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Record W4319461429 · doi:10.1007/s11121-023-01493-6

Subgroup Analyses of Girl2Girl, a Text Messaging-Based Teen Pregnancy Prevention Program for Sexual Minority Girls: Results from a National RCT

2023· article· en· W4319461429 on OpenAlexaff
Michele L. Ybarra, Elizabeth Saewyc, Margaret Rosario, Shira Dunsiger

Bibliographic record

VenuePrevention Science · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of British Columbia
FundersOffice of Population AffairsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human Development
KeywordsAbstinenceHealth psychologyCondomMedicineRandomized controlled trialBirth controlPregnancyDemographySexual abstinenceReproductive healthPublic healthPsychologyPopulationFamily planningFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract This study aims to investigate whether Girl2Girl, a text messaging-based pregnancy prevention program for cisgender LGB+ girls, had different effects on subgroups based on age, sexual identity, and experience with penile-vaginal sex. A total of 948 girls, 14–18 years old, were recruited nationally via social media and enrolled over the telephone. Once they completed the baseline, they were randomized to either Girl2Girl or an attention-matched control program that discussed “healthy lifestyle” topics (e.g., self-esteem). Both programs were 5 months long: Girls received daily messages for 8 weeks, and then went through a “latent” period of 3 months, and finished with a 1-week review. Outcome measures included condom-protected sex, uptake of other types of birth control, abstinence, and pregnancy. Measures were collected at baseline; 3-month, 6-month, 9-month, and 12-month post-intervention end, which was 17 months after enrollment. Effect modification was examined using longitudinal mixed effects models. Overall, results suggested significant moderating effects of age, (f2 = .12), sexual identity (f2 < .14), and sexual experience (f2 = .11) on rates of condom use and use of other contraception. Although there were no significant moderating effects on pregnancy, abstinence, or intentions to use condoms, use birth control, or be abstinent, (p’s > .16), patterns of effects were in the same direction as for significant findings. For example, at 9-month post-intervention, among those who identified as bisexual, the incidence rate of protected sex events was 39% higher for intervention vs. control (IRR = 1.39, 95% CI: 1.06–2.70), adjusting for baseline rate of condom use and sexual experience. Similarly, at 12 months, among bisexual participants, intervention participants had a significantly higher IRR of condom-protected sexual events (IRR = 2.65, 95% CI: 1.31–5.34). There were also higher odds of uptake of birth control use other than condoms for intervention vs. control at 6- (OR = 1.10, 95% CI: 1.01–1.77), 9 m (OR = 1.11, 95% CI: 1.07–1.89), and 12-month (OR = 1.13, 95% CI: 1.07–1.78) follow-up. Girl2Girl appears to be particularly effective for older adolescents, bisexual girls, and those who have already had penile-vaginal sex. No one single approach is going to affect teen pregnancy. Instead, it is more likely that different intervention content and delivery methods will be more accessible and salient to some but not other youth. Understanding for whom the intervention works is just as important as understanding for whom the intervention does not, as this can inform opportunities for future intervention development. Clinical Trial Registration: ClinicalTrials.gov ID# NCT03029962.

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)0.019
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.042
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.012
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.389
GPT teacher head0.574
Teacher spread0.185 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations3
Published2023
Admission routes1
Has abstractyes

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