Demographic and Life Styles Determinants of Somatic Complaints’ Structures: A Cross-sectional Study on a Large Sample of Iranian Adults Using Factor Mixture Model
Bibliographic record
Abstract
Background: To identify somatic complaints dimensions, classify studied population and study the association of demographic and lifestyle factors with somatic complaints dimensions. Methods: In a cross-sectional study conducted on 4763 Iranian adults, somatic complaints were assessed using a comprehensive 30-item questionnaire. Self-administered standard questionnaires were used to assess demographic and lifestyle factors. Factor mixture modeling (FMM) was used to identify somatic complaints dimensions and classify studied population. Results: The mean age of participants was 36.58 ± 0.13 years, 55.8% were females, 81.2% were married, and 57.2% had college education. About 9.4% of individuals were obese, and 34.8% of participants had regular physical activity. Four domains of somatic complaints were extracted, including “psychological,” “gastrointestinal,” “neuro-skeletal,” and “pharyngeal-respiratory.” Females, obese and inactive participants, and those in low educations had significantly greater scores in terms of four domains than the others ( P < 0.05). A two-class, four-factor structure fitted to the somatic complaints based on FMM. Two classes were labeled “high psychological complaints” (519 individuals (11%) and “low psychological complaints” (4243 individuals (89%). There were no significant differences between two classes in terms of demographic and lifestyle factors, except in educational level. Conclusions: This study suggested that somatic complaints had a dimensional-categorical structure within studied population so that it could be useful for dealing with diagnostic and therapeutic approaches. The results did not show any association between somatic complaints dimensions and demographic, lifestyle factors, except in educational level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".