Sex addiction in Turkey: A large-scale survey with a national community sample
Bibliographic record
Abstract
Abstract Prior studies on sex addiction have mostly relied on a narrow range of risk factors among small and heterogeneous samples. The purpose of the present study was to examine the psychological markers related to sex addiction in a large-scale community sample of Turkish adults. A total of 24,380 individuals completed a survey comprising the Sex Addiction Risk Questionnaire, the Brief Symptom Inventory, the Positive and Negative Affect Schedule, the Personal-Wellbeing Index Adult Form, the Toronto Alexithymia Scale, and the Experiences in Close Relationships-Revised (50% males; mean age = 31.79 years; age range = 18 to 81 years). Utilizing hierarchical regression analysis, sex addiction was associated with being male, being younger, having a lower education level, being single, being an alcohol and nicotine user, psychiatric distress, low personal wellbeing, positive and negative affect, alexithymia, and anxious attachment. This study suggests that socio-demographic factors and aforementioned detrimental psychological factors exacerbate higher engagement in addictive sexual behaviors among the Turkish community. However, more studies are needed to better understand the factors associated with sex addiction in Turkey.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".