Publications by authors named "Eric Muth"

58 Publications

The role of self-efficacy and information processing in weight loss during an mHealth behavioral intervention.

Digit Health 2020 Jan-Dec;6:2055207620976755. Epub 2020 Nov 30.

Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, USA.

Self-efficacy (SE) and information processing (IP) may be important constructs to target when designing mHealth interventions for weight loss. The goal of this study was to examine the relationship between SE and IP with weight loss at six-months as part of the Dietary Interventions Examining Tracking with mobile study, a six-month randomized trial with content delivered remotely via twice-weekly podcasts. Participants were randomized to self-monitor their diet with either a mobile app (n = 42) or wearable Bite Counter device (n = 39). SE was assessed using the Weight Efficacy Life-Style Questionnaire and the IP variables assessed included user control, cognitive load, novelty, elaboration. Regression analysis examined the relationship between weight loss, SE change & IP at six months. Results indicate that elaboration was the strongest predictor of weight loss (ß =-0.423, P = 0.011) among all SE & IP variables and that for every point increase in elaboration, participants lost 0.34 kg body weight.
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http://dx.doi.org/10.1177/2055207620976755DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708700PMC
November 2020

A virtual experimenter does not increase placebo hypoalgesia when delivering an interactive expectancy manipulation.

Sci Rep 2020 11 23;10(1):20353. Epub 2020 Nov 23.

Division of Human Centered Computing, School of Computing, Clemson University, Clemson, SC, USA.

Lack of standardization and unblinding threaten the research of mechanisms involved in expectancy effects on pain. We evaluated a computer-controlled virtual experimenter (VEx) to avoid these issues. Fifty-four subjects underwent a baseline-retest heat pain protocol. Between sessions, they received an expectancy manipulation (placebo or no-treatment) delivered by VEx or text-only control condition. The VEx provided standardized "social" interaction with the subjects. Pain ratings and psychological state/trait measures were recorded. We found an interaction of expectancy and delivery on pain improvement following the intervention. In the text conditions, placebo was followed by lower pain, whereas in the VEx conditions, placebo and no-treatment were followed by a comparable pain decrease. Secondary analyses indicated that this interaction was mirrored by decreases of negative mood and anxiety. Furthermore, changes in continuous pain were moderated by expectation of pain relief. However, retrospective pain ratings show an effect of expectancy but not of delivery. We conclude that we successfully applied an automated protocol for inducing expectancy effects on pain. The effect of the VEx regardless of treatment may be due to interactions of attention allocation and locus of control. This points to the diversity of expectancy mechanisms, and has implications for research and computer-based treatment applications.
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http://dx.doi.org/10.1038/s41598-020-77453-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7684301PMC
November 2020

Does maladaptive cardiovagal modulation extend to gastric modulation in women with chronic pelvic pain?

Neurourol Urodyn 2021 Jan 12;40(1):193-200. Epub 2020 Oct 12.

Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.

Background: Women with chronic pelvic pain (CPP) have poor cardiovagal modulation. It is unclear whether this finding reflects a broader abnormality across many systems such as gastro-vagal modulation.

Aim: To determine if maladaptive cardiovagal activity in females with CPP is accompanied by maladaptive gastric myoelectric activity.

Methods: A total of 36 health controls (HC) and 75 CPP underwent supine (10 min), then upright (tilted 70° head up; 30 min), and back to supine (10 min) positions. High-frequency heart rate variability (HF-HRV; 0.15-0.4 Hz) was measured as an index of cardiovagal activity. Cutaneous electrogastrography (EGG) assessed gastric myoelectric activity pre- and during-upright tilt. EGG measures from 16 HC and 31 CPP patients were available for analysis and included relative percentage of gastric activity within the normal (2-4 cpm) and tachygastria (4-10 cpm) ranges, plus ratio of normal/tachygastria.

Results: HF-HRV was lower in CPP individuals at all time points (each p < .05). CPP individuals showed lesser decrease in HF-HRV from supine to upright, and poorer HF-HRV recovery from upright back to supine (F[1, 106] = 4.62, p = .034). HC showed increase in tachygastria activity (t[15] = -2.09, p = .054) while the CPP group showed no change in tachygastria activity from pre-upright to upright (t[30] = -0.62, p = .537).

Conclusions: Individuals with CPP going from supine to upright demonstrate an impairment in both tachygastria and the parallel decrement in HRV. These results support the hypothesis of a generalized blunting in the physiological modulation in CPP individuals affecting both cardiovascular and gastric systems.
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http://dx.doi.org/10.1002/nau.24532DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902291PMC
January 2021

In Memoriam: Robert M. Stern.

Neurogastroenterol Motil 2020 09 18;32(9):e13970. Epub 2020 Aug 18.

Division of Research and Economic Development, North Carolina Agricultural and Technical State University, Greensboro, NC, USA.

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http://dx.doi.org/10.1111/nmo.13970DOI Listing
September 2020

Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions.

J Acad Nutr Diet 2019 09 30;119(9):1516-1524. Epub 2019 May 30.

Background: Mobile dietary self-monitoring methods allow for objective assessment of adherence to self-monitoring; however, the best way to define self-monitoring adherence is not known.

Objective: The objective was to identify the best criteria for defining adherence to dietary self-monitoring with mobile devices when predicting weight loss.

Design: This was a secondary data analysis from two 6-month randomized trials: Dietary Intervention to Enhance Tracking with Mobile Devices (n=42 calorie tracking app or n=39 wearable Bite Counter device) and Self-Monitoring Assessment in Real Time (n=20 kcal tracking app or n=23 photo meal app).

Participants/setting: Adults (n=124; mean body mass index=34.7±5.6) participated in one of two remotely delivered weight-loss interventions at a southeastern university between 2015 and 2017.

Intervention: All participants received the same behavioral weight loss information via twice-weekly podcasts. Participants were randomly assigned to a specific diet tracking method.

Main Outcome Measures: Seven methods of tracking adherence to self-monitoring (eg, number of days tracked, and number of eating occasions tracked) were examined, as was weight loss at 6 months.

Statistical Analyses Performed: Linear regression models estimated the strength of association (R) between each method of tracking adherence and weight loss, adjusting for age and sex.

Results: Among all study completers combined (N=91), adherence defined as the overall number of days participants tracked at least two eating occasions explained the most variance in weight loss at 6 months (R=0.27; P<0.001). Self-monitoring declined over time; all examined adherence methods had fewer than half the sample still tracking after Week 10.

Conclusions: Using the total number of days at least two eating occasions are tracked using a mobile self-monitoring method may be the best way to assess self-monitoring adherence during weight loss interventions. This study shows that self-monitoring rates decline quickly and elucidates potential times for early interventions to stop the reductions in self-monitoring.
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http://dx.doi.org/10.1016/j.jand.2019.03.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856872PMC
September 2019

Between- and Within-Subjects Predictors of the Kilocalorie Content of Bites of Food.

J Acad Nutr Diet 2019 07 16;119(7):1109-1117. Epub 2019 Feb 16.

Background: This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables.

Objective: The purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex.

Participants/setting: Seventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured.

Main Outcome Measures: The outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods.

Statistical Analyses Performed: Multilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance.

Results: All hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB.

Conclusions: This model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures.
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http://dx.doi.org/10.1016/j.jand.2018.12.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592756PMC
July 2019

Bite count rates in free-living individuals: new insights from a portable sensor.

BMC Nutr 2018 18;4:23. Epub 2018 May 18.

Department Electrical & Computer Engineering Department, Clemson University, Clemson, SC 29634-0915 USA.

Background: Conclusions regarding bite count rates and body mass index (BMI) in free-living populations have primarily relied on self-report. The objective of this exploratory study was to compare the relationship between BMI and bite counts measured by a portable sensor called the Bite Counter in free-living populations and participants eating in residence.

Methods: Two previously conducted studies were analyzed for relationships between BMI and sensor evaluated bite count/min, and meal duration. Participants from the first study ( = 77) wore the bite counter in a free-living environment for a continuous period of 14 days. The second study ( = 214) collected bite count/min, meal duration, and total energy intake in participants who consumed one meal in a cafeteria. Linear regression was applied to examine relationships between BMI and bite count/min.

Results: There was no significant correlation in the free-living participants average bite counts per second and BMI (R = 0.03,  = 0.14) and a significant negative correlation in the cafeteria participants (  = 0.04,  = 0.03) with higher bite count rates observed in lean versus obese participants. There was a significant correlation between average meal duration and BMI in the free-living participants (  = 0.08,  = 0.01). Total energy intake in the cafeteria participants was also significantly correlated to meal duration (  = 0.31,  < 0.001).

Conclusions: With additional novel applications of the Bite Counter, insights into free-living eating behavior may provide avenues for future interventions that are sustainable for long term application.
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http://dx.doi.org/10.1186/s40795-018-0227-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050775PMC
May 2018

Byte by Bite: Use of a mobile Bite Counter and weekly behavioral challenges to promote weight loss.

Smart Health (Amst) 2017 Sep 26;3-4:20-26. Epub 2017 Apr 26.

Professor, Psychology, Clemson University, Clemson, SC USA.

The goal of this study was to examine the usability and feasibility of the mobile Bite Counter (a watch-like device that detects when a user consumes food or beverage) and the impact of weekly behavioral challenges on diet and physical activity outcomes. Overweight (mean BMI 31.1±4.9 kg/m) adults (n=12) were recruited to participate in a four-week study to test both the usability and feasibility of using the device as part of a behavioral weight loss intervention. Participants were instructed to self-monitor number of bites/day using the Bite Counter, attend weekly group sessions, and listen to weekly podcasts. Participants were given weekly challenges: use a daily bite limit goal (wk1), turn off Bite Counter when fruits/vegetables are consumed (wk2), self-monitor kilocalories vs. bites (wk3), and receive a 10 bites/day bonus for every 30 minutes of exercise (wk4). Participants lost a mean of -1.2±1.3 kg. Only the wk3 challenge produced significant differences in kcal change (wk3 1302±120 kcal/day vs. baseline 2042±302 kcal/d, <0.05). Bite Counter use was significantly correlated with weight loss (= -0.58, P<0.05). Future studies should examine the use of the Bite Counter and impact of behavioral challenges over a longer period of time in a controlled study.
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http://dx.doi.org/10.1016/j.smhl.2017.03.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5663239PMC
September 2017

A comparison of bite size and BMI in a cafeteria setting.

Physiol Behav 2017 Nov 8;181:38-42. Epub 2017 Sep 8.

The Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, United States.

Our study investigated the relationship between BMI and bite size in a cafeteria setting. Two hundred and seventy one participants consumed one meal each. Participants were free to select any food provided by the cafeteria and could return for additional food as desired. Bite weights were measured with a table embedded scale. Data were analyzed with ANOVAs, regressions, Kolmogorov-Smirnov tests, and a repeated measures general linear model for quartile analysis. Obese participants were found to take larger bites than both normal (p=0.002) and overweight participants (p=0.017). Average bite size increased by 0.20g per point increase in BMI. Food bites and drink bites were analyzed individually, showing 0.11g/BMI and 0.23g/BMI slopes, respectively. Quartiles of bites were also analyzed, and a significant interaction was found between normal and obese participants (p=0.034) such that the lower two quartiles were similar, but the upper two quartiles showed an increase in bite size for obese participants. The source of these effects could be the result of a combination of several uncontrolled factors.
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http://dx.doi.org/10.1016/j.physbeh.2017.09.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633523PMC
November 2017

The Dietary Intervention to Enhance Tracking with Mobile Devices (DIET Mobile) Study: A 6-Month Randomized Weight Loss Trial.

Obesity (Silver Spring) 2017 08 10;25(8):1336-1342. Epub 2017 Jun 10.

Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, South Carolina, USA.

Objective: To examine the use of two different mobile dietary self-monitoring methods for weight loss.

Methods: Adults with overweight (n = 81; mean BMI 34.7 ± 5.6 kg/m ) were randomized to self-monitor their diet with a mobile app (App, n = 42) or wearable Bite Counter device (Bite, n = 39). Both groups received the same behavioral weight loss information via twice-weekly podcasts. Weight, physical activity (International Physical Activity Questionnaire), and energy intake (two dietary recalls) were assessed at 0, 3, and 6 months.

Results: At 6 months, 75% of participants completed the trial. The App group lost significantly more weight (-6.8 ± 0.8 kg) than the Bite group (-3.0 ± 0.8 kg; group × time interaction: P < 0.001). Changes in energy intake (kcal/d) (-621 ± 157 App, -456 ± 167 Bite; P = 0.47) or number of days diet was tracked (90.7 ± 9.1 App, 68.4 ± 9.8 Bite; P = 0.09) did not differ between groups, but the Bite group had significant increases in physical activity metabolic equivalents (+2015.4 ± 684.6 min/wk; P = 0.02) compared to little change in the App group (-136.5 ± 630.6; P = 0.02). Total weight loss was significantly correlated with number of podcasts downloaded (r = -0.33, P < 0.01) and number of days diet was tracked (r = -0.33, P < 0.01).

Conclusions: While frequency of diet tracking was similar between the App and Bite groups, there was greater weight loss observed in the App group.
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http://dx.doi.org/10.1002/oby.21889DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529231PMC
August 2017

Assessing the Accuracy of a Wrist Motion Tracking Method for Counting Bites Across Demographic and Food Variables.

IEEE J Biomed Health Inform 2017 05 21;21(3):599-606. Epub 2016 Sep 21.

This paper describes a study to test the accuracy of a method that tracks wrist motion during eating to detect and count bites. The purpose was to assess its accuracy across demographic (age, gender, and ethnicity) and bite (utensil, container, hand used, and food type) variables. Data were collected in a cafeteria under normal eating conditions. A total of 271 participants ate a single meal while wearing a watch-like device to track their wrist motion. A video was simultaneously recorded of each participant and subsequently reviewed to determine the ground truth times of bites. Bite times were operationally defined as the moment when food or beverage was placed into the mouth. Food and beverage choices were not scripted or restricted. Participants were seated in groups of 2-4 and were encouraged to eat naturally. A total of 24 088 bites of 374 different food and beverage items were consumed. Overall the method for automatically detecting bites had a sensitivity of 75% with a positive predictive value of 89%. A range of 62-86% sensitivity was found across demographic variables with slower eating rates trending toward higher sensitivity. Variations in sensitivity due to food type showed a modest correlation with the total wrist motion during the bite, possibly due to an increase in head-toward-plate motion and decrease in hand-toward-mouth motion for some food types. Overall, the findings provide the largest evidence to date that the method produces a reliable automated measure of intake during unrestricted eating.
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http://dx.doi.org/10.1109/JBHI.2016.2612580DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5503793PMC
May 2017

Different Disclosed Probabilities to Receive an Antiemetic Equally Decrease Subjective Symptoms in an Experimental Placebo Study: To Be or Not to Be Sure.

Clin Ther 2017 Mar 20;39(3):487-501. Epub 2016 Dec 20.

Department of Psychosomatic Medicine and Psychotherapy, University Hospital Tübingen, Tübingen, Germany.

Purpose: The purpose of this study was to examine whether the disclosed probability of receiving an antiemetic affects nausea.

Methods: Forty-eight healthy participants (mean [SD] age, 26.8 [5.4] years; 50% female) were exposed to 5 × 2 minutes of nauseogenic body rotations on 2 days. On day 2, participants were randomized to 3 experimental groups that were given different instructions concerning the probability of receiving an antiemetic remedy (100%, 50%, or 0% probability), whereas all received an inert substance. Subjective symptoms, behavioral (rotation tolerance) measures, and physiologic (electrogastrogram) measures of nausea were assessed and mediator and moderator analyses performed for effects of expectations and psychological characteristics on outcomes.

Findings: Disclosed probabilities of both 100% and 50% significantly reduced subjective symptoms of nausea in an equal manner compared with the 0% probability group from day 1 to day 2. This effect was found for neither rotation tolerance nor myoelectric gastric activity. Expectations and psychological characteristics did not affect the results found. Post hoc analyses revealed that women only seem to be susceptible to this placebo effect.

Implications: Nausea is susceptible to placebo effects independent of the disclosed probability of receiving a drug and of explicit expectations. In line with placebo research, this effect is probably attributable to central mechanisms, and it is speculated that it could be related to the reward circuitry and social interactions.
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http://dx.doi.org/10.1016/j.clinthera.2016.11.022DOI Listing
March 2017

Measuring the Consumption of Individual Solid and Liquid Bites Using a Table-Embedded Scale During Unrestricted Eating.

IEEE J Biomed Health Inform 2017 11 24;21(6):1711-1718. Epub 2016 Nov 24.

The universal eating monitor (UEM) is a table-embedded scale used to measure grams consumed over time while a person eats. It has been used in laboratory settings to test the effects of anorectic drugs and behavior manipulations such as slowing eating, and to study relationships between demographics and body weight. However, its use requires restricted conditions on the foods consumed and behaviors allowed during eating in order to simplify analysis of the scale data. Individual bites can only be measured when the only interaction with the scale is to carefully remove a single bite of food, consume it fully, and wait a minimum amount of time before the next bite. Other interactions are prohibited such as stirring and manipulating foods, retrieving or placing napkins or utensils on the scale, and in general anything that would change the scale weight that was not related to the consumption of an individual bite. This paper describes a new algorithm that can detect and measure the weight or individual bites consumed during unrestricted eating. The algorithm works by identifying time periods when the scale weight is stable, and then, analyzing the surrounding weight changes. The series of preceding and succeeding weight changes is compared against patterns for single food bites, food mass bites, and drink bites to determine if a scale interaction is due to a bite or some other activity. The method was tested on 271 subjects, each eating a single meal in a cafeteria setting. A total of 24 101 bites were manually annotated in synchronized videos to establish ground truth as to the true, false, and missed detections of bites. Our algorithm correctly detected and weighed approximately 39% of bites with approximately one false positive (FP) per ten actual bites. The improvement compared to the UEM is approximately three times the number of true detections and a 90% reduction in the number of FPs. Finally, an analysis of bites that could not be weighed compared to those that could be weighed revealed no statistically significant difference in average weight. These results suggest that our algorithm could be used to conduct studies using a table scale outside of laboratory or clinical settings and with unrestricted eating behaviors.
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http://dx.doi.org/10.1109/JBHI.2016.2632621DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5728994PMC
November 2017

Effects of Bite Count Feedback from a Wearable Device and Goal Setting on Consumption in Young Adults.

J Acad Nutr Diet 2016 11 23;116(11):1785-1793. Epub 2016 Jun 23.

Background: New technologies are emerging that may help individuals engage in healthier eating behaviors. One paradigm to test the efficacy of a technology is to determine its effect relative to environment cues that are known to cause individuals to overeat.

Objective: The purpose of this work was to independently investigate two questions: How does the presence of a technology that provides bite count feedback alter eating behavior? and, How does the presence of a technology that provides bite count feedback paired with a goal alter eating behavior?

Design: Two studies investigated these research questions. The first study tested the effects of a large and small plate crossed with the presence or absence of a device that provided bite count feedback on intake. The second study tested the effects of a bite count goal with bite count feedback, again crossed with plate size, on intake. Both studies used a 2×2 between-subjects design.

Participants/setting: In the first study, 94 subjects (62 women aged 19.0±1.6 years with body mass index [BMI] 23.04±3.6) consumed lunch in a laboratory. The second study examined 99 subjects (56 women aged 18.5±1.5 years with BMI 22.73±2.70) under the same conditions.

Intervention: In both studies subjects consumed a single-course meal, using either a small or large plate. In the first study participants either wore or did not wear an automated bite counting device. In the second study all participants wore the bite counting device and were given either a low bite count goal (12 bites) or a high bite count goal (22 bites).

Statistical Analyses: Effect of plate size, feedback, and goal on consumption (grams) and number of bites taken were assessed using 2×2 analyses of variance. As adjunct measures, the effects of serving size, bite size (grams per bite), postmeal satiety, and satiety change were also assessed.

Results: In the first study there was a main effect of plate size on grams consumed and number of bites taken such that eating from a large plate led to greater consumption (P=0.001) and a greater number of bites (P=0.001). There was also a main effect of feedback on consumption and number of bites taken such that those who received feedback consumed less (P=0.011) and took fewer bites (P<0.001). In the second study there was a main effect of plate size on consumption such that those eating from a large plate consumed more (P=0.003) but did not take more bites. Further analysis revealed a main effect of goal on number of bites taken such that those who received the low goal took fewer bites (P<0.001) but did not consume less.

Conclusions: Providing feedback on the number of bites taken from a wearable intake monitor can reduce overall intake during a single meal. Regarding the first research question, providing feedback significantly reduced intake in both plate size groups and reduced the overall number of bites taken. Regarding the second research question, participants were successful in eating to their goals. However, individuals in the low goal condition appeared to compensate for the restricted goal by taking larger bites, leading to comparable levels of consumption between the low and high goal groups. Hence, the interaction of technology with goals should be considered when introducing a health intervention.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5085901PMC
http://dx.doi.org/10.1016/j.jand.2016.05.004DOI Listing
November 2016

Frequency, Not Amplitude, of Latency Affects Subjective Sickness in a Head-Mounted Display.

Aerosp Med Hum Perform 2016 Jul;87(7):604-9

Clemson University, Clemson, SC, USA.

Background: Interactions between frequency and amplitude of latency in head-mounted displays (HMDs) are thought to affect simulator sickness. Many studies have linked system latency to subjective sickness, but recent research has found that at least with the case of inertia-based head tracking technology, latency is not a constant; rather it varies systematically over time due to sensor errors and clock asynchronization. The purpose of this experiment was to further explore the relationship between frequency and amplitude of latency as they relate to subjective sickness experienced in an HMD.

Methods: In a 2 (frequency) × 2 (amplitude) design, 120 subjects were randomly assigned to 4 latency conditions. Frequency of latency was either 0.2 Hz or 1.0 Hz. Amplitude of latency was either 100 ms fixed or 20-100 ms varying.

Results: A main effect of frequency of latency was found. Subjects reported greater sickness in the 0.2-Hz frequency conditions (39.0 ± 27.8) compared to the 1-Hz conditions (30.3 ± 17.0). Additionally, 18 subjects withdrew their participation early in the 0.2-Hz conditions compared to 7 in the 1.0-Hz conditions.

Discussion: In conclusion, frequency of latency appears to play a role in the experience of sickness in HMDs in both subjective reporting of symptoms and subject performance. The current study confirms results of earlier studies, finding that real motion around a frequency of 0.2 Hz is more sickening than other frequencies. Future work should continue to parse the effects of frequency and amplitude of latency in head-tracked HMDs. Kinsella A, Mattfeld R, Muth E, Hoover A. Frequency, not amplitude, of latency affects subjective sickness in a head-mounted display. Aerosp Med Hum Perform. 2016; 87(7):604-609.
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http://dx.doi.org/10.3357/AMHP.4351.2016DOI Listing
July 2016

A virtual experimenter to increase standardization for the investigation of placebo effects.

BMC Med Res Methodol 2016 07 18;16:84. Epub 2016 Jul 18.

Department of Psychology, Clemson University, Clemson, SC, USA.

Background: Placebo effects are mediated by expectancy, which is highly influenced by psychosocial factors of a treatment context. These factors are difficult to standardize. Furthermore, dedicated placebo research often necessitates single-blind deceptive designs where biases are easily introduced. We propose a study protocol employing a virtual experimenter - a computer program designed to deliver treatment and instructions - for the purpose of standardization and reduction of biases when investigating placebo effects.

Methods: To evaluate the virtual experimenter's efficacy in inducing placebo effects via expectancy manipulation, we suggest a partially blinded, deceptive design with a baseline/retest pain protocol (hand immersions in hot water bath). Between immersions, participants will receive an (actually inert) medication. Instructions pertaining to the medication will be delivered by one of three metaphors: The virtual experimenter, a human experimenter, and an audio/text presentation (predictor "Metaphor"). The second predictor includes falsely informing participants that the medication is an effective pain killer, or correctly informing them that it is, in fact, inert (predictor "Instruction"). Analysis will be performed with hierarchical linear modelling, with a sample size of N = 50. Results from two pilot studies are presented that indicate the viability of the pain protocol (N = 33), and of the virtual experimenter software and placebo manipulation (N = 48).

Discussion: It will be challenging to establish full comparability between all metaphors used for instruction delivery, and to account for participant differences in acceptance of their virtual interaction partner. Once established, the presence of placebo effects would suggest that the virtual experimenter exhibits sufficient cues to be perceived as a social agent. He could consequently provide a convenient platform to investigate effects of experimenter behavior, or other experimenter characteristics, e.g., sex, age, race/ethnicity or professional status. More general applications are possible, for example in psychological research such as bias research, or virtual reality research. Potential applications also exist for standardizing clinical research by documenting and communicating instructions used in clinical trials.
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http://dx.doi.org/10.1186/s12874-016-0185-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4950761PMC
July 2016

Resting blood pressure differentially predicts time course in a tonic pain experiment.

Psychophysiology 2016 10 18;53(10):1600-7. Epub 2016 Jul 18.

Department of Psychology, Clemson University, Clemson, South Carolina, USA.

Resting blood pressure (BP) shows a negative relationship with pain sensitivity (BP-related hypoalgesia). In chronic pain conditions, this relationship is inverted. The precise mechanisms responsible for the inversion are unknown. Using a tonic pain protocol, we report findings closely resembling this inversion in healthy participants. Resting BP and state measures of anxiety and mood were assessed from 33 participants (21 female). Participants then immersed their dominant hand in painfully hot water (47 °C) for five trials of 1-min duration, with 30-s intertrial intervals. Throughout the trials, participants continually registered their pain. After a 35-min intermission, the trial sequence was repeated. A disassociation of the negative relationship of resting systolic BP (as per Trial 1) was found using hierarchical linear modeling (p < .001, R(2)  = .07). The disassociation unfolds over each consecutive trial, with an increasingly positive relationship. In Sequence 2, the initially negative relationship is almost completely absent. Furthermore, the association of BP and pain was found to be moderated by anxiety, such that only persons with low anxiety exhibited BP hypoalgesia. Our findings expand the existing literature by incorporating anxiety as a moderator of BP hypoalgesia. Furthermore, the protocol emulates the changing relationship between BP and pain observed in chronic pain patients. The protocol has potential as a model for chronic pain; however, future research should determine if similar physiological systems are involved. The finding holds potential diagnostic or prognostic relevance for certain clinical pain conditions, especially those involving dysfunction of the descending modulation of pain.
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http://dx.doi.org/10.1111/psyp.12724DOI Listing
October 2016

Crowdsourcing for self-monitoring: Using the Traffic Light Diet and crowdsourcing to provide dietary feedback.

Digit Health 2016 Jan-Dec;2:2055207616657212. Epub 2016 Jul 12.

Holcombe Department of Electrical and Computer Engineering, Clemson University, USA.

Background: Smartphone photography and crowdsourcing feedback could reduce participant burden for dietary self-monitoring.

Objectives: To assess if untrained individuals can accurately crowdsource diet quality ratings of food photos using the Traffic Light Diet (TLD) approach.

Methods: Participants were recruited via Amazon Mechanical Turk and read a one-page description on the TLD. The study examined the participant accuracy score (total number of correctly categorized foods as red, yellow, or green per person), the food accuracy score (accuracy by which each food was categorized), and if the accuracy of ratings increased when more users were included in the crowdsourcing. For each of a range of possible crowd sizes ( = 15,  = 30, etc.), 10,000 bootstrap samples were drawn and a 95% confidence interval (CI) for accuracy constructed using the 2.5th and 97.5th percentiles.

Results: Participants ( = 75; body mass index 28.0 ± 7.5; age 36 ± 11; 59% attempting weight loss) rated 10 foods as red, yellow, or green. Raters demonstrated high red/yellow/green accuracy (>75%) examining all foods. Mean accuracy score per participant was 77.6 ± 14.0%. Individual photos were rated accurately the majority of the time (range = 50%-100%). There was little variation in the 95% CI for each of the five different crowd sizes, indicating that large numbers of individuals may not be needed to accurately crowdsource foods.

Conclusions: Nutrition-novice users can be trained easily to rate foods using the TLD. Since feedback from crowdsourcing relies on the agreement of the majority, this method holds promise as a low-burden approach to providing diet-quality feedback.
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http://dx.doi.org/10.1177/2055207616657212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6001271PMC
July 2016

Comparison between Human and Bite-Based Methods of Estimating Caloric Intake.

J Acad Nutr Diet 2016 10 14;116(10):1568-77. Epub 2016 Apr 14.

Background: Current methods of self-monitoring kilocalorie intake outside of laboratory/clinical settings suffer from a systematic underreporting bias. Recent efforts to make kilocalorie information available have improved these methods somewhat, but it may be possible to derive an objective and more accurate measure of kilocalorie intake from bite count.

Objective: This study sought to develop and examine the accuracy of an individualized bite-based measure of kilocalorie intake and to compare that measure to participant estimates of kilocalorie intake. It was hypothesized that kilocalorie information would improve human estimates of kilocalorie intake over those with no information, but a bite-based estimate of kilocalorie intake would still outperform human estimates.

Participants/settings: Two-hundred eighty participants were allowed to eat ad libitum in a cafeteria setting. Their bite count and kilocalorie intake were measured. After completion of the meal, participants estimated how many kilocalories they consumed, some with the aid of a menu containing kilocalorie information and some without. Using a train and test method for predictive model development, participants were randomly divided into one of two groups: one for model development (training group) and one for model validation (test group).

Statistical Analysis: Multiple regression was used to determine whether height, weight, age, sex, and waist-to-hip ratio could predict an individual's mean kilocalories per bite for the training sample. The model was then validated with the test group, and the model-predicted kilocalorie intake was compared with human-estimated kilocalorie intake.

Results: Only age and sex significantly predicted mean kilocalories per bite, but all variables were retained for the test group. The bite-based measure of kilocalorie intake outperformed human estimates with and without kilocalorie information.

Conclusions: Bite count might serve as an easily measured, objective proxy for kilocalorie intake. A tool that can monitor bite count may be a powerful assistant to self-monitoring.
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http://dx.doi.org/10.1016/j.jand.2016.03.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5039049PMC
October 2016

Effect of a weight reduction program on baseline and stress-induced heart rate variability in children with obesity.

Obesity (Silver Spring) 2016 Feb 25;24(2):439-45. Epub 2015 Dec 25.

Department of Psychosomatic Medicine and Psychotherapy, University Medical Hospital, Tübingen, Germany.

Objective: Autonomic dysregulation is a well-established feature in adults with obesity but not in children. Since this dysregulation could contribute to weight dynamics, this study aimed to compare autonomic regulation in children with obesity and normal-weight peers and to track autonomic status during weight reduction.

Methods: Sixty children with obesity and 27 age- and sex-matched normal-weight healthy participants were included. Heart rate variability (HRV) was assessed at baseline and during a mental stress test and a subsequent recovery period. Children with obesity were investigated both upon admission and discharge.

Results: Upon admission, no significant differences in HRV parameters were found for normal-weight participants and those with obesity. Inpatient treatment led to significant changes in HRV with increase in general variability (standard deviation of the normal-to-normal interval (SDNN), P < 0.001) as well as of parasympathetic regulation (root mean square successive difference (RMSSD) and high frequency power (logHF), P < 0.01). Children with obesity had sympathetic activation similar to normal-weight controls during mental stress with subsequent return to baseline values, and weight loss did not affect this profile.

Conclusions: A weight reduction program induced a change in autonomic activity in children with obesity toward parasympathetic dominance but had no influence on autonomic nervous system reactivity during stress conditions.
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http://dx.doi.org/10.1002/oby.21355DOI Listing
February 2016

Prediction of Symptom Change in Placebo Versus No-Treatment Group in Experimentally Induced Motion Sickness.

Appl Psychophysiol Biofeedback 2015 Sep;40(3):163-72

Department of Internal Medicine - Psychosomatic Medicine and Psychotherapy, University Hospital Tübingen, Tübingen, Germany,

The long-standing question of who responds to placebo and who does not is of great theoretical and clinical relevance and has received increasing attention in recent years. We therefore performed a post hoc analysis of one of our previously published studies on placebo responses (PRs). In the analysis, fourteen potential predictors for the PR on experimentally induced motion sickness in 32 healthy volunteers were explored using moderated multiple regression. Generalized self-efficacy, generalized self, internal locus of control and cognitive flexibility were significantly associated with symptom improvement in the placebo group, as compared to the untreated control group. Notably, the directions of the associations were such that the "unfavorable" side of the constructs (e.g. low self-efficacy) predicted a higher PR. Instead, the "favorable" side predicted symptom improvement in the control group. Results fit well with prior research into psychological influences on motion sickness. Although PRs in motion sickness are not well established, it is suggested to include the identified constructs in future research involving motion sickness-related symptoms such as nausea and vertigo. Concerning PRs in general, the results may have implications for clinical as well as experimental research on other symptoms and disorders, such as pain or depression.
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http://dx.doi.org/10.1007/s10484-015-9284-yDOI Listing
September 2015

How to study placebo responses in motion sickness with a rotation chair paradigm in healthy participants.

J Vis Exp 2014 Dec 14(94). Epub 2014 Dec 14.

Psychosomatic Medicine and Psychotherapy, University Hospital Tübingen.

Placebo responses occur in every medical intervention when patients or participants expect to receive an effective treatment to relieve symptoms. However, underlying mechanisms of placebo responses are not fully understood. It has repeatedly been shown that placebo responses are associated with changes in neural activity but for many conditions it is unclear whether they also affect the target organ, such as the stomach in motion sickness. Therefore, we present a methodology for the multivariate assessment of placebo responses by subjective, behavioral and objective measures in motion sickness with a rotation chair paradigm. The physiological correlate of motion sickness is a shift in gastric myoelectrical activity towards tachygastria that can be recorded with electrogastrography. The presented study applied the so-called balanced placebo design (BPD) to investigate the effects of ginger compared to placebo and the effects of expectations by verbal information. However, the study revealed no significant main or interactional effects of ginger (as a drug) or information on outcome measures but showed interactions when sex of participants and experimenters are taken into considerations. We discuss limitations of the presented study and report modifications that were used in subsequent studies demonstrating placebo responses when rotation speed was lowered. In general, future placebo studies have to identify the appropriate target organ for the studied placebo responses and to apply the specific methods to assess the physiological correlates.
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http://dx.doi.org/10.3791/52471DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396966PMC
December 2014

Prediction of placebo responses: a systematic review of the literature.

Front Psychol 2014 1;5:1079. Epub 2014 Oct 1.

Department of Internal Medicine - Psychosomatic Medicine and Psychotherapy, University Hospital Tübingen Tübingen, Germany.

Objective: Predicting who responds to placebo treatment-and under which circumstances-has been a question of interest and investigation for generations. However, the literature is disparate and inconclusive. This review aims to identify publications that provide high quality data on the topic of placebo response (PR) prediction.

Methods: To identify studies concerned with PR prediction, independent searches were performed in an expert database (for all symptom modalities) and in PubMed (for pain only). Articles were selected when (a) they assessed putative predictors prior to placebo treatment and (b) an adequate control group was included when the associations of predictors and PRs were analyzed.

Results: Twenty studies were identified, most with pain as dependent variable. Most predictors of PRs were psychological constructs related to actions, expected outcomes and the emotional valence attached to these events (goal-seeking, self-efficacy/-esteem, locus of control, optimism). Other predictors involved behavioral control (desire for control, eating restraint), personality variables (fun seeking, sensation seeking, neuroticism), or biological markers (sex, a single nucleotide polymorphism related to dopamine metabolism). Finally, suggestibility and beliefs in expectation biases, body consciousness, and baseline symptom severity were found to be predictive.

Conclusions: While results are heterogeneous, some congruence of predictors can be identified. PRs mainly appear to be moderated by expectations of how the symptom might change after treatment, or expectations of how symptom repetition can be coped with. It is suggested to include the listed constructs in future research. Furthermore, a closer look at variables moderating symptom change in control groups seems warranted.
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http://dx.doi.org/10.3389/fpsyg.2014.01079DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181242PMC
October 2014

Improving the recognition of eating gestures using intergesture sequential dependencies.

IEEE J Biomed Health Inform 2015 May 5;19(3):825-31. Epub 2014 Jun 5.

This paper considers the problem of recognizing eating gestures by tracking wrist motion. Eating gestures are activities commonly undertaken during the consumption of a meal, such as sipping a drink of liquid or using utensils to cut food. Each of these gestures causes a pattern of wrist motion that can be tracked to automatically identify the activity. Previous works have studied this problem at the level of a single gesture. In this paper, we demonstrate that individual gestures have sequential dependence. To study this, three types of classifiers were built: 1) a K-nearest neighbor classifier which uses no sequential context, 2) a hidden Markov model (HMM) which captures the sequential context of subgesture motions, and 3) HMMs that model intergesture sequential dependencies. We built first-order to sixth-order HMMs to evaluate the usefulness of increasing amounts of sequential dependence to aid recognition. On a dataset of 25 meals, we found that the baseline accuracies for the KNN and the subgesture HMM classifiers were 75.8% and 84.3%, respectively. Using HMMs that model intergesture sequential dependencies, we were able to increase accuracy to up to 96.5%. These results demonstrate that sequential dependencies exist between eating gestures and that they can be exploited to improve recognition accuracy.
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http://dx.doi.org/10.1109/JBHI.2014.2329137DOI Listing
May 2015

PreDictor Research in Obesity during Medical care - weight Loss in children and adolescents during an INpatient rehabilitation: rationale and design of the DROMLIN study.

J Eat Disord 2014 10;2. Epub 2014 Mar 10.

Department of Psychosomatic Medicine and Psychotherapy, University Medical Hospital, Tübingen, Germany ; Department of Psychosomatic Medicine and Psychotherapy, University of Tübingen, Medical Hospital, Frondsbergstrasse 23, 72070 Tübingen, Germany.

Background: Obesity in adults and children is increasing worldwide at alarming rates. Obese children and adolescents are likely to become obese adults with increased risk of a number of comorbidities. In addition to preventing the development of obesity at young age, it is necessary to individualize the therapy of already obese children and adolescents in order to increase the likelihood of weight loss and maintenance. Therefore, the aim of this study is to identify predictors which play a significant role in successful weight loss and weight loss maintenance in children and adolescents.

Methods/design: Over a one year period, 60 obese children and adolescents between 9 to 17 years of age shall be recruited at an inpatient children rehabilitation facility in Germany. They will be investigated twice within a few days following admission and prior to discharge. The study will be an integrated component of an established inpatient weight-loss and in part psychosomatic therapy. The collected data can be grouped into four clusters: 1) demographic, sociometric and psychometric data, 2) objective and subjective parameters of body condition, 3) autonomic nervous system regulated functions and 4) objective and subjective parameters for eating behavior. Primary outcome is the change of the body mass index standard deviation score (BMI-SDS). In order to evaluate the data appropriately, all examinations will be also conducted in a normal-weight reference group, matched for age and gender.

Discussion: For some of the collected parameters the time span between measures may be too short. Therefore, a 6 months, 1 year and 2 year follow-up will be performed for evaluating the different predictors and their influence in regard to a successful intervention. Further middle- and long-term follow-up studies are planned.

Trial Registration: The study protocol was approved by the Ethics Committee of the University Hospital Tübingen, Germany. This study is registered at the German Clinical Trials Register (DRKS) with the clinical trial number DRKS00005122.
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http://dx.doi.org/10.1186/2050-2974-2-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984741PMC
April 2014

Sensitivity and specificity of hypnosis effects on gastric myoelectrical activity.

PLoS One 2013 16;8(12):e83486. Epub 2013 Dec 16.

Department of Psychosomatic Medicine, University Hospital, Tübingen, Germany.

Objectives: The effects of hypnosis on physiological (gastrointestinal) functions are incompletely understood, and it is unknown whether they are hypnosis-specific and gut-specific, or simply unspecific effects of relaxation.

Design: Sixty-two healthy female volunteers were randomly assigned to either a single session of hypnotic suggestion of ingesting an appetizing meal and an unappetizing meal, or to relax and concentrate on having an appetizing or unappetizing meal, while the electrogastrogram (EGG) was recorded. At the end of the session, participants drank water until they felt full, in order to detect EGG-signal changes after ingestion of a true gastric load. During both conditions participants reported their subjective well-being, hunger and disgust at several time points.

Results: Imagining eating food induced subjective feelings of hunger and disgust as well as changes in the EGG similar to, but more pronounced than those seen with a real gastric water load during both hypnosis and relaxation conditions. These effects were more pronounced when imagining an appetizing meal than with an unappetizing meal. There was no significant difference between the hypnosis and relaxation conditions.

Conclusion: Imagination with and without hypnosis exhibits similar changes in subjective and objective measures in response to imagining an appetizing and an unappetizing food, indicating high sensitivity but low specificity.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0083486PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3865216PMC
October 2014

Examining the utility of a bite-count-based measure of eating activity in free-living human beings.

J Acad Nutr Diet 2014 Mar 12;114(3):464-9. Epub 2013 Nov 12.

The obesity epidemic has triggered a need for novel methods for measuring eating activity in free-living settings. Here, we introduce a bite-count method that has the potential to be used in long-term investigations of eating activity. The purpose of our observational study was to describe the relationship between bite count and energy intake and determine whether there are sex and body mass index group differences in kilocalories per bite in free-living human beings. From October 2011 to February 2012, 77 participants used a wrist-worn device for 2 weeks to measure bite count during 2,975 eating activities. An automated self-administered 24-hour recall was completed daily to provide kilocalorie estimates for each eating activity. Pearson's correlation indicated a moderate, positive correlation between bite count and kilocalories (r=0.44; P<0.001) across all 2,975 eating activities. The average per-individual correlation was 0.53. A 2 (sex)×3 (body mass index group: normal, overweight, obese) analysis of variance indicated that men consumed 6 kcal more per bite than women on average. However, there were no body mass index group differences in kilocalories per bite. This was the longest study of a body-worn sensor for monitoring eating activity of free-living human beings to date, which highlights the strong potential for this method to be used in future, long-term investigations.
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http://dx.doi.org/10.1016/j.jand.2013.09.017DOI Listing
March 2014

Detecting periods of eating during free-living by tracking wrist motion.

IEEE J Biomed Health Inform 2014 Jul 17;18(4):1253-60. Epub 2013 Sep 17.

This paper is motivated by the growing prevalence of obesity, a health problem affecting over 500 million people. Measurements of energy intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require a considerable manual effort, leading to underreporting of consumption, noncompliance, and discontinued use over the long term. The purpose of this paper is to describe a new method that uses a watch-like configuration of sensors to continuously track wrist motion throughout the day and automatically detect periods of eating. Our method uses the novel idea that meals tend to be preceded and succeeded by the periods of vigorous wrist motion. We describe an algorithm that segments and classifies such periods as eating or noneating activities. We also evaluate our method on a large dataset (43 subjects, 449 total h of data, containing 116 periods of eating) collected during free-living. Our results show an accuracy of 81% for detecting eating at 1-s resolution in comparison to manually marked event logs of periods eating. These results indicate that vigorous wrist motion is a useful indicator for identifying the boundaries of eating activities, and that our method should prove useful in the continued development of body-worn sensor tools for monitoring energy intake.
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http://dx.doi.org/10.1109/JBHI.2013.2282471DOI Listing
July 2014

What a rude e-mail! Examining the differential effects of incivility versus support on mood, energy, engagement, and performance in an online context.

J Occup Health Psychol 2013 Jul;18(3):297-309

Department of Psychology, Clemson University.

Existing research on workplace incivility has demonstrated an association with a host of negative outcomes, including increased burnout, turnover intentions, and physical symptoms. With the rise in Internet communication over the last decade, interpersonal mistreatment has spilled over to the Internet, but little is known about the impact of incivility communicated via e-mail on employee psychological and performance outcomes. The current study presents a within-subjects experiment wherein incivility and support were manipulated in a laboratory-based simulated workplace setting. Eighty-four participants completed a series of math tasks while interacting with either an uncivil or a supportive supervisor via e-mail. Data were collected on energy, cardiac activity, mood, task performance, and engagement. Findings indicate that participants reported higher levels of negative affect and lower levels of energy after working with the uncivil supervisor than with the supportive supervisor. Additionally, participants performed significantly worse on the math tasks and had lower engagement in the uncivil condition than the supportive condition, and these relationships were mediated by energy. No differences were found in cardiac activity between the two conditions. Results are discussed in terms of their implications for the 21st century world of work.
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http://dx.doi.org/10.1037/a0032851DOI Listing
July 2013