Effect of MindSearch Intervention Application Based on HCI Design Principles for Depression and Anxiety among Youth
Keywords:
depression, anxiety, youth, MindSearch, REBT, HCIAbstract
The use of digital technology to support and improve young people's psychological health is becoming more popular, and there are increasing indications that these methods are helpful. However, questions have been raised concerning the degrees of user participation, acceptance, and adherence. The most significant proposal for digital health interferences is the importance of intervention and early user participation in knowledge production, assessment, and deployment. This contributes to ensuring that the technology is appealing, useful, fulfilling, and advantageous.
Objective: Our findings point to significant advantages of using codesigning computer-based interventions for depression, and anxiety. There is a lack of research to guide the co-design of computer-based devices that might recover the psychological health of adolescents. The findings are incorporated from ethical considerations and the Human-Computer Interaction (HCI) study perspective in a novel online intervention “MindSearch Application” for youth. Find the effectiveness of the intervention along with the satisfaction of using it.
Methods: The MindSearch Application is based on Rational Emotive Behavioural Therapy (REBT) developed in association with a psychological research institute. The REBT is preferred as the major focus group is youth between 18 to 25 age group. The application design and testing is done through HCI principles, usability study, and finally feedback evaluation. The significance and effect size of the intervention is done through a pretest and post-test of an experimental and controlled group.
Results: The mean depression frequency scores before and after intervention were 7.98 ± 3.56 and 5.90 ± 5.44, respectively (p>0.01) with d=0.58. The mean depression intensity scores before and after intervention were 8.41 ± 3.97 and 5.56 ± 4.69, respectively (p<0.01) with d=0.72. The mean anxiety frequency scores before and after intervention were 9.06± 3.61 and 5.85 ± 5.55, respectively (p<0.01) with d=0.89. The mean anxiety intensity scores before and after intervention were 9.11± 3.78 and 5.45 ± 4.91, respectively (p<0.01) with d=0.97. These values define the significance of the result and effect size of the experimental group is more as compared to the control group.
Conclusion: Our results showed that the MindSearch Application intervention has made a statistically significant difference in depression’s frequency, intensity, and Anxiety’s intensity and frequency of youth. The REBT-base of psychology and HCI design principles of the application increase the effectiveness, efficiency, and satisfaction of the application and population group. The present study's findings underscore the necessity for additional investigation into computer-based intervention techniques aimed at improving functioning and clinical symptoms.
Downloads
References
D. Yang, J. W. Hur, Y. Bin Kwak, and S. W. Choi, “A systematic review and meta-analysis of applicability of web-based interventions for individuals with depression and quality of life impairment,” Psychiatry Investig., vol. 15, no. 8, pp. 759–766, 2018, doi: 10.30773/pi.2018.03.15.
J. Borghouts et al., “Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review,” J. Med. Internet Res., vol. 23, no. 3, 2021, doi: 10.2196/24387.
R. Bevan Jones et al., “Practitioner review: Co-design of digital mental health technologies with children and young people,” J. Child Psychol. Psychiatry Allied Discip., vol. 61, no. 8, pp. 928–940, 2020, doi: 10.1111/jcpp.13258.
A. Søgaard Neilsen and R. L. Wilson, “Combining e-mental health intervention development with human computer interaction (HCI) design to enhance technology-facilitated recovery for people with depression and/or anxiety conditions: An integrative literature review,” Int. J. Ment. Health Nurs., vol. 28, no. 1, pp. 22–39, 2019, doi: 10.1111/inm.12527.
E. G. Lattie, E. C. Adkins, N. Winquist, C. Stiles-Shields, Q. E. Wafford, and A. K. Graham, “Digital mental health interventions for depression, anxiety and enhancement of psychological well-being among college students: Systematic review,” J. Med. Internet Res., vol. 21, no. 7, 2019, doi: 10.2196/12869.
J. S. Feather, M. Howson, L. Ritchie, P. D. Carter, D. T. Parry, and J. Koziol-McLain, “Evaluation methods for assessing users’ psychological experiences of web-based psychosocial interventions: A systematic review,” J. Med. Internet Res., vol. 18, no. 6, pp. 1–13, 2016, doi: 10.2196/jmir.5455.
F. Alqahtani and R. Orji, “Insights from user reviews to improve mental health apps,” Health Informatics J., vol. 26, no. 3, pp. 2042–2066, 2020, doi: 10.1177/1460458219896492.
M. R. Hoque, M. S. Rahman, N. J. Nipa, and M. R. Hasan, “Mobile health interventions in developing countries: A systematic review,” Health Informatics J., vol. 26, no. 4, pp. 2792–2810, 2020, doi: 10.1177/1460458220937102.
F. Burger, M. A. Neerincx, and W. P. Brinkman, “Technological State of the Art of Electronic Mental Health Interventions for Major Depressive Disorder: Systematic Literature Review,” J. Med. Internet Res., vol. 22, no. 1, p. e12599, 2020, doi: 10.2196/12599.
R. Grist, A. Croker, M. Denne, and P. Stallard, “Technology Delivered Interventions for Depression and Anxiety in Children and Adolescents: A Systematic Review and Meta-analysis,” Clin. Child Fam. Psychol. Rev., vol. 22, no. 2, pp. 147–171, 2019, doi: 10.1007/s10567-018-0271-8.
A. Fonseca and J. Osma, “Using information and communication technologies (Ict) for mental health prevention and treatment,” Int. J. Environ. Res. Public Health, vol. 18, no. 2, pp. 1–6, 2021, doi: 10.3390/ijerph18020461.
A. Wijayanti, D. Yuwono, P. Sugiharto, and M. E. Wibowo, “The Effectiveness of Rational Emotive Behavior Therapy ( REBT ) Group Counseling to Reduce Cheating Behavior,” J. Bimbing. Konseling, vol. 8, no. 187, pp. 102–107, 2019.
F. Farnoodi, H. Amiri, M. Arefi, K. A. Nia, A. Akbar, and P. Fard, “Comparing the Effectiveness of Ellis ’ Rational-Emotive- Behavior Therapy ( REBT ) and Glasser ’ s Reality Therapy ( RT ) on Reducing Depression Symptoms in Hemodialysis Patients and Control Group,” Arch. Pharm. Pract., vol. 11, pp. 161–167, 2020.
M. J. Turner and J. B. Barker, “Examining the Effects of Rational Emotive Behavior Therapy (REBT) on the Irrational Beliefs of Blue-Chip Professionals,” J. Ration. - Emotive Cogn. - Behav. Ther., vol. 33, no. 1, pp. 17–36, 2015, doi: 10.1007/s10942-014-0200-9.
S. L. Anderson, “The effects of a rational emotive behavior therapy intervention on irrational beliefs and burnout among middle school teachers in the state of Iowa.,” Diss. Abstr. Int. Sect. A Humanit. Soc. Sci., vol. 61, no. 6-A, p. 2193, 2000, [Online]. Available: http://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc3&NEWS=N&AN=2000-95023-027
Turner, MJ and Ewen, and D and Barker, “An Idiographic Single-Case Study Examining the Use of Rational Emotive Behavior Therapy ( REBT ) with Three Amateur Golfers to Alleviate Social Anxiety . Journal of Applied Sport Psychology . ISSN 1041-320,” J. Appl. Sport Psychol. , no. ISSN 1041-3200, 2018.
S. L. & G. M. Vasilia Peppa, “Human-computer interaction and usability testing application adoption.pdf,” Glob. J. Eng. Educ., vol. 14, no. 1, p. 7, 2012.
A. G. Lopes, “Using Research Methods in Human Computer Interaction to Design Technology for Resilience,” J. Inf. Syst. Technol. Manag., vol. 13, no. 3, pp. 363–388, 2016, doi: 10.4301/s1807-17752016000300001.
E. Karyotaki et al., “Examining the effectiveness of a web-based intervention for symptoms of depression and anxiety in college students: Study protocol of a randomised controlled trial,” BMJ Open, vol. 9, no. 5, pp. 1–11, 2019, doi: 10.1136/bmjopen-2018-028739.
C. Popa and R. Predatu, “The effect of an integrative CBT/REBT intervention in improving emotional functioning and emotional stability in Romanian medical students,” J. Evidence-Based Psychother., vol. 19, no. 1, pp. 59–71, 2019, doi: 10.24193/jebp.2019.1.4.
A. Venkatesan, L. Rahimi, M. Kaur, and C. Mosunic, “Digital cognitive behavior therapy intervention for depression and anxiety: Retrospective study,” JMIR Ment. Heal., vol. 7, no. 8, pp. 1–13, 2020, doi: 10.2196/21304.
M. D. Attridge, R. C. Morfitt, D. J. Roseborough, and E. R. Jones, “Internet-based cognitive-behavioral therapy for college students with anxiety, depression, social anxiety, or insomnia: four single-group longitudinal studies of archival commercial data and replication of employee user study,” JMIR Form. Res., vol. 4, no. 7, 2020, doi: 10.2196/17712.
N. R. Hemmings et al., “Development and feasibility of a digital acceptance and commitment therapy⇓based intervention for generalized anxiety disorder: Pilot acceptability study,” JMIR Form. Res., vol. 5, no. 2, 2021, doi: 10.2196/21737.
McCloud T, Jones R, Lewis G, Bell V, Tsakanikos E, Effectiveness of a Mobile App Intervention for Anxiety and Depression Symptoms in University Students: Randomized Controlled Trial, JMIR Mhealth Uhealth 2020;8(7):e15418, URL: ,ttps://mhealth.jmir.org/2020/7/e15418, DOI: 10.2196/15418
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
