Investigating adolescent morphed emotional face processing: the influence of gender differences and alexithymia
Bibliographic record
Abstract
Facial expression recognition is essential for effective social interactions and develops across the lifespan. Adolescence represents a particularly important period for forming and maintaining social relationships, therefore, their ability to accurately interpret ambiguous emotional expressions is crucial. During this stage, however, factors such as gender differences and alexithymia, characterised by difficulties in identifying and processing emotions, may impact this capacity. This study examines morphed emotional face processing in adolescents while considering gender and alexithymia symptoms. Twenty-four adolescents (ages 14–18, n = 24) completed an emotion discrimination task and the Toronto Alexithymia Scale-20. Stimuli included happy, neutral, sad, and morphed faces, blending two emotions at varying intensities. Results showed that adolescents can categorise sad-happy morphed faces based on the dominant emotional intensity. However, females demonstrated difficulty classifying sad-happy morphed faces with higher happiness intensity under a single emotion. Additionally, overall alexithymia symptoms and difficulty in identifying feelings were negatively correlated with accuracy in rating of emotional intensity in sad-happy faces, though individuals with lower alexithymia levels misidentified more happy faces to be sad compared to those with higher alexithymia levels. Findings provide valuable insights into adolescents’ social behavior and emotional well-being, potentially contributing to both social research and clinical studies exploring psychiatric disorders in relation to emotional face processing, gender, and alexithymia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".