Login
Register
Submit a Paper
Propose a Special lssue
Open Access
ARTICLE
From Fragmentation to Integration: A Multi-Site Pilot Study of Psychodrama in Chinese University Mental Health Systems
1 School of Social Work, China University of Labor Relations, Beijing, China
2 Mental Health Education Center, Beijing Institute of Graphic Communication, Beijing, China
3 College of Humanities and Urban-Rural Development, Beijing University of Agriculture, Beijing, China
4 Nien-Hwa Lai, Zhiying Counseling Room, Osaka, Japan
5 Department of Social Work, The Chinese University of Hong Kong, Hong Kong, China
* Corresponding Authors: Nien-Hwa Lai. Email: ; Rui Ding. Email:
# Xiaohui Wang, Aiqin Liu and Zechun Ma contribute equally to this paper
International Journal of Mental Health Promotion 2026, 28(6), 3 https://doi.org/10.32604/ijmhp.2026.078910
Received 10 January 2026; Accepted 11 March 2026; Issue published 23 June 2026
View Full Text
Download PDFAbstract
Objectives: Chinese higher education faces rising depression rates amidst fragmented campus mental health services. This pilot study examined the feasibility and preliminary outcomes of implementing a standardized psychodrama program across multiple university sites. Methods: This single-arm study was conducted across three Beijing universities from September 2024 to January 2025. A total of 27 undergraduates completed an 8-week psychodrama intervention program comprising weekly 2.5-h sessions. A unified protocol was ensured through centralized facilitator training and cross-site supervision. Depressive symptoms were assessed using the Beck Depression Inventory-II at baseline, post-intervention, 3-month, and 6-month follow-ups. Retention rates were 93.8% at post-intervention and 84.4% at both follow-up assessments. Results: Significant reductions in Beck Depression Inventory II (BDI-II) scores were observed from baseline to post-intervention and follow-ups, with scores decreasing from a baseline median of 13.00 [9.50–21.50] (mean ± Standard Deviation = 14.67 ± 8.73) to 5.00 [3.50–10.50] (7.11 ± 5.87) at post-intervention (padj < 0.001, r = 0.817). Friedman tests confirmed significant temporal declines across all sites (p < 0.05). At the individual level, 37.0% of participants achieved a ≥50% BDI-II reduction at post-intervention, and 29.6% at 6-month follow-up. Improvement to minimal depression (BDI-II ≤ 13 from baseline ≥14) was achieved by 33.3% at post-intervention and 22.2% at 6 months. Conclusions: This study demonstrated the feasibility of a standardized, multi-site psychodrama framework in Chinese university settings and provided preliminary evidence of symptom reduction from baseline to post-intervention, with reductions sustained through 6-month follow-up. These findings support further controlled trials to evaluate efficacy and sustainability.Keywords
Depression is a surging crisis for global universities [1]. One in three college students worldwide experience varying degrees of depression, a condition associated academical, interpersonal, and societal stressors [2,3,4]. This is particularly pronounced in China, where prevalence rates escalated from pre-pandemic estimates of 30% to 50% during the pandemic era [5,6,7], documenting a significant rise in symptom severity. Depression impacts the physical activity, academic performance, and social functioning of Chinese college students [8,9,10], posing a growing challenge to the national mental health landscape. For decades, mounting evidence across sociological and psychological research has highlighted the buffering effects of social networks on depression interventions [11,12,13]. Higher perceived adequacy of social support, stronger close social link, as well as larger social capital all correlate with depressive alleviation [14,15]. As proof, Chinese college students with weaker social connections exhibit a higher tendency toward suicide [16]. Despite the aforementioned insight in the field, the depression intervention paradigm within higher education systems remains largely atomized [17,18,19,20].
Building social networks for vulnerable groups is highly challenging within Chinese context [21,22]. On the cultural front, students, unlike their Western peers, are less prone to actively seek social support when facing mental health adversities [23,24]. The stigma surrounding mental health issues, particularly the fear of social exclusion, often leads students to handle problems on their own [25,26]. Within the administrative system, the depression intervention module of university mental health departments is significantly restricted by limitations in financial resources, ethical guidelines, and professional staff availability [27,28,29]. Furthermore, collaborations on mental health systems between universities are often lacking [29,30]. Implementing network-oriented depression interventions, as opposed to atomized ones, typically involves longer timeframes and higher resource demands, posing additional challenges [31]. As empirically documented by a China-Canada research team [32], the aforementioned dual challenges—in both help-seeking culture and administrative structures—are further intertwined as systemic barriers that shape the current Chinese campus mental health landscape. To date, there is a lack of evidence regarding how to foster network-based interventions within these constrained campus mental health ecosystems.
We attempted to address these challenges in four ways. First, we implemented psychodrama (PD), an established group therapy that uses role-playing and sociometry to promote healing, with evidence of efficacy across cultures [33]. PD is accredited in Europe [34], and supported by meta-analytic evidence for reducing depression through mechanisms like cognitive restructuring cognitive restructuring [35], behavioral activation [11,12,13], and neuroendocrine regulation [36]. Second, we culturally contextualized the intervention for Chinese collectivist frameworks [37,38,39]—which shape help-seeking behaviors and therapeutic engagement [40,41]. Adaptation in non-Western settings enhances PD’s acceptability and gives it distinct characteristics in China [42,43]. Third, we standardized delivery using a “one program, multiple sites” protocol with centralized training and cross-site supervision, balancing fidelity with local adaptability to support scaling. Fourth, we fostered social networks both within and beyond sessions, encouraging real-world and online connections among participants [44].
Our pilot study therefore aimed to: (a) examine the potential of psychodrama to reduce depressive symptoms among Chinese college students, and (b) evaluate the feasibility of a standardized, multi-site delivery model within the fragmented university mental health system. By bridging these gaps, we position psychodrama as a clinically and administratively scalable intervention within China’s university mental health infrastructure. As the first multi-site PD trial in Chinese mainland, this work pioneers a replicable, culturally responsive framework for university settings, contributing to evidence-based, resource-efficient service models.
Depression among college students is increasingly understood not only as an individual condition but as one embedded in and worsened by deficient social networks [45,46]. This is particularly salient in China, where cultural and administrative factors make building such networks uniquely challenging [47,48,49,50]. Given its theoretical grounding in social systems and its action-based approach to fostering connection, psychodrama has the potential to address this dual challenge.
2.1 Theoretical Foundations: Psychodrama as a Catalyst for Social Bonding
Grounded in the work of Moreno, psychodrama is an action-based group therapy that employs role-playing and dramatic action to facilitate therapeutic change [51,52]. Its core theoretical constructs provide a robust framework for understanding and intervening in social relationships. The concept social atom—the smallest unit of an individual’s social network—offers a model for mapping an individual’s relational world [53]. This concept exhibits a remarkable theoretical congruence with modern social network theory, which systematically analyses how the connections (ties) between individuals (nodes) shape a range of outcomes, including health and well-being [54].
Complementing this, sociometry provides the methodological tools to quantitatively and qualitatively assess these relationships, thereby revealing group dynamics, affinities, and isolates [55]. Through sociometric exercises, psychodrama makes social structures visible and offers a means to strengthen positive ties and reintegrate individuals into the group fabric [56]. Parallelly, role theory contends that much psychological distress originates from rigid, conflicted, or underdeveloped social roles [57,58]. Psychodrama intervenes precisely here through techniques of role expansion and role reversal, creating a safe yet dynamic space for participants to experiment with new ways of being and to foster empathic understanding, thereby directly mitigating social anxiety and building relational skills [51]. Underpinning this entire process is tele, Moreno’s (1953) concept of the authentic, two-way flow of feeling and perception, which is the critical mechanism that makes genuine encounter and change possible in the group.
2.2 Mechanisms of Change: Psychodrama beyond Intra-Group Bonding
Drawing on its theoretical foundations, psychodrama may build social capacity through sequential, action-based mechanisms. In this conceptualization, the first process is posited to begin within the therapeutic group, where psychodrama can be theorized to function as a social skills simulator [59,60]. It is suggested that through structured role-playing and situational enactment, participants may safely practice emotional expression, conflict resolution, and empathic communication, thereby potentially rebuilding the interpersonal competencies [56]. Second, this foundation of enhanced social skills could enable a second mechanism: the active construction of robust social networks [61]. Techniques such as mirroring and doubling can foster trust and reduce negative affect through shared drama-based action [62,63]. As meaningful bonds form, the group can evolve into a supportive peer network, thereby directly countering the social isolation prevalent among depressed students [64].
Third, psychodrama potentially promote the development of sustainable social support and capital. From a sociological perspective, the therapeutic ethos of mutual aid and collective reflection is expected to foster a foundation of trust and reciprocity—core components of social capital [65]. These relational resources is anticipated to extend beyond therapy, helping to create a durable support system that maintains therapeutic gains and buffers against future adversity [66]. Thus, psychodrama may facilitate a progression from skill development to network reinforcement, offering a comprehensive approach to the social aspects of depression [67].
2.3 Incorporating Modern Theories into Psychodrama Practice
Contemporary psychodrama theory continues to refine its application for modern mental health challenges [68]. Recent advances emphasize its utility in mitigating social isolation and enhancing relational resilience, making it a relevant intervention for university setting [69,70]. Its action-oriented, group-based nature can circumvent the help-seeking barriers and stigma, as it promotes self-disclosure in groups of university students [71].
A growing evidence base supports the cross-cultural applicability of psychodrama. Meta-analyses confirm its effectiveness in reducing depressive symptoms across diverse populations [42,72,73]. Importantly for this study, research in Chinese cultural contexts—including Chinese mainland, Hong Kong, and Taiwan—demonstrates its acceptability and positive impact on social connectedness [43]. Successful adaptations have integrated core cultural values into role-playing and sociometric exercises, enhancing its relevance within collectivist frameworks [40,74,75]. This evidence justifies the cultural contextualization effort central to our research design.
Based on this review, psychodrama presents a promising framework with the potential to mitigate depression through social network enhancement, by fostering bonding capital within groups and developing external relational skills. This supports the design of the current pilot study, which examines the feasibility and preliminary outcomes of implementing a standardized psychodrama program across multiple university sites. The approach addresses critical gaps by testing whether this culturally adaptable, group-based modality can function effectively within the fragmented landscape of Chinese campus mental health services.
Ethics. This program serves as a pilot model for future larger-scale interventions. It has completed ethical scrutiny in Chinese mainland (Department of Psychology at Renmin University of China IRB No. 24-054). Participants provided informed consent before the baseline assessment, affirming their voluntary engagement in the study and granting permission for data collection for subsequent quantitative analysis. Furthermore, comprehensive risk management strategies were implemented to safeguard participants and researchers throughout the study. These measures ensured adherence to ethical standards and upheld participant confidentiality at all stages.
Settings. This trial was implemented across three government-funded public universities in Beijing (Universities A, B, and C). The campuses are geographically dispersed across the metropolitan area—located in the southern suburbs, urban center, and northern suburbs, respectively—which minimizes potential cross-site interaction. They also differ in institutional focus and scale: University A is technology-oriented with an enrollment of approximately 9500; University B has a humanities and social sciences focus with about 6700 students; and University C specializes in agricultural sciences with around 10,000 students. This heterogeneity in location, academic orientation, and student population allows the study to examine the feasibility and implementation of the psychodrama intervention across distinct campus contexts within a single metropolitan setting.
Standardization. To standardize operations across the three universities, we developed a unified protocol. Pre-intervention training was provided to facilitators. During the intervention, biweekly supervision and weekly debriefing were implemented. For assessment, the Beck Depression Inventory-II [76] was uniformly applied, and pre-tests, post-tests, and follow-ups were conducted electronically via WJX (an online platform), ensuring the multi-site trial’s standardization.
Control. Due to participant number constraints, this trial did not include a control group.
Eligibility Criteria. Participants were full-time students from the three universities, fulfilling these criteria: (1) Enrolled as undergraduates; (2) Aged 18–25; (3) In good physical health; (4). Expressed a desire for emotional support related to depressive mood or distress; (5) Willing to participate and provide signed informed consent. Participants were excluded if they: (1) Had recent suicidal behavior (within the past month); (2) Were unwilling to fully participate in the study. Given the pilot nature of this study, eligibility was determined through a semi-structured interview conducted by trained personnel, rather than by applying a predetermined psychometric cutoff.
Recruitment & Selection. To mitigate the potential stigma associated with seeking mental health support, we used multiple recruitment channels—including social media announcements, campus posters, and official university websites—to reach students across the three institutions. Applicants from each university were assessed separately by three screening teams in accordance with the eligibility criteria outlined above. Several applicants subsequently declined participation, primarily due to the time commitment required for the eight-session intervention. In total, 32 participants completed the baseline assessment (Univ. A = 8, Univ. B = 14, Univ. C = 10). A complete flowchart of participant recruitment, screening, and retention is provided in the flow diagram (Fig. 1).
Facilitators. Three certified psychodramatists (Liu at University A, Wang at University B, Ma at University C) led the intervention groups. Each holds credentials as a Certified Practitioner (CP) and Practitioner Applicant for Trainer (PAT) from the American Board of Examiners in Psychodrama, Sociometry and Group Psychotherapy (ABEPSGP) and had prior experience delivering psychodrama to college students. Support staff from university counseling centers and social work units assisted at each site. All facilitators completed centralized training and received ongoing cross-site supervision to ensure protocol adherence and intervention quality.
Supervisor. The study was supervised by Lai, an advanced psychodramatist credentialed as a Trainer, Educator, and Practitioner (TEP) by ABEPSGP, a Trained Leader (TL) and Trainer in the Therapeutic Spiral Model (TSM), and a recognized director by the International Zerka Moreno Institute. LNH guided the development of the intervention protocol and provided continuous supervision throughout the trial.
Framework. The trial is a network-based psychodrama intervention framework targeting college students. The intervention comprised eight weekly sessions, each lasting 2.5 h (see Fig. 1 for an overview). The process was divided into three thematic phases (Early, Mid-term, and Final) to structure group development. Sessions combined interactive discussion—focusing on shared experiences and resource identification—with structured role-playing designed to externalize social connections and internal barriers, thereby facilitating network building.
Techniques. Core psychodrama techniques were utilized, including mirroring, role reversal, role playing, sculpture, social atom mapping, use of intermediate objects, sociometric exercises, and role training. These techniques aimed to: (a) enhance relationships with key social stakeholders, (b) develop emotional awareness of social support, and (c) actively construct supportive social networks. The intervention guided participants to identify both university/community resources and personal support strengths, culminating in exercises focused on future self-empowerment. In addition to in-session work, the intervention encouraged the development of social support outside the formal setting. This was facilitated through structured activities such as phone-based check-ins and guidance on forming connections outside the PD group.
Instrument. Depressive symptoms were assessed using the Chinese version of the Beck Depression Inventory-II. This 21-item self-report instrument is rated on a 4-point Likert scale from 0 (no symptom) to 3 (most severe), with total scores ranging from 0 to 63. The Chinese BDI-II has been validated in previous studies and demonstrated high reliability and validity across diverse Chinese populations [77], including college students [78,79]. Based on established cut-offs, scores were interpreted as follows: 0–13 indicating minimal or no depression, 14–19 mild depression, 20–28 moderate depression, and 29–63 severe depression [76,80]. To evaluate the reliability of the scale in the current sample, we calculated internal consistency coefficients at different time points (baseline, post-intervention, first follow-up, and second follow-up). The results demonstrated excellent reliability of the BDI-II in our sample: Cronbach’s α = 0.903 at baseline, α = 0.826 at post-intervention, α = 0.842 at first follow-up, and α = 0.846 at second follow-up. The overall Cronbach’s α coefficient was 0.886, indicating high internal consistency reliability among Chinese college students.
Procedure. In this study, eligible college students provided informed consent and were assessed with the Chinese BDI-II alongside a semi-structured diagnostic interview. Measurements were administered electronically via the WJX platform, a widely used online survey tool in China that allowed participants to complete the survey on their mobile devices or computers. The pre-intervention assessment was administered before the initial session, while the post-intervention survey was completed within three days following the eighth session. In addition to the BDI-II diagnosis, baseline data included demographic and health-related characteristics, such as age, sex, race, educational levels of parents, family structure, and self-reported physical health. Recognizing the absence of data on the stability of PD intervention effects, this study implements a multi-wave assessment protocol: Baseline (T0, 1 week pre-intervention), Post-intervention (T1, within 1 week after final session), Short-term follow-up (T2, 3 months post-intervention), and Medium-term follow-up (T3, 6 months post-intervention).
We employed a sequential, two-stage analytical strategy to first to examine preliminary changes in depressive symptoms and to assess the consistency of these changes across varied university sites. Data are presented primarily as medians with interquartile ranges [IQR] due to the non-normal distribution; means and standard deviations are also reported to facilitate comparison with previous studies.
First, to assess changes in depressive symptoms across the study period, we focused on within-participant comparisons. Due to the single-arm design, intention-to-treat analysis was not applicable. Missing data were handled by complete-case analysis, including only participants with Chinese BDI-II scores at all four assessments, resulting in a final sample of 27 participants (93.8% retention at post-intervention and 84.4% at follow-ups). Shapiro-Wilk tests indicated significant deviations from normality at post-intervention (W = 0.924, p = 0.049), 3-month (W = 0.877, p = 0.004), and 6-month (W = 0.783, p < 0.001) assessments. We therefore employed non-parametric methods, using Friedman rank-sum tests to detect omnibus time effects, followed by post-hoc Wilcoxon signed-rank tests for pairwise comparisons. The p-value represents the probability of obtaining the observed results, or results more extreme, under the assumption that the null hypothesis is true. A p-value < 0.05 was considered statistically significant for the primary Friedman tests. For the post-hoc pairwise comparisons, the significance level was adjusted to padj < 0.0083 (0.05/6) after applying the Bonferroni correction for six planned comparisons. Effect sizes (r) were computed to quantify the magnitude of effects independent of sample size.
Second, to explore potential heterogeneity in intervention response across the three university sites, we conducted site-specific Friedman and Wilcoxon tests following the same analytical approach described above. This allowed us to examine whether the observed temporal patterns were consistent or varied across different campus contexts. This analytical approach enabled a focused investigation of the intervention’s temporal effects and cross-site consistency, aligning with the pilot study’s objectives of assessing feasibility and preliminary within-person change.
Figure 1: Overview of the Enrollment and Selection Protocol. Figure legend for Fig. 1: (Left Panel) Program Implementation Framework: Illustrates the key stages of the study (Design, Pre-Intervention, Intervention, and Follow-up) and the primary teams responsible at each phase (Research Team, Facilitators, Supervisor). (Upper Right Panel) Flow Diagram: Depicts the flow of participants through the three university sites (A, B, and C), including recruitment, screening, allocation, intervention completion, and assessment points. (Lower Right Panel) Structure of the 8-Session Psychodrama Intervention: Outlines the thematic progression of the weekly sessions (Early, Mid-term, and Final phases), lists the core psychodrama techniques employed, and highlights the integration of the social network theme throughout the intervention process. Note: BDI-II = Beck Depression Inventory-II; PD = Psychodrama.
4.1 Baseline and Participant Characteristics
The final analytic sample of this single-arm intervention program consisted of 27 undergraduate students (mean age = 19.63 ± 0.93 years; 66.7% female) from three Beijing universities (University A = 6, University B = 14, University C = 7), all serving as experimental sites receiving the same intervention. Participants were predominantly urban residents (55.6%), with 44.4% holding rural hukou (a system of household registration), and reported an average of 1.74 ± 0.66 children per family. Most fathers had high school education or below (70.4%). Regarding health profiles, 74.1% self-rated as physically healthy, 55.6% exercised ≥2–3 times weekly, and the cohort showed elevated baseline depression symptoms (BDI-II score: 13.00 [9.50–21.50]; mean ± SD = 14.67 ± 8.73), with only 18.5% having prior counseling experience. Baseline characteristics of participants are presented in Table 1.
Table 1: Baseline characteristics of participants with complete data in the program.
| Characteristic | Overall (N = 27) | Three Sites | ||
|---|---|---|---|---|
| Univ. A (n = 6) | Univ. B (n = 14) | Univ. C (n = 7) | ||
| Age (mean, SD) | 19.63 (0.93) | 18.67 (0.82) | 20.21 (0.58) | 19.29 (0.76) |
| Sex | ||||
| Male | 9 (33.3%) | 2 (33.3%) | 3 (21.4%) | 4 (57.1%) |
| Female | 18 (66.7%) | 4 (66.7%) | 11 (78.6%) | 3 (42.9%) |
| Hukou | ||||
| Rural | 12 (44.4%) | 2 (33.3%) | 6 (42.9%) | 4 (57.1%) |
| City | 15 (55.6%) | 4 (66.7%) | 8 (57.1%) | 3 (42.9%) |
| Number of children in the family | 1.74 (0.66) | 1.67 (0.52) | 1.71 (0.73) | 1.86 (0.69) |
| Father Education Level | ||||
| High school and below | 19 (70.4%) | 4 (66.7%) | 10 (71.4%) | 5 (71.4%) |
| University and above | 8 (29.6%) | 2 (33.3%) | 4 (28.6%) | 2 (28.6%) |
| Self-evaluated Physical Health | ||||
| Healthy | 20 (74.1%) | 5 (83.3%) | 10 (71.4%) | 5 (71.4%) |
| Neutral or Unhealthy | 7 (25.9%) | 1 (16.7%) | 4 (28.6%) | 2 (28.6%) |
| Get Exercise | ||||
| 2–3 times one week or more | 15 (55.6%) | 3 (50.0%) | 8 (57.1%) | 4 (57.1%) |
| Less than 2–3 times one week | 12 (44.4%) | 3 (50.0%) | 6 (42.9%) | 3 (42.9%) |
| Seeking help from Counselors | ||||
| Yes | 5 (18.5%) | 1 (16.7%) | 3 (21.4%) | 1 (14.3%) |
| No | 22 (81.5%) | 5 (83.3%) | 11 (78.6%) | 6 (85.7%) |
4.2 Intervention Effects on Primary Outcome
Significant within-subject changes across all timepoints were confirmed through Friedman tests. For the overall sample, χ2(3) = 30.97, p < 0.001 with moderate effect magnitude (Kendall’s W = 0.38); University B showed significant temporal variation (χ2(3) = 18.34, p < 0.001, W = 0.44, moderate effect); University A demonstrated significant changes (χ2(3) = 9.22, p = 0.03, W = 0.51, large effect); and University C likewise exhibited significant variation across timepoints (χ2(3) = 12.09, p = 0.01, W = 0.58, large effect). Overall and site-specific trajectories of BDI-II scores are illustrated in Fig. 2. Corresponding BDI-II scores across timepoints are presented in Table 2 (median [IQR]; mean ± SD provided for reference). Friedman test results are presented in Table 3.
Figure 2: BDI-II scores across time points: overall and site-specific trajectories. Figure legend for Fig. 2: (Left Panel) Overall BDI-II scores for the full sample (N = 27) at four time points: pre-test (baseline), post-test, 3-month follow-up, and 6-month follow-up. Boxplots show median (central line), interquartile range (box), and range (whiskers: 1.5× IQR). Individual data points are jittered to avoid overlap, with grey lines connecting repeated measures from the same participant. Half-violin plots illustrate score distributions. Significance brackets indicate Bonferroni-corrected pairwise comparisons (Wilcoxon signed-rank tests) between baseline vs. post-test, baseline vs. 3-month follow-up, and baseline vs. 6-month follow-up. (Right Panel) Site-specific BDI-II scores for University A (top), University B (middle), and University C (bottom) at the same four time points, presented using the same graphical conventions. Note: BDI-II = Beck Depression Inventory-II. Wilcoxon signed-rank tests with Bonferroni correction for multiple comparisons (significance threshold: p < 0.0083); only comparisons with p < 0.0083 are considered statistically significant. ***p < 0.001 indicates a statistically significant difference.
Table 2: Shapiro-wilk test for normality assumption.
| Analysis Population | Mean (SD) | Median (IQR) | Skewness | Kurtosis | Shapiro-Wilk | ||
|---|---|---|---|---|---|---|---|
| W | p | ||||||
| BDI-II Pre-test | Overall (N = 27) | 14.667 (8.731) | 13.00 [9.50–21.50] | 0.001 | 2.085 | 0.972 | 0.645 |
| Univ. A (n = 6) | 14.500 (11.167) | 15.00 [7.00–20.00] | 0.137 | 1.98 | 0.985 | 0.972 | |
| Univ. B (n = 14) | 12.429 (8.465) | 10.00 [8.25–19.00] | 0.352 | 2.245 | 0.955 | 0.647 | |
| Univ. C (n = 7) | 19.286 (5.880) | 22.00 [14.50–23.50] | −0.331 | 1.491 | 0.901 | 0.335 | |
| BDI-II Posttest | Overall (N = 27) | 7.111 (5.873) | 5.00 [3.50–10.50] | 0.795 | 2.675 | 0.924 | 0.049 |
| Univ. A (n = 6) | 5.333 (5.989) | 3.50 [0.75–8.50] | 0.700 | 2.026 | 0.875 | 0.248 | |
| Univ. B (n = 14) | 6.214 (5.925) | 4.00 [3.25–6.00] | 1.254 | 3.400 | 0.827 | 0.011 | |
| Univ. C (n = 7) | 10.429 (5.062) | 9.00 [8.00–12.00] | 0.829 | 3.027 | 0.929 | 0.539 | |
| BDI-II 3-month Follow-up | Overall (N = 27) | 7.000 (6.552) | 6.00 [2.00–9.00] | 1.125 | 3.548 | 0.877 | 0.004 |
| Univ. A (n = 6) | 9.833 (7.935) | 9.50 [3.75–13.75] | 0.369 | 1.864 | 0.941 | 0.664 | |
| Univ. B (n = 14) | 5.429 (5.302) | 4.00 [2.00–8.50] | 0.889 | 2.801 | 0.896 | 0.100 | |
| Univ. C (n = 7) | 7.714 (7.631) | 6.00 [4.50–7.50] | 1.533 | 4.250 | 0.774 | 0.023 | |
| BDI-II 6-month Follow-up | Overall (N = 27) | 7.037 (8.300) | 3.00 [1.50–13.50] | 1.739 | 6.396 | 0.783 | <0.001 |
| Univ. A (n = 6) | 7.833 (6.824) | 8.50 [2.25–14.00] | −0.061 | 1.085 | 0.977 | 0.935 | |
| Univ. B (n = 14) | 7.071 (9.973) | 3.50 [1.25–6.75] | 1.982 | 6.140 | 0.709 | <0.001 | |
| Univ. C (n = 7) | 6.286 (6.550) | 2.00 [1.50–11.50] | 0.459 | 1.494 | 0.848 | 0.118 | |
Table 3: Friedman test results of BDI-II scores across timepoints by university.
| School | n | χ2 | df | p | Effect Size (Kendall’s W) | Magnitude |
|---|---|---|---|---|---|---|
| University A | 6 | 9.22 | 3 | 0.026 | 0.51 | large |
| University B | 14 | 18.34 | 3 | <0.001 | 0.44 | moderate |
| University C | 7 | 12.09 | 3 | 0.007 | 0.58 | large |
| Overall | 27 | 30.97 | 3 | <0.001 | 0.38 | moderate |
4.2.2 Pre-Post Intervention Effects
The 8-week psychodrama intervention was associated with reductions in BDI-II scores across all participants, with BDI-II scores decreasing from 13.00 [9.50–21.50] (mean ± SD = 14.67 ± 8.73) at baseline to 5.00 [3.50–10.50] (7.11 ± 5.87) post-intervention (p < 0.001, Wilcoxon signed-rank test with Bonferroni adjustment, r = 0.817). Non-parametric analyses were used due to non-normality in post-intervention BDI-II distributions overall (W = 0.924, p = 0.049) (see Table 2).
Site-specific analyses indicated varying trajectories. At University B, BDI-II scores decreased from 10.00 [8.25–19.00] (12.43 ± 8.46) to 4.00 [3.25–6.00] (6.21 ± 5.93) (padj = 0.012, r = 0.832). At University A, scores changed from 15.00 [7.00–20.00] (14.50 ± 11.17) to 3.50 [0.75–8.50] (5.33 ± 5.99) (padj = 0.347, r = 0.863). At University C, scores moved from 22.00 [14.50–23.50] (19.29 ± 5.88) to 9.00 [8.00–12.00] (10.43 ± 5.06) (padj = 0.301, r = 0.772). Complete pairwise comparisons are provided in Table 4.
4.2.3 3-Month Follow-up Outcomes
At the 3-month follow-up, BDI-II scores for the overall sample were 6.00 [2.00–9.00] (mean ± SD = 7.00 ± 6.55), compared to baseline (13.00 [9.50–21.50]; 14.67 ± 8.73) (padj < 0.001, r = 0.801). Scores did not differ significantly from post-intervention levels (5.00 [3.50–10.50]; 7.11 ± 5.87) (padj > 0.999, r = 0.111).
Site-specific analyses showed the following patterns. At University A, scores changed from baseline (15.00 [7.00–20.00]; 14.50 ± 11.17) to 9.50 [3.75–13.75] (9.83 ± 7.94) (padj > 0.999, r = 0.601) and from post-intervention (3.50 [0.75–8.50]; 5.33 ± 5.99) to 9.50 [3.75–13.75] (9.83 ± 7.94) (padj = 0.204, r = 0.909). At University B, scores changed from baseline (10.00 [8.25–19.00]; 12.43 ± 8.46) to 4.00 [2.00–8.50] (5.43 ± 5.30) (padj = 0.015, r = 0.859) and from post-intervention (4.00 [3.25–6.00]; 6.21 ± 5.93) to 4.00 [2.00–8.50] (5.43 ± 5.30) (padj = 0.714, r = 0.441). At University C, scores changed from baseline (22.00 [14.50–23.50]; 19.29 ± 5.88) to 6.00 [4.50–7.50] (7.71 ± 7.63) (padj = 0.188, r = 0.831) and from post-intervention (9.00 [8.00–12.00]; 10.43 ± 5.06) to 6.00 [4.50–7.50] (7.71 ± 7.63) (padj = 0.630, r = 0.645). Complete statistical details are provided in Table 4.
4.2.4 6-Month Follow-up Outcomes
At the 6-month follow-up, BDI-II scores for the overall sample were 3.00 [1.50–13.50] (mean ± SD = 7.04 ± 8.30), compared to baseline (13.00 [9.50–21.50]; 14.67 ± 8.73) (padj < 0.001, r = 0.769). Scores did not differ significantly from post-intervention levels (5.00 [3.50–10.50]; 7.11 ± 5.87) (padj > 0.999, r = 0.133).
Site-specific analyses showed the following patterns. At University A, scores changed from baseline (15.00 [7.00–20.00]; 14.50 ± 11.17) to 8.50 [2.25–14.00] (7.83 ± 6.82) (padj = 0.347, r = 0.863) and from post-intervention (3.50 [0.75–8.50]; 5.33 ± 5.99) to 8.50 [2.25–14.00] (7.83 ± 6.82) (padj > 0.999, r = 0.432). At University B, scores changed from baseline (10.00 [8.25–19.00]; 12.43 ± 8.46) to 3.50 [1.25–6.75] (7.07 ± 9.97) (padj = 0.137, r = 0.665) and from post-intervention (4.00 [3.25–6.00]; 6.21 ± 5.93) to 3.50 [1.25–6.75] (7.07 ± 9.97) (padj > 0.999, r = 0.035). At University C, scores changed from baseline (22.00 [14.50–23.50]; 19.29 ± 5.88) to 2.00 [1.50–11.50] (6.29 ± 6.55) (padj = 0.134, r = 0.896) and from post-intervention (9.00 [8.00–12.00]; 10.43 ± 5.06) to 2.00 [1.50–11.50] (6.29 ± 6.55) (padj = 0.542, r = 0.672). Complete statistical details are provided in Table 4.
Table 4: Pairwise comparisons of BDI-II scores across timepoints by school (Wilcoxon signed-rank test with bonferroni adjustment).
| School | Comparison | n | Statistic | p | padj | Effect Size (r) | Magnitude |
|---|---|---|---|---|---|---|---|
| University A | |||||||
| Baseline vs. Post-intervention | 6 | 15 | 0.058 | 0.347 | 0.863 | Large | |
| Baseline vs. 3-month follow-up | 6 | 17.5 | 0.172 | >0.999 | 0.601 | Large | |
| Baseline vs. 6-month follow-up | 6 | 15 | 0.058 | 0.347 | 0.863 | Large | |
| Post-intervention vs. 3-month follow-up | 6 | 0 | 0.034 | 0.204 | 0.909 | Large | |
| Post-intervention vs. 6-month follow-up | 6 | 3 | 0.279 | >0.999 | 0.432 | Moderate | |
| 3-month vs. 6-month follow-up | 6 | 12 | 0.281 | >0.999 | 0.430 | Moderate | |
| University B | |||||||
| Baseline vs. Post-intervention | 14 | 102 | 0.002 | 0.012 | 0.832 | Large | |
| Baseline vs. 3-month follow-up | 14 | 78 | 0.002 | 0.015 | 0.859 | Large | |
| Baseline vs. 6-month follow-up | 14 | 68.5 | 0.023 | 0.137 | 0.665 | Large | |
| Post-intervention vs. 3-month follow-up | 14 | 68 | 0.119 | 0.714 | 0.441 | Moderate | |
| Post-intervention vs. 6-month follow-up | 14 | 22 | >0.999 | >0.999 | 0.035 | Small | |
| 3-month vs. 6-month follow-up | 14 | 24 | 0.449 | >0.999 | 0.178 | Small | |
| University C | |||||||
| Baseline vs. Post-intervention | 7 | 26 | 0.050 | 0.301 | 0.772 | Large | |
| Baseline vs. 3-month follow-up | 7 | 27 | 0.031 | 0.188 | 0.831 | Large | |
| Baseline vs. 6-month follow-up | 7 | 28 | 0.022 | 0.134 | 0.896 | Large | |
| Post-intervention vs. 3-month follow-up | 7 | 24 | 0.105 | 0.630 | 0.645 | Large | |
| Post-intervention vs. 6-month follow-up | 7 | 24.5 | 0.090 | 0.542 | 0.672 | Large | |
| 3-month vs. 6-month follow-up | 7 | 18 | 0.553 | >0.999 | 0.256 | Small | |
| Overall | |||||||
| Baseline vs. Post-intervention | 27 | 342 | <0.001 | <0.001 | 0.817 | Large | |
| Baseline vs. 3-month follow-up | 27 | 316.5 | <0.001 | <0.001 | 0.801 | Large | |
| Baseline vs. 6-month follow-up | 27 | 283 | <0.001 | <0.001 | 0.769 | Large | |
| Post-intervention vs. 3-month follow-up | 27 | 196.5 | 0.601 | >0.999 | 0.111 | Small | |
| Post-intervention vs. 6-month follow-up | 27 | 129 | 0.650 | >0.999 | 0.133 | Small | |
| 3-month vs. 6-month follow-up | 27 | 154 | 0.637 | >0.999 | 0.084 | Small |
4.2.5 Individual-Level Improvement
To complement the group-level analyses, we examined individual-level improvement using three complementary indicators: improved to minimal depression, improvement by at least one severity category, and ≥50% reduction in BDI-II scores. As shown in Table 5, at post-intervention, 9 of 27 participants (33.3%) who were at least mildly depressed at baseline recovered to minimal depression (BDI-II ≤ 13); 10 participants (37.0%) improved by at least one severity category; and 10 of 27 participants (37.0%) achieved a ≥50% reduction in BDI-II scores from a baseline of at least mild depression. At 3-month follow-up, 8 (29.6%) recovered to minimal depression, 10 (37.0%) improved by at least one category, and 7 (25.9%) achieved a ≥50% reduction. At 6-month follow-up, 6 (22.2%) recovered to minimal depression, 10 (37.0%) improved by at least one category, and 8 (29.6%) achieved a ≥50% reduction. The proportion of participants whose severity category remained unchanged ranged from 59.3% to 63.0%, while deterioration was observed in 1 participant (3.7%) at 6-month follow-up.
Table 5: Improvement in depressive symptoms from baseline to post-intervention and follow-ups.
| Post-Intervention vs. Baseline (N = 27) (%) | Month Follow-up vs. Baseline (N = 27) (%) | 6-Month Follow-up vs. Baseline (N = 27) (%) | |
|---|---|---|---|
| Improved to minimal depression (BDI-II ≤ 13 from ≥14) | 9 (33.3) | 8 (29.6) | 6 (22.2) |
| Improved by ≥1 severity category | 10 (37.0) | 10 (37.0) | 10 (37.0) |
| BDI-II Reduction ≥ 50% (BDI-II baseline ≥14) | 10 (37.0) | 7 (25.9) | 8 (29.6) |
| Unchanged | 17 (63.0) | 17 (63.0) | 16 (59.3) |
| Worsened | 0 (0.0) | 0 (0.0) | 1 (3.7) |
5.1 Feasibility and Preliminary Outcomes, and Short-Term Stability
This pilot study demonstrates the feasibility of implementing a standardized psychodrama program across multiple university sites in Beijing. we delivered an 8-week intervention concurrently at three institutions with differing academic profiles. Centralized training for facilitators and ongoing cross-site supervision were employed to ensure consistent protocol delivery. The model proved operationally feasible: recruitment targets were met across sites, and participant retention remained high throughout the study period, indicating high acceptability. Quantitative data indicated reductions in depressive symptoms post-intervention, with these lower scores maintained at the 3-month and 6-month follow-ups. The successful administration of a unified protocol and the observed retention rates suggest that a standardized, cross-campus approach to psychodrama is viable within Chinese university mental health systems. Multi-site studies represent a recognized strategy for examining the feasibility and preliminary outcomes of interventions across varied settings [81,82]. Compared to single-site investigations, such designs can aid in recruiting participants from multiple sources and allow for the observation of implementation processes in different contexts [83] thereby improving generalizability through broader geographical and demographic representation [84]. To further refine such multi-site models, future feasibility studies could consider (a) prespecifying benchmarks for site-level recruitment and retention, (b) systematically documenting any necessary local adaptations to the core protocol, and (c) planning analyses to explore how site characteristics may relate to implementation processes or outcomes.
Preliminary data also suggested beneficial outcomes that were maintained over time. As highlighted in recent systematic reviews, fewer than 30% of published PD studies incorporate follow-up assessments [85], leading to limited longitudinal data on outcome stability [68,73]. Similarly in China, empirical investigation into the sustained efficacy of PD interventions remain scarce [43]. To contribute preliminary longitudinal data, this pilot study included follow-up assessments at 3 and 6 months post-intervention. BDI-II scores remained lower than baseline at both follow-ups, with no statistically significant changes observed between the post-intervention, 3-month, and 6-month time points. This pattern suggests that symptom levels did not return to baseline within the 6-month observation window and remained relatively stable after the active intervention phase. Future studies should extend follow-up periods (e.g., 12–24 months) to examine the longer-term trajectory of outcomes and explore factors associated with maintenance or change.
5.2 Design Rationale: Addressing Engagement Barriers through Social Connection
The intervention design was informed by the recognition that stigma and reluctance to seek formal help are salient barriers to mental health engagement among Chinese college students [25,26], which can pose implementation challenges for conventional interventions in Chinese university settings [86]. Our intervention was designed with a dual-component structure aiming to foster social connections: (a) structured in-session exercises to cultivate social awareness and bonding within the psychodrama group, and (b) encouragement of peer contact and mutual support outside formal sessions. This design sought to integrate therapeutic processes with peer-support elements, potentially offering a less stigmatizing entry point for engagement. The high retention rates observed in this study are consistent with the acceptability of such a format. Future research is needed to qualitatively explore participants’ experiences of social connectedness and to empirically test whether such design features can effectively reduce engagement barriers.
5.3 Methodological Considerations and Limitations
Several key limitations must be considered when interpreting the findings of this pilot study. First, the single-arm design and small sample size limit causal inference and reduce statistical power. Second, the lack of randomization and a control group increases risks of selection bias and confounding from factors such as academic stress or natural symptom fluctuation. Third, participant characteristics (e.g., predominantly urban hukou, 66.7% female) may restrict generalizability to other student populations. Fourth, the 6-month follow-up period is insufficient to assess the longer-term stability of outcomes. Fifth, the reliance on certified psychodramatists may pose challenges for scalability in resource-constrained settings.
The issue of sample size needs particular discussion, as it is a common constraint in psychodrama interventions. Small cohort sizes inherently reduce statistical power in intervention research [87,88,89], presenting particular methodological constraints for PD studies in Chinese mainland. Campus-based interventions typically enroll fewer than 30 participants, with randomized controlled trials (RCTs) occasionally including fewer than 10 individuals [42,43]. Such constrained samples significantly compromise statistical power and limit generalizability [90]. To address the recruitment challenges typical of such modalities, this study employed a multi-site design across three universities, enrolling 27 participants in total. While this approach pooled recruitment efforts and allowed for preliminary cross-site observation, the resulting subgroup sizes per site (6 to 14) remained small. This is reflected in our site-specific analyses, where some within-site changes did not reach statistical significance, illustrating how limited subgroup samples affect statistical conclusions. The single-arm design further means that the observed improvements, while consistent with a treatment effect, could also be influenced by non-specific factors.
These methodological considerations collectively point to clear priorities for future research. First, randomized controlled trials with larger, more diverse samples are essential to establish causal efficacy and enhance generalizability. Second, such trials should incorporate longer follow-up periods (e.g., 12–24 months) and multi-method assessments to better understand long-term trajectories and underlying mechanisms [91]. Third, to improve scalability, research should explore implementation strategies such as hybrid delivery models or task-shifting approaches to reduce dependency on highly specialized facilitators. Building on the feasibility demonstrated in this pilot study, future work can thus more rigorously evaluate psychodrama’s effectiveness and its potential role in campus mental health systems.
This multi-site pilot study examined the feasibility and preliminary outcomes of implementing a standardized psychodrama program for Chinese college students across three Beijing universities. The 8-week intervention, delivered to 27 undergraduates reporting depressive symptoms, employed core psychodrama techniques including role reversal, mirroring, and sociometry. Quantitative data indicated reductions in BDI-II scores post-intervention, with reductions maintained at the 3-month and 6-month follow-ups. The study demonstrated feasibility in terms of protocol standardization, cross-site coordination, and high participant retention. Limitations include the small sample size, absence of a control group, and reliance on self-report measures. The findings provide preliminary support for further investigation of psychodrama as a culturally responsive group intervention within university mental health systems.
Acknowledgement:
Funding Statement: This work was supported by the 2025 Education and Teaching Reform Project of China University of Labor Relations: Application and Practical Research of Service-Learning Model in the Course Group Social Work Laboratory (Grant No. JG25026).
Author Contributions: Xiaohui Wang, Aiqin Liu, and Zechun Ma contributed equally to this paper as co-first authors. They jointly participated in the experimental design, co-conducted the experimental operations, and were involved in the subsequent manuscript writing and revision process. Nien-Hwa Lai was primarily responsible for the quality control of the experiment, monthly experimental supervision, and manuscript revision. Rui Ding was mainly in charge of data collection, data analysis, manuscript writing, and revision. All authors reviewed and approved the final version of the manuscript.
Availability of Data and Materials: The relevant data of this study are available upon request from the corresponding author.
Ethics Approval: This study has been approved by the Ethics Committee of the Department of Psychology at Renmin University of China (IRB No. 24-054). In this study, eligible college students provided informed consent.
Conflicts of Interest: The authors declare no conflicts of interest.
Abbreviations
| PD | Psychodrama |
| BDI-II | Beck Depression Inventory-II |
| CP | Certified Practitioner |
| PAT | Practitioner Applicant for Trainer |
| ABEPSGP | American Board of Examiners in Psychodrama, Sociometry and Group Psychotherapy |
| TEP | Trainer, Educator, Practitioner |
| TSM | Therapeutic Spiral Model |
| IRB | Institutional Review Board |
| WJX | Wenjuanxing (Questionnaire Star) |
| RCT | Randomized Controlled Trial |
References
1. Villemaire-Krajden R , Barker E . Curbing the campus mental health crisis: the role of extracurricular activity participation. J Youth Dev. 2024; 19( 2): 1– 17. [Google Scholar]
2. Agyapong B , Shalaby R , Wei Y , Agyapong VIO . Can ResilienceNHope, an evidence-based text and email messaging innovative suite of programs help to close the psychological treatment and mental health literacy gaps in college students? Front Public Health. 2022; 10: 890131. doi:10.3389/fpubh.2022.890131. [Google Scholar] [CrossRef]
3. Chang H . Depressive symptom manifestation and help-seeking among Chinese college students in Taiwan. Int J Psychol. 2007; 42( 3): 200– 6. doi:10.1080/00207590600878665. [Google Scholar] [CrossRef]
4. Rao WW , Xu DD , Cao XL , Wen SY , Che WI , Ng CH , et al. Prevalence of depressive symptoms in children and adolescents in China: a meta-analysis of observational studies. Psychiatry Res. 2019; 272: 790– 6. doi:10.1016/j.psychres.2018.12.133. [Google Scholar] [CrossRef]
5. Cheng S , An D , Yao Z , Liu JJ , Ning X , Wong JP , et al. Association between mental health knowledge level and depressive symptoms among Chinese college students. Int J Environ Res Public Health. 2021; 18( 4): 1850. doi:10.3390/ijerph18041850. [Google Scholar] [CrossRef]
6. Jiang CX , Li ZZ , Chen P , Chen LZ . Prevalence of depression among college-goers in mainland China: a methodical evaluation and meta-analysis. Medicine. 2015; 94( 50): e2071. doi:10.1097/MD.0000000000002071. [Google Scholar] [CrossRef]
7. Yu M , Tian F , Cui Q , Wu H . Prevalence and its associated factors of depressive symptoms among Chinese college students during the COVID-19 pandemic. BMC Psychiatry. 2021; 21( 1): 66. doi:10.1186/s12888-021-03066-9. [Google Scholar] [CrossRef]
8. Bi Y , Moon M , Shin M . The longitudinal effects of depression on academic performance in Chinese adolescents via peer relationships: the moderating effect of gender and physical activity. Int J Environ Res Public Health. 2022; 20( 1): 181. doi:10.3390/ijerph20010181. [Google Scholar] [CrossRef]
9. Liu Y , Chen J , Chen K , Liu J , Wang W . The associations between academic stress and depression among college students: a moderated chain mediation model of negative affect, sleep quality, and social support. Acta Psychol. 2023; 239: 104014. doi:10.1016/j.actpsy.2023.104014. [Google Scholar] [CrossRef]
10. Yin Z , Ong LZ , Qiao M . Psychological factors associated with Chinese international students’ well-being in the United States: a systematic review. Jis. 2024; 14( 4): 529– 51. doi:10.32674/jis.v14i4.6428. [Google Scholar] [CrossRef]
11. Cohen S , Wills TA . Stress, social support, and the buffering hypothesis. Psychol Bull. 1985; 98( 2): 310– 57. doi:10.1037/0033-2909.98.2.310. [Google Scholar] [CrossRef]
12. Seeman TE . Social ties and health: the benefits of social integration. Ann Epidemiol. 1996; 6( 5): 442– 51. doi:10.1016/S1047-2797(96)00095-6. [Google Scholar] [CrossRef]
13. Kawachi I . Social ties and mental health. J Urban Health Bull N Y Acad Med. 2001; 78( 3): 458– 67. doi:10.1093/jurban/78.3.458. [Google Scholar] [CrossRef]
14. Sirin SR , Gupta T , Ryce P , Katsiaficas D , Suárez-Orozco C , Rogers-Sirin L . Understanding the role of social support in trajectories of mental health symptoms for immigrant adolescents. J Appl Dev Psychol. 2013; 34( 5): 199– 207. doi:10.1016/j.appdev.2013.04.004. [Google Scholar] [CrossRef]
15. Zhao G , Xie F , Li S , Ding Y , Li X , Liu H . The relationship between perceived social support with anxiety, depression, and insomnia among Chinese college students during the COVID-19 pandemic: the mediating role of self-control. Front Psychiatry. 2022; 13: 994376. doi:10.3389/fpsyt.2022.994376. [Google Scholar] [CrossRef]
16. Yin K , Li X , Sun J , Yu H . Social networks of college students. Adv Psychol Sci. 2016; 24( 8): 1279. doi:10.3724/SP.J.1042.2016.01279. [Google Scholar] [CrossRef]
17. Drum DJ , Denmark AB . Campus suicide prevention: bridging paradigms and forging partnerships. Harv Rev Psychiatry. 2012; 20( 4): 209– 21. doi:10.3109/10673229.2012.712841. [Google Scholar] [CrossRef]
18. Fu Z , Zhou S , Burger H , Bockting CLH , Williams AD . Psychological interventions for depression in Chinese university students: a systematic review and meta-analysis. J Affect Disord. 2020; 262: 440– 50. doi:10.1016/j.jad.2019.11.058. [Google Scholar] [CrossRef]
19. Shan Y , Ji M , Xie W , Li R , Qian X , Zhang X , et al. Interventions in Chinese undergraduate students’ mental health: systematic review. Interact J Med Res. 2022; 11( 1): e38249. doi:10.2196/38249. [Google Scholar] [CrossRef]
20. Toczyski P . Barriers and opportunities of psychosocial support for student well-being at Polish universities. Psychiatr Psychol Klin. 2025; 24( 4): 314– 24. doi:10.15557/PiPK.2024.0039. [Google Scholar] [CrossRef]
21. Shi B . Perceived social support as a moderator of depression and stress in college students. Soc Behav Pers. 2021; 49( 1): 1– 9. doi:10.2224/sbp.9893. [Google Scholar] [CrossRef]
22. Yu M , Cheng S , Fung KP , Wong JP , Jia C . More than mental illness: experiences of associating with stigma of mental illness for Chinese college students. Int J Environ Res Public Health. 2022; 19( 2): 864. doi:10.3390/ijerph19020864. [Google Scholar] [CrossRef]
23. Zong JG , Cao XY , Cao Y , Shi YF , Wang YN , Yan C , et al. Coping flexibility in college students with depressive symptoms. Health Qual Life Outcomes. 2010; 8: 66. doi:10.1186/1477-7525-8-66. [Google Scholar] [CrossRef]
24. Prasertsri N , Holden J , Keefe FJ , Wilkie DJ . Repressive coping style: relationships with depression, pain, and pain coping strategies in lung cancer outpatients. Lung Cancer. 2011; 71( 2): 235– 40. doi:10.1016/j.lungcan.2010.05.009. [Google Scholar] [CrossRef]
25. He H , Wu Q , Hao Y , Chen S , Liu T , Liao Y . Stigmatizing attitudes toward depression among male and female, medical and non-medical major college students. Front Psychol. 2021; 12: 648059. doi:10.3389/fpsyg.2021.648059. [Google Scholar] [CrossRef]
26. Wang X , Peng S , Li H , Peng Y . How depression stigma affects attitude toward help seeking: the mediating effect of depression somatization. Soc Behav Pers. 2015; 43( 6): 945– 53. doi:10.2224/sbp.2015.43.6.945. [Google Scholar] [CrossRef]
27. Aguilera-Martín Á , Gálvez-Lara M , Cuadrado F , Moreno E , García-Torres F , Venceslá JF , et al. Cost-effectiveness and cost-utility evaluation of individual vs. group transdiagnostic psychological treatment for emotional disorders in primary care (PsicAP-Costs): a multicentre randomized controlled trial protocol. BMC Psychiatry. 2022; 22( 1): 99. doi:10.1186/s12888-022-03726-4. [Google Scholar] [CrossRef]
28. Li J , Li J , Zhang W , Wang G , Qu Z . Effectiveness of a school-based, lay counselor-delivered cognitive behavioral therapy for Chinese children with posttraumatic stress symptoms: a randomized controlled trial. Lancet Reg Health West Pac. 2023; 33: 100699. doi:10.1016/j.lanwpc.2023.100699. [Google Scholar] [CrossRef]
29. Rahman A , Malik A , Nazir H , Zaidi A , Nisar A , Waqas A , et al. Technology-assisted cognitive-behavioral therapy for perinatal depression delivered by lived-experience peers: a cluster-randomized noninferiority trial. Nat Med. 2025; 31( 7): 2196– 203. doi:10.1038/s41591-025-03655-1. [Google Scholar] [CrossRef]
30. Weist MD , Mellin EA , Chambers KL , Lever NA , Haber D , Blaber C . Challenges to collaboration in school mental health and strategies for overcoming them. J Sch Health. 2012; 82( 2): 97– 105. doi:10.1111/j.1746-1561.2011.00672.x. [Google Scholar] [CrossRef]
31. Newson M , Peitz L , Cunliffe J , Whitehouse H . A soccer-based intervention improves incarcerated individuals’ behaviour and public acceptance through group bonding. Nat Hum Behav. 2024; 8( 12): 2304– 13. doi:10.1038/s41562-024-02006-3. [Google Scholar] [CrossRef]
32. Ning X , Wong JP , Huang S , Fu Y , Gong X , Zhang L , et al. Chinese university students’ perspectives on help-seeking and mental health counseling. Int J Environ Res Public Health. 2022; 19( 14): 8259. doi:10.3390/ijerph19148259. [Google Scholar] [CrossRef]
33. López-González MA , Morales-Landazábal P , Topa G . Psychodrama group therapy for social issues: a systematic review of controlled clinical trials. Int J Environ Res Public Health. 2021; 18( 9): 4442. doi:10.3390/ijerph18094442. [Google Scholar] [CrossRef]
34. Cruz A , Sales CMD , Alves P , Moita G . The core techniques of morenian psychodrama: a systematic review of literature. Front Psychol. 2018; 9: 1263. doi:10.3389/fpsyg.2018.01263. [Google Scholar] [CrossRef]
35. Hamamci Z . Integrating psychodrama and cognitive behavioral therapy to treat moderate depression. Arts Psychother. 2006; 33( 3): 199– 207. doi:10.1016/j.aip.2006.02.001. [Google Scholar] [CrossRef]
36. Erbay LG , Reyhani İ , Ünal S , Özcan C , Özgöçer T , Uçar C , et al. Does psychodrama affect perceived stress, anxiety-depression scores and saliva Cortisol in patients with depression? Psychiatry Investig. 2018; 15( 10): 970– 5. doi:10.30773/pi.2018.08.11.2. [Google Scholar] [CrossRef]
37. Hwang WC . The psychotherapy adaptation and modification framework: application to Asian Americans. Am Psychol. 2006; 61( 7): 702– 15. doi:10.1037/0003-066X.61.7.702. [Google Scholar] [CrossRef]
38. Sang ZQ , Huang HM , Benko A , Wu Y . The spread and development of psychodrama in mainland China. Front Psychol. 2018; 9: 1368. doi:10.3389/fpsyg.2018.01368. [Google Scholar] [CrossRef]
39. Lai NH . The development and practice of psychodrama in education in Taiwan. In: Giacomucci S , Junqueira Fleury H , Altınay D , editors. Psychodrama in education. Singapore: Springer Nature; 2024. p. 163– 86. doi:10.1007/978-981-97-8377-9_8. [Google Scholar] [CrossRef]
40. Lai NH , Tsai HH . Practicing psychodrama in Chinese culture. Arts Psychother. 2014; 41( 4): 386– 90. doi:10.1016/j.aip.2014.06.005. [Google Scholar] [CrossRef]
41. Wang X , Ma Z , Ding R . Application of psychodrama in the education in Chinese mainland. In: Giacomucci S , Junqueira Fleury H , Altınay D , editors. Psychodrama in education. Singapore: Springer Nature; 2024. p. 187– 200. doi:10.1007/978-981-97-8377-9_9. [Google Scholar] [CrossRef]
42. Wang Q , Ding F , Chen D , Zhang X , Shen K , Fan Y , et al. Intervention effect of psychodrama on depression and anxiety: a meta-analysis based on Chinese samples. Arts Psychother. 2020; 69: 101661. doi:10.1016/j.aip.2020.101661. [Google Scholar] [CrossRef]
43. Wang X , Ding R , Luo R . Effectiveness of psychodrama on mental health outcomes based on Chinese samples: a systematic review and meta-analysis of randomized controlled studies. Glob Ment Health. 2024; 11: e116. doi:10.1017/gmh.2024.89. [Google Scholar] [CrossRef]
44. Skeggs A , Orben A . Social media interventions to improve well-being. Nat Hum Behav. 2025; 9( 6): 1079– 89. doi:10.1038/s41562-025-02167-9. [Google Scholar] [CrossRef]
45. Hefner J , Eisenberg D . Social support and mental health among college students. Am J Orthopsychiatry. 2009; 79( 4): 491– 9. doi:10.1037/a0016918. [Google Scholar] [CrossRef]
46. Santini ZI , Koyanagi A , Tyrovolas S , Mason C , Haro JM . The association between social relationships and depression: a systematic review. J Affect Disord. 2015; 175: 53– 65. doi:10.1016/j.jad.2014.12.049. [Google Scholar] [CrossRef]
47. Kleiman EM , Liu RT . Social support as a protective factor in suicide: findings from two nationally representative samples. J Affect Disord. 2013; 150( 2): 540– 5. doi:10.1016/j.jad.2013.01.033. [Google Scholar] [CrossRef]
48. Tang F , Qin P . Influence of personal social network and coping skills on risk for suicidal ideation in Chinese university students. PLoS One. 2015; 10( 3): e0121023. doi:10.1371/journal.pone.0121023. [Google Scholar] [CrossRef]
49. Chu C , Buchman-Schmitt JM , Stanley IH , Hom MA , Tucker RP , Hagan CR , et al. The interpersonal theory of suicide: a systematic review and meta-analysis of a decade of cross-national research. Psychol Bull. 2017; 143( 12): 1313– 45. doi:10.1037/bul0000123. [Google Scholar] [CrossRef]
50. Zhang S , Li Y , Ren S , Liu T . Associations between undergraduates’ interpersonal relationships and mental health in perspective of social network analysis. Curr Psychol. 2023; 42( 3): 2059– 66. doi:10.1007/s12144-021-01629-3. [Google Scholar] [CrossRef]
51. Karp M , Holmes P , Bradshaw Tauvon K . The handbook of psychodrama. London, UK: Routledge; 2005. doi:10.4324/9780203977767. [Google Scholar] [CrossRef]
52. Baim C , Burmeister J , Maciel M . Psychodrama: advances in theory and practice. Abingdon, UK: Taylor and Francis; 2013. doi:10.4324/9780203961100. [Google Scholar] [CrossRef]
53. Smith ER , Moreno JL . Who shall survive? Foundations of sociometry, group psychotherapy and sociodrama. Am Cathol Sociol Rev. 1953; 14( 3): 194. doi:10.2307/3706701. [Google Scholar] [CrossRef]
54. Borgatti SP , Mehra A , Brass DJ , Labianca G . Network analysis in the social sciences. Science. 2009; 323( 5916): 892– 5. doi:10.1126/science.1165821. [Google Scholar] [CrossRef]
55. Aichinger A , Holl W . Group therapy with children. Wiesbaden, Germany: Springer Fachmedien; 2017. doi:10.1007/978-3-658-15813-2. [Google Scholar] [CrossRef]
56. Hale AE . Conducting clinical sociometric explorations: a manual for psychodramatists and sociometrists. Roanoke, VA, USA: Royal Pub.; 1985. [Google Scholar]
57. Moreno ZT . Psychodrama, role theory, and the concept of the social atom. J Group Psychother Psychodrama Sociom. 1987; 42( 3): 178– 86. [Google Scholar]
58. Blatner A . Foundations of psychodrama: history, theory, and practice. 4th ed. New York, NY, USA: Springer Publishing Co.; 2000. [Google Scholar]
59. Kellermann PF . Focus on psychodrama: the therapeutic aspects of psychodrama. London, UK: Jessica Kingsley Publishers; 1992. [Google Scholar]
60. Şahin Yoluk İ , Togay A , Kırlangıç Şimşek B . The effectiveness of psychodrama on social skills and life satisfaction of disadvantaged early-adolescents. Z Für Psychodrama Und Soziometrie. 2020; 19( 1): 7– 19. doi:10.1007/s11620-020-00559-9. [Google Scholar] [CrossRef]
61. Giacomucci S . Social work, sociometry, and psychodrama: experiential approaches for group therapists, community leaders, and social workers. Singapore: Springer; 2021. doi:10.1007/978-981-33-6342-7. [Google Scholar] [CrossRef]
62. Kellermann PF . Let’s face it: mirroring in psychodrama. In: Psychodrama. London, UK: Routledge; 2013. p. 107– 20. doi:10.4324/9780203961100-12. [Google Scholar] [CrossRef]
63. Usluoglu F . The effects of psychodrama on relationship between the self and others: a case study. Curr Psychol. 2023; 42( 35): 30863– 77. doi:10.1007/s12144-022-04103-w. [Google Scholar] [CrossRef]
64. Ulusoy Y , Sumbas E , Sertkaya B . Psychodrama as an intervention management instrument for internal/external adolescent problems: a systematic literature review. Arts Psychother. 2023; 83: 102000. doi:10.1016/j.aip.2023.102000. [Google Scholar] [CrossRef]
65. Putnam RD . Bowling alone: the collapse and revival of American community. New York, NY, USA: Simon & Schuster; 2000. doi:10.1145/358916.361990. [Google Scholar] [CrossRef]
66. Amoosoltani S , Yazdkhasti F , Oreyzi H , Abbasi Jondani J . The Effectiveness of psychodrama with the content of life skills on loneliness, happiness, affective relationship and parents’ social support in adolescent girls dependent on the cellphone. Couns Cult Psycother. 2021; 12( 45): 239– 68. doi:10.22054/qccpc.2020.49718.2316. [Google Scholar] [CrossRef]
67. Schnabel K . Using psychodrama and sociodrama to overcome social trauma. In: Hamburger A , Hancheva C , Volkan VD , editors. Social trauma—an interdisciplinary textbook. Cham, Switzerland: Springer International Publishing; 2020. p. 131– 7. doi:10.1007/978-3-030-47817-9_14. [Google Scholar] [CrossRef]
68. Lim M , Carollo A , Annabel Chen SH , Esposito G . Surveying 80 years of psychodrama research: a scientometric review. Front Psychiatry. 2021; 12: 780542. doi:10.3389/fpsyt.2021.780542. [Google Scholar] [CrossRef]
69. Giacomucci S , Skolnik S . The experiential social work educator: integrating sociometry into the classroom environment. J Teach Soc Work. 2021; 41( 2): 192– 202. doi:10.1080/08841233.2021.1886223. [Google Scholar] [CrossRef]
70. Giacomucci S . Sociometry and psychodrama in higher education: experiential teaching in counseling, psychology, and social work. In: Giacomucci S , Junqueira Fleury H , Altınay D , editors. Psychodrama in education. Singapore: Springer Nature; 2024. p. 41– 72. doi:10.1007/978-981-97-8377-9_3. [Google Scholar] [CrossRef]
71. Çam O . The influence of psychodrama on promoting self-disclosure in groups of university students. Z Für Psychodrama Und Soziometrie. 2016; 15( 1): 255– 74. doi:10.1007/s11620-015-0309-6. [Google Scholar] [CrossRef]
72. Kipper DA , Ritchie TD . The effectiveness of psychodramatic techniques: a meta-analysis. Group Dyn Theory Res Pract. 2003; 7( 1): 13– 25. doi:10.1037/1089-2699.7.1.13. [Google Scholar] [CrossRef]
73. Orkibi H , Keisari S , Sajnani NL , de Witte M . Effectiveness of drama-based therapies on mental health outcomes: a systematic review and meta-analysis of controlled studies. Psychol Aesthet Creat Arts. 2025; 19( 4): 878– 95. doi:10.1037/aca0000582. [Google Scholar] [CrossRef]
74. Lai ESY , Kwok CL , Wong PWC , Fu KW , Law YW , Yip PSF . The effectiveness and sustainability of a universal school-based programme for preventing depression in Chinese adolescents: a follow-up study using quasi-experimental design. PLoS One. 2016; 11( 2): e0149854. doi:10.1371/journal.pone.0149854. [Google Scholar] [CrossRef]
75. Luo R , Ding R , Wang X , Zhou W , Hou Y . Enhancing emotion regulation through group: a pilot study of psychodrama intervention among college students in China. Arts Psychother. 2025; 96: 102361. doi:10.1016/j.aip.2025.102361. [Google Scholar] [CrossRef]
76. Beck AT , Steer RA , Brown G . Beck depression inventory-II (BDI-II). San Antonio, TX, USA: The Psychological Corporation; 1996. doi:10.1037/t00742-000. [Google Scholar] [CrossRef]
77. Wang Z , Yuan CM , Huang J , Li ZZ , Chen J , Zhang HY , et al. Reliability and validity of the Chinese version of Beck Depression Inventory-II among depression patients. Chin Ment Health J. 2011; 25( 6): 476– 80. [Google Scholar]
78. Peng F . Application of Chinese version of beck depression inventory-II to Chinese first-year college students. Chin J Clin Psychol. 2012; 20( 6): 762– 4. [Google Scholar]
79. Li H , Fu R , Zou Y , Cui Y . Predictive roles of three-dimensional psychological pain, psychache, and depression in suicidal ideation among Chinese college students. Front Psychol. 2017; 8: 1550. doi:10.3389/fpsyg.2017.01550. [Google Scholar] [CrossRef]
80. Li S , Yang F , Li P , Wang X , Dai J , Deng Y . Psychometric properties of the Chinese version of the intolerance of uncertainty inventory in Chinese college students. Neuropsychiatr Dis Treat. 2020; 16: 2579– 89. doi:10.2147/NDT.S268313. [Google Scholar] [CrossRef]
81. O’Mara A , Bauer-Wu S , Berry D , Lillington L . A needs assessment of oncology nurses’ perceptions of National Cancer Institute-supported clinical trial networks. Oncol Nurs Forum. 2007; 34( 2): E23– 7. doi:10.1188/07.ONF.E23-E27. [Google Scholar] [CrossRef]
82. Friese CR , Mendelsohn-Victor K , Ginex P , McMahon CM , Fauer AJ , McCullagh MC . Lessons learned from a practice-based, multisite intervention study with nurse participants. J Nurs Scholarsh. 2017; 49( 2): 194– 201. doi:10.1111/jnu.12279. [Google Scholar] [CrossRef]
83. Smith L , Tan A , Stephens JD , Hibler D , Duffy SA . Overcoming challenges in multisite trials. Nurs Res. 2019; 68( 3): 227– 36. doi:10.1097/NNR.0000000000000324. [Google Scholar] [CrossRef]
84. White NM , Barnett AG . Analysis of multisite intervention studies using generalized linear mixed models. Infect Control Hosp Epidemiol. 2019; 40( 8): 910– 7. doi:10.1017/ice.2019.114. [Google Scholar] [CrossRef]
85. Maya J , Pérez-Berbel M , Giraldo-Arroyave L , Hurtado I . Psychodrama: implementation, study design and effectiveness: a systematic review. BMC Complement Med Ther. 2025; 25( 1): 232. doi:10.1186/s12906-025-04959-y. [Google Scholar] [CrossRef]
86. Qiu L , Feng Y , Luo J , Zhang Y , Yang Q . Predictors of personal depression stigma in medical students in China: differences in male and female groups. Med Educ Online. 2022; 27( 1): 2093427. doi:10.1080/10872981.2022.2093427. [Google Scholar] [CrossRef]
87. Alvarez G , Núñez-Cortés R , Solà I , Sitjà-Rabert M , Fort-Vanmeerhaeghe A , Fernández C , et al. Sample size, study length, and inadequate controls were the most common self-acknowledged limitations in manual therapy trials: a methodological review. J Clin Epidemiol. 2021; 130: 96– 106. doi:10.1016/j.jclinepi.2020.10.018. [Google Scholar] [CrossRef]
88. Etz KE , Arroyo JA . Small sample research: considerations beyond statistical power. Prev Sci. 2015; 16( 7): 1033– 6. doi:10.1007/s11121-015-0585-4. [Google Scholar] [CrossRef]
89. Miciak J , Taylor WP , Stuebing KK , Fletcher JM , Vaughn S . Designing intervention studies: selected populations, range restrictions, and statistical power. J Res Educ Eff. 2016; 9( 4): 556– 69. doi:10.1080/19345747.2015.1086916. [Google Scholar] [CrossRef]
90. Sturm R , Unützer J , Katon W . Effectiveness research and implications for study design: sample size and statistical power. Gen Hosp Psychiatry. 1999; 21( 4): 274– 83. doi:10.1016/S0163-8343(99)00024-9. [Google Scholar] [CrossRef]
91. Sun X , Guo S , Peng J , Li N , Fraser MW . Comparison of two controlled trials designed to reduce aggressive behavior in China. Res Soc Work Pract. 2025; 35( 4): 372– 88. doi:10.1177/10497315241275492. [Google Scholar] [CrossRef]
Cite This Article
Copyright © 2026 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Downloads
Citation Tools
