Code for: "Psychometric validation of a parent-reported measure of childhood alexithymia: the Alexithymia Questionnaire for Children – Parent (AQC-P)" Analysis Input

Code for: Brown, R. H., Murray, A., Stewart, M. E., & Auyeung, B. (2022). Psychometric Validation of a Parent-Reported Measure of Childhood Alexithymia: The Alexithymia Questionnaire for Children–Parent (AQC-P). European Journal of Psychological Assessment, 38(1), 24-31. https://doi.org/10.1027/1015-5759/a000640 R code and SPSS syntax for all analyses conducted. Alexithymia can be defined as difficulties in describing one’s emotions and is of interest within clinical and developmental psychology as a potential mediating and exacerbating factor across multiple forms of psychopathology. Measuring alexithymia via self-reports can be challenging, as those with heightened alexithymia may have difficulties in recognizing their alexithymia traits due to impaired metacognitive skills. Thus, there would be considerable benefits to the availability of a psychometrically validated parent-reported alexithymia measure that may circumvent the issue of self-reports. We, therefore, examined the psychometric properties of a new parent-reported alexithymia measure, the Alexithymia Questionnaire for Children – Parent (AQC-P) in a community sample of 257 child-parent dyads. Furthermore, we examined the level of agreement between the parent-rated AQC-P and its self-rated counterpart, the Alexithymia Questionnaire for Children (AQC). Confirmatory factor analysis found that an oblique three-factor structure provided the best model for both AQC-P and AQC, with this structure showing measurement invariance across child gender. All subscales had omega internal consistency values > .70, supporting their reliability. Cross-informant consistency was supported by significant correlations between AQC and AQC-P scores. Results support the use of the AQC-P as a measure of parent-reported alexithymia in children. This study received no grants or other financial support. Bonnie Auyeung was supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 813546, the Baily Thomas Charitable Fund TRUST/VC/AC/SG/469207686, the Data Driven Innovation Programme, and the UK Economic and Social Research Council (ES/N018877/1) during the course of this work. unknown unknown