Evidence map›Paper›PMID 42343026›Full record

ArticleArchives of sexual behavior2026

From Friends to Lovers: Understanding Motivations and Barriers in AI Companionship.

Laura M Vowels, Valerie A Lapointe, Shannon K Sweeney, George Nash, Temian Schnell, Simon Dubé, Matthew J Vowels

Abstract read
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In one paragraph

Article in Archives of sexual behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Laura M VowelsSchool of Psychology, University of Roehampton, London, UK. laura.vowels@roehampton.ac.uk.ORCID http://orcid.org/0000-0001-5594-2095
Valerie A LapointeDepartment of Psychology, University of Quebec, Montreal, QC, Canada.
Shannon K SweeneyInstitute of Psychology, University of Lausanne, Lausanne, Switzerland.
George NashSchool of Psychology, University of Roehampton, London, UK.
Temian SchnellSchool of Psychology, University of Roehampton, London, UK.
Simon DubéKinsey Institute, Indiana University, Bloomington, IN, USA.
Matthew J VowelsThe Sense Innovation and Research Center, Lausanne and Sion, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) companions are increasingly used for social, emotional, and sometimes romantic fulfillment, raising questions about how people perceive and engage with these technologies. This study explored attitudes toward AI companionship and whether interviewer type (AI, human, or unmoderated) affects disclosure or engagement. A mixed-methods design was employed with 135 adult participants, who completed structured interviews including Likert scale items and open-ended questions about their views on AI companions. Most participants (55.6%) expressed hesitancy or resistance toward emotionally significant relationships with AI, although several reported openness to non-intimate or functional companionship such as friendship or mentoring. Motivations for engaging with AI included its non-judgment and trustworthiness, as well as its ability to provide emotional support and optimize daily life. Key barriers involved its lack of physicality, lack of humanity, incapacity to form an emotional connection, and privacy concerns. Participants in the unmoderated condition rated AI as a friend significantly higher than those in the human interviewer condition, and rated AI as equivalent to a human companion and as a potential romantic partner significantly higher than those in both the chatbot and human interviewer conditions. No statistically significant differences emerged across conditions in self-reported honesty. Participants' engagement metrics were generally higher in the human and unmoderated interviews compared to AI. These findings offer methodological insights for research on sensitive topics and highlight the complex, context-dependent ways people relate to AI companionship. Implications for policy, clinical practice, and the design of future AI companion systems are discussed.

Indexed as

AI companionshipIntimacyTechnology and relationships

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.