Dataset Information

Predicting Attentional Impairment in Women With Posttraumatic Stress Disorder Using Self-Reported and Objective Measures of Sleep.

ABSTRACT: STUDY OBJECTIVES:There is growing evidence to support sleep impairment as a core feature of posttraumatic stress disorder (PTSD). Sleep impairment in PTSD is associated with severe distress and poorer treatment outcomes. Therefore, specific attention to this symptom of PTSD is warranted and accurate assessment of sleep impairment is critical. The current study investigated the association between self-reported and objective assessment of sleep and sustained attention in women with PTSD. METHODS:Study participants include 50 treatment-seeking, female, interpersonal violence survivors who have PTSD. Nocturnal sleep duration was measured with self-report sleep diaries and objective actigraphy assessment over the course of 7 nights. Sustained attention during daytime was measured by the Psychomotor Vigilance Task (PVT). RESULTS:Results indicated that self-reported nocturnal sleep duration, but not objective or global sleep quality measures, best predicted attentional deficits as indicated by lapses and inverse reaction time on the PVT. Daily sleep diaries predicted 19% and 14% of the variance in attentional lapses and inverse reaction time, respectively. CONCLUSIONS:In a sample of women with PTSD, self-reported nocturnal sleep duration predicted deficits in sustained attention. Conversely, sleep duration as measured by actigraphy and global sleep quality, did not predict sustained attention. Findings suggest that assessing sleep impairment on a daily basis may provide clinically relevant information in evaluating daytime symptoms and provide guidance in targeting this particularly troublesome symptom in the treatment of PTSD. CITATION:Werner KB, Arditte Hall KA, Griffin MG, Galovski TE. Predicting attentional impairment in women with posttraumatic stress disorder using self-reported and objective measures of sleep. J Clin Sleep Med. 2019;15(9):1329-1336.

SUBMITTER: Werner KB

PROVIDER: S-EPMC6760408 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting Attentional Impairment in Women With Posttraumatic Stress Disorder Using Self-Reported and Objective Measures of Sleep.

Werner Kimberly B KB Arditte Hall Kimberly A KA Griffin Michael G MG Galovski Tara E TE

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 20190901 9

<h4>Study objectives</h4>There is growing evidence to support sleep impairment as a core feature of posttraumatic stress disorder (PTSD). Sleep impairment in PTSD is associated with severe distress and poorer treatment outcomes. Therefore, specific attention to this symptom of PTSD is warranted and accurate assessment of sleep impairment is critical. The current study investigated the association between self-reported and objective assessment of sleep and sustained attention in women with PTSD.< ...[more]

PMID: 31538604

Similar Datasets

Project description:Study objectivesTo investigate the association between self-reported and objective measures of sleep and wind turbine noise (WTN) exposure.MethodsThe Community Noise and Health Study, a cross-sectional epidemiological study, included an in-house computer-assisted interview and sleep pattern monitoring over a 7 d period. Outdoor WTN levels were calculated following international standards for conditions that typically approximate the highest long-term average levels at each dwelling. Study data were collected between May and September 2013 from adults, aged 18-79 y (606 males, 632 females) randomly selected from each household and living between 0.25 and 11.22 kilometers from operational wind turbines in two Canadian provinces. Self-reported sleep quality over the past 30 d was assessed using the Pittsburgh Sleep Quality Index. Additional questions assessed the prevalence of diagnosed sleep disorders and the magnitude of sleep disturbance over the previous year. Objective measures for sleep latency, sleep efficiency, total sleep time, rate of awakening bouts, and wake duration after sleep onset were recorded using the wrist worn Actiwatch2® from a subsample of 654 participants (289 males, 365 females) for a total of 3,772 sleep nights.ResultsParticipant response rate for the interview was 78.9%. Outdoor WTN levels reached 46 dB(A) with an arithmetic mean of 35.6 and a standard deviation of 7.4. Self-reported and objectively measured sleep outcomes consistently revealed no apparent pattern or statistically significant relationship to WTN levels. However, sleep was significantly influenced by other factors, including, but not limited to, the use of sleep medication, other health conditions (including sleep disorders), caffeine consumption, and annoyance with blinking lights on wind turbines.ConclusionsStudy results do not support an association between exposure to outdoor WTN up to 46 dB(A) and an increase in the prevalence of disturbed sleep. Conclusions are based on WTN levels averaged over 1 y and, in some cases, may be strengthened with an analysis that examines sleep quality in relation to WTN levels calculated during the precise sleep period time.

Project description:ObjectivesThe aim of this study was to evaluate the agreement between self-reported sleep measures and insomnia with objectively measured sleep parameters in people with HIV (PWH) and HIV-negative individuals.DesignA cross-sectional analysis of PWH and lifestyle-similar HIV-negative individuals.MethodsSelf-reported measures included time spent in bed, sleep onset latency and a validated insomnia questionnaire. Objective measures were assessed via 7-days/nights of actigraphy data to determine average and intra-individual variability of several sleep measures (including time spent in bed and onset latency). Spearman's correlation coefficient and Cohen's κ were used to assess the agreement between self-reported and actigraphy-assessed measures. Associations between insomnia and actigraphy-assessed sleep parameters were evaluated using partial least-square discriminant analysis (PLS-DA).ResultsWe found fair correlation between self-reported and actigraphy-assessed time spent in bed in 342 PWH (rs = 0.46) and 119 HIV-negative individuals (rs = 0.48). Among PWH, the correlation did not differ by age, education, depressive symptoms and self-reported insomnia (all P > 0.05), but was stronger in men (P = 0.05) and in those with a BMI of at least 25 kg/m2 (P < 0.001). Agreement between self-reported and actigraphy-assessed sleep onset latency was poor in both PWH (κ = 0.002, P = 0.49) and HIV-negative individuals (κ = 0.009, P = 0.65). According to PLS-DA, self-reported insomnia most strongly correlated with intra-individual variability of sleep duration, movement index and efficiency.ConclusionWe report poor-to-fair agreement between self-reported and actigraphy-assessed sleep measures in PWH. Insomnia symptoms correlated with regularity of sleep duration, quality and efficiency. These findings highlight the importance of both patient-reported and objective measures of daily sleep variation, for better understanding sleep disorders in PWH.

Project description:Researchers interested in the effect of health on various life outcomes (such as employment, earnings and life satisfaction) often use self-reported health and disease status as an indicator of true, underlying health status. Self-reports appear to be reasonable measures of overall health. For example, self-assessed overall health has been found to be a reliable predictor of mortality. However, the validity of self-reports is questionable when investigating specific diseases such as diabetes and hypertension. A small and nascent body of research comparing self-reported status on certain diseases with the true status based on clinical diagnoses has found significant gaps. These validation exercises predominantly use data from high-income countries. In this paper, we use survey data from India to compare self-reports of disease prevalence to diagnostic tests conducted on the same individuals. We focus on hypertension and lung disease, two of the primary causes of death in India. We find that self-reported measures substantially understate the true disease burden for both conditions. The attenuation bias from using self-reports is over 80 percent for both diseases, and bigger than estimates from high-income countries. We test and reject the hypothesis that self-reports of the disease status are identical to the true disease status in expectation. We identify characteristics associated with false negative reporting (reporting not having the disease but testing positive for it) for both diseases. The large awareness gap between self-reports and true disease burden indicates multiple deficiencies in India's public health policy. The survey data depicts limited access to medical facilities, high levels of health illiteracy, low rates of health insurance, and other barriers related to poverty and lack of equity in the delivery of health services. These factors prevent timely intervention for managing health and controlling disease, invariably leading to morbidity and often to premature death.

Dataset Information

Predicting Attentional Impairment in Women With Posttraumatic Stress Disorder Using Self-Reported and Objective Measures of Sleep.

Publications

Predicting Attentional Impairment in Women With Posttraumatic Stress Disorder Using Self-Reported and Objective Measures of Sleep.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets