Synthetic House-Tree-Person Drawing Test: A New Method for Screening Anxiety in Cancer Patients.
Sheng Lijuan,Yang Guifang,Pan Qian,Xia Chunfang,Zhao Liping
Journal of oncology
The synthetic house-tree-person (S-HTP) drawing test is a projective measure primarily designed to assess specific complex personality traits. It is widely used in general psychological problems and mental illness such as psychological crisis intervention. Applicability and validity of S-HTP drawing test in cancer patients suffering from anxiety are still unclear and there are no reports on such research. The aim of this study was to explore the prevalence of anxiety in cancer patients and to investigate the applicability of S-HTP drawing test in such patients. Self-rating anxiety scale (SAS) and the S-HTP drawing test were applied to 167 cancer patients (58.7% male; 41.3% female), 52.92±10.43 years old. On SAS, anxiety rate was found in 16.17% cancer patients. Using the evaluation results from SAS as the dependent variable and the anxiety drawing characteristics as the independent variables, the logistic regression equation was established, and 9 drawing features were employed in the regression equation (2=56.982, P≤0.001, Nagelkerke R2=0.492). It is concluded that there is a positive correlation between S-HTP drawing test and SAS for anxiety state of cancer patients (p<0.01). S-HTP drawing test and SAS have interrater reliability and test-retest reliability. Our findings indicate that the S-HTP drawing test could help in screening anxiety in cancer patients.
10.1155/2019/5062394
Feasibility study on using house-tree-person drawings for automatic analysis of depression.
Computer methods in biomechanics and biomedical engineering
Major depression is a severe psychological disorder typically diagnosed using scale tests and through the subjective assessment of medical professionals. Along with the continuous development of machine learning techniques, computer technology has been increasingly employed to identify depression in recent years. Traditional methods of automatic depression recognition rely on using the patient's physiological data, such as facial expressions, voice, electroencephalography (EEG), and magnetic resonance imaging (MRI) as input. However, the acquisition cost of these data is relatively high, making it unsuitable for large-scale depression screening. Thus, we explore the possibility of utilizing a house-tree-person (HTP) drawing to automatically detect major depression without requiring the patient's physiological data. The dataset we used for this study consisted of 309 drawings depicting individuals at risk of major depression and 290 drawings depicting individuals without depression risk. We classified the eight features extracted from HTP sketches using four machine-learning models and used multiple cross-validations to calculate recognition rates. The best classification accuracy rate among these models reached 97.2%. Additionally, we conducted ablation experiments to analyze the association between features and information on depression pathology. The results of Wilcoxon rank-sum tests showed that seven of the eight features significantly differed between the major depression group and the regular group. We demonstrated significant differences in HTP drawings between patients with severe depression and everyday individuals, and using HTP sketches to identify depression automatically is feasible, providing a new approach for automatic identification and large-scale screening of depression.
10.1080/10255842.2023.2231113
Association of Synthetic House-Tree-Person Drawing Test and Depression in Cancer Patients.
BioMed research international
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 (2 = 68.657, P < 0.001. Nagelkerke R= 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.
10.1155/2019/1478634
Characteristics of House-Tree-Person Drawing Test in Junior High School Students with Depressive Symptoms.
Clinical child psychology and psychiatry
OBJECTIVE:This study aims to explore the drawing characteristics of the house-tree-person drawing test (HTP) in junior high school students with depressive symptoms. METHODS:A total of 167 junior high school students were recruited and completed HTP and questionnaires. 12 drawing characteristics of HTP were extracted and compared to explore the potential drawing characteristics of depressive symptoms. RESULTS:Among 12 drawing characteristics, eight drawing characteristics appeared more frequently in the depressed group (CES-D ≥ 20) than in the non-depressed group (CES-D < 20), while one drawing characteristic appeared with a lower frequency. Further, controlling for the risk perception of COVID-19, seven drawing characteristics, not suggestive of movement, lacking details, blackening the paper, drawing in an only dark color, drawing a detailed crown, hands behind the back, and omitting expression, emerged as predictors of depressive symptoms (CES-D ≥ 20) in junior high school students. CONCLUSION:Seven drawing characteristics of HTP are significantly associated with depressive symptoms in junior high school students. HTP is insightful for early screening for junior high school students with depressive symptoms.
10.1177/13591045221129706
Analysis of the screening and predicting characteristics of the house-tree-person drawing test for mental disorders: A systematic review and meta-analysis.
Frontiers in psychiatry
Background:The house-tree-person (HTP) drawing test has received growing attention from researchers as a common projective test. However, the methods used to select and interpret drawing indicators still lack uniformity. Objective:This study aims to integrate drawing indicators into the process of screening for or classifying mental disorders by conducting a systematic review and meta-analysis of the application of the HTP test. Methods:A search of the following electronic databases was performed in May 2022: PubMed, Web of Science, Embase, EBSCO, CNKI, VIP, and Wanfang. Screening and checking of the literature were performed independently by two researchers. The empirical studies published on the use of the HTP test in mental disorders and studies providing specific data on the occurrence frequency of drawing characteristics were analyzed. A total of 30 studies were included in the meta-analysis, including 665 independent effect sizes and 6,295 participants. The strength of the association between drawing characteristics of the HTP test and the prevalence of mental disorders was measured by the ratio (OR) with a . Publication bias was assessed using a funnel plot, Rosenthal's fail-safe number ( ), and the trim and fill method. Results:The results revealed 50 drawing characteristics that appeared at least three times in previous studies, of which 39 were able to significantly predict mental disorders. The HTP test can be divided into the following four dimensions: house, tree, person, and the whole. These dimensions reflect the structure, size, and other characteristics of the picture. The results showed that the greatest predictor of mental disorders was the whole (OR = 4.20, < 0.001), followed by the house (OR = 3.95, < 0.001), the tree (OR = 2.70, < 0.001), and the person (OR = 2.16, < 0.001). The valid predictors can be categorized into the following four types: item absence, bizarre or twisted, excessive details, and small or simplified. The subgroup analysis showed that the affective-specific indicators included thought-specific indicators included , , , and ; and common indicators of mental disorders included , , , , and . Conclusion:These findings can promote the standardization of the HTP test and provide a theoretical reference for the screening and clinical diagnosis of mental disorders.
10.3389/fpsyt.2022.1041770
The Application of Human Figure Drawing as a Supplementary Tool for Depression Screening.
Frontiers in psychology
Objective:Depression is one of the most prevalent mental disorder in college students. The traditional screening method for is psychological measurements or scales, but social desirability can cause students to mask their thoughts, and an auxiliary projective test may be needed. This study was designed to measure the validity of applying human figure drawing (HFD) test as an auxiliary tool for depression screening in this population. Methods:The HFD test was administered to 113 clinical participants diagnosed with major depressive disorder and 97 healthy college students with self-rating depression scale scores <50. Correlation analysis, chi-square tests, and logistic regression were conducted to identify specific drawing features that associated with depression and could differentiate between the clinical and control subjects. ROC curve was also implemented to evaluate the diagnostic accuracy. Results:Eleven drawing features were significantly related to depression based on the chi-square test results and seven drawing features were associated with depression based on correlation analysis. After logistic regression by controlling gender and age, three drawing features were associated with depression: shaded eyes, drawing clothes in detail, and drawing other personal belongings. Further, drawing clothes in detail and drawing other personal belongings were two significant variables in ROC curve analysis. Conclusion:Logistic regression showed that shaded eyes, drawing clothes in detail and drawing other personal belongings were significant drawing features. Individuals with depression will have less energy to put extra effort into drawing and are less likely to have detailed drawings. And the shading of eyes may represent that depressive individuals have a low willingness to communicate and tend to isolate themselves. The results indicated that Human Figure Drawing could be used as an auxiliary tool in college students' depression screening. Further, the ROC curve analysis showed low discrimination of single drawing features, suggesting that the application of Human Figure Drawing should be considered as a whole instead of focusing on the single drawing feature.
10.3389/fpsyg.2022.865206