and interpersonal evaluations: Getting to know one another a bit at a time. Human Communication Research, 28(3), 317-348.
  77. Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19(6), 349-357.
  78. Towner, E., Grint, J., Levy, T., Blakemore, S. J., & Tomova, L. (2022). Revealing the self in a digital world: A systematic review of adolescent online and offline self-disclosure. Current Opinion in Psychology, 45, 101309.
  79. Vedsted, P., Sokolowski, I., & Heje, H. N. (2008). Data quality and confirmatory factor analysis of the Danish EUROPEP questionnaire on patient evaluation of general practice. Scandinavian Journal of Primary Health Care, 26(3), 174-180.
  80. Waycott, J., Bennett, S., Kennedy, G., Dalgarno, B., & Gray, K. (2010). Digital divides? Student and staff perceptions of information and communication technologies. Computers & Education, 54(4), 1202-1211.
  81. Weidman, A. C., Fernandez, K. C., Levinson, C. A., Augustine, A. A., Larsen, R. J., & Rodebaugh, T. L. (2012). Compensatory internet use among individuals higher in social anxiety and its implications for well-being. Personality and Individual Differences, 53(3), 191-195.
  82. Wheeless, L. R., & Grotz, J. (1976). Conceptualization and measurement of reported self-disclosure. Human Communication Research, 2(4), 338-346.
  83. Winstone, N. E., Nash, R. A., Rowntree, J., & Parker, M. (2017). ‘It’d be useful, but I wouldn’t use it’: Barriers to university students’ feedback seeking and recipience. Studies in Higher Education, 42(11), 2026-2041.
  84. Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806-838.
  85. Xu, Y., Pace, S., Kim, J., Iachini, A., King, L. B., Harrison, T., DeHart, D., Levkoff, S. E., Browne, T. A., Lewis, A. A., Kunz, G. M., Reitmeier, M., Utter, R. K., & Simone, M. (2022). Threats to online surveys: Recognizing, detecting, and preventing survey bots. Social Work Research, 46(4), 343-350.