Body Composition Measurement in Children with Cerebral Palsy, Spina Bifida and Spinal Cord Injury: A Systematic Review of the Literature

Pediatric obesity is a major health concern that has an increased prevalence in children with special needs. In order to categorize a child’s weight, an assessment of body composition is needed. Obtaining an accurate body composition measurement in children with special needs has many challenges associated with it. This perplexing scenario limits the provider’s ability to screen, prevent and treat an abnormal weight status in this vulnerable population. This systematic review summarizes common methods of body composition measurements, their strengths and limitations and reviews the literature when measurements were used in children with cerebral palsy, spina bifida and spinal cord injury. Following PRISMA guidelines, 222 studies were identified. The application of the inclusion and exclusion criteria yielded a final sample of nine studies included in this review. Overall, articles reinforced the inconsistencies of body composition measurement and methodology when used with children with special needs. Concerns include small sample sizes, the need to validate prediction equations for this population, and the lack of controlled trials and reporting of measurement methodology. Healthcare providers need to be aware of the complexities associated with measuring body composition in children with special needs and advocate for further testing of these measurements. Additional studies addressing the reliability and validity of these measures are needed to facilitate appropriate health promotion in children

Assessing Order Effects in Online Community-based Health Forums

Measuring the quality of health content in online health forums is a challenging task. The majority of the existing measures are based on evaluations of forum users and may not be reliable. We employed machine learning techniques, text mining methods, and Big Data platforms to construct four measures of textual quality to automatically determine the similarity of a given answer to professional answers. We then used them to assess the quality of 66,888 answers posted on Yahoo! Answers Health section. All four measures of textual quality revealed a higher quality for asker-selected best answers indicating that askers, to some extent, have a proper judgment to select the best answers. We also studied the presence of order effects in online health forums. Our results suggest that the textual quality of the first answer positively influences the mean textual quality of the subsequent answers and negatively influences the quantity of subsequent answers