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Artificial Intelligence and Digital Technologies in Family and Parenting Contexts

Year 2026, Volume: 10 Issue: 1, 149 - 156, 31.01.2026
https://doi.org/10.30621/jbachs.1868255

Abstract

Artificial intelligence (AI) and digital technologies are increasingly influencing family life, parenting practices, and pediatric health and mental health services. Applications include AI-enabled parenting support tools, mobile health interventions, digital therapeutics, remote monitoring systems, and algorithm-based platforms for neurodevelopmental and psychiatric assessment. While these technologies offer opportunities to enhance parental support, personalize care, and improve access to services, they also raise concerns related to ethics, equity, data privacy, and parent–child relationships. This narrative review offers an integrative overview of AI and digital technologies in family and parenting contexts, focusing on key domains such as AI-supported parenting interventions, digital health literacy, pediatric and perinatal care, neurodevelopmental and mental health assessment, digital media use, and family communication. Reported benefits, emerging risks, and unintended consequences are discussed with particular attention to parental roles, family-centered design, and implementation challenges. Overall, evidence suggests that AI-enabled tools are most effective when they are transparent, co-designed with parents and clinicians, and integrated into existing health and social care systems. Nonetheless, gaps remain regarding long-term outcomes, equitable access, ethical governance, and sustainable implementation. AI in digital parenting should therefore be viewed as a complementary resource that augments, rather than replaces, parental judgment and professional care.

References

  • Woods P, Donohoe S, Turtle L, et al. Enhancing Parenting Using AI: Exploratory Hackathon. JMIR Form Res. 2025;9:e68780.
  • Chua JYX, Choolani M, Chee CYI, et al. A Mobile App-Based Intervention (Parentbot-a Digital Healthcare Assistant) for Parents: Secondary Analysis of a Randomized Controlled Trial. J Med Internet Res. 2025;27:e64882.
  • Westrupp EM, Bates M, Bufton KJ, et al. Protocol for a randomized and a non-randomized controlled trial testing Daily Growth: a personalised 'ecological momentary intervention' parenting app for parents and carers of children aged 2-5 years. BMC Psychol. 2025;13(1):704.
  • Litwin S, Mohabir M, Kocak IS, Singh D. Creating a Parent-Informed Pediatric Emergency Department Wait Time App: Human-Centered Design Approach to Creating an AI Health Care Tool. J Particip Med. 2025;17:e66644.
  • Aloi MA, Caldwell PHY, Taba M, et al. Co-designing an online educational resource to help adolescents improve their digital health literacy. BMC Public Health. 2025 May 21;25(1):1870. doi: 10.1186/s12889-025-22949-0. Erratum in: BMC Public Health. 2025;25(1):3037.
  • Kim H, Kang JH, Kwon Y, et al. Development of a Smart Health Care Service Using Metaverse and Chatbot Technologies for Adolescents, Parents, and School Health Teachers: User-Centered Design Approach. J Med Internet Res. 2025;27:e69190.
  • Zaman S, Ashley-Norman T, Sutcliffe J, Cartledge P. A "Curriculum of Information Needs" of Parents of Children With Chronic Constipation. Clin Pediatr (Phila). 2025:99228251395563.
  • Heerman WJ, Rothman RL, Sanders LM, et al. A Digital Health Behavior Intervention to Prevent Childhood Obesity: The Greenlight Plus Randomized Clinical Trial. JAMA. 2024;332(24):2068-2080.
  • Pervanidou P, Chatzidaki E, Nicolaides NC, et al. The Impact of the ENDORSE Digital Weight Management Program on the Metabolic Profile of Children and Adolescents with Overweight and Obesity and on Food Parenting Practices. Nutrients. 2023;15(7):1777.
  • Lewkowitz AK, Schlichting LE, Ayala NK, et al. Association Between Hispanic Ethnicity and Engagement in a Remote Postpartum Blood Pressure Monitoring Programs: Secondary Analysis of a Pilot Randomized Trial. R I Med J (2013). 2024;107(6):17-18.
  • Wang G, Bennamoun H, Kwok WH, et al. Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach. J Med Internet Res. 2025;27:e68030.
  • Chung K, Jhung K, Cho HY, Park JY. Father-inclusive chatbot-based prenatal education during COVID-19 pandemic enhances maternal-fetal attachment in Korean primigravida women across levels of partner support. Sci Rep. 2025;15(1):28541.
  • Washington P, Chrisman B, Leblanc E, et al. Crowd annotations can approximate clinical autism impressions from short home videos with privacy protections. Intell Based Med. 2022;6:None.
  • Dubey I, Bishain R, Dasgupta J, et al. Using mobile health technology to assess childhood autism in low-resource community settings in India: An innovation to address the detection gap. Autism. 2024;28(3):755-769.
  • Amirova A, Rakhymbayeva N, Zhanatkyzy A, Telisheva Z, Sandygulova A. Effects of Parental Involvement in Robot-Assisted Autism Therapy. J Autism Dev Disord. 2023;53(1):438-455.
  • Aydemir U. ChatGPT-Delivered Physical Activity Intervention for Children With Autism Spectrum Disorder: Pre-Post Feasibility Study. JMIR Hum Factors. 2025;12:e71119.
  • Sibley MH, Bickman L, Atkins D, et al. Developing an Implementation Model for ADHD Intervention in Community Clinics: Leveraging Artificial Intelligence and Digital Technology. Cogn Behav Pract. 2024;31(4):482-497.
  • Cho Y, Talboys SL. Trends in South Korean Medical Device Development for Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder: Narrative Review. JMIR Biomed Eng. 2024;9:e60399.
  • Guo W, He Q, Lin Z, et al. Enhancing depression recognition through a mixed expert model by integrating speaker-related and emotion-related features. Sci Rep. 2025;15(1):4064.
  • Grimes PZ, Mitchell BL, Thompson KN, et al. Genome-wide association study of adolescent-onset depression. medRxiv [Preprint]. 2025:2025.09.26.25335972.
  • Lee E, van Dijk MT, Kim BG, et al. Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology. Mol Psychiatry. 2025 Sep 8. doi: 10.1038/s41380-025-03221-8. Epub ahead of print.
  • Efrati Y, Rosenberg H, Ophir Y. Effective parental strategies against problematic smartphone use among adolescents: A 6-month prospective study. Addict Behav. 2024;154:108024.
  • Bao K, Zhang X, Cai L. The Closed Loop Between Parental Upbringing and Online Game Addiction: A Narrative Study of Rural Children's Growth in China. Psychol Res Behav Manag. 2024;17:1703-1716.
  • Bolch MB, Moore RM, Robertson GC, Scafe MJ, Milkovich LM. Screens Are Not the Enemy: Recommendations for Developing Healthy Digital Habits in Youth. Mo Med. 2025;122(4):297-303.
  • Christakis DA, Gilkerson J, Richards JA, et al. Audible television and decreased adult words, infant vocalizations, and conversational turns: a population-based study. Arch Pediatr Adolesc Med. 2009 Jun;163(6):554-8.
  • Glassman J, Humphreys K, Yeung S, et al. Parents' Perspectives on Using Artificial Intelligence to Reduce Technology Interference During Early Childhood: Cross-sectional Online Survey. J Med Internet Res. 2021;23(3):e19461.
  • Weintraub MJ, Posta F, Arevian AC, Miklowitz DJ. Using machine learning analyses of speech to classify levels of expressed emotion in parents of youth with mood disorders. J Psychiatr Res. 2021;136:39-46.
  • Fisher HL, Firth Z, Aicardi C, Downs J. Editorial: "What say you?" The promise and potential pitfalls of using automated and passive monitoring approaches to assess parenting behaviours from verbal and written communication. J Child Psychol Psychiatry. 2024;65(7):871-873.
  • Heo S, Jeong S, Paeng H, Yoo S, Son MH. Communication challenges and experiences between parents and providers in South Korean paediatric emergency departments: a qualitative study to define AI-assisted communication agents. BMJ Open. 2025;15(4):e094748.
  • Cao M, Shao X, Chan P, et al. High-resolution analyses of human sperm dynamic methylome reveal thousands of novel age-related epigenetic alterations. Clin Epigenetics. 2020;12(1):192.
  • Myers KA, Bennett MF, Hildebrand MS, et al. Transcriptome analysis of a ring chromosome 20 patient cohort. Epilepsia. 2021;62(1):e22-e28.
  • Kopal J, Huguet G, Marotta J, et al. A pattern-learning algorithm associates copy number variations with brain structure and behavioural variables in an adolescent population cohort. Nat Biomed Eng. 2025 Jul 18. doi: 10.1038/s41551-025-01454-0. Epub ahead of print.
  • D'Amours G, Clausen M, Luca S, et al. Genetics Navigator: protocol for a mixed methods randomized controlled trial evaluating a digital platform to deliver genomic services in Canadian pediatric and adult populations. BMJ Open. 2024;14(9):e090084.
  • Li J, Hojlo MA, Chennuri S, et al. Underrepresentation of Phenotypic Variability of 16p13.11 Microduplication Syndrome Assessed With an Online Self-Phenotyping Tool (Phenotypr): Cohort Study. J Med Internet Res. 2021;23(3):e21023.
  • Alfeir NM. Dimensions of artificial intelligence on family communication. Front Artif Intell. 2024;7:1398960.
  • Ye J. Pediatric Mental and Behavioral Health in the Period of Quarantine and Social Distancing With COVID-19. JMIR Pediatr Parent. 2020;3(2):e19867.
  • Rico-Juan JR, Peña-Acuña B, Navarro-Martinez O. Holistic exploration of reading comprehension skills, technology and socioeconomic factors in Spanish teenagers. Heliyon. 2024;10(12):e32637.

Artificial Intelligence and Digital Technologies in Family and Parenting Contexts

Year 2026, Volume: 10 Issue: 1, 149 - 156, 31.01.2026
https://doi.org/10.30621/jbachs.1868255

Abstract

Artificial intelligence (AI) and digital technologies are increasingly influencing family life, parenting practices, and pediatric health and mental health services. Applications include AI-enabled parenting support tools, mobile health interventions, digital therapeutics, remote monitoring systems, and algorithm-based platforms for neurodevelopmental and psychiatric assessment. While these technologies offer opportunities to enhance parental support, personalize care, and improve access to services, they also raise concerns related to ethics, equity, data privacy, and parent–child relationships. This narrative review offers an integrative overview of AI and digital technologies in family and parenting contexts, focusing on key domains such as AI-supported parenting interventions, digital health literacy, pediatric and perinatal care, neurodevelopmental and mental health assessment, digital media use, and family communication. Reported benefits, emerging risks, and unintended consequences are discussed with particular attention to parental roles, family-centered design, and implementation challenges. Overall, evidence suggests that AI-enabled tools are most effective when they are transparent, co-designed with parents and clinicians, and integrated into existing health and social care systems. Nonetheless, gaps remain regarding long-term outcomes, equitable access, ethical governance, and sustainable implementation. AI in digital parenting should therefore be viewed as a complementary resource that augments, rather than replaces, parental judgment and professional care.

References

  • Woods P, Donohoe S, Turtle L, et al. Enhancing Parenting Using AI: Exploratory Hackathon. JMIR Form Res. 2025;9:e68780.
  • Chua JYX, Choolani M, Chee CYI, et al. A Mobile App-Based Intervention (Parentbot-a Digital Healthcare Assistant) for Parents: Secondary Analysis of a Randomized Controlled Trial. J Med Internet Res. 2025;27:e64882.
  • Westrupp EM, Bates M, Bufton KJ, et al. Protocol for a randomized and a non-randomized controlled trial testing Daily Growth: a personalised 'ecological momentary intervention' parenting app for parents and carers of children aged 2-5 years. BMC Psychol. 2025;13(1):704.
  • Litwin S, Mohabir M, Kocak IS, Singh D. Creating a Parent-Informed Pediatric Emergency Department Wait Time App: Human-Centered Design Approach to Creating an AI Health Care Tool. J Particip Med. 2025;17:e66644.
  • Aloi MA, Caldwell PHY, Taba M, et al. Co-designing an online educational resource to help adolescents improve their digital health literacy. BMC Public Health. 2025 May 21;25(1):1870. doi: 10.1186/s12889-025-22949-0. Erratum in: BMC Public Health. 2025;25(1):3037.
  • Kim H, Kang JH, Kwon Y, et al. Development of a Smart Health Care Service Using Metaverse and Chatbot Technologies for Adolescents, Parents, and School Health Teachers: User-Centered Design Approach. J Med Internet Res. 2025;27:e69190.
  • Zaman S, Ashley-Norman T, Sutcliffe J, Cartledge P. A "Curriculum of Information Needs" of Parents of Children With Chronic Constipation. Clin Pediatr (Phila). 2025:99228251395563.
  • Heerman WJ, Rothman RL, Sanders LM, et al. A Digital Health Behavior Intervention to Prevent Childhood Obesity: The Greenlight Plus Randomized Clinical Trial. JAMA. 2024;332(24):2068-2080.
  • Pervanidou P, Chatzidaki E, Nicolaides NC, et al. The Impact of the ENDORSE Digital Weight Management Program on the Metabolic Profile of Children and Adolescents with Overweight and Obesity and on Food Parenting Practices. Nutrients. 2023;15(7):1777.
  • Lewkowitz AK, Schlichting LE, Ayala NK, et al. Association Between Hispanic Ethnicity and Engagement in a Remote Postpartum Blood Pressure Monitoring Programs: Secondary Analysis of a Pilot Randomized Trial. R I Med J (2013). 2024;107(6):17-18.
  • Wang G, Bennamoun H, Kwok WH, et al. Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach. J Med Internet Res. 2025;27:e68030.
  • Chung K, Jhung K, Cho HY, Park JY. Father-inclusive chatbot-based prenatal education during COVID-19 pandemic enhances maternal-fetal attachment in Korean primigravida women across levels of partner support. Sci Rep. 2025;15(1):28541.
  • Washington P, Chrisman B, Leblanc E, et al. Crowd annotations can approximate clinical autism impressions from short home videos with privacy protections. Intell Based Med. 2022;6:None.
  • Dubey I, Bishain R, Dasgupta J, et al. Using mobile health technology to assess childhood autism in low-resource community settings in India: An innovation to address the detection gap. Autism. 2024;28(3):755-769.
  • Amirova A, Rakhymbayeva N, Zhanatkyzy A, Telisheva Z, Sandygulova A. Effects of Parental Involvement in Robot-Assisted Autism Therapy. J Autism Dev Disord. 2023;53(1):438-455.
  • Aydemir U. ChatGPT-Delivered Physical Activity Intervention for Children With Autism Spectrum Disorder: Pre-Post Feasibility Study. JMIR Hum Factors. 2025;12:e71119.
  • Sibley MH, Bickman L, Atkins D, et al. Developing an Implementation Model for ADHD Intervention in Community Clinics: Leveraging Artificial Intelligence and Digital Technology. Cogn Behav Pract. 2024;31(4):482-497.
  • Cho Y, Talboys SL. Trends in South Korean Medical Device Development for Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder: Narrative Review. JMIR Biomed Eng. 2024;9:e60399.
  • Guo W, He Q, Lin Z, et al. Enhancing depression recognition through a mixed expert model by integrating speaker-related and emotion-related features. Sci Rep. 2025;15(1):4064.
  • Grimes PZ, Mitchell BL, Thompson KN, et al. Genome-wide association study of adolescent-onset depression. medRxiv [Preprint]. 2025:2025.09.26.25335972.
  • Lee E, van Dijk MT, Kim BG, et al. Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology. Mol Psychiatry. 2025 Sep 8. doi: 10.1038/s41380-025-03221-8. Epub ahead of print.
  • Efrati Y, Rosenberg H, Ophir Y. Effective parental strategies against problematic smartphone use among adolescents: A 6-month prospective study. Addict Behav. 2024;154:108024.
  • Bao K, Zhang X, Cai L. The Closed Loop Between Parental Upbringing and Online Game Addiction: A Narrative Study of Rural Children's Growth in China. Psychol Res Behav Manag. 2024;17:1703-1716.
  • Bolch MB, Moore RM, Robertson GC, Scafe MJ, Milkovich LM. Screens Are Not the Enemy: Recommendations for Developing Healthy Digital Habits in Youth. Mo Med. 2025;122(4):297-303.
  • Christakis DA, Gilkerson J, Richards JA, et al. Audible television and decreased adult words, infant vocalizations, and conversational turns: a population-based study. Arch Pediatr Adolesc Med. 2009 Jun;163(6):554-8.
  • Glassman J, Humphreys K, Yeung S, et al. Parents' Perspectives on Using Artificial Intelligence to Reduce Technology Interference During Early Childhood: Cross-sectional Online Survey. J Med Internet Res. 2021;23(3):e19461.
  • Weintraub MJ, Posta F, Arevian AC, Miklowitz DJ. Using machine learning analyses of speech to classify levels of expressed emotion in parents of youth with mood disorders. J Psychiatr Res. 2021;136:39-46.
  • Fisher HL, Firth Z, Aicardi C, Downs J. Editorial: "What say you?" The promise and potential pitfalls of using automated and passive monitoring approaches to assess parenting behaviours from verbal and written communication. J Child Psychol Psychiatry. 2024;65(7):871-873.
  • Heo S, Jeong S, Paeng H, Yoo S, Son MH. Communication challenges and experiences between parents and providers in South Korean paediatric emergency departments: a qualitative study to define AI-assisted communication agents. BMJ Open. 2025;15(4):e094748.
  • Cao M, Shao X, Chan P, et al. High-resolution analyses of human sperm dynamic methylome reveal thousands of novel age-related epigenetic alterations. Clin Epigenetics. 2020;12(1):192.
  • Myers KA, Bennett MF, Hildebrand MS, et al. Transcriptome analysis of a ring chromosome 20 patient cohort. Epilepsia. 2021;62(1):e22-e28.
  • Kopal J, Huguet G, Marotta J, et al. A pattern-learning algorithm associates copy number variations with brain structure and behavioural variables in an adolescent population cohort. Nat Biomed Eng. 2025 Jul 18. doi: 10.1038/s41551-025-01454-0. Epub ahead of print.
  • D'Amours G, Clausen M, Luca S, et al. Genetics Navigator: protocol for a mixed methods randomized controlled trial evaluating a digital platform to deliver genomic services in Canadian pediatric and adult populations. BMJ Open. 2024;14(9):e090084.
  • Li J, Hojlo MA, Chennuri S, et al. Underrepresentation of Phenotypic Variability of 16p13.11 Microduplication Syndrome Assessed With an Online Self-Phenotyping Tool (Phenotypr): Cohort Study. J Med Internet Res. 2021;23(3):e21023.
  • Alfeir NM. Dimensions of artificial intelligence on family communication. Front Artif Intell. 2024;7:1398960.
  • Ye J. Pediatric Mental and Behavioral Health in the Period of Quarantine and Social Distancing With COVID-19. JMIR Pediatr Parent. 2020;3(2):e19867.
  • Rico-Juan JR, Peña-Acuña B, Navarro-Martinez O. Holistic exploration of reading comprehension skills, technology and socioeconomic factors in Spanish teenagers. Heliyon. 2024;10(12):e32637.
There are 37 citations in total.

Details

Primary Language English
Subjects Translational and Applied Bioinformatics, Bioinformatics and Computational Biology (Other)
Journal Section Review
Authors

Ahu Pakdemirli 0000-0001-9224-3007

Submission Date January 20, 2026
Acceptance Date January 22, 2026
Publication Date January 31, 2026
Published in Issue Year 2026 Volume: 10 Issue: 1

Cite

APA Pakdemirli, A. (2026). Artificial Intelligence and Digital Technologies in Family and Parenting Contexts. Journal of Basic and Clinical Health Sciences, 10(1), 149-156. https://doi.org/10.30621/jbachs.1868255
AMA Pakdemirli A. Artificial Intelligence and Digital Technologies in Family and Parenting Contexts. JBACHS. January 2026;10(1):149-156. doi:10.30621/jbachs.1868255
Chicago Pakdemirli, Ahu. “Artificial Intelligence and Digital Technologies in Family and Parenting Contexts”. Journal of Basic and Clinical Health Sciences 10, no. 1 (January 2026): 149-56. https://doi.org/10.30621/jbachs.1868255.
EndNote Pakdemirli A (January 1, 2026) Artificial Intelligence and Digital Technologies in Family and Parenting Contexts. Journal of Basic and Clinical Health Sciences 10 1 149–156.
IEEE A. Pakdemirli, “Artificial Intelligence and Digital Technologies in Family and Parenting Contexts”, JBACHS, vol. 10, no. 1, pp. 149–156, 2026, doi: 10.30621/jbachs.1868255.
ISNAD Pakdemirli, Ahu. “Artificial Intelligence and Digital Technologies in Family and Parenting Contexts”. Journal of Basic and Clinical Health Sciences 10/1 (January2026), 149-156. https://doi.org/10.30621/jbachs.1868255.
JAMA Pakdemirli A. Artificial Intelligence and Digital Technologies in Family and Parenting Contexts. JBACHS. 2026;10:149–156.
MLA Pakdemirli, Ahu. “Artificial Intelligence and Digital Technologies in Family and Parenting Contexts”. Journal of Basic and Clinical Health Sciences, vol. 10, no. 1, 2026, pp. 149-56, doi:10.30621/jbachs.1868255.
Vancouver Pakdemirli A. Artificial Intelligence and Digital Technologies in Family and Parenting Contexts. JBACHS. 2026;10(1):149-56.