ARTIFICIAL INTELLIGENCE IN PARENTAL INFORMATION-SEEKING ABOUT CHILD HEALTH AND DEVELOPMENT

The aim of this study was to examine the extent to which parents use artificial intelligence (AI) as a source of information about child health and development, as well as to analyze the influence of age and educational level on the frequency of AI use. A cross-sectional study was conducted on a sample of 400 parents using a structured electronic questionnaire. The study analyzed the frequency of AI use, trust in AI and experts, and the association between demographic characteristics and the use of digital information sources. Overall, 52.5% of parents reported using AI tools to obtain information about child development. Younger parents and those with higher levels of education used these tools significantly more often. Parents with higher education had a fourteen-fold higher likelihood of using AI compared to respondents with only primary education. Most parents expressed moderate to high trust in AI, but at the same time, 83.8% believed that AI cannot replace professionals. The findings indicate that AI is becoming an important source of information among parents, particularly among younger and highly educated individuals. Based on the obtained results regarding parents’ attitudes toward AI technologies, these tools have potential as a supplementary resource for initial information seeking; however, professional judgment remains irreplaceable. The data provided by parents also highlight the need for the development of medically validated and regulated AI tools, as well as education on their safe and responsible use.

Authors

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-12-01
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ARTIFICIAL INTELLIGENCE IN PARENTAL INFORMATION-SEEKING ABOUT CHILD HEALTH AND DEVELOPMENT

Mirela Duranović, Ana Madžar Čančar, Ajla Mahmutović Babić, Ivana Lovrić et al.
SHILAP Revista de lepidopterología
Artificial Intelligence in Healthcare and Education
article

ARTIFICIAL INTELLIGENCE IN PARENTAL INFORMATION-SEEKING ABOUT CHILD HEALTH AND DEVELOPMENT

Mirela Duranović, Ana Madžar Čančar, Ajla Mahmutović Babić, Ivana Lovrić, Ana Mari Petrović
article en

Abstract

The aim of this study was to examine the extent to which parents use artificial intelligence (AI) as a source of information about child health and development, as well as to analyze the influence of age and educational level on the frequency of AI use. A cross-sectional study was conducted on a sample of 400 parents using a structured electronic questionnaire. The study analyzed the frequency of AI use, trust in AI and experts, and the association between demographic characteristics and the use of digital information sources. Overall, 52.5% of parents reported using AI tools to obtain information about child development. Younger parents and those with higher levels of education used these tools significantly more often. Parents with higher education had a fourteen-fold higher likelihood of using AI compared to respondents with only primary education. Most parents expressed moderate to high trust in AI, but at the same time, 83.8% believed that AI cannot replace professionals. The findings indicate that AI is becoming an important source of information among parents, particularly among younger and highly educated individuals. Based on the obtained results regarding parents’ attitudes toward AI technologies, these tools have potential as a supplementary resource for initial information seeking; however, professional judgment remains irreplaceable. The data provided by parents also highlight the need for the development of medically validated and regulated AI tools, as well as education on their safe and responsible use.

SHILAP Revista de lepidopterología
Quality Education
Openalex Percentile: Top 37%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.