Fetal health anxiety: development and psychometric properties of the fetal health anxiety inventory
Bibliographic record
Abstract
Objective: To develop a measure to assess fetal health anxiety and examine its factor structure, convergent and divergent validity.Methods: In Study 1, the Short Health Anxiety Inventory-14 item version (SHAI) (Salkovskis et al., Psychol Med. 2002;32:843–853) was adapted for use with pregnant women to examine fetal health anxiety named the Fetal Health Anxiety Inventory (FHAI). Four pregnant women and three subject matter experts (SMEs) reviewed the FHAI. In Study 2, 100 pregnant women completed the FHAI and related self-report measures.Results: In Study 1, both reviewer groups provided feedback directing minor changes to the FHAI. In Study 2, a revised version was used. The revised FHAI demonstrated excellent internal consistency (α = 0.91). Results from an EFA suggested that the FHAI may be conceptualized as a one- or two-factor scale. Convergent (pregnancy-related anxiety [r = 0.56, p = .0001], parental health anxiety [r = 0.53, p = .0001], anxiety [r = 0.57, p = .0001], anxiety sensitivity [r = 0.28, p = .004] and intolerance of uncertainty [r = 0.29, p = .003]) and divergent (parental depression [r = 0.16, p = .12]) validity was evidenced with additional measures of interest.Conclusion: Preliminary findings suggest that the FHAI represents a psychometrically sound instrument to measure the construct of fetal health anxiety. Practical and theoretical implications of the present results are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".