Sleep,resilience, and psychological distress in United States military Veterans

Sleep problems are prevalent among Veterans. Left untreated, such problems may elevate psychological distress and increase risk of subsequent mental health disorders. Psychological resilience may buffer against negative psychological outcomes, yet the relationship between sleep and resilience has not been studied. This study explored poor sleep, resilience, and psychological distress using questionnaires collected as part of the Study of Post-Deployment Mental Health. Participants (N = 1,118) had served in the US military since September 11, 2001, had one or more overseas deployments, and were free from a past-month DSM-defined mental health disorder. Hierarchical linear regression was used to examine the association between poor sleep quality (Pittsburgh Sleep Quality Index total score) and psychological distress (Global Symptom Index; Symptom Checklist-90-R), controlling for demographic and health characteristics. Moderation analyses tested for a potential buffering effect of resilience (Connor-Davidson Resilience Scale). Poor sleeping Veterans had worse physical and psychological health, lower resilience, and endorsed more lifetime traumatic events. Poor sleep was associated with greater psychological distress controlling for health and demographic characteristics. Both resilience factors—adaptability and self-efficacy—had significant buffering effects on the relationship between poor sleep and psychological distress, suggesting that resilience may protect against negative outcomes in poor sleepers. Additional research is warranted to better understand the relationships between sleep, resilience, and psychological distress. Such research may inform pertinent prevention efforts, including interventions that improve sleep, enhance resilience, and protect against incident mental health diagnoses.     

Courseware for observational research (COR): A new approach to teaching naturalistic observation

Naturalistic observation is one of the most basic and widely used techniques of scientific research, yet it often receives only a cursory treatment in the research methods course. In this paper, we describe a new interactive multimedia software program that teaches interval, frequency, and duration coding with the use of brief digitized video clips and model check sheets. The program teaches basic observational techniques by leading students through the stages of developing a behavioral coding scheme, collecting data, establishing interrater reliability, and analyzing with chi square. It also has a laboratory component that allows students to practice their skills.     

COR V2: Teaching observational research with multimedia courseware

Courseware for Observational Research (COR Version 2) is an interactive multimedia program designed to teach the foundation of the scientific method: systematic observation. COR uses digital video with interactive coding to teach basic concepts, such as creating precise operational definitions; using frequency, interval, and duration coding; developing sampling strategies; and analyzing and interpreting data. Through lessons, a case study, and laboratory exercises, it gradually scaffolds students from teacher-directed learning into self-directed learning. The newest addition to COR is a case study in which students work collaboratively, using their own observations to make recommendations about a child’s disruptive behavior in an after-school program. Evaluations of the lessons showed that classes using COR received better grades on their field observations than did those using methods that are more traditional. Students’ confidence and knowledge increased as they moved through each section of the program.     

COR V2: teaching observational research with multimedia courseware.

Courseware for Observational Research (COR Version 2) is an interactive multimedia program designed to teach the foundation of the scientific method: systematic observation. COR uses digital video with interactive coding to teach basic concepts, such as creating precise operational definitions; using frequency, interval, and duration coding; developing sampling strategies; and analyzing and interpreting data. Through lessons, a case study, and laboratory exercises, it gradually scaffolds students from teacher-directed learning into self-directed learning. The newest addition to COR is a case study in which students work collaboratively, using their own observations to make recommendations about a child's disruptive behavior in an after-school program. Evaluations of the lessons showed that classes using COR received better grades on their field observations than did those using methods that are more traditional. Students' confidence and knowledge increased as they moved through each section of the program.