scholarly journals Mothers’ Attitudes as Organizers of Discipline Practices and Related Anticipatory Processes

2018 ◽  
Author(s):  
Michael F Lorber ◽  
Jaimee Stuart
Keyword(s):  
Heart Rate ◽  
Social Cognitive ◽  
Negative Emotion ◽  
Electrodermal Activity ◽  
Laboratory Assessment ◽  
Negative Attitudes ◽  
Maternal Attitudes ◽  
Observational Measure ◽  
Electrodermal Reactivity ◽  
Lax Discipline

We hypothesized that mothers’ negative attitudes toward their toddlers would set in motion an anticipatory social cognitive-affective cascade that influenced their parenting during immediately subsequent discipline encounters. Ninety-seven mothers of 2- to 3-year-old children completed a laboratory assessment consisting of (a) an interview/observational measure of their attitudes toward their toddlers, questionnaires tapping (b) expectancies of their children’s difficult behavior in upcoming discipline encounters and (c) anticipatory changes in their own experience of negative emotion, (d) measures of anticipatory changes in their heart rate and electrodermal activity, and (e) observations of their overreactive and lax discipline. Negative maternal attitudes were associated with lax discipline, negative expectancies, and anticipatory electrodermal reactivity. Negative expectancies were associated with anticipatory increases in mothers’ experience of negative emotion. Other than negative maternal attitudes, however, no factor in the hypothesized social cognitive-affective cascade predicted discipline. Thus, the hypothesized model was not fully supported by the data.

scholarly journals Gender Differences in Stress Responses during a Virtual Reality Trier Social Stress Test

2019 ◽  
Vol 19 (2) ◽  
Author(s):  
Julia Santl ◽  
Youssef Shiban ◽  
Andreas Plab ◽  
Stefan Wüst ◽  
Brigitte M. Kudielka ◽  
...  
Keyword(s):  
Gender Differences ◽  
Heart Rate ◽  
Virtual Reality ◽  
Stress Responses ◽  
Social Stress ◽  
Electrodermal Activity ◽  
Stress Test ◽  
Trier Social Stress Test ◽  
Cortisol Responses ◽  
Electrodermal Reactivity

The Trier Social Stress Test (TSST) is commonly used to induce stress in laboratories by instructing participants to deliver a speech and to solve arithmetic tasks in front of a committee. Its implementation in virtual reality (VR) enables an investigation of stress responses under highly standardized controllable conditions. The aim of this study was to compare stress responses among men and women in a VR version of the TSST (VR-TSST). To this end, 16 women taking oral contraceptives and 16 men underwent the VR-TSST in a modified version including a competitor. Stress ratings, heart rate, electrodermal reactivity, and salivary cortisol responses were analyzed. The VR-TSST induced endocrine, peripher-physiological and self-reported stress responses, indicated by a significant increase in heart rate, electrodermal activity and stress ratings as well as a small but significant cortisol response. Significant gender differences were found only for stress ratings. In conclusion, these findings confirm earlier results that VR is suitable to induce social stress both in males and females.

Smiling won’t make you feel better: Response-focused emotion regulation strategies have little impact on cognitive, behavioural, physiological, and subjective outcomes

2020 ◽  
Author(s):  
Nancy Bahl ◽  
Allison Ouimet
Keyword(s):  
Emotion Regulation ◽  
Negative Emotion ◽  
Electrodermal Activity ◽  
Adaptive Strategy ◽  
Expressive Suppression ◽  
Memory Accuracy ◽  
Cognitive Behavioural ◽  
Regulation Strategies ◽  
The Common ◽  
Subjective Outcomes

Background and Objectives. Response-focused emotion regulation (RF-ER) strategies may alter people’s evoked emotions, influencing psychophysiology, memory accuracy, and affect. Researchers have found that participants engaging in expressive suppression (ES; a RF-ER strategy) experience increased sympathetic nervous system arousal, affect (i.e., higher subjective anxiety and negative emotion), and lowered memory accuracy. It is unclear, however, whether all RF-ER strategies exert maladaptive effects. Expressive dissonance (ED; displaying an expression opposite from how one feels) is a RF-ER strategy, and thus likely considered “maladaptive”. As outlined by the facial feedback hypothesis, however, smiling may increase positive emotion, suggesting it may be an adaptive strategy. We compared the effects of ED and ES to a control condition on psychophysiology, memory accuracy, and affect, to assess whether ED is an adaptive RF-ER strategy, relative to ES. Methods. We randomly assigned 144 female participants to engage in ED, ES, or to naturally observe, while viewing negative and arousing images. We recorded electrodermal activity and self-reported affect throughout the experiment and participants completed memory tasks. Results. There were no differences between groups across outcomes. Conclusion. Engaging in ES or ED may not lead to negative or positive impacts, shedding doubt on the common conclusion that specific strategies are categorically adaptive or maladaptive.

scholarly journals Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3461
Author(s):  
Blake Anthony Hickey ◽  
Taryn Chalmers ◽  
Phillip Newton ◽  
Chin-Teng Lin ◽  
David Sibbritt ◽  
...  
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Electrodermal Activity ◽  
Smart Devices ◽  
Stress Detection ◽  
Wearable Technologies ◽  
Detection Of Stress ◽  
Anxiety Depression

Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depression, or stress. The included articles that assessed stress and anxiety unanimously used heart rate variability (HRV) parameters for detection of anxiety and stress, with the latter better detected by HRV and electroencephalogram (EGG) together. Electrodermal activity was used in recent studies, with high accuracy for stress detection; however, with questionable reliability. Depression was found to be largely detected using specific EEG signatures; however, devices detecting depression using EEG are not currently available on the market. This systematic review highlights that average heart rate used by many commercially available smart devices is not as accurate in the detection of stress and anxiety compared with heart rate variability, electrodermal activity, and possibly respiratory rate.

Quantifying Occupational Stress in Intensive Care Unit Nurses: An Applied Naturalistic Study of Correlations Among Stress, Heart Rate, Electrodermal Activity, and Skin Temperature

2021 ◽  
pp. 001872082110408
Author(s):  
Nima Ahmadi ◽  
Farzan Sasangohar ◽  
Tariq Nisar ◽  
Valerie Danesh ◽  
Ethan Larsen ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Heart Rate ◽  
Intensive Care ◽  
Skin Temperature ◽  
Electrodermal Activity ◽  
Laboratory Research ◽  
Prior Literature ◽  
High Level ◽  
Intensive Care Unit Nurses ◽  
Skin Temperatures

Objective To identify physiological correlates to stress in intensive care unit nurses. Background Most research on stress correlates are done in laboratory environments; naturalistic investigation of stress remains a general gap. Method Electrodermal activity, heart rate, and skin temperatures were recorded continuously for 12-hr nursing shifts (23 participants) using a wrist-worn wearable technology (Empatica E4). Results Positive correlations included stress and heart rate (ρ = .35, p < .001), stress and skin temperature (ρ = .49, p < .05), and heart rate and skin temperatures (ρ = .54, p = .0008). Discussion The presence and direction of some correlations found in this study differ from those anticipated from prior literature, illustrating the importance of complementing laboratory research with naturalistic studies. Further work is warranted to recognize nursing activities associated with a high level of stress and the underlying reasons associated with changes in physiological responses. Application Heart rate and skin temperature may be used for real-time detection of stress, but more work is needed to validate such surrogate measures.

scholarly journals Trends in Heart-Rate Variability Signal Analysis

2021 ◽  
Vol 3 ◽  
Author(s):  
Syem Ishaque ◽  
Naimul Khan ◽  
Sri Krishnan
Keyword(s):  
Machine Learning ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Electrodermal Activity ◽  
Well Being ◽  
Good Health ◽  
Machine Learning Techniques ◽  
Video Gaming ◽  
Clinical Events ◽  
Learning Techniques

Heart rate variability (HRV) is the rate of variability between each heartbeat with respect to time. It is used to analyse the Autonomic Nervous System (ANS), a control system used to modulate the body's unconscious action such as cardiac function, respiration, digestion, blood pressure, urination, and dilation/constriction of the pupil. This review article presents a summary and analysis of various research works that analyzed HRV associated with morbidity, pain, drowsiness, stress and exercise through signal processing and machine learning methods. The points of emphasis with regards to HRV research as well as the gaps associated with processes which can be improved to enhance the quality of the research have been discussed meticulously. Restricting the physiological signals to Electrocardiogram (ECG), Electrodermal activity (EDA), photoplethysmography (PPG), and respiration (RESP) analysis resulted in 25 articles which examined the cause and effect of increased/reduced HRV. Reduced HRV was generally associated with increased morbidity and stress. High HRV normally indicated good health, and in some instances, it could signify clinical events of interest such as drowsiness. Effective analysis of HRV during ambulatory and motion situations such as exercise, video gaming, and driving could have a significant impact toward improving social well-being. Detection of HRV in motion is far from perfect, situations involving exercise or driving reported accuracy as high as 85% and as low as 59%. HRV detection in motion can be improved further by harnessing the advancements in machine learning techniques.

scholarly journals Quantitative assessment of the relationship between behavioral and autonomic dynamics during propofol-induced unconsciousness

2020 ◽  
Author(s):  
Sandya Subramanian ◽  
Patrick L. Purdon ◽  
Riccardo Barbieri ◽  
Emery N. Brown
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Prediction Models ◽  
Electrodermal Activity ◽  
Strong Relationship ◽  
Pulse Amplitude ◽  
Physiological Data ◽  
Statistical Tool ◽  
Autonomic Changes ◽  
Before And After

ABSTRACTDuring general anesthesia, both behavioral and autonomic changes are caused by the administration of anesthetics such as propofol. Propofol produces unconsciousness by creating highly structured oscillations in brain circuits. The anesthetic also has autonomic effects due to its actions as a vasodilator and myocardial depressant. Understanding how autonomic dynamics change in relation to propofol-induced unconsciousness is an important scientific and clinical question since anesthesiologists often infer changes in level of unconsciousness from changes in autonomic dynamics. Therefore, we present a framework combining physiology-based statistical models that have been developed specifically for heart rate variability and electrodermal activity with a robust statistical tool to compare behavioral and multimodal autonomic changes before, during, and after propofol-induced unconsciousness. We tested this framework on physiological data recorded from nine healthy volunteers during computer-controlled administration of propofol. We studied how autonomic dynamics related to behavioral markers of unconsciousness: 1) overall, 2) during the transitions of loss and recovery of consciousness, and 3) before and after anesthesia as a whole. Our results show a strong relationship between behavioral state of consciousness and autonomic dynamics. All of our prediction models showed areas under the curve greater than 0.75 despite the presence of non-monotonic relationships among the variables during the transition periods. Our analysis highlighted the specific roles played by fast versus slow changes, parasympathetic vs sympathetic activity, heart rate variability vs electrodermal activity, and even pulse rate vs pulse amplitude information within electrodermal activity. Further advancement upon this work can quantify the complex and subject-specific relationship between behavioral changes and autonomic dynamics before, during, and after anesthesia. However, this work demonstrates the potential of a multimodal, physiologically-informed, statistical approach to characterize autonomic dynamics.

A Comparison of the Physiological Demands of Wheelchair Basketball and Wheelchair Tennis

2010 ◽  
Vol 5 (3) ◽  
pp. 301-315 ◽  
Author(s):  
Louise Croft ◽  
Suzanne Dybrus ◽  
John Lenton ◽  
Victoria Goosey-Tolfrey
Keyword(s):  
Heart Rate ◽  
Regression Equations ◽  
Wheelchair Basketball ◽  
Laboratory Assessment ◽  
Basketball Players ◽  
Tennis Players ◽  
High Intensity Training ◽  
Physiological Profiles ◽  
Physiological Demands ◽  
Playing Time

Purpose:To examine the physiological profiles of wheelchair basketball and tennis and specifically to: (a) identify if there are differences in the physiological profiles of wheelchair basketball and tennis players of a similar playing standard, (b) to determine whether the competitive physiological demands of these sports differed (c) and to explore the relationship between the blood lactate [Bla−] response to exercise and to identify the sport specific heart rate (HR) training zones.Methods:Six elite athletes (4 male, 2 female) from each sport performed a submaximal and VO2 peak test in their sport specific wheelchair. Heart rate, VO2, and [Bla−] were measured. Heart rate was monitored during international competitions and VO2 was calculated from this using linear regression equations. Individual HR training zones were identified from the [Bla–] profile and time spent within these zones was calculated for each match.Results:Despite no differences in the laboratory assessment of HRpeak, the VO2peak was higher for the basketball players when compared with the tennis players (2.98 ± 0.91 vs 2.06 ± 0.71; P = .08). Average match HR (163 ± 11 vs 146 ± 16 beats-min–1; P = .06) and average VO2 (2.26 ± 0.06 vs 1.36 ± 0.42 L-min-1; P = .02) were higher during actual playing time of basketball when compared with whole tennis play. Consequently, differences in the time spent in the different training zones within and between the two sports existed (P < .05).Conclusions:Wheelchair basketball requires predominately high-intensity training, whereas tennis training requires training across the exercise intensity spectrum.

Five New Things: Seizure Detection Devices

2021 ◽  
pp. 10.1212/CPJ.0000000000001044
Author(s):  
Alexandra Carrick Atwood ◽  
Cornelia Natasha Drees
Keyword(s):  
Heart Rate ◽  
Motion Detection ◽  
Electrodermal Activity ◽  
False Positive Rate ◽  
Seizure Detection ◽  
Mechanisms Of Action ◽  
Unexpected Death ◽  
Positive Rate ◽  
Convulsive Seizures ◽  
Electroencephalogram Eeg

ABSTRACT:Purpose: The purpose of this paper is to review seizure detection devices, their mechanisms of action, efficacy and reflecting upon potential improvements for future devices.Recent Findings: There are five main categories of seizure detection devices ([email protected]), these include electroencephalogram (EEG), heart rate detection (HR), electrodermal activity (EDA), motion detection and electromyography (EMG). These devices can be used in combination or in isolation to detect seizures. These devices are high in their sensitivity for convulsive seizures, but low in specificity because of a tendency to detect artifact. Overall, they perform poorly identifying non-convulsive seizures.Summary: Seizure detection devices are currently most useful in detecting convulsive seizures and thereby might help against sudden unexpected death in epilepsy (SUDEP), though they have a high false positive rate. These devices are much less adept at detecting more clinically subtle seizures.

scholarly journals Physiological Synchrony in EEG, Electrodermal Activity and Heart Rate Detects Attentionally Relevant Events in Time

2020 ◽  
Vol 14 ◽  
Author(s):  
Ivo V. Stuldreher ◽  
Nattapong Thammasan ◽  
Jan B. F. van Erp ◽  
Anne-Marie Brouwer
Keyword(s):  
Heart Rate ◽  
Stimulus Type ◽  
Electrodermal Activity ◽  
Physiological Signals ◽  
Independent Group ◽  
Top Down ◽  
Event Type ◽  
Physiological Synchrony ◽  
Electroencephalogram Eeg ◽  
Over Time

Interpersonal physiological synchrony (PS), or the similarity of physiological signals between individuals over time, may be used to detect attentionally engaging moments in time. We here investigated whether PS in the electroencephalogram (EEG), electrodermal activity (EDA), heart rate and a multimodal metric signals the occurrence of attentionally relevant events in time in two groups of participants. Both groups were presented with the same auditory stimulus, but were instructed to attend either to the narrative of an audiobook (audiobook-attending: AA group) or to interspersed emotional sounds and beeps (stimulus-attending: SA group). We hypothesized that emotional sounds could be detected in both groups as they are expected to draw attention involuntarily, in a bottom-up fashion. Indeed, we found this to be the case for PS in EDA or the multimodal metric. Beeps, that are expected to be only relevant due to specific “top-down” attentional instructions, could indeed only be detected using PS among SA participants, for EDA, EEG and the multimodal metric. We further hypothesized that moments in the audiobook accompanied by high PS in either EEG, EDA, heart rate or the multimodal metric for AA participants would be rated as more engaging by an independent group of participants compared to moments corresponding to low PS. This hypothesis was not supported. Our results show that PS can support the detection of attentionally engaging events over time. Currently, the relation between PS and engagement is only established for well-defined, interspersed stimuli, whereas the relation between PS and a more abstract self-reported metric of engagement over time has not been established. As the relation between PS and engagement is dependent on event type and physiological measure, we suggest to choose a measure matching with the stimulus of interest. When the stimulus type is unknown, a multimodal metric is most robust.

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