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Record W7116978019 · doi:10.2196/preprints.89328

Digital interventions for adolescent and young adult sexual and reproductive health knowledge and behaviour: A systematic review (2017–2023) (Preprint)

2025· article· W7116978019 on OpenAlexaboutno aff
Olivia Vaikla, Angela Karellis, Elizabeth Woolhouse, Roni Deli-Houssein, Melisa Eraslan, Hani Rukh-E-Qamar, Suma Nair, Qihuang Zhang, Nitika Pant Pai

Bibliographic record

Venuenot available
Typearticle
Language
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionTelehealthReproductive healthRandomized controlled trialCondomSystematic reviewDigital healthYoung adult

Abstract

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BACKGROUND Digital platforms provide accessible innovative solutions to bridge gaps in sexual and reproductive health (SRH) for adolescents and young adults. Given barriers to high-quality, evidence-based SRH education, digital interventions offer promising strategies to enhance knowledge and influence behaviour, supporting universal SRH access goals. OBJECTIVE This systematic review synthesizes evidence on the impact of digital SRH innovations on behaviour and knowledge. METHODS Five reviewers independently searched PubMed and Embase (June 1st, 2017–April 15th, 2023) for studies on digital SRH innovations for adolescents and young adults (10-30 years). Of 11,156 citations screened, 112 studies were included. Given heterogeneity in methods and outcomes, findings were narratively synthesized. Study quality was assessed using the Newcastle-Ottawa Scale, Cochrane Risk of Bias Tool 2, and Cochrane Risk of Bias in Non-randomized Studies – of Interventions Tool. RESULTS 112 studies reported data from 50,658 individuals across 24 countries with most studies conducted in the United States (US; 66.1%, 74/112). Studies evaluated mobile applications (n=24), web-based interventions (n=22), text messaging (n=18), multimodal interventions (n=14), websites (n=11), games (n=9), videos (n=7), telehealth (n=3), and other digital interventions (n=4). Randomized controlled trials (RCTs) and pilot RCTs comprised 65.2% (73/112) of studies, while 34.8% (39/112) were quasi-experimental, cross-sectional, or cohort studies. Behavioural outcomes were reported in 78 studies (69.6%) and knowledge in 70 studies (62.5%). Multimodal interventions, combining at least two digital components to deliver SRH content, proved most effective. A trial demonstrated increased pre-exposure prophylaxis adherence (Mean 0.02 to 0.05, possible range: 0-1, P<.001) and reduced condom use errors (Mean 4.04 to 3.70, possible range: 0-9, P<.05). General SRH knowledge improved in all studies where assessed (38.6%, 27/70), with increases ranging from 8.1%-76.0% reported in Nicaragua, Thailand, and the United States. Behavioural changes varied, with notable United States-based trials reporting increased STI testing (P=.016), improved contraception and condom use (IRR=1.39 [95% CI 1.09–2.11]), higher clinic attendance and follow-up (aOR=1.6 [1.1–2.3], P=.01), and reduced sexual risk-taking (PR=0.83 [0.70–0.99], P=.04). Quality varied across studies. CONCLUSIONS Digital interventions improve SRH knowledge, while promoting safer behaviours among adolescents and young adults. Future research should prioritize large-scale trials with culturally tailored approaches for broader impact. While these tools demonstrated significant promise, wide variability in outcomes underscores the need for a standardized evaluation framework that will ensure reliable reporting and comparisons across studies to steer normative guidance. CLINICALTRIAL PROSPERO CRD42021258889

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)0.010
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.008
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.068
GPT teacher head0.452
Teacher spread0.383 · 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 designSystematic review
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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