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Abstract

Mindfulness-based stress reduction (MBSR) is becoming more and more popular in treating depressive symptoms, but previous studies have come to different conclusions. This meta-analysis aimed to evaluate the effectiveness of MBSR in alleviating depressive symptoms. A systematic search was conducted across seven electronic databases: Scopus, Web of Science, Embase, the Cochrane Library, PubMed, PsycINFO, and Google Scholar. Meta-analytic methods were applied by using random-effect models. The quality was assessed with the Cochrane Handbook for Systematic Reviews of Interventions. Thirty-two randomized controlled trials (RCTs) and 37 independent effect sizes were eligible for the meta-analysis. The meta-analysis revealed that MBSR showed significant improvements on depressive symptoms compared to the control group, and the intervention effects were more significant for people with major depression disorder. However, neither cultural background nor sample origin had significant effects on the results of intervention. In addition, there was no publication bias in the meta-analysis, and the sensitivity analysis results indicated that the result was reliable. Findings suggests that MBSR can improve depressive symptoms, and future studies should consider the effects of different levels of depression to improve the intervention benefits of MBSR.

Keywords

depressive symptom mindfulness-based stress reduction meta-analysis

Introduction

Depression often occurs together with other negative consequences in many areas of psychosocial function, such as career performance, interpersonal function, and quality of life (Clayborne et al., 2019). Furthermore, untreated depression may extend to major depression (Mullen, 2018). However, less than 50% of young people with mental disorders have received specialized treatment services (Ye & Bapuji, 2014). Thus, it is imperative to strengthen effective intervention for depressive symptoms, to guide and reduce the risk of individual depressive symptoms.

Currently, guidelines and clinical studies in many countries recommend psychotherapy as the primary treatment for depression (Cuijpers et al., 2016; Hopkins et al., 2016). Studies found that Mindfulness-based Stress Reduction (MBSR) has been widely applied in relieving depressive symptoms (Bohlmeijer et al., 2010; Li & Bressington, 2019). MBSR is a group-based physical and mental intervention program, including mindfulness breathing, sitting meditation, body scanning, mindfulness yoga, mindfulness walking, and other physical and mental exercises (Kabat-Zinn, 1990). It is used by many healthcare agencies and consulting agencies around the world. Besides, MBSR is a standard course intervention program from 2 to 2.5 h. a week. After 6–7 weeks, there will be a full-day course, which will focus on reviewing what has been practiced (Vibe et al., 2017). MBSR can not only effectively reduce depressive symptoms in healthy individuals, but also effectively relieve depressive symptoms in clinical patients to promote the recovery of their diseases (Chen et al., 2020; Sharma et al., 2015). However, the conclusions of previous studies on the intervention effect of MBSR on depressive symptoms were inconsistent (Bohlmeijer et al., 2010; Hofmann et al., 2010; Young & Baime, 2010). Therefore, we speculate that the intervention effect of MBSR on depressive symptoms is likely to be affected by other moderating variables.

First, the sample origin: Previous studies suggested that MBSR can effectively alleviate depression in healthy adolescents and the elderly (Bluth et al., 2016; Jansen et al., 2017; Li & Bressington, 2019). It can also improve the depressive symptoms of patients with different clinical diseases (such as cancer, maintenance hemodialysis, etc.) (Yang et al., 2020, 2022). Meta-analysis has shown that the intervention effect of MBSR on depressive symptoms in patients with clinical diseases is better than that in non-clinical individuals (Zoogman et al., 2015). Unfortunately, the previous study only included English literature, and the external validity and stability of their conclusions were low. Therefore, we divided the included participants into clinical and non-clinical groups under the background of Eastern and Western culture, and explored the moderating effect in a sample origin.

Second, the level of depression symptom: Previous studies suggested that MBSR was more effective for individuals with low levels of depression (Gallegos et al., 2013). However, one meta-analysis found that the higher the level of depression, the better the intervention effect of MBSR (Chi et al., 2018). To explore the moderating effect of the level of depression, we divided the participants of no depression (ND), mild to moderate depression (MMD), and major depression disorder (MDD) according to the evaluation of different depression scale.

Finally, the cultural background. Mindfulness was conceived in the Eastern Buddhist culture and developed rapidly in the field of Western clinical psychology (Schmidt et al., 2011). Different cultural beliefs and behavioral patterns between East and West profoundly influence patients’ treatment response to depression, compliance, and expectations of interaction with clinicians (Chen et al., 2009). In addition, the intervention effect of MBSR on depressive symptoms of breast cancer patients is greater than in the East (d = 0.58) (Zainal et al., 2013; Zhang et al., 2018). However, the impact of culture on the effects of MBSR intervention remains unclear. Therefore, we explored the moderating effect by including relevant studies in Eastern and Western cultural backgrounds.

It is noteworthy that previous meta-analyses have examined the efficacy of MBSR in the treatment of depressive symptoms. Li and Bressington (2019) included six studies and found that MBSR had a significant intervention effect on depressive symptoms in older adults. However, it included fewer studies, and the conclusions are of low application value and stability. Hofmann et al. (2010) found that MBSR was more effective treating depressive symptoms in people with depressive disorders than other clinical conditions. However, they included mindfulness-based cognition therapy (MBCT) and did not explore the specific effects of MBSR on depressive symptoms. Zainal et al. (2013) found that MBSR significantly alleviated depressive symptoms in breast cancer patients. Yang et al. (2020) found that MBSR significantly alleviated depressive symptoms in patients with maintenance hemodialysis. However, these were only clinical studies. In addition, although previous meta-analyses have explored the effects of baseline depression on the effectiveness of MBSR, it was only for teenagers aged 18–25 (Chi et al., 2018). Importantly, no researchers have explored the effects of Eastern and Western cultural backgrounds on the intervention effects of MBSR.

Therefore, we aim to explore: (a) Effect size: What is the overall effect of MBSR with clinical and non-clinical populations (clinical refers to patients with physical disease, non-clinical refers to samples without physical disease)? (b) Treatment moderators: In what sample origin (clinical vs. non-clinical), level of depression (MDD, MMD, or ND), or cultural background (East vs. West) is MBSR most helpful?

Methods

Selection of studies

We searched seven electronic databases from 2010 to 2020 for studies that were written in English. The databases were: Scopus, Web of Science, Embase, the Cochrane Library, PubMed, PsycINFO, and Google Scholar. We used the following search terms: mindfulness, mindfulness meditation, mindfulness-based stress reduction combined with depression, depressive mood, and depressive symptoms. In addition, the citations of recent meta-analyses on MBSR with depression symptoms were manually searched for other potential qualified.

Inclusion criteria

We included primary studies if they were evaluated according to: (1) randomized controlled trials that explored the effect of MBSR intervention on depressive symptoms; (2) participants including clinical patients (cancer, chronic pain, coronary heart disease, etc.) and non-clinical individuals; (3) the intervention group was designed to perform MBSR according to Kabat-Zinn's manual (1990); (4) appearing in journals.

Exclusion criteria

Studies were excluded if they were: (1) non-RCT studies such as single-group design; (2) studies that excluded MBSR in combination with other interventions (such as MBSR and BCT combination) or online interventions; (3) conference papers and dissertations that have not been peer-reviewed.

Data extraction

The literature feature codes of this study include the first author and the year of publication, country, sample origin, sample size, age, research settings and implementer, intervention, control group type, MBSR duration, dropout, follow-up time, and outcome measure. The differences in the data extraction process are discussed by two authors to ensure the accuracy of the data.

Risk of bias assessment

We used the Cochrane Collaboration's risk-of-bias tool as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins & Green, 2008) to evaluate bias risk and assess the quality of various studies. The tool includes assessing the risk of bias for each study in multiple areas, including high, low, or unclear degrees of bias: randomization generation, allocation concealment, the blindness of participants and personnel, blindness of outcome assessment, incomplete outcome data, selective reporting, and other risks of bias. Based on the above seven aspects, the results of bias risk assessment were summarized into RevMan 5.3 to generate a summary table of bias risk assessment.

Statistical analysis

We used Review Manager (version 5.3) (The Cochrane Collaboration, Copenhagen, Denmark) and Stata software (version 14) (Stata-Corp, Texas, USA) in this meta-analysis. We used standardized mean difference (SMD) Cohen's d with 95% confidence interval (CIs) to calculate the effects of continuous data. Heterogeneity was examined by I² statistics, wherein I² refers to the proportion of the variance between various studies in the total variance (I² = 25%, 50%, 75%, and the heterogeneity is low, medium, and high, respectively) (Higgins et al., 2003). Nevertheless, we will only perform a random-effects model to calculate all pooled results regardless of actual level of heterogeneity across studies because substantial variations in population, interventions, and outcome measures are inevitable.

Finally, the funnel plot, Duval and Tweedle's trim and fill method, Begg and Mazumdar rank correlation, Egger's regression were all used to estimate the publication bias. When funnel plots showed that each study was evenly distributed on both sides of the total effect size, it suggests that there was no publication bias (Egger et al., 1997). The funnel plot trim-and-fill method described by Duval and Tweedie (2000) was used to adjust for possible bias in the overall effect size by accounting for effect sizes from the estimated number of missing studies. The Begg and Mazumdar test computes the rank–order correlation (Kendall's τ) between the standard treatment effect and variances (standard error, which is primarily affected by sample size). If this test shows no significant results (P > 0.05; one-tailed), it suggests no publication bias (Begg & Mazumdar, 1994). When the intercept obtained by Egger's regression test was close to 0 and P > 0.05 (one-tailed), it suggests no publication bias.

Results

Literature search and screening

A total of 488 records were obtained for the online database search. After the removal of duplicates, 271 studies remained, as 139 of them were excluded at the title and abstract screening stages. The remain 94 studies were then included in the full-text screening process. Finally, 32 studies remained after this process and were put into the meta-analysis. Thirty-two studies (RCTs) (Bluth et al., 2016; Bränström et al., 2012; Chen et al., 2013, 2017; Duncan et al., 2012; Ellis et al., 2018; Fogarty et al., 2019; Freedenberg et al., 2017; Gayner et al., 2012; Gross et al., 2010; Hartmann et al., 2012; Hazlett-Stevens & Oren, 2017; Hoffman et al., 2012; Hou et al., 2013; Jansen et al., 2017; Jiao et al., 2018; la Cour & Petersen, 2015; Lau & Hue, 2011; Liu et al., 2019; Mallya & Fiocco, 2016, 2019; Moss et al., 2014; Moynihan et al., 2013; Omidi et al., 2013; Parswani et al., 2013; Perez-Aranda et al., 2019; Reich et al., 2017; Schmidt et al., 2011; Shomaker et al., 2017; Song & Lindquist, 2015; Whitebird et al., 2013; Zhang et al., 2018) with a total of 3,238 participants were included in this meta-analysis. Of these participants, the age was from 14.50 to 83.30, with 15.63% for adolescents (14–18), 71.87% for adults (18–65), and 12.50% for the elderly (≥65). The process of literature screening is shown in Figure 1.

Figure 1.

Flow diagram showing the process of study selection.

Characteristics of the studies

The characteristics of the 32 included studies are shown in Table 1. The years of publication range from 2010 to 2020.

Table 1.

Characteristics of the studies included in the meta-analysis

Study	Country	Sample origin	Sample size(n)(EG/CG)	Age, M(SD) or range (EG/CG)	Intervention	Control Group	MBSR duration	Follow-up time	Dropout rate	Outcome measure
Bluth et al. (2016)	USA	NCP	27(14/13)	16.80 ± 1.30/17.20 ±1.10	L2B	SBC	11-week	None	L2B:0 SBC: 30.77	SMFQ
Bränström et al. (2012)	Sweden	CP	71(32/39)	51.80 ± 9.86	MTP	Waitlist	8-week	6-month	MTP:21.9 Waitlist:10.3	HADS
Chen et al. (2013)	China	NCP	60(30/30)	19.4 ± 0.85/19.7 ± 0.88	MMT	Waitlist	7-day	None	0	SDS
Chen et al. (2017)	China	CP	232(80/81/71)	30.70 ± 5.5/31.1 ± 6.50/29.7 ± 5.6	MBSR	Waitlist HC	8-week	None	MBSR:5 Waitlist:7.4 HC:0	SDS
Duncan et al. (2012)	USA	CP	76(40/36)	47.90 ± 6.80/48.20 ± 9.10	MBSR	TAU	8-week	6-month	MBSR: 15 TAU:13.89	BDI
Ellis et al. (2018)	USA	CP	48(16/16/16)	18.00 ± 1.50/18.10 ± 1.3/18.50 ± 1.60	MM	CBSM/DS	9-week	3-month	MM:18.75 CBSM:25 DS:18.75	CES-D
Fogarty et al. (2019)	New Zealand	CP	51(26/25)	55 ± 13/52 ± 12	MBSR	TAU	8-week	3-month	MBSR :19.23 TAU :16	HADS
Freedenberg et al. (2017)	USA	CP	52(30/22)	15.10 ± 1.80/14.50 ± 1.60	MMT	VOG	6-week	None	MMT: 13.33 VOG: 9.09	HADS
Gayner et al. (2012)	Canada	CP	117(78/39)	42.90 ± 7.10/45.50 ± 6.70	MBSR	TAU	8-week	6-month	MBSR : 39.74 TAU : 10.26	HADS
Gross et al. (2010)	USA	CP	138(72/66)	55.00 ± 11.30/52.00 ± 10.40	MBSR	Waitlist	8-week	6-month	MBSR:6.94 Waitlist:9.09	CES-D
Hartmann et al. (2012)	Germany	CP	110(53/57)	58.7 ± 7.4/59.3 ± 7.8	MM	TAU	6-month	1-year	MBSR:1.89 Waitlist:10.53	PHQ-9
Hazlett-Stevens and Oren (2017)	United States	NCP	92(47/45)	22.1 ± 4.70/22.1 ± 4.70	MBSR	Waitlist	10-week	None	MBSR :47 Waitlist:40	DASS-21
Hoffman et al. (2012)	UK	CP	229(114/115)	49.00 ± 9.26/50.10 ± 9.14	MBSR	Waitlist	8-week	None	MBSR :9.65 Waitlist:3.48	POMS
Hou et al. (2013)	China	NCP	141(70/71)	57.90 ± 8.49/57.08 ± 9.21	MBSR	SHHE	8-week	3-month	MBSR :12.9 SHHE:26.8	CES-D
Jansen et al. (2017)	Germany	NCP	66(25/19/22)	63.29 ± 8.53/62.57 ± 4.19/65.24 ± 4.66	MBSR	Karate/Waitlist	8-week	None	MBSR: 21.05 karate: 8 Waitlist : 22.73	HADS
Jiao et al. (2018)	China	NCP	100(50/50)	29.50 ± 7.10	MBSR	Waitlist	8-week	None	MBSR : 4 Waitlist: 6	SDS
la Cour and Petersen (2015)	Denmark	CP	109(54/55)	46.52 ± 12.42/48.84 ± 12.20	MBSR	Waitlist	8-week	6-month	MBSR : 40 25.93	HADS
Lau and Hue (2011)	China	NCP	48(24/24)	15.83	MM	Waitlist	6-week	None	0	DASS-21
Liu et al. (2019)	China	CP	120(60/60	43.32 ± 10.99/42.38 ± 12.60	MBSR	TAU	8-week	None	MBSR: 18.33 TAU: 11.67	SDS
Mallya and Fiocco (2015)	Canada	NCP	97(/57/40)	68.84 ± 4.64/69.68 ± 4.87	MBSR	R&R	8-week	None	MBSR: 8.77 R&R: 30	GDS
Mallya and Fiocco (2019)	Canada	NCP	57(33/24)	64.18 ± 6.69/69.13 ± 7.86	MBSR	PS	8-week	None	MBSR:30.30 PS:16.67	CES-D
Moss et al. (2014)	USA	NCP	39(20/19)	83.30 ± 5.30/80.60 ± 8.90	MBSR	Waitlist	8-week	None	MBSR :20 Waitlist:0	BSI-18
Moynihan et al. (2013)	US	CP.	208(105/103)	73.30 ± 6.70/73.60 ± 6.70	MBSR	Waitlist	8-week	6-month	MBSR :20 Waitlist:0	CES-D
Omidi et al. (2013)	Iran	CP	62(31/31)	35–49	MBSR	TAU	8-week	None	MBSR:0 TAU:0	BRUMS
Parswani et al. (2013)	New Zealand	CP	30(15/15)	47.26 ± 12.15/50.60 ± 8.21	MBSR	TAU	8-week	3-month	MBSR: 25 TAU: 66.67	HADS
Perez-Aranda et al. (2019)	Spain	CP	150(75/75/)	52.96 ± 7.98/54.21 ± 7.41/52.65 ± 8.52	MM	FibroQoL/TAU	8-week	12-month	MM: 34.67 FibroQoL : 32 TAU: 34.67	HADS
Reich et al. (2017)	USA	CP	322(167/155)	56.6	MBSR	TAU	6-week	3-month	MBSR : 7.19 TAU : 4.52	CES-D
Schmidt et al. (2011)	US	CP	177(59/59/59)	53.40 ± 8.70/ 52.3 ± 10.9//51.90 ± 9.20	MBSR	PMR/Waitlist	8-week	None	MBSR: 10.17 PMR: 5.08 Waitlist: 0	CES-D
Shomaker et al. (2017)	US	CP.	33(17/16)	15.01 ± 1.68/14.97 ± 1.75	L2B	CBP	6-week	6-month	L2B: 29.41 CBP:6	CES-D
Song and Lindquist (2015)	Korea	NCP	50(25/25)	19.60 ± 1.70/19.50 ± 2.00	MBSR	Waitlist	8-week	None	MBSR : 16 Waitlist: 8	DASS-21
Whitebird et al. (2013)	US	NCP	78(38/40)	57.20 ± 9.60/56.40 ± 10.2	MBSR	CCES	8-week	None	0	CES-D
Zhang et al. (2018)	China	CP	64(32/32)	48.88 ± 5.36 / 46.66 ± 5.46	MBSR	TAU	6-week	None	MBSR : 6.25 TAU: 12.5	SDS

Note: CP: Clinical patients; NCP: Non-clinical participants; TAU: Treatment as usual; MBSR: Mindfulness-based stress reduction; L2B: Learning to breathe; SBC: Substance abuse class; MTP: Mindfulness training program; MM: Modified MBSR; CBSM: Cognitive-behavioral stress management; VOG: Video online group; SHHE: Self-help health education; R&R: Reading and relax; PS: Psychoeducation-social support group; KT: Karate training; CBP: Cognitive behavioral program; PMR: Progressive muscle relaxation training; HC: Healthy control; DS: Diabetes support group; CCES: Community caregiver education and social support; SMFQ: The Short Mood and Feelings Questionnaire; HADS: Hospital Anxiety and Depression Scale; SDS: Self-Rating Depression Scale; BDI: Beck Depression Inventory; CES-D: Center for Epidemiologic Studies Depression Scale; PHQ-9: Patient Health Questionnaire; DASS-21: Depression Anxiety Stress Scales-21; POMS: Profile of Mood State; GDS: The Geriatric Depression Scale; BSI-18: The Brief Symptom Inventory–18; BRUMS: 2-Inventory of mood status.

Risk of bias assessment

As shown in Figure 2, most included RCTs were categorized as being at low risk of bias with respect to randomization sequence generation, incomplete outcome data, selective reporting, and other risks of bias (K = 29, 90.63%, K = 26, 81.25%, K = 32, 100%, K = 30, 93.75%, respectively). Allocation concealment and blinding of outcome assessment often went unreported (K = 13, 40.63% and K = 14, 43.75%, respectively) in the included studies. Risk of bias was high for blinding of participants/personnel in all included studies (K = 14, 43.75%).

Figure 2.

Risk of bias graph of authors’ judgments as percentages across all included studies.

Main findings

The 32 studies involved 1,589 participants in the MBSR intervention group and 1,649 participants in the control group. Due to the relatively high heterogeneity among the included studies (I² = 81.80%; P < 0.001), a random-effect model was selected for quantitative synthesis. Overall, the meta-analysis revealed a significant difference between the MBSR intervention and control groups in alleviating depression symptoms (SMD = −0.40, 95% CI −0.56 to −0.24, P < 0.001). The forest plot of the meta-analysis is shown in Figure 3.

Figure 3.

Forest plot of MBSR intervention versus conventional control in alleviating depression symptoms.

Subgroup analyses

The sample origin

As the results of the heterogeneity test were significant, it suggested that there might be moderating variables playing an important potential moderating role on the effect size, so subgroup analysis was needed to further test the moderating effect. Moderator analysis showed no significant difference in the depressive symptoms between studies with clinical patients (CP) and studies with non-clinical participants (NCP) (P = 0.55). There was a significant difference between the MBSR group and the control group in clinical patients (SMD = −0.44, 95% CI −0.65 to −0.22, P < 0.001) and non-clinical participants (SMD = −0.33, 95%CI−0.59 to −0.08, P < 0.001). The results showed that MBSR had a significant effect on depressive symptoms in both clinical patients and non-clinical individuals, and the intervention was not affected by the sample origin (as illustrated in Figure 4a).

Figure 4a.

Subgroup analyses of depression outcome (sample origin).

The level of depressive symptom

According to the criteria of the depression scale, the depressive symptoms of the participants were divided into MDD, MMD, and ND. Moderator analysis showed a significant difference in the depressive symptoms between studies with levels of depressive symptoms (P = 0.01), MBSR was more effective on MDD (SMD = −1.06, 95%CI −1.66 to −0.46, P < 0.001) than studies on MMD (SMD = −0.51, 95%CI −0.81 to −0.21, P < 0.001) or ND (SMD = −0.25, 95%CI −0.39 to −0.11, P = 0.03). The results indicate that MBSR can significantly relieve individual depression symptoms, and the intervention effect is affected by different levels of depression (as illustrated in Figure 4b).

Figure 4b.

Subgroup analyses of depression outcome (level of depressive symptom).

The cultural background

In terms of culture, Figure 4c shows that there was no significant difference between studies with both cultural backgrounds (P = 0.50). In both Eastern cultures (SMD = −0.28, 95%CI −0.69 to −0.12, P = 0.001) and Western cultures (SMD = −0.44, 95%CI −0.61 to −0.26, P < 0.001), MBSR had a significant effect on depressive symptoms. It is suggested that different cultural backgrounds may not be the main factor affecting MBSR intervention.

Figure 4c.

Subgroup analyses of depression outcome (cultural background).

Publication bias assessment and sensitivity analysis

The funnel plot of depressive symptoms is presented in Figure 5. The funnel diagram shows a slightly visually asymmetric. Egger's regression test showed no evidence of asymmetry in the funnel plot (95%CI −0.86 to 0.22, t = −1.19, P = 0.24), and the trim-and-fill method indicated that no missing studies were needed to make the plot symmetric, with no difference between observed and adjusted mean effect sizes (SMD = −0.40, 95% CI −0.56 to −0.24, P < 0.001). These analyses suggest the summary effect is robust and free of publication bias.

Figure 5.

Funnel plot for the depressive symptom outcome.

Sensitivity analyses were conducted by excluding studies that may have large effects on meta-analysis results (i.e., either outliers or having a high or unclear risk of bias in multiple domains). No significant change was observed when any single study was deleted. Thus, the significant difference between the MBSR group and the control group in alleviating depressive symptoms would be considered stable (Figure 6).

Figure 6.

Sensitivity analysis included in the study.

Discussion

Summary of main findings

In this study, we attempt to assess the effect of MBSR on depressive symptoms by a meta-analysis of randomized controlled trials. We located 32 studies and found a medium effect size (SMD = −0.40, 95% CI −0.56 to −0.24, P < 0.001). The results of risk bias assessment showed that the included studies were at low risk of randomization sequence generation, incomplete outcome data, selective reporting, and other risks of bias, indicating that the conclusions of this study were reliable. Furthermore, the robustness of the results was supported by the sensitivity analysis. We can not compare our findings to prior meta-analyses because prior meta-analyses did not explore the intervention effect of MBSR on depression based on different cultural backgrounds, including clinical and non-clinical individuals of all ages (Chi et al., 2018; Li & Bressington, 2019; Yang et al., 2020; Zainal et al., 2013). Thus, our study is novel in that it evaluates the effects of MBSR on depression symptoms and moderator analyses that suggest future research directions.

The mindfulness-based emotion regulation model suggested that mindfulness training could gradually eliminate an individual's automatic response to depression by focusing on self-awareness (Chambers et al., 2009). Study of the mindfulness brain mechanisms also confirmed the effectiveness of mindfulness interventions in improving depression. For example, one study found that mindfulness traits were associated with reduced amygdala activity, which was often associated with depression (Creswell et al., 2007). Mindfulness meditation training could activate left prefrontal brain regions associated with positive emotions (Davidsen et al., 2003). This study confirmed that MBSR alleviates depressive symptoms. Future studies should further enhance the application of MBSR. For example, one study found that mindfulness meditation can be applied to moral education courses in schools (Kim, 2015). Therefore, the schools should actively try and explore the important role of MBSR in the students’ mental health education, and actively carry out the intervention training of MBSR in the mental health education classroom to improve the students’ mental health levels.

Findings of subgroup analysis

Sample origin has no significant moderating effect on MBSR interventions (P = 0.55), and the results are inconsistent with previous studies. Previous study found that MBSR has better clinical intervention effects. However, in addition to MBSR intervention training, previous study also integrated other mindfulness intervention training methods, and only four clinical studies were included (Zoogman et al., 2015). In addition, the clinical patients included in the previous meta-analysis only included depression (Chi et al., 2018). The specific intervention method and the diverse control of samples are the key factors affecting MBSR, which is also convenient to explore the intervention effect of MBSR on depressive symptoms more comprehensively and accurately. In our study, MBSR intervention was used to extend clinical individuals to patients with other clinical diseases. Previous study also confirmed that MBSR has good intervention effects on both clinical patients and non-clinical individuals. Therefore, the sample origin of this study did not have a significant moderating effect on MBSR intervention. Future research can further expand the application of MBSR in non-clinical individuals, so as to scientifically and effectively prevent the occurrence of depressive symptoms in the normal population, improve the psychological quality of the normal population, and improve their mental health level.

The level of depression significantly affects MBSR interventions on depressive symptoms (P = 0.01). MDD showed a greater improvement in depression than studies on MMD or ND. This finding is generally consistent with previous meta-analysis (Chi et al., 2018). One possible explanation might be that individuals with severe depression may have a stronger desire to get rid of negative emotions and pursue inner peace, be more willing to participate in training, and complete better-quality mindfulness exercises. In addition, patients with major depression had higher levels of depression at baseline and had more room to reduce their depressive mood after MBSR intervention. However, this issue is still controversial. For example, existing studies found that the intervention effect of MBSR is better for lower depression levels (Gallegos et al., 2013). Individuals with higher levels of depression have higher levels of rumination, which can prevent them from completing regular mindfulness training (Nolen-Hoeksema, 2000). Thus, interpretation should be done with caution.

In addition, our finding suggested that cultural background has no significant moderating effect on MBSR interventions (P = 0.50). Although mindfulness originated in Eastern culture (Schmidt et al., 2011), MBSR was developed in Western culture (Kabat-Zinn, 1990). With the popularization and improvement of MBSR in Eastern and Western cultures, both cultures have learned from each other about MBSR intervention methods, and both have also developed in the same direction and homogeneity, which may weaken the influence brought by cultural background differences.

Future research

First, due to the limitation of search methods, only English literature was included, and high-quality relevant studies in other languages may be excluded. Excluding non-English reports may cause language bias and reduce the accuracy of summary treatment effect estimates (Haidich, 2010; Jüni et al., 2002). Thus, future studies should search for more correlative studies in other languages and broader databases. Second, most of the included studies did not perform follow-up evaluations. The long-term intervention effects of MBSR on depressive symptoms cannot be determined. Therefore, further research should be carried out. What's more, many included studies have unclear and high deviation risks in concealment and blindness. Sensitivity analysis of the included literature was performed to balance the potential risk of bias and to ensure the accuracy of the results of the meta-analysis. Future research should focus on the rigor of experimental design, especially in allocation concealment and blind settings to reduce the potential risk of bias.

Conclusion

This meta-analysis is important as it reveals strong evidence of the efficacy of MBSR for depressive symptoms in randomized trials. The level of depression is an important moderating variable affecting the intervention effect, and the intervention effect of MBSR is better for patients with MDD. Furthermore, the sample origin (clinical vs. non-clinical) and cultural backgrounds (East vs. West) had no significant regulatory effect, suggesting that the intervention effect may not be affected by both. However, since only English literature was included in this meta-analysis, it is necessary to expand databases in other languages to further explore this issue. Given the growing demand for psychotherapy, MBSR as an effective intervention to alleviate depression symptoms should further broaden its application field in the future to reduce the risk of depression continuing to deteriorate into depressive disorder.

Footnotes

Acknowledgments

We would like to express our appreciation to every member of our research group for their valuable comments on earlier versions of this article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (grant number: 31860283).

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Can mindfulness-based stress reduction relieve depressive symptoms? A systematic review and meta-analysis

Abstract

Keywords

Introduction

Methods

Selection of studies

Inclusion criteria

Exclusion criteria

Data extraction

Risk of bias assessment

Statistical analysis

Results

Literature search and screening

Characteristics of the studies

Risk of bias assessment

Main findings

Subgroup analyses

The sample origin

The level of depressive symptom

The cultural background

Publication bias assessment and sensitivity analysis

Discussion

Summary of main findings

Findings of subgroup analysis

Future research

Conclusion

Footnotes

Acknowledgments

Declaration of conflicting interests

Funding

References