The Emotion Awareness Questionnaire (Eaq30): A Call for Revision
Bibliographic record
Abstract
IntroductionThe Emotion Awareness Questionnaire (EAQ30; Rieffe, Oosterveld, Miers, Meerum Terwogt, & Ly, 2008) is a self-report instrument measuring emotion awareness (EA) as a multi-dimensional construct in children and adolescents aged between 9 and 16 years old. The dimensions of EA are drawn from the theory surrounding alexithymia, expanded to contain more than difficulties in identifying and describing emotions and preference for analyzing external rather than internal information (Rieffe et al., 2007). Consequently, EA, the opposite of alexithymia, is defined as an attention and attitudinal process comprising the monitoring and differentiation of emotions, of their causes, and of their physiological correspondents as well as the evaluation of emotions as positive or negative, private or interpersonal (Rieffe et al., 2007, 2008).Nevertheless, the six dimensions of the EAQ30 originate (Rieffe et al., 2007) rather from an already existing measure of alexithymia (Toronto Alexithymia Scale - child form; Rieffe, Oosterveld, & Terwogt, 2006) than on the proposed conceptualization of EA. Specifically, the Differentiating Emotions subscale (7 items; e.g., often don't know why I am angry), measuring the ability to differentiate emotions and understand their causes, was based on the emotion identification dimension of alexithymia. The Bodily Awareness subscale (5 items; e.g., When I am sad my body feels weak), measuring the identification of emotions related to physiological phenomena, was added to compensate for the non-inclusion of somatic complaint items from the identification dimension of the Toronto Alexithymia Scale. The score on this subscale is reversed, even though low awareness of emotion-related bodily sensations is specific to alexithymia (Haviland & Reise, 1996), and thus could not adequately represent its opposing construct. Next, the Verbal Sharing subscale (3 items; e.g., can easily explain to a friend how I feel inside) referring to disclosure of one's own emotions to others directly originated from the expression of emotions' dimension of alexithymia. The Not Hiding subscale (5 items; e.g., When I am upset, I try not to show it) was added to distinguish between an unwillingness to hide and unwillingness to share emotions. Finally, the Analyses of Emotions subscale (5 items; e.g., It is important to understand how I am feeling), measuring the tendency to analyze internal emotional information, was developed in opposition to the preference for analyzing the external information dimension of alexithymia. Additionally, the Attending to Others subscale (5 items; e.g., It is important to know how my friends are feeling) was added to assess the willingness to analyze other peoples' emotions.As a result of the low focus on the proposed definition of EA, the aspect referring to the evaluation of emotions as positive or negative (Rieffe et al., 2007, 2008) was left unmeasured. Additionally, the reliability, validity and factor structure problems indicated in all previous validation studies (Camodeca & Rieffe, 2013; Lahaye et al., 2011; Lahaye, Luminet, Van Broeck, Bodart, & Mikolajczak, 2010; Rieffe et al., 2008) raise doubts regarding the contribution of each dimension to the construct of EA. Therefore, further analysis of the psychometric properties of EAQ30 may help to gain a better understanding of the construct.Review of psychometric problems based on previous validation studiesThe psychometric properties of the EAQ30 were analyzed in Dutch (Rieffe et al., 2008), Spanish (Rieffe, Villanueva, Adrian, & Gorriz, 2009), Belgian (Lahaye et al., 2010) and Italian (Camodeca & Rieffe, 2013) samples. All these studies concluded that EAQ30 is a valid instrument despite some obvious issues with the reliability, stability, structure and validity of the construct.Namely, the EAQ30 subscales showed low internal consistencies, Cronbach's a ranging from . …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.014 |
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 source (direct Gemma or distilled Codex), 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".