Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

Using Multivariate Statistics

Researchers studying work—family conflict, and to a lesser extent work—family enrichment, have often relied on Frone, Russell, and Cooper’s domain specificity model to explain the relationships between bidirectional work—family interactions and family and job satisfaction. However, in more recent times, theorists have proposed an alternative model, the source attribution perspective, which predicts a different pattern of relationships. Using meta-analytic path analysis, the present study compared competing hypotheses to examine the relative merits of each theory for both positive and negative work—family interactions. The results universally supported the less popular source attribution perspective. The moderating role of gender in the pattern of relationships was also considered.

Reconsidering work-family interactions and satisfaction: A meta-analysis: (518422013-318)

Much clinical work has utilized Chapman’s (1995) ‘love languages’ model to promote relationship satisfaction, yet the model remains untested. This study addressed this issue by testing the hypothesis that couples with aligned love languages would report higher relationship satisfaction; we also explored the role that self-regulation played in promoting satisfaction. Sixty-seven heterosexual couples were assessed on love language preference, self-regulation and relationship satisfaction. Results provided limited evidence that love language alignment promotes satisfaction; rather self-regulation contributed greater variance in satisfaction. Dyadic analyses identified that female self-regulation positively impacted both male and female relationship satisfaction when couples had dissimilar primary love languages, although significant actor effects were also important predictors for both genders. The outcomes of this study suggest that the effectiveness of Chapman’s model may be dependent upon both spouses exhibiting appropriate self-regulatory behaviors, and that female self-regulation plays an important role in predicting relationship satisfaction for both partners when they have different preferred love languages.

Walking the walk, talking the talk: Love languages, self-regulation and relationship satisfaction

https://files.eric.ed.gov/fulltext/ED585106.pdf

Working Before, During, and after Beginning at a Public 2-Year Institution: Labor Market Experiences of Community College Students. Stats in Brief. NCES 2018-428.

166 COPYRIGHT 2018 BY PSI CHI, THE INTERNATIONAL HONOR SOCIETY IN PSYCHOLOGY (SPECIAL ISSUE, VOL. 23, NO. 2/ISSN 2325-7342) The common characteristics of college students have been changing, particularly over the past decade; in addition to an increase in older students and students who are also parents, the majority of students now also hold a job outside of school. According to the National Center for Education Statistics (NCES, 2012), 25.9% of college students work full time, 36.4% work part time, and only 37.7% reported not working while going to school. The American College Health Association (2015) reported that most students no longer live on campus, such that 40.4% live in off-campus housing and only 34.5% live on campus in residence halls. In addition to living off campus, many students also take online or distance classes in order to better balance their multiple roles; more specifically, 26.4% of college students and 30.8% of postbaccalureate students reported taking at least one distance education course (NCES, 2013). This shift from students primarily not working, living on campus, and taking in-person courses to the current demographics described has given rise to a large group of students who are balancing multiple roles. Regardless of the reason a person elects to return to or begin schooling, research has demonstrated that transitioning to college often results in significant life changes such as elevated levels of stress and negative affect, declines in physical health (Gall, Evans, & Bellerose, 2000; Pritchard, Wilson, & Yamnitz, 2007), and a disruption in the balance

Not All Roles Are the Same: An Examination Between Work-Family-School Satisfaction, Social Integration, and Negative Affect Among College Students Balancing Multiple Roles

Sleep quality has been well-researched and supported as a predictor of physical and mental health (Ohayon et al., 2017). In 2016, The National Sleep Foundation provided an evidence-based set of recommendations regarding indicators of good sleep quality. Across the 277 studies included in the review, shorter sleep onset latencies, fewer awakenings, and higher sleep efficiency were indicators of good sleep quality across the lifespan (Ohayon et al., 2017). In contrast, poor sleep quality has been linked to a myriad of adverse consequences including increased stress responsivity, cognitive, memory, and performance deficits, impairment in emotion regulation, and increases in negative emotions (Medic et al., 2017; O’Leary et al., 2016). Poor sleep quality is also linked to long-term physical health difficulties including hypertension, cardiovascular disease, and weight-related issues (Medic et al., 2017). There is evidence that sleep disturbances and comorbid psychological and medical diagnoses have a cyclical influence such that sleep problems lead to greater decline in general and psychological health, which in turn worsens sleep problems (Kaplan & Harvey, 2014). Cognitive behavioral therapy for insomnia (CBT-I) is a psychological treatment comprised of sleep hygiene strategies including stimulus control, relaxation, and cognitive restructuring of dysfunctional beliefs about sleep. CBT-I posits that maladaptive beliefs about sleep are critical targets in treatment (Kaplan & Harvey, 2014). A randomized control trial conducted by Eidelman et al. (2016) found that individuals who participated in CBT-I had a significant decrease in dysfunctional beliefs about sleep and had reduced insomnia symptoms and impairment at both post-treatment and follow-up when compared to behavioral or cognitive therapy alone. A meta-analysis conducted by Geiger-Brown et al. (2015) found that CBT-I improved subjective sleep quality post-treatment, reduced sleep onset latency, improved total sleep time, and increased sleep efficiency among those with comorbid diagnoses, and treatment effects were stable at follow-up. ABSTRACT. Sleep quality is correlated with physical and mental health and is an important target for overall well-being. CBT-I is an evidence-based strategy to improve sleep quality; however, shortage of qualified providers; logistical issues such as cost, travel, and time; privacy concerns; and a desire to resolve symptoms on one’s own limit access to CBT-I. Compared to traditional face-to-face or web-based delivery of CBT-I, app-delivered CBT-I may be an efficacious alternative capitalizing on the portability, privacy, and accessibility of mobile phones. The present study examined the effectiveness of the CBT-I Coach for educating participants about the importance of healthy sleep practices and dysfunctional beliefs about sleep and targeted sleep. The use of the CBT-I Coach resulted in significant improvements in sleep quality, dysfunctional beliefs about sleep, sleep hygiene behaviors, and sleep efficiency. This study supports the use of CBT-I Coach as an effective intervention for improving sleep quality.

Angela B. Duncan

Papers

The Effects of App-Delivered Cognitive Behavioral Therapy for Insomnia (CBT-I) on Sleep Quality, Dysfunctional Beliefs, and Sleep Hygiene