Development and Validation of the Spiritual Impact Rating Scale for Women (SIRSW): A Tool for Assessing College Women's Spirituality
Bibliographic record
Abstract
Spirituality impacts college student outcomes in the United States such as mental health, physical health, academic success, and healthy behaviors. Numerous studies consistently show gender differences on spirituality measures. The wealth of empirical evidence demonstrating gender differences in spirituality warranted the development of a tool for measuring college women's spirituality. The purpose of this study was to develop and examine the psychometric properties of the SIRSW, including its content validity, factorial structure, and internal consistency using a college women sample. A sample of 667 undergraduates (ages 18-26) at an all-women’s Catholic University in the upper Midwest completed the spirituality survey in Spring 2018. Demographic characteristics were analyzed using descriptive statistics. Demographic differences in spirituality score were assessed using t-test and one-way ANOVA. Psychometric characteristics of the SIRSW were assessed by evaluating variability, internal consistency reliability, and overall scale structure. There were no significant demographic differences in total spirituality score. Internal consistency was high (Cronbach alpha = 0.97). Item-scale coefficients were above the minimum criteria. Factor analysis revealed that the 16-items measuring spirituality fell under the one-factor component and accounted for 82% of the variance. The SIRSW was found to be a valid and reliable tool for assessing the spiritual well-being of college women. Understanding college women’s spirituality can inform the development of a spiritually oriented intervention that is consistent with their values enhancing their psychological, mental, and physical well-being.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".