Construct validity and internal consistency of the Home and Family Work Roles Questionnaires: a cross-sectional study with exploratory factor analysis
Bibliographic record
Abstract
INTRODUCTION: Exploratory Factor Analysis (EFA) measures the underlying relationships between questionnaire items and the factors ("constructs") measured by a questionnaire. The Home and Family Work Roles Questionnaire has not been assessed using EFA; therefore, our objective was to identify the factors measured by this questionnaire. METHODS: We recruited 314 persons to complete the questionnaire and to answer several demographic questions. We determined if the data was factorable by performing Bartlett's test of sphericity and the Kaiser-Meyer-Olkin measure of sampling adequacy. We used the Factor package in Jamovi statistical software to perform EFA. We employed an Oblimin rotation and a Principal Axis extraction method. We also calculated the internal consistency of the questionnaire as a whole as well as each individual question. RESULTS: Our sample consisted of 265 (85%) women, 45 (14%) men, and 3 (1%) non-binary or other genders. The mean age of our participants was 34.65 (SD = 11.57, range = 18-65) years. EFA suggested a three-factor model. Questions 11, 13, 14, 15, and 16 measured one factor (we interpreted this as "Caregiving Roles"), questions 1, 3, 4, 8, 9, 10, 18, and 19 measured a different factor ("Traditionally Feminine Roles"), and questions 2, 5, 6, and 12 measured the "Traditionally Masculine Roles". The questionnaire and each individual question demonstrated excellent internal consistency (Cronbach's α > 0.90). CONCLUSION: The Home and Family Work Roles Questionnaire may measure three distinct factors, which we have named Caregiving, Traditionally Feminine, and Traditionally Masculine Roles. This aligns with the theory used in developing the questionnaire. Separation of the Home and Family Work Roles Questionnaire into three sub-scales with distinct scores is recommended to measure each of the recommended constructs.
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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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".