A Meditation Based Cognitive Therapy (HMBCT) for Primary Insomnia: A treatment feasibility pilot study

A Meditation Based Cognitive Therapy (HMBCT) for Primary Insomnia: A treatment feasibility pilot study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Meditation Based Cognitive Therapy (HMBCT) for Primary Insomnia: A treatment feasibility pilot study Chandan Kumar Behera, Tharun Kumar Reddy, Laxmidhar Behera, Niels Birbaumer, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2453260/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Apr, 2023 Read the published version in Applied Psychophysiology and Biofeedback → Version 1 posted 7 You are reading this latest preprint version Abstract Previous evidence suggests a critical need for alternative therapies which are cost-effective and can add to the list of well-established treatments for insomnia. This pilot study evaluates a novel therapy for treating insomnia. It comprises a randomized controlled trial with two groups. Prior to Simple randomization, the participants are included/excluded based on research diagnostic criteria (RDC) for insomnia (Edinger et al., 2004) by the American Academy of Sleep Medicine (AASM). Participants (belonging to Hindu, Muslim and Christian faiths) were assigned to either the therapy group (Hare Krishna Mantra Based Cognitive Therapy: HMBCT) or non-therapy group (control with relaxing music) (other conventional aspects of CBT: Stimulus Control, Sleep Restriction, Sleep Hygiene etc. being common to both the groups) for a 6 weeks treatment procedure (6-sessions were conducted in 6 weeks, each on an average of 45-minute duration in the evening and in addition, the participants who underwent sleep quality behavioral measures, sleep logs and Polysomnography recording were asked to practice therapy in the evening of the day of sleep recording). For a week, before and after the 6 weeks duration, no treatment is provided. HMBCT produced significant improvements in sleep quality measures, like ESS (Epworth Sleepiness Scale) (a reduction of 61% post treatment) and ISI (Insomnia Severity Index) (a reduction of 80% post treatment) scores. The participants abstained from taking any sleep-inducing medication during this study. We conclude that the addition of mantra chanting to CBT may add to the improvement of sleep quality. Polysomnography Behavioral sleep measures Meditation Insomnia Mantra CBT (Cognitive Behavioural Therapy) Hare Krishna Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction According to the US National Sleep Foundation, one out of every three people has insomnia at some point in their life. For instance, 18 million people in the US suffer from sleep apnea and 20 million suffer from restless leg syndrome (Institute of Medicine: US Committee on Sleep Medicine and Research, 2006). Numerous medications available, carry side effects. In addition, addiction occurs frequently to these medications (Huang, et al., 2014). Hence, there is a need of alternative therapeutic techniques for sleep disorders. Accord-based propositions in the American Association for Sleep Medicine (AASM) clinical guidelines (Schutte-Rodin, et al., 2008) regarding pharmacologic treatments for chronic insomnia suggest that medications are to be accompanied by cognitive behavioural therapy (CBT). A notable achievement in this field is the development and generalization of Cognitive Behavioural Therapy schemes and their variants for different disorders. Multi-component treatments like Cognitive Behavioural Therapy for Insomnia (CBT-I) demonstrated efficacy with results supported by large effect sizes on sleep logs and polysomnography parameters (Epstein, et al., 2012), but evidence from research points out only about 0.26 to 0.43 probability for a person to experience a complete elimination from insomnia after CBT (Buysse, et al., 2011; Morin, et al., 2009). Considering the increase in insomniacs, there is an imbalance between available CBT professionals and the number of insomnia sufferers (Prakash, 2007). There is a dire need for alternative therapies which are cost effective and can add to the list of well-established therapies for insomnia. National Health Interview Survey (NHIS) 2002 and 2007 survey data reveals a trend with 3.5% increase in the overall use of alternative therapies from 2002 to 2007. Among the class of alternative therapies, meditation-based therapies find a unique place in the literature, from the year 2006, meditation has been a part of the initiative for National Policy of Integrative and Complementary Practices of the National Health Service in Brazil (Field, 2009; Sampaio et al., 2017). Meditation was among the top five complementary health approaches performed by adults with a rise from 7.6% in 2002 to 9.4% in 2007, and 8% in 2012 (Clarke et al., 2015). Mantra meditation consists of meditation practices in which repeating a mantra (i.e., a word, sound, or symbol) is the principal constituent. It is speculated that Mantra-based chanting probably synchronizes the left and right hemispheres of brain. (Dudeja, 2017; Bhaskar et al., 2020). For instance, Harne and Hiwale (2018) conducted a study on OM based mantra meditation for the potential role of loud ‘OM’ chanting in offering relaxation (enhanced theta power and theta amplitude has been noticed in naïve meditators after meditation). Enhanced theta power across all cortical regions may reflect reductions in cortical arousal (Jacobs & Friedman 2004 ; Behera & Reddy 2014). Many spiritual schemes promote mantra-based chanting such as Niyyah – The intention, Salah – The formal prayer in Islam (Sayeed et al., 2013), and Monodic Christian chant, particularly Gregorian. Vedas, a huge body of literature originating in the ancient Indian sub-continent contains reference to Hare Krishna Mantra which is essentially a spiritual tool, said to have been designed to apparently "cleanse" the mind so as to attain spiritual consciousness. In Europe, a typical “grandmother advice” to children complaining of insomnia since centuries is “counting sheeps on a field”. Recently, several researchers mentioned achieving stress reduction (Niva et al., 2021) and improved psychosocial functioning (Wolf et al., 2003) after chanting Hare Krishna Mahamantra. Moving forward in a similar direction, we attempted to develop an adaptive therapy known as Hare Krishna Mantra Based Cognitive Therapy (HMBCT), which is a mantra meditation-based curriculum and it intermixes with behavioural techniques for insomnia. In the HMBCT method, we employed audible chanting of Hare Krishna Mahamantra as a possible alternative therapy for treatment of primary insomnia. Cognitive behavioural therapy for insomnia (CBT-I), a psychological and behavioural treatment with well-proven standards of efficacy (Morin et al., 1994) is a promising treatment. To start with, CBT-I was prescribed for the treatment of chronic or extreme cases of insomnia (Chesson et al., 1999). Although delivered as a transient intervention, it has long-term clinical implications (Morin et al., 1999). Conversely, pharmacologic interventions are less effective (Friedman, 2002; Krystal et al., 2003). Recently, several studies implemented mindfulness-based CBT or acceptance-based CBT for insomnia and perceived self-efficacy demonstrating significant effects in total waking time, sleep-onset latency, sleep quality, sleep efficiency, and PSQI global score (Gong et al., 2016; Charoensukmongkol, 2014). CBT-I treatment led to notable changes in sleep onset latency, waking time after sleep onset, total sleep time, sleep efficiency, and sleep quality among subjective sleep measures (DeViva et al., 2005). In a recent study which prescribed a CBT-I and IR (Imagery Rehearsal) treatment for a sample of 22 veterans (Ulmer et al., 2011), the treatment group showed an effective impact for subjective severity of insomnia and sleep quality contrasted with the monitor only control group. Deviations from sound sleep remain at clinically notable levels ensuing IR Therapy (Schoenfeld et al., 2012), while CBT-I has demonstrable impact on improving sleep related disturbances. IR Therapy requires professional help, while CBT-I can be provided by novice trainers (Manber et al., 2012). These novel therapies fall under the broader group of behavioural therapy. Examples include dialectic behavioural therapy (Linehan, 1993), acceptance and commitment therapy (Pankey & Hayes, 2003) and mindfulness-based cognitive therapy (Segal, Williams, & Teasdale, 2002). Anecdotal reports recently suggested the practice of Maha mantra meditation enhanced the sleep quality among primary insomnia subjects. Hence, this motivated us to pursue the combination of CBT-I and Mantra Chanting. This study has been designed and conducted as a pilot investigation to analyse the effect of principles of CBT-I (Stimulus Control Therapy: SCT and Sleep Hygiene) in conjunction with mantra-chanting based training. As a preliminary study, the primary objective of the therapy was to examine the impact of a 6-session, 6-week therapy on the sleep disturbances in primary insomnia in order to generate specific hypotheses for a larger controlled trial. Method Study design This study is based on a simple randomized parallel group HMBCT design and was executed at the Indian Institute of Technology, Kanpur, India. Baseline measurements were requested from the participants prior to the group assignment. Polysomnography recordings were taken from all subjects at pre-treatment and post-treatment time points. Every individual in the treatment group went through HMBCT chanting on the day of his/her recording along with other standard guidelines of CBT (Stimulus Control, Sleep Restriction Therapy, Sleep Hygiene etc. The control group participants were not given any mantra treatment and were told to listen to relaxing music of their choice before sleep while simultaneously following standard guidelines of CBT (Stimulus Control, Sleep Restriction Therapy, Sleep Hygiene etc.). We have collected the baseline recordings data even before the group assignment and treatment explanation to the subjects. Alongside, the participants were asked to keep a record of the sleep parameters like Total Sleep Time (TST), Number of Awakenings (NWAK), Time in Bed (TIB), Wake After Sleep Onset (WASO), Sleep Onset Latency (SOL), Total Nap time (TNT) by maintaining a regular electronic sleep diary (making daily entries in the morning and evening). Participants were randomly assigned to either the HMBCT treatment condition or a control group after the Polysomnography, Sleep Behavioural data, Sleep logs data has been collected. They were notified that the purpose of this research was to test the usefulness of an intervention for improving sleep quality in subjects with Primary Insomnia. The discussion with each participant is private and the instructions about the purpose and details of study are quite generic in nature for any participant to know if they are in control group or not. Also, the participants are mostly unknown to each other, while being sampled from diverse cultures and backgrounds, and disjoint degree programmes at the university. In other words, we ensured the control group never knew they were control. At all the time points in the study, the behavioural and polysomnography technicians and other staff at the sleep lab were unaware of the treatment given to each participant. Therapy sessions were conducted once a week away from the sleep lab where the sleep recordings took place. In particular, current work falls within the scope and satisfies the norms of Stage I as part of the Stage-wise Model of Behavioural Therapies (Rounsaville et al., 2001). The control group was included in order to examine the efficacy of Hare Krishna Maha mantra based treatment over the effects of just hearing to any relaxing music with other factors remaining the same in both the groups (Control and Therapy). For our study, an open trial comprising pre, mid, post treatment phases with inclusion of a control group was chosen. The entire experimental program from subject recruitment to therapy efficacy evaluation and follow-up is depicted in Fig. 1 . Participants 48 male (26 HMBCT group and 22 control group) participants with mean age of 25.23 (SD = 4.68) and 23.82 (SD = 3.01), respectively, volunteered for this study. They were recruited through advertisements. Several participants were also recommended by doctors. Their average education was 15.82 years. All participants maintained an Electronic Sleep Diary (ESD) during the one-week baseline period, for the duration of the six-week treatment or monitor-only periods, and in the course of the post-treatment, one week assessment period. Demographic data for the subjects from these two groups are shown in Table 1 . The group included persons 19–45 years old (mean age = 24.04 years). The specific inclusion criteria followed recommended guidelines for insomnia research (Edinger et al., 2004). The participants (1) met diagnostic criteria for Primary Insomnia screened through structured psychiatric and sleep interviews (Williams et al., 1992; First et al., 1996); (2) had no notable medical illnesses affecting sleep; (3) had a mean WASO and/or SOL > 30 mins in a week of sleep log monitoring; (4) complaints of daytime fatigue and sleepiness; (5) Insomnia Severity Index (ISI) > 15; and (6) had sleep disturbance of at least 3 nights per week for at least 6 months. Candidates were excluded who (1) reported alcohol or drug abuse or unstable current medication in the past year, non-clinically noteworthy insomnia (Edinger et al., 2004). (2) could not commit enough time to participate in the study (n = 6), and disagreed to take part. (3) had total sleep time (TST > 6 hrs), Sleep efficiency (SE > 85%), WASO > 60 mins in a week of sleep log monitoring, ISI > 22, and a stable sleep period between 22:00 and 08:00 hrs. All the participants were students or employees from the university and were chosen based on their informed consent and interest to participate in a study of 8 weeks duration. The investigation was carried out in accordance with the latest version of the Declaration of Helsinki. The Institute Ethics Committee of the technological institute approved this study (IITK/IEC/2015-16/2/1). Informed consent of the participants was recorded after the nature of the procedures had been explained to them. Both groups received the similar instructions that the study tries to measure sleep quality to nonpharmacological treatment. Screening Screening interviews were conducted during the pre-treatment period to determine the eligibility of the participants for the measurements. Only insomniacs at the early stage or primary period were included in the study based on the screening. The total number of participants enrolled were 74 males. Due to the difficulty in finding an experienced female polysomnographic technician, we could not work with female subjects in this preliminary study. The screening criteria were as follows: (1) Structured Clinical Interview for DSM-IV (SCID), a segment of the Duke Structured Interview for Sleep Disorders (DSISD), a medical record review. After the screening, some of the subjects were excluded based on: (1) unstable current medication (n = 7); (2) alcohol or substance abuse or dependence in the past year, non-clinically significant insomnia (n = 8); (3) not being able to meet Research Diagnostic Criteria for Insomnia (n = 5); (4) lack of commitment to appointment (n = 6). Screened Participants were randomly assigned in a blindfold manner to either the HMBCT treatment condition or a control group. The final screened subjects included 26 patients who received HMBCT and 22 who were allotted to the control group, out of which 1 dropped out in both the groups during the intervention period. Measures Duke Structured Interview for Sleep Disorders (DSISD), Folstein Mini-Mental Status Exam (MMSE), Sleep diary, Sleep ritual diaries, Insomnia Severity Index (ISI), Pre-Sleep Arousal Scale (PSAS), Pittsburgh sleep quality index (PSQI), Epworth Sleepiness Scale (ESS) and polysomnography based measures constitute the major measures used in this study. A detailed description about the measures can be found in supplementary material ( https://bit.ly/3fsj4r0 ). Polysomnography-based measures, Insomnia Severity Index (ISI), Pre-Sleep Arousal Scale (PSAS), Pittsburgh sleep quality index (PSQI) and Epworth Sleepiness Scale (ESS) constitute the primary measures. Duke Structured Interview for Sleep Disorders (DSISD), Folstein Mini-Mental Status Exam (MMSE), Sleep diary, Sleep ritual diaries constitute the secondary measures. The baseline characteristics of the primary and secondary measures are indicated in column I of Tables 2 , 3 &4 in the supplementary material ( https://bit.ly/3fsj4r0 ). Demographic distribution: Demographic distribution of the two groups is presented in Table 1 . The participants’ groups consisted of 48 men between 19 and 45 years old (mean = 24.06, SD = 4.5). All participants were Indians and either employees (n = 5) or students (n = 43) of IITK. Mean education duration of CBT group (mean = 16.22, SD = 2) is slightly higher than that of Monitor only music control group (mean = 15.42, SD = 1.21). Most of them were unmarried (n = 41) with a mean insomnia duration of 0.75 years. 16.67% of the participants had medical comorbidity and 10.42% had some psychiatric comorbidity. Table 1 Demographic characteristics for participating subjects (mean [Standard Deviation] or number (%)). Attributes HMBCT Group (Mean, Standard Deviation) Control group (Mean, Standard Deviation) Test Statistic Aggregate P value (N = 26) (N = 22) (N = 48) Age (years) (25.23, 4.68) (23.82, 3.01) t = 1.477 (24.06, 4.51) 0.147 Education (years) (16.22, 2.00) (15.42, 1.21) t = 1.599 (15.87, 1.50) 0.117 Marital Status (Indicated in the rows below) χ2(1) = 0.002 0.958 Married (4, 14.80) (3, 14.28) (7, 14.58) Unmarried (23, 85.20) (18, 85.72) (41, 85.42) Insomnia Duration, years (0.9, 0.64) (0.57, 0.24) t = 2.186 (0.75, 0.35) 0.034 Comorbidity (%) 16.67% χ2(1) = 0.008 .928 Medical (5, 18.50) (3, 14.28) (8, 16.67) Psychiatric (3, 11.10) (2, 9.50) (5, 10.42) Procedure As mentioned earlier, a total of 48 participants qualified for the final study after all the screening process. They were further randomized into HMBCT group (n = 26) and control group (n = 22). Due to the small sample size, simple randomization causes unequal sample sizes (Schulz & Grimes, 2002), hence we had 26 subjects in treatment group and 22 in control group, in contrary to an expected 24 subjects each. HMBCT group was led by one of the authors, one who has a formal training in mantra meditation and the other trainer is a professional sleep practitioner and a fellow of AASM (American Association of Sleep Medicine). The participants went through 6 weeks duration of HMBCT treatment, 1 week of baseline ESD (Electronic Sleep Diary) measurements. A total of 94 polysomnography recordings were collected (48 pre and 46 post treatment). Those who met the eligibility criteria were asked to maintain a sleep diary. One week before treatment, 3 weeks (after 3 sessions) through the middle of treatment and a week after 6 weeks of treatment, their sleep diary outcomes were assessed. Based on the answers in the questionnaires and the 1-week sleep diary outcomes, the participants were randomized into two groups - control (n = 22) and HMBCT group (n = 26). Those in the HMBCT group were scheduled for their 1st HMBCT training session within a week time and completed 6 sessions over the following 6 weeks. The control group was not given any training in HMBCT except for relaxing music and standard practices of CBT for Insomnia (Stimulus Control, Sleep Restriction therapy, Sleep Hygiene etc). The control group were alongside told to listen to their favorite music before sleeping. There was 1 dropout each in both the therapy and the control groups. After the 6th session, the participants completed the post intervention sleep diary over the last week. In the HMBCT method, each training session had three steps: the first step consists of a plain mindful meditation where subjects evaluate their entire day mentally in a meditative manner seated with backs straight. The second step consisted of an audible hearing and chanting of the mahamantra tune played as an audio sung by a senior practitioner while the subject is seated in a cross-legged sitting posture. The third step consisted of an audible hearing and chanting of the mahamantra tune played as an audio sung by a senior practitioner while the subject is in shavasana or in a lying down posture. All other strategies of CBT-I (Cognitive Behavioral Therapy for Insomnia) like stimulus control, sleep restriction etc are also taught to the subjects during training session. Sleep diary outcome measures can be found in supplementary material ( https://bit.ly/3fsj4r0 ). Also, based on the sleep diary measures, it is evident that the inclusion of three steps training of HMBCT helped enhance the sleep parameters compared to the case when they were only relying on stimulus control, sleep hygiene and sleep restriction. 6 training sessions of HMBCT were conducted in 6 weeks duration and subjects were also practicing it everyday before sleep. Stimulus control, sleep hygiene and sleep restriction are common to both groups, but the three step mantra chanting method taught in training session is practiced exclusively by HMBCT group. Each training session lasted on an average for 45 minutes. Data Analysis Data are available upon a reasonable request to the authors. Repeated-measures analysis of variance (ANOVA) was conducted on measures amassed at three time points (baseline, mid-treatment, and post-treatment) in both settings (monitor only control, intervention). In addition, a group of post-hoc paired t-tests were conducted on both the groups (control and treatment groups) comparing sleep and polysomnography indicators at baseline and after 4 months monitor only period. Cohen’s d (effect size) for mixed model comparisons were calculated as average group difference fractionated by pooled standard deviation. In addition, partial eta squared (effect size) as a measure of variance has been used in ANOVA. To verify the performance of treatment, various indices of clinical importance were calculated. For more details on data analysis, readers are referred to the supplementary material ( https://bit.ly/3fsj4r0 ). Specific results from this section containing effect size analysis for secondary measures are presented in Table 2 of the supplementary material ( https://bit.ly/3fsj4r0 ). Results Epworth Sleepiness Scale (ESS): For the ESS measure, a repeated measures ANOVA was conducted with group (HMBCT, Control) as the between and time (pre-treatment, mid-treatment, post-treatment) as the within-subjects variables. There was a significant main effect of time (F = 64.495, p < 0.001, η2 = 0.584) and group (F = 71.782, p < 0.001, η2 = 0.609) in addition to the significant time × group interaction (F = 12.288, p < 0.001, η2 = 0.211). Bonferroni multiple comparisons indicated no significant difference between groups at baseline (t = − .588, p = 0.559) and the control group did not change significantly over time across the baseline towards mid (p = 1) but changed significantly (p < 0.001) over the next half of the study. The HMBCT group (t = 10.1, p < 0.001, d = 1.4) changed significantly across the baseline towards the end of therapy period (corresponding p values are less than 0.001). Estimated marginal means plot in (Fig. 2 ) illustrates the significant interaction. Insomnia Severi ty Index ( ISI) : Repeated measures ANOVA with group (HMBCT, Control) as between-subjects variable and time (at time instants labelled pre, mid, post) as within-subjects variable shows a significant main effect of time (F = 49.930, p < 0.001, η2 = 0.520) and group (F = 161.186, p < 0.001, η2 = 0.778) in addition to the significant time × group interaction (F = 27.076, p < 0.001, η2 = 0.371). Bonferroni multiple comparisons indicated no significant difference between groups at baseline (t= -1.54, p = 0.128) but the difference became significant with time. The HMBCT group (t = 18.1, p < 0.001, d = 2.49) changed significantly across the baseline towards the end of therapy period (corresponding p values are less than 0.001), while the control group has not changed significantly. Estimated marginal means plot (Fig. 3 ) indicates the significant interaction. Post treatment mean ISI values are close to 7 indicating a decrease in insomnia symptoms due to the therapy. Close to 60% of the participants in the therapy group demonstrated no clinically relevant insomnia with ISI values less than 7. While 90% of subjects in the control group were not freed from insomnia. Pittsburg Sleep Quality Index ( PSQI) : Repeated measures ANOVA with group (HMBCT, Control) as the between-subjects variable and time (pre-treatment, mid-treatment, post-treatment) as the within-subject variable show a significant main effect of time (F = 77.794, p < 0.001, η2 = 0.628) and group (F = 61.040, p < 0.001, η2 = 0.570) in addition to the significant time × group interaction (F = 20.054, p < 0.001, η2 = 0.304). Bonferroni multiple comparisons indicate that there was by no means any significant difference between groups at baseline (t= -0.975, p = 0.334) but the difference became significant with time. The HMBCT group’s PSQI change from the baseline to the mid-treatment end period was statistically significant (t = 14.75, p < 0.001, d = 2.75) with corresponding p values less than 0.001 and also that from mid-treatment till the end-treatment period change of PSQI for treatment group is statistically significant (t = 5.387, p < 0.001, d = 1.03)). There is a statistically significant difference noticeable for the control group only from mid-treatment to post-treatment period. Estimated marginal means plot (Fig. 4 ) indicates the significant interaction. Post treatment Mean PSQI values are close to 5 indicating almost no difficulty in maintaining sleep. Cognitive PSAS (Pre Sleep Arousal Scale): Repeated measures ANOVA with group (HMBCT, Control) as the between-subjects variable and time (pre-treatment, mid-treatment, post-treatment) as the within-subject variable resulted into a significant main effect of time (F = 109.051, p < 0.001, η2 = 0.703) and group (F = 11.784, p < 0.001, η2 = 0.204)) in addition to the significant time × group interaction (F = 8.422, p < 0.001, η2 = 0.155). Bonferroni multiple comparisons indicated that there was no significant difference between groups at baseline (t= -0.730, p = 0.472) but the difference became significant with time. Both the HMBCT (t = 14.45, p < 0.001, d = 2.8) and control group’s scores changed significantly right from the baseline till the treatment end period (t = 11.126, p < 0.001, d = 2.5). Estimated marginal means plot (Fig. 5 ) demonstrates significant interaction. Somatic PSAS (Pre Sleep Arousal Scale) Repeated measures ANOVA with group (HMBCT, Control) as the between-subject variable and time (pre-treatment, mid- treatment, post-treatment) as the within-subject variable resulted into a significant main effect of both time (F = 10.716, p < 0.001, η2 = 0.189) and group (F = 36.228, p < 0.001, η2 = 0.441). A significant time × group interaction (F = 3.627, p < 0.001, η2 = 0.073) was also found. Bonferroni multiple comparisons indicate that there was no significant difference between groups at baseline (t= -1.315, p = 0.195) but the difference became significant only at post treatment period (t= -5.3818, p < 0.001). The HMBCT group’s scores changed significantly right from the baseline till the treatment end period (t = 6.638, p < 0.001, d = 1.296) while there are no statistically significant differences in the scores of the control group right from the baseline till the treatment end period. Estimated marginal means plot (Fig. 6 ) demonstrates significant interaction. The statistical analysis for sleep diary-based measures can be found in supplementary material ( https://bit.ly/3fsj4r0 ) and a summary of the same is included in the discussion section. Table 2 Sample Means of self-reported measures (ESS, ISI, PSQI, CogPSAS, Somatic PSAS) for both treatment and control groups in the format of Mean (Standard Deviation) Pre-treatment Mean (Standard Deviation) Mid-treatment Mean (Standard Deviation) Post-treatment Mean (Standard Deviation) ESS HMBCT Control 12.59 (1.91) 13.8 (3.2) 8.48 (0.51) 14.5 (2.9) 5.59 (0.50) 10.6 (2.7) ISI HMBCT Control 16.33 (3.71) 19.0 (3.6) 12.70 (3.06) 16.9 (3.2) 6.56 (2.95) 14.5 (2.9) PSQI HMBCT Control 13.81 (2.79) 13.3 (2.7) 10.30 (2.35) 13.4 (2.7) 4.78 (2.06) 12.7 (2.6) CogPSAS HMBCT Control 22.22 (3.71) 23.0 (3.1) 17.96 (2.56) 20.1 (2.6) 15.41 (1.39) 19.1 (1.8) Somatic PSAS HMBCT Control 14.30 (3.07) 13.5 (3.0) 12.00 (2.27) 13.1 (2.0) 11.00 (1.64) 13.0 (1.8) Table 3 - Sample Means and standard deviations for Sleep parameters from Polysomnography Behavioural recordings data in the format Mean (Standard Deviation) Polysomnography data Time in Bed (TIB) (in minutes) HMBCT Control Total Sleep Time, (in hours) HMBCT Control Sleep Efficiency (in percent) HMBCT Control Sleep Onset Latency, (in minutes) HMBCT Control Wake After Sleep Onset (WASO), (in minutes) HMBCT Control Total Arousals, (in minutes) HMBCT Control Percent Rapid Eye Movement Sleep, (in %) HMBCT Control Baseline 479.0(6.1) 474.2(11.5) 5.70(0.39) 5.73(0.47) 71.50(4.91) 72.41(5.33) 32.34(6.01) 29.75(5.63) 44.8(5.04) 42.93(4.57) 54.77(5.42) 48.9(5.13) 11.85(4.00) 11.97(3.47) Post-treatment 470.47(2.89) 466.0(4.0) 7.02(1.5) 6.37(1.0) 89.51(4.41) 81.92(4.16) 14.95(5.31) 21.85(5.50) 24.62(4.55) 33.48(3.80) 38.85(4.43) 42.02(9.35) 21.40(3.52) 17.43(5.13) Polysomnography (PSG) based Measures: PSG measurements are conducted in both the groups both before and after administering therapy. To address this kind of design both a univariate Analysis of covariance and paired t-test have been conducted. Time in Bed (TIB): A univariate analysis of covariance (ANCOVA) was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=15.642,P<0.001,\eta {\rho }^{2}=0.258\right)\) where the HMBCT group had a smaller TIB value at post-treatment. Paired samples t-test reveals statistically significant change in the mean TIB score in the HMBCT group \(\left(t\left(26\right)=7.266,P<0.001,d=1.39\right)\) . Total Sleep Time (TST): A univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=37.77,P<0.001,\eta {\rho }^{2}=0.456\right)\) where the HMBCT group had a larger TST value at post-treatment. Paired samples t-test reveals statistically significant change in the mean TST score in the HMBCT group \(\left(t\left(26\right)=-12.437,P<0.001,d=2.39\right)\) . Sleep Efficiency: A univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=34.94,P<0.001,\eta {\rho }^{2}=0.437\right)\) where, the HMBCT group had a larger Sleep Efficiency value at post- treatment. Paired samples t-test reveals statistically significant change in the mean Sleep Efficiency score in the HMBCT group \(\left(t\left(26\right)=-12.218,P<0.001,d=2.34\right)\) . Sleep Onset Latency (SOL): A univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=32.33,P<0.001,\eta {\rho }^{2}=0.418\right)\) . Paired samples t-test reveals statistically significant change in the mean Sleep onset latency score in the HMBCT group \(\left(t\left(26\right)=-12.273,P<0.001,d=2.36\right)\) . Wake After Sleep Onset (WASO): A univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=47.008,P<0.001,\eta {\rho }^{2}=0.511\right)\) . Paired samples t-test reveals statistically significant change in the mean Wake After Sleep onset (WASO) score in the HMBCT group \(\left(t\left(26\right)=-13.135,P<0.001,d=2.53\right)\) . Total Arousals: A univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=7.955,P<0.001,\eta {\rho }^{2}=0.150\right)\) where the HMBCT group had a smaller mean total arousals in their sleep at post-treatment. Paired samples t-test reveals statistically significant change in the mean total arousals score in the HMBCT group \(\left(t\left(26\right)=11.413,P<0.001,d=2.2\right)\) . Percentage REM (Rapid Eye Movement) sleep: A univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment measure value is chosen as the covariate. There is a statistically significant effect of group \(\left(F\left(\text{1,45}\right)=13.525,P<0.001,\eta {\rho }^{2}=0.231\right)\) where the HMBCT group had a larger mean percent REM sleep value at post-treatment. Paired samples t-test reveals statistically significant change in the mean percent REM sleep score in the HMBCT group \(\left(t\left(26\right)=-8.576,P<0.001,d=1.65\right)\) . Discussion The statistical analysis revealed evidence of intervention improving the outcome measures of sleep (namely TST, TIB, WASO, SOL, SE, NWAK, Total arousals, REM%, ISI, PSQI, ESS, PSAS). The magnitude of Cohen’s effect size in within-subjects framework was found to be large for NWAK (d = 1.48), total arousals (d = 2.2), TIB (d = 1.39), %SE (d = 2.34), ESS (d = 1.4), ISI (d = 2.49), PSQI (d = 2.75), WASO (d = 2.53) and moderate for TST (d = 2.39).In particular, the CBT-I portion of our therapy focused on relaxation training (the three step mantra based chanting follows in HMBCT belongs to the class of relaxation training technique in CBT-I (Perlis et al., 2006)) and behavioural attributes of stimulus control and sleep hygiene. 80% of the subjects experienced a 32% decrease in total arousals and a detailed examination of weekly differences in total arousals showed a quasi-linear trend with a mean per week reduction of (2–3) arousals across the 6 weeks of intervention. Towards the end of intervention, 7.4% of subjects in the HMBCT group met the diagnostic criteria for insomnia and about 2 subjects attained under the threshold for clinically noticeable insomnia on the ISI scale. The plot depicting fluctuations in TST indicated a gradual decline from baseline till week 2 of the intervention, because of the imposition of sleep restriction followed by a moderate growth across the next 4 weeks of providing intervention. Such a course is typical of behavioural therapy studies that incorporate sleep restriction and stimulus control (Perlis et al., 2006) and further extrapolation suggests that the possibility for further improvements beyond the six weeks period is high. Overall, this combined intervention of CBT-I and Mantra chanting showed many improvements in the sleep quality of the subjects with insomnia that are robust compared to several previous studies on CBT-I alone. The sleep ritual, as administered along with the chanting of mantra can be incorporated within the CBT-I framework. CBT-I is non-specific and requires trained practitioners to teach the participants. In this study, we have incorporated a few aspects of it and used a novel cognitive technique along with them. The intervention was easy to follow and showed an overall improvement of nocturnal sleep insomnia in the HMBCT group, reductions in sleep arousals, decrease in daytime sleepiness symptoms and sleep related disbeliefs, compared to the control group. The slight improvement in sleep quality of the control group may be attributed to psychological placebo attention effect and/or an effect of listening to preferred music. Most importantly, a strong impact of sleep ritual practices was observed on sleep quality improvement through reduction in sleep arousals and decrease in daytime sleepiness in the HMBCT group. The attendance, recruitment, and low dropout rates of the participants indicates that adults suffering from insomnia can be recruited and comply with such a composite setting of HMBCT treatment. The comprehensive consistency concerning the advocated sleep education guidelines is moderate. An average deviation of 10 minutes (SD = 6) between prescribed Time In Bed (TIB) and actual Time In Bed (TIB) and 12 minutes (SD = 7) was observed between prescribed Time Out of Bed (TOB) and actual Time Out of Bed (TOB). These variations are comparable to the compliance with sleep schedules reported for older adults (Chand & Grossberg, 2013) The compliance with sleep ritual sessions was moderate with 66.7% of the therapy group subjects going through the sleep ritual session on an average of 5 sessions per week, with a mean duration of 18 minutes per session. These results and evidence needs further testing on a large sample size. Limitations & Future Directions The pilot findings above necessitate further testing of the effectiveness of this treatment protocol. In this work, we largely focused on a preliminary evaluation of the treatment feasibility of HMBCT in a pilot trial in comparison with a control group who have received music of the subject’s choice. We also limited ourselves to students and employees of the Institute who all have completed their secondary education up to diploma, BTech, MTech, doctoral. The future work may also separately examine the effects of Hare Krishna Mantra chants compared to CBT-I (Cognitive Behavioural Therapy for Insomnia) on subjects diagnosed with primary sleep insomnia. A brief treatment manual is available at https://cutt.ly/tRXxGjz for readers as additional material. Future works should also incorporate power spectral analysis on sleep EEG recordings to evaluate the neural correlates of sleep insomnia (Kalak et al. 2012; Zhao et al. 2021). 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Cite Share Download PDF Status: Published Journal Publication published 27 Apr, 2023 Read the published version in Applied Psychophysiology and Biofeedback → Version 1 posted Editorial decision: Major revision 07 Feb, 2023 Reviews received at journal 27 Jan, 2023 Reviewers agreed at journal 17 Jan, 2023 Reviewers invited by journal 16 Jan, 2023 Editor assigned by journal 10 Jan, 2023 Submission checks completed at journal 10 Jan, 2023 First submitted to journal 07 Jan, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2453260","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":166488430,"identity":"faa67fec-1c74-4701-8ba9-f68078f9fecc","order_by":0,"name":"Chandan Kumar Behera","email":"","orcid":"","institution":"Yale University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chandan","middleName":"Kumar","lastName":"Behera","suffix":""},{"id":166488431,"identity":"8f31140f-df5c-45f9-83db-2ef40f07ad00","order_by":1,"name":"Tharun Kumar Reddy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYDACCTgrwYDhA4hmZmyACDBj18GDrIVxBkRLYwPRWph5ICyYNdiBvXTzs8+8Oxjy+dmTt0nbVNjJMbAztz+uYLCTZ2DnPYDVFpljxrN5zzBYzux5ViadcybZGOSwxjMMyYYNzHwJ2B2WYMzM28ZgYHAjx0w6t+1AYgNISwMDcwIDM48Bdi3pn8Fa7EFaLP8dqIdqqcejJQdqiwRQC2PDgQQGiJbDuLXcyClmnNsmYSBx5lmxZc+xZMM2oJaZDQbHgQzsWthnpG9meNtmY8Dfnrzxxo8aO3l+/uMPPjZUVAMZZ7BqgQJw7LCASTawgAGMgR8wfyBC0SgYBaNgFIxAAAAXM0y8uyE5MwAAAABJRU5ErkJggg==","orcid":"","institution":"Indian Institute of Technology Roorkee","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Tharun","middleName":"Kumar","lastName":"Reddy","suffix":""},{"id":166488433,"identity":"276da19b-b2c8-492a-b783-9043ec125b55","order_by":2,"name":"Laxmidhar Behera","email":"","orcid":"","institution":"Indian Institute of Technology Kanpur","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Laxmidhar","middleName":"","lastName":"Behera","suffix":""},{"id":166488435,"identity":"b54ca33b-ee15-4e08-81d1-6a5fa5d316bc","order_by":3,"name":"Niels Birbaumer","email":"","orcid":"","institution":"University of Tübingen","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Niels","middleName":"","lastName":"Birbaumer","suffix":""},{"id":166488436,"identity":"ff3a28f8-5839-4c06-8285-2fe7672413c7","order_by":4,"name":"Krishna Ika","email":"","orcid":"","institution":"Brain Wave Science Inc.","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Krishna","middleName":"","lastName":"Ika","suffix":""}],"badges":[],"createdAt":"2023-01-07 11:44:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2453260/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2453260/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10484-023-09586-2","type":"published","date":"2023-04-27T20:35:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":31480244,"identity":"9c7c34b3-6654-421c-924d-f7b15ba09eb3","added_by":"auto","created_at":"2023-01-12 13:40:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":120290,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental Program Flow-chart: Subject allocation after recruitment and exclusion followed by randomization to HMBCT and Control Groups\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/e575e22a9d0b2631a329ec5d.png"},{"id":31481366,"identity":"c2ab9c36-020d-40b7-8a85-5b717839cb48","added_by":"auto","created_at":"2023-01-12 13:48:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86293,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated Marginal Means (EMM) of ESS: Epworth Sleepiness scores (ESS) for HMBCT and control groups. Group × time interaction present (P\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/3607130dbcc00c65102f7e77.png"},{"id":31480238,"identity":"54de9566-5dc6-43fa-aac3-565c24fee7b0","added_by":"auto","created_at":"2023-01-12 13:40:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":107139,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated Marginal Means (EMM) of ISI: Insomnia Severity Index (ISI) for HMBCT group and Control group. Group × time interaction present (P\u0026lt;0.001)\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/b89fa851427f875975706967.png"},{"id":31480239,"identity":"666b2335-372b-475b-89db-35459dcb258e","added_by":"auto","created_at":"2023-01-12 13:40:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":104150,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated Marginal Means (EMM) of PSQI: Pittsburgh Sleep quality Index (PSQI) for HMBCT group and control group. Group × time interaction present (P\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/4d757c9663428a81dc23c2f0.png"},{"id":31481367,"identity":"5fea5c5c-3aaa-4c26-be14-23f13c04be05","added_by":"auto","created_at":"2023-01-12 13:48:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":104883,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated Marginal Means (EMM) of cogPSAS: Cognitive Pre-sleep arousal score (cogPSAS) for HMBCT group and Control group. Group × time interaction present (P\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/a5b487cca256e216ed3a9c34.png"},{"id":31482133,"identity":"b1011d6c-f16d-42de-b14e-d6c9875acdd7","added_by":"auto","created_at":"2023-01-12 13:56:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":96139,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated Marginal Means (EMM) of Somatic PSAS: Somatic Pre-sleep arousal score (somPSAS) for HMBCT group and Control group. Group× time interaction present (P\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/cff045578c71652f2a745f2b.png"},{"id":44726834,"identity":"37556926-1185-4347-b86c-cd62caac1bf5","added_by":"auto","created_at":"2023-10-16 20:49:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":989340,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2453260/v1/33471b3d-66ba-4e15-93b2-71e3e4dc392b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Meditation Based Cognitive Therapy (HMBCT) for Primary Insomnia: A treatment feasibility pilot study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the US National Sleep Foundation, one out of every three people has insomnia at some point in their life. For instance, 18\u0026nbsp;million people in the US suffer from sleep apnea and 20\u0026nbsp;million suffer from restless leg syndrome (Institute of Medicine: US Committee on Sleep Medicine and Research, 2006). Numerous medications available, carry side effects. In addition, addiction occurs frequently to these medications (Huang, et al., 2014). Hence, there is a need of alternative therapeutic techniques for sleep disorders. Accord-based propositions in the American Association for Sleep Medicine (AASM) clinical guidelines (Schutte-Rodin, et al., 2008) regarding pharmacologic treatments for chronic insomnia suggest that medications are to be accompanied by cognitive behavioural therapy (CBT). A notable achievement in this field is the development and generalization of Cognitive Behavioural Therapy schemes and their variants for different disorders. Multi-component treatments like Cognitive Behavioural Therapy for Insomnia (CBT-I) demonstrated efficacy with results supported by large effect sizes on sleep logs and polysomnography parameters (Epstein, et al., 2012), but evidence from research points out only about 0.26 to 0.43 probability for a person to experience a complete elimination from insomnia after CBT (Buysse, et al., 2011; Morin, et al., 2009). Considering the increase in insomniacs, there is an imbalance between available CBT professionals and the number of insomnia sufferers (Prakash, 2007). There is a dire need for alternative therapies which are cost effective and can add to the list of well-established therapies for insomnia. National Health Interview Survey (NHIS) 2002 and 2007 survey data reveals a trend with 3.5% increase in the overall use of alternative therapies from 2002 to 2007. Among the class of alternative therapies, meditation-based therapies find a unique place in the literature, from the year 2006, meditation has been a part of the initiative for National Policy of Integrative and Complementary Practices of the National Health Service in Brazil (Field, 2009; Sampaio et al., 2017). Meditation was among the top five complementary health approaches performed by adults with a rise from 7.6% in 2002 to 9.4% in 2007, and 8% in 2012 (Clarke et al., 2015). Mantra meditation consists of meditation practices in which repeating a mantra (i.e., a word, sound, or symbol) is the principal constituent. It is speculated that Mantra-based chanting probably synchronizes the left and right hemispheres of brain. (Dudeja, 2017; Bhaskar et al., 2020). For instance, Harne and Hiwale (2018) conducted a study on OM based mantra meditation for the potential role of loud ‘OM’ chanting in offering relaxation (enhanced theta power and theta amplitude has been noticed in naïve meditators after meditation). Enhanced theta power across all cortical regions may reflect reductions in cortical arousal (Jacobs \u0026amp; Friedman \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Behera \u0026amp; Reddy 2014).\u003c/p\u003e \u003cp\u003eMany spiritual schemes promote mantra-based chanting such as Niyyah – The intention, Salah – The formal prayer in Islam (Sayeed et al., 2013), and Monodic Christian chant, particularly Gregorian. Vedas, a huge body of literature originating in the ancient Indian sub-continent contains reference to Hare Krishna Mantra which is essentially a spiritual tool, said to have been designed to apparently \"cleanse\" the mind so as to attain spiritual consciousness. In Europe, a typical “grandmother advice” to children complaining of insomnia since centuries is “counting sheeps on a field”. Recently, several researchers mentioned achieving stress reduction (Niva et al., 2021) and improved psychosocial functioning (Wolf et al., 2003) after chanting Hare Krishna Mahamantra. Moving forward in a similar direction, we attempted to develop an adaptive therapy known as Hare Krishna Mantra Based Cognitive Therapy (HMBCT), which is a mantra meditation-based curriculum and it intermixes with behavioural techniques for insomnia. In the HMBCT method, we employed audible chanting of Hare Krishna Mahamantra as a possible alternative therapy for treatment of primary insomnia.\u003c/p\u003e \u003cp\u003eCognitive behavioural therapy for insomnia (CBT-I), a psychological and behavioural treatment with well-proven standards of efficacy (Morin et al., 1994) is a promising treatment. To start with, CBT-I was prescribed for the treatment of chronic or extreme cases of insomnia (Chesson et al., 1999). Although delivered as a transient intervention, it has long-term clinical implications (Morin et al., 1999). Conversely, pharmacologic interventions are less effective (Friedman, 2002; Krystal et al., 2003). Recently, several studies implemented mindfulness-based CBT or acceptance-based CBT for insomnia and perceived self-efficacy demonstrating significant effects in total waking time, sleep-onset latency, sleep quality, sleep efficiency, and PSQI global score (Gong et al., 2016; Charoensukmongkol, 2014).\u003c/p\u003e \u003cp\u003eCBT-I treatment led to notable changes in sleep onset latency, waking time after sleep onset, total sleep time, sleep efficiency, and sleep quality among subjective sleep measures (DeViva et al., 2005). In a recent study which prescribed a CBT-I and IR (Imagery Rehearsal) treatment for a sample of 22 veterans (Ulmer et al., 2011), the treatment group showed an effective impact for subjective severity of insomnia and sleep quality contrasted with the monitor only control group. Deviations from sound sleep remain at clinically notable levels ensuing IR Therapy (Schoenfeld et al., 2012), while CBT-I has demonstrable impact on improving sleep related disturbances. IR Therapy requires professional help, while CBT-I can be provided by novice trainers (Manber et al., 2012). These novel therapies fall under the broader group of behavioural therapy. Examples include dialectic behavioural therapy (Linehan, 1993), acceptance and commitment therapy (Pankey \u0026amp; Hayes, 2003) and mindfulness-based cognitive therapy (Segal, Williams, \u0026amp; Teasdale, 2002). Anecdotal reports recently suggested the practice of Maha mantra meditation enhanced the sleep quality among primary insomnia subjects. Hence, this motivated us to pursue the combination of CBT-I and Mantra Chanting.\u003c/p\u003e \u003cp\u003eThis study has been designed and conducted as a pilot investigation to analyse the effect of principles of CBT-I (Stimulus Control Therapy: SCT and Sleep Hygiene) in conjunction with mantra-chanting based training. As a preliminary study, the primary objective of the therapy was to examine the impact of a 6-session, 6-week therapy on the sleep disturbances in primary insomnia in order to generate specific hypotheses for a larger controlled trial.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003cdiv id=\"Sec7\" class=\"Section4\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Method","content":"\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003eThis study is based on a simple randomized parallel group HMBCT design and was executed at the Indian Institute of Technology, Kanpur, India. Baseline measurements were requested from the participants prior to the group assignment. Polysomnography recordings were taken from all subjects at pre-treatment and post-treatment time points. Every individual in the treatment group went through HMBCT chanting on the day of his/her recording along with other standard guidelines of CBT (Stimulus Control, Sleep Restriction Therapy, Sleep Hygiene etc. The control group participants were not given any mantra treatment and were told to listen to relaxing music of their choice before sleep while simultaneously following standard guidelines of CBT (Stimulus Control, Sleep Restriction Therapy, Sleep Hygiene etc.). We have collected the baseline recordings data even before the group assignment and treatment explanation to the subjects. Alongside, the participants were asked to keep a record of the sleep parameters like Total Sleep Time (TST), Number of Awakenings (NWAK), Time in Bed (TIB), Wake After Sleep Onset (WASO), Sleep Onset Latency (SOL), Total Nap time (TNT) by maintaining a regular electronic sleep diary (making daily entries in the morning and evening). Participants were randomly assigned to either the HMBCT treatment condition or a control group after the Polysomnography, Sleep Behavioural data, Sleep logs data has been collected. They were notified that the purpose of this research was to test the usefulness of an intervention for improving sleep quality in subjects with Primary Insomnia. The discussion with each participant is private and the instructions about the purpose and details of study are quite generic in nature for any participant to know if they are in control group or not. Also, the participants are mostly unknown to each other, while being sampled from diverse cultures and backgrounds, and disjoint degree programmes at the university. In other words, we ensured the control group never knew they were control. At all the time points in the study, the behavioural and polysomnography technicians and other staff at the sleep lab were unaware of the treatment given to each participant. Therapy sessions were conducted once a week away from the sleep lab where the sleep recordings took place. In particular, current work falls within the scope and satisfies the norms of Stage I as part of the Stage-wise Model of Behavioural Therapies (Rounsaville et al., 2001). The control group was included in order to examine the efficacy of Hare Krishna Maha mantra based treatment over the effects of just hearing to any relaxing music with other factors remaining the same in both the groups (Control and Therapy). For our study, an open trial comprising pre, mid, post treatment phases with inclusion of a control group was chosen. The entire experimental program from subject recruitment to therapy efficacy evaluation and follow-up is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003e48 male (26 HMBCT group and 22 control group) participants with mean age of 25.23 (SD = 4.68) and 23.82 (SD = 3.01), respectively, volunteered for this study. They were recruited through advertisements. Several participants were also recommended by doctors. Their average education was 15.82 years. All participants maintained an Electronic Sleep Diary (ESD) during the one-week baseline period, for the duration of the six-week treatment or monitor-only periods, and in the course of the post-treatment, one week assessment period. Demographic data for the subjects from these two groups are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The group included persons 19–45 years old (mean age = 24.04 years).\u003c/p\u003e\u003cp\u003e The specific inclusion criteria followed recommended guidelines for insomnia research (Edinger et al., 2004). The participants (1) met diagnostic criteria for Primary Insomnia screened through structured psychiatric and sleep interviews (Williams et al., 1992; First et al., 1996); (2) had no notable medical illnesses affecting sleep; (3) had a mean WASO and/or SOL \u0026gt; 30 mins in a week of sleep log monitoring; (4) complaints of daytime fatigue and sleepiness; (5) Insomnia Severity Index (ISI) \u0026gt; 15; and (6) had sleep disturbance of at least 3 nights per week for at least 6 months.\u003c/p\u003e\u003cp\u003eCandidates were excluded who (1) reported alcohol or drug abuse or unstable current medication in the past year, non-clinically noteworthy insomnia (Edinger et al., 2004). (2) could not commit enough time to participate in the study (n = 6), and disagreed to take part. (3) had total sleep time (TST \u0026gt; 6 hrs), Sleep efficiency (SE \u0026gt; 85%), WASO \u0026gt; 60 mins in a week of sleep log monitoring, ISI \u0026gt; 22, and a stable sleep period between 22:00 and 08:00 hrs.\u003c/p\u003e\u003cp\u003e All the participants were students or employees from the university and were chosen based on their informed consent and interest to participate in a study of 8 weeks duration. The investigation was carried out in accordance with the latest version of the Declaration of Helsinki. The Institute Ethics Committee of the technological institute approved this study (IITK/IEC/2015-16/2/1). Informed consent of the participants was recorded after the nature of the procedures had been explained to them. Both groups received the similar instructions that the study tries to measure sleep quality to nonpharmacological treatment.\u003c/p\u003e\u003ch2\u003eScreening\u003c/h2\u003e\u003cp\u003eScreening interviews were conducted during the pre-treatment period to determine the eligibility of the participants for the measurements. Only insomniacs at the early stage or primary period were included in the study based on the screening. The total number of participants enrolled were 74 males. Due to the difficulty in finding an experienced female polysomnographic technician, we could not work with female subjects in this preliminary study. The screening criteria were as follows: (1) Structured Clinical Interview for DSM-IV (SCID), a segment of the Duke Structured Interview for Sleep Disorders (DSISD), a medical record review. After the screening, some of the subjects were excluded based on: (1) unstable current medication (n = 7); (2) alcohol or substance abuse or dependence in the past year, non-clinically significant insomnia (n = 8); (3) not being able to meet Research Diagnostic Criteria for Insomnia (n = 5); (4) lack of commitment to appointment (n = 6). Screened Participants were randomly assigned in a blindfold manner to either the HMBCT treatment condition or a control group. The final screened subjects included 26 patients who received HMBCT and 22 who were allotted to the control group, out of which 1 dropped out in both the groups during the intervention period.\u003c/p\u003e\u003ch2\u003eMeasures\u003c/h2\u003e\u003cp\u003eDuke Structured Interview for Sleep Disorders (DSISD), Folstein Mini-Mental Status Exam (MMSE), Sleep diary, Sleep ritual diaries, Insomnia Severity Index (ISI), Pre-Sleep Arousal Scale (PSAS), Pittsburgh sleep quality index (PSQI), Epworth Sleepiness Scale (ESS) and polysomnography based measures constitute the major measures used in this study. A detailed description about the measures can be found in supplementary material (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bit.ly/3fsj4r0\u003c/span\u003e\u003cspan address=\"https://bit.ly/3fsj4r0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Polysomnography-based measures, Insomnia Severity Index (ISI), Pre-Sleep Arousal Scale (PSAS), Pittsburgh sleep quality index (PSQI) and Epworth Sleepiness Scale (ESS) constitute the primary measures. Duke Structured Interview for Sleep Disorders (DSISD), Folstein Mini-Mental Status Exam (MMSE), Sleep diary, Sleep ritual diaries constitute the secondary measures. The baseline characteristics of the primary and secondary measures are indicated in column I of Tables \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e,\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026amp;4 in the supplementary material (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bit.ly/3fsj4r0\u003c/span\u003e\u003cspan address=\"https://bit.ly/3fsj4r0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e\u003ch2\u003eDemographic distribution:\u003c/h2\u003e\u003cp\u003eDemographic distribution of the two groups is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The participants’ groups consisted of 48 men between 19 and 45 years old (mean = 24.06, SD = 4.5). All participants were Indians and either employees (n = 5) or students (n = 43) of IITK. Mean education duration of CBT group (mean = 16.22, SD = 2) is slightly higher than that of Monitor only music control group (mean = 15.42, SD = 1.21). Most of them were unmarried (n = 41) with a mean insomnia duration of 0.75 years. 16.67% of the participants had medical comorbidity and 10.42% had some psychiatric comorbidity.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics for participating subjects (mean [Standard Deviation] or number (%)).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttributes\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHMBCT Group\u003c/p\u003e \u003cp\u003e(Mean, Standard Deviation)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003cp\u003e(Mean, Standard Deviation)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest Statistic\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAggregate\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(N = 26)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(N = 22)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(N = 48)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(25.23, 4.68)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(23.82, 3.01)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et = 1.477\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(24.06, 4.51)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(16.22, 2.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(15.42, 1.21)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et = 1.599\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(15.87, 1.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(Indicated in the rows below)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ2(1)\u003c/p\u003e \u003cp\u003e= 0.002\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarried\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4, 14.80)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3, 14.28)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(7, 14.58)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnmarried\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(23, 85.20)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(18, 85.72)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(41, 85.42)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsomnia Duration, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.9, 0.64)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.57, 0.24)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et = 2.186\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.75, 0.35)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.67%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ2(1)\u003c/p\u003e \u003cp\u003e= 0.008\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.928\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(5, 18.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3, 14.28)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(8, 16.67)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychiatric\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(3, 11.10)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2, 9.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(5, 10.42)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eProcedure\u003c/h2\u003e\u003cp\u003eAs mentioned earlier, a total of 48 participants qualified for the final study after all the screening process. They were further randomized into HMBCT group (n = 26) and control group (n = 22). Due to the small sample size, simple randomization causes unequal sample sizes (Schulz \u0026amp; Grimes, 2002), hence we had 26 subjects in treatment group and 22 in control group, in contrary to an expected 24 subjects each. HMBCT group was led by one of the authors, one who has a formal training in mantra meditation and the other trainer is a professional sleep practitioner and a fellow of AASM (American Association of Sleep Medicine). The participants went through 6 weeks duration of HMBCT treatment, 1 week of baseline ESD (Electronic Sleep Diary) measurements. A total of 94 polysomnography recordings were collected (48 pre and 46 post treatment). Those who met the eligibility criteria were asked to maintain a sleep diary. One week before treatment, 3 weeks (after 3 sessions) through the middle of treatment and a week after 6 weeks of treatment, their sleep diary outcomes were assessed. Based on the answers in the questionnaires and the 1-week sleep diary outcomes, the participants were randomized into two groups - control (n = 22) and HMBCT group (n = 26). Those in the HMBCT group were scheduled for their 1st HMBCT training session within a week time and completed 6 sessions over the following 6 weeks. The control group was not given any training in HMBCT except for relaxing music and standard practices of CBT for Insomnia (Stimulus Control, Sleep Restriction therapy, Sleep Hygiene etc). The control group were alongside told to listen to their favorite music before sleeping. There was 1 dropout each in both the therapy and the control groups. After the 6th session, the participants completed the post intervention sleep diary over the last week.\u003c/p\u003e\u003cp\u003eIn the HMBCT method, each training session had three steps: the first step consists of a plain mindful meditation where subjects evaluate their entire day mentally in a meditative manner seated with backs straight. The second step consisted of an audible hearing and chanting of the mahamantra tune played as an audio sung by a senior practitioner while the subject is seated in a cross-legged sitting posture. The third step consisted of an audible hearing and chanting of the mahamantra tune played as an audio sung by a senior practitioner while the subject is in shavasana or in a lying down posture. All other strategies of CBT-I (Cognitive Behavioral Therapy for Insomnia) like stimulus control, sleep restriction etc are also taught to the subjects during training session. Sleep diary outcome measures can be found in supplementary material (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bit.ly/3fsj4r0\u003c/span\u003e\u003cspan address=\"https://bit.ly/3fsj4r0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Also, based on the sleep diary measures, it is evident that the inclusion of three steps training of HMBCT helped enhance the sleep parameters compared to the case when they were only relying on stimulus control, sleep hygiene and sleep restriction. 6 training sessions of HMBCT were conducted in 6 weeks duration and subjects were also practicing it everyday before sleep. Stimulus control, sleep hygiene and sleep restriction are common to both groups, but the three step mantra chanting method taught in training session is practiced exclusively by HMBCT group. Each training session lasted on an average for 45 minutes.\u003c/p\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eData are available upon a reasonable request to the authors. Repeated-measures analysis of variance (ANOVA) was conducted on measures amassed at three time points (baseline, mid-treatment, and post-treatment) in both settings (monitor only control, intervention). In addition, a group of post-hoc paired t-tests were conducted on both the groups (control and treatment groups) comparing sleep and polysomnography indicators at baseline and after 4 months monitor only period. Cohen’s d (effect size) for mixed model comparisons were calculated as average group difference fractionated by pooled standard deviation. In addition, partial eta squared (effect size) as a measure of variance has been used in ANOVA. To verify the performance of treatment, various indices of clinical importance were calculated. For more details on data analysis, readers are referred to the supplementary material (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bit.ly/3fsj4r0\u003c/span\u003e\u003cspan address=\"https://bit.ly/3fsj4r0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Specific results from this section containing effect size analysis for secondary measures are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e of the supplementary material (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bit.ly/3fsj4r0\u003c/span\u003e\u003cspan address=\"https://bit.ly/3fsj4r0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eEpworth Sleepiness Scale (ESS):\u003c/h2\u003e\n \u003cp\u003eFor the ESS measure, a repeated measures ANOVA was conducted with group (HMBCT, Control) as the between and time (pre-treatment, mid-treatment, post-treatment) as the within-subjects variables. There was a significant main effect of time (F\u0026thinsp;=\u0026thinsp;64.495, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.584) and group (F\u0026thinsp;=\u0026thinsp;71.782, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.609) in addition to the significant time \u0026times; group interaction (F\u0026thinsp;=\u0026thinsp;12.288, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.211). Bonferroni multiple comparisons indicated no significant difference between groups at baseline (t\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.588, p\u0026thinsp;=\u0026thinsp;0.559) and the control group did not change significantly over time across the baseline towards mid (p\u0026thinsp;=\u0026thinsp;1) but changed significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) over the next half of the study. The HMBCT group (t\u0026thinsp;=\u0026thinsp;10.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.4) changed significantly across the baseline towards the end of therapy period (corresponding p values are less than 0.001). Estimated marginal means plot in (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) illustrates the significant interaction.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInsomnia Severi\u003c/strong\u003e\u003cstrong\u003ety Index (\u003c/strong\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003e\u003cstrong\u003eISI)\u003c/strong\u003e\u003c/span\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eRepeated measures ANOVA with group (HMBCT, Control) as between-subjects variable and time (at time instants labelled pre, mid, post) as within-subjects variable shows a significant main effect of time (F\u0026thinsp;=\u0026thinsp;49.930, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.520) and group (F\u0026thinsp;=\u0026thinsp;161.186, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.778) in addition to the significant time \u0026times; group interaction (F\u0026thinsp;=\u0026thinsp;27.076, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.371). Bonferroni multiple comparisons indicated no significant difference between groups at baseline (t= -1.54, p\u0026thinsp;=\u0026thinsp;0.128) but the difference became significant with time. The HMBCT group (t\u0026thinsp;=\u0026thinsp;18.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;2.49) changed significantly across the baseline towards the end of therapy period (corresponding p values are less than 0.001), while the control group has not changed significantly. Estimated marginal means plot (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e) indicates the significant interaction. Post treatment mean ISI values are close to 7 indicating a decrease in insomnia symptoms due to the therapy. Close to 60% of the participants in the therapy group demonstrated no clinically relevant insomnia with ISI values less than 7. While 90% of subjects in the control group were not freed from insomnia.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePittsburg Sleep Quality Index (\u003c/strong\u003e \u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003ePSQI)\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eRepeated measures ANOVA with group (HMBCT, Control) as the between-subjects variable and time (pre-treatment, mid-treatment, post-treatment) as the within-subject variable show a significant main effect of time (F\u0026thinsp;=\u0026thinsp;77.794, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.628) and group (F\u0026thinsp;=\u0026thinsp;61.040, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.570) in addition to the significant time \u0026times; group interaction (F\u0026thinsp;=\u0026thinsp;20.054, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.304). Bonferroni multiple comparisons indicate that there was by no means any significant difference between groups at baseline (t= -0.975, p\u0026thinsp;=\u0026thinsp;0.334) but the difference became significant with time. The HMBCT group\u0026rsquo;s PSQI change from the baseline to the mid-treatment end period was statistically significant (t\u0026thinsp;=\u0026thinsp;14.75, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;2.75) with corresponding p values less than 0.001 and also that from mid-treatment till the end-treatment period change of PSQI for treatment group is statistically significant (t\u0026thinsp;=\u0026thinsp;5.387, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.03)).\u003c/p\u003e\n \u003cp\u003eThere is a statistically significant difference noticeable for the control group only from mid-treatment to post-treatment period. Estimated marginal means plot (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e) indicates the significant interaction. Post treatment Mean PSQI values are close to 5 indicating almost no difficulty in maintaining sleep.\u003c/p\u003e\n \u003cdiv class=\"Section3\" id=\"Sec12\"\u003e\n \u003ch2\u003eCognitive PSAS (Pre Sleep Arousal Scale):\u003c/h2\u003e\n \u003cp\u003eRepeated measures ANOVA with group (HMBCT, Control) as the between-subjects variable and time (pre-treatment, mid-treatment, post-treatment) as the within-subject variable resulted into a significant main effect of time (F\u0026thinsp;=\u0026thinsp;109.051, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.703) and group (F\u0026thinsp;=\u0026thinsp;11.784, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.204)) in addition to the significant time \u0026times; group interaction (F\u0026thinsp;=\u0026thinsp;8.422, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.155). Bonferroni multiple comparisons indicated that there was no significant difference between groups at baseline (t= -0.730, p\u0026thinsp;=\u0026thinsp;0.472) but the difference became significant with time. Both the HMBCT (t\u0026thinsp;=\u0026thinsp;14.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;2.8) and control group\u0026rsquo;s scores changed significantly right from the baseline till the treatment end period (t\u0026thinsp;=\u0026thinsp;11.126, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;2.5). Estimated marginal means plot (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) demonstrates significant interaction.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section3\" id=\"Sec13\"\u003e\n \u003ch2\u003eSomatic PSAS (Pre Sleep Arousal Scale)\u003c/h2\u003e\n \u003cp\u003eRepeated measures ANOVA with group (HMBCT, Control) as the between-subject variable and time (pre-treatment, mid- treatment, post-treatment) as the within-subject variable resulted into a significant main effect of both time (F\u0026thinsp;=\u0026thinsp;10.716, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.189) and group (F\u0026thinsp;=\u0026thinsp;36.228, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.441). A significant time \u0026times; group interaction (F\u0026thinsp;=\u0026thinsp;3.627, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;2\u0026thinsp;=\u0026thinsp;0.073) was also found. Bonferroni multiple comparisons indicate that there was no significant difference between groups at baseline (t= -1.315, p\u0026thinsp;=\u0026thinsp;0.195) but the difference became significant only at post treatment period (t= -5.3818, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The HMBCT group\u0026rsquo;s scores changed significantly right from the baseline till the treatment end period (t\u0026thinsp;=\u0026thinsp;6.638, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, d\u0026thinsp;=\u0026thinsp;1.296) while there are no statistically significant differences in the scores of the control group right from the baseline till the treatment end period. Estimated marginal means plot (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e) demonstrates significant interaction.\u003c/p\u003e\n \u003cp\u003eThe statistical analysis for sleep diary-based measures can be found in supplementary material (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bit.ly/3fsj4r0\u003c/span\u003e\u003c/span\u003e) and a summary of the same is included in the \u003cspan class=\"InternalRef\"\u003ediscussion\u003c/span\u003e section.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSample Means of self-reported measures (ESS, ISI, PSQI, CogPSAS, Somatic PSAS) for both treatment and control groups in the format of Mean (Standard Deviation)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePre-treatment\u003c/p\u003e\n \u003cp\u003eMean (Standard Deviation)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMid-treatment\u003c/p\u003e\n \u003cp\u003eMean (Standard Deviation)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePost-treatment\u003c/p\u003e\n \u003cp\u003eMean (Standard Deviation)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eESS\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.59 (1.91)\u003c/p\u003e\n \u003cp\u003e13.8 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.48 (0.51)\u003c/p\u003e\n \u003cp\u003e14.5 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.59 (0.50)\u003c/p\u003e\n \u003cp\u003e10.6 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eISI\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.33 (3.71)\u003c/p\u003e\n \u003cp\u003e19.0 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.70 (3.06)\u003c/p\u003e\n \u003cp\u003e16.9 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.56 (2.95)\u003c/p\u003e\n \u003cp\u003e14.5 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSQI\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.81 (2.79)\u003c/p\u003e\n \u003cp\u003e13.3 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.30 (2.35)\u003c/p\u003e\n \u003cp\u003e13.4 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.78 (2.06)\u003c/p\u003e\n \u003cp\u003e12.7 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCogPSAS\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.22 (3.71)\u003c/p\u003e\n \u003cp\u003e23.0 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.96 (2.56)\u003c/p\u003e\n \u003cp\u003e20.1 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.41 (1.39)\u003c/p\u003e\n \u003cp\u003e19.1 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSomatic PSAS\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.30 (3.07)\u003c/p\u003e\n \u003cp\u003e13.5 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.00 (2.27)\u003c/p\u003e\n \u003cp\u003e13.1 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.00 (1.64)\u003c/p\u003e\n \u003cp\u003e13.0 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e- Sample Means and standard deviations for Sleep parameters from Polysomnography Behavioural recordings data in the format Mean (Standard Deviation)\u003c/p\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"margin-right: calc(39%); width: 61%;\" width=\"509\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50.4377%;\" valign=\"top\" width=\"47.347740667976424%\"\u003e\n \u003cp\u003ePolysomnography data\u003c/p\u003e\n \u003cp\u003eTime in Bed (TIB) (in minutes)\u003cbr\u003e\u0026nbsp;HMBCT\u003cbr\u003e\u0026nbsp;Control\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;Total Sleep Time, (in hours)\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSleep Efficiency (in percent)\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSleep Onset Latency, (in minutes)\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWake After Sleep Onset (WASO), (in minutes)\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTotal Arousals, (in minutes)\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePercent Rapid Eye Movement Sleep, (in %)\u003c/p\u003e\n \u003cp\u003eHMBCT\u003c/p\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9274%;\" valign=\"top\" width=\"24.75442043222004%\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003cp\u003e479.0(6.1)\u003c/p\u003e\n \u003cp\u003e474.2(11.5)\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;5.70(0.39)\u003c/p\u003e\n \u003cp\u003e5.73(0.47)\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e71.50(4.91)\u003c/p\u003e\n \u003cp\u003e72.41(5.33)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32.34(6.01)\u003c/p\u003e\n \u003cp\u003e29.75(5.63)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e44.8(5.04)\u003c/p\u003e\n \u003cp\u003e42.93(4.57)\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;54.77(5.42)\u003c/p\u003e\n \u003cp\u003e48.9(5.13)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11.85(4.00)\u003c/p\u003e\n \u003cp\u003e11.97(3.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.5124%;\" valign=\"top\" width=\"27.897838899803535%\"\u003e\n \u003cp\u003ePost-treatment\u003c/p\u003e\n \u003cp\u003e470.47(2.89)\u003c/p\u003e\n \u003cp\u003e466.0(4.0)\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;7.02(1.5)\u003c/p\u003e\n \u003cp\u003e6.37(1.0)\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e89.51(4.41)\u003c/p\u003e\n \u003cp\u003e81.92(4.16)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14.95(5.31)\u003c/p\u003e\n \u003cp\u003e21.85(5.50)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24.62(4.55)\u003c/p\u003e\n \u003cp\u003e33.48(3.80)\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;38.85(4.43)\u003c/p\u003e\n \u003cp\u003e42.02(9.35)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.40(3.52)\u003c/p\u003e\n \u003cp\u003e17.43(5.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u003cspan style=\"text-align: inherit;\"\u003ePolysomnography (PSG) based Measures:\u003c/span\u003e\u003c/div\u003e\n \u003cp\u003ePSG measurements are conducted in both the groups both before and after administering therapy. To address this kind of design both a univariate Analysis of covariance and paired t-test have been conducted.\u003c/p\u003e\n \u003cp\u003eTime in Bed (TIB):\u003c/p\u003e\n \u003cp\u003eA univariate analysis of covariance (ANCOVA) was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=15.642,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.258\\right)\\)\u003c/span\u003e\u003c/span\u003e where the HMBCT group had a smaller TIB value at post-treatment. Paired samples t-test reveals statistically significant change in the mean TIB score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=7.266,P\u0026lt;0.001,d=1.39\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eTotal Sleep Time (TST):\u003c/p\u003e\n \u003cp\u003eA univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=37.77,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.456\\right)\\)\u003c/span\u003e\u003c/span\u003e where the HMBCT group had a larger TST value at post-treatment. Paired samples t-test reveals statistically significant change in the mean TST score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=-12.437,P\u0026lt;0.001,d=2.39\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eSleep Efficiency:\u003c/p\u003e\n \u003cp\u003eA univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=34.94,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.437\\right)\\)\u003c/span\u003e\u003c/span\u003e where, the HMBCT group had a larger Sleep Efficiency value at post- treatment. Paired samples t-test reveals statistically significant change in the mean Sleep Efficiency score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=-12.218,P\u0026lt;0.001,d=2.34\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eSleep Onset Latency (SOL):\u003c/p\u003e\n \u003cp\u003eA univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=32.33,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.418\\right)\\)\u003c/span\u003e\u003c/span\u003e. Paired samples t-test reveals statistically significant change in the mean Sleep onset latency score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=-12.273,P\u0026lt;0.001,d=2.36\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eWake After Sleep Onset (WASO):\u003c/p\u003e\n \u003cp\u003eA univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=47.008,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.511\\right)\\)\u003c/span\u003e\u003c/span\u003e. Paired samples t-test reveals statistically significant change in the mean Wake After Sleep onset (WASO) score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=-13.135,P\u0026lt;0.001,d=2.53\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eTotal Arousals:\u003c/p\u003e\n \u003cp\u003eA univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment PSG measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=7.955,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.150\\right)\\)\u003c/span\u003e\u003c/span\u003e where the HMBCT group had a smaller mean total arousals in their sleep at post-treatment. Paired samples t-test reveals statistically significant change in the mean total arousals score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=11.413,P\u0026lt;0.001,d=2.2\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003ePercentage REM (Rapid Eye Movement) sleep:\u003c/p\u003e\n \u003cp\u003eA univariate ANCOVA was conducted with group (HMBCT, Control) as the between subjects variable and pre-treatment measure value is chosen as the covariate. There is a statistically significant effect of group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(F\\left(\\text{1,45}\\right)=13.525,P\u0026lt;0.001,\\eta {\\rho }^{2}=0.231\\right)\\)\u003c/span\u003e\u003c/span\u003e where the HMBCT group had a larger mean percent REM sleep value at post-treatment. Paired samples t-test reveals statistically significant change in the mean percent REM sleep score in the HMBCT group \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(t\\left(26\\right)=-8.576,P\u0026lt;0.001,d=1.65\\right)\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe statistical analysis revealed evidence of intervention improving the outcome measures of sleep (namely TST, TIB, WASO, SOL, SE, NWAK, Total arousals, REM%, ISI, PSQI, ESS, PSAS). The magnitude of Cohen\u0026rsquo;s effect size in within-subjects framework was found to be large for NWAK (d\u0026thinsp;=\u0026thinsp;1.48), total arousals (d\u0026thinsp;=\u0026thinsp;2.2), TIB (d\u0026thinsp;=\u0026thinsp;1.39), %SE (d\u0026thinsp;=\u0026thinsp;2.34), ESS (d\u0026thinsp;=\u0026thinsp;1.4), ISI (d\u0026thinsp;=\u0026thinsp;2.49), PSQI (d\u0026thinsp;=\u0026thinsp;2.75), WASO (d\u0026thinsp;=\u0026thinsp;2.53) and moderate for TST (d\u0026thinsp;=\u0026thinsp;2.39).In particular, the CBT-I portion of our therapy focused on relaxation training (the three step mantra based chanting follows in HMBCT belongs to the class of relaxation training technique in CBT-I (Perlis et al., 2006)) and behavioural attributes of stimulus control and sleep hygiene. 80% of the subjects experienced a 32% decrease in total arousals and a detailed examination of weekly differences in total arousals showed a quasi-linear trend with a mean per week reduction of (2\u0026ndash;3) arousals across the 6 weeks of intervention. Towards the end of intervention, 7.4% of subjects in the HMBCT group met the diagnostic criteria for insomnia and about 2 subjects attained under the threshold for clinically noticeable insomnia on the ISI scale. The plot depicting fluctuations in TST indicated a gradual decline from baseline till week 2 of the intervention, because of the imposition of sleep restriction followed by a moderate growth across the next 4 weeks of providing intervention. Such a course is typical of behavioural therapy studies that incorporate sleep restriction and stimulus control (Perlis et al., 2006) and further extrapolation suggests that the possibility for further improvements beyond the six weeks period is high. Overall, this combined intervention of CBT-I and Mantra chanting showed many improvements in the sleep quality of the subjects with insomnia that are robust compared to several previous studies on CBT-I alone.\u003c/p\u003e \u003cp\u003eThe sleep ritual, as administered along with the chanting of mantra can be incorporated within the CBT-I framework. CBT-I is non-specific and requires trained practitioners to teach the participants. In this study, we have incorporated a few aspects of it and used a novel cognitive technique along with them. The intervention was easy to follow and showed an overall improvement of nocturnal sleep insomnia in the HMBCT group, reductions in sleep arousals, decrease in daytime sleepiness symptoms and sleep related disbeliefs, compared to the control group. The slight improvement in sleep quality of the control group may be attributed to psychological placebo attention effect and/or an effect of listening to preferred music. Most importantly, a strong impact of sleep ritual practices was observed on sleep quality improvement through reduction in sleep arousals and decrease in daytime sleepiness in the HMBCT group.\u003c/p\u003e \u003cp\u003eThe attendance, recruitment, and low dropout rates of the participants indicates that adults suffering from insomnia can be recruited and comply with such a composite setting of HMBCT treatment. The comprehensive consistency concerning the advocated sleep education guidelines is moderate. An average deviation of 10 minutes (SD\u0026thinsp;=\u0026thinsp;6) between prescribed Time In Bed (TIB) and actual Time In Bed (TIB) and 12 minutes (SD\u0026thinsp;=\u0026thinsp;7) was observed between prescribed Time Out of Bed (TOB) and actual Time Out of Bed (TOB). These variations are comparable to the compliance with sleep schedules reported for older adults (Chand \u0026amp; Grossberg, 2013) The compliance with sleep ritual sessions was moderate with 66.7% of the therapy group subjects going through the sleep ritual session on an average of 5 sessions per week, with a mean duration of 18 minutes per session. These results and evidence needs further testing on a large sample size.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations \u0026amp; Future Directions\u003c/h2\u003e \u003cp\u003eThe pilot findings above necessitate further testing of the effectiveness of this treatment protocol. In this work, we largely focused on a preliminary evaluation of the treatment feasibility of HMBCT in a pilot trial in comparison with a control group who have received music of the subject\u0026rsquo;s choice. We also limited ourselves to students and employees of the Institute who all have completed their secondary education up to diploma, BTech, MTech, doctoral. The future work may also separately examine the effects of Hare Krishna Mantra chants compared to CBT-I (Cognitive Behavioural Therapy for Insomnia) on subjects diagnosed with primary sleep insomnia. A brief treatment manual is available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cutt.ly/tRXxGjz\u003c/span\u003e\u003cspan address=\"https://cutt.ly/tRXxGjz\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e for readers as additional material. Future works should also incorporate power spectral analysis on sleep EEG recordings to evaluate the neural correlates of sleep insomnia (Kalak et al. 2012; Zhao et al. 2021). It was claimed that high frequency in REM correlates with higher sleep efficiency (Zhao et al. 2021), It was also reported that the Heart Rate Variability parameters (HRV) increase with the psychological well-being (Damerla et al., 2018).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;All procedures performed in studies involving human Participants were in accordance with the ethical standards of the institutional and/or Indian Council for Medical Research or comparable ethical standards (IITK/IEC/2015-16/2/1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed-Consent\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Informed written\u0026nbsp;consent was obtained from all individual participants included in the study.\u003cbr\u003e\u0026nbsp;\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Funding details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work of the corresponding author was supported by the Institute funds under contingency head of the Projects TCS/CS/2011191A, SRG/2022/001886 (SER-1968-ECD), FIG-100953.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBehera, C. 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EEG Spectral Analysis in Insomnia Disorder: A Systematic Review and Meta-Analysis. \u003cem\u003eSleep Medicine Reviews\u003c/em\u003e, 101457.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Polysomnography, Behavioral sleep measures, Meditation, Insomnia, Mantra, CBT (Cognitive Behavioural Therapy), Hare Krishna","lastPublishedDoi":"10.21203/rs.3.rs-2453260/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2453260/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevious evidence suggests a critical need for alternative therapies which are cost-effective and can add to the list of well-established treatments for insomnia. This pilot study evaluates a novel therapy for treating insomnia. It comprises a randomized controlled trial with two groups. Prior to Simple randomization, the participants are included/excluded based on research diagnostic criteria (RDC) for insomnia (Edinger et al., 2004) by the American Academy of Sleep Medicine (AASM). Participants (belonging to Hindu, Muslim and Christian faiths) were assigned to either the therapy group (Hare Krishna Mantra Based Cognitive Therapy: HMBCT) or non-therapy group (control with relaxing music) (other conventional aspects of CBT: Stimulus Control, Sleep Restriction, Sleep Hygiene etc. being common to both the groups) for a 6 weeks treatment procedure (6-sessions were conducted in 6 weeks, each on an average of 45-minute duration in the evening and in addition, the participants who underwent sleep quality behavioral measures, sleep logs and Polysomnography recording were asked to practice therapy in the evening of the day of sleep recording). For a week, before and after the 6 weeks duration, no treatment is provided. HMBCT produced significant improvements in sleep quality measures, like ESS (Epworth Sleepiness Scale) (a reduction of 61% post treatment) and ISI (Insomnia Severity Index) (a reduction of 80% post treatment) scores. The participants abstained from taking any sleep-inducing medication during this study. We conclude that the addition of mantra chanting to CBT may add to the improvement of sleep quality.\u003c/p\u003e","manuscriptTitle":"A Meditation Based Cognitive Therapy (HMBCT) for Primary Insomnia: A treatment feasibility pilot study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-12 13:40:46","doi":"10.21203/rs.3.rs-2453260/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-02-07T17:39:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-01-27T06:56:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9954286a-5417-49c5-a03e-eec419799476","date":"2023-01-17T08:09:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-01-16T15:23:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-01-10T09:37:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-01-10T09:37:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Psychophysiology and Biofeedback","date":"2023-01-07T11:41:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0766b09e-eb03-4fb5-9ebd-3ff9954387eb","owner":[],"postedDate":"January 12th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:41:18+00:00","versionOfRecord":{"articleIdentity":"rs-2453260","link":"https://doi.org/10.1007/s10484-023-09586-2","journal":{"identity":"applied-psychophysiology-and-biofeedback","isVorOnly":false,"title":"Applied Psychophysiology and Biofeedback"},"publishedOn":"2023-04-27 20:35:10","publishedOnDateReadable":"April 27th, 2023"},"versionCreatedAt":"2023-01-12 13:40:46","video":"","vorDoi":"10.1007/s10484-023-09586-2","vorDoiUrl":"https://doi.org/10.1007/s10484-023-09586-2","workflowStages":[]},"version":"v1","identity":"rs-2453260","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2453260","identity":"rs-2453260","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}