Facial Appearance as Core Expression Scale: Benchmarks and Properties

Objective

Patients presenting for corrective facial surgery may have ideals that are not congruent with their surgeon's expectations for surgical outcomes. To identify and reduce disparities in expectations, the Facial Appearance as Core Expression Scale (FACES) was developed to assess the extent to which individuals identify their own faces as representing their ideal self.

Method

In Study 1, 504 healthy young adult participants answered online questions about their own faces. In Study 2, 165 participants rated their own faces, digitally manipulated images of four patients before and after surgery, and two digitally averaged benchmark images.

Results

In Study 1, the final FACES instrument had seven items and was highly reliable across genders and races. Study 2 replicated reliability findings. The before surgery and after surgery pictures yielded significant improvements in ratings, suggesting scale validity.

Conclusions

The FACES consists of 14 items including a benchmark image to detect unusual responding. Results indicate the measure is reliable and sensitive to perceptions of surgical changes to faces. While the scale needs to be validated in a clinical sample, the measure may help identify patients with atypical ideal expectations for their face and may be used to quantify surgical outcomes.

Applying the mixed-blessings model and labeling theory to stigma in inclusive education: An experimental study of student and trainee teachers’ perceptions of pupils with ADHD, DLD, and intellectual disability

Institutional and individual stigmatization represent major barriers that prevent children with disabilities from accessing education. It can be presumed that children with disabilities are labeled as such even in inclusive educational settings and that teachers’ attitudes toward inclusive education and children with disabilities play a crucial role in this context. Against this background, the present study aims to (a) apply and conceptualize the mixed-blessings model in the context of stigma-related reactions to children’s disability labels in inclusive education and (b) shed light on the causal attributions of teachers that underlie stigma-related attitudes toward children with various disabilities. A 3 × 2 × 2 × 2 × 2 online experiment examined the ways in which disability-specific causes and symptoms, the type of disability in question, the children’s sex, and efficacy cues regarding educational efforts affect future teachers’ attitudes toward and expectations of inclusive education as well as their social distance toward children with disabilities. The participants in this experiment were N = 605 German student and trainee teachers representing different types of teaching professions. A multivariate analysis of variance (MANOVA) revealed that, in particular, the cause attributed to the disability, the depicted type of disability and the probability of learning success led to changes in attitudes. Respondents’ teaching self-efficacy and their status as students or trainees emerged as moderators of the effect of pupils’ type of disability. As a result, teacher education and training as well as communication regarding pupils with disabilities require a high degree of sensitivity to disability-specific and efficacy-related cues to prevent (accidental) professional or institutional stigmatization.

The paired A-Not A design within signal detection theory: Description, differentiation, power analysis and application

Signal detection theory gives a framework for determining how well participants can discriminate between two types of stimuli. This article first examines similarities and differences of forced-choice and A-Not A designs (also known as the yes-no or one-interval). Then it focuses on the latter, in which participants have to classify stimuli, presented to them one at a time, as belonging to one of two possible response categories. The A-Not A task can be, on a first level, replicated or non-replicated, and the sub-design for each can be, on a second level, either a monadic, a mixed, or a paired design. These combinations are explained, and the present article then focuses on the both the non-replicated and replicated paired A-Not A task. Data structure, descriptive statistics, inference statistics, and effect sizes are explained in general and based on example data (Düvel et al., 2020). Documents for the data analysis are given in an extensive online supplement. Furthermore, the important question of statistical power and required sample size is addressed, and several means for the calculation are explained. The authors suggest a standardized procedure for planning, conducting, and evaluating a study employing an A-Not A design.

Breaking the myths of competition: a cross-sectional analysis of injuries among CrossFit trained participants

Objectives

The purpose of this study was to examine the injury rates of individuals engaged in CrossFit training and examine the risk of injury associated with competition.

Study design

Cross-sectional analysis.

Methods

Descriptive statistics, including injury incidence and rates, were examined for individuals reporting participation in a CrossFit sanctioned competition between 2013 and 2017. To examine the odds of being injured, we considered logistic regression models, where the primary independent measure was participation length—individual measures of interest included age, sex, body mass index, CrossFit affiliation and competition status.

Results

3049 individuals completed the survey (60% completion rate). All competitors, regardless of competition level, had similar incidence of injury (χ²=1.1, p=0.571). For those who reported competing, our calculated injury rate was 0.21–0.54 injuries per 1000 training hours, while for those not competing, the injury rate was calculated as 0.39–1.30 injuries per 1000 training hours. Logistic regression demonstrated short length of participation in CrossFit training as the main factor associated with the odds of being injured (OR=1.82; 95% CI: 1.15 to 2.92). Additionally, training at an official CrossFit affiliate appeared to have a protective effect from injury (OR=0.85; 95% CI: 0.65, 1.10).

Conclusion

Our findings provide evidence of the low risk of injury related to these events. Moreover, these findings support the notion that musculoskeletal injuries may be the result of poor progression plans, which may be minimised by participating in an official CrossFit affiliate.

Study Protocol on Ecological Momentary Assessment of Health-Related Quality of Life Using a Smartphone Application

Health-Related Quality of Life (HRQoL) is a construct of increasing importance in modern healthcare, and has typically been assessed using retrospective instruments. While such measures have been shown to have predictive utility for clinical outcomes, several cognitive biases associated with human recall and current mood state may undermine their validity and reliability. Retrospective tools can be further criticized for their lack of ecology, as individuals are usually assessed in less natural settings such as hospitals and health centers, and may be obliged to spend time and money traveling to receive assessment. Ecological momentary assessment (EMA) is an alternative, as mobile assessment using mobile health (mHealth) technology has the potential to minimize biases and overcome many of these limitations. Employing an EMA methodology, we will use a smartphone application to collect data on real-time HRQoL, with an adapted version of the widely used WHOQOL-BREF questionnaire. We aim to recruit a total of 450 healthy participants. Participants will be prompted by the application to report their real-time HRQoL over 2 weeks together with information on mood and current activities. At the end of 2 weeks, they will complete a retrospective assessment of their HRQoL and they will provide information about their sleep quality and perceived stress. The psychometric properties of real-time HRQoL will be assessed, including analysis of the factorial structure, reliability and validity of the measure, and compared with retrospective HRQoL responses for the same 2-week testing period. Further, we aim to identify factors associated with real-time HRQoL (e.g., mood, activities), the feasibility of the application, and within- and between-person variability in real-time HRQoL. We expect real-time HRQoL to have adequate validity and reliability, and positive responses on the feasibility of using a smartphone application for routine HRQoL assessment. The direct comparison of real-time and retrospective measures in this study will provide important novel insight into the efficacy of mHealth applications for HRQoL assessment. If shown to be valid, reliable and feasible for the collection of HRQoL data, mHealth applications may have future potential for facilitating clinical assessment, patient-physician communication, and monitoring individual HRQoL over course of treatment.

Why follow? The interplay of leader categorization, identification, and feeling respected

Guided by both social cognitive and identity-based perspectives of leadership, the present study investigated how and when the process of leader categorization results in greater leader effectiveness. Specifically, we propose that the relationship between leader categorization and subordinates’ openness toward leadership should be partially mediated by subordinates’ identification with their leaders. Furthermore, seeking to corroborate that the issue of self-esteem is the central ingredient in the identification process, we argue that the mediation should become weaker the more subordinates feel that they are being treated disrespectfully by their leaders, and thus are explicitly undermined in their efforts toward self-enhancement. The proposed mediating effect was tested and supported in two field studies ( N1 = 244, N2 = 645). In the second study, we also tested and found support for the proposed moderated mediation model. The theoretical and managerial consequences are discussed.