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. 2025 Jul 29;41(4):e70083. doi: 10.1002/smi.70083

The Cumulative Effect of a 12‐Week Online Mindfulness‐Based Meditation Intervention Programme on Autonomic Nerve Functions by Pupillary Light Reflex: A Pilot Randomised Controlled Trial

Koichiro Adachi 1,✉, Ryu Takizawa 1,2,✉
PMCID: PMC12306148  PMID: 40728207

ABSTRACT

This study aimed to determine whether online‐guided mindfulness‐based interventions (MBIs) in daily life improve autonomic nervous system function as measured by the pupillary light reflex (PLR) in healthy subjects. A total of 94 university students were randomly allocated to either an intervention group or a waitlist control group. Participants practiced single‐session meditation in a laboratory. During the intervention period, the participants practiced brief online mindfulness meditation for 12 weeks. PLR and psychological indices were measured before and after single and multiple mindfulness sessions. Using a multiple‐regression analysis controlling for the baseline values, participants in the intervention group showed significantly decreased emotional fluctuations and significantly increased relaxation compared to those in the control group in a single session, whereas no significant differences in physiological indices were detected. In 12‐week multiple sessions, participants in the intervention group showed significantly decreased state anxiety (p = 0.05), and marginally significantly decreased sympathetic nervous system activation (VD, p = 0.08) and perceived stress (p = 0.07) compared to those in the control group. These results suggest that the effects of mindfulness meditation on autonomic nerve function may be cumulative. These findings highlight the preventive effects of continuing online‐guided MBIs in a healthy population and the potential usefulness of pupilometers in monitoring intervention effects. The applicability of pupillometry is further supported by the finding that MBIs improved psychological indices.

Trial Registration: This study was not pre‐registered

Keywords: internet intervention, meditation, mindfulness, pupillary light reflex, pupillometry

1. Introduction

The need for preventive psychological interventions has been emphasised. Mendelson and Eaton (2018) suggest that many interventions to prevent mental disorders are effective, economical, and cost‐effective and recommend promising areas for further development. However, the current impact of preventive interventions remains uncertain because it is impractical to deliver these interventions to the community due to limited healthcare resources (Ebert et al. 2017). The limitations of prevention programs can be overcome through online interventions, which have advantages such as affordability and portability (Creswell 2017; Ebert et al. 2017).

Mendelson and Eaton (2018) also recommend mindfulness‐based interventions (MBIs) as a promising area. Mindfulness, defined as purposeful and non‐judgemental present‐moment awareness (Kabat‐Zinn 2003), has been shown to be effective for both physiological and psychological indices in non‐clinical populations (Pascoe et al. 2017; Reive 2019; Galante et al. 2021). However, preventive online MBIs have a minimal effect on psychological indices, due to a floor effect, in which healthy populations are likely to have less room for improvement than clinical populations (Spijkerman et al. 2016). It is important to rigorously and multidimensionally validate the effectiveness of online MBIs in combination with objective indicators, such as biomarkers.

The autonomic nervous system (ANS), comprising the sympathetic (SNS) and the parasympathetic nervous system (PNS),maintains the state of the mind and body by regulating responses and promoting recovery (Nesse et al. 2016). Previous studies have suggested that hyperactivation of the SNS and deactivation of the PNS may be linked to major depressive disorder (Kemp et al. 2010; Koch et al. 2019; Wu et al. 2023).

While some systematic reviews have shown that MBIs decrease SNS activation and increase PNS activation (Churchill et al. 2024; Heckenberg et al. 2018; Pascoe et al. 2017), the evidence is limited due to methodological issues such as small samples, a lack of a control group, a lack of power, and a lack of baseline measurements in several of the included studies (Pascoe et al. 2017; Reive 2019). Thus, randomised controlled trials (RCTs) with sufficient sample sizes are required to improve the evidence quality. In addition, heart rate variability (HRV) is primarily used to assess the ANS function in physiological research on mindfulness (Churchill et al. 2024). HRV refers to the fluctuation in the duration of R‐R intervals between adjacent heartbeats and reflects neurocardiac function generated by heart‐brain interactions and dynamic non‐linear ANS processes (Shaffer and Ginsberg 2017). However, it has been criticised for not truly measuring what it claims to measure (Churchill et al. 2024). Recent studies have begun addressing this issue by incorporating complementary physiological measures. For example, Jeong et al. (2025) provided evidence of a reduction in SNS activity due to MBI using intraneural measures of SNS activity directed to muscle.

Pupillometry has attracted attention as an established quantitative and non‐invasive tool for measuring ANS (Hall and Chilcott 2018). Pupillometry, as a measurement of the ANS, is categorised as pupillary light reflex (PLR), the task‐related pupillary response to emotional or cognitive stimuli (Ferencová et al. 2021), and pupillary hippus (Turnbull et al. 2017).

Vasquez‐Rosati et al. (2017) reported that negative images evoked greater pupillary contraction and weaker dilation in mindfulness meditation experts than in non‐meditators and that the experts had a faster physiological recovery to baseline levels. Kirk et al. (2022) conducted a single‐arm clinical trial on adults reporting post‐traumatic stress disorder symptoms to examine the effectiveness of web‐based cognitive behavioural therapy, mindfulness, and yoga programs. They demonstrated a significant pre‐post reduction in peak pupil dilation while the participants viewed negative images. Pomè et al. (2020) showed that pupillary oscillations in meditation experts increased by 53% in mindfulness meditation compared to baseline periods.

PLR describes the constriction and subsequent dilation of the pupil in response to light as a result of the antagonistic actions of the parasympathetically innervated iris sphincter muscles and sympathetically innervated iris dilator muscles; therefore, parameters of the PLR can be used as one of the important indicators for either sympathetic or parasympathetic modulation (Hall and Chilcott 2018). Recent PLR studies demonstrated that the pupil area at the peak of constriction in patients with depression was significantly larger than that in healthy controls (Wang et al. 2014) and that depressed adolescents had significantly lower contractile changes in the left eye than healthy adolescents (Mestanikova et al. 2017). Although PLR may be a promising biomarker for detecting mental conditions, to the best of our knowledge, no study has used PLR to investigate the effects of MBIs. If pupil indicators can be improved in a healthy population, the potential use of pupillometry for prevention can be demonstrated.

In addition, most studies have only demonstrated that meditation experts differ in the ANS from non‐practitioners, or that one‐session mindfulness practice could change ANS functions before and after the one‐session practice. Therefore, research on the cumulative effects of continuous mindfulness practice using pupillometry is limited. Grossman et al. (2017) stated that a temporary change in a laboratory might be distinguished from a cumulative change in everyday life because experimental demand characteristics in laboratory studies lead participants to consciously or unconsciously behave in a certain manner.

This study aimed to determine whether online‐guided MBIs in daily life improve ANS function, as assessed by PLR, in healthy subjects. The PLR was measured before and after both single and multiple mindfulness sessions to compare the effects of one‐ and multi‐session mindfulness meditation. We hypothesised that routine MBIs would be associated with changes in psychological indices, a decrease in SNS indices, and an increase in PNS indices. In addition, we hypothesised that the cumulative effect of multiple sessions would be greater than that of a single session.

2. Methods

2.1. Study Design

This study design was a crossover‐design RCT with a waitlist control group. Eligible participants were allocated to either an intervention group or a control group. The data were collected in the laboratory in June and July 2021 (T0), September and October 2021 (T1), and January 2022 (T2). The study protocol was approved by the ethics committee of the author's organisation (Approval No. 21–18, dated November 5, 2021). The study was conducted in accordance with the Declaration of Helsinki.

2.2. Participants

The participants were recruited through classroom announcements and open calls from websites. The inclusion criteria were undergraduate and graduate students at Japanese universities. The exclusion criteria were as follows: (1) aged younger than 18 years, (2) currently diagnosed with a mental disorder, (3) K6 (Japanese version) score ≥ 13 (Furukawa et al. 2008; Kessler et al. 2002) (to exclude participants with clinically severe depressive/anxiety symptoms), and (4) inability to participate in laboratory measurements.

2.3. Sample Size

Power analysis was conducted using the G*Power software version 3.1.9.7. In this study, the between‐group effect size was assumed to have small effect size (η 2 = 0.03; equivalent to Cohen's f = 0.176) based on previous research (Wolever et al. 2012). The repeated measures scores were expected to have a moderate to strong correlation of 0.5. To achieve 80% power, a total sample size of 66 participants was required. Considering an estimated attrition rate of approximately 15% based on similar previous studies (Wolever et al. 2012), we planned to recruit 78 participants and assign 39 participants to each group.

2.4. Procedure

Applicants completed a web form that included a pre‐screening survey (K6). Participants who met the criteria were randomly assigned to either the intervention or the control group. Randomisation was conducted using a computerised system in a ratio of 1:1 and was independently managed by research staff after recruitment was completed. Due to the nature of the study, blinding was not feasible, as participants engaged in the meditation independently by following a guide.

Each participant provided informed consent, completed the pre‐test questionnaires via a web form, and attended a 60‐min measurement in the laboratory. Participants reported their emotion and relaxation levels and had their pupil responses measured before and after they underwent one‐session guided intervention or active control (T0). Participants in the intervention group began their daily mindfulness practice for 12 weeks. The participants in the control group were asked to spend the control period as usual.

After 12 weeks, the participants completed a post‐test measurements. Participants in the control group reported their emotional and relaxation levels and had their pupil responses before and after they underwent one‐session meditation (T1), as did participants in the intervention group at T0. After the T1 measurements, participants in the control group started daily mindfulness practice for 12 weeks. After 12 weeks, the participants in the control group completed a post‐intervention questionnaire and underwent physiological measurements (T2). Electrocardiogram data were also collected for the purpose of analysing HRV. However, the HRV data are not presented here, as the current report focuses exclusively on PLR parameters.

2.5. Intervention

The MBI was conducted using guided audio. The participants listened to ‘Breathing Meditation’ (5 min 31 s) and practiced meditation in the laboratory. During the intervention, participants entered their assigned identifiers and passwords on the website and listened to audio recordings daily. Log‐in data were recorded automatically and used to calculate the number of days each participant practiced. The content was changed monthly (every 4 weeks) based on previous studies (Armstrong 2012). The reason for using multiple meditation techniques is that mindfulness meditation consists of focus attention (FA) meditation and open monitoring (OM) meditation, and the structure of first starting with FA meditation and then losing the OM meditation is considered effective (Lutz et al. 2008). The participants listened to ‘Breathing Meditation’ (5 min 31 s) for the first month, ‘Body Scan Meditation’ (3 min 34 s) for the next month, and ‘Body and Sound Meditation’ (3 min 47 s) for the last month. The first two correspond to FA meditation and the last to OM meditation. The prerecorded audio mindfulness meditations were created from Japanese scripts based on those used by the UCLA Mindful Awareness Research Center (2021). To promote adherence, reminder emails were sent twice per week throughout the intervention period.

Participants in the control group listened to an educational excerpt of a radio programme from the Japan Broadcasting Corporation (2021) in the laboratory, which was about preventing dementia. The time of the active control was the same as that of ‘Breathing Meditation’. Figure 1 illustrates the intervention timeline and components.

FIGURE 1.

FIGURE 1

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The intervention timeline and components.

2.6. Measurements

2.6.1. Sociodemographic Variables

The participants' age, sex, course, marital status, living status (alone or with others), household income, psychiatric history, disease status, medications, medicines, and previous relaxation practice experiences, including mindfulness, were recorded using a questionnaire. These variables were selected based on established guidelines and previous studies demonstrating their relevance to ANS functioning (e.g., Kirk et al. 2022; Steinhauer et al. 2022). The number of years of education of the participants' parents was also obtained as an indicator of socioeconomic status.

2.6.2. Pupillometry

Pupil responses were recorded using an electronic near‐infrared pupillometer (DK‐101, Scalar Corporation, Tokyo, Japan). Changes in pupil size were measured by placing a pupillometer over the left eye for 6 s, during which the pupil was briefly illuminated (0.5 s) following a 1‐s baseline. The video signal was processed every 33.33 ms (30 fps) to determine pupil diameter, with a resolution of 1280 × 720. The device emitted white light at an intensity of 600 lx. The ambient light level in the laboratory was approximately 820 lx. For artefact rejection, data with (i) no signal, (ii) no pupil constriction, (iii) interference with eyelashes, or (iv) Wi‐Fi noise between the pupilometer and the measurement tablet were excluded from the statistical analysis. After applying these criteria, 82.61% of the trials remained for analysis.

The following indicators assessed the measures of autonomic nerve function based on the pupillary response (Figure 2). The dilation time constant (T5) and maximum dilation velocity (VD) are indicators of pupil dilation that measure sympathetic nerve activation. T5 is 63% of the recovery time from maximum pupil constriction (unit: s). VD is the maximum velocity of pupil dilation (mm/s). T5 and VD are commonly used indicators of sympathetic activation (Hall and Chilcott 2018; Muppidi et al. 2013). The maximum constriction amplitude (A3), relative constriction amplitude (CR), and maximal constriction velocity (VC) are pupil constriction indicators that are commonly used to measure parasympathetic activation (Hall and Chilcott 2018). A3 is calculated as the difference between the baseline and minimum pupil areas (unit: mm2). CR is the contraction rate of the pupil and is calculated as the ratio of the minimum pupil area to the baseline pupil area. VC is the maximum velocity of pupil constriction (mm/s). The reliability of PLR indices has been previously reported by Isotani et al. (2000), showing excellent reliability for initial pupil diameter and A3, good for CR, fair for AC and VD, and poor for VC and T5 in healthy adults. For each variable, the distribution was assessed using Q‐Q plots. When extreme outliers clearly distorted the distribution, those values were removed based on Smirnov‐Grubbs test and visual inspection.

FIGURE 2.

FIGURE 2

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Description of measurement symbols.

2.6.3. One‐Session Intervention

The effect of the one‐session intervention was measured using psychological indices that capture state changes.

2.6.4. The Rating Scale of Relaxation

A rating scale for relaxation was used to assess the degree of participants' relaxation (Nedate and Agari 1984). This scale comprises four items rated on a 10‐point scale. The four items are as follows; feeling high (1)—stable (10), tense (1)—relaxing (10), anxiety (1)—relief (10), and restrictive (1)—free (10). The sum of the four scores was calculated as the relaxation score. Internal consistency reliability was α = 0.835 in this sample.

2.6.5. PANAS

The Positive and Negative Affect Schedule (PANAS) was used to measure the degree to which the participants had experienced positive and negative emotions within the past week (Watson et al. 1988). The PANAS consists of 20 items (10 positive and 10 negative) rated on a five‐point Likert scale ranging from 1 (‘not at all’) to 5 (‘extremely’). Sample items for positive emotion scores include ‘interested’ and ‘proud’, while those for negative emotion scores include ‘distressed’ and ‘upset’. The total scores of the 10 positive and 10 negative items were calculated separately to obtain the positive and negative emotion scores. The Japanese version has demonstrated high reliability and validity (Kawahito et al. 2012). In this sample, the internal consistency reliabilities of positive and negative emotions were α = 0.836 and 0.868, respectively.

2.6.6. STAI‐S

The 20‐item Spielberger State‐Trait Anxiety Inventory (STAI; Spielberger et al. 1970) state version was used to assess state anxiety levels, that is, participants felt at the moment. Responses were provided on a four‐point scale from 1 (never) to 4 (always). Sample items are: ‘I am tense’, and ‘I feel nervous’. The total scores of the 20 items were calculated to obtain the state anxiety score. Shimizu and Imae (1981) translated the Japanese version of STAI and confirmed its reliability and validity. The internal consistency reliability was α = 0.915 in this sample.

2.6.7. Multi‐Session Intervention

The effects of the multi‐session intervention were measured using psychological indicators that measure long‐term change, in addition to psychological indicators that capture state changes used in the single session.

2.6.8. PSS

The Perceived Stress Scale (PSS) is a 14‐item self‐report questionnaire intended to measure the degree of stress perceived by an individual in their life within the past month (S. Cohen et al. 1983; S. Cohen and Williamson 1988). Responses were given on a four‐point scale from 0 (never) to 4 (very often). A sample item is: ‘In the last month, how often have you felt that you were unable to control the important things in your life?’ The total scores of the 14 items were calculated to obtain the PSS score. Sumi (2003), (2006) translated the Japanese version of PSS and confirmed its reliability and validity. Internal consistency reliability was α = 0.815 in this sample.

2.6.9. STAI‐T

The 20‐item Spielberger State‐Trait Anxiety Inventory trait version (STAI‐T; Spielberger et al. 1970) was used to assess trait anxiety levels, that is, how participants generally felt. Responses were provided on a four‐point scale from 1 (never) to 4 (always). Sample items are: ‘I tyre quickly’, and ‘I worry too much over something that really doesn't matter’. The total scores of the 20 items were calculated to obtain the trait anxiety score. Shimizu and Imae (1981) translated the Japanese version of STAI‐T and confirmed its reliability and validity. Internal consistency reliability was α = 0.899 in this sample.

2.7. Analytical Method

The RCT was conducted using a crossover design. The means and standard deviation (SD) under the intervention and control groups were calculated. Baseline differences across the groups were examined using independent t‐tests for normally distributed variables and Wilcoxon rank‐sum tests for non‐normally distributed variables. Normality of the data was assessed using the Kolmogorov–Smirnov test. For categorical values, baseline differences across the groups were examined using the chi‐square test. When at least one cell had an expected value of less than five, the baseline differences across groups were examined using Fisher's exact test.

Changes before and after the intervention or control period were assessed using paired t‐tests. When the Kolmogorov–Smirnov test did not satisfy normality for the difference between the pre‐ and post‐test values, the Wilcoxon signed‐rank test was used to evaluate the difference between the pre‐ and post‐test values. Effect sizes for paired t‐tests were reported as Cohen's d, with cutoff values of 0.2, 0.5, and 0.8 for small, medium, and large effects, respectively (J. Cohen 1988). Those for Wilcoxon signed‐rank test were reported as Cohen's r, with cutoff values of 0.1, 0.3, and 0.5 for small, medium, and large effects, respectively (J. Cohen 1988).

To compare the changes in values across groups, we used multiple regression analysis controlling for pre‐intervention values. The model regressed the outcomes on the assignment (1 for the intervention group and 0 for the control group), considering the pre‐intervention values as a covariate. Effect sizes for multiple regression analysis were reported as Cohen's f 2, with cutoff values of 0.02, 0.15, and 0.35 for small, medium, and large effects, respectively (J. Cohen 1988). In comparisons showing any significant baseline differences, we additionally controlled for pre‐intervention values that were significantly different between the groups to verify the robustness of the results. All tests were two‐tailed with an alpha level of 0.05. Missing data were handled using listwise deletion in all analyses. Statistical analyses were conducted using R Studio version 2023.6.0.421 and R version 4.2.2.

3. Results

3.1. Participant Flow

A total of 100 participants applied for this study. Six participants dropped out before random allocation because they had K6 scores of ≥ 13. A total of 94 participants were included in this study. Among the 94 participants, 47 each were randomly assigned to the intervention and control groups. Eighty participants completed single‐session pre‐ and post‐intervention measurements at T0. Fourteen participants were excluded from the study because of lost contact before the T0 measurement, technical issues with pupillometry, or withdrawal of informed consent later. The loss of contact was considered to be primarily due to loss of interest or motivation. A total of 65 participants completed the multi‐session intervention and pre‐post measurements at T0 and T1. Fifteen participants were excluded from the multi‐session analysis because they did not undergo the T1 measurements. Thirty‐six participants in the control group completed a single session of pre‐post measurement at T1. Thirty‐one participants in the control group completed the multisession intervention and pre‐post measurements at T1 and T2. Data from six participants were excluded from the multi‐session analysis because they were absent from the T2 measurement.

A total of 116 pre‐post data points were included in the single‐session analysis. A total of 96 pre‐post data points were included in the multi‐session analysis. The number of participants at each stage is illustrated in Figure 3.

FIGURE 3.

FIGURE 3

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Intervention flowchart. Abbreviations: IC, informed consent.

3.2. Baseline Data

Tables 1 and 2 show the demographic characteristics and baseline values of the participants who completed pupillometry measurements before and after the one‐session intervention at T0. Table 1 shows the demographic and clinical characteristics and baseline psychological values. Table 2 lists the baseline physiological parameters. The sample included 80 participants (mean age, 21.61 years [SD, 3.95 years]; females: 53.8%; living alone: 47.5%). No participant had diseases, such as cardiovascular or endocrinological, which significantly affect ANS activity. None of the participants reported taking any medication that could affect the ANS (Steinhauer et al. 2022). No demographic characteristics and baseline values differed significantly between the groups. On average, participants in the intervention group practiced for 24.37 days [SD, 27.76 days].

TABLE 1.

Demographic and clinical characteristics and baseline values.

Total Intervention group Control group Group difference
Mean SD Mean SD Mean SD Test Estimate df p‐value
n 80 41 39
Age 21.61 3.95 22.24 5.10 20.95 2.05 Z −1.60 0.11
Sex, women/men 37/43 17/24 20/19 χ 2 0.43 1 0.51
Course, undergraduate/graduate 59/21 29/12 30/9 χ 2 0.14 1 0.71
Living, alone/together 28/37 9/18 19/19 χ 2 1.17 1 0.28
Psychiatric history, yes/no 77/3 40/1 37/2 Fisher 2.14 0.61
Psychiatric history for family, yes/no 64/6 28/3 36/3 Fisher 1.05 1.00
Relaxation experience, yes/no 9/70 5/36 4/34 Fisher 0.82 1.00
Parents' education, years 16.04 1.86 16.17 2.01 15.90 1.70 Z −1.08 0.30
Household income (million yen) 8.64 3.48 8.68 3.47 8.61 3.52 t 0.09 76 0.93
Perceived stress 28.64 7.79 28.39 7.72 28.90 7.96 t −0.29 78 0.77
Trait anxiety 48.15 10.39 46.39 10.91 50.00 9.61 t −1.57 78 0.12
State anxiety 39.88 9.98 38.85 11.04 40.28 9.39 t −0.62 78 0.54
Relaxation 26.83 6.69 27.37 6.83 25.90 7.33 t 0.93 78 0.36
Positive emotion 31.13 7.90 30.76 8.10 31.13 7.92 t −0.21 78 0.84
Negative emotion 20.45 8.13 19.71 8.20 20.72 8.71 t −0.53 78 0.59
T5 2.07 1.25 2.16 1.28 1.97 1.22 t −0.68 77 0.50
VD 14.26 5.23 14.41 4.98 14.09 5.55 t −0.27 73 0.79
A3 13.97 5.75 14.13 5.26 13.79 6.30 t 0.80 78 0.43
CR 0.57 0.09 0.55 0.10 0.58 0.08 t 1.34 71 0.18
VC −48.01 23.14 −47.23 21.18 −48.88 25.43 t −0.30 68 0.76
Initial pupil diameter 5.73 0.86 5.79 0.83 5.66 0.90 t 0.69 78 0.49
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Note: Z, Wilcoxon rank‐sum test; χ 2, chi‐square test; Fisher, Fisher's exact test.

TABLE 2.

Comparison of short‐term changes in the intervention and control groups.

Intervention condition (n = 77) Pre/post comparison Control condition (n = 39) Group comparison
Pre Post Estimate p‐value ES Pre Post b SE t‐value p‐value Cohen's f 2
State anxiety 40.64 10.03 34.27 6.30 −7.61 0.00 −0.68 40.95 8.74 36.05 7.61 −1.56 0.93 −1.67 0.10 0.03
Relaxation 26.33 6.30 30.79 5.65 5.45 0.00 0.74 26.26 6.59 28.97 6.14 1.83 1.08 1.69 0.09 0.03
Positive emotion 30.76 7.93 26.25 7.87 −7.07 0.00 −0.58 31.51 7.78 28.85 7.83 −2.17 1.07 −2.03 0.04 0.04
Negative emotion 20.82 7.65 16.12 6.08 −7.71 0.00 −0.68 21.23 8.09 18.05 7.20 −1.80 0.78 −2.32 0.02 0.05
T5 2.00 1.17 1.75 1.01 −2.66 0.01 0.22 1.95 1.22 1.73 0.99 0.00 0.17 −0.01 0.99 0.00
VD 14.23 5.30 13.63 3.95 1.11 0.27 −0.13 13.66 4.33 12.49 3.68 0.89 0.69 1.30 0.20 0.02
A3 13.78 5.10 12.59 4.70 −2.59 0.01 −0.24 13.58 6.35 12.80 5.78 −0.35 0.62 −0.57 0.57 0.00
CR 0.56 0.10 0.55 0.08 −0.20 0.85 −0.02 0.58 0.09 0.55 0.08 0.01 0.01 1.12 0.26 0.01
VC −45.25 18.63 −42.52 15.94 1.22 0.23 0.16 −48.14 25.47 −40.92 20.39 −2.83 3.04 −0.93 0.35 0.01
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Note: All pre/post comparisons were conducted using t‐tests, except for T5, which was analysed using the Wilcoxon signed‐rank test. Degrees of freedom for t‐tests in pre/post comparisons were generally 73, except for A3 (df = 76), CR (df = 72), and VC (df = 75), due to outlier exclusion and missing data. Degrees of freedom for t‐tests in group comparisons were generally 110, except for T5, A3 (df = 113), VD (df = 104), and CR (df = 105).

Abbreviations: ES, effect size.

3.3. One‐Session Mindfulness

Table 2 shows the mean and SD values, pre‐post comparisons in the intervention condition, and between‐group comparisons. Pre‐post comparisons revealed that participants in the intervention condition demonstrated significant pre‐post‐intervention increases in relaxation and significant decreases in state anxiety, positive and negative emotions, T5 and A3. Participants in the intervention condition demonstrated significant decreases in positive and negative emotions (positive emotions, b = −2.17, t (110) = −2.03, p = 0.04, Cohen's f 2 = 0.04; negative emotions, b = −1.80, t (110) = −2.32, p = 0.02, Cohen's f 2 = 0.03) in comparison with those in the control group after controlling for the pre‐intervention values (Figure 4). The participants in the intervention group demonstrated marginally significant increases in relaxation (b = 1.83, t (110) = 1.69, p = 0.09, Cohen's f 2 = 0.03), and a marginally significant decrease in state anxiety (b = −1.56, t (110) = −1.67, p = 0.10, Cohen's f 2 = 0.03) in comparison with those in the control group after controlling for the pre‐intervention values.

FIGURE 4.

FIGURE 4

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Changes in positive and negative emotion scores before and after the one‐session intervention. Bar plots represent mean values ± SD for each group at pre‐ and post‐intervention time points. Individual data points are overlaid as grey dots. Significant pre‐post or between‐group differences are annotated with p‐values.

3.4. Twelve‐Week Multi‐Session Mindfulness Programme

Table 3 shows the mean and SD values, pre‐post comparisons in the intervention group, and between‐group comparisons. Pre‐post comparisons revealed that participants in the intervention group demonstrated significant decreases in T5, VD and A3, marginally significant increases in VC, and marginally significant decreases in PSS, trait anxiety and positive emotions. The participants in the intervention group demonstrated significant decreases in state anxiety (b = −3.37, t (91) = −2.03, p = 0.05) compared to those in the control group after controlling for pre‐intervention values (Figure 5). Marginally significant decreases were also observed in PSS (b = −2.41, t (91) = −1.83, p = 0.07, Cohen's f 2 = 0.04), VD (b = −1.71, t (93) = −1.77, p = 0.08, Cohen's f 2 = 0.03) and A3 (b = −1.47, t (93) = −1.92, p = 0.06, Cohen's f 2 = 0.04).

TABLE 3.

Comparison of long‐term changes in the intervention and control groups.

Intervention group (n = 59) Pre/post comparison Control group (n = 36) Group comparison
Pre Post Estimate p‐value ES Pre Post b SE t‐value p‐value Cohen's f 2
PSS 29.46 7.17 27.90 7.44 −1.78 0.08 −0.20 29.25 8.17 30.31 7.28 −2.41 1.32 −1.83 0.07 0.04
Trait anxiety 49.00 8.80 47.66 7.81 −1.74 0.09 −0.17 50.28 9.77 49.94 6.94 −1.57 1.04 −1.50 0.14 0.02
State anxiety 40.80 9.19 39.53 8.51 −0.96 0.34 −0.14 40.86 8.87 43.00 8.29 −3.37 1.66 −2.03 0.05 0.05
Relaxation 26.32 5.50 26.77 5.63 0.50 0.62 0.08 26.11 6.76 25.09 5.50 1.61 1.08 1.50 0.14 0.02
Positive emotion 31.44 8.05 29.82 7.46 −1.99 0.05 −0.21 31.58 7.97 30.49 7.75 −0.61 1.25 −0.49 0.63 0.00
Negative emotion 21.56 7.99 20.55 8.09 −0.84 0.41 −0.13 21.50 8.24 22.71 7.29 −2.21 1.53 −1.44 0.15 0.02
T5 2.07 1.18 1.73 0.94 −2.12 0.04 −0.31 1.92 1.22 1.81 1.02 −0.11 0.19 −0.59 0.56 0.00
VD 14.12 5.17 12.79 3.58 −2.01 0.05 −0.29 14.22 5.24 14.53 6.22 −1.71 0.97 −1.77 0.08 0.03
A3 13.92 5.21 12.50 4.13 −2.98 0.00 −0.29 13.44 6.55 13.73 5.36 −1.47 0.76 −1.92 0.06 0.04
CR 0.55 0.10 0.56 0.09 0.92 0.36 0.14 0.58 0.09 0.56 0.10 0.01 0.02 0.63 0.53 0.00
VC −44.89 19.24 −40.32 11.13 1.93 0.06 0.28 −46.57 24.75 −42.99 15.84 2.47 2.80 0.88 0.38 0.01
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Note: All pre/post comparisons were conducted using t‐tests. Degrees of freedom for t‐tests in pre/post comparisons were generally 58, except for T5, A3 (df = 59), and VC (df = 57), due to outlier exclusion and missing data. Degrees of freedom for t‐tests in group comparisons were generally 91, except for Trait anxiety (df = 92), T5, A3 (df = 93), VD (df = 89), CR and VC (df = 88).

Abbreviations: ES, effect size; PSS, perceived stress scale.

FIGURE 5.

FIGURE 5

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Changes in VD and state anxiety before and after the multi‐session intervention. Bar plots show the mean values ± SD for each group at pre‐ and post‐intervention time points. Individual data points are overlaid as grey dots. Significant pre‐post or between‐group differences are annotated with p‐values.

4. Discussion

These findings suggest that participants in the intervention group had improved psychological indices compared to those in the control group after a single session, whereas no differences in physiological indicators were observed between groups. Participants in the intervention group showed decreased SNS activation (VD), state anxiety, and perceived stress compared to those in the control group over 12‐week multiple sessions.

The finding that MBIs can decrease indicators of SNS activation is consistent with the results of previous studies (e.g., May et al. 2016; Lindsay et al. 2018; Jeong et al. 2025). However, this is the first PLR study to detect the long‐term changes resulting from daily multi‐session mindfulness practice in a healthy population. These findings suggest that the effects of mindfulness meditation on ANS function may be cumulative and support the practical significance of continuing mindfulness training in healthy populations. In addition, these findings highlight the potential usefulness of pupillometry for monitoring intervention effects. The applicability of pupillometry is supported by the finding that brief mindfulness meditation improves psychological indices.

The finding that MBIs can decrease SNS activation, anxiety, and perceived stress and stabilise emotions might support the mechanism proposed in previous studies (Gotink et al. 2016; Reive 2019). According to Peters et al. (2017), the neurobiological pathway from acute stress to SNS activation involves the following mechanisms: the anterior cingulate cortex assesses the degree of uncertainty when acute stress is perceived. The amygdala initiates stress responses when future well‐being is uncertain or threatening. The amygdala activates the SNS and hypothalamus‐pituitary‐adrenal axis via the ventromedial hypothalamus and paraventricular nucleus. Reive (2019) proposed that MBIs might temper amygdala reactivity through learnt non‐judgemental in‐the‐moment awareness. According to a systematic review, MBIs can make more efficient prefrontal cortex inhibition of amygdala responses and improve emotion regulation (Gotink et al. 2016). This study suggests that MBIs might temper the amygdala response and SNS activation in a healthy population, making emotions more stable and making it easier to cope with stress and anxiety.

However, the finding that MBIs did not significantly increase the indicators of PNS activation is inconsistent with previous studies (e.g. Delgado et al. 2010; Adler‐Neal et al. 2020). One potential factor is the ceiling effect. In this study, the participants were healthy university students in a normal environment, whereas some previous studies have measured participants and situations that tend to have low PNS activity (Delgado et al. 2010; Adler‐Neal et al. 2020). The Scalar Corporation (Tokyo, Japan), which manufactures pupillometers, has indicated reference values for the general population ranging from 0.39 to 0.69 for CR, 5 to 15 for A3, and 24 to 44 for VC. This study was conducted on healthy university students, and the results were close to the upper limits, especially for A3 and VC.

4.1. Strength

Most mindfulness studies have investigated only self‐reported psychological measures. However, it is difficult to measure the effects of MBIs using only psychological scales because of recall bias, social desirability bias, and the cognitive skills needed to accurately report one's own experiences (Davidson and Kaszniak 2015; Visted et al. 2015). It is useful to combine subjective psychological indicators with objective physiological measures for assessing the effectiveness of MBIs more accurately. The key strengths of the present study include the integration of psychological indices and multiple physiological measures of ANS function.

Although some studies have explored the association between mindfulness and ANS function, the evidence remains limited. Another key strength is the scientific rigour based on its RCT methodology and larger sample size. Previous intervention studies examining the effects of mindfulness using pupillometry had small sample sizes and lacked randomisation (Vasquez‐Rosati et al. 2017, n = 20; Pomè et al. 2020, n = 44; Kirk et al. 2022, n = 22). Additionally, research on the cumulative effects of continuous mindfulness practice remains more limited than research on its temporary effects. To our knowledge, this is the first PLR clinical trial to investigate the effects of both single‐ and multi‐session MBIs in a healthy population within a preventive context.

4.2. Limitations

However, this study has several limitations. First, adherence (27%; 24.37/90 days) to the multi‐session online MBI was low. Therefore, low adherence may have been a source of bias. Low adherence is a common concern in many online intervention studies, often attributed to the use of an unguided self‐help approach and the absence of facilitators or therapists (Winter et al. 2022). The mean adherence rate in this study was comparable to that of a previous online MBI study (29%, Mak et al. 2018). To address this challenge, future research could incorporate strategies to enhance engagement, such as automated reminders, the ability to customise programme content or interact with features (Winter et al. 2022).

Second, this study employed a crossover RCT design to enhance the statistical power of the results. Because psychological intervention studies generally cannot eliminate the carryover effects of interventions by a washout period, this study employed a one‐way crossover design, similar to most psychological intervention studies. The parallel design analyses showed no significant group differences, but the same trend as the crossover design analyses such as VD of multiple sessions (t (59) = 0.96, p = 0.34, Cohen's f 2 = 0.02). Third, the target population of this study was mainly university students in the urban areas of Japan, and the study population was relatively healthy. Therefore, the applicability of the findings of this study to diverse populations, such as older adults and people with mental illnesses, is unknown. The generalisability of these findings to other populations should be explored in future studies. To address these limitations, we are currently conducting an intervention study using smartphone applications co‐developed with an application development company (Kurosawa et al. 2024).

Another limitation is that objective body mass index was not assessed. Weight abnormalities such as obesity or underweight affect ANS activity (Triggiani et al. 2017; Segal et al. 2022). Future studies should use objective height and weight data to control for the influence of body mass index on ANS indicators.

4.3. Future Perspectives

Future studies should be conducted with larger and more diverse samples, and the mechanisms of the MBIs and ANS function measured using pupillometry should be explored in more detail. Investigating the relationship between the PLR and psychological indices may enhance our understanding of these mechanisms. The association between changes in pupillometry and psychological indices is supported by the findings that multi‐session MBIs reduced SNS activation, anxiety and perceived stress. However, differences in emotion regulation strategies may moderate the correspondence between emotional stress responses and physiological responses (Campbell and Ehlert 2012). To validate the proposed mechanisms (Gotink et al. 2016; Reive 2019), future studies should examine the pathway linking biomarkers, emotional stress, and emotion regulation.

Investigating their associations with other physiological and neurological biomarkers may also clarify these mechanisms. PLR mainly reflects the central autonomic regulation, while HRV reflects the peripheral autonomic regulation (Hatsukawa and Ishikawa 2021). Although both HRV and PLR are reflected by ANS functions, they do not always correlate directly. For example, while partial associations have been observed in healthy adults (Bär et al. 2009), no significant correlation was found in healthy children (Daluwatte et al. 2012). These findings suggest that the two measures may provide complementary assessment of different aspects of the ANS function (Daluwatte et al. 2012).

In addition, PLR and HRV, particularly high‐frequency HRV indicating respiratory sinus arrhythmia, are also linked to emotion regulation (N. Cohen et al. 2015; Thayer and Lane 2009). Emotion regulation suggested to be improved by MBIs through more efficient prefrontal cortex inhibition of amygdala responses (Gotink et al. 2016). Ferencová et al. (2021) suggest that the pupils represent the gateway to the brain and recommend a complex research approach that integrated pupillometry with functional neuroimaging to explore the exact ‘brain‐pupil’ relationships. Lutz et al. (2009) investigated the interactions between the brain and the cardiovascular system during meditation and confirmed that compassion enhances emotional and somatosensory brain representations of others' emotions. However, their study focused on comparing experts and novices rather than assessing cumulative changes in MBIs in healthy individuals. Therefore, it is necessary to investigate the relationship between changes in brain function, such as the amygdala and prefrontal cortex, and changes in ANS function with pupillometry and long‐term recorded HRV following multi‐session MBI. With a better understanding of the physiological mechanisms underlying MBIs, pupillometry can be used as a biofeedback tool to monitor daily mindfulness training in both clinical and preventive settings.

Ethics Statement

The study protocol was approved by the Ethics Committee of the University of Tokyo (No. 21–18, Dated 11/5/2021).

Consent

Participants provided informed consent before data collection and were aware that they could withdraw at any time during the study. All data were de‐identified, and collected data and personal information were stored separately.

Conflicts of Interest

The authors declare no conflicts of interest.

Permission to Reproduce Material From Other Sources

This study does not include material from other sources that require permission to reproduce.

Acknowledgements

The authors would like to thank all the participants in this study. This work was funded by the Japan Science and Technology Agency (JPMJSP2108 to KA), the Japan Society for the Promotion of Science (JSPS) Grant‐in‐Aid for Scientific Research (JP16H05653, JP19K03278, 22H01091, 22K18582, 23K22362 and 25K21957 to RT) and the Royal Society and British Academy (AL150003 to RT). The funders had no role in data collection or analysis, decision to publish, or preparation of the manuscript.

Adachi, Koichiro , and Takizawa Ryu. 2025. “The Cumulative Effect of a 12‐Week Online Mindfulness‐Based Meditation Intervention Programme on Autonomic Nerve Functions by Pupillary Light Reflex: A Pilot Randomised Controlled Trial.” Stress and Health: e70083. 10.1002/smi.70083.

Funding: This work was funded by the Japan Science and Technology Agency (JPMJSP2108 to KA), the Japan Society for the Promotion of Science (JSPS) Grant‐in‐Aid for Scientific Research (JP16H05653, JP19K03278, 22H01091, 22K18582, 23K22362 and 25K21957 to RT) and the Royal Society and British Academy (AL150003 to RT).

Contributor Information

Koichiro Adachi, Email: adachi-koichiro342@g.ecc.u-tokyo.ac.jp.

Ryu Takizawa, Email: takizawar-tky@umin.ac.jp.

Data Availability Statement

The data sets generated and analysed during this study are not publicly available, as data sharing was not included in the informed consent. However, they can be obtained from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data sets generated and analysed during this study are not publicly available, as data sharing was not included in the informed consent. However, they can be obtained from the corresponding author upon reasonable request.

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