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Impact of combiner aerobic and resistance training on depression: a systematic review and meta-analysis of randomized controlled trials

BMC Sports Science, Medicine and Rehabilitation volume 17, Article number: 10 (2025) Cite this article

Abstract

Objective

To summarize the existing literature and evaluate the efficacy of combined resistance and aerobic training in alleviating depressive symptoms among individuals with depression. Subgroup analyses were conducted based on study region, age, depression severity, intervention duration, intervention frequency, and whether the intervention was supervised or unsupervised.

Methods

Five databases were thoroughly examined from database establishment until August 20, 2024, to find randomized controlled trials that investigated resistance combined aerobic training impact on depression.

Results

Finally, 27 eligible studies were included, involving a total of 2,342 patients with depression. The outcomes indicated that resistance combined aerobic training notably improved signs of depression in these patients (SMD=-1.39, 95%CI=-1.80 to -0.96, p = 0.000). Subgroup analysis based on study area, age, severity of depressive symptoms, and exercise prescription revealed that resistance combined aerobic training had a particularly significant effect on middle-aged and elderly patients with depression, as well as on those with moderate depression. Additionally, moderate period (9–24 weeks), moderate frequency (3–4 times per week), a total weekly duration of more than 180 min and supervised training displayed the best results.

Conclusion

Resistance combined aerobic training serves as an efficient approach to relieve depression-related symptoms, particularly in middle-aged and elderly patients with depression and those with moderate depression. Moderate training intensity, duration, frequency, and total weekly duration offer the greatest benefit.

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Introduction

Depression is a common mood disorder that affects hundreds of millions of people worldwide. The World Health Organization (WHO) identifies depression as one of the leading causes of global disability, with an estimated 300 million people affected globally [1]. Depression profoundly impacts an individual’s mood, behavior, and cognition, and is frequently accompanied by other physical and mental health issues, such as cardiovascular disease, metabolic syndrome, and an increased risk of suicide [1]. Research indicates that the underlying mechanisms of depression may involve multiple biological pathways. For instance, changes in inflammatory biomarkers and cellular pathways can significantly influence mood and brain function, highlighting the critical relationship between inflammatory factors and mental health [2, 3].

Currently, pharmacological and psychological treatments are the primary approaches for managing depression, but individual responses to these treatments vary, and some patients experience limited benefits from traditional therapies [4]. As a result, the exploration and promotion of non-pharmacological interventions have increasingly become a focus of research.

In recent years, the role of exercise interventions in improving mental health has garnered significant attention and validation. Studies show that various forms of exercise, including aerobic training, resistance training, and mind-body exercises, positively influence mental health indicators across different populations. Exercise not only alleviates common mental health issues such as depression and anxiety but also effectively enhances overall well-being and quality of life [5]. Additionally, physical activity promotes mental health by regulating inflammation and improving sleep quality. For example, studies have demonstrated that physical activity lowers C-reactive protein levels [6] and systemic inflammation indices [7], suggesting its potential anti-inflammatory properties. Physical activity has also been shown to reduce sleep disturbances and depressive symptoms associated with environmental pollution exposure [8].

Among the various forms of exercise, aerobic activities such as running and cycling are considered some of the most effective interventions. Aerobic exercise improves cerebral blood flow, enhances neuroplasticity, and regulates neurotransmitter levels, including serotonin and dopamine [9], thereby exerting a positive influence on individuals with depression. Furthermore, aerobic exercise boosts self-efficacy, improves sleep quality, and alleviates stress and anxiety, addressing depression from a psychological perspective [10].

While earlier studies primarily focused on the effects of aerobic exercise on depression, resistance training (RT) has gained increasing recognition [11, 12] in recent years. RT not only enhances muscular strength and endurance but has also shown significant effectiveness in alleviating depressive symptoms. Meta-analyses indicate that patients with depression who engage in RT experience reductions in symptom severity, as well as improvements in self-identity and quality of life [13]. These benefits may be attributed to increased body confidence, enhanced metabolism, and hormone regulation associated with resistance training [14].

Moreover, a growing body of research suggests that combining aerobic and resistance training may further enhance therapeutic outcomes for depression through synergistic effects [15]. Aerobic training reduces depressive symptoms by enhancing cardiorespiratory fitness and modulating mood, while resistance training improves body image and self-confidence, offering a more comprehensive approach to mental health [16]. Previous studies have shown that combined aerobic and resistance training improves both cardiorespiratory fitness and muscular strength, providing significant and well-rounded benefits for mental health [17]. Additionally, research highlights that combined training plays a crucial role in improving cardiometabolic health, which in turn facilitates adaptive changes linked to better mental health [18, 19].

Despite these findings, existing research on the effects of combined training on depression shows significant heterogeneity in terms of study design, sample sizes, intervention intensity, and duration [11, 12]. The efficacy of different exercise interventions may vary, and the underlying mechanisms, as well as the optimal parameters for intervention, remain to be fully explored. A systematic integration of current evidence through meta-analysis is essential to quantify the overall effect of combined training on depressive symptoms and identify potential moderators.

Therefore, this study aims to assess the impact of combined resistance and aerobic training interventions on patients with depression through a systematic meta-analysis. We will explore how different intensities, frequencies, and durations of interventions influence improvements in depressive symptoms, providing a stronger evidence base for future clinical practice.

Materials and methods

This research adhered closely to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

Protocol and registration

Protocol was submitted to the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD42024583422.

Search strategy

From database establishment until August 20, 2024, we performed extensive searches in Web of Science, PubMed, EMBASE, the Cochrane Central Register of Controlled Trials, and China National Knowledge Infrastructure (CNKI). No language restrictions were applied during the search process. To obtain relevant research, we used a combination of search terms related to RT, AE and depression. Specifically, terms related to RT included “resistance training,” “strength training,” “weightlifting strengthening program,” “weight-lifting exercise program,” “weight-bearing strengthening program,” “weight-bearing exercise program,” or “training, resistance,” and “training, strength.” terms related to AE included: “Exercises”, “Physical Exercise”, “Physical Exercises”, “Physical Activity”, “Activities, Physical”, “Activities, Physical”, “Aerobic Exercise”, “Aerobic Exercises”, “Exercises, Aerobic”, “Exercise, Isometric”, “Exercises, Isometric”, “Isometric Exercises” .Depression-related terms encompassed “depressive disorder,” “neurosis, depressive,” “depression, endogenous,” “melancholies,” “depressive syndrome,” “major depression,” “moderate depression,” and “mild depression.” What’s more, we applied two search filters: “human” and “article type: randomized controlled trial” to ensure accuracy and relevance of search results. In addition to searching the databases directly, we reviewed references of all gathered papers to uncover additional related studies.

Eligibility criteria

The criteria for trials based on the “PICOS” framework in this review were as follows:

  • P (Population): Patients aged 18 and older with depressive symptoms, as determined through clinical diagnosis or self-report exceeding predetermined clinical thresholds (e.g., Beck Depression Inventory II score > 13).

  • I (Intervention): Resistance Combined Aerobic Training.

  • C (Comparison): (1) Psychological intervention control group: patients receiving standard psychotherapy or mental health interventions (e.g., cognitive behavioral therapy CBT or mild counseling); (2) Non-intervention control group: patients who do not receive any form of exercise intervention or mental health intervention to maintain daily living status.

  • O (Outcome): Depression-related scales such as BDI, HAM-D, BDI-II, PHQ-9, DASS, CES-D, HRSD, MADRS, and QIDS.

  • S (Study Design): RCT.

Exclusion criteria:

  1. (1)

    Research conducted using animal models.

  2. (2)

    Investigations lacking a control group or using control groups with diverse exercise types.

  3. (3)

    Conference abstracts, observational research, papers, and correspondence.

  4. (4)

    Duplicate publications, review articles, letters to the editor, and papers with unavailable original data.

Study selection

All retrieved references were entered into EndNote x9 by WH. Subsequently, WH and BL independently screened and removed duplicate records and evaluated whether each study fulfilled the inclusion criteria. Any disagreements were addressed and settled with the help of YP. For eligible studies, information related to study design, participant characteristics, sample size, study quality, intervention type, frequency, intensity, and duration, depression scales, attendance rates, and any adverse events were collected and recorded. All data were independently extracted by WH and BL.

The means and standard deviations (SDs) of depression scale results were extracted before and after the intervention. For investigations with missing data (e.g., missing post-intervention means and SDs), we initially reached out to the authors via email to request the raw data. In the event that the data were unavailable, post-intervention means were estimated based on the baseline and post-intervention change scores, and post-intervention SDs were calculated via Formula 1: SD post−intervention = √(SD² change - SD² baseline) / (2 * Corr * SD² baseline), where Corr = 0.5 [20]. This Corr value was estimated under assumption of a moderate association between the baseline and post-intervention measurements [21]. Formula 2: SD post−intervention = √N * (upper limit - lower limit) / 2 * t-distribution value, where N = sample size,, and this formula was applicable for sample sizes less than 60 [22]. For studies reporting multiple time points during the intervention period, only the time points after the completion of the exercise training were used to evaluate the results after the intervention.

Definition of subgroups: Intervention frequency: Low frequency was defined as 1–2 sessions/week, moderate frequency as 3–4 sessions/week, and high frequency as 5 or more sessions/week [22]. Training duration: Short-term was defined as 4–8 weeks, medium-term as 9–24 weeks, and long-term as > 24 weeks [22]. Age groups: Young (< 30), middle-aged (30–60), and elderly (> 60). Weekly intervention duration: <120 min, 120–180 min, and > 180 min [20]. According to the depression scale score and clinical diagnosis, the severity of depression was categorized as mild, moderate, or severe. BDI scoring system: no or minimal (0–13), mild (14–19), moderate (20–28), and severe depression (29–63) (See Appendix 2 for details).

Risk of bias assessment

WH and BL separately evaluated the risk of bias through the Cochrane Collaboration tool. The risks in each domain were clearly evaluated and classified as high risk, low risk, or unclear, to ensure reliability of research and research credibility of the findings.

GRADE evidence rating

The quality of evidence was assessed using GRADE profiler 3.6, and the evidence was categorized into four levels: high, moderate, low, and very low. The evaluation covered five aspects: risk of bias, inconsistency, indirectness, imprecision, and publication bias.

Data analysis

For all studies reporting continuous data, outcomes were summarized as MDs or SMDs, accompanied by 95% CIs. Because of significant methodological heterogeneity among the included studies (e.g., variations in depression scales), a random effects model (REM) was employed to summarize effect sizes. Cochran’s Q test and the I² statistic were utilized to evaluate result heterogeneity [23, 24]. If P < 0.05 and I²>50%, significant heterogeneity was considered to exist; otherwise, heterogeneity was deemed insignificant. To investigate possible reasons for heterogeneity, subgroup analyses were performed, considering various factors including study area, intervention duration, intensity, frequency, severity of depression, and age. Sensitivity analyses were conducted to evaluate outcome stability, while Begg’s test was employed to detect publication bias [25]. Statistical analyses were done by RevMan 5.4 and Stata 16.0.

Begg’s test is a rank correlation-based statistical method used to detect potential publication bias in meta-analyses. The principle involves assessing the correlation between the standard errors and effect sizes of the included studies. If significant bias is present, studies with smaller standard errors are more likely to report larger effect sizes, resulting in statistical significance in the test [25].

In practice, we performed Begg’s test using Stata 16.0 statistical software, with the significance level set at 0.05. Publication bias was determined by evaluating the p-value and Z-value from the test results. A p-value of less than 0.05 indicated significant publication bias, while a p-value of 0.05 or greater suggested no significant bias. Additionally, a funnel plot was created to visually assess the symmetry of the study results, providing further insight into the degree and direction of publication bias.

Results

Study selection

Our study retrieved 2304 related articles, including 220 articles from PubMed, 890 from Embase, 689 from Web of Science, and 505 from Cochrane. However, no relevant articles were found in CNKI. Two researchers (WH and BL) first removed duplicate articles (n = 467), then removed clearly unrelated articles (n = 1669) according to the abstracts or titles. Additionally, 21 articles were removed because of the inability to obtain the full text. Subsequently, the two researchers carried out an in-depth examination of the remaining articles and further excluded irrelevant studies (n = 120). Ultimately, 27 RCTs were included (Fig. 1).

Fig. 1
figure 1

PRISMA flowchart

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Trial characteristics

This study included 27 RCTs involving 2342 individuals with depression, comprising 1124 with mild depression, 884 with moderate depression, and 334 with severe depression. The experimental group consisted of 1,206 individuals, and while the control group comprised 1,136 individuals.

These investigations were performed in the Europe (n = 11), North America (n = 8), Asia (n = 7), and Oceania (n = 1). All articles were published in English.

The included studies provided explicit diagnostic criteria and specified the eligibility criteria. Complications were reported in 10 of the included studies involving 706 patients, including dialysis patients, chronic obstructive pulmonary disease (COPD), chronic low back pain, coronary artery disease, COVID-19, diabetes, multiple sclerosis, and breast cancer.

Exercise training frequencies ranged from 2 to 5 sessions/week, with the most frequent being thrice a week (n = 11). Training session durations varied from 30 to 90 min, with most investigations focusing on moderate sessions of 30 to 60 min. Interventions lasted from 3 to 48 weeks, with 12 studies at 12 weeks Various scales were used to evaluate depression, including BDI (n = 2),GDS (n = 6), CES-D (n = 2), HADS (n = 3), MADRS (n = 4), BDI-II (n = 3), PHQ-9 (n = 3), CSDD (n = 1), CGI(n = 1),CDRS(n = 1)and QIDS (n = 2) (Appendix 1).

Risk of bias

Figure 2A-B provided an overview of the risk of bias. All investigations revealed random allocation, with 20 studies explicitly mentioning allocation concealment, such as storing allocation numbers in sealed containers. Most studies had unclear blinding information for implementers and participants, resulting in a higher risk of bias since it was challenging to implement blinding for participants, personnel, and staff during the intervention process. 11 studies implemented blinding for outcome assessors, which minimized the risk of detection bias. 22 studies exhibited low risk of bias regarding data integrity, with 19 reporting complete data. The remaining studies provided detailed explanations for participants’ reasons for withdrawal or loss to follow-up and adopted appropriate methods to handle incomplete data. The bias in selective reporting was relatively low, as the results of 22 trials were analyzed and reported according to their methods sections or descriptions in public protocols. However, due to unclear details about the exercise interventions and limited sample sizes, there were other risks of bias in the seven studies, with the specific circumstances of these risks being unclear or high. For detailed information, please refer to Fig. 2B in Appendix 3.

Fig. 2
figure 2

Risk of bias of each study

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Results of meta-analysis

As shown in Figs. 3 and 27 studies involving 2,342 patients with depression reported the effects of resistance combined aerobic training on depression, using various depression scales for assessment, including BDI (n = 2),GDS (n = 6), CES-D (n = 2), HADS (n = 3), MADRS (n = 4), BDI-II (n = 3), PHQ-9 (n = 3), CSDD (n = 1), CGI(n = 1),CDRS(n = 1)and QIDS (n = 2). Due to the diversity of the scales used, a random effects model was applied to combine the effect sizes. The results showed high heterogeneity between the studies (I²=94.3%, P = 0.000), with a combined effect size of [SMD=−1.39, 95% CI=−1.80 to −0.98, P = 0.000], indicating that resistance training significantly improved depressive symptoms in patients with depression.

Caption: Compared to the control group, resistance combined aerobic training can significantly improve depressive symptoms in patients with depression (p < 0.000001).

Fig. 3
figure 3

Forest plot of resistance combined aerobic training effect on depression

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Subgroup analysis

Following a thorough screening, we performed a subgroup analysis by study region, age, depressive symptoms, frequency, training duration, weekly exercise time and supervision or non-supervision to explore the specific impacts of resistance combined aerobic training on depression.

Study area

The subgroup analysis included 27 studies from different regions, with 7 from Asia, 8 from North America, 1 from Oceania, and 11 from Europe. Using a random-effects model to pool effect sizes, the results indicated that combined resistance and aerobic training had a significant impact on depression patients in Asia, Oceania, and Europe (p = 0.000/p = 0.000/p = 0.000). However, for patients in North America, the intervention did not show a significant effect (p = 0.088). In terms of effect size, combined resistance and aerobic training was most effective for patients in Asia (SMD = −2.13, 95% CI = −3.21 to −1.05). (Fig. 4).

Caption: Compared to the control group, combined resistance and aerobic training significantly improved depressive symptoms in patients from Asia, Europe, and Oceania, but did not show a significant impact on patients from North America. In terms of effect size, the improvement was greatest for patients in Asia.

Fig. 4
figure 4

Forest plot of subgroup analyses stratified by study area

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Age

A total of 26 studies were included, involving 2,300 patients with depression: 261 young adults, 1,457 middle-aged adults, and 582 older adults. The results showed that resistance combined with aerobic training significantly improved depressive symptoms in middle-aged and older adults (p = 0.000/p = 0.000), but no significant improvement was observed in young adults (p = 0.052). In terms of effect size, the greatest improvement was seen in middle-aged adults (SMD=−1.52, 95% CI=−2.16, −0.87) (Fig. 5).

Fig. 5
figure 5

Forest plot of subgroup analyses stratified by age

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Depressive symptom

A total of 27 studies were included, with patients categorized as having mild, moderate, or severe depression based on depression scale scores. These studies involved 2,342 patients with depression: 1,124 with mild depression, 884 with moderate depression, and 334 with severe depression. The results of the random effects model showed that resistance combined with aerobic training significantly improved depressive symptoms in patients with mild, moderate, and severe depression (p = 0.000/p = 0.000/p = 0.000). In terms of effect size, the greatest improvement was observed in patients with moderate depression (SMD=−2.01, 95% CI=−2.95, −1.07). (Fig. 6).

Fig. 6
figure 6

Forest plot of subgroup analyses stratified by depression severity

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Training duration

A total of 27 studies, involving 2,342 patients with depression, were included. In the short term (4–8 weeks), 533 patients were studied, in the medium term (9–24 weeks), 1,662 patients, and in the long term (more than 24 weeks), 147 patients. The results of the random effects model showed that resistance combined with aerobic training significantly improved depressive symptoms in the short, medium, and long term (p = 0.013/p = 0.000/p = 0.000). In terms of effect size, the greatest improvement was observed in the medium term (9–24 weeks) (SMD=−1.61, 95% CI=−2.21, −1.00) (Fig. 7).

Fig. 7
figure 7

Forest plot of subgroup analyses stratified by training duration

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Intervention frequency

A total of 22 studies involving 1,831 patients with depression were included. The low-frequency group (1–2 times per week) comprised 165 patients, the moderate-frequency group (3–4 times per week) included 1,336 patients, and the high-frequency group (> 5 times per week) included 330 patients. Results from the random-effects model showed that moderate- and high-frequency combined resistance and aerobic training significantly improved depressive symptoms (p = 0.000/p = 0.017), whereas no significant improvement was observed in the low-frequency group (p = 0.166). In terms of effect size, moderate-frequency training had the greatest effect (SMD=−2.02, 95% CI=−2.79, −1.26) (Fig. 8).

Fig. 8
figure 8

Forest plot of subgroup analyses stratified by frequency of weekly interventions

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Weekly intervention duration

A total of 20 studies involving 1,749 patients with depression were included. Of these, 200 patients engaged in less than 120 min of combined resistance and aerobic training per week, 1,370 patients trained for 120–180 min per week, and 179 patients trained for more than 180 min per week. Results from the random-effects model showed that all three groups (< 120 min/week, 120–180 min/week, and > 180 min/week) experienced significant improvements in depressive symptoms (p = 0.001/p = 0.000/p = 0.000). In terms of effect size, the greatest improvement was observed in the group training for more than 180 min per week (SMD=−2.25, 95% CI=−3.34, −1.16) (Fig. 9).

Fig. 9
figure 9

Forest plot of subgroup analyses stratified by length of intervention per week

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Supervision or non-supervision

A total of 27 studies involving 2,342 patients with depression were included. Based on the reported supervision of the training interventions, patients were divided into supervised and unsupervised groups. A random-effects model was used to combine effect sizes, and the results showed that both supervised and unsupervised training interventions significantly improved depressive symptoms (p = 0.000/p = 0.027). However, in terms of effect size, supervised combined resistance and aerobic training had the greatest impact on improving depressive symptoms (SMD=−1.57, 95% CI=−2.07, −1.08). (Fig. 5). (Fig. 10).

Fig. 10
figure 10

Forest plot of subgroup analyses stratified by supervision or non-supervision

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Publication bias and sensitivity analysis

Publication bias

To assess publication bias, Begg’s test was employed. The result of Begg’s test was p = 1.9961, indicating that there is no significant publication bias in the included studies Table 1.

Table 1 Begg’s test
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Sensitivity analysis

Figure 11 illustrates the changes in meta-analysis effect sizes and their 95% confidence intervals after sequentially excluding individual studies. The vertical axis lists the names of the excluded studies, while the horizontal axis shows the estimated range of effect sizes. The circles in the figure represent the new effect size estimates after excluding each study, and the horizontal lines indicate the 95% confidence intervals of these estimates.

The results of the sensitivity analysis indicate that, following the sequential exclusion of individual studies, the overall effect size (Estimate) and its 95% confidence interval (CI) did not exhibit significant changes. This suggests that no single study had a decisive influence on the outcome of the meta-analysis. Furthermore, the effect size consistently remained within the negative range (−1.03 to −0.72) after the exclusion of any individual study, further supporting the robustness and consistency of the results.

To explore potential sources of bias, we conducted a focused analysis on studies whose exclusion resulted in the greatest variation in effect size. The analysis revealed that the exclusion of Mitchell 2014 [26], Joyce 2021 [27], Hallgren 2015 [28], Dieli-Conwright 2018 [29], and Henriksson 2022B [30] led to relatively larger fluctuations in effect size. We hypothesize that this variability may stem from the following factors:

Differences in depression assessment scales – The studies employed varying depression assessment tools, and discrepancies in scoring criteria and sensitivity across scales may have contributed to fluctuations in effect size.

Small sample sizes – Studies with smaller sample sizes are more susceptible to the influence of individual variability or outliers, thereby amplifying the instability of effect size estimates.

Variations in study design – Differences in intervention modalities, training frequency, and duration across studies may have led to inconsistencies in results.

Publication bias – Studies with statistically significant results are more likely to be published, whereas negative or null findings may remain unpublished, introducing bias that could distort the representativeness of the overall meta-analysis.

In summary, these factors likely explain the observed fluctuations in effect size following the exclusion of certain studies. This underscores the importance of methodological consistency and transparency in the design and reporting of future research to mitigate potential biases and enhance the reliability of conclusions.

Fig. 11
figure 11

Sensitivity analysis

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GRADE evidence grading

Table 2 presents the GRADE evidence rating for this meta-analysis, and the results indicate the following: In terms of risk of bias, the evidence was downgraded by one level, suggesting that methodological limitations in the included studies may affect the credibility of the results. For inconsistency, the evidence was also downgraded by one level, indicating significant heterogeneity among the study results. No downgrades were made for indirectness and imprecision, reflecting stability in these areas. The research objectives were directly aligned with the actual interventions, and the measurement outcomes were relatively precise. Similarly, publication bias was not downgraded, suggesting that its impact on the results was minimal. Considering the overall assessment across these dimensions, the final evidence quality was rated as low. This reflects certain limitations in the study outcomes, which necessitate cautious interpretation.

Table 2 GRADE Evidence Rating Table
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Summary of meta-analysis results

The results of the meta-analysis indicate that combined resistance and aerobic training can significantly improve symptoms in patients with depression. Subgroup analysis further highlights the influence of various factors on the intervention’s effectiveness. First, geographic differences suggest that combined resistance and aerobic training has a significant positive effect on patients with depression in Asia, Europe, and Oceania, but no significant effect on patients in North America. Second, age-related analysis shows that this form of exercise significantly improves depressive symptoms in middle-aged and older adults, but does not show notable effects in younger individuals. Third, the training was effective in improving symptoms across mild, moderate, and severe depression, with the most significant improvement observed in patients with moderate depression. Fourth, regarding intervention duration, short-term (4–8 weeks), medium-term (9–24 weeks), and long-term (> 24 weeks) programs all showed significant improvements, with the largest effect size seen in medium-term interventions. Fifth, analysis of training frequency shows that moderate-frequency (3–4 times per week) and high-frequency (> 5 times per week) programs significantly improved depressive symptoms, while low-frequency (1–2 times per week) training did not produce significant improvements. The greatest effect size was found with moderate-frequency programs. Sixth, the total amount of training also influenced the results: less than 120 min per week, 120–180 min per week, and more than 180 min per week of exercise all led to significant improvements, with the greatest effect size observed in those training more than 180 min per week. Seventh, both supervised and unsupervised training interventions resulted in significant improvements, but supervised programs were more effective.

To address the high level of heterogeneity observed in the studies included in this research, we conducted seven subgroup analyses to explore potential sources of heterogeneity. The analyses examined factors such as study region, participant age, severity of depressive symptoms, training frequency, duration of training, total weekly exercise time, and whether the training was supervised. The results indicated that none of these factors significantly explained the heterogeneity between studies.

Therefore, we hypothesize that the primary source of the observed heterogeneity may stem from differences in the depression assessment scales used across studies. Variations in the scoring criteria of these scales could contribute to discrepancies in results. Additionally, differences in total training volume may have further contributed to the heterogeneity to some extent.

To mitigate the impact of heterogeneity on the study outcomes, we employed standardized mean difference (SMD) and random-effects models (REM) to ensure the stability and reliability of our conclusions.

Discussion

The results of this meta-analysis indicate that combined resistance and aerobic training can significantly improve the symptoms of patients with depression, which aligns with findings from existing literature. Numerous studies have confirmed that exercise interventions, as a non-pharmacological treatment approach, have a positive therapeutic effect on depression. For example, research by Mura [31] and Schuch [32] has demonstrated that exercise interventions can effectively enhance the emotional state of patients with depression, alleviating symptoms while promoting overall health improvements. Specifically, resistance training can increase muscle strength, improve posture, and enhance physical function, thereby boosting patients’ self-confidence and self-efficacy. This physical improvement not only aids in the psychological recovery of patients with depression but also helps them establish a more positive self-perception, alleviating low self-esteem and negative emotions [13].

Meanwhile, aerobic training primarily improves mood by regulating neurotransmitter levels in the brain. Studies by Gupta [33] and Wipfli [34] have shown that aerobic exercise can significantly increase the secretion of neurotransmitters like serotonin and dopamine, which are closely associated with mood regulation and maintenance. By elevating the levels of these “feel-good” chemicals in the brain, aerobic training can help patients with depression improve their mood, reduce feelings of anxiety, and enhance their ability to cope with stress.

Therefore, the combination of resistance and aerobic training can more comprehensively improve the physical and mental health of patients with depression. The Potential complementary mechanism are evident not only in physical enhancements like increased strength, fitness, and endurance but also in helping patients better regulate their mood and alleviate anxiety through neurotransmitter modulation. This dual approach to intervention is poised to become an indispensable treatment method in the rehabilitation process for patients with depression. Our study also conducted subgroup analyses of various factors to deeply explore the key elements affecting the intervention’s effectiveness, providing valuable references for clinical practice and personalized treatment.

  • 1. Impact of geographic regional differences

The results of the meta-analysis indicate that combined resistance and aerobic training demonstrated significant effects among patients in Asia, Europe, and Oceania, but similar results were not observed in North American patients. This discrepancy may be profoundly influenced by cultural and social factors. Research suggests that responses to treatment methods can vary significantly across different cultural contexts [35, 36]. For example, the social cultures in Asia and Europe place greater emphasis on collective activities and external social support, and patients with depression are generally more willing to participate in organized group exercise interventions [37]. This form of participation may enhance adherence to exercise and promote sustained engagement, thereby improving treatment outcomes for patients with depression.

In contrast, North American culture tends to prioritize individualism, and patients with depression may experience greater social isolation, resulting in lower participation rates in exercise interventions [38, 39]. Additionally, economic conditions and differences in healthcare systems across North America may further affect the accessibility and efficacy of exercise interventions. Studies have shown that in environments with heavier financial burdens or limited health insurance coverage, patients are more likely to opt for pharmacological treatments, which are more cost-effective, rather than long-term exercise intervention programs that require consistent effort [40, 41].

Furthermore, societal awareness of mental health issues and the clinical adoption of exercise interventions may be relatively lower in North America, limiting the promotion and implementation of exercise-based therapies [42]. Variations in healthcare systems’ support for exercise interventions may also affect patients’ ability to access professional exercise guidance and long-term treatment. To address this regional discrepancy, future research should focus on the potential influence of cultural contexts, social support systems, and healthcare coverage on the effectiveness of exercise interventions. Exploring ways to optimize exercise-based interventions in diverse social and cultural environments can help provide more tailored non-pharmacological treatments for depression.

  • 2. Influence of age on intervention effectiveness

Combined resistance and aerobic training has shown significant improvement in depression among middle-aged and elderly individuals, whereas its effect on younger people is relatively weaker. The differences related to age may be associated with life stress, social roles, and physical health status [43]. Middle-aged and elderly people often face more health issues, including chronic diseases, physical decline, and changes in social roles; these factors may make them more susceptible to depression [44]. Exercise training can enhance the physical health of these patients, thereby indirectly alleviating their depressive symptoms [45]. In contrast, for young people, the causes of depression may be more related to external factors such as social pressure and academic stress; these factors may limit the effectiveness of exercise interventions [46, 47]。Research has also shown that sleep is a critical factor influencing mental health. Studies using near-infrared spectroscopy have demonstrated associations between sleep duration and brain function [48, 49]. Furthermore, population-based studies have revealed potential nonlinear relationships between physical activity and health indicators across different sleep duration groups [50]. This finding may partially explain the moderating effect of age on exercise interventions.

Therefore, in future exercise interventions targeting young patients with depression, it may be necessary to combine other psychosocial intervention methods to improve treatment outcomes.

  • 3. Effect of depression severity

The meta-analysis further demonstrates that combined resistance and aerobic training significantly improves depressive symptoms across patients of varying severity levels, with the most substantial effect observed in those with moderate depression. This outcome may be related to patients’ functional status and adherence [51, 52]. Although patients with moderate depression exhibit noticeable symptoms, they typically can maintain certain daily functions, making them more likely to actively participate in exercise interventions and benefit from them [53]. In contrast, while exercise interventions remain effective for patients with severe depression, their intense symptoms may limit their ability to engage in physical activities, thereby impacting the effectiveness of the intervention [54]. Additionally, severe depression is accompanied by more profound psychological distress; relying solely on exercise interventions may not be sufficient to significantly alleviate their symptoms. Comprehensive intervention methods combining medication and psychotherapy are required [4].

  • 4. Effects of intervention period, frequency, intensity, and weekly intervention duration

This study found that combined resistance and aerobic training significantly improved depressive symptoms across all intervention periods—short-term (4–8 weeks), medium-term (9–24 weeks), and long-term (over 24 weeks)—with the medium-term (9–24 weeks) intervention showing the best effect. This result is consistent with previous research [51]. Studies indicate that although short-term exercise interventions can rapidly alleviate depressive symptoms, their effects tend to diminish after the intervention ends [51]. Medium-term interventions not only provide significant improvement but also have higher adherence; patients are more likely to stick to longer intervention plans, thereby consolidating the benefits of exercise on depressive symptoms [55]. While long-term interventions are effective, decreased patient adherence over time makes it more challenging to maintain a high volume of exercise in the long run, which may explain why long-term interventions are less effective than medium-term ones [56, 57].

Regarding intervention duration, our study found that training for more than 180 min per week yielded the best results, which aligns with the World Health Organization’s recommendation of 150–300 min of exercise per week [58]. Longer exercise durations can more effectively promote the release of neurotransmitters, especially endorphins and serotonin, leading to more significant improvements in depressive symptoms [59, 60].

Furthermore, research shows that a moderate training frequency (3–4 times per week) can significantly improve depressive symptoms. While both high frequency (> 5 times per week) and low frequency (1–2 times per week) interventions also improve symptoms, the effect size is greatest with moderate training frequency. This is consistent with the views of Rethorst et al., who suggested that the frequency and intensity of exercise interventions should be at moderate levels [61]. Excessive exercise frequency may lead to fatigue or overtraining, negatively impacting mental health. Conversely, too low a frequency may be insufficient to elicit physiological and psychological adaptations, resulting in less noticeable intervention effects [32]. Therefore, for patients with depression, a reasonable design of exercise frequency is crucial.

  • 5. Differences in the effects of supervised and unsupervised training

Supervised exercise interventions are significantly more effective than unsupervised ones, which is consistent with previous research [62, 63]. This discrepancy may be attributed to multiple mechanisms. Supervised interventions are typically conducted under the guidance of professionals, providing patients with timely feedback and psychological support, which helps maintain their exercise motivation and participation while ensuring the standardization and safety of the training process [64].

In contrast, while unsupervised interventions offer greater flexibility, the absence of external supervision and technical support makes it easier for patients to experience reduced adherence or perform exercises incorrectly, ultimately affecting treatment outcomes. Studies have shown that patients are more likely to discontinue training due to a lack of motivation and self-discipline in the absence of supervision, leading to diminished intervention effectiveness [65]. Additionally, supervised interventions can promptly detect emotional fluctuations during exercise and provide necessary psychological adjustments and encouragement, highlighting the critical role of social support in depression recovery.

Research also suggests that group participation and social support significantly enhance exercise adherence and treatment outcomes in patients with depression [66]. The benefits of supervised interventions extend beyond technical guidance by offering multidimensional support at both psychological and social levels. By fostering connections with trainers or peers, patients experience greater social interaction and emotional support, which enhances self-efficacy and reduces feelings of isolation and dropout risk during the training process [67].

Future research and practice should further explore how remote supervision or peer support mechanisms can be incorporated into unsupervised interventions, such as through digital platforms or virtual coaching, to improve patient engagement and adherence. This hybrid intervention approach may become a key direction for exercise-based depression interventions, addressing the shortcomings of unsupervised programs and enhancing overall effectiveness.

  • 6. Compare with existing research

The results of this study indicate that combined resistance and aerobic training can significantly improve the mental health and physical function of patients with depression, aligning with findings from recent related research. In recent years, a growing body of evidence has demonstrated the positive effects of combined resistance and aerobic training on multiple health indicators, including body composition, mental health, physical performance, and cardiometabolic health.

For example, a recent systematic review highlighted that combined resistance and aerobic training not only enhances mental health but also significantly reduces body fat percentage and increases muscle mass [68]. Another study further emphasized the role of multimodal exercise interventions in alleviating symptoms of anxiety and depression, while also promoting improvements in skeletal muscle mass and insulin sensitivity [69].

Additionally, a study on adolescent populations found that regular participation in combined resistance and aerobic training led to significant improvements in both body composition and mental health. This suggests that diverse exercise modalities can have beneficial effects across different age groups [69].

Among middle-aged and older adults, research has confirmed that multimodal training enhances physical function and metabolic health, particularly in reducing the risk of cardiovascular disease and regulating blood glucose levels [68]. This is consistent with the improvements observed in mental health and physical fitness among depressed patients in the present study.

Moreover, a meta-analysis indicated that combined training yields greater improvements in mental health and quality of life compared to single-mode exercise interventions. It also showed more pronounced benefits in reducing inflammatory markers and enhancing cardiovascular function [70]. These findings further support the advantages of combined training as an intervention for depression, reinforcing the results observed in this study.

Limitations

This study had several limitations. Firstly, although we employed REM to reduce the impact of heterogeneity, differences in study designs, intervention protocols, and outcome measurement scales among the studies might have interfered with the results to some extent. Secondly, the limited sample sizes of certain included studies may have reduced the statistical power of the findings. Moreover, while this study explored the effects of training frequency, training duration, and weekly intervention duration on the improvement of depressive symptoms, subgroup analysis of total work performed (Total Work Performed = Frequency × Training Duration × Weekly Intervention Duration) was not conducted due to space and data limitations. Future research should systematically evaluate the role of total work performed, investigating how it influences the psychological and physiological responses of patients with depression through varying intervention intensities and durations, thereby optimizing exercise intervention protocols.

Future directions

In future research, we recommend designing personalized training programs tailored to the characteristics of different populations, with a particular focus on the following aspects:

Customized Training Plans: Considering the varying responses to exercise interventions based on gender, age, and severity of depression, future studies should aim to develop individualized training plans. For example, moderate- to low-intensity resistance combined with aerobic training programs could be designed for older adults to enhance adherence and ensure safety, while younger populations might benefit from incorporating higher-intensity resistance combined with aerobic training to improve physical fitness and emotional regulation.

Optimization of Medium- to Long-Term Interventions: Research has shown that medium-term interventions (9–24 weeks) yield the best results; however, strategies for maintaining long-term effects (> 24 weeks) require further investigation. Future studies should focus on optimizing the sustainability of long-term exercise interventions by adjusting intervention frequency, increasing supervision levels, and incorporating remote guidance to maintain patient engagement and intervention efficacy.

Diversification and Integration of Interventions: Future research should explore different combinations of resistance and aerobic training, analyzing the effects of varying intensities and durations to identify the most effective intervention models for alleviating depressive symptoms.

Incorporating Psychological and Social Support: Studies should also examine how to integrate greater social support and psychological elements into exercise interventions. This may include group training, peer supervision, or digital remote guidance to enhance patient engagement and long-term adherence.

By addressing these aspects, future research can contribute to the development of more comprehensive and effective non-pharmacological interventions for depression, ultimately improving clinical outcomes and enhancing the overall well-being of patients.

Conclusion

Overall, this meta-analysis demonstrates that combined resistance and aerobic training significantly improves depressive symptoms, with the most pronounced effects observed in middle-aged and elderly patients and those with moderate depression. In terms of training intensity and volume, the optimal results were achieved with medium-duration interventions (9–24 weeks), moderate frequency (3–4 times per week), more than 180 min of training per week, and supervised sessions. This study provides important references for clinical practice, supporting combined resistance and aerobic training as an effective intervention for treating depression. Future research should continue to optimize intervention strategies to ensure the maximal clinical efficacy of this non-pharmacological treatment.

Data availability

All data and material reported in this review and meta-analysis were from peer-reviewed publications. The datasets supporting the conclusions of this article are included within the article and its additional files.

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    Hai Wang, Qinzheng Liu & Yingxu Pan

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HW: Data curation, Formal Analysis, Methodology, Supervision, Writing–original draft, Writing–review and editing. XP: Data curation, Formal Analysis, Writing–review and editing. LQ: Data curation, Formal Analysis, Methodology, Writing–review and editing. XP: Formal Analysis, Supervision, Validation, Writing–review and editing.

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Wang, H., Liu, Q. & Pan, Y. Impact of combiner aerobic and resistance training on depression: a systematic review and meta-analysis of randomized controlled trials. BMC Sports Sci Med Rehabil 17, 10 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13102-025-01058-w

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BMC Sports Science, Medicine and Rehabilitation

ISSN: 2052-1847

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