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Biomedical subjects

David F Dinges

Publications and source records attributed to David F Dinges.

At least 37 records · Page 2Linked to original sources
PubMed2005

Individual differences in adult human sleep and wakefulness: Leitmotif for a research agenda.

This paper reviews the literature on interindividual variability in human sleep parameters, sleepiness, responses to sleep deprivation, and manifestations of sleep disorders. Variability among individuals in sleep/wake biology and behavior is pervasive. The magnitude of such individual differences is often considerable and comparable to the effect sizes of many experimental and clinical interventions. Evidence is accumulating that certain aspects of sleep/wake-related variability--such as sleep duration, daytime sleepiness, and vulnerability to the effects of sleep loss--involve trait characteristics in healthy populations and among sleep-disordered patients. Establishing the trait-specific nature of variability in sleep/wake parameters is a prerequisite for elucidating the corresponding neurophysiologic and/or genetic mechanisms. At present, it remains largely unknown what underlies or predicts sleep/wake-related traits, what relationships these traits may have to each other, and what functional significance may be associated with specific traits. Scientific studies addressing these issues are warranted, as understanding the basis of trait variability may yield new insights into sleep/wake regulation and sleep pathology. Understanding individual differences in sleep and wakefulness may also have provocative but important implications for health economics and clinical care, as well as for safety, productivity, and general well-being. This paper gives suggestions for a research agenda focusing on individual differences in sleep research and sleep medicine.

Adolescent↗
PubMed2005

Claustrophobia and adherence to CPAP treatment.

This study evaluated the effect of claustrophobia, an abnormal dread or fear of closed spaces, on adherence to continuous positive airway pressure (CPAP) therapy. The design was a secondary analysis of data from a prospective study of participants (N = 153) that completed 3 months of CPAP therapy from seven sleep disorders centers in the United States and Canada. A 15-item subscale adapted from the Fear and Avoidance Scale measured claustrophobic tendencies pre-CPAP treatment and again after 3 months. An overt monitor attached to the CPAP machines recorded mask-on CPAP adherence. There was a statistically significant difference in claustrophobia scores by adherence group (< 2 hours, 2 to < 5 hours, > or = 5 hours) and time period (pre-CPAP and after 3 months CPAP). Poor CPAP adherence (< 2 hours per night)was more than two times higher in participants with a claustrophobia score > or = 25. Identification of persons with increased claustrophobia tendencies and targeted interventions may increase adherence.

Adult↗
PubMed2005

Optical computer recognition of facial expressions associated with stress induced by performance demands.

Application of computer vision to track changes in human facial expressions during long-duration spaceflight may be a useful way to unobtrusively detect the presence of stress during critical operations. To develop such an approach, we applied optical computer recognition (OCR) algorithms for detecting facial changes during performance while people experienced both low- and high-stressor performance demands. Workload and social feedback were used to vary performance stress in 60 healthy adults (29 men, 31 women; mean age 30 yr). High-stressor scenarios involved more difficult performance tasks, negative social feedback, and greater time pressure relative to low workload scenarios. Stress reactions were tracked using self-report ratings, salivary cortisol, and heart rate. Subjects also completed personality, mood, and alexithymia questionnaires. To bootstrap development of the OCR algorithm, we had a human observer, blind to stressor condition, identify the expressive elements of the face of people undergoing high- vs. low-stressor performance. Different sets of videos of subjects' faces during performance conditions were used for OCR algorithm training. Subjective ratings of stress, task difficulty, effort required, frustration, and negative mood were significantly increased during high-stressor performance bouts relative to low-stressor bouts (all p < 0.01). The OCR algorithm was refined to provide robust 3-d tracking of facial expressions during head movement. Movements of eyebrows and asymmetries in the mouth were extracted. These parameters are being used in a Hidden Markov model to identify high- and low-stressor conditions. Preliminary results suggest that an OCR algorithm using mouth and eyebrow regions has the potential to discriminate high- from low-stressor performance bouts in 75-88% of subjects. The validity of the workload paradigm to induce differential levels of stress in facial expressions was established. The paradigm also provided the basic stress-related facial expressions required to establish a prototypical OCR algorithm to detect such changes. Efforts are underway to further improve the OCR algorithm by adding facial touching and automating application of the deformable masks and OCR algorithms to video footage of the moving faces as a prelude to blind validation of the automated approach.

Adult↗
PubMed2005

The cognitive interview: does it successfully avoid the dangers of forensic hypnosis?

Seventy-two undergraduates viewed a videotape of a bank robbery that culminated in the shooting of a young boy. Several days later, participants were interviewed about their recollection of events in the film through baseline oral and written narrative accounts followed by random assignment to a hypnosis (HYP) condition, the cognitive interview (CI), or a motivated, repeated recall (MRR) control interview. Participants also completed a forced interrogatory recall test, which indexed potential report criterion differences between the interview conditions. In terms of information provided for the first time during treatment interviews, HYP led to greater productivity than the CI or the MRR interview, which did not differ significantly from each other. Evidence that these differences in recall resulted primarily from report criterion differences rather than differences in accessible memory was obtained from the forced interrogatory recall test. In this test, no differences were observed between the three interview conditions. Finally, the data revealed that participants' hypnotic ability was associated with the recall of erroneous and confabulatory material for those tested in the HYP and CI conditions but not those in the MRR condition. This suggests that some CI mnemonics may invoke hypnotic-like processes in hypnotizable people.

Adult↗
PubMed2005

The neural basis of the psychomotor vigilance task.

STUDY OBJECTIVE: To identify brain regions underlying the fastest and slowest reaction times on the Psychomotor Vigilance task (PVT) under well-rested conditions, as well as brain regions related to particularly poor performance after sleep deprivation. DESIGN: Subjects took the PVT twice while undergoing functional magnetic resonance imaging: once 12 hours after waking from a normal night of sleep and once after 36 hours of total sleep deprivation (TSD). Session order was counterbalanced. SETTING: UCSD J. Christian Gillin Laboratory for Sleep and Chronobiology (the sleep core of the General Clinical Research Center) and UCSD Magnetic Resonance Institute. PATIENTS OR PARTICIPANTS: Twenty right-handed healthy adults (8 women; age = 27.4 +/- 6.7 years; education = 15.6 +/- 1.5 years). MEASUREMENTS AND RESULTS: After a normal night of sleep, optimal performance was related to greater cerebral responses within a cortical sustained attention network and the cortical and subcortical motor systems. Slow reaction times, particularly after TSD, were associated with greater activity in the "default mode network" consisting of frontal and posterior midline regions. CONCLUSIONS: Optimal performance on the PVT appears to rely on activation both within the sustained attention system and within the motor system. Poor performance following TSD may result from a disengagement from the task and related inattention, and brain regions responsible for this localize within midline structures shown to be involved in the brain's "default mode." Finally, particularly poor performance after TSD may elicit a subsequent attentional recovery that manifests as greater activation within the same regions normally responsible for fast reaction times.

Adult↗
PubMed2004

Systematic interindividual differences in neurobehavioral impairment from sleep loss: evidence of trait-like differential vulnerability.

OBJECTIVES: To investigate interindividual differences in neurobehavioral deficits during sleep deprivation, and to establish to what extent the neurobehavioral responses to sleep loss are a function of sleep history versus trait-like differential vulnerability. DESIGN: Individuals were exposed to sleep deprivation on 3 separate occasions in order to determine the stability of interindividual differences in neurobehavioral impairment. SETTING: The sleep-deprivation experiments were conducted under standardized laboratory conditions with continuous monitoring of wakefulness. Each subject underwent a laboratory-adaptation session before entering the sleep-deprivation phase of the study. PARTICIPANTS: A total of 21 healthy adults (aged 21-38 years) completed the experiment. INTERVENTIONS: Subjects came to the laboratory 3 times at intervals of at least 2 weeks. During each laboratory session, they underwent neurobehavioral testing every 2 hours during 36 hours of total sleep deprivation, which was preceded by baseline sleep and followed by recovery sleep. In the week prior to each sleep-deprivation session and on the baseline night in the laboratory, subjects were required to either restrict their sleep to 6 hours per day (prior sleep restriction condition) or to extend their time in bed to 12 hours per day (prior sleep extension condition), so as to experimentally manipulate sleep history (in randomized counterbalanced order). RESULTS: There was strong evidence that interindividual differences in neurobehavioral deficits during sleep deprivation were systematic and trait-like. The magnitude of interindividual variability was substantial relative to the magnitude of the effect of prior sleep restriction (which on average involved a reduction of 4.1 hours sleep per day, compared to prior sleep extension, for 7 days). Overall, interindividual differences were not explained by subjects' baseline functioning or a variety of other potential predictors. Interindividual variability clustered on 3 distinct neurobehavioral dimensions: self-evaluation of sleepiness, fatigue, and mood; cognitive processing capability; and behavioral alertness as measured by sustained attention performance. CONCLUSIONS: Neurobehavioral deficits from sleep loss varied significantly among individuals and were stable within individuals. Interindividual differences in neurobehavioral responses to sleep deprivation were not merely a consequence of variations in sleep history. Rather, they involved trait-like differential vulnerability to impairment from sleep loss, for which neurobiologic correlates have yet to be discovered.

Adaptation, Psychological↗
PubMed2004

Effect of sleep loss on C-reactive protein, an inflammatory marker of cardiovascular risk.

OBJECTIVES: We sought to investigate the effects of sleep loss on high-sensitivity C-reactive protein (CRP) levels. BACKGROUND: Concentrations of high-sensitivity CRP are predictive of future cardiovascular morbidity. In epidemiologic studies, short sleep duration and sleep complaints have also been associated with increased cardiovascular morbidity. Two studies were undertaken to examine the effect of acute total and short-term partial sleep deprivation on concentrations of high-sensitivity CRP in healthy human subjects. METHODS: In Experiment 1, 10 healthy adult subjects stayed awake for 88 continuous hours. Samples of high-sensitivity CRP were collected every 90 min for 5 consecutive days, encompassing the vigil. In Experiment 2, 10 subjects were randomly assigned to either 8.2 h (control) or 4.2 h (partial sleep deprivation) of nighttime sleep for 10 consecutive days. Hourly samples of high-sensitivity CRP were taken during a baseline night and on day 10 of the study protocol. RESULTS: The CRP concentrations increased during both total and partial sleep deprivation conditions, but remained stable in the control condition. Systolic blood pressure increased across deprivation in Experiment 1, and heart rate increased in Experiment 2. CONCLUSIONS: Both acute total and short-term partial sleep deprivation resulted in elevated high-sensitivity CRP concentrations, a stable marker of inflammation that has been shown to be predictive of cardiovascular morbidity. We propose that sleep loss may be one of the ways that inflammatory processes are activated and contribute to the association of sleep complaints, short sleep duration, and cardiovascular morbidity observed in epidemiologic surveys.

Adult↗
PubMed2004

Circadian eating and sleeping patterns in the night eating syndrome.

OBJECTIVE: To compare the eating and sleep-wake patterns of persons with the night eating syndrome (NES) with those of matched control subjects. RESEARCH METHODS AND PROCEDURES: Forty-six overweight/obese NES subjects (mean age 43.3 +/- 9.8 years; 32 women) and 43 similar controls (mean age 39.0 +/- 11.0 years; 28 women) wore wrist actigraphs for 7 days and completed sleep and food diaries at home. RESULTS: There was no difference between the total energy intake of the NES and the control subjects, but the pattern of energy intake differed greatly. Relative to control subjects, the temporal pattern of food intake of night eaters was delayed. Food intake after the evening meal, as a proportion of the 24-hour intake, was more than 3-fold greater in NES subjects than in controls (34.6 +/- 10.1% vs. 10.0 +/- 6.9%, p = 0.001). NES subjects had sleep onset, offset, and total sleep duration times comparable with those of controls. NES subjects reported more nocturnal awakenings than did controls (1.5 +/- 1.0 per night vs. 0.5 +/- 0.5; p < 0.001), and their actigraphically monitored arousals occurred earlier during sleep (at 128 minutes after sleep onset vs. 193 minutes, p = 0.01). NES subjects consumed food on 74% of the awakenings vs. 0% for the controls. DISCUSSION: The pattern of cumulative energy intake of the night eaters suggests a phase delay in energy consumption relative to sleep-wake times. NES may involve a dissociation of the circadian control of eating relative to sleep.

Activity Cycles↗
PubMed2004

Summary of the key features of seven biomathematical models of human fatigue and performance.

BACKGROUND: Biomathematical models that quantify the effects of circadian and sleep/wake processes on the regulation of alertness and performance have been developed in an effort to predict the magnitude and timing of fatigue-related responses in a variety of contexts (e.g., transmeridian travel, sustained operations, shift work). This paper summarizes key features of seven biomathematical models reviewed as part of the Fatigue and Performance Modeling Workshop held in Seattle, WA, on June 13-14, 2002. The Workshop was jointly sponsored by the National Aeronautics and Space Administration, U.S. Department of Defense, U.S. Army Medical Research and Materiel Command, Office of Naval Research, Air Force Office of Scientific Research, and U.S. Department of Transportation. METHODS: An invitation was sent to developers of seven biomathematical models that were commonly cited in scientific literature and/or supported by government funding. On acceptance of the invitation to attend the Workshop, developers were asked to complete a survey of the goals, capabilities, inputs, and outputs of their biomathematical models of alertness and performance. Data from the completed surveys were summarized and juxtaposed to provide a framework for comparing features of the seven models. RESULTS: Survey responses revealed that models varied greatly relative to their reported goals and capabilities. While all modelers reported that circadian factors were key components of their capabilities, they differed markedly with regard to the roles of sleep and work times as input factors for prediction: four of the seven models had work time as their sole input variable(s), while the other three models relied on various aspects of sleep timing for model input. Models also differed relative to outputs: five sought to predict results from laboratory experiments, field, and operational data, while two models were developed without regard to predicting laboratory experimental results. All modelers provided published papers describing their models, with three of the models being proprietary. CONCLUSIONS: Although all models appear to have been fundamentally influenced by the two-process model of sleep regulation by Borbély, there is considerable diversity among them in the number and type of input and output variables, and their stated goals and capabilities.

Aircraft↗
PubMed2004

Nonlinear mixed-effects modeling: individualization and prediction.

The development of biomathematical models for the prediction of fatigue and performance relies on statistical techniques to analyze experimental data and model simulations. Statistical models of empirical data have adjustable parameters with a priori unknown values. Interindividual variability in estimates of those values requires a form of smoothing. This traditionally consists of averaging observations across subjects, or fitting a model to the data of individual subjects first and subsequently averaging the parameter estimates. However, the standard errors of the parameter estimates are assessed inaccurately by such averaging methods. The reason is that intra- and inter-individual variabilities are intertwined. They can be separated by mixed-effects modeling in which model predictions are not only determined by fixed effects (usually constant parameters or functions of time) but also by random effects, describing the sampling of subject-specific parameter values from probability distributions. By estimating the parameters of the distributions of the random effects, mixed-effects models can describe experimental observations involving multiple subjects properly (i.e., yielding correct estimates of the standard errors) and parsimoniously (i.e., estimating no more parameters than necessary). Using a Bayesian approach, mixed-effects models can be "individualized" as observations are acquired that capture the unique characteristics of the individual at hand. Mixed-effects models, therefore, have unique advantages in research on human neurobehavioral functions, which frequently show large inter-individual differences. To illustrate this we analyzed laboratory neurobehavioral performance data acquired during sleep deprivation, using a nonlinear mixed-effects model. The results serve to demonstrate the usefulness of mixed-effects modeling for data-driven development of individualized predictive models of fatigue and performance.

Bayes Theorem↗
PubMed2004

Dealing with inter-individual differences in the temporal dynamics of fatigue and performance: importance and techniques.

Inter-individual differences in performance impairment from sleep loss are substantial and consistent, as demonstrated and quantified here by means of the intraclass correlation coefficient (ICC) in two laboratory-based sleep deprivation studies. There is an urgent need, therefore, to consider inter-individual variability in biomathematical models of fatigue and performance, which currently treat individuals as being all the same. Traditional regression techniques do not handle inter-individual variability, but cutting-edge mixed-effects modeling techniques have recently become available to deal with inter-individual differences in the temporal dynamics of fatigue and performance. The standard two stage (STS), restricted maximum likelihood (REML), and non-linear mixed-effects modeling (NMEM) approaches to mixed-effects models are compared here using data from a chronic partial sleep deprivation experiment. Mixed-effects modeling can be incorporated in the two distinct steps (the direct and inverse problems) of biomathematical model development in order to deal with inter-individual differences. This paper demonstrates that inter-individual variability accounts for a large percentage of observed variance in neurobehavioral responses to sleep deprivation, and describes tools that model developers will need to produce a new generation of fatigue and performance models capable of incorporating inter-individual variability and useful for subject-specific prediction.

Fatigue↗
PubMed2004

Critical research issues in development of biomathematical models of fatigue and performance.

This article reviews the scientific research needed to ensure the continued development, validation, and operational transition of biomathematical models of fatigue and performance. These models originated from the need to ascertain the formal underlying relationships among sleep and circadian dynamics in the control of alertness and neurobehavioral performance capability. Priority should be given to research that further establishes their basic validity, including the accuracy of the core mathematical formulae and parameters that instantiate the interactions of sleep/wake and circadian processes. Since individuals can differ markedly and reliably in their responses to sleep loss and to countermeasures for it, models must incorporate estimates of these inter-individual differences, and research should identify predictors of them. To ensure models accurately predict recovery of function with sleep of varying durations, dose-response curves for recovery of performance as a function of prior sleep homeostatic load and the number of days of recovery are needed. It is also necessary to establish whether the accuracy of models is affected by using work/rest schedules as surrogates for sleep/wake inputs to models. Given the importance of light as both a circadian entraining agent and an alerting agent, research should determine the extent to which light input could incrementally improve model predictions of performance, especially in persons exposed to night work, jet lag, and prolonged work. Models seek to estimate behavioral capability and/or the relative risk of adverse events in a fatigued state. Research is needed on how best to scale and interpret metrics of behavioral capability, and incorporate factors that amplify or diminish the relationship between model predictions of performance and risk outcomes.

Circadian Rhythm↗