Manfred Schmitt

BlenderFace is a highly precise marker‐based approach for measuring facial activity. Unlike most camera‐based automated facial expression recognition (AFER) systems, which rely on fixed natural landmarks, blenderFace flexibly tracks virtually any point of interest using painted markers. However, visible markers, like EMG electrodes, may alter appearance, increase self‐awareness, and affect spontaneous responding in face‐to‐face interactions. To address these limitations, we introduce blenderFaceUV, which uses sunscreen‐based markers that are visible only under ultraviolet (UV) light (365 nm). In Study 1, we assessed UV‐marker tracking accuracy using parallel visible‐light and UV recordings from two participants. In Study 2, we examined the scalability of blenderFaceUV in N = 18 lay participants prompted to produce a broad range of facial movements using common emotion terms. We also compared identical facial movements measured with blenderFaceUV and OpenFace, a widely used AFER system based on a point distribution model (PDM). Study 1 showed that UV markers could be tracked with similarly high accuracy as visible markers (reprojection/solve error < 0.3 pixels). Across 10 markers and two participants, with more than 3800 measurement occasions per participant, the mean correlation between visible and UV marker movements across the x‐ and y‐coordinates was r = 0.957, while centered RMSE values indicated average deviations of approximately 1 mm. Study 2 demonstrated the scalability of the method and revealed PDM‐related artifacts in OpenFace measurements, particularly during eye blinks and large mouth movements. PDM‐interpolated landmarks, such as upper‐lip markers, also deviated substantially from marker‐based blenderFaceUV measurements. Practical challenges remain, including the complexity of applying invisible markers and the relatively high cost of UV cameras (≈$2000–$6000). We discuss technical requirements, limitations, and a recommended workflow for implementing blenderFaceUV.

The use of journal impact factors and other metric indicators of research productivity, such as the h-index, has been heavily criticized for being invalid for the assessment of individual researchers and for fueling a detrimental "publish or perish" culture. Multiple initiatives call for developing alternatives to existing metrics that better reflect quality (instead of quantity) in research assessment. This report, written by a task force established by the German Psychological Society, proposes how responsible research assessment could be done in the field of psychology. We present four principles of responsible research assessment in hiring and promotion and suggest a two-phase assessment procedure that combines the objectivity and efficiency of indicators with a qualitative, discursive assessment of shortlisted candidates. The main aspects of our proposal are (a) to broaden the range of relevant research contributions to include published data sets and research software, along with research papers, and (b) to place greater emphasis on quality and methodological rigor in research evaluation.

With three studies, we scrutinized the domain specificity of indirect measures in predicting behavior. We compared indirect and direct measures of disgust (Study 1, N = 121), speech anxiety (Study 2, N = 111), and evaluation of a minority group (Study 3, N = 97). In each study, data was collected at three measurement occasions (t1, t2, t3). At t1, direct measures of explicit disgust, anxiety, and attitude (liking vs. disliking) were taken. Direct measures were each implemented by a questionnaire and a picture rating. At t2, indirect counterparts using variants of the implicit association task (IAT) were employed. Automatic and controlled behavior was recorded at t3. In Study 1 (disgust), both indirect and direct measures of disgust significantly predicted behavioral indices of approaching a cockroaches, but the effect of the direct measure was larger. By contrast, both measures did not significantly predict coded facial and bodily reactions while approaching cockroaches. In Study 2 (anxiety), the indirect measure of speech anxiety significantly predicted nervous facial and bodily reactions during a speech, while the direct measure significantly predicted the choice of audience size. In Study 3 (liking vs. disliking of a minority group), the indirect measure of attitudes toward minority group members significantly predicted facial and bodily approach reactions toward a visibly minoritized confederate compared to a visibly non-minoritized confederate, whereas a picture rating as the direct measure did not significantly predict rated sympathy and potential collaboration with the comparison of the confederates. However, the questionnaire as direct measure did significantly predict the sympathy and potential collaboration rating comparison of the confederates. In addition, we tested for moderating effects of acute and chronic cognitive control resources (dispositional self-control, working memory capacity) assessed at t1, and experimentally manipulated at t3. No consistent moderation effects emerged (analyses are reported in the supplement). The findings of our studies support the specificity of the evaluations and the discriminant validity of the direct and indirect measures, and supplement previous research on indirect measures, which has either focused on single constructs and ignored mismatching evaluations, or used self-reports as behavior proxies.