Psychometric applications of generative artificial intelligence: Lifecycle, risks, and research agenda

ABSTRACT Introduction Anxiety is central to the psychotherapy process, yet psychotherapists routinely infer a client's anxiety intensity from observable behaviour rather than from formal measurement, with no widely accepted framework to organise which observable markers indicate which levels of anxiety. This exploratory study examined how therapists make such classifications. Method Ninety‐one mental health professionals were randomly assigned to classify 41 text‐described behavioural and physiological markers using either a 5‐level or a simplified 3‐level category system, both derived from an integrated model of state anxiety in psychotherapy. Results Response distributions departed significantly from uniformity for nearly all markers in both formats, and the rank ordering of markers by intensity was highly consistent across formats, suggesting that therapists may share broad intuitions about relative marker intensity. Which markers elicited agreement, however, was far less reproducible, depending substantially on the response format. Convergence also depended on where the agreement criterion was set, declining from 90.2% to 51.2% of markers in the 3‐level format and from 63.4% to 22.0% in the 5‐level format as the criterion rose from > 0.50 to > 0.70. The 3‐level format yielded more classifiable markers at every criterion, although this advantage was not consistent across indices, whereas the 5‐level format elicited fewer ‘Insufficient to Determine’ responses. Markers placed at the highest intensity levels were classified most consistently. Discussion These findings offer preliminary groundwork for research on marker operationalisation, contextualised rating tasks and the development of training materials for psychotherapy process research.

Transitioning out of professional sport can present challenges for athletes and their wider environments, frequently necessitating coordinated physical, psychological, and economic support. Although these concerns have been documented in elite cycling, the extent to which structured transition programmes exist within the sport remains insufficiently understood, particularly in Europe, the historical centre of professional cycling. We conducted a cross-sectional qualitative documentary analysis, distributing a standardised inquiry to all European Cycling Federations (ECFs; N = 51) between December 2024-March 2025. Federations were asked whether they had formal strategies, policies, or resources related to athlete retirement. Responses were categorised as “ECF-level literature or initiative”, “No ECF-level provision”, or “No response” and relevant materials were descriptively synthesised. Amongst the 21 federations that responded, the majority (n = 17; ≈81%) reported no ECF-level retirement initiatives. Common reasons included limited resources, low perceived demand, or reliance on national or international bodies (i.e., Olympic Committees or sport-specific unions). Four ECFs (~19%) described transition-related structures, though these varied considerably in scope, definition, and delivery. Despite well-documented needs, structured retirement support for professional cyclists remains uncommon across European national federations, and existing programmes appear heterogeneously applied. As cycling expands globally, effective transition planning becomes increasingly important for athlete wellbeing and the long-term sustainability of the sport. Holistic, international collaborations led by cycling’s major governance bodies could strengthen career-long support systems, reinforce the public image of cycling as a health-promoting discipline, and create responsible, athlete-centered ecosystems.

Background: Patients with chronic kidney disease undergoing hemodialysis frequently experience physical and psychological complaints that may affect their sleep quality. Uremic pruritus, restless legs syndrome, anxiety, and post-hemodialysis fatigue are potential factors that may disrupt sleep quality. Objective: This study aimed to identify the factors influencing the sleep quality of patients with chronic kidney disease undergoing hemodialysis at Bahteramas Regional General Hospital, Southeast Sulawesi Province. Methods: This study employed a quantitative analytical approach with a cross-sectional design. The sample consisted of 83 respondents. Data were collected using the Pittsburgh Sleep Quality Index (PSQI), 5-D Itch Scale, International Restless Legs Syndrome Rating Scale (IRLS), Hospital Anxiety and Depression Scale-Anxiety (HADS-A), and a post-hemodialysis fatigue assessment instrument. Data were analyzed using the Chi-square test and binary logistic regression. Results: Bivariate analysis showed that uremic pruritus (p = 0.046), restless legs syndrome (p = 0.015), anxiety (p = 0.029), and post-hemodialysis fatigue (p = 0.049) were statistically significant factors associated with sleep quality. Simultaneously, the four variables had a statistically significant effect on sleep quality (p = 0.007), with a Nagelkerke R Square value of 0.217. In the multivariable analysis, only anxiety showed a statistically significant independent effect (p = 0.019). Conclusion: Uremic pruritus, restless legs syndrome, anxiety, and post-hemodialysis fatigue were statistically associated with sleep quality in the bivariate analysis. The four variables were jointly significant in the multivariable model, whereas only anxiety remained statistically significant after adjustment for the other variables.

Background: Prolonged screen exposure, after-hours connectivity, and sedentary work are linked to poor sleep and occupational burnout among Indian working professionals. Ayurvedic Dinacharya regulates waking, Vyayama, Bhojana Vidhi, and Nidra Vidhi; however, digital-era disruption of these domains among working adults remains unstudied. This study aimed to assess digital lifestyle behaviours mapped to Dinacharya principles as behavioural markers of Pragyaparadha, in relation to sleep quality and occupational burnout among working adults, and to identify behaviours independently associated with poor sleep and higher burnout. Methods: A cross-sectional analytical survey (STROBE-reported) was conducted at the All-India Institute of Ayurveda (AIIA), New Delhi, during (January 2026 to July 2026), among 400 working adults aged 25-40 years with ≥1 year of occupational experience. A structured proforma captured sociodemographic details and Dinacharya-mapped digital behaviours across five domains (morning routine, bedtime device use, after-hours connectivity, screen breaks/sedentary time, mealtime practices). Sleep quality and burnout were assessed using the PSQI and Copenhagen burnout inventory. Results: Of 400 participants, 56.8% had poor sleep quality, 61% personal burnout, and 55.8% work-related burnout. Bedtime device use and inadequate screen breaks/sedentary behaviour independently predicted poor sleep (aOR 1.76 and 1.98). After-hours connectivity, sedentary behaviour, and mealtime digital engagement predicted personal burnout; bedtime device use, sedentary behaviour, mealtime digital engagement, and digital overload predicted work-related burnout (all p<0.05). Conclusions: Digital lifestyle behaviours reflect patterns of Pragyaparadha in daily digital conduct. Interpreted through Dinacharya and Nidra, the findings support a culturally grounded, preventive Digital Dinacharya framework for digital-era occupational health.