Hostname: page-component-848d4c4894-x5gtn Total loading time: 0 Render date: 2024-05-20T19:36:19.764Z Has data issue: false hasContentIssue false

A Pragmatic Randomized Controlled Trial of Computerized CBT (SPARX) for Symptoms of Depression among Adolescents Excluded from Mainstream Education

Published online by Cambridge University Press:  05 December 2011

Theresa Fleming*
The University of Auckland, New Zealand
Robyn Dixon
The University of Auckland, New Zealand
Christopher Frampton
University of Otago, Christchurch, New Zealand
Sally Merry
The University of Auckland, New Zealand
Reprint requests to Theresa Fleming, The University of Auckland, Department of Psychological Medicine, Private Bag 92019, Auckland 1142, New Zealand. E-mail:


Background: Adolescents excluded from mainstream education have high mental health needs. The use of computerized Cognitive Behavioural Therapy (cCBT) has not been investigated with this group. Aims: To test the efficacy of the SPARX cCBT programme for symptoms of depression among adolescents in programmes for students excluded or alienated from mainstream education. Method: Adolescents (32; 34% Maori, 38% Pacific Island, 56% male) aged 13–16 with Child Depression Rating Scale Revised (CDRS-R) scores indicating possible through to almost certain depressive disorder were randomized to SPARX to be completed over the following 5 weeks (n = 20) or to waitlist control (n = 12). Assessments were at baseline, 5 weeks and 10 weeks. Those in the wait condition were invited to complete SPARX after the 5 week assessment. Results: Most participants (n = 26, 81%) completed at least 4 levels of SPARX and 22 (69%) completed all 7 levels. Among the 30 (94%) participants who began treatment as randomized and provided 5-week data, significant differences were found between cCBT and wait groups on the CDRS-R (baseline to 5-week mean change –14.7 versus –1.1, p<.001), remission (78% vs. 36%, p = .047) and on the Reynolds Adolescent Depression Scale (–4.6 vs. +3.2 p = .05) but not on other self-rating psychological functioning scales. In intent-to-treat analyses CDRS-R changes and remission remained significant. Gains were maintained at 10-week follow-up. Conclusions: SPARX appears to be a promising treatment for students with symptoms of depression who are in alternative schooling programmes for those excluded from mainstream education.

Research Article
Copyright © British Association for Behavioural and Cognitive Psychotherapies 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Abeles, P., Verduyn, C., Robinson, A., Smith, P., Yule, W. and Proudfoot, J. (2009). Computerized CBT for adolescent depression (“Stressbusters”) and its initial evaluation through an extended case series. Behavioural and Cognitive Psychotherapy, 37, 151165.CrossRefGoogle ScholarPubMed
Albert, M., MacKay, L., Stewart, D., Saewyc, E. and Centre Society, the McCreary. (2007). Making the Grade: a review of Alternative Education programs in British Columbia. Vancouver, BC: McCreary Centre Society.Google Scholar
Andrews, G., Cuijpers, P., Craske, M. G., McEvoy, P. and Titov, N. (2010). Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: a meta-analysis. PLoS ONE, 5, e13196.CrossRefGoogle ScholarPubMed
Brooks, S. J. and Kutcher, S. (2001). Diagnosis and measurement of adolescent depression: a review of commonly utilized instruments. Journal of Child and Adolescent Psychopharmacology 11, 341376.CrossRefGoogle ScholarPubMed
Clark, T. C., Smith, J. M., Raphael, D., Jackson, C., Fleming, T., Denny, S., et al. (2010). Youth’09: the health and wellbeing of young people in Alternative Education. Auckland: The University of Auckland.Google Scholar
Denny, S., Clark, T. and Watson, P. (2004). The health of Alternative Education students compared to secondary students: a New Zealand study. The New Zealand Medical Journal, 117, 112.Google Scholar
Endicott, J., Nee, J., Yang, R. and Wohlberg, C. (2006). Pediatric Quality of Life Enjoyment and Satisfaction Questionnaire (PQ-LES-Q): reliability and validity. Journal of the American Academy of Child and Adolescent Psychiatry, 45, 401407.CrossRefGoogle ScholarPubMed
Everitt, B. S. (2002). The Cambridge Dictionary of Statistics (2nd edn.). Cambridge: Cambridge University Press.Google Scholar
Fleming, T., Dixon, R. and Merry, S. (in press). “It's mean!” the views of young people alienated from mainstream education on depression, help seeking and computerised therapy. Advances in Mental Health.Google Scholar
Freudenberg, N. and Ruglis, J. (2007). Reframing school dropout as a public health issue. Preventing Chronic Disease, 4, A107.Google ScholarPubMed
Gerrits, R. S., van der Zanden, R. A. P., Visscher, R. F. M. and Conijn, B. P. (2007). Master your mood online: a preventive chat group intervention for adolescents. Australian e-Journal for the Advancement of Mental Health, 6, 111.CrossRefGoogle Scholar
Kazdin, A. E., French, N. H., Unis, A. S., Esveldt-Dawson, K. and Sherick, R. B. (1983). Hopelessness, depression, and suicidal intent among psychiatrically disturbed inpatient children. Journal of Consulting and Clinical Psychology, 51, 504510.CrossRefGoogle ScholarPubMed
Ministry of Health (2004). Ethnicity Data Protocols for the Health and Disability Sector. Wellington: Ministry of Health.Google Scholar
Myers, K. and Winters, N. C. (2002). Ten-year review of rating scales. II: scales for internalizing disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 41, 634659.CrossRefGoogle ScholarPubMed
National Institute for Health and Clinical Excellence (2005). Depression in children and young people: identification and management in primary, community and secondary care. Retrieved 1.6.2011, from Scholar
Nowicki, S. and Duke, M. P. (Eds.) (1983). The Nowicki-Strickland Lifespan Locus of Control Scales: construct validity (Vol. 2). New York: Academic Press.Google Scholar
Nowicki, S. and Strickland, B. (1973). A locus of control scale for children. Journal of Consulting and Clinical Psychology, 40, 148154.CrossRefGoogle Scholar
O'Brien, P., Thesing, A. and Herbert, P. (2001). Alternative Education: literature review and report on key informants’ experiences. Auckland: Ministry of Education.Google Scholar
O'Kearney, R., Gibson, M., Christensen, H. and Griffiths, K. M. (2006). Effects of a cognitive-behavioural internet program on depression, vulnerability to depression and stigma in adolescent males: a school-based controlled trial. Cognitive Behaviour Therapy, 35, 4354.CrossRefGoogle ScholarPubMed
O'Kearney, R., Kang, K., Christensen, H. and Griffiths, K. (2009). A controlled trial of a school-based Internet program for reducing depressive symptoms in adolescent girls. Depression and Anxiety, 26, 6572.CrossRefGoogle ScholarPubMed
Ou, S.-R. (2008). Do GED recipients differ from graduates and school dropouts? Urban Education, 43, 83117.CrossRefGoogle Scholar
Poznanski, E. O. and Mokros, H. B. (1996). Children's Depression Rating Scale-Revised: manual. Los Angeles: Western Psychological Services.Google Scholar
Reynolds, W. M. (2002). Reynolds Adolescent Depression Scale, 2nd Ed (RADS-2): Professional Manual. Lutz: Psychological Assessment Resources.Google Scholar
Richardson, T., Stallard, P. and Velleman, S. (2010). Computerised cognitive behavioural therapy for the prevention and treatment of depression and anxiety in children and adolescents: a systematic review. Clinical Child and Family Psychology Review, 13, 275290.CrossRefGoogle ScholarPubMed
Spence, S. H. (1997). Structure of anxiety symptoms among children: a confirmatory factor-analytic study. Journal of Abnormal Psychology, 106, 280297.CrossRefGoogle ScholarPubMed
Spence, S. H., Barrett, P. M. and Turner, C. M. (2003). Psychometric properties of the Spence Children's Anxiety Scale with young adolescents. Journal of Anxiety Disorders, 17, 605625.CrossRefGoogle ScholarPubMed
Stallard, P., Richardson, T., Velleman, S. and Attwood, M. (2011). Computerized CBT (Think, Feel, Do) for depression and anxiety in children and adolescents: outcomes and feedback from a pilot randomized controlled trial. Behavioural and Cognitive Psychotherapy, 39, 273284.CrossRefGoogle ScholarPubMed
Stewart, A. L. and Nápoles-Springer, A. M. (2003). Advancing health disparities research: can we afford to ignore measurement issues? Medical Care, 41, 12071220.CrossRefGoogle ScholarPubMed
Van Voorhees, B. W., Ellis, J., Stuart, S., Fogel, J. and Ford, D. E. (2005). The study of a primary care internet-based depression prevention intervention for late adolescents. The Canadian Child and Adolescent Psychiatry Review, 14, 4043.Google Scholar
Van Voorhees, B. W., Fogel, J., Reinecke, M. A., Gladstone, T., Stuart, S., Gollan, J., et al. (2009). Randomized clinical trial of an Internet-based depression prevention program for adolescents (Project CATCH-IT) in primary care: 12-week outcomes. Journal of Developmental and Behavioral Pediatrics, 30, 2337.CrossRefGoogle ScholarPubMed
Waller, R. and Gilbody, S. (2009). Barriers to the uptake of computerized cognitive behavioural therapy: a systematic review of the quantitative and qualitative evidence. Psychological Medicine, 39, 705712.CrossRefGoogle Scholar
Submit a response


No Comments have been published for this article.