The Short Version of the Problematic Pornography Consumption Scale (PPCS-6): A Reliable and Valid Measure in General and Treatment-Seeking Populations
Bibliographic record
Abstract
To date, no short scale existed that could assess problematic pornography use (PPU) having a solid theoretical background and strong psychometric properties. Having such a short scale may be advantageous when scarce resources are available and/or when respondents’ attention spans are limited. The aim of the present investigation was to develop a short scale that can be utilized to screen for PPU. The Problematic Pornography Consumption Scale (PPCS-18) was used as a basis for the development of a short measure of PPU (PPCS-6). A community sample (N1 = 15,051), a sample of pornography site visitors (N2 = 760), and a sample of treatment-seeking individuals (N3 = 266) were recruited to investigate the reliability and validity of the PPCS-6. Also, its association was tested to theoretically-relevant correlates (e.g., hypersexuality, frequency of masturbation), and a cutoff score was determined. The PPCS-6 yielded strong psychometric properties in terms of factor structure, measurement invariance, reliability, correlated reasonably with the assessed variables, and an optimal cutoff was identified that could reliably distinguish between PPU and non-problematic pornography use. PPCS-6 can be considered as a short, reliable, and valid scale to assess PPU in studies when the length of a questionnaire is essential or when a brief screening for PPU is necessary.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".