ISSN: 2222-6990
Open access
This study highlights the crucial role of accepting counseling services in online flexible distance learning higher education institutions, particularly as students face unique mental health and academic performance challenges. The primary aim of the research was to explore the relationships among counseling accessibility, counselor competency, and perceived benefits and how these factors influence students' intentions to accept counseling services. A quantitative approach was employed, utilising a structured survey for data collection among 358 participants. The data analysis used Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed hypotheses. The results of the hypotheses testing indicated significant positive relationships, with perceived benefits demonstrating the most decisive influence on counseling acceptance, followed by counselor competency and then counseling accessibility. These findings suggest that enhancing students' perceptions of the benefits of counseling can significantly increase their willingness to seek help. Future research should consider longitudinal studies to assess the long-term impacts of counselling services and investigate the influence of demographic factors on student perceptions. Additionally, qualitative inquiries could provide deeper insights into students' barriers to counselling. The implications of this study are substantial, providing actionable insights for higher education institutions aiming to improve mental health outcomes.
Ajlouni, A., Almahaireh, A., & Whaba, F. (2023). Students’ perception of using ChatGPT in counseling and mental health education: the benefits and challenges. International Journal of Emerging Technologies in Learning (iJET), 18(20), 199-218.
Almajali, A. A. B., Al-Bourini, E. S., Almajali, H. K., & Awamleh, W. J. (2023). The Extent Of The Importance Of Family Counseling In Supporting Parents' Acceptance Of Their Disabled Children From Their Point Of View In Jordan. Journal of Namibian Studies: History Politics Culture, 33, 6157-6176.
Alvarez-Hernandez, L. R., Childs, E. M., Fatehi, M., & Yeo, H. (2022). How perception relates to student utilization of college campus counseling services. Journal of American College Health, 1-9.
American College Counseling Association. (ACCA). (2017). Best practices for college counseling centers: A guide for leadership and practice. American College Counseling Association.
Baker, A. J., & Duncan, B. L. (2013). The benefits of college counseling centers: A meta-analysis. Journal of College Student Development, 54(2), 187-202.
Bathje, G. J., Pillersdorf, D., & Eddir, H. (2022). Multicultural competence as a common factor in the process and outcome of counseling. Journal of Humanistic Psychology, 00221678221099679.
Caskie, G. I., Sutton, M. C., & Voelkner, A. R. (2024). Clinical and counseling psychology doctoral trainees’ attitudes toward and interest in working with older adult clients. Gerontology & Geriatrics Education, 45(2), 141-155.
Cerolini, S., Zagaria, A., Franchini, C., Maniaci, V. G., Fortunato, A., Petrocchi, C., ... & Lombardo, C. (2023). Psychological Counseling among University Students Worldwide: A Systematic Review. European Journal of Investigation in Health, Psychology and Education, 13(9), 1831-1849.
Chen, W. C., Chan, H. Y., Sung, Y. H., Chen, P. L., Hung, Y. F., Huang, K. C., & Hsu, S. S. (2023). Therapists’ practical implementation and preparation of online counseling in the post-pandemic era. Current Psychology, 42(34), 30548-30560.
Chen, X., Du, A., & Qi, R. (2022). Factors affecting willingness to receive online counseling: the mediating role of ethical concerns. International Journal of Environmental Research and Public Health, 19(24), 16462.
Chen, X., Du, A., & Qi, R. (2022). Factors affecting willingness to receive online counseling: the mediating role of ethical concerns. International Journal of Environmental Research and Public Health, 19(24), 16462.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. doi:10.1037/0033- 2909.112.1.155
De Veirman, A. E., Thewissen, V., Spruijt, M. G., & Bolman, C. A. (2022). Factors Associated With Intention and Use of e–Mental Health by Mental Health Counselors in General Practices: Web-Based Survey. JMIR Formative Research, 6(12), e34754.
El-Hachem, S. S., Lakkis, N. A., Osman, M. H., Issa, H. G., & Beshara, R. Y. (2023). University students’ intentions to seek psychological counseling, attitudes toward seeking psychological help, and stigma. Social psychiatry and psychiatric epidemiology, 58(11), 1661-1674.
El-Hachem, S. S., Lakkis, N. A., Osman, M. H., Issa, H. G., & Beshara, R. Y. (2023). University students’ intentions to seek psychological counseling, attitudes toward seeking psychological help, and stigma. Social psychiatry and psychiatric epidemiology, 58(11), 1661-1674.
Grimmett, M. A., Lupton?Smith, H., Beckwith, A., Messinger, E., Edwards, M., Moody, B., ... & Bates, D. (2024). Intent and impact: Connecting multicultural and social justice counselor training to community client experiences. Journal of Multicultural Counseling and Development, 52(2), 107-121.
Guzman, L. E., Bridges, A. J., Díaz Benitez, D. E., & Hovey, J. D. (2024). Acculturation and Depression Help-Seeking Intentions in a Majority Mexican American College Student Sample. Journal of Immigrant and Minority Health, 1-10.
Haas, J., Walsh, D. D., & Marroquin, M. (2024). Enhancing Cultural Competence in Counselor Education through Sociolinguistic Awareness. Teaching and Supervision in Counseling, 6(3), 4.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: SAGE.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3 ed.). Thousand Oaks, CA: Sage.
Hair, J.F., M. Sarstedt, C.M. Ringle, and S.P. Gudergan. (2018). Advanced issues in partial least squares structural equation modeling. Thousand Oakes, CA: Sage Publications
Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling, Journal of the Academy of Marketing Science, 43(1): 115-135
Intaratat, K., Osman, Z., Nguyen, H. A. T., Suhandoko, A. D. J., & Sultana, N. (2024). Peer and tutor interaction effects on collaborative learning: The role of learning self-efficacy. Edelweiss Applied Science and Technology, 8(4), 2108-2121.
Jiang, G., Yang, W., & Zhang, N. (2022). Effect of perceived risks, perceived benefits and regulatory events on users’ supervision intention towards e-hailing platforms: A mixed method. Journal of Information Science, 01655515221128422.
Kebah, M., Raju, V., & Osman, Z. (2019). Growth of online purchase in Saudi Arabia retail industry. International Journal of Recent Technology and Engineering, 8(3), 869-872.. ISSN: 2277-3878
Kebah, M., Raju, V., & Osman, Z. (2019). Online purchasing trend in the retail industry in Saudi. International Journal of Recent Technology and Engineering (IJRTE), 8(3), 865-868. ISSN: 2277-3878
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10.
Kock, N., & Lynn, G.S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580.
Li, X. T., Rahman, A., Connie, G., & Osman, Z. (2020). Examining customers' perception of electronic shopping mall's e-service quality. International Journal of Services, Economics and Management, 11(4), 329-346.
Li, L., Peng, W., & Rheu, M. M. (2024). Factors predicting intentions of adoption and continued use of Artificial Intelligence chatbots for mental health: examining the role of Utaut model, stigma, privacy concerns, and artificial intelligence hesitancy. Telemedicine and e-Health, 30(3), 722-730.
Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: Coveted, Yet Forsaken? Introducing a Cross-validated Predictive Ability Test in Partial Least Squares Path Modeling. Decision Sciences, 52(2), 362-392.
Liu, H. H. (2022). A Study of Factors Affecting Acceptance of Counseling Service System Service Users’ Perspective. Journal of Robotics, Networking and Artificial Life, 9(1), 54-58.
Liu, Y. L., Yan, W., Hu, B., Li, Z., & Lai, Y. L. (2022). Effects of personalization and source expertise on users’ health beliefs and usage intention toward health chatbots: Evidence from an online experiment. Digital Health, 8, 20552076221129718.
Lu, F., Wang, X., & Huang, X. (2023). Counseling for Health: How Psychological Distance Influences Continuance Intention towards Mobile Medical Consultation. International Journal of Environmental Research and Public Health, 20(3), 1718.
Maiman, L. A., & Becker, M. H. (1974). The health belief model: Origins and correlates in psychological theory. Health education monographs, 2(4), 336-353.
Nardini-Bubols, M., Costa, D. B., Moret-Tatay, C., & Irigaray, T. Q. (2024). Effects of the Religious and Spiritual Competencies Training in Brazilian Psychologists: A Pilot Study. International Journal of Latin American Religions, 1-16.
Osman, Z., Mohamad, W., Mohamad, R. K., Mohamad, L., & Sulaiman, T. F. T. (2018). Enhancing students’ academic performance in Malaysian online distance learning institutions. Asia Pacific Journal of Educators and Education, 33, 19-28.
Park, G., Chung, J., & Lee, S. (2024). Human vs. machine-like representation in chatbot mental health counseling: the serial mediation of psychological distance and trust on compliance intention. Current Psychology, 43(5), 4352-4363.
Pedersen, P. B., Draguns, J. G., Lonner, W. J., & Trimble, J. E. (2002). Counseling across cultures (5th ed.). Routledge.
Ringle, C.M., and M. Sarstedt. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems. 116: 1865–1886.
Ringle, Christian M., Wende, Sven, & Becker, Jan-Michael. (2022). SmartPLS 4. Oststeinbek: SmartPLS. Retrieved from https://www.smartpls.com
Rosenstock, I. M. (1974). The Health Belief Model and Personal Health Behavior. Health Education Monographs, 2(4), 354-386.
Sahoo, A. K., Dash, A., & Nayak, P. (2023). Perceived risk and benefits of e-health consultation and their influence on user’s intention to use. Journal of Science and Technology Policy Management.
Sari, R. K., Kurdi, M. S., Kurdi, M. S., Lukiani, E. R. M., & Cakranegara, P. A. (2023). Self-Acceptance for Students Through Reality Counseling Containing Local Wisdom. AL-ISHLAH: Jurnal Pendidikan, 15(4), 6055-6062.
Shmueli, G., M. Sarstedt, J.F. Hair, J.-H. Cheah, H. Ting, S. Vaithilingam, and C.M. Ringle. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing. 53: 2322–2347.
Shmueli, G., S. Ray, J.M. Velasquez Estrada, and S.B. Chatla. (2016). The elephant in the room: predictive performance of PLS models. Journal of Business Research, 69: 4552–4564.
Skinner, C. S., Tiro, J., & Champion, V. L. (2015). Background on the health belief model. Health behavior: Theory, research, and practice, 75, 1-34.
Vogel, D. L., Wade, N. G., & Haake, E. M. (2006). Measuring the self-stigma associated with seeking psychological help. Journal of Counseling Psychology, 53(3), 325-337.
Yandri, H., Mudjiran, M., Karneli, Y., & Netrawati, N. (2023). Mindfulness in Counseling: Implementation of Counseling in the Society 5.0. Indonesian Journal of Counseling and Development, 5(1), 24-31.
Yeung, N. C., Lau, S. T., Mak, W. W., Cheng, C., Chan, E. Y., Siu, J. Y., & Cheung, P. S. (2024). Applying the Unified Theory of Acceptance and Use of Technology to Identify Factors Associated With Intention to Use Teledelivered Supportive Care Among Recently Diagnosed Breast Cancer Survivors During COVID-19 in Hong Kong: Cross-Sectional Survey. JMIR cancer, 10(1), e51072.
Osman, Z., Ali, A., Aziz, R. C., & Yusoof, F. (2025). Drivers of Counseling Services Acceptance among Online and Flexible Distance Learning Students. International Journal of Academic Research in Business and Social Sciences, 15(3), 48–64.
Copyright: © 2025 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode