Psychometric testing on two weight stigma instruments in Iran: Weight Self-Stigma Questionnaire and Weight Bias Internalized Scale.

PURPOSE: This study aimed to comprehensively and thoroughly examine the psychometric properties of two commonly used weight-related self-stigma instruments on Iranian adolescents with overweight or obesity: Weight Self-Stigma Questionnaire [WSSQ] and Weight Bias Internalization Scale [WBIS]. METHODS: After ensuring the linguistic validity of both the WSSQ and WBIS in their Persian versions, 737 Iranian adolescents with overweight or obesity (male = 354; mean age = 15.8 ± 1.3 years; body mass index = 30.0 ± 4.8 kg/m2) completed both questionnaires and other relevant measures regarding their depression, anxiety, stress, dietary self-efficacy, weight efficacy lifestyle, quality of life, body fat, self-esteem, body shape preoccupation, and sleepiness. RESULTS: In the scale level, the confirmatory factory analysis verified the two-factor structure for the WSSQ and the single-factor structure for the WBIS. The factorial structures were further found to be invariant across gender (male vs. female) and across weight status (overweight vs. obesity). Additionally, both the WSSQ and WBIS had promising properties in internal consistency, test-retest reliability, separation reliability, and separation index. In the item level, all items but WBIS item 1 (infit mean square = 1.68; outfit mean square = 1.60) had satisfactory properties in factor loadings, corrected item-total correlation, test-retest reliability, and infit and outfit mean square. Moreover, all the items did not display substantial differential item functioning (DIF) across gender and across weight status. CONCLUSION: Both the WSSQ and WBIS were valid instruments to assess the internalization of weight bias for Iranian adolescents with overweight or obesity. LEVEL OF EVIDENCE: Level V, cross-sectional descriptive study.

Mediated effects of eating disturbances in the association of perceived weight stigma and emotional distress.

PURPOSE: This study aimed to examine the relationships between perceived weight stigma, eating disturbances, and emotional distress across individuals with different self-perceived weight status. METHODS: University students from Hong Kong (n = 400) and Taiwan (n = 307) participated in this study and completed several questionnaires: Perceived Weight Stigma questionnaire; Three-factor Eating Questionnaire; Hospital Anxiety and Depression Scale. Each participant self-reported their height, weight, and self-perceived weight status. RESULTS: After controlling for demographics, perceived weight stigma was associated with eating disturbances (ß = 0.223, p < 0.001), depression (ß = 0.143, p < 0.001), and anxiety (ß = 0.193, p < 0.001); and eating disturbances was associated with depression (ß = 0.147, p < 0.001) and anxiety (ß = 0.300, p < 0.001) in the whole sample. Additionally, eating disturbances mediated the association between perceived weight stigma and emotional distress. Similar findings were shown in the subsamples who perceived themselves as higher weight or normal weight and in the male and female subsamples. However, in the subsamples who perceived themselves as lower weight, only the links between eating disturbances and emotional distress were significant. CONCLUSION: Perceived weight stigma was associated with eating disturbances and emotional distress in young adults with both higher and normal weight. Eating disturbances were associated with emotional distress regardless of participants' weight status. LEVEL OF EVIDENCE: Level V, cross-sectional descriptive study.

The Mediating Effects of Eating Disorder, Food Addiction, and Insomnia in the Association between Psychological Distress and Being Overweight among Iranian Adolescents.

With obesity and excess weight remaining a serious concern worldwide, investigating the mechanisms underlying this is of great importance. Psychological distress is a possible trigger contributing to excess weight for adolescents. Moreover, the association between psychological distress and excess weight may be mediated by eating disorder, food addiction, and insomnia. The present study utilized parallel mediation analysis to assess the aforementioned associations and possible mediation effects among Iranian adolescents. Through stratified and clustered sampling, adolescents (N = 861; mean ± SD age = 15.9 ± 3.2; 372 males) participated and were followed for a one-year period. Excess weight (standardized body mass index, z-BMI); psychological distress (Depression, Anxiety, and Stress Scale-21); eating disorder attitudes (Eating Attitude Test-26); food addiction (Yale Food Addiction Scale for Children); and insomnia (Insomnia Severity Index) were assessed. Eating disorder attitudes, food addiction, and insomnia were significant mediators in the association of psychological distress and z-BMI. Additionally, psychological distress had direct effects on z-BMI. Given that eating disorder attitudes, food addiction, and insomnia showed mediated effects in the temporal association of psychological distress and excess weight, healthcare providers are encouraged to design programs on improving these three mediators to help adolescents overcome excess weight problems.

The Relationship Between Sleep Duration and Participation in Home, School, and Community Activities Among School-Aged Children.

Sleep duration has important implications for children's participation in daily activities; however, past attempts to examine this relationship has been limited to specific types of physical or educational activities. The present study aimed to investigate the relationship between sleep duration and participation in various daily activities among school-aged children. A school-based sample of 391 children aged 5-12 years (boys: 52.4%) participated in this cross-sectional survey. Sleep duration was quantified using parental reports of their children's bedtime and wake-up time on weekdays and weekends. The parent-reported Participation and Environment Measure for Children and Youth was used to measure their children's participation frequency and involvement in 25 home, school, and community activities. The results of hierarchical regression analyses showed that, when the demographic variables were controlled for, weekday sleep duration was positively related to homework involvement and negatively related to the frequency of TV viewing; however, it was unrelated to participation in school and community activities. Conversely, weekend sleep duration was positively related to overall participation in school activities, and participation frequency and involvement in some home and community activities. Furthermore, sleep duration was approximately an hour shorter on weekdays than on weekends. These results suggest that weekend sleep duration has stronger positive implications for children's participation in daily activities than does weekday sleep duration. Interventions aiming to promote children's activity participation may either prolong children's weekend sleep duration or address their shorter weekday sleep duration.

Prediction of preterm deliveries from EHG signals using machine learning.

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier.