AN EXAMINATION OF ARTIFICIAL INTELLIGENCE USAGE PATTERNS AMONG YOUNG ADULTS IN THE CONTEXT OF LONELINESS LEVELS

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Kayım F., Demirkol Baysal S.

20th Annual International Conference on Psychology, Athens, Yunanistan, 25 - 29 Mayıs 2026, ss.37-38, (Özet Bildiri)

  • Yayın Türü: Bildiri / Özet Bildiri
  • Basıldığı Şehir: Athens
  • Basıldığı Ülke: Yunanistan
  • Sayfa Sayıları: ss.37-38
  • İstanbul Kültür Üniversitesi Adresli: Evet

Özet

The aim of this study is to examine the usage patterns of artificial intelligence tools among young adults aged 18-24 in relation to their level of loneliness, and to qualitatively analyze the reasons of participants who use artificial intelligence for psychological support purposes.

The sample of the study consisted of 141 participants aged 18-24, 99 (70.2%) of whom were female and 42 (29.8%) male, who did not have a psychiatric diagnosis, were not using psychiatric medication, and were actively using artificial intelligence tools. It was determined that the participants were predominantly undergraduate students (78.7%), living with their families (77.3%), single (71.6%), and had not previously received psychotherapy (82.3%). Purposes of AI use were assessed using 1-5 Likert-type items rated from 1 to 5, with higher scores indicating more frequent use. AI was most frequently used for educational purposes (3.50), followed by personal curiosity (3.23), understanding personal problems (2.44), decision-making (2.42), medical assistance (2.23), increasing motivation (1.88), reducing anxiety (1.85), psychological support (1.77) and reducing feelings of loneliness (1.50). Differences in loneliness scores across AI usage groups were examined using analysis of variance (ANOVA). Significant group differences were observed for several usage purposes. For AI use aimed at reducing anxiety, frequent users exhibited higher loneliness scores than occasional users (p = .019) and non-users (p = .007). In a similar pattern, individuals who frequently used AI for decision-making reported higher loneliness scores than those who never used it (p = .004; p = .002). Significant differences were also found for AI use aimed at understanding personal problems (p = .015), with very frequent users reporting higher loneliness scores than non-users (p = .039). For AI use aimed reducing feelings of loneliness, frequent and very frequent users demonstrated elevated loneliness scores compared to non-users (p < .001; p = .014). Additional differences were found between occasional and frequent users (p = .007) and between low-frequency and frequent users (p = .028). In addition, participants who reported that AI was somewhat helpful for psychological support exhibited higher loneliness scores than those who reported not using AI for this purpose (p = .010; p = .005).

In addition to quantitative findings, open-ended responses regarding the reasons for choosing AI for psychological support among 29 participants (20.56%) were examined using thematic analysis. The responses were grouped into four main themes. 50% of the responses cited easey of access and speed, 29.16% cited economic reasons, 16.66% cited perceived benefit and convenience, and 12.5% ​​cited distrust toward mental health professionals and psychotherapy.

Furthermore, 49 participants (34.75%) stated that they found AI tools useful for psychological support; of these, 32 (22.69%) expressed their reasons for using them in an open-ended manner. The thematic analysis of these responses identified four main themes. Themes such as emotion regulation and immediate calming effects were mentioned in 40.62% of responses, increased motivation and action in 25%, gaining different perspectives and receiving suggestions in 21.87%, and ease of use and perceived functionality in 15.65%.