A-220 Hooper Visual Organization Test: Item Analyses and Scale Performance in a Nonclinical Adult Sample
Bibliographic record
Abstract
Abstract Objective: The 30-item Hooper Visual Organization Test (HVOT) measures visuospatial synthesis. While satisfactory reliability estimates have been reported, some items show poor discrimination and items do not appear to be ordered by increasing difficulty level. Little psychometric evidence, however, has been gathered with healthy nonclinical adults in North America. Examination of item performance in healthy adult samples aids in understanding what might be clinically noteworthy in neurological or psychiatric patients. Thus, we examined HVOT total score performance, item difficulty and discrimination, internal consistency reliability, and correlations of HVOT total scores with demographic and neuropsychological variables in a healthy adult sample in Canada. Method: Participant were 71 cognitively intact, non-depressed men and women ages 21-82 years (M=51.5, SD=18.3), with 9-21 years of education (M=15.0, SD=2.79), recruited from the general community. Participants were tested individually on various neuropsychological tests (HVOT, MMSE, Block Design, ROCF, Trails, Five Point Test, FAS/Animals, Vocabulary). Results: Items ranged in difficulty (0.16-1.00) but tended to be easy (M=0.82). Item discrimination ranged from -.17 to.47. Cronbach’s alpha was 0.62. Total scores ranged from 17-29.5 out of 30 (M=25.4) and correlated significantly with age, MMSE, Block Design, ROCF, Trails, and Animals (r=|.29|-|.44|). Conclusions: Our results suggest that some HVOT items are too easy and/or show poor discrimination. Items are not well-ordered by difficulty. We discuss some notable divergences from proposed re-orderings from clinical samples. Demographic results fit with the literature; correlations with other measures extend previous findings. Our results serve as a guide for revisions and a useful baseline for clinical comparison.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".