Held online, 1-2pm, Tue 03/03/26, 1-2pm
Anqi has chosen not to share the recording of her presentation, however her slides are still available below. She is happy to answer questions by email .
Using multi-dimensional experience sampling via smartphones to map thought-emotion interactions in daily life
Anqi Lei, PhD researcher at the University of Plymouth
Patterns of on-going thought have crucial implications for emotional health. In the present study, we used multi-dimensional experience sampling (MDES) via smartphones to examine how daily-life thought patterns relate to concurrent affective states (valence, arousal, stress) as well as how alexithymia traits (reflecting atypical emotional awareness) modulate these thought patterns across a range of affective and social situations. Principal Component Analysis of the MDES data identified four latent thought dimensions: future-self orientation, intrusive distraction, sensory engagement, and task-focus. Linear Mixed Models revealed different associations between thought dimensions and affective states, which may reflect distinct adaptive and maladaptive cognitive processes, particularly in relation to alexithymia. High overall alexithymia predicted fewer future-self-oriented thoughts as well as more different sensory engagement across affective and social contexts. Regarding specific facets of alexithymia, difficulty identifying feelings selectively reduced future-self orientation during intense sadness, and externally oriented thinking rendered thought patterns less sensitive to affective contexts. By mapping affective experiences onto thought dimensions in daily life, these findings uncover cognitive pathways that support emotional well-being, providing a scalable framework for understanding variability in human affective experience.
Measuring sensitive constructs in conservative contexts
Sara Yadollahi, PhD researcher at the University of Bath
As a psychometrician, I was responsible for data gathering and analysis in the project: “Development and Validation of an Iranian Scale for Problematic Online Pornography Use,” which used a descriptive-correlational design and online non-random snowball sampling. A total of 1,921 adults (813 women, 1,108 men) completed the scales: the Iranian Scale for Problematic Online Pornography Use (developed by the research team following multiple steps, including a thorough literature review) and Difficulties in Emotion Regulation Scale (DERS).
Data were analysed using AMOS and SPSS. Confirmatory factor analysis supported a seven-factor model—Salience, Mood Modification, Tolerance and Escalation, Withdrawal, Relapse, Conflict and Problems, and Guilt (RMSEA=0.07, CFI=0.91, df=228). Construct validity was confirmed through intercorrelations among subscales and the total score; discriminant validity by the Fornell-Larcker criterion; convergent validity by Average Variance Extracted (AVE); and criterion validity by correlations with pornography use frequency (r=0.56), duration per session (r=0.35), and frequency of masturbation with (r=0.56) and without pornography (r=0.25). Reliability was strong (CR=0.98, α=0.93). In this webinar, I will focus on the data analysis process, including designing the scale with the research team, conducting the pilot study, being creative in measuring sensitive constructs in conservative contexts, working with a large dataset, and ensuring participant anonymity during data collection and analysis.