Mindfulness training has been gaining popularity in the past decade as a means of improving general well-being. This trend appears in response to the new stressors that have arisen with the increased stress of the 21st century. Studies have shown that the psychological state of metacognitive awareness encapsulated in mindfulness can promote the decreasing of stress as well as the secondary effect of improving sleep quality; both outcome measures of this study. While the body of research evaluating these benefits is growing, there is limited emphasis placed on the individual differences that can affect the overall efficacy of mindfulness training.

Our aim in this study is to observe the effects of mindfulness training on perceived stress levels as well as on sleep using subjective measures in a large sample of trainees. To achieve this, participants will be recruited from a pool of people who have signed up for a 4-week foundational mindfulness or 8-week mindfulness based stress reduction course at Brahm Centre. Questionnaires will be administered both before and after these courses to evaluate both stress levels and sleep habits as well as other factors which could contribute to the efficacy of mindfulness training. These inventories will probe the different facets of interpersonal differences that could serve to influence the effectiveness of the mindfulness intervention. In addition, the investigators will also test the effect of conducting the course online during a situation of emergency, like it is the partial lockdown that was implemented in Singapore due to the spread of Covid-19.

The proposed study has the potential to provide new insights into the factors that affect the efficacy of mindfulness on stress and sleep, in a situation of non-emergency (until February the 6th 2020) as well as during a period of heightened restrictions (DORSCON Orange, from 7th of February to 6th of April 2020) and a partial lockdown (from 7th of April to 1st of June 2020, or until resume of normal activity). Further, the investigators hope to build an algorithm that can predict the potential effectiveness of mindfulness on a person by person basis. This could serve as a foundation for future recommendations for mindfulness training as well as open the door for future studies that could serve to further customize the mindfulness training framework to accommodate individual differences

Health and well-being are increasingly being emphasized in modern society. In response, mindfulness-based training (MBT) (e.g. Mindfulness Based Stress Reduction (MBSR) (Kabat-Zinn,1990)) is slowly gaining popularity as a method to alleviate the stress of modern day living. MBT involves bringing one's attention to the present moment, stopping one's thoughts from drifting into concerns about the past or the future It has significant effects on improving mental health via reducing symptoms of stress, anxiety and depression (Fjorback, Arendt, Ørnbøl, Fink & Walach, 2019). Local studies have similarly demonstrated the efficacy of mindful training in stress reduction for mental health professionals in Singapore (Suyi, Meredith & Khan, 2017).

Reducing stress and improving metacognitive processes also contributes to better emotional regulation, thus facilitating better sleep quality (Chiesa et al., 2011; Zeidan et al., 2010).. By breaking up cycles of rumination and worry, mindfulness is hypothesized to reduce "verbal overregulation" and facilitate the disengagement necessary to fall asleep (Gross et al., 2011). Mindfulness programs have been found to improve sleep quality in both healthy individuals (Lazar et al., 2000) and patients with medical or psychiatric illness, including insomnia and depression (Carlson & Garland, 2005; Heidenreich et al., 2006).

While there is much documentation supporting the efficacy of mindfulness training on stress and sleep, there is little research that attempts to evaluate the interpersonal differences or factors that predict the efficacy of mindfulness training on sleep and stress. Isolating these predictive variables consequently allows a better way to evaluate suitability of the mindfulness intervention on an individual basis; maximizing the results for the individual. With this new information, individuals suffering from stress and bad sleep would be able to better be able to select the most effective intervention.

While the concepts above have often been explored in relation to mindfulness, no studies to date have used machine learning to assess how these variables predispose an individual to benefit from mindfulness training. Generating this algorithm will allow for the prediction of treatment response in future trainees. Further, a better understanding of the effect of individual differences on efficacy can open the door for future research to examine how and why these differing results exist and incorporate this information to increase the effectiveness of mindfulness training.

Participants signing up for the 4 or 8 weeks mindfulness training courses at the Brahm Centre and run by Potential Project (two external organization providing Mindfulness based courses) will be automatically sent a link to the questionnaire packet several days after course enrolment. Participants will be provided with a survey link in the enrolment email that is sent to participants to confirm their enrolment, separate recruitment e-mails will not be sent out.

Participants will be informed that the data will form part of a research study, that any information provided is anonymous, and that they can opt out of completing the questionnaires without any penalty to their class enrolment. Recruitment emails will not be sent out. On enrollment in any of the courses, participants will be informed that there is an option to take part in the study.

Staff sending out emails will be separate from staff carrying out the mindfulness training programs. This will ensure that there will be no scenario where a dependent relationship will occur.

Participants can decide if they prefer to sign up for the 4 weeks or 8 weeks Mindfulness courses, depending on availability at the Mindfulness centres.

Questionnaires will be administered through the platform SurveyMonkey ©. SSL encryption will be used to protect sensitive data as it is relayed between the respondent's computer and SurveyMonkey© servers.

Questionnaires will be administered twice, with the predictor surveys administered at pre-intervention only, and outcome variables collected both pre- and post-intervention (PSQI and PSAS).

Predictive factors 10 predictive factors were chosen to evaluate their predictive qualities on the effectiveness of mindfulness training in reducing stress and improving sleep: Personality: Mindfulness training has been shown to be more effective in students with higher scores in conscientiousness and neuroticism (Winning & Boag, 2015). As such, the NEO-FFI-3 will be used to measure the dimensions of personality.

Trait Mindfulness: Baseline trait mindfulness has been shown to be a significant moderator of MBSR intervention effects (Shapiro, Brown, Thoresen, & Plante, 2010). The investigators have included trait mindfulness to corroborate previous studies that have shown this relationship as well as to explore its effect within a local population.

Mood and depression: While depression and mood has been often measured in conjunction with Mindfulness training, there has been little to no research on how it relates to mindfulness training efficacy State-Trait Anxiety: Mindfulness has been shown to alleviate state trait anxiety in individuals (Bergen-Cico & Cheon, 2013). The investigators are thus interested in whether a higher or lower baseline score in the STAI will affect the efficacy of mindfulness training Empathy: There are mixed results in regards to the relationship between empathy and mindfulness; with some studies finding no significant connection (Bergen-Cico & Cheon, 2013), and others showing differing effectiveness dependent on personality traits (Winning & Boag, 2015; Ridderinkhof, de Bruin, Brummelman, & Bögels, 2017).

Self-compassion: Self compassion is believed to be developed and enhanced through mindfulness training. Birnie, Speca & Carlson (2010) found strong associations between self-compassion and mindfulness. It was found that changes in self-compassion were predictive of changes in mindfulness.

Learning styles: This was included to investigate whether the difference in learning styles in individuals would affect the ways in which the mindfulness training are internalized; in turn influencing the efficacy of mindfulness training.

Expectancy/Credibility: Expectancy has been shown to be predictive in evaluating the outcome on some measures (Devilly & Borkovec, 2000). It would be beneficial to understand its effect on the effectiveness of mindfulness training.

Emotional Regulation: Emotion regulation has been shown to improve with mindfulness-based interventions (Guendelman, Medeiros & Rampes, 2017). The investigators are interested in understanding the effect of emotional regulation on mindfulness training.

Coping Methods: Mindfulness has been shown to affect the coping strategies used in individuals. The effect of coping methods on mindfulness training efficacy is thus of interest to our study.

Questionnaires Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989)

Perceived Stress Scale (PSS; Cohen, Kamarck & Mermelstein,1983)

Objectives

This research has four objectives:

To corroborate findings on the effect of mindfulness training on perceived stress.

Hypothesis: based on previous literature, the investigators predict that mindfulness interventions will decrease perceived stress, with lower PSS score post intervention.

To test whether individual differences might be predictive of the effectiveness of mindfulness training on stress Hypothesis: through the use of machine learning, the investigators aim to create a model that can predict changes in perceived Stress (PSS) post intervention based on individual predictors as defined above.

To test whether individual differences might be predictive of the effectiveness of mindfulness training on sleep Hypothesis: through the use of machine learning, the investigators aim to create a model that can predict changes in Sleep quality (PSQI) post intervention based on individual predictors as defined above.

To test the effects of group mindfulness interventions on stress and sleep quality during a period of global uncertainty, a partial lockdown due to the COVID-19 pandemic, compared to Mindfulness intervention in a non-emergency situation.

Hypothesis (i):the investigator predict that participants would report higher levels of perceived stress and poorer sleep quality at baseline during the period of the pandemic (DORSCON Orange and lockdown) relative to an earlier control period; Hypothesis (ii): the investigators predict that online mindfulness training (during lockdown) would have be non-inferior/equivalent in reducing perceived stress and improving sleep quality compared with DORSCON Orange and the control period.

Inclusion Criteria:

• Any individual above 21 years old enrolled in Mindfulness-Based Stress Reduction/Mindfulness Foundation course at Brahm Centre or with a mindfulness course with Potential Project can be included in the study.

Exclusion Criteria:

• no exclusion criteria

Any individual above 21 years old enrolled in Mindfulness-Based Stress Reduction/Mindfulness Foundation course at Brahm Centre or with a mindfulness course with Potential Project Singapore that is also interested in participating in the study.