Evaluating a treatment selection approach for online single‐session interventions for adolescent depression
Bibliographic Data
| ID | 21345089 |
|---|---|
| Authors | Isaac Ahuvia (0000-0003-4558-2123, Stony Brook University Stony Brook NY USA, corresponding author), Michael C Mullarkey (0000-0002-2267-2532, Stony Brook University Stony Brook NY USA), Jenna Y Sung (0000-0003-1232-7433, Stony Brook University Stony Brook NY USA), Kathryn R Fox (0000-0002-2697-7771, University of Denver Denver CO USA), Jessica L Schleider (0000-0003-2426-1953, Stony Brook University Stony Brook NY USA) |
| Year | 2023 |
| Volume | 64 |
| Issue | 12 |
| Pages | 1679-1688 |
| Publication date | 2023-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Child Psychology and Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 0021-9630 • E-ISSN: 1469-7610 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/jcpp.13822 |
| PMID | 37183368 |
| OpenAlex | W4376570097 |
| Language | EN |
| Citations received | 1 |
| References cited | 43 |
BACKGROUND: The question 'what works for whom' is essential to mental health research, as matching individuals to the treatment best suited to their needs has the potential to maximize the effectiveness of existing approaches. Digitally administered single-session interventions (SSIs) are effective means of reducing depressive symptoms in adolescence, with potential for rapid, large-scale implementation. However, little is known about which SSIs work best for different adolescents. OBJECTIVE: We created and tested a treatment selection algorithm for use with two SSIs targeting depression in high-symptom adolescents from across the United States. METHODS: Using data from a large-scale RCT comparing two evidence-based SSIs (N = 996; ClinicalTrials.gov: NCT04634903), we utilized a Personalized Advantage Index approach to create and evaluate a treatment-matching algorithm for these interventions. The two interventions were Project Personality (PP; N = 482), an intervention teaching that traits and symptoms are malleable (a 'growth mindset'), and the Action Brings Change Project (ABC; N = 514), a behavioral activation intervention. RESULTS: Results indicated no significant difference in 3-month depression outcomes between participants assigned to their matched intervention and those assigned to their nonmatched intervention. The relationship between predicted response to intervention (RTI) and observed RTI was weak for both interventions (r = .39 for PP, r = .24 for ABC). Moreover, the correlation between a participants' predicted RTI for PP and their predicted RTI for ABC was very high (r = .79). CONCLUSIONS: The utility of treatment selection approaches for SSIs targeting adolescent depression appears limited. Results suggest that both (a) predicting RTI for SSIs is relatively challenging, and (b) the factors that predict RTI for SSIs are similar regardless of the content of the intervention. Given their overall effectiveness and their low-intensity, low-cost nature, increasing youths' access to both digital SSIs may carry more public health utility than additional treatment-matching efforts
Depression (economics) · Intervention (counseling) · Matching (statistics) · Mindset · Psychiatry · Psychological intervention · Randomized controlled trial · Session (web analytics) · Artificial Intelligence · Child and Adolescent Psychosocial and Emotional Development · Clinical Psychology · Computer Science · Digital Mental Health Interventions · Health Policy Implementation Science · Internal Medicine · Medicine · Psychology
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| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |