Evidence map›Paper›PMID 42260619›Full record

ArticleBMC psychology2026

Loneliness and AI chatbot dependence in young adults: the mediating role of perceived social support.

Özkan Uğuz, Satı Doğan, Dilay Güngör

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In one paragraph

Article in BMC psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Özkan Uğuz *Liver Transplantation Unit, Department of General Surgery, Republic of Türkiye Ministry of Health, University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Istanbul, 34480, Türkiye.ORCID http://orcid.org/0000-0002-9410-9511
Satı Doğan *Department of Mental Health and Psychiatric Nursing, Faculty of Nursing, Ege University, Izmir, 35100, Türkiye. sati.dogan@ege.edu.tr.ORCID http://orcid.org/0000-0002-9935-3265
Dilay GüngörLiver Transplantation Unit, Department of General Surgery, Republic of Türkiye Ministry of Health, University of Health Sciences, Başakşehir Çam and Sakura City Hospital, Istanbul, 34480, Türkiye.ORCID http://orcid.org/0000-0002-5988-570X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesRapid advancements in artificial intelligence (AI) have facilitated the widespread integration of AI chatbots into everyday life, positioning them as alternative agents for social and emotional interaction. While such technologies may help regulate experiences of loneliness, stress, and social isolation, increasing reliance on AI-mediated interactions raises concerns regarding the emergence of maladaptive use patterns, including AI chatbot dependence. Despite growing attention to technology-related dependence, the underlying psychosocial mechanisms remain insufficiently examined. Accordingly, this study investigates the association between loneliness and AI chatbot dependence, with a particular focus on the mediating role of perceived social support among young adults.

methodsA quantitative research design was employed using a relational survey approach. Data were collected via an online questionnaire from 610 young adults (aged 18-30) residing in Türkiye. Measures included the UCLA Loneliness Scale-6, the AI Chatbot Dependence Scale, and the Perceived Social Support Scale. Data were analyzed using descriptive statistics, correlation analysis, and structural equation modeling (SEM) conducted in AMOS 24.0. The mediating effect was tested using a bootstrapping procedure.

resultsLoneliness was positively associated with AI chatbot dependence, whereas it was negatively associated with perceived social support; perceived social support, in turn, was negatively associated with AI chatbot dependence. Mediation analyses indicated that loneliness significantly predicted AI chatbot dependence both directly and indirectly, with perceived social support partially mediating this relationship. The proposed model demonstrated an acceptable fit to the data.

conclusionThese findings suggest that robust social support networks may function as a protective factor against emerging forms of AI chatbot dependence and highlight the importance of psychosocial interventions. Accordingly, coordinated efforts across universities, public institutions, local authorities, and mental health professionals are needed to develop evidence-based and sustainable interventions aimed at strengthening social connectedness and enhancing coping mechanisms for loneliness among young adults.

Indexed as

Artificial IntelligenceInternet Addiction DisorderLonelinessSocial SupportAdolescentAdultFemaleHumansMaleSurveys and QuestionnairesYoung AdultAI chatbot dependenceArtificial intelligenceLonelinessPerceived social supportYoung adults

Identifiers

PMID42260619
PMCPMC13471535

What Socratic holds

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Registered trials

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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 Socratic graph.