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Tree Imagery in Drawing Tests for Screening Mental Disorders: A Systematic Review and Meta-Analysis.

Huibing Guo^1,2, Bin Feng^1,3, Tiantian Liu⁴

¹Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, Psychoradiology Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China, wchscu.cn.

Depression and Anxiety

|July 12, 2026

Summary

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Tree drawing features can nonverbally screen for mental disorders. Specific characteristics like blackened trees and lack of vitality significantly predict conditions, aiding clinical assessment.

Area of Science:

Psychology
Psychiatry
Clinical Psychology

Background:

Tree imagery in projective drawing tests is a potential nonverbal tool for mental disorder screening.
Clinical utility is limited by inconsistent predictor selection.
A systematic review and meta-analysis is needed to synthesize characteristics and evaluate predictive efficacy.

Purpose of the Study:

To systematically review and synthesize characteristics of tree imagery linked to mental disorders.
To evaluate the predictive efficacy of these tree imagery characteristics.
To address the gap in consistent predictor selection for mental disorder screening.

Main Methods:

Systematic review and meta-analysis following PRISMA guidelines.
Analysis of 42 studies with 8552 participants from English and Chinese databases (1948-2024).

Keywords:

affective and thought disorders drawing test mental disorders meta-analytic review systematic review tree imagery

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Identification and classification of 24 specific characteristics predicting mental disorders.

Main Results:

Twenty-four specific tree drawing characteristics significantly predicted mental disorders (p < 0.05).
Key categories include blackened out, scribbled lines, oddly shaped, no vitality, and overly simple drawings.
Subgroup analyses revealed "roots" uniquely associated with thought disorders, while "blackened tree" and "no motion" linked to affective disorders.

Conclusions:

Tree imagery offers a valuable nonverbal, adjunctive approach for mental disorder screening.
Statistically supported indicators in tree drawings can complement traditional assessment tools.
Standardized interpretation of tree imagery characteristics can enhance diagnostic accuracy.