Adapting Cognitive Interviewing For Early Adolescent Hispanic Girls And Sensitive Topics

Cognitive interviewing is a research technique commonly used in survey research to improve measurement validity. However, this technique is useful to researchers planning to use self-report measures in intervention research because invalidity of such measures jeopardizes detection of intervention effects. Little research currently exists regarding the use of cognitive interviewing techniques with adolescent populations, particularly those who are Hispanic. This article describes common challenges to conducting cognitive interviewing with early adolescent girls and how these challenges are impacted by Hispanic culture and sensitive topics. A focus group approach is recommended over the traditional one-on-one cognitive interview format, and experiences from actual focus groups conducted in preparation for an intervention study are used to illustrate strategies for accomplishing the goals of cognitive interviewing. Creative and careful planning, attention to developmental considerations, and incorporation of cultural values are essential to the success of this approach

Adapting Cognitive Interviewing for Early Adolescent Hispanic Girls and Sensitive Topics

Cognitive interviewing is a research technique commonly used in survey research to improve measurement validity. However, this technique is useful to researchers planning to use self-report measures in intervention research because invalidity of such measures jeopardizes detection of intervention effects. Little research currently exists regarding the use of cognitive interviewing techniques with adolescent populations, particularly those who are Hispanic. This article describes common challenges to conducting cognitive interviewing with early adolescent girls and how these challenges are impacted by Hispanic culture and sensitive topics. A focus group approach is recommended over the traditional one-on-one cognitive interview format, and experiences from actual focus groups, conducted in preparation for an intervention study are used to illustrate strategies for accomplishing the goals of cognitive interviewing. Creative and careful planning, attention to developmental considerations, and incorporation of cultural values are essential to the success of this approach

Ambient Stimuli Perpetuate Nighttime Sleep Disturbances in Hospital Patients With TBI

Background and Objectives: The effect of the ambient environment, sound, light, and movement, on the nighttime rest-activity of patients hospitalized with moderate-severe traumatic brain injury (TBI) is poorly understood. The purpose of this study was to examine how sound, light, and movement in these patients' hospital rooms may contribute to nighttime awakenings. Methods: An observational design was used with 18 adult participants on a neuroscience step-down unit diagnosed with moderate-severe TBI. For up to five consecutive nights, actigraphy was used to capture nighttime awakenings while a custom-made multisensory device captured sound, light, and movement exposures in the participant's room. Results: Participants were awake for 24% (or about 3 hr) of the time during the designated nighttime period of 8 pm to 8 am. Average nighttime exposures of sound was 52 dB, light was nine lumens, and movement, measured as a proportion, was 0.28% or 28%. With each stimuli exposure set at its average, there was a 20% probability of participant nighttime awakenings. Clinically meaningful reductions of movement in and out the participant's room and elevated sound significantly decreases the participant's probability of nighttime awakenings (p < .05), but reductions in light did not. Conclusion: The ambient environment seems to impede restful sleep in immediate post-injury phase of patients with moderate-severe TBI

Interaction of obstructive sleep apnea severity and amyloid burden on novel plasma biomarkers of tau and neurofilament light protein in community‐dwelling cognitively normal older‐adults

Background Recent evidence suggest that plasma Tau and neurofilament light (NfL) have high potential as markers of neurodegeneration in Alzheimer disease (AD). Obstructive sleep apnea (OSA) severity increases AD risk and is associated with well‐validated markers of AD pathology in cognitively normal older‐adults. We determined the independent and combined effects of OSA severity and amyloid burden on plasma levels of Tau, and NfL, in community‐dwelling cognitively normal older‐adults. Method Cross‐sectional analysis of baseline data from 70 community‐dwelling cognitively normal older‐adults, selected from ongoing NYU prospective longitudinal studies on memory, sleep and aging. CSF‐Aβ42 (measured using ELISA) quantified amyloid burden. OSA severity was defined using AHI4%. Levels of plasma Tau and NfL were determined using single molecule array (SIMOA) technology ultra‐sensitive assays. Associations of OSA severity and plasma Tau and NfL were assessed using Pearson correlation analysis. The interactive associations of OSA severity and CSF‐Aβ42 levels on plasma Tau and NfL was assessed using generalized linear models. Analyses were adjusted for age, sex, BMI, education and APOE4. Result Of the 70 participants, 42 (60%) were women. Mean (SD) age was 68.7 (7.1) years. Mean (SD) AHI was 11.4/hr. (13.7) {29 (40%) had AHI 30}. Independent of CSF‐Aβ42, OSA severity was not associated with plasma Tau (r=.11, p‐value=.38), or plasma NfL (r=.05, p‐value=.67). The interactive associations of OSA severity and CSF‐Aβ42 levels on plasma Tau (β =0.042; 95% CI, 0.013 to 0.070) and NfL (β = 0.055; 95% CI, 0.022 to 0.089) were significant, P < .05 for all. The analysis was not powered for generating dichotomized strata specific (i.e. OSA+/Aβ+, OSA+/Aβ‐, OSA‐/Aβ+ and OSA‐/Aβ‐) estimates. Conclusion In this sample of cognitively normal older‐adults, OSA severity was not associated with plasma levels of Tau and NfL. However, β estimates of the interactive associations of OSA severity and CSF‐Aβ42 levels suggest that their combined effect is associated with higher plasma levels of Tau or NfL. Larger cohorts are necessary to delineate mechanisms and examine for OSA/Aβ strata‐specific estimates

Age-associated differences in sleep duration in the US population: potential effects of disease burden

Objectives: We contrasted the relative risks (RR) of short [8 h] sleep experienced by middle-aged (45-64 years) and older (>65 years) adults, compared with young adults (20-44 years). Methods: We utilized NHANES data (2005-2016), capturing sociodemographic, socioeconomic, and health-related data among US adults. Results: The Relative Risk (RR) of short sleep between young and middle-aged adults did not differ [RR = 1.02, NS]. However, the RR of short sleep was significantly reduced among older participants [RR = 0.81, p < 0.01]. Middle-aged adults had significantly lower RR of long sleep [RR = 0.80, p < 0.01], whereas older adults had significantly greater RR of long sleep [RR = 1.41, p < 0.01]. Compared with young adults, older adults with or without increased disease burden had significantly lower RR of short sleep [RR = 0.81, p < 0.01 and RR = 0.80, p < 0.01], respectively. However, for middle-aged adults, the RR of short sleep did not differ whether they reported a greater disease burden. Relative to young adults, older adults with or without disease burden had higher RRs of long sleep [RR = 1.39, p < 0.01] and [RR = 1.45, p < 0.01], respectively. For middle-aged adults without disease burden, the RR of long sleep was lower than among young adults [RR = 0.72, p < 0.01]. Conclusions: Compared with young adults, older adults were not at increased risk for short sleep. Rather, they reported longer sleep time regardless of the presence of disease burden. Future studies should investigate longitudinal effects of aging on objective sleep time, with or without common diseases. (c) 2021 Elsevier B.V. All rights reserved

Wearable and nonwearable sleep-tracking devices

Abstract The current chapter provides a broad and in-depth overview of wearable and nonwearable sleep devices, specifically highlighting their (i) features (hardware and software), (ii) accuracy, reliability, and validity, and (iii) utility and applications in assessment, diagnosis, and management of sleep health parameters including sleep duration, quality, disorders, efficiency, sleep architecture, and sleep stages. We acknowledge and briefly discuss the debate as to whether wearables and nonwearables should be included in traditional sleep and circadian medicine/science. Our suggestion is that wearables and nonwearables must be incorporated in medicine to meet the demands of sleep healthcare delivery

Interactive Associations of Neuropsychiatry Inventory-Questionnaire Assessed Sleep Disturbance and Vascular Risk on Alzheimer's Disease Stage Progression in Clinically Normal Older Adults

Background: To determine whether sleep disturbance (SD) and vascular-risk interact to promote Alzheimer's disease (AD) stage-progression in normal, community-dwelling older adults and evaluate their combined risk beyond that of established AD biomarkers.Methods: Longitudinal data from the National Alzheimer's Coordinating Center Uniform-Dataset. SD data (i.e., SD+ vs. SD-), as characterized by the Neuropsychiatric Inventory-Questionnaire, were derived from 10,600 participants at baseline, with at-least one follow-up visit. A subset (n = 361) had baseline cerebrospinal fluid (CSF) biomarkers and MRI data. The Framingham heart study general cardiovascular disease (FHS-CVD) risk-score was used to quantify vascular risk. Amnestic mild cognitive impairment (aMCI) diagnosis during follow-up characterized AD stage-progression. Logistic mixed-effects models with random intercept and slope examined the interaction of SD and vascular risk on prospective aMCI diagnosis.Results: Of the 10,600 participants, 1,017 (9.6%) reported SD and 6,572 (62%) were female. The overall mean (SD) age was 70.5 (6.5), and follow-up time was 5.1 (2.7) years. SD and the FHS-CVD risk-score were each associated with incident aMCI (aOR: 1.42 and aOR: 2.11, p < 0.01 for both). The interaction of SD and FHS-CVD risk-score with time was significant (aOR: 2.87, p < 0.01), suggesting a synergistic effect. SD and FHS-CVD risk-score estimates remained significantly associated with incident aMCI even after adjusting for CSF (A beta, T-tau, P-tau) and hippocampal volume (n = 361) (aOR: 2.55, p < 0.01), and approximated risk-estimates of each biomarker in the sample where data was available.Conclusions: Clinical measures of sleep and vascular risk may complement current AD biomarkers in assessing risk of cognitive decline in older adults