Aims: This study aims to explore the prevalence of mobile phone use among young children aged 6 months to 4 years. We studied the usage patterns, optimal age for use, and the attitudes of parents toward their child's mobile phone use.
Methods: We conducted a cross-sectional study in a pediatric OPD of a tertiary teaching hospital for a period of 2-months. Ethics committee approval and informed consent was taken before conducting the research. A predesigned and validated questionnaire was used to collect data. We calculated a sample size of 90 children at a 95% confidence level. Chi-square test and Fischer's exact test were used as a test of significance at 5% level of significance.
Results: We observed that 73.34% of children were using mobile phones and mobile phone usage increased with age. Children used mobile phones for educational purposes (43.9%), and for less than an hour a day (57.6%). In the 3-4 year age group, 19% used mobile phones for 3 hours or more. While 93.3% of parents felt they shouldn't give their child a phone, 71.4% children of these parents still used one.
Conclusions: Our study highlights a high prevalence of mobile phone use among young children aged 6 months to 4 years. Although parents aimed to limit their child's phone usage, the reality was different. We recommend that guidelines on mobile phone use be followed in India.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10866234 | PMC |
http://dx.doi.org/10.4103/jfmpc.jfmpc_703_23 | DOI Listing |
JMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFJMIR Ment Health
January 2025
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background: Lifestyle interventions have been acknowledged as effective strategies for preventing type 2 diabetes mellitus (T2DM). However, the accessibility of conventional face-to-face interventions is often limited. Digital health intervention has been suggested as a potential solution to overcome the limitation.
View Article and Find Full Text PDFPLoS One
January 2025
European IPF/ILD Registry and Biobank (eurIPFreg/bank, eurILDreg/bank), Giessen, Germany.
Background And Aims: Predicting progression and prognosis in Interstitial Lung Diseases (ILD), especially Idiopathic Pulmonary Fibrosis (IPF) and Progressive Pulmonary Fibrosis (PPF), remains a challenge. Integrating patient-centered measurements is essential for earlier and safer detection of disease progression. Home monitoring through e-health technologies, such as spirometry and oximetry connected to smartphone applications, holds promise for early detection of ILD progression or acute exacerbations, enabling timely therapeutic interventions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!