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TRUVACE RECORD VERSION
record: TRV-2026-2530
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T07:49:08.821351Z
status: published
lens: p_space
sector: education
headline: From boredom to problematic AI chatbot use: a three-wave half-longitudinal mediation study of loneliness and dual-system self-control
dek: Background: Problematic use of AI chatbots (PUAIC) is an emerging concern. Drawing on the I-PACE model and the dual-system model of self-control, this study examined the mediating roles of loneliness, the control system, and the impulsive system. Methods: A three-wave half-longitudinal mediation design was used with 551 Chinese college students at baseline. Boredom proneness was assessed at Time 1, loneliness and the control and impulsive systems at Time 2, and PUAIC at Time 3. Missing data were handled using 20…
gain_title: (none)
problem_title: In a three-wave study of 551 Chinese college students, higher boredom proneness was associated with more problematic AI chatbot use two months later, directly (β = .25) and through loneliness and impulsive tendencies.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: In a three-wave study of 551 Chinese college students, higher boredom proneness was associated with more problematic AI chatbot use two months later, directly (β = .25) and through loneliness and impulsive tendencies.
problem_evidence: boredom proneness was associated with loneliness (β = .57), the impulsive system (β = .31), the control system (β = -.38), and PUAIC directly (β = .25; all p < .001)
quick_read: A study of 551 students at two Chinese universities found that those who scored higher on boredom proneness in October 2024 reported more problematic AI chatbot use in December 2024. The direct association was β = .25, and boredom proneness was also tied to loneliness (β = .57) and stronger impulsive tendencies (β = .31).

Loneliness and the impulsive system each carried part of the link. Indirect effects were .073 through loneliness, .077 through impulsivity and .038 through loneliness followed by impulsivity. The total effect was .401, and the models explained 23% of the variance in problematic use.

The results are associations, not proof of cause. Baseline levels of loneliness, self-control and problematic use were not measured, so earlier problematic use may have contributed, and a reverse-order model also produced a significant pathway between impulsivity and loneliness. The authors say prevention ideas, such as work on loneliness and boredom coping, need experimental testing.
limitation: Boredom proneness, mediators and problematic use were each measured at only one wave, with no baseline controls, so causal and change-over-time conclusions are ruled out; the sample was convenience-based, from two Chinese universities, and relied on self-report.
tag: Evidence-backed problem
key_points: Researchers recruited 551 students from two Chinese universities; 533 took part in wave 2 and 521 gave valid wave 3 responses, with complete data for 503. | Boredom proneness was measured in October 2024, loneliness and self-control in November, and problematic AI chatbot use in December, with about 30 days between waves. | Boredom proneness was linked to loneliness (β = .57), stronger impulsivity (β = .31), weaker control (β = -.38) and problematic chatbot use (β = .25). | The total indirect effect was .156; the control-system pathways were not significant. | A complete-case analysis of 503 students gave the same conclusions, with a direct effect of β = .243. | Most students mainly used Doubao (68.2%) or DeepSeek (21.9%), and averaged 2.98 hours a week with chatbots. | Problematic use was measured with an 11-item scale adapted from a ChatGPT-use scale, and the authors say frequent use alone is not treated as problematic.
rundown: The study used a half-longitudinal design across the fall 2024 semester. Participants were recruited by convenience sampling at two Chinese universities; 57.5% were female and the mean age was 19.02. Missing data were handled with 20 imputed datasets and PROCESS Model 81, with sex and grade level as covariates.

Within the model, loneliness was associated with the impulsive system (β = .27) and with problematic use (β = .13), and the impulsive system with problematic use (β = .24). The control system was not significantly associated with problematic use (β = .08, p = .072), and its indirect effects were not significant.

The authors suggest universities pair mental health education and digital literacy with peer activities and counselling, and that AI providers add usage reminders and referrals to psychological support. They describe these as tentative targets for future experimental evaluation, since no intervention was tested.
sources:
- peer_reviewed | Australian Journal of Psychology | https://doi.org/10.1080/00049530.2026.2737094 | 2026-09-27
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