Search

Current two-step measures of gender identity do not prescribe methods for using expanded responses (e.g., multiple selections) among sexual and gender minority (SGM) people, though they want the opportunity to provide these responses. To increase statistical power using expanded gender identity responses, we created an automated algorithm to generate analyzable categories. Participants’ expanded gender identity responses and sex assigned at birth were used to create five categories (i.e., cisgender men, cisgender women, gender expansive individuals, transgender men, and transgender women) from a cohort of SGM people (N = 6,312, 53% cisgender individuals). Data was collected from June 2020 to June 2021. Chi-square tests were performed to assess the association between the algorithm-generated and participant-selected gender categories, and to identify demographic differences between participants in the algorithm-generated categories. Forty-six percent of our sample may have been classified into an “other” category without an algorithm due to writing their own response (5.7%), selecting “another gender identity” (5.7%), or selecting multiple (42.6%) or less commonly described (10.2%) gender identities. There was a relationship between the categories formed by our algorithm and participants’ single category selection (χ2 [20] = 19,000, p < .001). Concordance rates were high (97-99%) among all groups except for participants classified as gender expansive (74.3%). Without an algorithm to incorporate expanded gender identity responses, almost half of the sample may have been classified into an “other” category or dropped from analyses. Our algorithm successfully classified participants into analyzable categories from expanded gender responses.

Person reliability parameters (PRPs) model temporary changes in individuals' attribute level perceptions when responding to self-report items (higher levels of PRPs represent less fluctuation). PRPs could be useful in measuring careless responding and traitedness. However, it is unclear how well current procedures for estimating PRPs can recover parameter estimates. This study assesses these procedures in terms of mean error (ME), average absolute difference (AAD), and reliability using simulated data with known values. Several prior distributions for PRPs were compared across a number of conditions. Overall, our results revealed little differences between using the ? or lognormal distributions as priors for estimated PRPs. Both distributions produced estimates with reasonable levels of ME; however, the AAD of the estimates was high. AAD did improve slightly as the number of items increased, suggesting that increasing the number of items would ameliorate this problem. Similarly, a larger number of items were necessary to produce reasonable levels of reliability. Based on our results, several conclusions are drawn and implications for future research are discussed.

We explored how students view the teaching evaluation process and assessed their self-reported behaviors when completing student evaluations of teaching (SETs). We administered a 28-item survey assessing these views to students from a cross section of majors across 20 institutions (N = 597). Responses to this measure were analyzed using exploratory factor analysis. Students also answered an open-ended question about their views; responses were coded into 21 categories. We found that students generally held positive views about the evaluation process and that, overall, these positive views were consistent across type of institution, academic discipline, class standing, and respondent gender. However, compared with small and midsize institutions, community college students were more positive about the usefulness of SETs, and seniors reported greater willingness to provide specific feedback (such as by providing written comments) when completing SETs compared to sophomores and juniors. We conclude by providing suggestions for improving the evaluation process based on our findings.

Utilizing the Job Demands-Resources (JD-R) theory as a guiding framework, the current study examined the relationships between job demands (work role strain) and occupational outcomes (burnout and job satisfaction) and assessed how job resources (team member social support and leader social support) mitigated the impact of high job demands for U.S. Air Force remotely piloted aircraft (RPA) operators. A total of 905 active duty U.S. Air Force RPA operators participated in a web-based occupational health assessment. Study findings confirmed that work role strain proved to be strongly related to negative occupational outcomes – increased burnout and reduced job satisfaction. Compelling evidence emerged suggesting that boosting job resources (i.e., team member and leader social support) may be a promising point of intervention to mitigate negative occupational outcomes. By investigating ongoing job demands that result in a higher incidence of burnout and job dissatisfaction, as well as job resources that protect against burnout and job dissatisfaction, researchers and practitioners can continue to introduce supportive resources at crucial points to alleviate the adverse consequences of occupational stress and burnout. Applying the JD-R theory to these findings highlights the importance of job resources for RPA operators and other employees working in high-risk, high-demand career fields. Implications and future directions are discussed. [ABSTRACT FROM AUTHOR]

The US Air Force remote warrior community comprises several career fields including remotely piloted aircraft pilots and intelligence, cyber, and sensor operators. The crews are responsible for working seamlessly together to provide 24/7 real-time intelligence, surveillance, and reconnaissance and precision-strike weapons capabilities for a wide range of global combat operations. Due to the rapid increase in global demands and operational tempo, there is growing concern from military leadership about the impact of operational stress on the health and psychological wellbeing of remote warriors. Previous assessments from 2011 and 2015 have demonstrated a significant increase in the reported rates of operators experiencing suicide ideation. The current study examined two protective factors expected to reduce the risk of suicide ideation -- team member social support and leader social support. A total of 905 active duty remote warriors participated in occupational health assessments conducted in 2018. Risk factors for suicide ideation included being unmarried, worsening relationship problems, occupational burnout, and increased operational stress. Results indicated that team member and leader social support were significant protective factors for shift workers and those who reported being less likely to seek mental healthcare. Implications of the findings, intervention recommendations, and directions for future research are discussed. [ABSTRACT FROM AUTHOR]

Introduction: U.S. Air Force remotely piloted aircraft (RPA) operators perform a variety of around-the-clock global intelligence, surveillance, and reconnaissance (ISR) missions that are considered critical to operational effectiveness. The growing need for ISR operations has led to significant increases in operational tempo and workload, resulting in elevated operational stress, burnout, and psychological distress. These negative outcomes are linked to conditions such as long hours, low manning, lack of sleep, and communication issues. Through regular assessments and the implementation of additional resources (i.e., embedded health care providers), Air Force leadership is working to alleviate the stressors and maintain psychological well-being. Thus, the purpose of this study is to compare the levels of stress, and prevalence of burnout and psychological distress across RPA career fields within two major commands.Materials and Methods: Assessments were completed by 571 RPA operators from 2 major commands: Air Force Special Operations Command (n = 158) and Air Combat Command (n = 413). RPA career fields included pilots (n = 331), sensor operators (n = 137), and intelligence operators (n = 103).Results: Results revealed that high stress levels from an array of sources continue to result in increased risk of burnout and psychological distress for RPA operators. Several significant differences in sources of high stress across career fields and major commands are identified and discussed.Conclusions: Overall, the results of this study highlight specific problem areas unique to certain subsets of the RPA community in need of targeted intervention and clarify several avenues for future research. [ABSTRACT FROM AUTHOR]