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Record W4410897422 · doi:10.1080/00224499.2025.2510451

‘How’ Matters More Than ‘How Much’: Demographics, Usage Context, and Sexual Well-Being Related to Partnered Teledildonics Use in Men

2025· article· en· W4410897422 on OpenAlexaff
Éliane Dussault, Madison Williams, David Lafortune

Bibliographic record

VenueThe Journal of Sex Research · 2025
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of New BrunswickUniversité du Québec à Montréal
Fundersnot available
KeywordsDemographicsContext (archaeology)PsychologyClinical psychologyDemographySociologyGeography

Abstract

fetched live from OpenAlex

Research on sex toys has mostly studied female or community samples of non-connected sex toy users. Less is known about connected sex toy use (i.e. teledildonics) among men, or the sociodemographics and sexual well-being associated with their usage. A convenience sample of 617 cisgender men who used connected sex toys was recruited among Kiiroo company's listserv and social media (i.e. Discord, Reddit) to respond to an online questionnaire assessing their demographics, sex toy usage (e.g. frequency, motivations), and sexual well-being (e.g. sexual satisfaction, pleasure, self-esteem, functioning). Descriptive, comparative, and binomial multivariable regression analyses were conducted. Partnered teledildonics use, compared to exclusively solo use, was significantly associated with relationship status, higher number of sex toys and sexual partners, higher sexual desire, ability to orgasm with a partner, and sexual self-esteem. This study helps us better understand male teledildonics use and the contexts in which it is associated with higher sexual well-being.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.377
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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