Globalization, socioeconomic restructuring, and community health.

New trends in global public health have social, economic, and political underpinnings that can be found in three 20th century revolutions: globalization, a new epidemiological transition, and an historical shift in patterns of production and consumption throughout the world. Globalization is more than the internationalization of commerce and manufacture; it represents a new development paradigm that creates new links among corporations, international organizations, governments, communities, and families. Social and economic restructuring is reflected in the emerging health profile in underdeveloped countries, including those in Latin America. This emerging profile defies simple categorization, however; while the prevalence of cardiovascular disease and cancer has increased, the traditional diseases (infectious and respiratory disease) are still the leading cause of death. At the same time, industrialized countries are experiencing the re-emergence of those same traditional diseases. These apparent anomalies can be understood by examining class structures within and among countries and by linking health outcomes at the local level to new patterns of production and consumption in the global system.

Short-term total sleep deprivations does not selectively impair higher cortical functioning.

Previous research has shown that total sleep deprivation produces impairment in sustained attention and vigilance especially if the deprivation period is greater than 48 hours. However little is known about the effects of sleep deprivation on performance of tasks considered to be measures of higher cortical functioning such as tests of cognitive flexibility and the capacity to shift from one response set to another. One current hypothesis is that sleep deprivation of a shorter duration (34-36 hours) adversely affects higher cortical function while effects on attention and vigilance tasks are relatively mild. Performance on an intelligence test, a test of sustained attention and tests designed to measure higher cortical function were compared in a group of 29 subjects who underwent 34-36 hours of continuous sleep deprivation and 32 normal sleeping control subjects. No significant group performance differences in the hypothesized direction were noted on any measure. One night of total sleep deprivation does not appear to impair performance on tasks that are designed to assess higher cortical functioning.

Generalized anxiety and sleep architecture: a polysomnographic investigation.

The sleep of 15 adult subjects who reported heightened generalized anxiety in the absence of other psychiatric syndromes and a 15-adult contrast group were studied by means of nocturnal polysomnography. Analysis of polysomnography variables revealed a significant discriminant function that accounted for 79% of the variance between groups, indicating that high-anxiety/worry subjects took longer to fall asleep, had a smaller percentage of deep (slow-wave) sleep, and more frequent transitions into light sleep [stage 1 nonrapid eye movement (NREM)]. Additional analyses indicated that high-anxiety/worry subjects had a greater percentage of light sleep, more early microarousals, a lower rapid eye movement (REM) density relative to low-anxiety subjects. These subjects also showed more electrodermal storming when slow-wave sleep and REM sleep variables were covaried. Results indicated disrupted sleep depth and continuity similar to that documented in clinical anxiety disorder patients and distinct from that of depressed patients. These results indicate that generalized anxiety and worry in otherwise healthy individuals may act to produce a clinically significant sleep disturbance in the absence of other psychiatric symptoms.

Decreased attentional responsivity during sleep deprivation: orienting response latency, amplitude, and habituation.

Ever increasing societal demands for uninterrupted work are causing unparalleled amounts of sleep deprivation among workers. Sleep deprivation has been linked to safety problems ranging from medical misdiagnosis to industrial and vehicular accidents. Microsleeps (very brief intrusions of sleep into wakefulness) are usually cited as the cause of the performance decrements during sleep deprivation. Changes in a more basic physiological phenomenon, attentional shift, were hypothesized to be additional factors in performance declines. The current study examined the effects of 36 hours of sleep deprivation on the electrodermal-orienting response (OR), a measure of attentional shift or capture. Subjects were 71 male undergraduate students, who were divided into sleep deprivation and control (non-sleep deprivation) groups. The expected negative effects of sleep deprivation on performance were noted in increased reaction times and increased variability in the sleep-deprived group on attention-demanding cognitive tasks. OR latency was found to be significantly delayed after sleep deprivation, OR amplitude was significantly decreased, and habituation of the OR was significantly faster during sleep deprivation. These findings indicate impaired attention, the first revealing slowed shift of attention to novel stimuli, the second indicating decreased attentional allocation to stimuli, and the third revealing more rapid loss of attention to repeated stimuli. These phenomena may be factors in the impaired cognitive performance seen during sleep deprivation.

Malingering detection with the dot counting test.

The Dot Counting Test (DCT) offers a technique for malingering detection that is less transparent than the forced-choice testing that has received so much recent attention. The present study defined six dependent variables derived from DCT responses, and examined these variables in the context of differentiating simulators from non-simulators. Four groups of subjects were studied: normal controls, neuropsychological evaluation patients, naive (uncoached) malingering simulators, and sophisticated (coached) malingering simulators. Results demonstrate that the DCT provides several different scores that significantly differ between simulators and non-simulators. The DCT appears to hold promise as an additional tool to neuropsychologists in the detection of malingering.

Dangerousness: assessing the risk of violent behavior.

Results of discriminant analyses for identifying dangerous inpatients and prison inmates are presented. Analysis of a hospital sample (N = 100) yielded a discriminant function containing 5 variables, which was 85% accurate in classifying the sample. Analysis of a prison sample (N = 100) yielded a discriminant model with 6 variables, which was 72% accurate in classifying the sample. Stepwise discriminant analysis of the combined hospital and prison derivation sample (N = 200) yielded a discriminant function containing 8 variables, which was 75% accurate in classifying the sample as dangerous or nondangerous. It was concluded that the derived population-specific (i.e., hospital or prison) models constitute empirically valid measures of dangerousness for the populations studied.

Attention, stress and negative emotion in persistent sleep-onset and sleep-maintenance insomnia.

This study investigated the relation of negative emotions, attention and stress to sleep parameters in insomniacs. It also assessed whether sleep-onset insomniacs differ from sleep-maintenance/mixed insomniacs in the relations of these variables to sleep parameters. Fourteen sleep-onset insomniacs, 13 sleep-maintenance or mixed insomniacs and 13 normal sleepers were recruited using two sequential questionnaires. The groups differed significantly on diagnostically relevant sleep parameters, assessed over 1 week by sleep diary. After completing standard anxiety, anger and depression inventories, subjects participated in two laboratory procedures during which electrophysiological responses were recorded: orienting response habituation and emotional stress elicitation. The 28 significant correlations of sleep parameters with emotion, habituation and stress measures averaged r = 0.415. In multiple regression analyses, emotion, attention and stress variables accounted for an average of 41% of the variance in sleep parameters (mean R = 0.64). Discriminant function analysis using these variables correctly classified 66% of the subjects into the three groups. It was concluded that negative emotions, stress responsiveness and attentional factors interact to influence insomnia.

The prediction of somatic complaints using the Autonomic Nervous System Response Inventory (ANSRI) and the Daily Stress Inventory (DSI).

Understanding and prediction of veridical somatic complaints not caused by disease, dysfunction, trauma, or toxin, requires the assessment of at least two critical variables: predisposition to respond to stressors with peripheral physiological activation; and intensity/frequency/duration of stressors. The Autonomic Nervous System Response Inventory (ANSRI) and the Daily Stress Inventory (DSI) were used to assess these variables, and somatic complaints were recorded using the Wahler Physical Symptoms Inventory (WPSI). Subjects were 72 healthy undergraduates who completed the inventories and reported illness and medication usage over a 2 week period. Regression analyses showed that ANSRI, DSI, illness, and medication accounted for 35% of the variance in somatic complaints, though only ANSRI and DSI contributed significantly. Neuroticism (Eysenck Personality Questionnaire) did not add to R2, but did influence stressors' subjective impact. The correlation between regression equation-generated WPSI scores (derivation sample) and actual WPSI scores (holdout sample) was 0.59. A discriminant function analysis equation (derivation sample) applied to the holdout sample correctly classified 80% of the upper and lower third WPSI subjects. It was concluded that the ANSRI and DSI, and the variables they assess, are substantially related to the self-report of somatic complaints.

The Autonomic Nervous System Response Inventory (ANSRI): prediction of psychophysiological response.

An experiment was conducted to test the validity of the ANSRI by determining whether self-report of physiological response to emotion-provoking imagery could predict individuals' patterns of physiological response to the same imagery. Fifty two undergraduate volunteers completed the ANSRI and, 2 weeks later, reconstructed their original imagery (fear, anger, sadness, joy, activity situations) while seven physiological response systems were recorded polygraphically. The ANSRI scales for a condition (e.g. fear) were entered as predictors of each electrophysiological measure recorded under that condition in Stepwise Multiple Regression Analyses. Forty-nine percent of the analyses were statistically significant (mean R = 0.52; 27% of the variance). Every electrophysiological variable was significantly predicted by the ANSRI's scales under at least one imagery condition, or by using the mean response to items across the five conditions. Cardiovascular, respiration and electrodermal measures were predicted best. Every ANSRI P scale corresponding to an electrophysiological measure was a major variable in the significant prediction of that measure in at least one condition.

The Autonomic Nervous System Response Inventory (ANSRI): discrimination among migraine headache sufferers, muscle contraction headache sufferers, and normal controls.

Twenty-three migraine headache sufferers, sixteen muscle contraction headache sufferers, and thirteen no headache control subjects were selected to test the discriminant validity of the ANSRI. Significant Chi-Squares indicated reliable differences among the groups in ANSRI F scale scores under the Anger condition and in P scale scores based on the means of items across four emotions (All E). Discriminant analyses yielded 69% correct classifications for All E P scales and 58% correct classifications for Anger F scales. All E P scale analyses revealed that the Muscle Tension scale separated the headache groups from the control group. A second function separated the three groups from each other, with the Cardiac, Respiration, and Gastrointestinal scales most responsible. Anger F scale analysis showed the Peripheral Vasoconstriction, Cardiac, and Pattern 2 scales separating the headache groups from each other and from the control group. Results demonstrated discriminant validity for the ANSRI, and were consistent with muscle tension and vasoconstriction as variables in muscle contraction and migraine headache, respectively.

Psychophysiological correlates of levels and stages of cognitive processing.

The psychophysiological manifestations of levels of cognitive processing were investigated. Words were processed at three cognitive levels (phonetic, low semantic, high semantic), and physiological recordings were made during cue, covert processing and verbalization stages. Differentiation of physiological reactivity across processing levels depending on stage of processing was found, with greater activation and incidental recall for the more complex semantic tasks. Heart rate and skin conductance showed greatest increases on trials that were later recalled. Results were interpreted as demonstrating a differentiation of the arousal of task expectancy from cognitive effort associated with processing level.

An Autonomic Nervous System Response Inventory (ANSRI): scaling, reliability, and cross-validation.

The Autonomic Nervous System Response Inventory (ANSRI) was designed to elicit individuals' self-reported patterns of peripheral physiological response to emotion-provoking stimuli. Fifty-one items reflecting such responses were rated as having been present (1 = absent to 5 = intense) during prototypical emotional situations drawn from experience, which were reconstructed and imagined by a subject. Items were rated for each of five conditions, four of which were emotions (fear, anger, sadness, joy) and one of which was an activation control condition (physical activity). Scales were developed to describe the relative activity of different physiological response systems: P scales based on physiological coherence of items and F scales based on factor analytic item clusters. The derivation and contents of the scales are described, and the following psychometric data are reported: test-retest reliabilities and internal consistency coefficients (original and cross-validation samples), factor analyses, and cross-validation of factors. Data indicate that the ANSRI and most of its scales are sufficiently reliable and replicable to warrant validity research.

Psychophysiological response patterns in vascular and muscle-contraction headaches.

The psychophysiological response patterns of 43 headache subjects were compared to the response patterns of 11 nonheadache control subjects. The headache group was composed of subjects diagnosed as suffering from either muscle-contraction (N = 11), classic migraine (N = 11), common migraine (N = 11), or mixed (N = 10) headache. Discriminant analyses indicated that (1) the headache groups could be perfectly differentiated from the nonheadache control group after a period of relaxation and during a period of psychological stress and (2) the stress condition differentiated among the various headache groups. In general, the headache groups showed a higher level of arousal and were more responsive to stress. Also, the response pattern profiles differed among the headache groups in the stress condition. Muscle-contraction subjects tended to respond with higher frontal EMG, and classic migraine and mixed headache groups tended to respond with larger cardiovascular responses.