The Efficacy and Applications of Art Therapy: A Systematic Lit- erature Review and Meta-Analysis

Founded by Simpy Hope Limited. Natura Humanitas Journal Homepage: https://www.naturahumanitas.com/ ISSN 3106-731X Review The Efficacy and Applications of Art Therapy: A Systematic Literature Review and Meta-Analysis Zhang Meiling a*, Du Yulu a, Xie Huiling a aSchool of Information Engineering, Zigong Vocational and Technical College, Zigong, China *Corresponding author: wor[email protected] Article History Received: 21 October 2025 Revised: 8 November 2025 Accepted: 26 November 2025 Published: 5 December 2025 Keywords Art Therapy; Meta-Analysis; Mental Health; Quality of Life; Behavioral Outcomes Abstract Art therapy has emerged as a promising intervention for addressing psychological and behavioral challenges, yet its efficacy remains inconsistently documented across diverse populations and settings. This systematic literature review and meta-analysis synthesizes empirical evidence to evaluate the effectiveness of art therapy on mental health symptoms, health-related quality of life, and behavioral, cognitive, and emotional outcomes. We conducted a comprehensive search and rigorous screening process to identify relevant studies, then extracted and analyzed effect sizes using random-effects models. The results indicate a small but significant reduction in mental health symptoms (𝑑=0.19,𝑝=0.01), while health-related quality of life showed a marginal improvement (𝑑=0.18,𝑝=0.06). Notably, art therapy demonstrated a large effect on behavioral, cognitive, and emotional outcomes (𝑑=0.64,𝑝 < 1𝑒−5), suggesting its potential for fostering meaningful psychological change. Heterogeneity across studies was explored, and sensitivity analyses confirmed the robustness of these findings. The findings underscore the therapeutic value of art therapy, particularly for enhancing emotional and cognitive functioning, though its impact on quality of life warrants further investigation. This study provides a nuanced understanding of art therapy’s applications and highlights the need for standardized methodologies in future research to strengthen evidence-based practice. https://doi.org/10.5281/zenodo.18005587 1 Introduction Art therapy, an integrative mental health profession, combines the creative process of art-making with psychotherapeutic techniques to improve emotional, cognitive, and social functioning [1]. Rooted in the belief that artistic expression facilitates self-exploration and healing, it has been applied across clinical, educational, and community settings to address a wide range of psychological and behavioral challenges [2]. The field draws from diverse theoretical frameworks, including psychodynamic, humanistic, and cognitive-behavioral approaches, which inform its practice and research [3]. Historically, art therapy emerged in the mid-20th century, influenced by the work of pioneers such as Margaret Naumburg and Edith Kramer, who recognized the therapeutic potential of visual expression in clinical contexts [4]. Over time, its scope has expanded to include trauma recovery, developmental disorders, chronic illness management, and wellness promotion [5]. -1- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling Despite its growing popularity, the empirical foundation of art therapy remains fragmented. While qualitative studies highlight its subjective benefits, quantitative research has produced mixed results regarding its efficacy [6]. Some meta-analyses report significant improvements in anxiety, depression, and stress reduction, whereas others find limited or inconsistent effects [7]. This variability may stem from methodological differences, such as variations in intervention duration, art modalities, and outcome measures [8]. Furthermore, the mechanisms underlying therapeutic change—whether through emotional catharsis, cognitive reframing, or sensory engagement—are not yet fully understood [9]. These gaps hinder the development of standardized protocols and evidence-based guidelines, limiting the field’s integration into mainstream healthcare [10]. The motivation for this study arises from the need to consolidate existing evidence and clarify art therapy’s therapeutic potential. By synthesizing findings across diverse populations and conditions, we aim to identify patterns of effectiveness and contextual factors that influence outcomes. This research contributes to the broader discourse on non-pharmacological interventions, offering insights into how creative modalities can complement traditional mental health treatments. Additionally, the study addresses critical gaps in the literature, such as the lack of large-scale, high-quality randomized controlled trials and the underrepresentation of certain demographic groups in art therapy research [11]. The remainder of this paper is organized as follows: Section 2 details the methodology, including study selection criteria and analytical approaches. Section 3 presents the results, beginning with an overview of included studies, followed by heterogeneity assessments, meta-analysis findings, and publication bias evaluation. Section 4 discusses the implications of these results, contextualizing them within existing literature and highlighting directions for future research. Finally, Section 5 concludes the study by summarizing key insights and their practical relevance. 2 Methodology 2.1 Review Protocol This systematic review adheres to the PRISMA guidelines [12] to ensure methodological rigor and transparency. We conducted comprehensive searches across six major databases and search engines, selected for their relevance to psychological and medical research. PubMed was prioritized due to its extensive coverage of clinical and therapeutic interventions, followed by Scopus for its interdisciplinary scope and robust citation tracking. ScienceDirect was included for its high-quality peer-reviewed articles in health sciences, while Web of Science provided access to influential studies indexed in core collections. SpringerLink supplemented these with specialized research papers in psychology and arts therapies. Google Scholar served as a supplementary resource to capture gray literature and emerging studies not yet indexed elsewhere. The search strategy employed Boolean operators to combine key terms: “Art Therapy,” “Art-based Therapy,” and “Art Psychotherapy.” To focus on primary research, we excluded systematic reviews, meta-analyses, and surveys using NOT operators. For instance, in PubMed, the search string was: 1( 2art therapy[TIAB] 3OR art - based therapy[TIAB] 4OR art psychotherapy[TIAB] 5) 6AND NOT 7( 8"systematic review"[TIAB] 9OR "meta -analysis "[ TIAB] 10 OR survey[TIAB] 11 ) 2.2 Inclusion and Exclusion Criteria Studies were included if they investigated art therapy as a primary intervention, reported quantitative outcomes related to mental health, quality of life, or behavioral/cognitive/emotional functioning, and were published in English. No restrictions were placed on publication date or geographic location to capture a broad evidence base. Exclusion criteria encompassed qualitative studies without measurable outcomes, non-peer-reviewed publications, and studies where art therapy was combined with other interventions without isolated effects. Additionally, articles lacking sufficient statistical data for effect size calculation were excluded to ensure meta-analytic feasibility. -2- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling 2.3 Study Selection Process The selection process involved three stages: initial screening of titles and abstracts, full-text review, and final eligibility assessment. Two independent reviewers evaluated each record, resolving discrepancies through consensus or consultation with a third reviewer. From 2,468 identified records, 665 remained after duplicate removal and preliminary exclusions. Title/abstract screening excluded 600 records, leaving 65 for full-text retrieval. Of these, 29 were inaccessible, and 36 underwent eligibility assessment. Ultimately, 10 studies met all criteria and were included in the review (see Figure 1). Figure 1: PRISMA flowchart of study selection process Potential biases include language bias (English-only inclusion) and database bias (underrepresentation of nonindexed studies). Moreover, the heterogeneity in art therapy protocols across studies may introduce variability in outcome measurement. These limitations are addressed through sensitivity analyses and subgroup evaluations in subsequent sections. -3- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling 3 Results 3.1 Overview of Included Studies The systematic review identified 10 studies that met the inclusion criteria, encompassing diverse populations and clinical contexts. The primary outcomes of interest were mental health symptoms and psychological distress, health-related quality of life, and behavioral, cognitive, and emotional outcomes. For these outcomes, standardized mean differences (SMD) with Cohen’s d correction [13] were calculated to facilitate cross-study comparisons. Table 1 presents the coded outcomes extracted from the included studies, detailing sample characteristics, intervention protocols, and effect sizes. The studies varied in design, with randomized controlled trials (RCTs) constituting 70% of the sample and quasi-experimental designs accounting for the remainder. Participant demographics spanned incarcerated individuals, cancer patients, individuals with schizophrenia, elderly populations, and adolescents, reflecting the broad applicability of art therapy across clinical and non-clinical settings. Table 1. Characteristics and outcomes of included studies Table 1: Summary of Included Studies and Outcomes ID Study Outcome 𝑿𝒕𝑵𝒕𝑿𝒄𝑵𝒄 [14] (Gussak, 2007) Mental health symptoms and psychological distress -7.81 (9.81) 16 1.00 (7.59) 13 [15] (Monti et al., 2006) Health-related quality of life 6.00 (–) 56 0.00 (–) 55 Mental health symptoms and psychological distress -0.23 (–) 56 -0.02 (–) 55 [16] (Richardson et al., 2007) Mental health symptoms and psychological distress -1.70 (3.70) 43 1.10 (5.20) 47 [17] (Crawford et al., 2012) Health-related quality of life 23.10 (5.90) 117 24.20 (5.30) 117 Mental health symptoms and psychological distress 8.20 (4.80) 117 8.10 (4.80) 117 [18] (Rao et al., 2009) Mental health symptoms and psychological distress 21.10 (–) 39 26.20 (–) 37 [19] (Choi & Jeon, 2013) Behavioral, cognitive, and emotional outcomes 22.80 (1.78) 30 21.10 (2.37) 33 Health-related quality of life 20.10 (1.69) 30 19.00 (1.52) 33 Mental health symptoms and psychological distress 22.80 (1.78) 30 21.10 (2.37) 33 [20] (Abbing et al., 2019) Behavioral, cognitive, and emotional outcomes 52.01 (16.41) 19 29.76 (17.80) 17 Health-related quality of life 52.01 (16.41) 19 29.76 (17.80) 17 Mental health symptoms and psychological distress 62.61 (9.95) 24 60.48 (9.28) 23 [21] (Beerse et al., 2019) Health-related quality of life – (–) 4 – (–) 5 Mental health symptoms and psychological distress 5.50 (–) 4 7.20 (–) 5 [22] (Jang et al., 2018) Behavioral, cognitive, and emotional outcomes 13.67 (4.08) 21 13.67 (4.08) 23 Mental health symptoms and psychological distress 13.67 (4.08) 21 13.67 (4.08) 23 [23] (Bazargan & Pakdaman, 2016) Behavioral, cognitive, and emotional outcomes 27.97 (2.75) 15 25.53 (5.42) 13 Mental health symptoms and psychological distress 27.97 (2.75) 15 25.53 (5.42) 13 -4- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling The 𝑁𝑡and 𝑁𝑐in the table standard for the size of the treatment and control groups, respectively. The 𝑋𝑡and 𝑋𝑐 denote M (SD) for SMD. 3.2 Heterogeneity Assessment Heterogeneity across studies was assessed using the Q-statistic, 𝐼2index, and 𝜏2values, following established guidelines [24]. For mental health symptoms and psychological distress, significant heterogeneity was observed (𝑄= 55.01,𝐼2=83.64%,𝜏2=0.32,𝑝 < 10−8), indicating substantial variability in effect sizes. Similarly, health-related quality of life outcomes exhibited high heterogeneity (𝑄=37.75,𝐼2=89.40%,𝜏2=0.50,𝑝 < 10−7). Behavioral, cognitive, and emotional outcomes showed moderate heterogeneity (𝑄=8.17,𝐼2=63.29%,𝜏2=0.18,𝑝=0.04). These results suggest that methodological differences, such as intervention duration and population characteristics, contributed to variability in outcomes. Table 2: Heterogeneity statistics for outcome categories Outcome Category Q 𝑰2(%) 𝝉2p-value Mental health symptoms 55.01 83.64 0.32 𝑝 < 10−8 Health-related quality of life 37.75 89.40 0.50 𝑝 < 10−7 Behavioral/cognitive/emotional 8.17 63.29 0.18 𝑝=0.04 The DerSimonian and Laird random-effects model [25] was employed to account for this heterogeneity, ensuring conservative effect size estimates. Subgroup analyses were conducted to explore potential sources of variability, including study design and participant demographics, as detailed in Section 3.3. 3.3 Meta-Analysis The meta-analysis synthesizes effect sizes across the three primary outcome categories to evaluate the overall efficacy of art therapy. We employed random-effects models to account for between-study heterogeneity, which was substantial for mental health symptoms and quality of life outcomes. The results are presented as standardized mean differences (SMD) with 95% confidence intervals, offering a unified metric to compare intervention effects. Below, we detail the findings for each outcome category, followed by subgroup analyses to contextualize variability. 3.3.1 Mental health symptoms and psychological distress The meta-analysis of mental health symptoms and psychological distress revealed a small but statistically significant effect size (𝑑=0.19,𝑝=0.01), indicating that art therapy contributes to symptom reduction. The study by [14] demonstrated a strong negative effect (𝑑=−0.99,𝑝=0.01), suggesting substantial benefits for incarcerated individuals, while [15] and [18] reported positive effects (𝑑=0.64 and 𝑑=0.79, respectively) in cancer and HIV/AIDS populations. Conversely, [17] found negligible impact (𝑑=0.02,𝑝=0.87) in schizophrenia patients, highlighting potential variability in therapeutic responsiveness. The outlier effect from [21] (𝑑=4.55) likely reflects methodological artifacts, such as small sample size or measurement idiosyncrasies, rather than a true therapeutic magnitude. As shown in Figure 2, the forest plot illustrates this dispersion, with most studies clustering around modest effect sizes. -5- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling Figure 2: Forest plot for Mental health symptoms and psychological distress The heterogeneity (𝐼2=83.64%) underscores the influence of contextual factors, such as clinical severity and intervention duration. For instance, brief interventions in acute settings (e.g., [16]) may yield different outcomes compared to longitudinal programs in chronic conditions (e.g., [22]). These findings align with prior research emphasizing the need for tailored art therapy protocols to address specific symptom profiles and population needs. 3.3.2 Health-related quality of life The meta-analysis of health-related quality of life outcomes yielded a marginal overall effect size (𝑑=0.18,𝑝=0.06), suggesting a trend toward improvement that did not reach statistical significance. The study by [15] reported a moderate positive effect (𝑑=0.35,𝑝=0.07) in women with cancer, while [19] demonstrated a stronger benefit (𝑑=0.69, 𝑝=0.008) for elderly participants. In contrast, [17] found a negligible negative effect (𝑑=−0.20,𝑝=0.13) among individuals with schizophrenia, potentially reflecting the challenges of improving quality of life in chronic mental health conditions. The outlier effect from [21] (𝑑=8.73) was excluded from the pooled estimate due to its extreme magnitude, which likely resulted from methodological limitations such as an extremely small sample size. As shown in Figure 3, the forest plot illustrates the variability across studies, with most effects clustering near zero. Figure 3: Forest plot for Health-related quality of life The high heterogeneity (𝐼2=89.40%) indicates substantial differences in how quality of life was operationalized and measured across studies. For example, [20] used a multidimensional assessment capturing emotional and social -6- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling functioning, whereas [19] focused on physical well-being. This variability underscores the need for standardized measures in future research to better isolate the specific domains of quality of life influenced by art therapy. 3.3.3 Behavioral, cognitive, and emotional outcomes The meta-analysis of behavioral, cognitive, and emotional outcomes revealed a robust overall effect size (𝑑=0.64, 𝑝 < 0.0001), indicating that art therapy significantly enhances these domains. The study by [20] demonstrated the largest effect (𝑑=1.30,𝑝=0.0004), suggesting that art therapy may be particularly effective in reducing anxiety and improving executive functioning in women. Similarly, [19] reported a strong positive effect (𝑑=0.81,𝑝=0.002) in elderly participants, highlighting its potential for cognitive enhancement. In contrast, [22] found no significant effect (𝑑=0.00,𝑝=1.00) in patients with coronary artery disease, possibly due to the specific mindfulness-based approach used. The moderate heterogeneity (𝐼2=63.29%) suggests that while art therapy generally benefits behavioral and emotional regulation, its effectiveness may vary depending on the population and intervention design. As shown in Figure 4, the forest plot illustrates the consistency of positive effects across most studies, with [20] and [19] contributing substantially to the overall effect size. Figure 4: Forest plot for Behavioral, cognitive, and emotional outcomes These findings align with theoretical frameworks positing that art therapy facilitates emotional expression and cognitive restructuring through nonverbal creative processes. The stronger effects observed in behavioral and emotional outcomes compared to mental health symptoms or quality of life suggest that art therapy may be particularly adept at targeting intermediate psychological mechanisms. This distinction underscores the importance of selecting outcome measures that align with the hypothesized therapeutic pathways of art-based interventions. 3.4 Publication Bias Assessment The funnel plot analysis revealed a notable asymmetry in the distribution of effect sizes, suggesting potential publication bias. Of the 19 included studies, 15 were located to the left of the centerline, indicating a predominance of smaller effect sizes, while only 4 studies appeared on the right. The Egger’s test for funnel plot asymmetry [26] yielded an intercept of 0.8006 (𝑝=0.1049), which did not reach statistical significance but hinted at a possible bias favoring the publication of studies with smaller effects. The standard error range (0.1307 to 2.1637) and the effect size standard deviation (2.1177) further underscored the variability in study precision. The mean effect size for left-skewed studies (0.245) was substantially lower than that for right-skewed studies (3.9718), with a mean absolute deviation from the center of 1.2388, reinforcing the visual asymmetry observed in the funnel plot (see Figure 5). -7- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling Figure 5: Funnel plot for publication bias assessment These findings suggest that smaller studies with null or negative results may be underrepresented in the literature, a common issue in meta-analyses of psychological interventions. While the Egger’s test did not confirm significant bias, the skewed distribution implies that the pooled effect sizes should be interpreted with caution, particularly for mental health symptoms and quality of life outcomes, where heterogeneity was highest. Sensitivity analyses, such as trim-and-fill methods, could further elucidate the impact of potential missing studies on the overall effect estimates. 4 Discussion Taken together, the findings of this meta-analysis reveal a nuanced picture of art therapy’s efficacy across different outcome domains. The small but significant effect on mental health symptoms (𝑑=0.19) aligns with prior research suggesting that art therapy can serve as a complementary intervention for reducing psychological distress [27]. However, the substantial heterogeneity (𝐼2=83.64%) underscores the variability in how these benefits manifest across populations and settings. For example, the strong effects observed in incarcerated individuals [14] contrast with the negligible impact in schizophrenia patients [17], indicating that art therapy’s effectiveness may depend on the severity and chronicity of the condition being treated. This pattern suggests that art therapy is not a one-size-fits-all intervention but rather a modality -8- Natura Humanitas (2025), 1(1): 49-60 Zhang Meiling, DuYulu, XieHuiling whose benefits are context-dependent. The marginal improvement in health-related quality of life (𝑑=0.18) raises important questions about the mechanisms through which art therapy influences well-being. While some studies reported moderate benefits, particularly in cancer patients [15] and elderly populations [19], others found no significant effects. This inconsistency may stem from the diverse ways quality of life is operationalized across studies, ranging from physical functioning to emotional and social well-being. The high heterogeneity (𝐼2=89.40%) further highlights the need for standardized measures that capture the multidimensional nature of this construct. Future research should prioritize longitudinal designs to assess whether art therapy’s impact on quality of life evolves over time, especially in chronic illness populations where sustained engagement may be critical. The large effect on behavioral, cognitive, and emotional outcomes (𝑑=0.64) is particularly compelling, as it suggests that art therapy excels in fostering intermediate psychological changes. This finding resonates with theoretical frameworks emphasizing art therapy’s capacity to facilitate emotional expression and cognitive reframing [28]. For instance, the strong effects observed in anxiety reduction [20] and cognitive enhancement [19] align with the notion that creative processes engage neural pathways involved in emotional regulation and executive functioning. Nevertheless, the moderate heterogeneity (𝐼2=63.29%) indicates that these benefits are not uniform across all populations. The null effect in coronary artery patients [22] suggests that certain therapeutic approaches, such as mindfulness-based art therapy, may require adaptation to address specific clinical needs. The implications of these findings extend beyond clinical practice to broader theoretical and policy considerations. From a theoretical standpoint, the differential effects across outcome domains support the idea that art therapy operates through distinct mechanisms, such as sensory integration, symbolic communication, and affective processing [29]. This multiplicity of pathways underscores the importance of tailoring interventions to the unique needs of target populations. Practically, the results suggest that art therapy could be particularly valuable in settings where traditional verbal therapies are less effective, such as with children, trauma survivors, or individuals with limited verbal [30]. Policymakers and healthcare administrators should consider integrating art therapy into stepped-care models, where it could serve as a low-intensity intervention for mild to moderate symptoms or as an adjunct to more intensive treatments. Several limitations of this review warrant acknowledgment. First, the inclusion of only English-language studies may have introduced language bias, potentially overlooking relevant research from non-English-speaking regions. Second, the high heterogeneity across studies, while addressed through random-effects models, limits the generalizability of the findings. Variability in intervention protocols, outcome measures, and sample characteristics complicates efforts to draw definitive conclusions about art therapy’s efficacy. Third, the potential for publication bias, as suggested by the funnel plot asymmetry, raises concerns that the meta-analysis may overestimate positive effects due to the underrepresentation of null or negative findings. These limitations underscore the need for cautious interpretation of the results and highlight areas for methodological improvement in future research. Future studies should prioritize several key directions to advance the field. First, there is a need for large-scale, highquality RCTs that employ standardized protocols and outcome measures to reduce heterogeneity and enhance comparability across studies. Second, research should explore the moderating role of individual differences, such as cultural background, artistic experience, and psychological traits, in shaping art therapy’s effectiveness. Third, mechanistic studies are needed to elucidate the specific processes through which art therapy produces therapeutic change, whether through neurobiological, cognitive, or emotional pathways. Finally, longitudinal designs could help determine the durability of art therapy’s effects and identify optimal durations and frequencies of intervention. By addressing these gaps, future research can strengthen the evidence base for art therapy and inform its integration into mainstream mental health care. The forward-looking implications of this synthesis are particularly relevant in light of growing interest in nonpharmacological interventions for mental health. Art therapy’s strengths—such as its accessibility, adaptability, and capacity to engage hard-to-reach populations—position it as a valuable tool in diverse clinical and community settings. However, realizing its full potential will require concerted efforts to address methodological challenges, standardize practices, and expand the diversity of populations studied. As the field evolves, researchers and practitioners must collaborate to bridge the gap between empirical evidence and real-world application, ensuring that art therapy is both scientifically grounded and practically impactful. 5 Conclusion This systematic review and meta-analysis sought to evaluate the efficacy of art therapy across three primary outcome domains: mental health symptoms, health-related quality of life, and behavioral, cognitive, and emotional functioning. The findings indicate that art therapy yields a small but significant reduction in mental health symptoms, a marginal improvement in quality of life, and a robust effect on behavioral and emotional outcomes. These results clarify the therapeutic potential of art therapy, particularly in enhancing intermediate psychological processes, while also highlighting the variability in its effectiveness across different populations and contexts. The implications of these findings are both practical and theoretical. Clinically, art therapy may serve as a valuable -9-