Evidence map›Paper›PMID 42903122›Full record

ArticleFrontiers in psychology2026

Multimodal data processing for affective perception in AI-supported developmental bibliotherapy: a mixed-methods feasibility study in university libraries.

Chenyang Zhou, Wei Kang

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Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Chenyang ZhouJiangsu Second Normal University, Nanjing, China.
Wei KangJiangsu Second Normal University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Multimodal data processing is increasingly important for understanding human affective experience in naturalistic settings. In this study, "multimodal" refers to the integration of heterogeneous human-centered evidence streams rather than synchronized perceptual or physiological sensing. We evaluated a low-threshold university-library support model integrating developmental bibliotherapy salons with AI chatbot-supported emotional expression. Methods: A convergent mixed-methods feasibility and acceptability design was conducted at a Chinese university. Of 180 baseline respondents, 45 voluntarily registered for a three-week intervention and 38 completed all sessions and post-intervention assessments; 68 non-participating students with complete baseline and follow-up assessments served as a descriptive comparison group. Evidence sources included psychological self-report data, participation records, AI-use feedback, participant evaluations, and semi-structured interviews with nine intervention participants. Quantitative indicators assessed recruitment, retention, acceptability, and exploratory SCL-90 change, while thematic analysis examined participants' affective experiences and perceived mechanisms. Results: All available intervention places were filled within two days, retention reached 84.4%, and 94.7% of completers reported moderate or considerable benefit. The intervention-group mean SCL-90 change was -0.12 points, with an approximate 95% confidence interval of [-0.23, -0.01]. Because allocation was voluntary and non-randomized, no causal group-by-time intervention effect is claimed. Qualitative findings suggested that bibliotherapy salons supported interpersonal resonance, cognitive reframing, and shared reflection, whereas the AI chatbot provided a private and non-judgmental channel for emotional disclosure. Discussion: AI-supported developmental bibliotherapy appears feasible and acceptable as a low-threshold university-library wellbeing service. The findings support feasibility, acceptability, and perceived mechanisms only; they do not establish treatment efficacy, clinical effectiveness, or a neuroscience mechanism. More broadly, the study illustrates how heterogeneous psychological, behavioral, and experiential evidence can be integrated in a naturalistic educational setting.

Indexed as

affective perceptiondevelopmental bibliotherapyhuman-centered AImultimodal data processingstudent wellbeing

Identifiers

PMID42903122
PMCPMC13680240

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.