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A Meta-Analysis of the Impact of Universal and Indicated Preventive Technology-Delivered Interventions for Higher Education Students
Abstract
The uses of technology-delivered mental health treatment options, such as interventions delivered via computer, smart phone, or other communication or information devices, as opposed to primarily face-to-face interventions, are proliferating. However, the literature is unclear about their effectiveness as preventive interventions for higher education students, a population for whom technology-delivered interventions (TDIs) might be particularly fitting and beneficial. This meta-analytic review examines technological mental health prevention programs targeting higher education students either without any presenting problems (universal prevention) or with mild to moderate subclinical problems (indicated prevention). A systematic literature search identified 22 universal and 26 indicated controlled interventions, both published and unpublished, involving 4763 college, graduate, or professional students. As hypothesized, the overall mean effect sizes (ESs) for both universal (0.19) and indicated interventions (0.37) were statistically significant and differed significantly from each other favoring indicated interventions. Skill-training interventions, both universal (0.21) and indicated (0.31), were significant, whereas non-skill-training interventions were only significant among indicated (0.25) programs. For indicated interventions, better outcomes were obtained in those cases in which participants had access to support during the course of the intervention, either in person or through technology (e.g., email, online contact). The positive findings for both universal and indicated prevention are qualified by limitations of the current literature. To improve experimental rigor, future research should provide detailed information on the level of achieved implementation, describe participant characteristics and intervention content, explore the impact of potential moderators and mechanisms of success, collect post-intervention and follow-up data regardless of intervention completion, and use analysis strategies that allow for inclusion of cases with partially missing data.
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“Some studies found larger effects indicated than for universal or selective Internet-delivered prevention approaches for adolescents and adults [62, 64].”
From Efficacy of a transdiagnostic Internet prevention approach in adolescents (EMPATIA study): study protocol of a randomized controlled trial (2024) · cites this paper as [64]
In the citing paper
“Several systematic reviews and meta-analyses have attested that digital interventions have the potential to improve mental well-being among this population [14,15,27-29]”
From Optimization of a Transdiagnostic Mobile Emotion Regulation Intervention for University Students: Protocol for a Microrandomized Trial (2023) · cites this paper as [27]
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“[49] conducted a meta-analytic review of evidence on the impact of universal and indicated technology-delivered interventions (TDIs) targeting mental health outcomes in 4763 higher education students, including randomized and quasi-experimental study designs (rated as moderate methodological quality).”
Background
Metadata
- Authors
- Conley, C. S., Durlak, J. A., Shapiro, J. B., Kirsch, A. C., & Zahniser, E.
- Affiliations
- Loyola University Chicago (US)
- Corresponding author
- Conley, Colleen S.
- Venue
- Prevention Science
- Published
- 2016-05-26
- Volume
- 17
- Issue
- 6
- Pages
- 659-678
- ISSN
- 1389-4986 (ISSN-L)
- 1573-6695
- OpenAlex
- W2401775412
- Cited by
- 110
- References
- 97
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 11 · 2023: 15 · 2022: 18 · 2021: 13 · 2020: 10 · 2019: 8 · 2018: 8 · 2017: 5
- FWCI
- 1.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Prevention Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- technology-based interventions, mental health prevention, universal prevention, indicated prevention, university students, online mental health services, implementation fidelity
- MeSH terms
- Female, Humans, Male, Mental Health, Preventive Medicine, Students, Telecommunications, Universities
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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