Family life factors associated with parental depression.

Family life factors associated with parental depression.</p

Pupil ADHD and family context factors (X²).

BackgroundAttention Deficit Hyperactivity Disorder (ADHD) is increasingly recognized as a major problem for children and their families in China. However, its influence on parental mental health has been seldom explored.ObjectiveTo examine the prevalence of attention deficit hyperactivity disorder in a community sample of children aged 6–13 years, and the extent to which it impacts parental mental health.MethodCross-sectional study of primary school pupils (number = 2497) in Deyang, Sichuan Province, South-West China. We used standardized instruments to identify children with ADHD symptoms and parent depression.ResultsThe prevalence of ADHD was 9.8%. Factors associated with the likelihood of ADHD, included family environment(P = 0.003), time spent with children(P = 0.01), parenting style(P = 0.01), and parental relationship, pupils self-harm and lower academic ability (P = 0.001). After controlling for other factors, having a child with ADHD increased the likelihood of parents’ depression (OR = 4.35, CI = 2.68~7.07), additional factors included parent relationship.ConclusionsADHD may be a common disorder among Chinese children, the symptoms of which may increase the likelihood of parent depression. There is a need for greater detection of ADHD in schools, acknowledgement of the challenges the disorder creates for academic success and family wellbeing, and psychoeducational tools for supporting parents of children with ADHD.</div

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BackgroundAttention Deficit Hyperactivity Disorder (ADHD) is increasingly recognized as a major problem for children and their families in China. However, its influence on parental mental health has been seldom explored.ObjectiveTo examine the prevalence of attention deficit hyperactivity disorder in a community sample of children aged 6–13 years, and the extent to which it impacts parental mental health.MethodCross-sectional study of primary school pupils (number = 2497) in Deyang, Sichuan Province, South-West China. We used standardized instruments to identify children with ADHD symptoms and parent depression.ResultsThe prevalence of ADHD was 9.8%. Factors associated with the likelihood of ADHD, included family environment(P = 0.003), time spent with children(P = 0.01), parenting style(P = 0.01), and parental relationship, pupils self-harm and lower academic ability (P = 0.001). After controlling for other factors, having a child with ADHD increased the likelihood of parents’ depression (OR = 4.35, CI = 2.68~7.07), additional factors included parent relationship.ConclusionsADHD may be a common disorder among Chinese children, the symptoms of which may increase the likelihood of parent depression. There is a need for greater detection of ADHD in schools, acknowledgement of the challenges the disorder creates for academic success and family wellbeing, and psychoeducational tools for supporting parents of children with ADHD.</div

Multivariate analysis of factors associated with ADHD symptoms.

Multivariate analysis of factors associated with ADHD symptoms.</p

Multivariate analysis of factors associated with parental depression at higher and lower levels of severity (for PHQ scores >6; and scores >10).

Multivariate analysis of factors associated with parental depression at higher and lower levels of severity (for PHQ scores >6; and scores >10).</p

Semi-Supervised Fuzzy Clustering with Feature Discrimination

<div><p>Semi-supervised clustering algorithms are increasingly employed for discovering hidden structure in data with partially labelled patterns. In order to make the clustering approach useful and acceptable to users, the information provided must be simple, natural and limited in number. To improve recognition capability, we apply an effective feature enhancement procedure to the entire data-set to obtain a single set of features or weights by weighting and discriminating the information provided by the user. By taking pairwise constraints into account, we propose a semi-supervised fuzzy clustering algorithm with feature discrimination (SFFD) incorporating a fully adaptive distance function. Experiments on several standard benchmark data sets demonstrate the effectiveness of the proposed method.</p></div

Primer sequences for <i>β-actin</i> and other target genes.

<p>Primer sequences for <i>β-actin</i> and other target genes.</p

Effect of DHEA on glucose content and metabolic hormone in rats fed a high-fat diet.

<p>A: Glucose content; B: Leptin content; C: Glucagon content; D: Insulin content. Data are expressed as means ± SE (n = 15). ** <i>P</i> < 0.01 and * <i>P</i>< 0.05, compared with the HCG group.</p

Experimental design.

<p>Experimental design.</p

Effect of DHEA on body weight, Feed intake, BMI, and Lee’s index in rats fed a high-fat diet.

<p>A: Body weight; B: Average daily gain; C: Feed intake; D: Body mass index (BMI); E: Lee`s index. Data are expressed as means ± SE (n = 15). * <i>P</i> < 0.05, compared with the HCG group.</p