Psychological predictor variables of emotional maladjustment in infertility: Analysis of the moderating role of gender
Bibliographic record
Abstract
The objective of this study is to find out if the variables state-anxiety, trait-anxiety, positive-affect, negative-affect, alexithymia, and adaptive (personal and interpersonal) resources can predict emotional maladjustment in infertile people, taking into account the potentially moderating role of gender. A sample of 101 participants with an infertility diagnosis (51 males and 50 females) completed a battery of psychological tests (DERA, Emotional Maladjustment and Adaptive Resources in Infertility questionnaire, State-Trait Anxiety Inventory [STAI], PANAS, Positive and Negative Affect Schedule, and TAS-20, [Toronto Alexithymia Scale]). The moderating, partial, and interactive effects of the variables were analyzed using hierarchical regression analysis. The resulting model explained 71.1% of total variance, resulting in gender as an important moderating variable and trait anxiety, state anxiety, negative affect, and low interpersonal resources as strong predictors of emotional maladjustment in infertile people. These results provide guidance in selecting the most appropriate psychological support and treatment for the emotional adjustment of infertile women and men.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".