BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//SWDTP - ECPv6.15.16.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:SWDTP
X-ORIGINAL-URL:https://www.swdtp.ac.uk
X-WR-CALDESC:Events for SWDTP
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20261025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20270328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20271031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260303T000000
DTEND;TZID=Europe/London:20260306T235959
DTSTAMP:20260416T043450
CREATED:20260217T095411Z
LAST-MODIFIED:20260217T095411Z
UID:10000580-1772496000-1772841599@www.swdtp.ac.uk
SUMMARY:Digital Research Skills for Social Scientists
DESCRIPTION:Date: 3rd – 6th March 2026 (four consecutive mornings) \nLocation: online \nThe National Centre for Research Methods are offering the opportunity to attend this introductory short course for the reduced price of £25 for all participants. Improve the efficiency and reliability of your research. Learn foundational computational skills including automating tasks using the command line on your computer\, tracking changes to your work using version control and building simple programs using the programming language python. These skills are the foundation of many powerful data analysis techniques including using Artificial Intelligence or High Performance Computing. \nPlaces are limited so don’t delay. Book your place here: https://www.ncrm.ac.uk/training/show.php?article=14333 [ncrm.ac.uk]
URL:https://www.swdtp.ac.uk/event-calendar/digital-research-skills-for-social-scientists/
CATEGORIES:Higher Level Training,Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260303T130000
DTEND;TZID=Europe/London:20260303T140000
DTSTAMP:20260416T043450
CREATED:20251205T142720Z
LAST-MODIFIED:20260113T142353Z
UID:10000564-1772542800-1772546400@www.swdtp.ac.uk
SUMMARY:Validating constructs through quantitative sampling
DESCRIPTION:Using multi-dimensional experience sampling via smartphones to map thought-emotion interactions in daily life\nAnqi Lei\, PhD researcher at the University of Plymouth \nPatterns 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. \n  \nMeasuring sensitive constructs in conservative contexts\nSara Yadollahi\, PhD researcher at the University of Bath \nAs 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). \nData 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). \nIn 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. \nThis session is part of the SWDTP Data Analysis Webinar Series. Visit the following link for further information and registration: https://www.tickettailor.com/events/swdtp/1956811
URL:https://www.swdtp.ac.uk/event-calendar/validating-constructs-through-quantitative-sampling/
CATEGORIES:Higher Level Training,Training,Webinar/Seminar/Symposium
END:VEVENT
END:VCALENDAR