Amber N. Schroeder

Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth

Although the Internet has transformed the way our world operates, it has also served as a venue for cyberbullying, a serious form of misbehavior among youth. With many of todays youth experiencing acts of cyberbullying, a growing body of literature has begun to document the prevalence, predictors, and outcomes of this behavior, but the literature is highly fragmented and lacks theoretical focus. Therefore, our purpose in the present article is to provide a critical review of the existing cyberbullying research. The general aggression model is proposed as a useful theoretical framework from which to understand this phenomenon. Additionally, results from a meta-analytic review are presented to highlight the size of the relationships between cyberbullying and traditional bullying, as well as relationships between cyberbullying and other meaningful behavioral and psychological variables. Mixed effects meta-analysis results indicate that among the strongest associations with cyberbullying perpetration were normative beliefs about aggression and moral disengagement, and the strongest associations with cyberbullying victimization were stress and suicidal ideation. Several methodological and sample characteristics served as moderators of these relationships. Limitations of the meta-analysis include issues dealing with causality or directionality of these associations as well as generalizability for those meta-analytic estimates that are based on smaller sets of studies (k < 5). Finally, the present results uncover important areas for future research. We provide a relevant agenda, including the need for understanding the incremental impact of cyberbullying (over and above traditional bullying) on key behavioral and psychological outcomes.

Comparison of online and traditional performance appraisal systems

Purpose – The purpose of this paper is to compare employee reactions to the use of an online performance appraisal (PA) system to the traditional paper‐and‐pencil (P&P) approach.Design/methodology/approach – A quasi‐experimental study is conducted comparing the reactions of a group of 83 employees evaluate with a traditional P&P PA instrument to the reactions of a group of 152 employees evaluated with an online version of the same assessment tool.Findings – Employees rate with the online version reported significantly higher levels of rater accountability and employee participation than employees rate with the traditional instrument. They report no difference in perceived security of the ratings, utility of the ratings, or satisfaction with the PA. Online employees report significantly lower levels of quality for the PA ratings than traditional employees.Research limitations/implications – The paper is limited to employees in one organization and the variables examined. In the future, researchers should e...

What a Rude E-Mail! Examining the Differential Effects of Incivility Versus Support on Mood, Energy, Engagement, and Performance in an Online Context

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.

Cyber incivility @ work: The new age of interpersonal deviance.

The current study was designed to extend the interpersonal deviance literature into the online domain by examining the incidence and impact of supervisor cyber incivility and neuroticism on employee outcomes at work. Conservation of Resources (COR) theory was used as the guiding framework because cyber incivility is thought to deplete energetic resources in much the same way that other stressors do, ultimately leading to negative outcomes like burnout. Results indicate that supervisor cyber incivility is positively related to burnout, absenteeism, and turnover intentions. Support was also found for the role of neuroticism as a moderator of the relationship between supervisor cyber incivility and outcomes. In general, the relations between cyber incivility and outcomes were stronger for those individuals reporting higher levels of neuroticism. Results are discussed in terms of COR theory, and possible mechanisms for the role of neuroticism in the stressor-strain relationship are discussed. The current study highlights the importance of understanding workplace online behavior and its impact on employee health and organizational well-being. Future research directions examining online interpersonal deviance are suggested.

Chapter 14 Cyber Bullying Among College Students: Evidence from Multiple Domains of College Life

Although media and research accounts of cyber bullying suggest this misbehavior is localized primarily among middle school students, and that its frequency decreases with age, this chapter presents empirical data showing that cyber bullying occurs with considerable frequency among college students across multiple domains of life, specifically school and work. In Study 1, 28 male and 82 female undergraduate students completed a survey examining their online activities as well as their experiences with cyber bullying. Over 30% of the participants indicated that their first experience with cyber bullying was in college. No gender differences were observed with regard to victimization or perpetration, except with online gaming where males reported a higher rate of victimization than females. With regard to personality differences among victims and perpetrators, victims were lower in agreeableness than non-victims. Study 2 examined the prevalence of cyber bullying among 107 college students at work, as well as the negative outcomes linked to the experience of workplace cyber bullying. Nearly a third of the college student sample reported having been the target of cyber bullying within the past six months. Individuals in jobs in which the Internet is essential and racial minorities reported higher rates of cyber bullying at work. Additionally, cyber bullying was positively linked to several negative emotions, as well as burnout and job search effort. These findings have important implications not only for potential negative outcomes that college students may be facing at school and at work but also for organizational justice issues, as differential treatment at work can lead to lawsuits and other negative work outcomes.

Managing heteroscedasticity in general linear models.

Heteroscedasticity refers to a phenomenon where data violate a statistical assumption. This assumption is known as homoscedasticity. When the homoscedasticity assumption is violated, this can lead to increased Type I error rates or decreased statistical power. Because this can adversely affect substantive conclusions, the failure to detect and manage heteroscedasticity could have serious implications for theory, research, and practice. In addition, heteroscedasticity is not uncommon in the behavioral and social sciences. Thus, in the current article, we synthesize extant literature in applied psychology, econometrics, quantitative psychology, and statistics, and we offer recommendations for researchers and practitioners regarding available procedures for detecting heteroscedasticity and mitigating its effects. In addition to discussing the strengths and weaknesses of various procedures and comparing them in terms of existing simulation results, we describe a 3-step data-analytic process for detecting and managing heteroscedasticity: (a) fitting a model based on theory and saving residuals, (b) the analysis of residuals, and (c) statistical inferences (e.g., hypothesis tests and confidence intervals) involving parameter estimates. We also demonstrate this data-analytic process using an illustrative example. Overall, detecting violations of the homoscedasticity assumption and mitigating its biasing effects can strengthen the validity of inferences from behavioral and social science data.

Helping yourself by helping others: examining personality perceptions

– The purpose of this paper is to investigate experimentally the effect of altruistic behavior on personality perceptions, advancement potential, and reward recommendations and assess whether personality perceptions serve as a mediating mechanism between altruistic behavior and job ratings (e.g. advancement potential)., – A randomized experimental design was used to investigate the mediating effect of personality perceptions on the relationship between altruistic behavior and advancement potential and reward recommendations., – It was found that altruistic employees were perceived as having more favorable personality characteristics and received higher advancement potential ratings and greater reward recommendations than their less altruistic counterparts. In addition, personality perceptions were found to mediate partially the relation between altruistic behavior and job ratings (i.e. advancement potential and reward recommendations)., – Research findings on citizenship behavior and personality are often based on the results of non‐experimental designs. This paper utilized a randomized experiment to investigate a mediating effect using a contemporary approach for testing hypothesized mediation.

Forced distribution rating systems: : When does rank and yank lead to adverse impact?

Despite widespread use of forced distribution rating systems (FDRSs), the potential for this performance appraisal method to lead to adverse impact (AI) in a layoff context has yet to be examined empirically. Thus, the current study uses a Monte Carlo simulation to examine the likelihood of encountering AI violations when an FDRS is used in the context of layoffs. The primary research questions included an examination of how AI violations change depending on the definition of the employment action (i.e., retention vs. layoff), the length of the repeated layoffs, and whether or not laid off employees are replaced each year. The current study also examined the impact of the size of the organization, the percentage of the workforce laid off, and the type of AI calculation method used on the likelihood of AI violations. Results suggest that defining the employment action as layoffs (rather than as retentions) may result in a greater likelihood of AI violations, and AI violations are likely to peak in the 1st year of use. Further, replacing laid off employees may result in higher levels of AI over time as compared with not replacing layoffs. Additionally, the greatest risk for AI occurs when the organization size is large (i.e., N = 10,000) and when certain AI calculation methods are used. Results are discussed in terms of their practical and legal implications for organizations.

Fake it 'til you make it: Examining faking ability on social media pages

Abstract The current study investigated job applicant faking ability on Facebook, including an examination of various individual differences and strategies predictive of faking success. Using an experimental design, results indicated that individuals are able to manipulate Facebook profiles in order to convey a certain image. Individual difference predictors of faking ability included age, daily Facebook usage, cognitive ability, Facebook impression motivation, self-monitoring ability and sensitivity, and neuroticism. Individuals used slightly different modification strategies across conditions, and interestingly, the most effective strategy, removing statuses, was a significant predictor of faking ability in only the “fake good” condition, which is consistent with research on negative salience effects. Profile suitability ratings provided by three independent raters demonstrated high inter-rater reliability, but low inter-rater agreement. Of the examined Facebook profile components, wall posts and likes emerged as significant predictors of overall suitability ratings. Thus, these findings highlight potential concerns regarding the use of social networking sites as applicant evaluation tools in organizational contexts. Future research directions are suggested.

Detecting Between-Groups Heteroscedasticity in Moderated Multiple Regression With a Continuous Predictor and a Categorical Moderator

Moderated multiple regression (MMR) is frequently used to test moderation hypotheses in the behavioral and social sciences. In MMR with a categorical moderator, between-groups heteroscedasticity is not uncommon and can inflate Type I error rates or reduce statistical power. Compared with research on remedial procedures that can mitigate the effects of this violated assumption, less research attention has focused on statistical procedures that can be used to detect between-groups heteroscedasticity. In the current article, we briefly review such procedures. Then, using Monte Carlo methods, we compare the performance of various procedures that can be used to detect between-groups heteroscedasticity in MMR with a categorical moderator, including a heuristic method and a variant of a procedure suggested by O’Brien. Of the various procedures, the heuristic method had the greatest statistical power at the expense of inflated Type I error rates. Otherwise, assuming that the normality assumption has not been violated, Bartlett’s test generally had the greatest statistical power when direct pairing occurs (i.e., when the group with the largest sample size has the largest error variance). In contrast, O’Brien’s procedure tended to have the greatest power when there was indirect pairing (i.e., when the group with the largest sample size has the smallest error variance). We conclude with recommendations for researchers and practitioners in the behavioral and social sciences.