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Parasomnias are a group of sleep disorders characterized by abnormal and unpleasant motor, verbal, or behavioral events that occur during sleep or during transitions between wake and sleep states. They disrupt sleep and can have a detrimental impact on the individual experiencing them. Our goal was to identify types of parasomnias and their prevalence in the current and recent post-secondary student population and to explore their coping strategies for parasomnias they found distressing. Seventy-seven post-secondary students completed the 21-item Munich Parasomnia Screening (MUPS) frequency scale. They also rated, on a 10-point scale, how disturbing each parasomnia experienced was. Not only did 92% percent of students report at least one parasomnia, but our results also indicate that the vast majority of students experienced several parasomnias. This led us to investigate the likelihood of the co-occurrence of different parasomnias. With respect to the level of subjectively experienced distress, the most prevalent parasomnias were not always the more disturbing. Coded open-ended responses about what students do about the disturbing parasomnias indicate that grounding strategies (i.e., coping strategies that help manage distressing feelings) and physical manipulation of one's body were the most common, although most participants indicated that in spite of distress, they do nothing to cope. In conclusion, our study found a strikingly high prevalence of parasomnias in this sample of young adults and a lack of knowledge about effective means of dealing with these. Therefore, we provide some accepted ways of dealing with these. [ABSTRACT FROM AUTHOR]

In an email-based questionnaire study, we investigated chronotype, sleep, and well-being among junior/community college students with (n = 52) and without disabilities (n = 27) during remote (COVID-19-related) and subsequent in-person learning periods. Overall, we found no significant differences between students with and without disabilities either in chronotype or in sleep quality. Morningness and intermediate chronotypes were related to better sleep quality during both the remote and in-person periods. We also found that sleep quality was better during the remote period than during the in-person period. This finding was robust as we identified this both in quantitative and qualitative results. We also discovered that, surprisingly, students had little concern with the possibility of catching the COVID-19 virus. Findings on well-being during the remote and in-person periods were mixed, although we noted mainly negative experiences during the in-person period. The findings make it clear that return to "in person" was not "return to normal." [ABSTRACT FROM AUTHOR]

The Sleep Behaviors Scale: 60+, which is a measure for insomnia, was developed and applied to a sample of older adults who were either poor or good sleepers. The measure proved useful and was able to further classify individuals into high- and low-distress groups. It used four subscales in the evaluation of results, namely, active behaviors, relaxation, cognitive arousal and medication.

The aims of this study were to examine the presence, type, and severity of insomnia complaints in obstructive sleep apnea (OSA) patients and to assess the utility of the Sleep Symptom Checklist (SSC) for case identification in primary care. Participants were 88 OSA patients, 57 cognitive-behavioral therapy for insomnia (CBT-I) patients, and 14 healthy controls (Ctrl). Each completed a sleep questionnaire as well as the SSC, which includes insomnia, daytime functioning, psychological, and sleep disorder subscales. Results showed that OSA patients could be grouped according to 3 insomnia patterns: no insomnia (OSA), n = 21; insomnia (OSA-I), n = 30, with a subjective complaint and disrupted sleep; and noncomplaining poor sleepers (OSA-I-NC), n = 37. Comparisons among the OSA, CBT-I, and Ctrl groups demonstrate distinct profiles on the SSC subscales, indicating its potential utility for both case identification and treatment planning. [ABSTRACT FROM AUTHOR]

Background: Medication use data are usually collected in clinical research. Yet no standardized method for categorizing these exists, either for sample description or for the study of medication use as a variable., Objective: The present investigation was designed to develop a simple, empirically based classification scheme for medication use categorization., Method: The authors used factor analysis to reduce the number of possible medication groupings. This permitted a pattern of medication usage to emerge that appeared to characterize specific clinical constellations. To illustrate the technique's potential, the authors applied this classification system to samples where sleep disorders are prominent: chronic fatigue syndrome and sleep apnea., Results: The authors' classification approach resulted in 5 factors that appear to cohere in a logical fashion. These were labeled Cardiovascular or Metabolic Syndrome Medication, Symptom Relief Medication, Psychotropic Medication, Preventative Medication, and Hormonal Medication., Conclusions: The findings show that medication profile varies according to clinical sample. The medication profile for participants with sleep apnea reflects known comorbid conditions; the medication profile associated with chronic fatigue syndrome appears to reflect the common perception of this condition as a psychogenic disorder.