Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth
Abstract
:1. Introduction
2. Method
2.1. Search Strategy
2.2. Data Extraction
3. Results
3.1. Description of Studies
3.2. Intervention Effects
3.3. Adherence and Drop-Out
3.4. Intention to Seek Help
3.5. Tailoring the Intervention
3.6. Symptom Severity
3.7. Risk Monitoring
3.8. Acceptability
3.9. Treatment Engagement
3.10. Time Spent by Therapist
3.11. Therapeutic Relation
3.12. Facilities for Computerized Interventions
4. Discussion
4.1. Strengths and Limitations
4.2. Suggestions for Future Research
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Study | Country | Intervention | Target Population | Study Participants | Study Type | Design | Outcome Measure |
---|---|---|---|---|---|---|---|
Abeles et al. (2009) [30] | United Kingdom | Unguided computer-based CBT | Youth (12–16 years) with depressive disorders | aN = 23 | Effect evaluation | Pre-post design without control condition | Intervention effects |
Berg et al. (2019) [39] | Sweden | Guided internet-based CBT vs. monitoring and non-specific counseling | Youth (15–19 years) with depressive disorders | aN = 70 | Effect evaluation | RCT | Mental health literacy |
Bobier et al. (2013) [50] | New Zealand | Self-help CBT-based computer game | Youth (16–19 years) admitted for severe psychiatric disorder (among which depressive disorders) | aN = 20 | Feasibility, usability and/or acceptability evaluation; | Pre-post design without control condition | Acceptability; adherence and dropout |
Bradford & Rickwood (2014) [60] | Australia | N/a b | Youth (15–19 years) with mood disorders | aN = 231 | Evaluation of preferred modes of help seeking | Cross-sectional study | Acceptability; intention to seek help |
Bradley et al. (2012) [31] | Canada | Unguided internet-based CBT | Youth (15–18 years) with depressive symptoms | aN = 13 | Feasibility, usability and/or acceptability evaluation | Pre-post design without control condition | Acceptability; intention to seek help; tailoring the intervention |
Cheek et al. (2014) [51] | Australia | Self-help CBT-based computer game | Youth (12–19 years) with depressive symptoms c | Youth (13–18) recruited from the general population N = 16 | Feasibility, usability and/or acceptability evaluation | Pre-post design without control condition | Acceptability |
Davidson et al. (2014) [32] | United States | Unguided internet-based behavioral activation | Youth at risk for post-disaster mental health problems among which mood disorders c | Study 1: Youth (12–17 years) recruited from the general population N = 24 Study 2: a N = 291 | Feasibility, usability and/or acceptability evaluation | Cross-sectional | Acceptability; treatment engagement; time spent; tailoring the intervention |
De Vos et al. (2017) [46] | Netherlands | Blended CBT | Youth (12–18 years) with depressive disorders | aN = 32 | Feasibility, usability and/or acceptability evaluation | Pre-post design without control condition | Acceptability; adherence and dropout; treatment engagement; time spent |
Fleming et al. (2012) [52] | New Zealand | Self-help CBT-based computer game vs. wait list control | Youth (13–16 years) with depressive symptoms | aN = 32 | Effect evaluation | Pragmatic RCT | Intervention effects; adherence and dropout; intention to seek help; risk monitoring |
Forchuk et al. (2016) [58] | Canada | Internet-based monitoring tool | Youth (16–21 years) in mental health care with depressive disorders | Mental health care providers from acute and tertiary care facilities N = 9 | Feasibility, usability and/or acceptability evaluation | Qualitative study | Acceptability; treatment engagement; time spent; therapeutic relation; symptoms severity |
Johnston et al. (2014) [40] | Australia | Therapist-guided internet-based CBT | Young adults (18–24 years) with mild or moderate depressive symptoms | aN = 18 | Effect evaluation | Pre-post design without control condition | Intervention effects; acceptability; adherence and dropout |
Kobak et al. (2015) [47] | United States | Blended CBT vs. treatment as usual | Youth (12–17 years) with mood disorders | aN = 76 | Feasibility, usability and/or acceptability evaluation | RCT | Intervention effects; acceptability; adherence and dropout; therapeutic relation; mental health literacy |
Kurki et al. (2018) [41] | Finland | Guided internet-based intervention | Youth (15–17 years) with depressive or anxiety disorders | Registered nurses from outpatient clinics for adolescent psychiatry N = 9 | Feasibility, usability and/or acceptability evaluation | Qualitative study | Symptoms severity; risk monitoring |
Kurki et al. (2011) [61] | Finland | N/a b | Youth (13–18 years) in mental health care with depressive symptoms | Registered nurses from outpatient clinics for adolescent psychiatry N = 14 | Evaluation of preferred modes of help seeking | Qualitative study | Therapeutic relation; symptoms severity; facilities for computerized interventions |
Logsdon et al. (2018) [33] | United States | Unguided internet-based intervention vs. no intervention control | Adolescent mothers (12–21 years) with depressive symptoms | aN = 292 | Effect evaluation | Pre-post design with control condition | Intervention effects; acceptability; intention to seek help |
Lokkerbol et al. (2018) [62] | Netherlands | N/a b | Young adults and adults (from age 18) with depressive disorders | aN = 165 | Evaluation of preferred modes of help seeking | Cross-sectional study | Acceptability |
Lucassen Hatcher et al. (2015) [53] | New Zealand | Self-help CBT-based computer game | Youth (13–19 years) from sexual minorities with depressive symptoms | aN = 25 | Feasibility, usability and/or acceptability evaluation | Qualitative study | Acceptability |
Lucassen et al. (2013) [54] | New Zealand | Self-help CBT-based computer game | Youth (16–21 years) from sexual minorities with depressive symptoms | aN = 10 | Feasibility, usability and/or acceptability evaluation | Qualitative study | Acceptability |
Lucassen, Merry et al. (2015) [55] | New Zealand | Self-help CBT-based computer game | Youth (13–19 years) from sexual minorities with depressive symptoms | aN = 21 | Feasibility, usability and/or acceptability evaluation | Pre-post design without control condition | Intervention effects; acceptability; adherence and dropout; mental health literacy |
Lucassen et al. (2018) [56] | New Zealand | Self-help CBT-based computer game | Youth (15–21 years) from sexual minorities with depressive symptoms | LGBT+ young people N = 21 Professionals in health and social care N = 6 | Feasibility, usability and/or acceptability evaluation | Qualitative study | Acceptability |
Merry et al. (2012) [57] | New Zealand | Self-help CBT-based computer game | Youth (12–19 years) with depressive symptoms | aN = 187 | Effect evaluation | RCT | Intervention effects; acceptability; adherence and dropout |
O’Kearney et al. (2006) [42] | Australia | Teacher-guided internet-based CBT vs. standard personal developmental activities | Male youth (15–16 years) with depressive symptoms | aN = 87 | Effect evaluation | Pre-post design with control condition | Intervention effects |
Rickhi et al. (2015) [34] | Canada | Unguided spirituality informed internet-based intervention vs. wait list control | Youth (13–18 years) and young adults (19–24 years) with depressive disorders | aN = 31 and N = 31 | Effect evaluation | RCT | Intervention effects; adherence and dropout |
Sethi (2013) [48] | Australia | Unguided internet-based CBT vs. face-to-face CBT vs. blended CBT vs. no intervention control | Young adults (18–25 years) with mild or moderate depressive or anxiety symptoms | aN = 89 | Feasibility, usability and/or acceptability evaluation | RCT | Intervention effects; adherence and dropout |
Sethi et al. (2010) [49] | Australia | Unguided internet-based CBT vs. face-to-face CBT vs. blended CBT vs. no intervention control | Youth and young adults (15–25 years) with mild or moderate depressive or anxiety symptoms | aN = 38 | Effect evaluation | RCT | Intervention effects |
Smith et al. (2015) [35] | United Kingdom | Unguided computer-based CBT vs. wait list control | Youth (12–16 years) with depressive symptoms | aN = 112 | Effect evaluation | RCT | Intervention effects |
Stallard et al. (2011) [43] | United Kingdom | Psychology assistant-guided computer-based CBT vs. wait list control | Youth (11–16 years) with depressive or anxiety disorders | aN = 20 | Feasibility, usability and/or acceptability evaluation | RCT | Intervention effects; acceptability; adherence and dropout; therapeutic relation |
Stasiak et al. (2014) [36] | New Zealand | Unguided computer-based CBT game vs. computer-based psychoeducation | Youth (13–18 years) with depressive symptoms | aN = 34 | Effect evaluation | RCT | Intervention effects; acceptability; adherence and dropout |
Sundram et al. (2017) [59] | New Zealand | Internet-based monitoring tool | Youth (12–19 years) with mild or moderate depressive symptoms | Youth (12–19 years) N = 29 Clinicians (GPs and school’s health staff) N = 50 | Feasibility, usability and/or acceptability evaluation | Qualitative study | Acceptability; treatment engagement; time spent; therapeutic relation; risk monitoring |
Topooco et al. (2018) [44] | Sweden | Guided internet-based CBT vs. monitoring and non-specific counseling | Youth (15–19 years) with depressive disorders | aN = 70 | Effect evaluation | RCT | Intervention effects; adherence and dropout; treatment engagement; time spent; therapeutic relation |
Van der Zanden et al. (2012) [45] | Netherlands | Guided internet-based CBT vs. wait list control | Youth (16–25 years) with depressive symptoms | aN = 244 | Effect evaluation | RCT | Intervention effects; adherence and dropout |
Vangberg et al. (2012) [37] | Norway | Unguided internet-based CBT | Youth (15–20 years) with depressive symptoms | aN = 1239 | Feasibility, usability and/or acceptability evaluation | Cross-sectional study | Acceptability |
Wright et al. (2017) [38] | United Kingdom | Unguided computer-based CBT vs. self-help websites | Youth (12–18 years) with depressive symptoms | aN = 91 | Effect evaluation | RCT | Intervention effects; adherence and dropout |
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Rasing, S.P.A.; Stikkelbroek, Y.A.J.; Bodden, D.H.M. Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth. Int. J. Environ. Res. Public Health 2020, 17, 153. https://doi.org/10.3390/ijerph17010153
Rasing SPA, Stikkelbroek YAJ, Bodden DHM. Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth. International Journal of Environmental Research and Public Health. 2020; 17(1):153. https://doi.org/10.3390/ijerph17010153
Chicago/Turabian StyleRasing, Sanne P. A., Yvonne A. J. Stikkelbroek, and Denise H. M. Bodden. 2020. "Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth" International Journal of Environmental Research and Public Health 17, no. 1: 153. https://doi.org/10.3390/ijerph17010153
APA StyleRasing, S. P. A., Stikkelbroek, Y. A. J., & Bodden, D. H. M. (2020). Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth. International Journal of Environmental Research and Public Health, 17(1), 153. https://doi.org/10.3390/ijerph17010153