Rokicki, S., Cohen, J., Salomon, J. A. & Fink, G. Impact of a text-messaging program on adolescent reproductive health: a cluster-randomized trial in Ghana. Am. J. Public Health 107, 298–305 (2017).
Google Scholar
Nuwamanya, E. et al. Effectiveness of a mobile phone application to increase access to sexual and reproductive health information, goods, and services among university students in Uganda: a randomized controlled trial. Contracept. Reprod. Med. 5, 31 (2020).
Google Scholar
Haruna, H. et al. Improving sexual health education programs for adolescent students through game-based learning and gamification. Int. J. Environ. Res Public Health 15, 2027 (2018).
Google Scholar
Sharma, A. et al. Pilot implementation of a user-driven, web-based application designed to improve sexual health knowledge and communication among young Zambians: mixed methods study. J. Med. Internet Res. 24, e37600 (2022).
Google Scholar
Harrington, E. K. et al. An mHealth SMS intervention on postpartum contraceptive use among women and couples in Kenya: a randomized controlled trial. Am. J. Public Health 109, 934–941 (2019).
Google Scholar
United Nations Development Programme. Information asymmetries in the digital sexual and reproductive health space. www.undp.org/publications/information-asymmetries-digital-sexual-and-reproductive-health-space (accessed 8 August 2023).
World Health Organization. Global strategy on digital health 2020–2025. www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf (2021).
Prata, N., Weidert, K. & Sreenivas, A. Meeting the need: youth and family planning in sub-Saharan Africa. Contraception 88, 83–90 (2013).
Google Scholar
Chandra-Mouli, V. & Akwara, E. Improving access to and use of contraception by adolescents: what progress has been made, what lessons have been learnt, and what are the implications for action? Best Pract. Res. Clin. Obstet. Gynaecol. 66, 107–118 (2020).
Google Scholar
Joint United Nations Programme on HIV/AIDS (UNAIDS). Young people and HIV. www.unaids.org/sites/default/files/media_asset/young-people-and-hiv_en.pdf (accessed 30 November 2023).
Joint United Nations Programme on HIV/AIDS (UNAIDS). Confronting inequalities: lessons for pandemic responses from 40 years of AIDS. www.unaids.org/sites/default/files/media_asset/2021-global-aids-update_en.pdf (accessed 30 November 2023).
Rosenberg, M. et al. Relationship between school dropout and teen pregnancy among rural South African young women. Int. J. Epidemiol. 44, 928–936 (2015).
Google Scholar
Glynn, J. R. et al. Early school failure predicts teenage pregnancy and marriage: a large population-based cohort study in northern Malawi. PLoS ONE 13, e0196041 (2018).
Google Scholar
Stoner, M. C. et al. The effect of school attendance and school dropout on incident HIV and HSV-2 among young women in rural South Africa enrolled in HPTN 068. AIDS 31, 2127–2134 (2017).
Google Scholar
Sunny, B. S. et al. Lusting, learning and lasting in school: sexual debut, school performance and dropout among adolescents in primary schools in Karonga district, northern Malawi. J. Biosoc. Sci. 51, 720–736 (2019).
Google Scholar
Ahinkorah, B. O., Ameyaw, E. K. & Seidu, A. A. Socio-economic and demographic predictors of unmet need for contraception among young women in sub-Saharan Africa: evidence from cross-sectional surveys. Reprod. Health 17, 163 (2020).
Google Scholar
Kassa, G. M., Arowojolu, A. O., Odukogbe, A. A. & Yalew, A. W. Prevalence and determinants of adolescent pregnancy in Africa: a systematic review and Meta-analysis. Reprod. Health 15, 195 (2018).
Google Scholar
Gunawardena, N., Fantaye, A. W. & Yaya, S. Predictors of pregnancy among young people in sub-Saharan Africa: a systematic review and narrative synthesis. BMJ Glob. Health 4, e001499 (2019).
Google Scholar
Nolan, C. et al. Design and impact evaluation of a digital reproductive health program in Rwanda using a cluster randomized design: study protocol. BMC Public Health 20, 1701 (2020).
Google Scholar
Hémono, R. et al. Digital self-care for improved access to family planning and reproductive health services among adolescents in Rwanda: preliminary findings from a pilot study of CyberRwanda. Sex. Reprod. Health Matters 29, 2110671 (2022).
Google Scholar
Abiodun, O. et al. A single-blind, parallel design RCT to assess the effectiveness of SMS reminders in improving art adherence among adolescents living with HIV (STARTA trial). J. Adolesc. Health 68, 728–736 (2021).
Google Scholar
Dodd, S. et al. School-based peer education interventions to improve health: a global systematic review of effectiveness. BMC Public Health 22, 2247 (2022).
Google Scholar
Blakemore, S. J. & Robbins, T. W. Decision-making in the adolescent brain. Nat. Neurosci. 15, 1184–1191 (2012).
Google Scholar
Reiter, A. M. F., Suzuki, S., O’Doherty, J. P., Li, S. C. & Eppinger, B. Risk contagion by peers affects learning and decision-making in adolescents. J. Exp. Psychol. Gen. 148, 1494–1504 (2019).
Google Scholar
Copeland, K. T., Checkoway, H., McMichael, A. J. & Holbrook, R. H. Bias due to misclassification in the estimation of relative risk. Am. J. Epidemiol. 105, 488–495 (1977).
Google Scholar
Yland, J. J., Wesselink, A. K., Lash, T. L. & Fox, M. P. Misconceptions About the Direction of Bias From Nondifferential Misclassification. Am. J. Epidemiol. 191, 1485–1495 (2022).
Google Scholar
Nwaogwugwu, J. C. & Isara, A. R. Utilization of digital media for sexual and reproductive health information among in-school adolescents in Benin city, Nigeria. West Afr. J. Med 39, 949–957 (2022).
Google Scholar
McCoy, S., Packel, L., Hunter, L. & Hémono R. CyberRwanda analysis plan. (2021).
Moher, D. et al. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. J. Clin. Epidemiol. 63, e1–e37 (2010).
Google Scholar
Campbell, M. K., Piaggio, G., Elbourne, D. R. & Altman, D. G. Consort 2010 statement: extension to cluster randomised trials. BMJ 345, e5661 (2012).
Google Scholar
Mbarushimana, V., Goldstein, S. & Conco, D. N. ‘Not just the consequences, but also the pleasurable sex’: a review of the content of comprehensive sexuality education for early adolescents in Rwanda. BMC Public Health 23, 49 (2023).
Google Scholar
Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991).
Google Scholar
Godin, G. & Kok, G. The theory of planned behavior: a review of its applications to health-related behaviors. Am. J. Health Promot. 11, 87–98 (1996).
Google Scholar
Hémono, R. et al. CyberRwanda’s pathway to impact: results from a cluster-randomized trial of adolescent family planning knowledge, beliefs, self-efficacy, and behavior. J. Adolesc. Health 74, 1239–1248 (2024).
Google Scholar
StataCorp. Stata Statistical Software: release 17. (2021).
Carril, A. Dealing with misfits in random treatment assignment. Stata J. 17, 652–667 (2017).
Google Scholar
Andersson, N. Community-led trials: Intervention co-design in a cluster randomised controlled trial. BMC Public Health 17, 397 (2017).
Google Scholar
Qualtrics (2019).
World Health Organization. SDG indicator 3.7.1: proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methods. www.who.int/data/gho/indicator-metadata-registry/imr-details/4988 (accessed 2 February 2024).
Croft, T. N. et al. Guide to DHS statistics. The Demographic and Health Surveys Program. www.dhsprogram.com/pubs/pdf/DHSG1/Guide_to_DHS_Statistics_DHS-8.pdf (accessed 2 February 2024).
Arnold, B. F., Hogan, D. R., Colford, J. M. & Hubbard, A. E. Simulation methods to estimate design power: an overview for applied research. BMC Med. Res. Method. 11, 94 (2011).
Google Scholar
National Institute of Statistics of Rwanda, Ministry of Finance and Economic Planning, Ministry of Health & The DHS Program. Rwanda Demographic and Health Survey, 2014–15: final report. dhsprogram.com/pubs/pdf/FR316/FR316.pdf (2016).
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).
Naimi, A. I. & Whitcomb, B. W. Estimating risk ratios and risk differences using regression. Am. J. Epidemiol. 189, 508–510 (2020).
Google Scholar
link