Caregiver stress and social determinants of health in key populations: immigrant parents, parents of children with medical complexity, and adolescent parents

PURPOSE OF REVIEW: To examine the five domains of social determinants of health - economic stability, education access, healthcare access and quality, neighborhood and built environment, and social and community context - and how these relate to caregiver stress in under-resourced populations. RECENT FINDINGS: Socioeconomic and family factors are increasingly understood as drivers of child health. Caregiver stress can impact family stability and child wellbeing. Immigrant parents, caregivers of children with medical complexity, and adolescent parents experience stressors due to the unique needs of their families. These groups of parents and caregivers also face various challenges identified as social determinants of health. Interventions to mitigate these challenges can promote resilience, care coordination, and community-based supports. SUMMARY: Current research describes caregiver stress in key populations, how caregiver stress affects children, and approaches to minimize and mitigate these effects. Pediatric providers can implement best practices to support families who are navigating stress due to caregiving and social determinants of health

Voice as a Biomarker of Pediatric Health: A Scoping Review

There is a paucity of literature in the field of pediatric voice analysis. This scoping review aims to condense all that is known about the use of AI for analyzing voice as a biomarker of pediatric health to further propel research in this area. "The human voice is often referred to as a unique print for each individual and contains biomarkers that have been linked in the adult literature to various diseases ranging from Parkinson’s disease to dementia, mood disorders and cancers. Voice contains complex acoustic markers that depend on the coordination between respiration, phonation, articulation, and prosody. Recent advances in acoustic analysis technology, in particular those linked to machine learning, have shed new insights into the detection of diseases. As a biomarker, voice is unique, cost-effective, easy and safe to collect in low resource settings. Moreover, the human voice not only contains speech, but also other acoustic biomarkers such as respiratory sounds, and cough

Voice as a Biomarker of Pediatric Health: A Scoping Review

The human voice has the potential to serve as a valuable biomarker for the early detection, diagnosis, and monitoring of pediatric conditions. This scoping review synthesizes the current knowledge on the application of artificial intelligence (AI) in analyzing pediatric voice as a biomarker for health. The included studies featured voice recordings from pediatric populations aged 0–17 years, utilized feature extraction methods, and analyzed pathological biomarkers using AI models. Data from 62 studies were extracted, encompassing study and participant characteristics, recording sources, feature extraction methods, and AI models. Data from 39 models across 35 studies were evaluated for accuracy, sensitivity, and specificity. The review showed a global representation of pediatric voice studies, with a focus on developmental, respiratory, speech, and language conditions. The most frequently studied conditions were autism spectrum disorder, intellectual disabilities, asphyxia, and asthma. Mel-Frequency Cepstral Coefficients were the most utilized feature extraction method, while Support Vector Machines were the predominant AI model. The analysis of pediatric voice using AI demonstrates promise as a non-invasive, cost-effective biomarker for a broad spectrum of pediatric conditions. Further research is necessary to standardize the feature extraction methods and AI models utilized for the evaluation of pediatric voice as a biomarker for health. Standardization has significant potential to enhance the accuracy and applicability of these tools in clinical settings across a variety of conditions and voice recording types. Further development of this field has enormous potential for the creation of innovative diagnostic tools and interventions for pediatric populations globally