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Role of Technology Self-Efficacy and Digital Alliance in Digital Mental Health Tool Acceptance Among University Students in Singapore
Open accessAbstract
Mental health challenges, accentuated by stress, are escalating in high-income countries, especially among adolescents and university students. Traditional mental health approaches face issues such as scalability and accessibility, making the emergence of digital tools crucial. However, adherence remains a challenge. This study examines the role of technology self-efficacy and digital alliance in influencing the acceptance of digital mental health tools among Singaporean university students. The results provide strong support for the role of digital alliance as a key factor impacting a student's intention to use mental health tools, as well as technology self-efficacy and digital alliance as serial mediators of task-technology fit and intention to use, highlighting our ever-evolving relationship with technology.
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“SE influenced undergraduate students’ cognitive processes and the intensity and stability of their emotional states when using new technology [58].”
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“SE was widely acknowledged as an essential predictor of students’ technology acceptance because it influences cognitive processing, emotional stability, and perceived ability to manage new technologies [58,59].”
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Research works printed but not linked: 65
- Davis, 1986, A technology acceptance model for empirically testing new end-user information systems: Theory and results, Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA
- 10.2307/249008 · DOI · Paper page
- 10.1145/506724.506730 · DOI · Paper page
- 10.1287/isre.6.2.144 · DOI · Paper page
- 10.1186/1472-6947-13-88 · DOI
- 10.1016/j.techsoc.2019.101212 · DOI
- 10.9790/0050-0112133 · DOI
- 10.1108/ITP-07-2016-0160 · DOI
- 10.2196/17256 · DOI · Paper page
- 10.1089/tmj.2019.0144 · DOI
- 10.2307/249689 · DOI · Paper page
- 10.1016/j.chb.2021.106900 · DOI
- 10.3390/healthcare11111550 · DOI
- 10.3390/su13116450 · DOI
- 10.1108/IJCHM-12-2019-1031 · DOI
- 10.1016/j.chb.2018.03.015 · DOI
- 10.1108/LHT-09-2016-0105 · DOI
- 10.1037//0033-295X.84.2.191 · DOI · Paper page
- 10.2307/249688 · DOI · Paper page
- 10.1016/j.dss.2003.08.001 · DOI
- 10.2196/jmir.1619 · DOI
- 10.1016/j.ijinfomgt.2019.03.005 · DOI
- 10.1016/j.chb.2018.09.024 · DOI
- 10.1037/h0085885 · DOI · Paper page
- 10.2196/21895 · DOI · Paper page
- 10.2196/jmir.2084 · DOI · Paper page
- 10.3389/fpsyt.2022.819623 · DOI · Paper page
- 10.1192/bjo.2018.86 · DOI · Paper page
- Dishaw, Extending the task-technology fit model with self-efficacy constructs, 1021
- 10.1016/j.chb.2010.01.013 · DOI · Paper page
- 10.1016/S0378-7206(98)00101-3 · DOI · Paper page
- 10.1111/isj.12082 · DOI
- 10.1287/isre.9.2.126 · DOI
- 10.1002/jclp.21912 · DOI
- 10.2307/249749 · DOI
- 10.2307/20650279 · DOI · Paper page
- 10.2307/30036540 · DOI · Paper page
- 10.2307/30036519 · DOI · Paper page
- 10.1287/mnsc.46.2.186.11926 · DOI · Paper page
- 10.1016/j.chb.2016.12.019 · DOI
- 10.1080/10864415.2003.11044275 · DOI · Paper page
- 10.1287/isre.2.3.192 · DOI · Paper page
- 10.2196/jmir.5069 · DOI
- 10.1136/jamia.2010.007336 · DOI
- 10.2307/20650295 · DOI · Paper page
- 10.1080/14783360701231302 · DOI · Paper page
- 10.2196/16407 · DOI · Paper page
- 10.1111/j.1540-5915.2008.00192.x · DOI · Paper page
- 10.2307/25148720 · DOI · Paper page
- 10.1016/j.aci.2014.09.001 · DOI
- 10.2196/jmir.2143 · DOI · Paper page
- 10.1111/isj.12131 · DOI · Paper page
- Chin, 1998, Commentary: Issues and opinion on structural equation modeling, MIS Q., 22, 7
- Hoyle, 1995, The structural equation modeling approach: Basic concepts and fundamental issues, 1
- 10.2307/248922 · DOI
- Klopping, 2004, Extending the technology acceptance model and the task-technology fit model to consumer E-commerce, Information Technology, Learning, and Performance Journal, 22, 35
- 10.1111/j.1467-8535.2010.01054.x · DOI
- 10.2196/jmir.3564 · DOI
- 10.1177/10731911211015310 · DOI · Paper page
- 10.1016/j.procs.2016.09.036 · DOI
- 10.17705/1cais.00407 · DOI · Paper page
- 10.2753/MTP1069-6679190202 · DOI · Paper page
- 10.1037//0033-2909.103.3.411 · DOI · Paper page
- Hair, 2021, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 10.1007/978-3-030-80519-7 · DOI · Paper page
- 10.1142/3573 · DOI
Cited by
Sorted by citations
Son, N. K., Sangaiah, A. K., Paramarthika, L. K. M., Rajendran, V., Bian, G., & Alenazi, M. J. F. (2025) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2025.3572596 · Cited by 3
“The result of those studies showcases the potential to alleviate the strain on healthcare resources [23], especially when the traditional approach faces issues such as scalability and accessibility [24].”
Zhou, Z., Zhou, Y., Ouyang, B., Man, S. S., & Chan, A. H. S. (2026) · Healthcare · doi:10.3390/healthcare14131978
“SE was widely acknowledged as an essential predictor of students’ technology acceptance because it influences cognitive processing, emotional stability, and perceived ability to manage new technologies [58,59].”
Barrios, P. P., Reales, E. B., Cantillo, L. B., Mendoza, P. S., Conde, W. R. I., & Brochado, E. R. C. (2025) · IEEE Colombian Caribbean Conference (C3) · doi:10.1109/c366505.2025.11340093
“Similarly, studies such as [14] and [15] demonstrated that online group interventions can achieve retention rates above 90% and significant reductions in social anxiety and technos-tress [13], [16], [17], [18], even with small samples of 35 students.”
Hierarchical Graph Convolutional Approach for Detecting Major Depressive Disorder from EEG Signals
Swetha, K., Sriraam, J., G.Ramya, et al. (2025) · International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) · doi:10.1109/icerect65215.2025.11379821
Metadata
- Authors
- Tan, T. H. B., Lim, S., & Vun, C. H. N.
- Affiliations
- Nanyang Technological University (SG)
- Venue
- International Journal of Crowd Science
- Publisher
- Tsinghua University Press
- Published
- 2024-08
- Volume
- 8
- Issue
- 3
- Pages
- 101-109
- ISSN
- 2398-7294 (ISSN-L)
- OpenAlex
- W4401691565
- Cited by
- 7
- References
- 0
- Citations by year
- 2026: 3 · 2025: 4
- FWCI
- 2.79
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Crowd Science (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- DR-NTU (Nanyang Technological University) (submittedVersion, cc-by)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- technology self-efficacy, digital mental health tools, technology acceptance, university students, intention to use, task-technology fit, serial mediation, student mental health, stress, Singapore
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Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Role of Technology Self-Efficacy and Digital Alliance in Digital Mental Health Tool Acceptance Among University Students in Singapore. https://app.cochat.ai/papers/10.26599/ijcs.2024.9100001
- The paper
- Tan, T. H. B., Lim, S., & Vun, C. H. N. (2024). Role of Technology Self-Efficacy and Digital Alliance in Digital Mental Health Tool Acceptance Among University Students in Singapore. International Journal of Crowd Science. https://doi.org/10.26599/ijcs.2024.9100001
