Online Mindfulness-Based Cognitive Therapy (MBCT) is a promising intervention for mental health, but its effectiveness in reducing depressive symptoms remains underexplored. While key mechanisms of change have been identified in traditional MBCT, their role in online delivery formats needs further investigation. This study aimed to evaluate the effectiveness of synchronous and asynchronous online MBCT in reducing depressive symptoms and to examine potential mechanisms of change.
Method
In this randomized clinical trial, 170 individuals with mild to moderate depression were assigned to a 6-week synchronous online MBCT group (n = 58), asynchronous online MBCT group (n = 59), or waitlist control (n = 53). Depression, anxiety, mindfulness, cognitive fusion, rumination, self-compassion, resilience, and experiential avoidance were assessed at baseline, post-treatment, and 3-month follow-up.
Results
Posttest assessments were completed by 42 participants (72%) in the synchronous group, 32 (54%) in the asynchronous group, and 51 (96%) in the waitlist control condition. Both MBCT formats significantly reduced depressive symptoms compared to the control group, with sustained effects at follow-up. Mindfulness and cognitive defusion emerged as significant mediators, explaining 52% of the variance in the post-treatment depression severity. Additionally, participants in both interventions showed decreased rumination and anxiety, and increased self-compassion and resilience—effects maintained at follow-up.
Conclusions
Both MBCT formats led to significant improvement in depression and related outcomes, with no significant differences detected between them. However, the study was not powered to test noninferiority, and these findings should be interpreted with caution. The synchronous format had lower attrition, suggesting that real-time interaction may enhance adherence. Either format can be used for mild to moderate depression, with the choice informed by expected engagement and available resources.
Preregistration
This trial was preregistered at ClinicalTrials.gov (Identifier: NCT05919875).
Depression is a prevalent mental health disorder, affecting approximately 5% of adults worldwide (World Health Organization, 2023). Individuals experiencing depression commonly report significant emotional distress, including feelings of guilt, worthlessness, and hopelessness, as well as sleep disturbances, changes in appetite, and persistent low mood (Radloff, 1977). Beyond these symptoms, depression disrupts multiple aspects of functioning, including cognitive (Baune & Air, 2016), social (Steger & Kashdan, 2009), biological (Cui et al., 2024; Nestler et al., 2002), psychological (Beck et al., 1993; Maier & Seligman, 1976), and occupational domains (Wang et al., 2004).
Despite the documented efficacy of evidence-based psychotherapies and pharmacological treatments, access to mental health care remains critically limited worldwide (Wainberg et al., 2017). A global analysis of the treatment gap between 2000 and 2019 revealed that the proportion of individuals receiving minimally adequate treatment for depression ranged from just 3% in low-income countries to 23% in high-income countries (Moitra et al., 2022). This persistent disparity is multifaceted and can be attributed to several factors, including the limited availability of trained specialists, the high cost of treatment, geographical barriers to accessing services, and the persistent stigma surrounding mental disorders (World Health Organization, 2022). Given these challenges, there is an urgent need to explore scalable alternatives that can bridge this gap and expand access to mental health care.
One promising approach is internet-based psychological interventions, which offer a cost-effective and scalable solution to mental health service delivery (Schueller & Torous, 2020). These interventions have demonstrated satisfactory effectiveness in treating mental health disorders, as evidenced by numerous meta-analyses (Fischer-Grote et al., 2024; Guo et al., 2021; Pauley et al., 2023; Wang et al., 2023), including depression (Karyotaki et al., 2021; Moshe et al., 2021). Despite their growing empirical support, more research is needed to understand how online programs can be effectively implemented in real-world settings to ensure accessibility, safety, and quality of delivery (Smith et al., 2023).
Among the various internet-based psychological interventions, online mindfulness-based interventions (MBIs) have been increasingly studied as a promising approach for reducing depressive symptoms (meta-analyses: Sommers-Spijkerman et al., 2021; Spijkerman et al., 2016). Research indicates that in-person MBIs target key cognitive and emotional mechanisms that contribute to the persistence of depression, including rumination (Li et al., 2022), worry (van der Velden et al., 2015), and repetitive negative thinking (MacKenzie et al., 2018). Additionally, MBIs have been associated with improvements in self-regulation (Wang et al., 2024), self-compassion (Ha & Kim, 2023), and resilience (Pérez-Aranda et al., 2021), all of which contribute to the reduction of depressive symptoms. Examining mechanisms of change is crucial for understanding how these interventions exert their effects and for identifying which processes are most relevant to clinical improvement (Kazdin, 2007). However, most of this evidence comes from in-person MBIs, and it remains unclear whether the same processes are engaged in digital formats that differ in structure, social interaction, and level of guidance. Understanding whether online adaptations activate similar mechanisms is important for refining digital mindfulness programs, tailoring them to user needs, and enhancing engagement and therapeutic effectiveness.
As research on online MBIs has expanded exponentially (Ferreira & Demarzo, 2024), challenges related to standardized reporting have become increasingly evident (Wolever et al., 2022). The term 'online intervention' encompasses a wide range of delivery methods, including guided and unguided formats, synchronous and asynchronous sessions, as well as mobile- and web-based platforms (Smoktunowicz et al., 2020). At the same time, this diversity can be seen as an advantage, allowing programs to adapt to different settings, available resources, and levels of professional support (Andersson et al., 2014). Testing various delivery formats helps identify approaches that are more scalable and feasible, especially where access to trained professionals is limited (Wolever et al., 2022). Still, this variability makes it difficult to classify and compare findings across studies and to determine which specific aspects of delivery drive the observed effects. Understanding these distinctions is essential, as delivery format appears to influence intervention outcomes. For example, one study found that an online (synchronous) MBI had a greater impact on stress reduction compared to an unguided, asynchronous program (Wolever et al., 2022). A meta-analysis by Taylor et al. (2021) suggested that unguided MBIs had a smaller effect on depression, mindfulness, and quality of life compared to non-digital unguided interventions (e.g., textbook and CD-based programs). Furthermore, these variations refer only to the technical aspects of intervention delivery, without accounting for substantial differences in content, duration, therapeutic approach, or symptom measurement/diagnosis methods, all of which may further influence intervention efficacy. To address these issues, there is a growing consensus that high-quality randomized controlled trials (RCTs) are needed to compare different online MBIs formats (Taylor et al., 2021), such as synchronous and asynchronous (Schwarze & Gerler, 2015; Toivonen et al., 2017) or reaching specific clinical populations (Sevilla-Llewellyn-Jones et al., 2018).
Within the broader category of mindfulness-based interventions, Mindfulness-Based Cognitive Therapy (MBCT) is one of the most extensively studied MBIs (Zhang et al., 2021). MBCT is an 8-week program consisting of weekly group sessions lasting 2 to 2.5 hr. The course integrates formal mindfulness practices, including the body scan, sitting meditation, and mindful movement, with cognitive-behavioral therapy components such as psychoeducation on depression or behavioral activation (Sipe & Eisendrath, 2012). Originally developed to prevent relapse in recurrent depression (Teasdale et al., 2000), MBCT has demonstrated effectiveness in this area, as supported by meta-analyses (Kuyken, et al., 2016; McCartney et al., 2021; Piet & Hougaard, 2011). However, research also indicates its efficacy in treating current depressive episodes (meta-analyses: Goldberg et al., 2019; Tseng et al., 2023).
While MBCT is well established in face-to-face settings, its online adaptation has thus far demonstrated only preliminary evidence of effectiveness in reducing stress (Dowd et al., 2015), emotional distress (Cillessen et al., 2018; Holas & Wardęszkiewicz, 2026), and symptoms of anxiety and depression (Nissen et al., 2020; Segal et al., 2020; Seritan et al., 2022). However, no study to date has directly compared the feasibility of different online MBCT delivery formats in treating depression.
Prior research suggests that guided psychological interventions are associated with higher adherence and greater symptom reduction than unguided approaches (Berger et al., 2011), including within online mindfulness interventions (Wolever et al., 2022). While both synchronous and asynchronous MBCT formats can include guidance, they differ substantially in the mode and immediacy of therapist interaction—potentially affecting engagement and outcomes. Notably, asynchronous online MBCT has been associated with higher attrition rates (Holas & Wardęszkiewicz, 2026), suggesting the delivery format itself may play a critical role.
However, no randomized controlled trial has directly compared these two delivery formats in individuals with mild to moderate depression. Clarifying their comparative effectiveness is critical for guiding implementation decisions in clinical and community settings, particularly in light of the high attrition rates observed in some online interventions. The present study addresses this gap by directly comparing synchronous online group-based MBCT and guided asynchronous MBCT in a randomized controlled trial, examining depressive symptoms, related psychological outcomes, and potential mechanisms of change.
The present study aimed to evaluate the effectiveness of an online adaptation of MBCT delivered in both synchronous and asynchronous formats in a sample of individuals with depression. Given the high heterogeneity of online MBI formats, which has posed a persistent challenge for meta-analytic synthesis (Gong et al., 2023), it was considered important to also investigate existing, structured, and standardized interventions alongside the development and evaluation of new approaches. Additionally, as individuals with depression represent a particularly vulnerable population, the selection of a well-established, evidence-based intervention was deemed essential. Among MBIs, MBCT has been one of the most rigorously studied and empirically supported programs, particularly for clinical populations (Zhang et al., 2021). Unlike other online MBIs, which vary considerably in structure and theoretical underpinnings, MBCT is a manualized program with well-defined protocols, making it a logical candidate for digital adaptation and larger-scale implementation.
Despite this, research on online MBCT has remained limited, particularly in individuals with clinical depression. As the debate regarding the most optimal delivery format has remained unresolved, further high-quality randomized controlled trials have been needed to clarify their comparative effectiveness. To address this gap, participants in the present study were randomly assigned to either online synchronous group MBCT or guided asynchronous MBCT, with a waitlist control group serving as a comparator. As no directional hypotheses were formulated regarding the relative effectiveness of the two delivery formats, comparisons between the synchronous and asynchronous conditions were exploratory in nature.
Method
Design
In the present study, our objective was to assess the efficacy and mechanisms of change associated with the online, 6-week MBCT intervention for individuals with mild-to-moderate depression. The study employed a three-arm design, comprising an asynchronous online guided MBCT, an online synchronous group MBCT, and a control group assigned to a waitlist. Despite the completion of pre-test and post-test questionnaires, participants were asked to complete a follow-up assessment after a 3-month interval. The design, inclusion and exclusion criteria, assessment tools and research questions were preregistered at ClinicalTrials.gov (Identifier: CT05919875).
Participants
Participants were recruited online through multiple channels. Advertisements were primarily posted in numerous Facebook groups targeting diverse populations (e.g., students, single parents, individuals interested in self-development, entrepreneurs, thematic groups focused on psychological problems, somatic illness support groups, Polish immigrants, people experiencing loneliness, and local community groups). The posts were widely reshared by individuals who expressed appreciation for the project and volunteered to disseminate the information further.
Additionally, administrators of Instagram accounts with moderate followings (approximately 2,000 – 30,000 followers) were contacted directly and invited to share information about the study; several agreed to do so. These accounts were mainly psychology-focused but also included lifestyle and health-related profiles.
Finally, information about the study was published on university and social welfares websites, and included in institutional newsletters.
The advertisements specified that the project was intended for adults experiencing significant deterioration in psychological functioning who wished to develop or improve self-regulation skills. The landing page explicitly stated that individuals experiencing severe depressive episodes, in crisis, diagnosed with psychotic or bipolar disorders, or currently undergoing psychotherapy were ineligible to participate.
Inclusion and Exclusion Criteria
The inclusion criteria were: (1) being over 18 years old, (2) fluency in the Polish language, (3) meeting the initial screening cut-off for mild depression on the CES-D-20 (≥ 16 points) and PHQ-9 (≥ 5 points), (4) having a diagnosed mild or moderate depressive episode as assessed by the M.I.N.I. structured online interview (Sheehan et al., 1998), and (5) agreeing to the study protocol and randomization, including the possibility of being assigned to the waitlist group. At screening, two self-report questionnaires were used to assess depressive symptoms: CES-D-20 and PHQ-9. Using both tools enhanced the validity of initial symptom assessment and minimized false positives or negatives prior to the diagnostic interview. Final inclusion decisions were based on the M.I.N.I. structured interview. For clarity and consistency, only CES-D results are reported in the main text, as both measures showed similar patterns in preliminary analyses. PHQ-9 results are available in the online Supplementary Information. The exclusion criteria were: (1) severe depression or suicidality, (2) current participation in psychotherapy, (3) a diagnosis of substance use disorder, psychotic disorder, or bipolar disorder, as assessed in the M.I.N.I. structured online interview, and (4) recent modifications to or instability in psychiatric medication.
Participant Flow
A total of 502 individuals registered on the platform, of whom 444 completed all required questionnaires. Of these, 117 were excluded due to ongoing psychotherapy, 33 did not exhibit depressive symptoms, and 12 reported severe depression and were referred to psychological support centers. Among the 282 structured interviews conducted, 198 participants met the inclusion criteria; however, 28 did not complete all required questionnaires. Ultimately, 170 participants were randomized into one of three conditions: the synchronous MBCT group (n = 58), the asynchronous MBCT group (n = 59), or the waitlist control group (WLC; n = 53).
The sample was predominantly female (76%), with a mean age of 36.8 years (SD = 10.9). Most participants had completed higher education (72%), and 64% were employed at the time of the study. Baseline depression severity, as measured by the CES-D, indicated mild to moderate symptoms (M = 27.61, SD = 8.18). Data on race or ethnicity were not collected. As the study was conducted in Poland and required fluency in Polish, participants were presumed to be predominantly of Polish or Eastern European background, although this cannot be confirmed.
Sample Size Planning
An a priori power analysis for a 3 × 2 (group x time) mixed design indicated that approximately 210 participants (70 per arm) would be required to detect small-to-medium effects (f ≈ 0.20) at α = 0.05 and power (1–β) = 0.80, assuming a within-subject correlation of 0.50. To account for an anticipated 30% dropout rate, the target recruitment size was set at 300 participants (100 per arm).
Due to practical and logistical constraints, this target could not be reached. The final sample provided adequate sensitivity for medium effects but limited power for detecting smaller between-group differences. Consequently, small effects may have gone undetected.
Randomization and Allocation
Participants were randomly assigned to one of the three conditions using a stratified randomization procedure to balance baseline characteristics across groups, including demographic variables (age, gender, and education level) and baseline levels of depression and mindfulness. Randomization was performed by an independent programmer using a custom algorithm that generated 43,276 possible allocations and selected the one that minimized between-group differences in means and standard deviations for the stratification variables.
Because the synchronous condition involved fixed meeting times, participants were also asked to indicate their availability for four possible session schedules or to select the option None of the above / I would prefer the asynchronous version. The randomization algorithm incorporated these preferences to ensure feasible group assignments while maintaining balance across experimental conditions. Characteristics of the sample are shown in Table 1 and flow chart (Fig. 1). Data on race or ethnicity were not collected.
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4.17 (SD = 1.24)
4.20 (SD = 1.20)
4.32(SD = 1.0)
Interventions
6-Week Online Group Synchronous MBCT
In this MBCT format, participants were assigned to four groups of up to 15 individuals based on their indicated date preferences. Their profiles on the study platform were moved to the appropriate group, ensuring that each participant could access only the materials, announcements, and chat box specific to their group. Participants received email reminders about upcoming meetings and encouragement to engage in practice. If a participant remained inactive for 5 consecutive days, they received a gentle reminder containing psychoeducational content on topics such as perfectionism, the importance of habit formation, negative thought patterns, or difficult emotions. The meetings were conducted online via Google Meet or Zoom. Each session was led by an experienced mindfulness teacher with an MBCT certification, accompanied by an assistant responsible for technical support. In this study, the training was conducted by two male and two female teachers, each of whom was assigned to a single group for the entire six-week duration.
The intervention was shortened to six weeks to enhance feasibility, reduce the risk of participant dropout, and remain within the available research budget, while preserving MBCT’s core therapeutic structure and content. Evidence from prior research indicates that shortened mindfulness-based programs (typically 4—6 weeks) can produce meaningful reductions in depressive and anxiety symptoms, supporting the feasibility of briefer MBCT formats in online settings (Cavanagh et al., 2018; Querstret et al., 2020; Spijkerman et al., 2016). The program used in the present study was a 6-week digital adaptation of the standard MBCT protocol, previously tested in an online format (Holas & Wardęszkiewicz, 2026). The session titles were as follows Table 2:
Table 2
6-week MBCT program
Week
Topic of the meeting
Content
Exercises/ Homework
1
Awareness and automatic pilot
Acting with(out) full awareness, raisin exercise, habitual patterns of distraction
Mindful eating, Body scan
2
Living in our heads
Tendency to be caught up in thoughts about the past and future; relationship between thoughts and feelings, body sensations
Sitting meditation, body scan. calendar of pleasant experiences
3
Being present in the body
Recognizing distracted mind; body as a gate to the mind and a breath as a stabilizer of attention
After each meeting, participants received a summary of the session, a workbook, and guided meditation recordings for the upcoming week via the study platform. They could use the chat box to communicate with each other or seek guidance from the researcher or a psychologist with expertise in mindfulness, who responded to content-related inquiries.
6-Week Guided Asynchronous MBCT
In this MBCT format, participants formed a single group of 58 individuals. On the dedicated study platform, all participants had access to a shared panel that included a chat box and study materials—audio recordings and a workbook—which were unlocked weekly in accordance with the session themes. The program was a pre-recorded equivalent of the synchronous version. Each week, participants received audio recordings introducing a new topic, guided meditation exercises (e.g., body scan, sitting meditation), reflective questions, psychoeducational content with emotional support, and instructions for the upcoming week. Similar to the synchronous condition, participants were reminded about the upcoming new sessions and encouraged to engage in daily practice. In cases of inactivity, automated reminder emails were sent, following the same procedure as in the synchronous format. To sustain the activity on the platform and provide support in situations of self-doubt, participants could use the chat box for communication with themselves and with a psychologist, who was answering few times a day. The chat function resembled a group forum, where all participants could read and reply to each other’s messages, and the psychologist could also post supportive or clarifying comments.
Control Group
After randomization, 53 participants were redirected to the “waitlist" webpage on the platform, where they had access to a dedicated chat box exclusively for their group. Throughout the 6-week waiting period, the group did not receive any form of intervention. During this time, three reminder emails were sent to inform participants about the study procedure and the mandatory second assessment required to gain access to the intervention. Upon completing all obligatory questionnaires, participants were granted access to the asynchronous MBCT intervention.
Symptom Measures
Primary Outcomes
Depression
To enhance the validity of depression assessment prior to the interview, a second measure was utilized. The Center for Epidemiologic Studies Depression Scale (CES-D-20) is a widely used self-report tool designed to assess depressive symptoms in the general population (Radloff, 1977). Participants respond to 20 items on a 4-point scale, with total scores ranging from 0 to 60, where higher scores indicate greater depressive symptomatology. The tool demonstrated strong psychometric properties, with Cronbach’s alpha coefficients of 0.89 at baseline, 0.92 post-intervention, and 0.90 at follow-up, indicating high internal consistency.
Anxiety
The GAD-7 (Spitzer et al., 2006) is a 7-item questionnaire assessing the severity of Generalized Anxiety Disorder (GAD) symptoms, including nervousness, excessive worry, restlessness, and difficulty relaxing. Participants rate how often they experienced symptoms over the past 2 weeks on a 4-point scale (0 = not at all, 3 = nearly every day), with total scores ranging from 0 to 21. The GAD-7 demonstrates strong reliability and validity across various populations (Kroenke et al., 2007; Spitzer et al., 2006). Cronbach’s alpha for this scale was 0.87 in the pre-test, 0.88 in the post-test, and 0.87 in the follow-up.
Process Measures
Mindfulness
Levels of mindfulness were measured with the Five Facet Mindfulness Questionnaire (FFMQ) shortened from the original 39 items (Baer et al., 2008) to 24 items by Bohlmeijer et al. (2011). It is a self-report tool designed to measure different aspects of mindfulness. It assesses five key components: observing, describing, acting with awareness, nonjudging of inner experience, and nonreactivity to inner experience. The FFMQ-24 has been used to assess mindfulness skills in relation to mental health, showing moderate–strong associations with experiential avoidance, depression, and anxiety (Ådnøy et al., 2023). Cronbach’s alpha for this scale was 0.87 in the pretest, 0.92 in the posttest, and 0.94 in the follow-up.
Resilience
Resilience was measured with the SPP-25 (Skala Pomiaru Prężności – Resilience Measurement Scale). It is a Polish, 25-item self-report questionnaire designed to assess psychological resilience, understood as an individual’s ability to adapt effectively to stress, adversity, and life challenges (Ogińska-Bulik & Juczyński, 2008). The scale conceptualizes resilience as a relatively stable personality trait that facilitates coping with both traumatic experiences and everyday stressors. Participants respond to each item using a 5-point Likert scale (0 = strongly disagree to 4 = strongly agree), with total scores ranging from 0 to 100, where higher scores indicate greater resilience. In our study, the scale has demonstrated good internal consistency (Cronbach’s α = 0.92 in pretest, 0.93 in posttest, and 0.91 in follow-up).
Self-Compassion Scale Short-Form
The Self-Compassion Scale – Short Form (SCS-SF) (Raes et al., 2011; Polish validation: Holas et al., 2024) was used to measure self-compassion. The SCS-SF consists of 12 items, rated on a 5-point scale. The SCS-SF is strongly correlated with the long form of the scale (r ≥ 0.97) and demonstrated consistently high internal reliability across populations (Neff & Pommier, 2013; Werner et al., 2012), with a reliability of Cronbach’s α = 0.80 in the pretest, 0.87 in posttest, and 0.75 in a follow-up measure in our study.
Cognitive-Fusion Scale
Cognitive fusion was assessed using the Cognitive Fusion Questionnaire-7 (CFQ-7), a 7-item self-report measure designed to evaluate the extent to which individuals become entangled with their thoughts and experience difficulty distancing themselves from them (Gillanders et al., 2014). Participants rate items on a 7-point Likert scale (1 = never true to 7 = always true), with higher scores indicating greater cognitive fusion. The Polish validation confirmed its unidimensional structure and demonstrated strong psychometric properties (Baran et al., 2019). In the present study, Cronbach’s α ranged from 0.91 to 0.94.
Rumination
In the present study, The Ruminative Responses Scale (RRS), a 22-item self-report questionnaire, was used to assess rumination, a cognitive style characterized by a repetitive and passive focus on one’s distress and its causes (Nolen-Hoeksema et al., 2008). Participants respond to statements on a 4-point Likert scale (1 = almost never to 4 = almost always), with higher scores indicating greater rumination. The scale evaluates how individuals repetitively dwell on negative emotions and thoughts rather than engaging in active problem-solving. The RRS has demonstrated strong internal consistency, with Cronbach’s α = 0.90 in the pretest, 0.92 in the posttest, and 0.90 in a follow-up assessment.
Experiential Avoidance
Experiential avoidance was assessed using the Brief Experiential Avoidance Questionnaire (BEAQ), a 15-item self-report measure designed to evaluate the tendency to evade or suppress unpleasant internal experiences, such as distressing emotions, thoughts, or bodily sensations (Gámez et al., 2014). The Polish validation study confirmed its bifactorial structure, identifying two dimensions: cognitive–emotional avoidance (CEA) and behavioral avoidance (BA) (Wardęszkiewicz & Holas, 2024). BEAQ items are rated on a 6-point Likert scale (1 = strongly disagree to 6 = strongly agree), with higher scores reflecting greater experiential avoidance. In the present study, Cronbach’s α ranged from 0.81 to 0.85, indicating good internal consistency.
Negative Effects
Negative effects were assessed using the Negative Effects Questionnaire (NEQ; Rozental et al., 2014). Following the intervention, participants responded to 20 items (e.g., Difficult memories came back or I felt anxious, rating the intensity of specific symptoms on a scale from 0 = not at all to 4 = extremely — and linking them to either intervention or external factors. The Cronbach’s α was 0.95 in the validation study (Rozental et al., 2019).
Data Analyses
In order to assess the effectiveness of the intervention, an analysis using linear mixed models (LMM) was conducted. The analyses were based on a 3 × 3 design, including three groups (control, synchronous, and asynchronous) and three measurement points. The interaction between these two factors was included as fixed effects. Additionally, participant ID was included as a random effect to account for inter-individual variance.
Although the study employed a three-group design, data for the control group were assessed only at pretest and posttest. Consequently, group effects at these time points reflect comparisons among three groups. In contrast, at the 3-month follow-up, analyses were restricted to the two intervention conditions (synchronous vs. asynchronous), resulting in a two-group comparison with a numerator degree of freedom of 1.
This model can be expressed using the following equation:
In the present study the proportion of individuals who completed the third measurement accounted for less than half of the original sample. Based on the analyses by Chakraborty and Gu (2009), it was decided to use mixed models without imputation. Their research suggests that this approach is more efficient and leads to more reliable results, especially when dealing with a high percentage of missing data.
To determine the mechanisms underlying the relationship between group membership and depression severity, a series of mediation analyses with parallel mediators was conducted using PROCESS macro by A. Hayes (Model 4). In each model, group membership served as the independent variable while depression severity at posttest as the dependent variable. Baseline scores of given variables were included as covariates to control for pre-existing differences. The significance of indirect effects was assessed using a bias-corrected bootstrapping procedure with 5000 resamples. Indirect effects were considered statistically significant if the 95% confidence interval did not include zero. Both the total indirect effect and the specific indirect effects of each mediator were analyzed. Partial mediation was inferred when the direct effect of group membership on depression severity remained significant after including the mediators in the model. To explore whether participants who dropped out of the study differed from those who completed it, a series of independent-samples t-tests were conducted on baseline demographic and psychological variables. These analyses aimed to identify potential predictors of attrition by comparing completers and non-completers across key characteristics measured prior to the intervention. In addition to the full-sample comparison, analyses were also conducted separately within the synchronous and asynchronous conditions to examine whether dropout patterns varied by intervention format.
Results
Effects
Depression (CES-D-20)
The model was evaluated using BIC = 2432.98. Fixed effects explained 31.4% of CES-D variance (marginal R2 = 0.314), while both fixed and random effects accounted for 53.7% (conditional R2 = 0.537). ICC = 0.223 indicated that 22.3% of variance was due to random effects. A significant group effect was found (F(2, 175.31) = 7.53, p < 0.001), with higher depression levels in the control group than in the asynchronous (p < 0.001) and synchronous (p = 0.008) groups. No significant difference was observed between the intervention groups (p = 0.068). A significant time effect (F(2, 205.10) = 76.97, p < 0.001) showed a decline in CES-D scores from the first to later measurements (both p < 0.001), with no significant difference between the posttest and follow-up assessments (p = 0.129). A significant interaction (F(3, 202.43) = 13.50, p < 0.001) indicated that depression severity remained stable in the control group (F(1, 176.47) = 2.98, p = 0.086), whereas both intervention groups showed significant reductions in the posttest and follow-up (asynchronous: F(2, 210.64) = 57.44, p < 0.001; synchronous: F(2, 206.81) = 33.70, p < 0.001). No significant group differences were found at baseline (F(2, 297.49) = 0.61, p = 0.546), confirming similar initial depression levels. However, differences emerged in posttest (F(2, 320.73) = 19.14, p < 0.001) and at the 3-month follow-up – where only the two intervention groups were compared – (F(1, 331.53) = 4.31, p = 0.039). Post hoc analyses showed that at posttest, the control group had significantly higher depression scores than both the asynchronous (p < 0.001) and synchronous (p < 0.001) groups, with no difference between the intervention groups (p = 0.096). At follow-up, depression was higher in the synchronous than in the asynchronous group (p = 0.039). Estimated marginal means are provided in Table 3.
Table 3
Estimated marginal means for CES-D by measurement time and group membership
Measurement
Group
M
SE
95% CI
LL
UL
1
WLC
26.55
1.21
24.17
28.92
asynchronous
27.86
1.14
25.62
30.11
synchronous
28.33
1.15
26.06
30.60
2
WLC
24.12
1.22
21.72
26.51
asynchronous
12.69
1.47
9.80
15.58
synchronous
16.94
1.32
14.35
19.54
3
WLC
-
-
-
-
asynchronous
12.60
1.72
9.22
15.99
synchronous
17.80
1.82
14.22
21.39
M = estimated marginal mean; SE = standard error; CI = confidence interval; LL = lower limit; UL = upper limit. WLC = waitlist control group. No follow-up data were available for the WLC condition
The parameters for fixed effects are presented in Table 4. The analysis showed that depression severity was significantly higher in the control group and significantly lower in the asynchronous group compared to the reference group (synchronous). CES-D scores were higher at the first measurement compared to the reference measurement (third measurement)—these parameters confirm the post hoc pairwise comparisons.
Table 4
Regression parameters for fixed effects in the model explaining CES-D
Parameters
b
SE
t
p
95% CI
LL
UL
Intercept
17.80
1.82
328.16
< 0.001
14.22
21.39
Pretest
10.52
1.95
222.05
< 0.001
6.69
14.36
Posttest
−0.86
2.00
205.12
0.667
−4.80
3.08
WLC
7.17
1.80
312.94
< 0.001
3.64
10.70
Asynchronous
−5.20
2.51
331.53
0.039
−10.13
−0.27
Pretest * WLC
−8.95
2.05
187.69
< 0.001
−12.99
−4.91
Pretest * asynchronous
4.74
2.68
224.09
0.079
−0.55
10.03
Posttest * asynchronous
0.95
2.80
197.69
0.736
−4.58
6.47
b = unstandardized regression coefficient; SE = standard error; t = t-value; p = significance level; CI = confidence interval; LL = lower limit; UL = upper limit. WLC = waitlist control group. The synchronous MBCT group served as the reference category
Anxiety
The model was evaluated using BIC = 1947.73. Fixed effects explained 30.5% of variance (R2 = .305), while total variance explained was 56.1% (R2 = .561). ICC = 0.256 indicated that 25.6% of variance was due to random effects. A significant group effect (F(2, 167.25) = 76.39, p = 0.002) showed that anxiety was higher in the control group than in asynchronous (p < 0.001) and synchronous (p = 0.001) groups, with no difference between intervention groups (p = 0.528). A significant time effect (F(2, 192.82) = 80.16, p < 0.001) revealed a decline in anxiety from the first to later measurements (both p < 0.001), with no significant difference between the second and third time points (p = 0.093). A significant interaction (F(3, 190.69) = 11.47, p < 0.001) indicated that anxiety remained stable in the control group, while both intervention groups showed significant reductions in later assessments (p < 0.001). No significant group differences were found at baseline (p = 0.346) or at the final assessment (p = 0.372), but the control group had higher anxiety than both intervention groups at the second time point (p < 0.001). No difference was observed between the synchronous and asynchronous groups (p = 1.000).
Cognitive Fusion
The model was assessed using BIC = 2237.79. Fixed effects accounted for 24.0% of variance (R2 = 0.240), while the total explained variance reached 62.8% (R2 = 0.628). ICC = 0.387 indicated that 38.7% of variance was attributed to random effects. A significant group effect (F(2, 183.82) = 5.64, p = 0.004) showed that cognitive fusion was highest in the control group, significantly exceeding levels in both asynchronous (p < 0.001) and synchronous (p < 0.001) groups. No differences were found between the two intervention groups (p = 1.000). A main effect of time was also significant (F(2, 203.72) = 55.25, p < 0.001), indicating a progressive decline in cognitive fusion over repeated measurements (all p < 0.001). A significant interaction (F(3, 202.61) = 14.46, p < 0.001) revealed that cognitive fusion remained stable in the control group, while both intervention groups experienced a significant reduction between the first and later assessments. No group differences emerged at baseline (p = 0.705) or the final measurement (p = 0.516), but fusion levels in the control group were significantly higher at the second time point compared to the intervention groups (p < 0.001). No difference was detected between synchronous and asynchronous conditions (p = 1.000).
Resilience
The model was evaluated using BIC = 2623.38. Fixed effects explained 12.7% of variance (R2 = 0.127), while total variance explained was 74.9% (R2 = 0.749). ICC = 0.622 indicated that 62.2% of variance was attributable to random effects. A significant group effect (F(2, 173.89) = 4.05, p = 0.019) showed that psychological resilience was lower in the control group compared to both asynchronous (p = 0.004) and synchronous (p = 0.003) groups, with no significant difference between intervention groups (p = 1.000). A significant time effect (F(2, 176.77) = 41.55, p < 0.001) indicated a progressive increase in resilience across measurements (all p < 0.001). A significant interaction (F(3, 176.44) = 5.80, p < 0.001) revealed that resilience remained stable in the control group, whereas both intervention groups showed a significant increase from the first to later measurements, with no difference between the second and third time points. No group differences were observed at baseline (p = 0.558) or in the final measurement (p = 0.855), but the control group had lower resilience levels at the second time point compared to both intervention groups (p < .001). No difference was found between synchronous and asynchronous groups (p = 1.000).
Experiential Avoidance
For BA, the model (BIC = 1963.25) explained 3.0% of variance through fixed effects (R2 = 0.030), while total variance explained was 58.9% (R2 = 0.589). ICC = 0.559 indicated that 55.9% of variance was due to individual differences. The group effect was not significant (p = 0.236), with comparable BA levels across groups. A small but significant time effect (p = 0.029) showed a decrease in BA from the first to the third measurement, while the interaction was non-significant (p = 0.548). Regression analysis confirmed that the only significant effect was the reduction in BA over time. For CEA, a separate model (BIC = 2133.07) explained 20.4% of variance through fixed effects (R2 = 0.204), with total variance explained at 65.4% (R2 = 0.654). ICC = 0.449 suggested that 44.9% of variance was due to individual differences. A significant group effect (p < 0.001) indicated that CEA was higher in the control group than in both intervention groups (p < 0.001), with no difference between the asynchronous and synchronous groups (p = 0.285). A significant time effect (p < 0.001) demonstrated a progressive decline in CEA across all measurements. A significant interaction effect (p < 0.001) showed that CEA remained stable in the control group between the first and second measurements (p = 0.209), while both intervention groups experienced a significant reduction from the first to later time points (p < 0.001), with no further change between the second and third measurements. No significant differences were found at baseline (p = 0.293) or the final measurement (p = 0.267). However, at the second measurement, CEA was significantly higher in the control group compared to both intervention groups (p < 0.001), with no difference between the synchronous and asynchronous groups (p = 0.471).
Mindfulness
The model was evaluated using BIC = 2587.46. Fixed effects accounted for 28.0% of the variance (R2 = 0.280), while the total explained variance was 68.8% (R2 = 0.688). The intraclass correlation coefficient (ICC = 0.408) indicated that 40.8% of the variance was attributable to individual differences. A significant group effect (F(2, 186.21) = 6.95, p = 0.001) showed that mindfulness levels were lower in the control group compared to the asynchronous (p < 0.001) and synchronous (p < .001) groups, with no significant difference between the two intervention groups (p = 1.000). A significant time effect (F(2, 199.10) = 81.84, p < 0.001) indicated a steady increase in mindfulness over time (all p < 0.001), with mean FFMQ scores rising from 69.87 at baseline to 80.04 at the second measurement and 87.69 at the third measurement. A significant interaction effect (F(3, 198.18) = 16.95, p < 0.001) revealed that mindfulness remained stable in the control group between the first and second assessments (p = 0.456), whereas both intervention groups showed a significant increase from the first to subsequent measurements (p < 0.001), with no further improvement between the second and third time points. No significant differences were found between groups at baseline (p = 0.406) or at the final assessment (p = 0.311). However, at the second measurement, mindfulness levels in the control group were significantly lower than in both intervention groups (p < 0.001). No differences were detected between the synchronous and asynchronous groups (p = 0.750).
Rumination
The model was evaluated using BIC = 2496.07. Fixed effects explained 17.4% of variance (R2 = 0.174), while total variance explained was 56.0% (R2 = 0.560). ICC = 0.386 indicated that 38.6% of variance was attributable to individual differences. The group effect was not significant (p = 0.099), but post hoc comparisons revealed that rumination was higher in the control group than in the asynchronous group (p = 0.005), while the synchronous group did not differ significantly from either. A significant time effect (p < 0.001) indicated a progressive decline in rumination across assessments (all p < 0.001), with no significant difference between the second and third measurements (p = 0.088). A significant interaction effect (p < 0.001) showed that rumination levels remained stable in the control group between the first and second assessments (p = 0.222), whereas both intervention groups exhibited a significant decrease between the first and later time points (p < 0.001), with no further decline between the second and third measurements. No differences were found at baseline (p = 0.440), but at the second measurement, rumination was significantly higher in the control group compared to the asynchronous group (p = 0.002). By the third measurement, the synchronous group had significantly higher rumination than the asynchronous group (p = 0.019).
Self-Compassion
The model was evaluated using BIC = 2239.97. Fixed effects explained 16.8% of variance (R2 = 0.168), while total variance explained was 45.5% (R2 = 0.455). ICC = 0.287 indicated that 28.7% of variance was due to individual differences. The group effect was not significant (p = 0.066), but post hoc analysis showed that self-compassion was lower in the control group compared to both the asynchronous (p = 0.030) and synchronous groups (p = 0.007), with no difference between the intervention groups (p < 0.001). A significant time effect (p < 0.001) indicated a gradual increase in self-compassion across assessments, with no difference between the second and third measurements (p = 0.227). A significant interaction effect (p < 0.001) showed that self-compassion remained stable in the control group between the first and second assessments (p = 0.490), while both intervention groups exhibited a significant increase from the first to later measurements (p < 0.001), with no further difference between the second and third time points. No differences were found at baseline (p = 0.139) or at the final measurement (p = 0.120). However, at the second measurement, self-compassion was significantly lower in the control group compared to the asynchronous (p < 0.001) and synchronous groups (p = 0.003), with no significant difference between the intervention groups (p = 0.291).
Mechanisms of Change
Out of 21 examined models, the best characteristic had mindfulness and cognitive fusion (measured at the second time point) as mediators of the relationship between group membership and depression severity (CES-D score at the second time point). FFMQ, CFQ, and CES-D from the first measurement were included as control variables. The analysis revealed a significant relationship between group membership and mindfulness (β = 0.93, p < 0.001), as well as between group membership and cognitive fusion (β = −0.95, p < 0.001). Participants in the interventions group reported higher mindfulness and lower cognitive fusion than those in the control group. Mindfulness was negatively associated with depression severity when controlling for group membership and baseline values (β = −0.30, p = 0.001), indicating that higher mindfulness levels corresponded with lower depression severity. Conversely, cognitive fusion was positively associated with depression severity (β = 0.35, p < 0.001), meaning higher fusion levels were linked to increased depression symptoms. After accounting for mediators, the direct effect of group membership on depression remained significant and negative (β = −0.30, p = 0.049). Mediation analysis confirmed a significant total indirect effect (b = −6.52; 95% CI [−9.25, −4.32]), with both mindfulness (b = −2.98; 95% CI [−5.46, −0.82]) and cognitive fusion (b = −3.54; 95% CI [−6.05, −1.65]) acting as significant mediators. The findings support partial mediation, as the direct effect between group membership and depression remained significant after accounting for mediators. This highlights the crucial role of mindfulness and cognitive fusion in explaining the relationship between group membership and depression severity. All of the examined models are described in the online Supplementary Information Table 5.
Table 5
Summary of mediation model for the relationship between group membership and depression severity (CES-D)
Model
Effecta
B
SE
β
t
p
CI 95%
R2
LL
UL
Model 1
M1: FFMQ
M2: CFQ
a1
13.21
1.86
0.93
7.10
< 0.001
9.53
16.90
a2
−7.86
1.15
−0.95
−6.84
< 0.001
−10.14
−5.59
b1
−0.23
0.06
−0.30
−3.50
0.001
−0.35
−0.10
b2
0.45
0.11
0.35
4.05
< 0.001
0.23
0.67
c’
−3.16
1.59
−0.30
−1.98
0.049
−6.31
−0.01
0.52
c
−9.68
1.63
−12.89
−6.45
c – c’
−6.52
1.24
−0.62
−9.25
−4.32
FFMQ
−2.98
1.18
−0.28
−5.46
−0.82
CFQ
−3.54
1.12
−0.34
−6.05
−1.65
In each model, the independent variable is group membership, while the dependent variable is depression severity (CES-D score). a c – c’ represents the total indirect effect, testing the mediation effect with both mediators included. If the confidence intervals do not contain zero, the mediation effect is statistically significant at p < 0.05. CFQ – Cognitive Fusion; FFMQ – Mindfulness
Negative Effects
After the intervention, 76 participants completed the Negative Effects Questionnaire (NEQ). To assess the overall intensity of negative effects, a mean NEQ score was calculated for each participant. The average NEQ score was 0.28 (SD = 0.36), with a minimum of 0, a maximum of 1.65, and a mode of 0.18. The mean number of summed negative effect items per participant was 5.58 (SD = 7.12), ranging from 0 to 33. Fourteen participants (17%) reported no negative effects, while the remaining 83% reported experiencing at least one negative effect during the intervention. For 75% of participants, the impact of negative effects ranged from experiencing multiple symptoms with minimal impact (up to 7 symptoms) to experiencing fewer symptoms (around 2) with strong or extreme impact. The most frequently reported negative effects were: increased levels of stress (n = 24, mean impact = 1.7), greater worry (n = 20, mean impact = 1.3), more frequent unpleasant feelings (n = 20, mean impact = 1.8), recurring unpleasant memories (n = 24, mean impact = 1.54).
Treatment Response
In a study on clinical significance and depression assessment tools, Kounali et al. (2022) found that a 20% reduction in the total questionnaire score can be classified as a minimal clinically important difference (MCID). Therefore, in the present study, a 20% reduction was used as the cutoff for "improvement." Scores between 0 and 20% were categorized as "no change," while an increased severity of symptoms was classified as "deterioration." Among the 77 participants who completed the post-test CES-D measurement, 62 (81%) met the criteria for a clinically significant treatment response, scoring more than 20% lower on the depression scale compared to their pre-intervention scores. The mean improvement was 44%, with a median of 51%. Table 6 presents detailed data, stratified by the asynchronous and synchronous groups.
Table 6
Detailed data, stratified by the asynchronous and synchronous groups
Deterioration
No change
Improvement
Mean improvement
Median
Min
Max
Asynchronous
3 (9%)
2 (6%)
29 (85%)
51%(SD = 35)
55%
−57%
98%
Synchronous
4 (9%)
6 (14%)
33 (77%)
39%(SD = 32)
45%
−52%
92%
Engagement
Participants' activity on the platform was tracked based on login counts and time spent on audio recordings. However, data from the synchronous group were excluded from analysis and interpretation, as mindfulness instructors allowed to use for guided meditation recordings their own websites, YouTube channels, or MP3 files they provided – what could not be controlled. Therefore, the engagement indicators presented for this group should be treated as descriptive only, as they do not fully reflect participants’ actual practice time and are not directly comparable to the asynchronous condition. In the asynchronous group, the mean time spent on recordings was 611 min (SD = 411), with a minimum of 33 min and a maximum of 1715 min (approximately 28 h). The mean number of logins was 100 (SD = 83; min: 15, max: 457) in the asynchronous and 101 (SD = 92; min = 91 and max = 405) in synchronous group Table 7.
Table 7
Engagement metrics: session count and time spent by synchronous vs. asynchronous groups
Mean time
Min time
Max time
Mean session number
Min
Max
Asynchronous
611 (SD = 411)
33
1715
100(SD = 83)
15
457
Synchronous
327 (SD = 543)
0
2771
101(SD = 92)
11
405
Time refers to the duration spent on recordings, not total time on the platform
Attrition
Out of 170 participants randomized into three conditions, 125 (74%) completed the posttest assessment. Attrition rates varied across groups: 28% in the synchronous group, 45% in the asynchronous group, and 4% in the control group. Participants who remained inactive for more than five days received automated emails containing psychoeducational content and encouragement to re-engage with the program. However, those who did not respond to these emails or remained inactive for over three weeks were classified as dropouts. Upon logging into the platform, they were presented with a pop-up requesting feedback on their reasons for discontinuation. After the three months, in the follow-up, the attrition was 59% in the asynchronous and 66% in synchronous condition. As a total of 45 participants did not complete the posttest, the amount of collected feedback was limited. The reported reasons for dropout included: Perceiving the program as too intense or experiencing frustration due to an inability to complete all tasks (n = 4), finding another solution that better suited their needs (n = 1), deciding to seek psychiatric consultation instead (n = 1).
No statistically significant differences were found between completers and non-completers on any of the baseline variables, either in the full sample or within the separate intervention conditions (all ps > 0.05). This included demographic factors (e.g., gender, education) as well as psychological variables such as baseline levels of depression, anxiety, mindfulness. Although a few comparisons approached significance (e.g., rumination and gender in the synchronous group), all effect sizes were small to moderate and non-significant. These findings suggest that dropout was not associated with specific participant characteristics.
The Perception of the Program
At the end of the posttest, participants were asked to rate the extent to which the program met their expectations on a scale from 0 to 4, with an option to provide additional comments. Of the 62 respondents (81% response rate), the average rating was 3.16 (SD = 0.61). The highest rating, 4 (definitively yes), was selected by 17 participants, while the lowest, 2 (hard to say), was chosen by 7 participants. Among those least satisfied, elaborated responses highlighted concerns such as the large number of exercises and the irritating need for sustained focus during exercises (n = 2), frustration with the difficulty of establishing a habit and maintaining regular practice (n = 2), and challenges in translating mindfulness knowledge and skills into self-efficacy (n = 1). Conversely, among participants whose expectations were met, the most common themes in their comments included noticeable improvements in mood and stress reduction (n = 12), increased self-awareness and new insights (n = 6), and perceived benefits of the program (n = 6). Additional comments (n = 9) covered recommendations for the researchers and reflections on the challenges of mindfulness practice.
Discussion
The aim of the study was to evaluate the effectiveness of an online MBCT intervention in individuals experiencing mild to moderate depression, and to compare two delivery formats—online group synchronous MBCT and guided asynchronous MBCT. Furthermore, the study aimed to identify key mechanisms of change. Results indicated that both intervention formats led to significant improvements across all measured outcomes, including depressive symptoms, resilience, self-compassion, rumination, cognitive fusion, experiential avoidance, and mindfulness. Importantly, the study focused on participants with mild to moderate depressive symptoms, as individuals with severe depression or marked functional impairment were excluded for ethical and safety reasons. Thus, the findings should be interpreted within this population and cannot be generalized to more severe clinical cases.
At posttest, there were no significant differences between the synchronous and asynchronous conditions, suggesting that both delivery formats may be comparably effective in reducing psychopathological symptoms and enhancing self-regulation. Although a difference in depressive symptoms was observed at follow-up, this finding should be interpreted with caution given the small and unbalanced follow-up sample and the higher attrition observed in the asynchronous condition. The study was not designed as a formal non-inferiority trial, and the sample size may have been insufficient to detect small between-group effects. Therefore, while the overall pattern supports comparable short-term benefits, these results should not be interpreted as definitive evidence of equivalence between the two formats. Future studies with larger and more balanced samples are needed to verify these preliminary indications. Despite this limitation, the overall pattern of results remains consistent with prior research demonstrating the effectiveness of online MBCT in reducing symptoms of anxiety and depression (Boettcher et al., 2014; Holas & Wardęszkiewicz, 2026; Liu et al., 2024; Nissen et al., 2020; Rodrigues et al., 2024; Segal et al., 2020, and in promoting resilience (Holas & Wardęszkiewicz, 2026). Moreover, the results align with the theoretical framework of MBCT, which posits that cultivating mindfulness—defined as nonjudgmental awareness of the present-moment (Kabat-Zinn, 2015)—interrupts maladaptive cognitive and emotional patterns such as rumination and cognitive fusion (Foroughi et al., 2020). By fostering the ability to observe thoughts and feelings as passing mental events, rather than identifying with them (Teasdale et al., 2002), mindfulness is theorized to reduce the risk of depressive relapse (Segal et al., 2013). Supporting this model, the present study identified mindfulness and cognitive fusion as the most robust mediators of treatment response. Similar findings were reported by Dimidjian et al. (2023), who observed that improvements following online MBCT were mediated by decentering, mindfulness, and reductions in rumination. Notably, improvement in cognitive defusion was observed despite the absence of the specific session typically dedicated to this concept in standard MBCT (“Thoughts are not facts”). This finding suggests that the capacity to relate to thoughts in a decentered way may develop more broadly throughout the MBCT training, even in its abbreviated format.
Despite the comparable efficacy across conditions, notable differences in attrition emerged between the two online abbreviated MBCT formats. Specifically, 45% of participants in the asynchronous condition discontinued the intervention prior to the posttest, compared to 28% in the synchronous group. These figures are within the range observed in previous online MBIs, where dropout rates have varied from 8 to 65% (Sommers-Spijkerman et al., 2021) and from 2.5% to 57%, with a mean of 25.8% (SD = 17.1) in another meta-analysis (Reangsing et al., 2023).
In the present study, completer – non-completer analyses did not reveal significant baseline differences, suggesting that dropout was not driven by symptom severity or demographic factors. Nevertheless, attrition may still have influenced the results – particularly if it was related to unmeasured variables such as motivation, engagement, or perceived support. While the mixed-model approach helps mitigate the effects of missing data under the missing-at-random assumption, unequal dropout between groups may have reduced statistical power and introduced uncertainty regarding long-term outcomes. Consequently, the results, especially at follow-up, should be interpreted with caution.
While no prior study has directly compared synchronous and asynchronous mindfulness-based interventions for depression, findings from broader online intervention literature consistently show that synchronous formats—characterized by real-time interaction and therapist guidance—are associated with greater adherence (Andersson & Titov, 2014; Mammarella et al., 2024). In contrast, asynchronous formats often show higher attrition, likely due to limited support and a lack of immediate feedback (Wolever et al., 2022). Nonetheless, asynchronous delivery offers important advantages, including time flexibility, scalability, and lower operational demands (Andersson & Titov, 2014). Given the comparable symptom reduction observed in both formats, the question may no longer be which format is superior in effectiveness, but rather how to optimize user engagement and minimize dropout, particularly in less guided interventions. Future studies should focus on developing and testing strategies to enhance adherence in asynchronous interventions, such as reminders, chatbot-guidance, or hybrid formats.
The findings suggest that structured, evidence-based programs like online MBCT—whether delivered synchronously or asynchronously—may serve as accessible, low-threshold interventions for the depressed population. In real-world healthcare, such interventions could be recommended following psychiatric consultations in less severe cases or offered as a meaningful form of support during waiting periods for in-person psychotherapy. Promoting early access to online interventions targeting self-regulation and mindfulness could help prevent symptom escalation and reduce long-term treatment needs.
Limitations and Future Research
One limitation of this study is that not all components of the intervention were delivered within a single, integrated study platform. While participants in the asynchronous condition completed the entire program within the platform, those in the synchronous condition attended live sessions via external tools such as Zoom or Google Meet. Additionally, mindfulness instructors provided external resources for guided meditation practice (e.g., personal websites or YouTube links). Under these circumstances, it was not possible to comprehensively track participant engagement in the synchronous condition. This use of external materials limited the ability to ensure consistency and full control over the intervention content across participants.
Another limitation concerns the lack of systematic recording and analysis of chat box activity. Although the chat function was available in both formats and appeared to serve different purposes (organizational in the synchronous condition and more social in the asynchronous one), the absence of objective data prevented a detailed understanding of participants’ interaction patterns and the role of online communication in engagement and adherence. A second limitation concerns the use of a waitlist control group rather than an active comparator. Although a waitlist design controls for some nonspecific factors, such as the passage of time, it may overestimate treatment effects and does not reflect real-life behavior, where individuals often search for alternative forms of support while waiting (Cunningham et al., 2013; Freedland et al., 2011). Moreover, the absence of a follow-up assessment in the control group limits the ability to compare long-term outcomes across all conditions. However, requiring participants with depression to remain without access to intervention for over 4 months was considered ethically inappropriate. Future studies should consider including an active control, such as treatment-as-usual (TAU) with a follow-up assessment. Another limitation involves the demographic homogeneity of the sample, which was predominantly female and well-educated. This overrepresentation is typical in mindfulness-based intervention research, where women often account for more than 70% of participants (Eichel et al., 2021). However, it restricts the generalizability of the findings. Future research should prioritize the inclusion of more diverse populations to better understand the applicability and impact of online MBCT across sociodemographic groups.
Additionally, individuals with severe depressive symptoms or marked functional impairment were excluded during screening for ethical and safety reasons, as online MBCT without continuous therapist monitoring may not provide adequate support for high-risk participants. While this decision ensured participant safety and intervention appropriateness, it also limits the generalizability of the findings to individuals with mild to moderate depression. Future studies could explore the safety and effectiveness of online MBCT in more severe cases when supported by closer clinical supervision or blended-care models.
Beyond the characteristics of the sample, several methodological aspects may also have influenced the results and should be considered when interpreting the findings. All outcomes in this study were assessed via self-report questionnaires. While the MINI was used for diagnostic screening during recruitment, the absence of clinician-rated or behavioral outcome measures may introduce biases. Incorporating objective assessments in future trials would enhance the validity of the findings.
Finally, the intervention was a shortened adaptation of the standard 8-week MBCT protocol, delivered over six weeks. Although the content remained consistent with MBCT’s core structure, the shortened duration may have limited the opportunity for skill consolidation or depth of practice. Future research should explore the comparative effectiveness of full-length and brief MBCT formats to better understand how modifications impact outcomes and adherence.
Building on the present findings, future research could explore the effectiveness of various engagement strategies—such as incorporating chatbots or blending design with other forms of real-time feedback—to improve adherence in asynchronous formats. In addition, systematically monitoring and analyzing chat activity could provide valuable insights into participants’ interaction patterns, the role of peer and therapist communication in maintaining engagement, and how online social support shapes adherence and outcomes. Efforts to recruit more diverse samples, particularly with regard to gender, education level, and digital literacy, would also help address current limitations in generalizability. Additionally, studying the impact of intervention length may offer valuable insights, as online MBIs vary widely in duration, typically ranging from 2 to 12 weeks (Spijkerman et al., 2016). Understanding how program length influences both adherence and perceived effectiveness could help optimize delivery for different populations. Future research could also explore individual characteristics that predict greater benefit from one delivery format over another, including factors such as self-discipline, motivation, attitudes towards psychological online interventions or confidence in therapy effectiveness.
The present study demonstrated that both synchronous group and asynchronous formats of online MBCT may serve as effective interventions for individuals experiencing mild to moderate depressive symptoms. While the synchronous format was associated with higher completion rates, the asynchronous format offers greater time flexibility and showed comparable effects in reducing depression and anxiety, as well as enhancing resilience, self-compassion, mindfulness, and cognitive defusion. These findings support the scalability of MBCT and highlight the importance of offering diverse delivery formats to accommodate individual needs and preferences.
Acknowledgements
We would like to thank Marta Formela for her support with statistical analyses. We are also grateful to the mindfulness teachers—Filip Kołodziejczyk, Dorota Wojtczak, Marcin Nowacki, and Krystyna Rybińska—for their contribution and guidance in delivering the intervention. We would like to thank Jan Lis for his assistance with software-related aspects of the study
Declarations
Ethics Approval
The study was approved by the Ethics Committee of the Psychology Faculty at University of Warsaw (NR: 11/04/2023).
Informed Consent Statement
Informed consent was obtained from all participants prior to study participation.
Use of Artificial Intelligence
AI was used for editing the manuscript to improve English language.
Conflict of interest
The authors declare no competing interests.
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