Association of Synthetic House-Tree-Person Drawing Test and Depression in Cancer Patients

Guifang Yang · Liping Zhao · Lijuan Sheng

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Psychological Testing and Assessment Cancer survivorship and care Art Therapy and Mental Health

Abstract

Background . Evidence regarding the relationship between synthetic house-tree-person (S-HTP) drawing test and depression in cancer patients is limited. The aim of this study was to explore the applicability and validity of S-HTP drawing test in cancer patients suffering from depression. Methods . As a population based cross-sectional study, 167 patients with cancer were enrolled in a hospital in China from December 2015 to December 2017. Self-edited general information questionnaire, self-rating depression scale (SDS), and the S-HTP drawing test were completed by all participants. Results . The average age of 167 selected participants was 52.92 ± 10.43 years old, and about 58.7% (98/167) of them were male. On SDS, depression rate was found in 34.1% (27/167) cancer patients. The logistic regression equation was established by using the depression drawing characteristics as the independent variables and the evaluation results from SDS as the dependent variable and 9 drawing characteristics employed in the regression equation ( χ 2 = 68.657, P < 0.001. Nagelkerke R 2 = 0.466). Correlation analysis revealed a positive correlation between S-HTP drawing test and SDS for depression state of cancer patients (p < 0.01). Conclusions . There are interrater reliability and test-retest reliability between S-HTP drawing test and SDS. The S-HTP drawing test could help in screening depression in cancer patients.

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References

1965A Self-Rating Depression Scale 1948The H-T-P technique. A qualitative and quantitative scoring manual 2006Advancing Personality Assessment Terminology: Time to Retire "Objective" and "Projective" As Personality Test Descriptors 2016Haitian children’s resilience and vulnerability assessed with house–tree–person (HTP) drawings.

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2022The House-Tree-Person test is not valid for the prediction of mental health: An empirical study using deep neural networks 2022Automated Drawing Psychoanalysis via House-Tree-Person Test 2024Adolescent mental health state assessment framework by combining YOLO with random forest 2025Effectiveness Evaluation for Clinical Depression Detection Using Deep Learning Based Synthetic House-Tree-Person Test 2026Tree Imagery in Drawing Tests for Screening Mental Disorders: A Systematic Review and Meta‐Analysis

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