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Record W4210551455 · doi:10.2196/33551

Internet-Delivered Interventions for Depression and Anxiety Symptoms in Children and Young People: Systematic Review and Meta-analysis

2022· review· en· W4210551455 on OpenAlexaffvenue
Nora Eilert, Rebecca Wogan, Aisling Leen, Derek Richards

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2022
Typereview
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsTrinity College
Fundersnot available
KeywordsAnxietyPsycINFOPsychological interventionMeta-analysisMental healthRandomized controlled trialSystematic reviewDepression (economics)MedicineIntervention (counseling)Publication biasMEDLINEClinical psychologyPsychiatryPsychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Mental health difficulties in children and adolescents are highly prevalent; however, only a minority receive adequate mental health care. Internet-delivered interventions offer a promising opportunity to increase access to mental health treatment. Research has demonstrated their effectiveness as a treatment for depression and anxiety in adults. This work provides an up-to-date examination of the available intervention options and their effectiveness for children and young people (CYP). OBJECTIVE: In this systematic review and meta-analysis, we aimed to determine the evidence available for the effectiveness of internet-delivered interventions for treating anxiety and depression in CYP. METHODS: Systematic literature searches were conducted throughout November 2020 using PubMed, PsycINFO, and EBSCO academic search complete electronic databases to find outcome trials of internet-delivered interventions treating symptoms of anxiety and/or depression in CYP by being either directly delivered to the CYP or delivered via their parents. Studies were eligible for meta-analysis if they were randomized controlled trials. Risk of bias and publication biases were evaluated, and Hedges g between group effect sizes evaluating intervention effects after treatment were calculated. Meta-analyses used random-effects models as per protocol. RESULTS: A total of 23 studies met the eligibility criteria for the systematic review, of which 16 were included in the meta-analyses, including 977 participants in internet-delivered treatment conditions and 1008 participants in control conditions across 21 comparisons. Random-effects models detected a significant small effect for anxiety symptoms (across 20 comparisons; Hedges g=-0.25, 95% CI -0.38 to -0.12; P<.001) and a small but not significant effect for depression (across 13 comparisons; Hedges g=-0.27, 95% CI -0.55 to 0.01; P=.06) in favor of internet-delivered interventions compared with control groups. Regarding secondary outcomes, there was a small effect of treatment across 9 comparisons for impaired functioning (Hedges g=0.52, 95% CI 0.24-0.80; P<.001), and 5 comparisons of quality of life showed no effect (Hedges g=-0.01, 95% CI -0.23 to 0.21; P=.94). CONCLUSIONS: The results show that the potential of internet-delivered interventions for young people with symptoms of anxiety or depression has not been tapped into to date. This review highlights an opportunity for the development of population-specific interventions and their research to expand our current knowledge and build an empirical base for digital interventions for CYP. TRIAL REGISTRATION: PROSPERO CRD42020220171; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220171.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.036
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0210.031
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.418
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2022
Admission routes2
Has abstractyes

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