Search

We evaluated the effects of TutorBright tutoring on the reading and mathematics skills of children in family foster care, examined several potential moderators of the impact of tutoring, an...

Parental involvement in children’s learning has been found to influence academic success. However, very few tools exist for measuring parental involvement, particularly ones that target adolescents’ self-report. The present study assessed the factor structure, reliability and convergent validity of a new scale to assess adolescents’ perceptions of their mothers’ and fathers’ educational involvement: the Parental Support for Learning Scale: Adolescent Short Form (PSLS-AS). The PSLS-AS, as well as a questionnaire measuring the risk of high school drop-out, was administered to a sample of 825 youth (aged 13–14 years). Exploratory factor analysis revealed a two-factor structure representing parental involvement: Controlling Involvement and Autonomy Supportive Involvement. Adolescents’ perceptions of their parents’ involvement correlated with a risk of high school drop-out. Implications and future directions for further validation of the PSLS-AS are discussed.

Background Because children in out-of-home care lag behind their peers in educational achievement, there have been increased efforts to improve their academic success. Previous research has found that 25 weeks of the Teach Your Children Well (TYCW) tutoring program enhances the academic skills of children in care. Objective This randomized control trial aimed to assess how much TCYW tutoring is enough to accelerate learning. Participants and Setting: In this study, we compared a shorter version of the TCYW method (15 weeks) with a longer version (25 weeks) in a sample of 72 children in care. Method 36 children were randomly assigned to the 15-week group and 36 to the 25-week group. The reading and math tutoring was conducted on a one-on-one basis by paid adult tutors in the children's placement homes. Results With but one exception, ANCOVAs via multiple hierarchical regression revealed no significant differences between the 15 and 25-week tutoring groups on the Woodcock-Johnson (WJ) III reading and math subtests. After we had collapsed across experimental conditions, paired t-tests revealed significant pre-test/post-test improvements on WJ-III Letter-Word Identification, Reading Fluency, Broad Reading composite, Calculation, Math Fluency, Applied Problems, and Broad Math composite. An attribute-treatment interaction analysis, conducted to assess potential moderating variables of the effectiveness of tutoring, revealed that children with higher executive functioning benefited more from the 15-week group. Conclusions Findings suggest that a shorter version of the TYCW program is as effective as a longer version in improving math and reading skills for children in care.

Given that sleep problems and serious motor vehicle collisions are increasingly prevalent in older adults, even minor drowsiness could potentially contribute to driving patterns in older drivers. To date, it is unknown whether less serious problems with sleep influence driving frequency and ability in older adults. We investigated the influence of everyday sleep disturbances on driving practices and driver perceptions in a large cohort of healthy older drivers. Selfreported measures of sleep problems were used to investigate the influence of sleep disturbance on self-reported driving practices and perceived driving abilities. On two measures of self-reported driving outcomes, participants with problems with rated themselves more poorly. However, this relationship disappeared when health and demographic variables were entered prior in hierarchical regression analyses. Our results show that the relationship between sleep problems, driving frequency and perceived abilities is better explained by mediating demographic, health, and cognitive factors.

The present study sought to investigate the influence of subclinical sleep disturbances on driving practices and driver perceptions in a large cohort of healthy older drivers. Participants from the Candrive II prospective cohort study were investigated. Self-reported measures of sleep problems were used to determine the influence of sleep disturbance on self-reported driving practices and perceived driving abilities, as measured by the Situational Driving Frequency, Situational Driving Avoidance, and Perceived Driving Abilities scales. Hierarchical regression analyses were used to estimate whether mild self-reported sleep problems were predictive of driving restrictions and perceived abilities, while controlling for a variety of health-related factors and demographic variables known to mediate sleep problems or to impact driving. Cross-sectional analysis of baseline data from the Candrive II study suggests that subclinical sleep problems do not significantly influence self-reported driving patterns or perceived driving abilities in older drivers once control variables are considered. The relationship between sleep problems, driving frequency, avoidance and perceived abilities is better explained by mediating demographic, health, and cognitive factors. Further research examining sleep disturbances and driving should include objective measures of driving practices (exposure, patterns) and outcomes (crashes, violations) and should take in consideration the severity of sleep problems.

The privilege of driving a vehicle is often a fundamental part of individuals’ daily lives. For many individuals who have suffered a traumatic brain injury (TBI), the ability to return to driving post TBI is an integral step to recovering independence and enhancing community reintegration (Rapport et al., 2008). Approximately 50% of TBI survivors with moderate to severe injuries resume driving, often irrespective of medical-legal evaluations (Fisk, Schneider, & Novack, 1998; Lew et al., 2005; Tamietto et al., 2006). Evidently, helping TBI survivors return to safe driving plays a pivotal role in their path to recovery and reintegration to the community. A proper assessment of a TBI survivor’s strengths and weaknesses can help prevent harm to the driver and other members of society and further enable their return to productive roles, work, and other favored activities. For instance, Kreutzer and colleagues (2003) revealed that the ability to drive post TBI is an independent moderator for employment stability. Determining whether a TBI survivor is safe or unsafe to drive remains a challenging issue since driving is a functional task with varying levels of complexity that can be potentially compensated for if impairments exist. Unfortunately, two negative outcomes may occur as a result of inaccurate driving assessment. The first negative outcome may be removing the privilege to drive from a TBI survivor who is either safe to drive, or could become safe to drive after retraining or further recovery (false positive result). The second outcome is a false negative result where the brain injury survivor is a potentially unsafe driver who is allowed to resume driving. Previous research suggests that TBI drivers tend to receive greater traffic violations (Haselkorn et al., 1998), tend to drive slower (in a simulated environment; Stinchcombe et al., 2008), and perhaps most importantly, have an increased crash risk compared to uninjured controls (e.g., Formisano et al., 2005; Lundqvist et al., 2008; but see Haselkorn et al., 1998; Schultheis et al., 2002). For example, Schanke and colleagues (2008) assessed driving behaviour of TBI survivors both pre and post injury. Results indicated that the accident rate of the TBI survivors was twice as high as that of the general population. Cyr and colleagues (2009) observed that in a simulated driving environment, TBI survivors who had returned to driving, compared to uninjured controls, were significantly more likely to crash in reaction to a surprising and challenging event.