Sentences with phrase «predicted by gender»

Depressive symptoms in adolescence were predicted by gender, children's depressive symptoms at age 8, maternal depressive symptoms in adolescence, and maternal depressive symptoms in infancy.

Gender, trait emotional intelligence, and cognitive empathy significantly predicted bullying, whereas victimization was predicted by gender, trait emotional intelligence and affective empathy.

In fact, for the first time, a person's vote is more easily predicted by their gender than their level of religiosity.

Not exact matches

Recently, Equilar, a research firm that focuses on board recruitment, put together a Gender Diversity Index and predicts that the board of directors on the Russell 3000 list — the 3000 largest companies based in the United States — will achieve parity, with a membership made up of 50 percent women and 50 percent men, by the fourth quarter of 2055.

The gender of such nouns can seldom be predicted and must be learned by observation.

Nor can you predict gender by fetal movements.

Figure 2 shows the distribution of infant weight for age by breastfeeding medication group, predicted by the regression model after adjustment for birth weight and gender.

«Risk of distracted driving predicted by age, gender, personality and driving frequency: Young men, people who drive more often, and extraverted or neurotic people are more likely to be distracted while driving.»

In a 2013 analysis of the myPersonality data published in the Proceedings of the National Academy of Sciences (PNAS), a team led by Kosinski showed that the pattern of people's likes on Facebook is enough to predict their personal traits such as gender, race, political persuasion, and even sexuality.

The findings held true for all students, regardless of whether they appeared likely or unlikely to attend selective schools, as predicted by student background characteristics such as race, gender, socioeconomic status, and pre-college test scores.

The predicted 10 - year risks of developing CVD varied significantly by age, gender, race - ethnicity, educational attainment, household income, and state of residence.

According to the district's draft of the policy, «equity is attained when there is sufficient evidence that each student has a high - quality education experience, and outcomes are not predicted by race, gender, socioeconomic status, [individualized education program] status, or learning English as a second language.»

Moreover, just 27 % of those employed in Britain's digital industries are women, and the UK Commission for mEmployment and Skills has predicted that by 2022, the figure will have only risen to 30 %, signifying a less than typical gender pay gap.

Specifically, we examined the extent to which four common teen drinking styles — frequent drinking, binge drinking, heavy binge drinking and loss of control over drinking — predict AUD diagnoses in young adulthood; and whether risks differ by gender and age of AUD diagnosis in young adulthood.

We investigated the possibility of a gender - by - poverty interaction in predicting grade repetition, but found none (χ2 = 0.01, P =.92).

Notwithstanding these gender - specific risk and protective factors, in most cases, the same factors — ADHD, negative temperament, impulsivity, compromised intelligence — predict antisocial behavior in both males and females, as suggested by the substantial overlap shown in figure 4.99 Although some analysts have argued the need to concentrate on the commonalities in predictors of male and female offending, it is also important to note the areas in which risk factors differ by gender.100 Even if the differences between male and female offenders are confined to only a few key areas, the differences in these areas — for example, sensitivity to victimization, timing of onset of persistent offending, prevalence of mental health problems — can be substantial and can profoundly influence the effectiveness of risk assessments and treatment programs.

RESULTS: Hierarchical regression analyses revealed that long - term success (at least 5 % weight reduction by the 1 - year follow - up) versus failure (dropping out or less weight reduction) was significantly predicted by the set of psychosocial variables (family adversity, maternal depression, and attachment insecurity) when we controlled for familial obesity, preintervention overweight, age, and gender of the index child and parental educational level.

The findings that children and adolescents accompanied by family members are less distressed than those who arrive accompanied by relatives corroborate the findings of Kinzie et al. (1986; 1989) who demonstrated that it was neither the amount nor type of trauma witnessed, nor the child's age or gender that predicted PTSD in Cambodian refugees.

Lack of seatbelt use was predicted by sensation seeking (β =.18, p <.01) and by male gender (β =.13, p <.01).

Although this pattern can not be ruled out, previous research (Suitor, Gilligan, & Pillemer, in press) has shown that mothers» preferences for care are shaped by perceptions of similarity, gender, and proximity, and are not predicted by offspring's present or previous difficult behaviors.

Third, although there are some data about various child and family characteristics that predict outcome (e.g., socioeconomic disadvantage, severity of child behaviour, maternal adjustment problems, treatment barriers), there has been a relative dearth of attention paid to a) the actual processes of change that are induced by PMT and b) whether there are certain subgroups (e.g., based on child gender or minority status or family socioeconomic status) for whom PMT is more or less effective.15 - 17

Because the injured child's age and gender did not differ by group or predict any of the family outcomes, these factors were not considered in analysis.

Other future research questions include (a) determination of whether CPI interacts with overall level of parent assistance with tasks in predicting outcomes longitudinally; (b) potential differences in the relation of CPI with diabetes outcomes by race, gender, family composition, and socio - economic status; and (c) the degree to which CPI is modifiable via behavioral intervention.