Opposite-sex relationship questionnaire for female adolescents: development and psychometric evaluation
Bibliographic record
Abstract
Aim The goal of the present study is to adopt state-of-the-art techniques and standards to develop and evaluate a measure, called the opposite-sex relationship questionnaire for female adolescents (OSRQFA), to assess the reasons why adolescent girls would or would not develop, a relationship with an adolescent boy. Methods A mixed-method, sequential, exploratory design was adopted. In the qualitative phase, an in-depth interview approach was used to identify the properties and dimensions to be included in the OSRQFA. In the quantitative phase, the psychometric properties of the OSRQFA were evaluated according to face, content and construct validity. Reliability and stability were assessed with Cronbach's α and test-retest analysis, respectively. Results A preliminary questionnaire including 86 items which emerged from the qualitative phase of the study was designed. Based on the impact scores for face validity and the cutoff points for the content validity ratio (CVR) and content validity index (CVI), the preliminary questionnaire was reduced to 57 items. The Kaiser criteria (eigenvalues >1) and scree plot tests demonstrated that 21 items forming six factors, which were labeled 'innate predilection', 'abstinence', 'peer pressure', 'fear of the relationship consequences', 'family atmosphere' and 'risk taking', that accounted for an estimated 66.19% of variance provided an optimal fit with the data. These scales had acceptable levels of internal consistency (α = 0.822) and stability (r = 0.871, p < 0.001). Conclusion The OSRQFA with 21 items and 6 factors demonstrated suitable validity and reliability in a sample of Iranian female adolescents. The OSRQFA's has good psychometric properties, and can be used by other researchers in future studies.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".