A Psychometric Study of the Kinetic-House-Tree-Person Scoring System for People with Psychiatric Disorders in Taiwan
Bibliographic record
Abstract
Objective/Background The Kinetic-House-Tree-Person (KHTP) drawing test is widely used by psychiatric occupational therapists in Taiwan; however, very little support has been provided through studies examining its psychometric properties. The aim of the study is to validate a scoring system for the KHTP on a group of people with psychiatric disorders. Methods A total of 66 individuals with psychiatric disorders were recruited for this study along with 53 college students as a comparative group. Each participant completed the KHTP test. Half of the individuals with psychiatric disorders (33 people) completed the KHTP again following a 2-week period. The KHTP scoring system contains 54 items representing drawing characteristics. Two independent raters determined the score of the drawings, with the validity and reliability of the KHTP scoring system being subsequently examined by the Rasch and traditional analysis. Results The results reveal both validity and unidimensionality of the KHTP scoring system, demonstrating acceptable test—retest reliability. The intraclass correlation coefficient of the scoring system's inter-rater reliability was .76, with significant statistical differences found between the KHTP scores of college students and individuals with psychiatric disorders. Conclusion The KHTP scoring system has acceptable construct validity, inter-rater reliability, and test—retest reliability. Because drawing tests have the advantage of expressing nonverbal characteristics, the scoring system should prove to be very useful for those who are unwilling or unable to communicate verbally. This study therefore provides valuable information for clinical application, particularly for the psychiatric rehabilitation professions.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".