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      Assessment of well-being using Fitbit technology in college students, faculty and staff completing breathing meditation during COVID-19: A pilot study

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          Abstract

          This pilot study aimed to explore the intersection of mindfulness, physical activity, and mental well-being within higher education populations during the COVID-19 pandemic. College students, faculty, and staff (n=34) from a public university participated in the study during spring, summer, and fall 2021. All participants wore a Fitbit for two weeks and were assigned to a treatment group (n=17), who completed a daily five-minute breathing meditation during the second week, and a control group (n=17), who did not complete breathing meditation. Amount of sleep and physical activity were measured with the Fitbit. Surveys assessed feasibility and acceptability of the intervention, along with perceived anxiety, depression, well-being, worry, and mindfulness at baseline and after the two-week study. Results demonstrated that the intervention was feasible, and that daily breathing meditation may help reduce anxiety and may lead to greater physical activity and rapid eye movement (REM) sleep. This pilot study lays the foundation for further research into mindfulness, physical activity, and mental health, which may have important implications for promoting mental well-being in college populations following the COVID-19 pandemic. 1 Introduction Within higher education, there are many factors that contribute to faculty, staff, and student stress, which negatively impacts well-being (Bamber & Schneider, 2016; Gewin, 2021). In 2019-2020, 42% of college students sampled considered stress to be a concern and 63% indicated anxiety as a concern (Center for Collegiate Mental Health, 2020). There was an unprecedented increase in stress and anxiety due to the COVID-19 pandemic (Huckins et al., 2020; Gewin, 2021). More specifically, 71.26% of students surveyed at Texas A&M University stated that their stress and anxiety levels had increased during the COVID-19 pandemic (Wang et al., 2020). Students also reported that having access to more mental health resources was important to them during the pandemic (Active Minds, 2020). Additionally, faculty and staff reported increased levels of stress, anxiety, and burnout during the pandemic (Gewin, 2021). For example, 70% of faculty reported feeling stressed in 2020, compared to 32% in 2019 (Gewin, 2021). Mindfulness can be defined as “the awareness that arises by paying attention on purpose, in the present moment, and non-judgmentally” and is a practice with origins in Buddhism (Kabat-Zinn, 2013, p. xxxv). Previous research has demonstrated that mindfulness can be used to reduce stress and is a skill that can be developed (Kabat-Zinn, 2013). Moreover, mindfulness practices can help facilitate focus and attention in college students, while also reducing stress, anxiety, and depression and improving well-being (Bamber & Morpeth, 2019; Bamber & Schneider, 2015; Dark-Freudeman et al., 2021; Sass et al., 2019; Wingert et al., 2022; Yamada & Victor, 2012). Additionally, college professors who participated in a four-day seminar on mindfulness, and integrated mindfulness practices into their teaching, demonstrated an improved connection with their students, higher levels of engagement and expressed greater enthusiasm (Brendel & Cornett-Murtada, 2018). Implementation of a two-day mind-body therapy intervention within a cohort of veterinary faculty and staff led to significant decreases in perceived stress and increased mindfulness (Artemiou et al., 2018). Lastly, graduate students, faculty, and staff who completed a 10-week yoga program experienced significantly reduced perceived stress (Brems, 2015). More recently and particularly during the COVID-19 pandemic, research explored the use of online and app-based mindfulness practices and demonstrated decreased stress, anxiety, and depression among participants (Lahtinen et al., 2023; Witarto et al., 2022). While there are different meditation practices available, breath meditation may require less perceived effort than other mindfulness practices (e.g., loving-kindness, observing-thoughts meditation) and may produce a lower heart rate compared to other meditation techniques (Carter & Carter III, 2016; Lumma et al., 2015). Therefore, breath meditation was used in this pilot study, and heart rate was measured to help serve as an indicator of the mental effort required to complete the meditation practice. Previous research has demonstrated that physical activity is positively connected to mental well-being, with walking being reported as one of the most common physical activities among adults (Bafageeh & Loux, 2022). Positive correlations between mindfulness, physical health, and beneficial behaviours, such as healthy eating and sleep have also been reported in college students (Murphy et al., 2012; Lentz & Brown, 2019). In undergraduate students, higher levels of dispositional mindfulness are correlated with better physical health and being mindful about physical activity led to higher participation in exercise (Biglassi & Bertuzzi, 2020; Murphy et al., 2012). Similarly, college students with higher levels of mindfulness reported more exercise, but unexpectedly, this correlation was not moderated by sleep (Lentz & Brown, 2019). However, Caldwell et al. (2010) found that movement-based courses led to increases in mindfulness, which were associated with improved sleep among college students. This was particularly relevant during the current COVID-19 pandemic, as college students report poor sleep quality, which may have been correlated with anxiety and worry related to the pandemic (Ulrich et al., 2021). For faculty and staff, the increase in online instruction related to COVID-19 elevated the risk of sedentary behaviour, further stressing the importance of physical activity (Fröberg, 2020). Several studies have used self-reported data to assess measures like stress, sleep, and physical activity (Artemiou et al., 2020; Caldwell et al., 2010; Murphy et al., 2012). Our pilot study expanded on these previous findings by using a mixed-methods approach, which included objective assessments for sleep and physical activity using Fitbits (a fitness tracking device) and self-reported data for mindfulness and well-being to examine the intersection of physical activity and mental well-being after completing breathing meditation during the COVID-19 pandemic. Our primary aim was to examine the feasibility and acceptability of an intervention that included both breathing meditation and the use of Fitbits within higher education populations during COVID-19. A secondary aim was to analyze the potential effectiveness of the assessment tools used to measure perceived stress, anxiety, mindfulness, and physical activity among participants. 2 Methods 2.1 Participants Participants were recruited via email announcements, class announcements, and personal contacts by the research team in three cohorts across the spring 2021, summer 2021, and fall 2021 semesters. Recruitment was limited to undergraduate and graduate students in the spring 2021 semester, and was extended to include students, faculty, and staff in the summer 2021 and fall 2021 semesters. Initial exclusion criteria included prior meditation or Fitbit experience. In the summer and fall cohorts, exclusion criteria only included prior meditation experience since all participants received the opportunity to familiarize themselves with the Fitbit during the first week of the study. This study was approved by the university's Institutional Review Board (IRB), and written informed consent was obtained from all participants. 2.2 Procedure Each participant was provided a pseudonym, and a Fitbit Inspire 2, which was linked to their mobile device using the Fitbit app. Participants’ height and weight were recorded at the beginning of the study to accurately set up their Fitbit accounts. Participants were added to a spreadsheet as they indicated interest in the study and then assigned to control or treatment groups in an alternating process, with an even distribution of faculty/staff and students in each group for the summer and fall cohorts. The treatment group wore the Fitbit for the duration of the two-week study and completed breathing meditations during the second week. Participants were asked to perform the breathing meditations using the Relax™ app on the Fitbit for five minutes daily within the first hour of waking. Practicing meditation in the early morning can help provide a time with fewer distractions and therefore promote better awareness, which may be more difficult later in the day when one might be tired (Kabat-Zinn, 2013). The Relax™ app utilizes a controlled breathing rhythm pattern and prompted the participant to inhale and exhale when the Fitbit vibrated. Additionally, they were instructed to focus on their breathing and when thoughts began to wander away from the breathing, to bring the attention back to the breath, non-judgmentally. The control group wore the Fitbit for two weeks and did not perform any breathing meditations. Participants in the control group were given the option to perform breathing meditation for one week following the two-week study. Participants in both the control and treatment groups were manually sent email reminders about the study throughout the two-week period (Figure 1 ). Figure 1 Study Design and Timeline Figure 1 Participants were asked to wear the Fitbits on their non-dominant wrist for as close to 24 hours a day as possible. Participants did not wear the Fitbit in water (e.g., showering) and that time was used to charge their device. Participants were asked to sync their Fitbit accounts with their mobile device at least once a day in the summer and fall cohorts. A guide was given to each participant, which had information on how to use the Fitbit, the Relax™ app, and how to log their activity and mindfulness exercises. Heart rate, sleep, and physical activity were recorded. Participants were asked to refrain from using guided Fitbit programs and the COVID-19 platform on the mobile app. Self-report assessments, as outlined below, were administered to participants in the control and treatment groups one week before the study began (baseline) and within one week of the end of the study (post). 2.3 Assessments 2.3.1 Hospital Anxiety and Depression Scale (HADS) The Hospital Anxiety and Depression Scale was used to identify clinically significant anxiety and depression. The Hospital Anxiety and Depression Scale (HADS) consists of 14 statements, which are rated on four-point (0-3) scales. Each statement measures depression or anxiety exclusively. The total sum of the responses for depression and anxiety were independently summed and evaluated as normal (0-7), borderline case (8-10), or case (11-21) (Zigmond & Snaith, 1982). The depression scale has been validated in the college student population; however, the anxiety scale may overestimate levels of anxiety (Andrews et. al, 2006). The Hospital Anxiety and Depression Scale (HADS) has also been validated in clinical populations (Zigmond & Snaith, 1983). Herrmann (1997) found strong internal reliability for both subscales (anxiety α = .90 – 0.93; depression α = .81 – .90), as well as discriminant and concurrent validity. In the current study, internal reliability was α = .66. 2.3.2 Mental Health Continuum Short-Form (MHC-SF) The Mental Health Continuum Short-Form is a 14-statement questionnaire designed to measure an individual's emotional, psychological, and social well-being. Participants rated statements based on frequency of experience over the past month, with the lowest score being “never” and the highest score being “every day.” Participants were determined to be flourishing (free of psychopathology and have high levels of emotional, psychological, and social well-being), languishing (low levels of well-being), or moderately mentally healthy. Participants who were neither “flourishing” or “languishing” were determined to have moderate mental health (Keyes, 2005). The Mental Health Continuum Short-Form (MHC-SF) has been validated among the college student population and in adults of ages 25 to 74 years (Robitschek & Keyes, 2009; Keyes, 2005). One participant from the treatment group was omitted from Mental Health Continuum Short-Form (MHC-SF) analysis because of not entering a participant code. Previous research found the Mental Health Continuum Short-Form (MHC-SF) to have acceptable internal reliability (all subscales α ≥ .80; Lamers et al., 2011). Internal reliability was acceptable in this current study, α = .62. 2.3.3 Penn State Worry Questionnaire (PSWQ) The Penn State Worry Questionnaire (PSWQ) is a 16-statement questionnaire used to measure levels of worry. Participants rated statements using a Likert scale with the lowest score being “not at all typical” (1) and the highest score being “very typical” (5). The total sum of all the responses was calculated (five statements were reverse scored), with a higher score indicating a greater state of worry. The Penn State Worry Questionnaire (PSWQ) has been validated among the college student and adult population (Meyer et al., 1990). Two participants from the control group were omitted from Penn State Worry Questionnaire (PSWQ) analysis because they did not fully complete the measure. Meyer and colleagues (1990) demonstrated that the Penn State Worry Questionnaire (PSWQ) had high levels of internal reliability (e.g., α ≥ .90) and strong validity. In the current study, internal reliability was α = .62. 2.3.4 The Mindful Attention Awareness Scale (MAAS) The Mindful Attention Awareness Scale (MAAS) was used to measure levels of mindfulness through a 15-statement questionnaire (Brown & Ryan, 2003). Participants rated each statement using a Likert scale with the lowest score being “almost always” (1) to the highest score being “almost never” (6). The average score of the 15 questions was determined, and a higher score is indicative of a higher level of mindfulness. The Mindful Attention Awareness Scale (MAAS) has been validated among the college student and adult population and has high internal reliability, α ≥ .80 (Brown & Ryan, 2003). In the current study, internal reliability was α = .58. 2.4 Program Surveys and Interviews Participants completed surveys to assess their experience with COVID-19 and to collect demographic information. The surveys also gathered student feedback on using Fitbits and completing the breathing meditation to help assess the feasibility and acceptability of these interventions. A subset of participants who indicated interest during the post-program survey was invited to participate in a post-program interview. Semi-structured interviews occurred via Zoom for an average of 21 minutes and included at least six questions, pertaining to partcipants’ perspectives on mindfulness, physical activity, breathing meditation, well-being, and sleep. Interviews were recorded using Zoom transcription and reviewed by at least two researchers independently by comparison to the original audio recording. The interview questions included: 1 How do you define mindfulness? 2 Do you consider yourself to be a physically active person? Why or why not? 3 What did you think of the breathing meditation exercise? 4 Did you use the breathing meditation exercise on your own? Why or why not? 5 How would you describe your well-being? Did it change because of the breathing meditation? 6 How would you describe the quantity and quality of your sleep? Did it change because of the breathing meditation? 2.5 Fitbit Data Data were exported from the Fitbit website and analysed using Microsoft Excel. There was a Fitbit firmware update between the spring and summer semesters, but no other firmware changes were noted during the study. Averages for each measure (activity, sleep, and heart rate) were calculated within the first week of the study and within the second week of the study. Additionally, the difference between week 2 and week 1 was calculated for each measure. Total activity minutes represents the sum of minutes lightly active, minutes fairly active, and minutes very active. For sleep measures, all periods of sleep (including naps) were averaged within the first week. The same was done for all periods of sleep in the second week. The average was calculated based on how many nights of sleep were recorded to account for any missing nights of sleep. The difference between average sleep during the second week and average sleep during the first week was calculated. Rapid eye movement (REM) sleep collection was limited to longer periods of sleep so many of the measures were missing as participants had shorter periods of sleep during the study. Seven participants (n=3 from control and n=4 from treatment) were excluded in the sleep analysis because they were missing more than 30% of sleep data in either week 1 or week 2 of the study. The difference in daily average resting heart rate was determined between the first and second weeks. However, the Fitbit devices did not consistently record heart rate for all participants and there were some missing data. Finally, the number of meditations that each participant completed was recorded based on the meditation log under Activities. This was compared to self-report surveys from each participant, as there may have been days when participants forgot to log their meditations but did complete the meditations. 2.6 Data Analysis Survey data was collected via Qualtrics (Provo, UT). Fitbit data was downloaded from participants’ Fitbit accounts into Microsoft Excel for analysis. Statistical analysis was completed using R (R Version 4.1.0, Vienna, Austria). Data was combined across all three cohorts for all analysis. All data was assessed for normality using the Shapiro-Wilk test, and p > 0.05 for all samples. Fisher's exact test was used to analyse categorical variables (race, class, sex), and t-tests were used to analyse continuous variables (age, BMI) between control and treatment groups in demographic data. Paired t-tests were used to compare baseline/post-study survey data and week 2/week 1 Fitbit data, and t-tests were used to compare control and treatment groups at each time point. All values are reported as mean ± standard deviation (SD). To examine the mean differences between groups, 95% confidence intervals (CI) were used (Cumming, 2014). 3 Results 3.1 Participants Participants who completed the study included students, faculty, and staff who were assigned to control (n=17) and treatment (n=17) groups (Figure 1). The largest percentage of participants identified as female and white in both control and treatment groups, with a range of class standings and representation from students, faculty and staff in each group (Table 1 ). There were no meaningful differences between control and treatment groups for age, body mass index (BMI), sex, race/ethnicity, and class. Few participants tested positive for COVID-19, and a majority did not have prior experience in quarantine. However, about half of the participants knew a family member or friend who tested positive for COVID-19, and about half of the participants had a family member or friend die or have complications related to COVID-19 (Table 1). Table 1 Participant Demographics Table 1 Control (N = 17) Treatment (N = 17) Age, Range, Mean (Standard Deviation) 18-57, 34 (14) 18-55, 31 (13) SexFemaleMaleTransgender (FTM) 82.4 %11.8 %5.9 % 70.6%29.4% Body Mass Index (BMI)Mean (Standard Deviation) 26.6 (6.4) 26.1 (6.9) Race and EthnicityWhiteBlack or African AmericanHispanic/Latino/SpanishAsianMulti-racial* Prefer not to answer 58.8 %5.9 %11.8 %11.8 %11.8 % 47.1 %35.3 %0%0%11.8 %5.9% ClassFreshmanSophomoreJuniorSeniorGraduate StudentFacultyStaffFaculty & Graduate Student 11.8 %5.9 %5.9 %17.6 %11.8 %23.5 %23.5 %0 % 5.9 %23.5 %11.8 %11.8 %0 %17.6 %23.5 %5.9 % COVID-19 PositiveYesNo 0%100% 6%94% Prior QuarantineYesNo 23.5%76.5% 29.4%70.6% Family/Friend COVID-19 PositiveYesNo 41.2%58.8% 41.2%58.8% Another Person COVID-19 PositiveYesNo 76.5%23.5% 70.6%29.4% Known death or complication due to COVID-19YesNo 41.2%58.8% 58.8%41.2% ⁎ Multi-racial includes Hispanic, Latino, or Spanish origin, white, Black or African American; Hispanic, Latino, or Spanish origin, white; American Indian or Alaska Native, white; Asian, white 3.2 Assessments Control and treatment groups had similar levels of mindfulness, worry, depression, and overall well-being after the two-week study compared to baseline (Table 2 ). Levels of anxiety in the control group were similar between baseline and post the two-week study, CI [-0.99, 1.34], but levels of anxiety decreased in the treatment group post the two-week study compared to baseline, CI [0.48, 4.22]. Additionally, there was a difference between control and treatment groups for the mean difference in anxiety, CI [-4.31, -0.04] (Table 2). Table 2 Survey Results Table 2 Assessment Group BaselineM (SD) PostM (SD) DifferenceM (SD) P Value 95% Confidence IntervalsLL UL Mindful Attention Awareness Scale (MAAS) Control (n=17)Treatment (n=17) 3.55 (0.98)3.72 (0.74) 3.47 (0.86)3.82 (0.78) -0.08 (0.57)0.10 (0.43) 0.308 -0.18 0.54 Penn State Worry Questionnaire (PSWQ) Control (n =15)Treatment (n =17) 59.40 (13.79)54.06 (13.31) 59.27 (14.57)52.47 (10.70) -0.13 (7.03)-1.59 (6.05) 0.538 -6.24 3.33 Hospital Anxiety and Depression Scale (HADS) (Anxiety) Control (n=17)Treatment (n=17) 10.29 (3.33)10.41 (4.78) 10.12 (3.67)8.06 (4.88)* -0.18 (2.27)-2.35 (3.64)+ 0.046 -4.31 -0.04 Hospital Anxiety and Depression Scale (HADS) (Depression) Control (n=17)Treatment (n=17) 5.94 (3.07)4.53 (3.32) 4.82 (3.43)4.00 (3.02) -1.12 (2.57)-0.53 (2.90) 0.536 -1.33 2.50 Mental Health Continnum Short-Form (MHC-SF) Control (n=17)Treatment (n=16) 36.41 (14.33)42.00 (13.66) 39.41(14.68)45.75 (14.15) 3.00 (8.89)3.75 (10.33) 0.825 -6.12 7.62 ⁎ indicates p < 0.05 (between baseline and post) + indicates p < 0.05 (between treatment and control) 3.3 Fitbit The number of steps recorded by participants in the treatment group was higher than the control group during week 2 of the study, CI [84.99, 6699.19] (Table 3 ). However, the difference in steps between week 2 and week 1 were similar between treatment and control groups. During week 1, participants within the treatment group spent less time in rapid eye movement (REM) sleep compared to the control group, CI [-38.86, -9.83] (Table 3). The difference in rapid eye movement (REM) sleep increased in participants within the treatment group compared to the control group, CI [-0.20, 32.77] (Table 3). Heart rate, active minutes, sedentary minutes, and total sleep minutes were similar between control and treatment groups and between week 1 and week 2 (Table 3). Table 3 Fitbit Results Table 3 Assessment Group Week 1 M (SD) Week 2 M (SD) DifferenceM (SD) P Value 95% Confidence Intervals LL UL Steps Control (n=17) 6744.76 (2845.74) 6688.65 (2414.90) -56.12 (1186.91) 0.534 -743.77 1399.93 Treatment (n=15) 9808.77 (5383.09) 10080.73 (5669.73)+ 271.96 (1678.45) Heart Rate Control (n =16) 71.15 (10.57) 70.66 (10.55) -0.49 (1.75) 0.674 -1.45 2.20 Treatment (n =14) 70.39 (8.33) 70.28 (9.29) -0.12 (2.84) Active Minutes Control (n=17) 242.28 (61.70) 234.82 (56.14) -7.45 (33.45) 0.497 -9.75 24.65 Treatment (n=15) 279.60 (106.47) 282.62 (114.11) 3.02 (49.70) Sedentary Minutes Control (n=17) 800.03 (122.73) 789.87 (117.63) -10.17 (121.49) 0.499 -112.82 56.19 Treatment (n=15) 783.81 (150.72) 745.32 (207.33) -38.48 (112.47) Sleep Minutes Control (n =14) 438.75 (39.98) 427.99 (34.74) -10.76 (36.47) 0.149 -6.63 40.81 Treatment (n =13) 378.27 (106.38) 384.60 (110.18) 6.33 (21.43) Rapid Eye Movement (REM) Sleep Control (n =12) 100.12 (13.21) 93.00 (21.20) -7.11 (22.17) 0.053 -0.20 32.77 Treatment (n =11) 75.77 (19.07)+ 84.95 (19.89) 9.17 (15.33)+ *indicates p < 0.05 (between week1 and week 2) +indicates p < 0.05 (between treatment and control) 3.4 Program Surveys Before beginning the research program, 79% of participants indicated that that they were either very interested or interested in practicing breathing meditation, and 91% indicated that they were either very interested or interested in using a Fitbit. When asked to describe their attitude towards breathing meditation, many responded positively, and some commented on how it can help with stress. A few mentioned attempting breathing exercises previously, but that they weren't consistent. Many were excited and interested in learning more. Based on the logged meditations through the Fitbit device, 76% of participants in the treatment group completed over 50% of the breathing meditations during the second week (Mean = 4.9 out of 7 days; Range = 0 – 8 days). After completing the research program, 53% of participants who practiced breathing meditation indicated that they were very likely or likely to continue practicing breathing meditation. There were mixed responses when asked about their attitude towards breathing meditation, which included: enjoyment, not finding it useful, difficult, calming, and interesting. Obstacles that prevented completing the breathing meditations included: being busy, forgetting, Fitbit technology concerns, and time of day (morning). After completing the research program, 62% of participants (both control and treatment) indicated that they were very likely or likely to continue using a Fitbit or related physical tracker device. Most (88%) described the time commitment required in this study as the right amount. Additionally, 76% of participants indicated that they wore the Fitbit as directed for the study, including the entire amount of time each day. The obstacles listed as reasons for not wearing the Fitbit included: forgetting to put it back on after removing it, time for charging the device, unable to wear it at work, mild skin irritation, and participating in a sleep study for one night. Most of the obstacles noted caused only temporary interruption to the study. 3.5 Interviews Eight participants completed post-program interviews across spring (n=1), summer (n=3), and fall (n=4) semesters. This subset of participants included students, faculty, and staff, who all completed breathing meditations. Four main themes emerged from these interviews and included the definition of mindfulness, aspects of well-being, responses to breathing meditation, and sleep quality and quantity (Table 4 ). Table 4 Interview Results Table 4 Theme Subtheme Sample Quote Definition of mindfulness Mindfulness is awareness, paying attention, being present in the moment, and having an open mind.Mindfulness in association with meditation “…just trying my best to stay in the moment um and pay attention to what's happening to me, or around me in the moment.”“I guess I would see mindfulness more as a product of meditation from my understanding, and that meditation would would lead to mindfulness and that maybe mindfulness would exist outside of meditation.” Aspects of well-being Physical activityMental healthBarriers to well-being “I do still try to walk every single day but I used to also do some other kinds of activities, and I definitely let those go and have not picked them back up…”“I think my well-being is in a good spot, but it could be better because I'm going to sleep really late these days because of work and homework.”“I would say that the main psychological toll [from COVID-19] came from being alone, and uh with the disruption of my routine and not having things that I normally do.” Mixed responses to breathing meditation PositiveNegativeNeutralTiming “I actually really enjoyed it. Every time I woke up, it was the first thing I did and I felt like it kind of like relaxed me a little bit…and get ready for the day and I feel like it really did help me throughout.”“And I could never get whether or not I was supposed to be breathing in or out with the Fitbit, I didn't know which was the inhale exhale, and that made me anxious.”“Well, it didn't really feel that different from earlier…when I didn't do them…it was just a thing to do, I guess.”“um the only two things that were really hard for me was doing it the first thing in the morning when I wake up” Sleep quality and quantity are generally poor. Not enough sleepNot good quality sleepSleep during the study “terrible could apply to both actually quantity and quality…but that's not an unusual thing for me…I have insomnia.”“Quantity I'm pretty close to that, but quality my sleep is still sort of broken up…”“I was monitoring my sleep…I know I was getting less than eight hours of sleep, but sometimes I was surprised at how, how much less…So I think I would say overall participating in this study was beneficial to me and at least thinking about…wellness, well-being.” Participants shared a number of conditions impacting their well-being including heart conditions, anxiety, depression, autoimmune disease, and insomnia. A variety of physical activities were mentioned including walking, biking, sports, going to the gym, weightlifting, and yoga. Stress, weather, injury, work, and COVID-19 were all mentioned as impacting levels of physical activity. Positive responses to breathing meditation included that it was interesting and enjoyable (e.g., "I actually really enjoyed it. Every time I woke up, it was the first thing I did and I felt like it kind of like relaxed me a little bit...”). Some participants reported that they did not think the meditation led to any changes (e.g., “It did not really feel that different from earlier... when I did not do them...”), while others noted perceived changes with sleep and relaxing (e.g., “...it helps me, um, you know, just be better adept at clearing out the, the activity in the brain and you know just calming my brain down.”). Other benefits included helping the participant wake up in the morning and creating more focus/clear mind (e.g., “...just sort of helped me ease into waking up a little bit instead of feeling so rushed in the morning...”). Interestingly, some found meditation in the morning to be stressful while trying to prepare themselves (and/or children) for the day. Some chose to move their meditation to the evening, although all participants were asked to meditate within the first hour of waking up. The main difficulties noted with the breathing meditation was time of day (morning) and trying to coordinate the breath with the Fitbit app, which created confusion for some. Other barriers to completing the breathing meditation included nasal drainage and quarantine due to COVID-19 exposure. Most participants did not continue practicing breathing meditation after the study, although others did. Among those who continued practicing, a variety of examples were provided including breathing when upset, during the middle of the night when waking up due to high anxiety, with music, before sleep, as a break from homework, and in the morning. Most participants noted that their quality and quantity of sleep was generally poor, although a few participants shared that their sleep quality is good. Several reasons were cited for why participants were not sleeping including homework, work, reading, watching TV, restlessness, getting up in the middle of the night, difficulty falling asleep, insomnia/sleep medication, and autoimmune disease. Some participants tried meditation before sleep and found it beneficial. Others noted that using the Fitbit brought awareness to their sleep patterns. 4 Discussion This pilot study examined the feasibility and acceptability of practicing a brief daily breath meditation in college students, faculty, and staff during the COVID-19 pandemic. A majority of participants successfully completed the study, and approximately half of participants who practiced breath meditation remained interested in continuing to practice breath meditation at the end of the study. Most felt that the time commitment required in this study was appropriate, and a majority of participants wore the Fitbit as directed for the study. Preliminary findings from this pilot study demonstrated that practicing daily breath meditations may help reduce levels of anxiety and may help increase physical activity (number of steps), and the amount of time spent in rapid eye movement (REM) sleep. These results suggest that there is potential for integrating mindfulness interventions, such as breath meditation, in college students, faculty, and staff to help alleviate university-associated stressors, particularly during the ongoing COVID-19 pandemic. Mindfulness practice is cost-effective, accessible, and may promote well-being among college students, faculty and staff. Past research has demonstrated that mindfulness practices can reduce anxiety and stress in college students (Bamber & Schneider, 2016). This is particularly relevant during the COVID-19 pandemic, when students, faculty, and staff reported increased levels of stress (Huckins et al., 2020; Gewin, 2021). Participants who practiced breathing meditation in our study reported a decrease in anxiety compared to the control group. Baseline levels of anxiety measured by Hospital Anxiety and Depression Scale (HADS) in both the control and treatment groups were within the range for borderline cases (Andrews et al., 2006; Zigmond & Snaith, 1983). A decrease in anxiety scores from 10.41 to 8.06 in the treatment group still remains within the range for borderline cases and may not be clinically meaningful; however, an average score of 8.06 is closer to the cut off for normal (Andrews et al. 2006; Zigmond & Snaith, 1983) and warrants further investigation in a future study. Although levels of worry were similiar after breathing meditation, the mean score decreased for the treatment group, indicating less worry. The large standard deviation is likely a result of the small sample size, and future studies should explore the impact of worry on measures of anxiety with a larger sample. Participants in our study who completed breathing meditation also recorded more steps compared to the control group. This aligns with previous studies that have demonstrated a positive correlation between dispositional mindfulness and physical health (Murphy et al., 2012). Also similar to a previous study (Caldwell et al., 2010), participants in our study increased amount of time in rapid eye movement (REM) sleep while completing breathing meditation. However, participants in the treatment group began with a lower average amount of time in rapid eye movement (REM) sleep during week 1 compared to the control group. Therefore, wearing the Fitbit device may have contributed to the increased amount of time spent in rapid eye movement (REM) sleep in the treatment group. Further research is needed to differentiate the contributions of wearing the Fitbit device and practicing breathing meditation on rapid eye movement (REM) sleep. In this study, rapid eye movement (REM) sleep was determined based on heart rate measurements from the Fitbit device; therefore, limitations with heart rate data outlined below may also apply to rapid eye movement (REM) sleep. Previous research suggests that heart rate can differ based on the type of meditation with higher heart rate during loving kindness and observing-thoughts meditations compared to breathing meditation (Lumma et al., 2015). However, in our study, there were no meaningful differences in heart rate. Heart rate measurements from wearables, like the Fitbit, may be influenced by a number of factors, including body mass index (BMI), biological sex, skin tone, wrist circumference, and dominant versus non-dominant hand use (Nelson et al., 2020). Additionally, the Fitbit uses a green light emitting diode (LED) sensor to detect changes in blood profusion, which serves as an indicator of heart rate. Previous studies have noted that the green light emitting diode (LED) may limit the amount of light that passes through tissue of individuals with darker skin tones (Nelson et al., 2020). We report on many of these factors in Table 1 and controlled for variations in hand use in our instructions to participants. Nonetheless, these factors may account for the lack of differences in heart rate based on the intervention. Additionally, some participants expressed that the Fitbit breathing pattern on the Relax™ app was difficult to follow and may have caused confusion, which could contribute to an increased heart rate. It is also important to note that during this study, the Fitbits did not consistently record resting heart rate and some data was excluded as a result. 4.1 Study Limitations and Future Directions Recruitment for this study was challenging due to the ongoing COVID-19 pandemic, therefore, consecutive cohorts across three different semesters were combined to create a more robust analysis of feasibility and acceptability of the intervention. Although the recruitment process clearly stated that participation was limited to individuals who had no prior meditation experience, during the interviews, some participants shared experiences that may be related to meditation, such as a breathing activity during school, using sounds at night to help sleep, and attending one yoga class. Clarifying what constitutes “meditation” will be useful in future studies. There were also a few technical difficulties with the Fitbit device that hindered some data collection; however, the majority of these issues were addressed within the first day of the study. Participants were asked to log their meditation activity using the Fitbit app and while 76% reported that they completed over 50% of the breathing meditations, this number may be an underestimation, as some participants may have completed the breathing meditation, but forgot to record it in the Fitbit app. Additionally, concerns have been raised about the use of self-reported psychometric scales for assessing mindfulness, such as the Mindful Attention Awareness Scale (MAAS) used in this study (Sauer et al., 2013). Our assessments also had lower than desired reliability scores, likely due to the small sample size. We recommend future replication of this study with a larger sample to more accurately assess intervention effectiveness. One of the strengths of this study includes a mixed methods approach, which combined psychometric scales with data from Fitbit devices and qualitative feedback through semi-structured interviews. This approach is highly recommended to provide a more comprehensive understanding of mindfulness (Sauer et al., 2013). Future research pertaining to the use of breathing meditation in college students, faculty, and staff should work to examine different intervals of practice, as previous research suggests that the number of mindfulness sessions may impact college student anxiety (Bamber & Morpeth, 2019). Feedback from participants in our study indicated that having the ability to practice breath meditations at additional times, such as the afternoon and evening, particularly before sleep, would have been beneficial for their well-being. Some comments focused on how difficult it was to complete meditation in the morning and that other times of day would be better. It was also recommended to extend the study for a longer period, to allow more weeks of meditation practice. Participants were also interested in practicing breathing meditations without using the Fitbit device and this could be a helpful comparison in future studies. Finally, examining the impact of the summer semester schedule on outcomes, particularly with faculty who are not teaching and may have fewer responsibilities, would provide insight into possible differences within the academic year. 5 Conclusions Recent research has utilized Fitbit technology to track physical activity, mental health, and associated parameters. However, the practice of mindfulness in conjunction with Fitbit tracking has not been thoroughly examined in the literature. This pilot study is one of the first that aims to address the intersection of physical and mental well-being with breathing meditation practice. This pilot study suggests that daily breathing meditation combined with wearing a Fitbit device is a feasible intervention among college populations and may help reduce anxiety, increase physical activity, and increase time spent in rapid eye movement (REM) sleep. These findings provide the framework for future studies aimed at determining the effects of mindfulness on physical activity in college students, faculty, and staff and are particularly relevant by providing accessible and affordable options for promoting well-being. Author Note This project was supported in part by grant P20GM103499-20 (SC INBRE) from the National Institute of General Medical Sciences, National Institutes of Health; a Winthrop Research Council Grant (FR20018-382013); and Winthrop University's Ronald E. McNair Postbaccalaureate Achievement Program (funded by U.S. Department of Education TRiO grant P217A180094). This study was registered with clinicaltrials.gov (NCT05101343). Uncited References R Core Team 2021, Brendel and Cornett-Murtada, 2019 CRediT authorship contribution statement Lily Garcia: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft. Shea Ferguson: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft. Leslie Facio: Methodology, Formal analysis, Investigation, Writing – original draft. David Schary: Conceptualization, Formal analysis, Writing – review & editing. Courtney Guenther: Conceptualization, Methodology, Formal analysis, Writing – review & editing, Supervision, Funding acquisition. Declaration of Competing Interest none

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                Author and article information

                Journal
                Ment Health Prev
                Ment Health Prev
                Mental Health & Prevention
                Elsevier GmbH.
                2212-6570
                5 May 2023
                5 May 2023
                : 200280
                Affiliations
                [a ]Department of Biology, Winthrop University, Rock Hill, South Carolina, USA
                [b ]Department of Educational Studies, University of South Carolina, Columbia, South Carolina, USA
                [c ]Department of Physical Education, Sport and Human Performance, Winthrop University, Rock Hill, South Carolina, USA
                Author notes
                [* ]Corresponding author: Dr. David Schary, Winthrop University, 701 Oakland Ave., Rock Hill, SC 29733
                [1]

                Lily Garcia and Shea Ferguson contributed equally to this work

                Article
                S2212-6570(23)00022-3 200280
                10.1016/j.mhp.2023.200280
                10159665
                37200555
                deb8d139-319b-4d9b-9aed-ea42003c5b72
                © 2023 Elsevier GmbH. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 22 December 2022
                : 30 April 2023
                : 3 May 2023
                Categories
                Article

                mindfulness,breathing meditation,anxiety,well-being,fitbit
                mindfulness, breathing meditation, anxiety, well-being, fitbit

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