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A Randomized Controlled Trial of Psychological Outcomes of A Randomized Controlled Trial of Psychological Outcomes of

Mobile Guided Resonant Frequency Breathing in Young Adults Mobile Guided Resonant Frequency Breathing in Young Adults

with Elevated Stress During the COVID-19 Pandemic with Elevated Stress During the COVID-19 Pandemic

Al Amira Safa Shehab The Graduate Center, City University of New York

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A RANDOMIZED CONTROLLED TRIAL OF PSYCHOLOGICAL OUTCOMES OF

MOBILE GUIDED RESONANT FREQUENCY BREATHING IN YOUNG ADULTS WITH

ELEVATED STRESS DURING THE COVID-19 PANDEMIC

by

AL AMIRA SAFA SHEHAB

A dissertation submitted to the Graduate Faculty in Psychology in partial fulfillment of the

requirements for the degree of Doctor of Philosophy, The City University of New York

2021

ii

Ó 2021

AL AMIRA SAFA SHEHAB

All Rights Reserved

iii

A Randomized Controlled Trial of Psychological Outcomes of Mobile Guided Resonant

Frequency Breathing in Young Adults with Elevated Stress During the COVID-19 Pandemic

by

Al Amira Safa Shehab

This manuscript has been read and accepted for the

Graduate Faculty in Psychology to satisfy the dissertation requirement for the degree of Doctor of Philosophy.

Joel R. Sneed, Ph.D.

__________________ ______________________________ Date Chair of Examining Committee

Richard Bodnar, Ph.D.

__________________ ______________________________

Date Executive Officer

Desiree Byrd, Ph.D.

Justin Storbeck, Ph.D.

Yvette Caro, Ph.D.

Valentina Nikulina, Ph.D.

Supervisory Committee

THE CITY UNIVERSITY OF NEW YORK

iv

ABSTRACT

A Randomized Controlled Trial of Psychological Outcomes of Mobile Guided Resonant Frequency Breathing in Young Adults with Elevated Stress During the COVID-19 Pandemic

by

Al Amira Safa Shehab

Advisor: Joel R. Sneed, Ph.D.

Deep breathing practices have shown promise in reducing stress, anxiety, and depression in

different populations, including young adults. Specifically, resonant frequency breathing can

exert an impact on stress response systems through the vagus nerve and the hypothalamo-

pituitary-adrenal (HPA) axis. This may induce reductions in stress and improvement in emotion

regulation. Young adults, including college students, tend to be at a higher risk for psychological

distress, as they face several psychosocial challenges. The COVID-19 pandemic has imposed

new and unique stressors that resulted in higher levels of stress and emotional symptoms and it

has been shown that this may have placed young adults at a particular disadvantage. The current

study is a randomized controlled trial that aimed to investigate the effects of a mobile application

guided resonant frequency breathing training on stress, anxiety, and depression in young adults

with elevated stress. Eighty participants were randomized to either a breathing group or a waitlist

control group (40 participants in each group). Breathing group participants were instructed to

complete two 10-minute breathing sessions per day for five days of the week for a period of 4

weeks. Self-report outcome measures were administered at baseline and at post-training, as well

as weekly through online questionnaires. The results showed that the breathing intervention did

not result in a higher decrease in stress, anxiety, or depression measured at post-training.

v

However, weekly data showed a decline in stress at weeks 3 and 4 and a lower perceived

psychological impact of the COVID-19 pandemic in the breathing group relative to the control

group. All participants also showed a decrease in psychological distress over time. The current

findings are in line with previous literature during the COVID-19 pandemic showing reductions

in psychological distress in young adults in the United States. This breathing paradigm could be

an accessible, effective, and feasible intervention for young adults experiencing increased stress.

vi

ACKNOWLEDGEMENTS

This is dedicated to Beirut, and to my brother, mother, father, friends, and family. All journeys

begin with you and unmistakably lead to you. Your love, unending support, strength, humor, and

relentless affirmation made this possible. Thank you for believing in me through every challenge

and every success, and for standing beside me across the distances and time zones. You inspire

me and I love you.

I am grateful to my advisor, Dr. Joel Sneed, and dissertation committee members, Dr. Desiree

Byrd, Dr. Justin Storbeck, Dr. Yvette Caro, and Dr. Valentina Nikulina, for their guidance,

wisdom, encouragement, and mentorship. Thank you for your insight that helped turn every

curveball into an opportunity to be creative and deeply thoughtful, and for the support that

allowed me to gracefully navigate the unpredictable to accomplish this dissertation.

vii

CONTENTS

CHAPTER ONE ............................................................................................................................. 1

Introduction ................................................................................................................................. 1

Breathing ................................................................................................................................. 1

Resonant Frequency Breathing and Heart Rate Variability. ............................................... 4

Stress ....................................................................................................................................... 6

Young Adult Mental Health in the COVID-19 Pandemic ...................................................... 7

Breathing and Stress ............................................................................................................. 16

Biofeedback Breathing/HRV Training. ............................................................................ 22

Breathing in Anxiety and Depression ................................................................................... 23

Limitations of the Breathing Studies .................................................................................... 27

The Use of Mobile Devices .................................................................................................. 29

Significance of the Current Study ............................................................................................. 31

The Current Study ..................................................................................................................... 32

Aims and Hypotheses ........................................................................................................... 33

Aim 1. ............................................................................................................................... 34

Aim 2. ............................................................................................................................... 34

Exploratory Aim 3. ........................................................................................................... 34

Exploratory Aim 4. ........................................................................................................... 34

CHAPTER TWO .......................................................................................................................... 36

Methods..................................................................................................................................... 36

Participants ............................................................................................................................ 36

Inclusion criteria. .............................................................................................................. 36

Exclusion criteria. ............................................................................................................. 36

Measures ............................................................................................................................... 37

Demographic and Screening Measures. ............................................................................ 37

COVID-19 Perceived Impact. ........................................................................................... 37

Self-Report Measures. ....................................................................................................... 37

Power Analysis ..................................................................................................................... 39

Procedures ............................................................................................................................. 39

Blinding Procedure. .......................................................................................................... 40

Mobile application. ........................................................................................................... 41

Weekly Self Report and Compliance Monitoring. ........................................................... 41

Statistical Analyses ............................................................................................................... 42

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CHAPTER THREE ...................................................................................................................... 44

Results ....................................................................................................................................... 44

Demographics ....................................................................................................................... 44

Baseline Outcome Variable Characteristics .......................................................................... 45

Correlations. ...................................................................................................................... 45

Baseline Group Differences. ............................................................................................. 46

Perceived Stress Scale (PSS) ................................................................................................ 46

Sex Differences in PSS. .................................................................................................... 46

State Trait Anxiety Inventory – State Anxiety ..................................................................... 47

Beck Depression Inventory (BDI) ........................................................................................ 47

Sex Differences in BDI. .................................................................................................... 47

Beck Anxiety Inventory (BAI) ............................................................................................. 48

Perception of the COVID-19 Pandemic’s Impact on Psychological Wellbeing .................. 48

Weekly Self Report ............................................................................................................... 48

Weekly Changes in Self-Reported Breathing Training Experience. ................................ 48

Weekly Stress. ................................................................................................................... 49

CHAPTER FOUR ......................................................................................................................... 50

Discussion ................................................................................................................................. 50

Significance and Future Directions ....................................................................................... 62

Limitations ............................................................................................................................ 64

Conclusion ................................................................................................................................ 66

REFERENCES ............................................................................................................................. 78

ix

TABLES

Table 1 .......................................................................................................................................... 68

Table 2 .......................................................................................................................................... 70

Table 3 .......................................................................................................................................... 71

Table 4 .......................................................................................................................................... 72

Table 5 .......................................................................................................................................... 73

Table 6 .......................................................................................................................................... 73

Table 7 .......................................................................................................................................... 74

Table 8 .......................................................................................................................................... 74

Table 9 .......................................................................................................................................... 75

Table 10 ........................................................................................................................................ 76

Table 11 ........................................................................................................................................ 77

Table 12 ........................................................................................................................................ 77

1

CHAPTER ONE

Introduction

Breathing

Breathing is an automatic mechanism recognized as a crucial and fundamental function

of the human body (Paulus, 2013). It is regulated by brainstem nuclei, specifically through

bulbospinal pathways from the medulla (Butler, 2007). Even when voluntarily controlled to

produce certain complex and often necessary actions such as speaking, swallowing, or coughing

through corticospinal projections (Butler, 2007), often little conscious attention or voluntary

thought is given to these brief manipulations of breath. Intuitively, breathing is a reflex that most

humans neglect unless when disrupted in some way (Zaccaro et al., 2018). However, breathing

has long been given special status in Eastern disciplines that went beyond a biologically vital

function (Chan et al., 2002; Telles & Singh, 2013).

Hindu and Buddhist philosophies consider the breath as the symbol of life and

incorporate breathing into different meditation practices (Tomasino et al., 2014). In addition to

meditation, other forms of training use the breath as a mechanism to regulate the functions of the

body and mind. Originating from Taoist philosophies and the principles of traditional Chinese

medicine, “Tai-jiquan” is a practice believed to prevent and treat disease when practiced

regularly. It requires deep, calm breathing coordinated with a focused mind, while completing a

series of continuous linked movements (Chan et al., 2002). The breath is a major element of

Chinese “body-mind-spirit” practices including “Qigong,” a 2000-3000 year old practice that

combines regulation of the breath/respiration, body motion, voice, and mind (Chan et al., 2002;

Tsang & Fung, 2008). In fact, traditional Chinese medicine considers the control of mood and

emotions to be the key to health and healing, to the reversal of the imbalance and disharmony in

2

a person’s biological systems controlled by the five elements of wood, fire, earth, metal, and

water. This mental regulation is believed to be attained by cultivating each of these practices,

including breathing (Chan et al., 2002).

In Japanese culture, healing practices focused on strengthening and fostering the belly,

considered to be central in promoting mental and physical health and vitality (Wu, 2016).

Traditionally practiced and more recently modernized and invented (in the early to mid-20th

century) Japanese “belly-cultivating” techniques utilize abdominal and deep breathing and the

harmonization of the breath with the mind to treat physical and emotional illnesses and even

existential turmoil. Practitioners of these techniques follow a predetermined breathing rate,

frequency and duration, as well as inhalation and exhalation lengths (Wu, 2016).

Yoga is likely today’s most popularized Eastern tradition in Western culture. According

to the National Health Interview Survey in the United States (Clarke & Stussman, 2018), yoga

was the most commonly used complementary health practice among adults aged 18 and over in

2012 and 2017. Also, there was an increase in the use of yoga from 9.5% of U.S. adults in 2012

to 14.3% in 2017, and women and individuals aged 18-44 used yoga the most (Clarke &

Stussman, 2018). Although most recognized and attractive for its active poses and movements,

yoga is a philosophy that incorporates a constellation of techniques forming a fully integrated

mental, physical, and spiritual practice (Chan et al., 2002). In fact, voluntary control of breathing

has a prime importance in the ancient science of yoga and believed to affect overall functioning

through its influence on mental state (Telles & Singh, 2013). Yoga means “union,” the

juxtaposition and equilibrium of opposites, yin and yang, mind and body, high and low energies,

etc. Originating in India, its principles and components were systematically compiled and

described by the sage Patanjali in his Yoga Sutras text (“sutra” roughly meaning “thread”) where

3

he denotes the 8 limbs of yoga (Telles & Singh, 2013). These are 1) “yama,” a moral code of

conduct, 2) “niyama,” self-purification or study, 3) “asana,” physical posture, 4) “pranayama,”

voluntary breath regulation, 5) “pratyahara,” sense withdrawal, 6) “dharana,” concentration, 7)

“dhyana,” meditation, and 8) “samadhi,” absorption in the self. As such, physical practice,

accompanied by and deepened through breathing regulation, promotes progress toward control of

mental and sensory factors, concentration, and meditation, to ultimately cultivate complete self-

effacement (Telles & Singh, 2013; Tomasino et al., 2014).

Those who study and practice each of these ancient philosophies learn that the breath is

affected by many physical and psychological factors, and that control or manipulation of the

breath can reciprocally influence similar physiological and psychological functions. Breathing

can be a medium through which health and illness are generated (Lalande et al., 2012). A

growing body of evidence has also more recently suggested that breathing at specific rates such

as at five breaths per minute can have positive effects on the nervous system, anxiety, and

depression (Scott et al., 2019). It is noteworthy that, as exemplified by the components of yoga,

breathing is often entangled with other practices, particularly with meditation, concentration, and

physical exercise. For instance, many meditation techniques are breathing focused or guided

(Zaccaro et al., 2018), and voluntary control of breath is invariably a practice that necessitates a

good deal of concentration or focused attention (Eisenbeck et al., 2018). When practicing yoga

asana, the movements are frequently guided with inhalation and exhalation. Further, different

combinations of these practices (breathing, focused attention, meditation, and physical training)

make up the experience of mindfulness (Tang, 2017). Mindfulness practices have been asserted

in recent years as evidence-based methods in psychotherapeutic protocols such as cognitive

4

behavioral therapy in the treatment of many psychological conditions including stress,

depression, and anxiety (Stein & Witkiewitz, 2020).

Resonant Frequency Breathing and Heart Rate Variability. Resonant frequency

breathing occurs when the rate of breathing corresponds to a person’s highest respiratory sinus

arrhythmia (RSA) (Lehrer, Vaschillo, & Vaschillo, 2000). RSA is the natural variability in heart

rate whereby heart rate increases during inhalation and decreases during exhalation. This rhythm

is possible due to the baroreflexes, which are homeostatic mechanisms that modulate blood

pressure and are mediated by sensory stretch receptors in the aorta and carotid arteries (Lehrer &

Vaschillo, 2004). During inhalation, heart rate increases, and blood pressure follows after about

4-5 seconds. During exhalation, heart rate decreases, and blood pressure falls 4-5 seconds later.

These fluctuations in blood pressure are detected by baroreceptors which fire to activate heart

rate and vascular tone changes (Shaffer & Ginsberg, 2017).

Accelerations and decelerations of heart rate are mediated by the vagus nerve, the tenth

cranial nerve and main component of the parasympathetic nervous system (Breit et al., 2018). It

extends from the medulla in the brainstem and provides the main parasympathetic supply to the

heart at the level of the thorax, thus regulating heart rate. However, the vagus nerve’s most

important function is afferent, bringing sensory information from inner organs like the heart to

the brain. These vagal afferent pathways are also involved in the regulation of the hypothalamo-

pituitary-adrenal (HPA) axis and thus in the organism’s response to stressors (Breit et al., 2018).

Variability in the heart’s rhythms is an indicator of health. In order to adjust to changing

or stressful environments and be able to adapt flexibly, the heart’s beat-to-beat fluctuations are

not linear, simple, nor constant (Shaffer & Ginsberg, 2017). The fluctuation in the time intervals

between adjacent heartbeats (called R-R intervals based on electrocardiogram signals) is referred

5

to as heart rate variability (HRV). HRV is commonly measured using time domain and

frequency domain indices (Shaffer & Ginsberg, 2017). Time domain methods determine the

heart rate at any point in time and quantify the amount of variability in measurements of

interbeat intervals (IBI) or the intervals between successive normal complexes on

electrocardiogram (ECG), obtaining normal-to-normal (N-N) intervals.

Frequency domain measures estimate the distribution of power, or variance within a

frequency band, as a function of frequency. Short-term recordings of HRV revealed 3 main

spectral components: very low frequency (VLF), low frequency (LF), and high frequency (HF)

components; and long-term recordings revealed an additional ultra-low frequency (ULF)

component (Task Force of the European Society of Cardiology and the North American Society

of Pacing and Electrophysiology, 1996). The LF and HF bands can be estimated with recordings

of a minimum of 1-2 minutes. At rest, the LF band reflects baroreflex activity and is thought to

be primarily related to parasympathetic activity. Heart rhythms can produce LF oscillations

during periods of slow respiration (below 8.5 breaths per minute) through respiratory related

efferent vagally mediated influences (Lehrer & Vaschillo, 2004; Shaffer & Ginsberg, 2017). The

HF band reflects parasympathetic activity and corresponds to heart rate changes related to

respiration cycles, or respiratory sinus arrhythmia (RSA) (Shaffer & Ginsberg, 2017). These

different measures of HRV are summarized in Table 1.

Resonant frequency breathing is characterized by a respiratory rate of around 6 breaths

per minute, and anywhere between 4-6.5 breaths per minute have been cited (Lehrer et al., 2013;

Tabachnick, 2015). At this breathing rate, RSA is maximized and a greater stimulation of the

baroreflex mechanism is obtained due to a greater fluctuation of blood pressure in each

respiratory phase (Jiménez Morgan & Molina Mora, 2017). At this frequency only, heart rate and

6

blood pressure oscillate 180° out of phase with each other (Lehrer & Vaschillo, 2004) and heart

rate goes up and down in phase with respiration (Lehrer et al., 2013). Respiration at resonant

frequency is expected to produce greater LF power due to a lower peak frequency than resting

baseline breathing (Shaffer & Ginsberg, 2017). Breathing at resonant frequency has been used as

a method for HRV biofeedback to maximize HRV (Lehrer et al., 2013; Tabachnick, 2015).

Stress

Stress is a physiological and psychological response to environmental or physical

conditions, mediated by the autonomic nervous system and HPA axis (Bhimani et al., 2011; Zhu

et al., 2017). Human stress systems are driven by highly interconnected central and peripheral

components that together constitute a major regulator of the organism’s reactions to acute or

chronic challenges (Agorastos et al., 2019). The hypothalamus and brainstem contain many of

the central components and are driven by inputs from the prefrontal cortex and amygdala, while

direct feedback regulation mediated by the baroreflex is driven by brainstem circuits via the

nucleus tractus solitarius. These responses are involved in neural pathways that regulate adaptive

functions to increase arousal, vigilance, and attention and inhibit situationally irrelevant

functions such as eating, growth, and reproduction (Agorastos et al., 2019). The HPA axis and

the sympathetic, sympatho-adrenomedullary, and parasympathetic systems of the autonomic

nervous system are the peripheral components responsible for stress related effector and

signaling molecules including hormones such as epinephrine (Agorastos et al., 2019). For

example, the sympathetic nervous system responds to stress through increased activity leading to

the secretion of cortisol, as well as increases in respiratory rate, heart rate, and systolic and

diastolic blood pressure (Hopper et al., 2019).

7

Adults in the Unites States have reported increasingly elevated levels of stress that they

consider to be higher than normal. Specifically, the young adult age group in the Stress in

America survey reported experiencing the most stress and the least relief, with lower ability to

cope with stressors (American Psychological Association, 2013). Trends in the 2020 Stress in

America Survey, which found a general profound compounding of stressors for Americans due

to the COVID-19 pandemic which was alarming of a national mental health crisis, again showed

that young adults were facing unprecedented uncertainty during this time and experiencing

elevated levels of stress as well as symptoms of depression (American Psychological

Association, 2020). Stressful normative transitions are typically experienced by this population,

including changes in living situations, navigating educational and professional development and

social and romantic relationships (Shanahan et al., 2020). High levels of persistent stress have

many negative consequences for physical and emotional health as well as psychosocial

functioning, including being a risk factor for cardiovascular disease, major depression, and poor

academic performance (Hunt et al., 2018; Perciavalle et al., 2017).

The World Health Organization (WHO) World Mental Health International College

Student Initiative found that 93.7% of first year college student from nine different countries

reported some perceived stress in at least one of six life areas: financial situation, health, love

life, relationships with family, relationships at work/school, and problems experiences by loved

ones (Karyotaki et al., 2020). In fact, a large proportion of students (73.8%) reported stress in at

least three life areas. Additionally, the extent of stress in these areas was found to predict

increased risk for mental disorders including generalized anxiety disorder, major depressive

disorder, panic disorder, and substance use disorders (Karyotaki et al., 2020).

Young Adult Mental Health in the COVID-19 Pandemic

8

The 2019 novel coronavirus (COVID-19) caused by the novel severe acute respiratory

syndrome coronavirus-2 (SARS-CoV-2) was first detected in the U.S. on January 21st, 2020. A

public health emergency was declared by the WHO on January 31st, with confirmation of a fast

spread of human-to-human transmission (AJMC Staff, 2021). The outbreak appeared to be

contained in the U.S. through February, followed by an accelerated spread by mid-March

(Schuchat, 2020). On March 11th, 2020, COVID-19 was declared as a pandemic by the WHO

and by March 13th it was recognized that Europe had become the epicenter of the pandemic with

more reported cases and deaths worldwide apart from China (https://www.who.int/news/item/29-

06-2020-covidtimeline, 2020), while it was declared as a national emergency in the U.S. (AJMC

Staff, 2021). The outbreak in New York City was particularly severe, making it an early

epicenter of the pandemic in the U.S. with the highest rate per capita by April 2020 as reported

by the Centers for Disease Control and Prevention (CDC, 2020; Hawes et al., 2021). With social

distancing and stay-at-home regulations put in place to limit the infections starting to roll out in

March, the WHO issued guidance on mental health and psychosocial considerations during the

COVID-19 outbreak (https://www.who.int/news/item/29-06-2020-covidtimeline, 2020). The toll

continued to rise in the U.S., surpassing 100,000 deaths by May 28th and two million confirmed

cases by June 10th. By July, record daily numbers of new cases were being recorded with as high

as 75,600 news cases in one day, and surpassing three million infections by July 7th. In august

2020, COVID-19 became the third leading cause of death in the U.S. behind heart disease and

cancer. After a period of relative control of the spread, cases began to spike again by mid-

October internationally, while the U.S. remained the hardest hit country in the world (AJMC

Staff, 2021).

9

The COVID-19 pandemic had numerous negative impacts on the general population, not

only due to its effect on safety and health but also due to social distancing and stay-at-home

measures, causing direct and indirect threats to the resources that support health (van der Velden

et al., 2020). These include the ability to maintain social contacts and support due to constraints

on physical movement and quarantine, and housing, work, and income securities that were

strained for many. In addition to these stressors due to sudden and radical lifestyle changes,

people were also scared and worried for their health and that of loved ones (Shanahan et al.,

2020; Son et al., 2020). Other stressful characteristics of the COVID-19 pandemic and associated

lockdown can include uncertainty, ambiguity, loss of control, social isolation (Shanahan et al.,

2020) as well as boredom and frustration (Holingue et al., 2020).

A systematic review of the psychosocial consequences of COVID-19 (Stavridou et al.,

2020) found that excess worry, irritability, home confinement, and fear of infection and

transmission were associated with mild to severe anxiety symptoms. In fact, social isolation can

be a precursor to psychological distress including depression and anxiety (Twenge & Joiner,

2020a). The review authors noted that isolation and social distancing can be risk factors for

mental health difficulties and can lead to distress, frustration, irritability, hopelessness, and

decreased interest or pleasure in activities, as well as increased mobile phone use and negative

emotions about COVID-19 (Stavridou et al., 2020). Some of these challenges are particularly

relevant for young adults’ mental function, such as restricted mobility and reduced physical

activity while screen time and social media use increased, loss of everyday peer-to-peer contact,

and uncertainty in academic trajectories. This review also found that telehealth and the use of

technology were paramount in managing emotional symptoms in this population (Stavridou et

al., 2020).

10

In fact, in April 2020 many full time college students in the U.S. reported anxiety about

COVID-19’s health implications on their families and community and on society’s economic

situation, and its impact on their educational experience (A. K. Cohen et al., 2020). Students

reported increased isolation from social and academic communities, restricted social behavior,

and most of those who had jobs were no longer employed or earned less. Although the physical

health impact of COVID‐19 on emerging adults could be less severe compared to later

adulthood, emerging adults likely experienced disruptions in educational or occupational

opportunities as well as limitations to their quest for independence, impacting many psychosocial

outcomes (Kujawa et al., 2020).

Several studies in the past year have investigated the mental health and wellbeing of adult

populations during the COVID-19 pandemic. Longitudinal studies are of particularly importance

as they can account for any increases in psychological distress during this time, especially in

young adults who may already be vulnerable before the pandemic (Twenge & Joiner, 2020a). In

the U.S., young adult full-time college students reported moderate levels of perceived stress and

anxiety in April and June 2020, with women reporting less wellbeing and a higher increase in

perceived stress between the two months compared to men (Hoyt et al., 2021). Of note, overall

levels of stress and anxiety decreased during this delay for most participants, which the authors

suggested might be related to many students not taking classes and to the pandemic having

become an expected reality (Hoyt et al., 2021). Further, White students had higher perceived

stress and generalized anxiety in April, but scores were higher in Black and multiracial students

in July. This was considered to be consistent with structural racism, health inequities, and

disproportional economic impact of the pandemic on these individuals (Hoyt et al., 2021).

11

A longitudinal study in emerging adults aged 18-25 found high rates of anxiety and

depression during the first study period in May 2020 which decreased one month later (June)

(Kujawa et al., 2020). Higher levels of stress severity in this study were endorsed by younger

participants, women, and Black individuals. Health effects of the COVID-19 pandemic were

rarely reported in this sample while internalizing symptoms were found to be more strongly

associated with experiences of psychosocial life disruptions and financial and interpersonal

difficulty rather than with health impact (Kujawa et al., 2020). In fact, the adult prevalence of

serious psychological distress measured by the Kessler 6 scale was similar in April (13.6%) and

July 2020 (13%) and consistently higher than rates reported in 2018 (McGinty et al., 2020).

Approximately a quarter of young adults reported serious distress in April and July 2020. Most

adults with serious distress reported that disruptions to education, employment, and finances due

to the pandemic negatively affected their mental health, all stressors considered to be particularly

relevant to young adults (McGinty et al., 2020).

A March 2020 survey of a nationally representative sample of adults in the U.S. with no

prior history of mental health condition found that more than one in four adults experienced

psychological distress for at least three days in the past week (Holingue et al., 2020). Anxiety

and depression symptoms were the most prevalent, reported by 39% and 19% of the sample

respectively. These rates were found to be elevated relative to data from January-June 2019

estimates from the National Health Interview Survey (NHIS). Additionally, psychological

distress was related to reported major life changes due to the pandemic and was higher in

participants who perceived the virus as a threat to their personal health (Holingue et al., 2020).

A nationally representative U.S. adult sample surveyed in late April 2020 showed that

more than one in four adults fit criteria for serious mental distress, eight times more than a

12

demographically similar sample from the NHIS most recent available data at the time (Twenge

& Joiner, 2020a). Also, over two thirds of the April 2020 sample showed moderate or serious

mental distress, with higher symptoms of sadness, hopelessness, and worthlessness. These

differences were also found to be larger in young adults (Twenge & Joiner, 2020a). Similarly, a

comparison between data from a nationally representative probability samples administered by

the U.S. Census Bureau in 2019 and adults sampled in April and May 2020 found that the

prevalence of anxiety and depression was three times higher during the pandemic (Twenge &

Joiner, 2020b). Over the course of April-May, symptoms remained high but there was indication

that anxiety decreased, possibly suggesting a mechanism of adaptation, and depressive

symptoms increased, indicating a growing “resignation” prompting authors to posit that this

might be “a concerning combination” of coping states (Twenge & Joiner, 2020b).

The New York metropolitan area specifically witnessed a high concentration of cases

early in the pandemic. Adolescents and young adults aged 12-22 from Long Island who were

previously sampled between December 2014 and July 2019 and reassessed between March 27th

and May 15th, 2020 reported increased symptoms of generalized and social anxiety with females

experiencing higher rates of depression and panic/somatic symptoms (Hawes et al., 2021). In

fact, 60% of females in the 2020 sample met clinical cutoff for at least one disorder. Increases in

psychiatric symptoms were also found to be related to different pandemic experiences. For

instance, depressive symptoms were uniquely associated with several school concerns including

passing classes, juggling schoolwork with other responsibilities, and the quality of online classes.

Additionally, both depressive and anxiety symptoms were associated with concern about

contracting COVID-19, experiencing more life changes, and meeting basic needs (Hawes et al.,

2021). On the other hand, concerns about home confinement including experiencing cabin fever

13

and limited social interaction were uniquely associated with increases in generalized anxiety but

less social anxiety symptoms. The authors concluded that these findings could suggest that

shelter-in-place and social distancing measures contributed to increased diffuse worries while

some youths found a relief from social pressures during the quarantine (Hawes et al., 2021).

As the first country in the world to detect cases of COVID-19, China also saw rises in the

prevalence of anxiety and depressive symptoms in the early months, with evidence of females

being more affected (Jiang et al., 2020). While China witnessed a rapid spike in early cases, there

was later a relative remission of the outbreak at least for a period of time. A longitudinal study

surveyed participants during a phase of rapid increase of newly diagnosed cases in China

(January 31-February 2) after which there was a sharp increase in cases and then during the start

of a rapid decline in cases (February 28-March 1) (C. Wang et al., 2020). Similar levels of stress,

anxiety, and depression were found during both phases while the psychological impact of

COVID-19, measured through post-traumatic stress symptoms, tended to decline (C. Wang et al.,

2020). In fact, during a time when the pandemic was already under relative control in China

(February 14-March 29), there was still a high prevalence of moderate to high levels of perceived

stress (Ren et al., 2020). Additionally, the psychological impact of prolonged lockdown was

higher among participants aged 12-21, who were mainly students likely impacted by prolonged

school closure, online education and uncertainty about examinations and matriculation status (C.

Wang et al., 2020).

A 2-wave longitudinal web-based study in Chinese college students found a decrease in

the prevalence of probable acute stress symptoms and an increase in rates of anxiety and

depression from the initial virus outbreak phase during February 3-10 2020 to a control phase

between March 24-April 3 (Li et al., 2021). Mental health symptoms were found to be associated

14

with the number of infected cases in the individual’s community and with social media exposure.

Female students, seniors, and graduates were also found to have increased mental health

problems (Li et al., 2021). Specifically, risk of depression was associated with worry about

family becoming infected and negative health behaviors such as smoking, alcohol consumption,

and less exercise time increased the risk of persistent and delayed onset of symptoms. On the

other hand, risk of anxiety was related to worry about oneself becoming infected. Social support

and positive family dynamics were found to have a protective role in predicting risk of poor

response to the outbreak (Li et al., 2021).

Germany was the first European country to detect cases of COVID-19

(https://www.who.int/news/item/29-06-2020-covidtimeline, 2020). A longitudinal study with

data from December 2019, March, April, and May 2020 found decreased life satisfaction,

positive affect, as well as negative affect between March and May (i.e., during the pandemic) but

not between December 2019 and March 2020 (Zacher & Rudolph, 2021). Italy faced high levels

of community transmission and was one of the most affected countries by the COVID-19

pandemic worldwide during March 2020, specifically northern Italy, the first epicenter of the

outbreak in Europe (https://www.who.int/news/item/29-06-2020-covidtimeline, 2020; Shanahan

et al., 2020). A study in Italy found high rates of moderate psychological distress including

depression, general anxiety, physical symptoms, and stress with females showing higher levels

of distress (Bonati et al., 2021). Psychological distress was also related to unemployment, living

situation restrictions, having new health problems, and house confinement during the quarantine,

and a higher prevalence of distress was seen the closer the participant was from Lombardy, a

zone of high infection (Bonati et al., 2021).

15

A prospective longitudinal cohort study in Zurich, Switzerland, a city close to northern

Italy, found increased perceived stress and anger and decreased internalizing symptoms during

the pandemic (April 2020) in 22-year-olds (Shanahan et al., 2020). Women had a higher risk of

perceived stress, internalizing, and anger. Also, past emotional distress was the largest risk factor

for pandemic stress symptoms, in addition to previous high hopelessness and lifestyle and

economic disruptions. In fact, when these factors were considered, the gender difference was

reduced (Shanahan et al., 2020). Responses to stress showed that participants with more

pandemic/lockdown distress were more likely to seek social support, engage in distractions, and

seek professional help, while less distress was associated with keeping a daily routine, positive

reappraisal/reframing, physical activity, and keeping in contact with family and friends

(Shanahan et al., 2020).

Follow-up web survey data from April 2020 in the United Kingdom national longitudinal

cohort study (UK Household Longitudinal Study UKHLS) found an increase in mental distress

in people aged 16 years and older compared with the previous year (Pierce et al., 2020). Authors

determined that this increase was not simply a continuation of previous upward trends. Also,

being young, a woman, and living with children was particularly influential on the extent to

which mental distress increased during the pandemic (Pierce et al., 2020). Studies in college

students from other European countries (e.g., France, Spain) during critical pandemic and

lockdown times also found high rates of anxiety, depression, distress, and stress, with large

proportions of the samples experience some psychological impacts of the pandemic (Essadek &

Rabeyron, 2020; Odriozola-González et al., 2020). Some factors associated with higher risk of

distress were female gender, living alone, having financial difficulties, and increases in social

distancing and isolation measures (Debowska et al., 2020; Essadek & Rabeyron, 2020).

16

In contrast with the aforementioned studies, a Dutch prospective population based study

using the Longitudinal Internet Studies for the Social Sciences (LISS) panel between March 2-31

2020 when cases rapidly increased in the Netherlands found that levels of anxiety and depression

and reported lack of emotional support did not change during the pandemic period (November

2019 to March 2020) as compared to prior prevalence (November 2018 to March 2019) (van der

Velden et al., 2020). It was suggested that these results indicated that the Dutch population was

able to cope and adjust to pandemic events possibly due to the government’s reaction and to

existing social welfare and healthcare systems. Also in contrast with other evidence, this study

found that while younger adults (18-34) were at higher risk of anxiety and depression in the year

before the pandemic, the older age group (35-49) was more at risk during the pandemic

suggesting a higher psychological load for this age group (van der Velden et al., 2020).

New Zealand is another country that had a remarkably effective response to the global

pandemic. Data from this country showed higher levels of distress between April 15-18 in

comparison to baseline rates from prior surveys, with younger adults under the age of 44 being

more impacted (Every-Palmer et al., 2020). This suggested that despite low infection and

mortality rates, increased psychological distress was detected due to factors such as strict

lockdown procedures. Additionally, the gender gap which previously put women at higher risk

of anxiety narrowed in the study period with similar proportions of males and females

experiencing moderate to severe anxiety, possibly due to both gender having responded similarly

to anxiety about the economic situation (Every-Palmer et al., 2020).

Breathing and Stress

Western culture has adopted the belief that breathing control has beneficial effects on

stress reduction, relaxation, and wellness (Zaccaro et al., 2018). Respiratory function has direct

17

impacts on the HPA axis and cardiovascular systems, which mediate its effects on health and

stress (Abelson et al., 2010). In fact, hypothalamic and hippocampal influences shape HPA axis

activity simultaneously with respiratory patterns, and it has been suggested that the close

functional integration and connection of breathing regulation and HPA function are critical in the

coordinated homeostatic defensive response (Abelson et al., 2010).

Specifically, mindful deep breathing has received attention as a potential mechanism to

improve parasympathetic activity, possibly leading to the correction of sympathovagal imbalance

characteristic of psychological conditions such as depression, anxiety, and stress (Cheng et al.,

2019). The view that breathing could enhance psychological wellbeing has received empirical

support in recent years, with studies focusing on different breathing paradigms such as deep

diaphragmatic breathing (e.g., Ma et al., 2017) and breathing practice incorporated within yoga

or mindfulness interventions (e.g., Yadav, Magan, Mehta, Sharma, & Mahapatra, 2012).

Following this line of support, breathing exercises have been incorporated in different clinical

therapies such as Cognitive Behavioral Therapy (CBT) and Dialectical Behavior Therapy (DBT)

(O’Donohue & Fisher, 2009) to treat psychological disorders such as post-traumatic stress

disorder (PTSD) (e.g., Leiva-Bianchi, Cornejo, Fresno, Rojas, & Serrano, 2018), anxiety

disorders (e.g., Pompoli et al., 2018), depression (O’Donohue & Fisher, 2009), as well as chronic

pain (Cano-García et al., 2017) and other stress-related conditions (Brown et al., 2013).

A recent systematic review evaluated the evidence on diaphragmatic breathing

interventions’ effectiveness in reducing physiological and psychological stress (Hopper et al.,

2019). Diaphragmatic breathing is achieved by breathing deeply into the lungs while expanding

the abdomen and releasing the diaphragm during the inhalation, followed by a full deep

exhalation. This review identified three studies, only one of which was a randomized controlled

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trial (Ma et al., 2017), that showed a positive relationship between diaphragmatic breathing as a

standalone practice and stress reduction. There was some evidence suggesting that this

intervention could decrease physiological stress based on indirect measurements including blood

pressure, respiratory rate, and salivary cortisol, as well as a self-report stress subscale (Hopper et

al., 2019).

Several experimental studies have shown evidence for the benefit of breathing training on

measures of stress and psychological functioning. A pilot randomized controlled trial (RCT) of a

healthy sample of employees of an information technology (IT) company in China implemented

a breathing intervention in a group assigned to 20 sessions of diaphragmatic breathing guided by

a coach in addition to a breathing monitoring device over an 8-week period every other day of

the weekdays (Ma et al., 2017). Each session was 30 minutes long, with 15 minutes of deep

breathing and 15 minutes of resting breathing with the eyes closed. The results showed reduced

salivary cortisol levels, a physiological indicator of stress, in the intensive training group as

compared to the control group, in addition to a reduction in negative affect (Ma et al., 2017).

Similarly, an “anti-stress protocol” based on deep breathing techniques was implemented in a

young adult sample from a university in Italy for 10 90-minute treatment sessions once per week

(Perciavalle et al., 2017). The experimental group showed improvements in measures of heart

rate and salivary cortisol levels as well as mood and perceived stress, as compared to a control

group.

An investigation of the outcomes of different durations of mindful deep breathing

randomized university students aged 18-30 years who had no prior knowledge of deep breathing

exercises to one of four groups: (1) control group, (2) mindful deep breathing for 5 minutes, (3)

mindful deep breathing for 7 minutes, or (4) mindful deep breathing for 9 minutes at a

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respiratory rate of 6 breaths per minute with 5 seconds of inhalation and 5 seconds of exhalation

(Cheng et al., 2019). The intervention was guided by a video showing smiley faces that prompt

inhalation and exhalation with petals appearing and disappearing around the smiley.

Additionally, a 10-minute Go/NoGo task was administered before and after the in-lab training.

Participants in the breathing groups were also instructed to perform the breathing exercise daily

for the following 7 days using the same video. This study found that, compared to the control

group, all three training durations resulted in increased measures of HRV while participants

performed the breathing but not after the intervention or at follow up (Cheng et al., 2019). Also,

self-reported depression decreased after 7 days for the 7- and 9-minute breathing groups with

higher session length resulting in the greatest decrease. It was suggested that the decline in

depression was related to the shifting toward vagal tone and activation of parasympathetic

nervous system especially at longer breathing duration. The absence of improvement in anxiety

and stress was thought to be likely due to the short duration of training (Cheng et al., 2019).

Breathing interventions have also been studied in non-healthy populations with physical

or psychological diagnoses. Patients with hypertension completed a relaxation and breathing

training program adapted for hypertensive patients based on a stress control training program

during 13 weekly 60-minute sessions in which 30 minutes were spent practicing relaxation and

breathing (Chicayban & Malagris, 2014). This study found a reduction in the rate of stress

symptoms in the experimental group as compared to a control group who had hypertension.

However, there was no reduction in blood pressure measurement after the training period

(Chicayban & Malagris, 2014), suggesting that the response may be specific and independent of

hypertension. In contrast, an investigation of a yogic deep breathing technique on blood pressure

and academic stress in a college student sample from India found that the deep breathing group

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had significantly lower systolic and diastolic blood pressure recordings after 10 minutes of

practice (Joshi et al., 2016).

Breathing incorporated in mind-body practices, such as yoga and mindfulness based

interventions have also been shown to be effective in stress reduction. A yogic breathing focused

practice, Shambhavi Mahamudra kriya, consisting of a series of controlled breathing techniques,

was investigated in a 3-day non-residential retreat for 21 minutes daily (Peterson et al., 2017).

The practice was also accompanied by yoga postures and open monitoring meditation, and

participants engaged in other retreat activities such as lectures on yoga topics and mind calming

techniques and were served vegetarian meals. At 6-week follow-up, participants reported

significantly reduced perceived stress and increased general wellbeing compared to baseline

(Peterson et al., 2017). Similarly, a yoga based outpatient lifestyle intervention program

consisting of yoga postures and breathing exercises as well as didactic lectures on healthy living

was conducted over 10 days for 2 hours daily in participants with chronic inflammatory disease

and excess weight (overweight/obese) (Yadav et al., 2012). Participants showed improvements in

biochemical markers of stress and inflammation such as plasma cortisol and Interleukin-6 levels,

as well as increased b-endorphin levels.

Mindfulness interventions that incorporate breathing in addition to other physical practice

were also studied in samples of students and trainees in various healthcare fields. A mind-body

skills training 11-week program consisting of a combination of breathing exercises, meditation,

biofeedback, guided imagery, and relaxation practiced for 20 minutes, 5 days per week showed

improvements in distress tolerance, stress, and wellbeing, as well as a better ability to adaptively

respond to emotional distress in first and second year medical students (Kraemer et al., 2016). A

mindfulness practice was also investigated in undergraduate and graduate students in

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communication sciences and speech/language pathology for 8 sessions over the duration of one

semester (Beck, Verticchio, Seeman, Milliken, & Schaab, 2017). This intervention consisted of

simple yoga stretches, 5 minutes of breathing, a writing task, and didactic sessions. As compared

to a control group, the mindfulness group showed a greater decrease in self-reported perceived

stress as well as improvement in HRV measures indicating reduced stress, though the control

group also reported a decrease in perceived stress between pretest and posttest. Participants in

the mindfulness group additionally showed increased self-compassion (Beck et al., 2017).

Other mind-body paradigms were studied in long-term practitioners assessed before and

after engaging in the breathing practice. The practice of Nishino breathing, which involves deep

breathing, physical relaxation and stretching exercise, and visualization of internal energy was

investigated in practitioners of 2-3 years (Kimura et al., 2005). After engaging in this combined

practice for 60 minutes in addition to 30 minutes of Taiki practice of “energy transfer”,

practitioners showed an increased activity of natural killer (NK) cells related to immunologic

function, without an increase in the number of these cells. The results indicated that the Nishino

breathing techniques improved immunologic activity, reduced stress, and improved mood after a

single practice session (Kimura et al., 2005). Similarly, a traditional Korean mind-body practice,

Kouksundo, including warm-up, 45 minutes of deep breathing meditation, and cool-down was

investigated in a sample of healthy and unhealthy (this group included different disorders such as

cardiovascular, musculoskeletal, and inflammatory disorders) trained practitioners with a median

training period of 37 months with regular practice of at least twice a week (Im et al., 2015). After

a practice session of Kouksundo, practitioners showed reduced measures of oxidative stress

determined through serum markers, including lowered levels of cortisol, dopamine, and

norepinephrine and increased levels of epinephrine. They also exhibited elevated time domain

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indices of HRV and reduced mean heart rate. These results suggested reduced psychological and

physical stress and increased health parameters in these practitioners (Im et al., 2015).

Biofeedback Breathing/HRV Training. Biofeedback paradigms to induce paced and

deep breathing have been implemented to investigate the relationship between physiological

measures of HRV and stress. Such interventions are often referred to as HRV biofeedback,

though not always reported to induce resonant frequency breathing. Students with high perceived

stress completed a paced breathing with biofeedback intervention as well as two control

interventions, a self-paced walk and quiet study attention control conditions, during three

separate sessions in the laboratory (Meier & Welch, 2016). The biofeedback paradigm consisted

of a respiration pacing screen instructing participants to engage in diaphragmatic breathing at a

rate of 6 breaths per minute. Each intervention was practiced for 10 minutes. The biofeedback

condition was found to reduce state anxiety and improve affective state, while these changes

were not seen in the other two conditions. It was also found that paced breathing biofeedback

induced an increase in a measure of HRV that correlated with a reduction in perceived energy

levels, while an increase in other HRV measures after the walking condition was associated with

increased tension. This signified that the biofeedback method induced higher states of calmness

(Meier & Welch, 2016).

HRV biofeedback was in fact found to induce a modified short-term physiological effect

in vagal modulation following laboratory-induced stress as compared to a control condition

(Prinsloo et al., 2013). In this study, males exposed to work related stress completed a pre-

intervention Stroop task followed by biofeedback breathing or a control condition with no

breathing instructions for 10 minutes. The biofeedback training was implemented using a

handheld mobile HRV biofeedback device that facilitates breathing according to participants’

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RSA, as they were instructed to perform pursed-lips abdominal breathing (Prinsloo et al., 2013).

After the intervention, participants completed a rest period followed by a Stroop task.

Participants in the biofeedback condition demonstrated increased LF power during the

intervention reflecting a heightened parasympathetic activity, with a decrease in this measure

during rest. These changes were not seen in the control condition. In response to induced stress,

the biofeedback group demonstrated a decrease in LF power but no change in HF power while

the control group showed decreased HF measures. These findings suggested that the short

biofeedback intervention resulted in a maintained HF vagal modulation in response to stressors,

and this was accompanied by higher alertness and relaxation states (Prinsloo et al., 2013).

In a study implementing respiratory biofeedback in a virtual reality paradigm, college

students were administered a stress induction task followed by either a mindful breathing guided

meditation condition, a respiratory feedback condition where participants perceived a visual

stimulus that followed their breathing rhythm, or a control feedback placebo condition where the

visual stimulus was constant (Tinga et al., 2019). The study found that subjective and objective

arousal, measured through self-report scales and respiratory, cardiac, and electroencephalogram

(EEG) data, were reduced in all conditions. However, respiratory biofeedback did not result in

the most effective arousal reduction, which was rather seen in the control feedback placebo

condition. These results suggested that biofeedback may not be necessary to induce relaxation

during meditation (Tinga et al., 2019).

Breathing in Anxiety and Depression

Breathing techniques have been proposed as an effective intervention for reducing

negative emotions, including anxiety and depression (Jerath et al., 2015; Lalande et al., 2012). A

diaphragmatic breathing relaxation training program over 8 weeks was implemented in a sample

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of participants with elevated anxiety. They completed the training twice a week for the first 4

weeks and once a week for the final 4 weeks in a hospital site and were required to practice at

least twice daily at home and keep a diary of their training (Chen et al., 2017). While the control

group did not receive any breathing training, they also obtained relaxation practice with

biofeedback monitoring. The results indicated that the diaphragmatic breathing training reduced

levels of self-reported anxiety and improved physiological indicators such as skin conductivity

and heart rate (Chen et al., 2017).

In a study described previously (Ma et al., 2017), an intensive 20-session diaphragmatic

breathing training resulted in a decrease in negative emotion. Also, stress management programs

that include breathing in addition to other techniques such as meditation, relaxation, and imagery

have been shown to be effective in reducing negative emotions, emotional instability,

hopelessness, anxiety, and salivary cortisol levels in undergraduate students (Iglesias et al.,

2012). It has also been shown that a mindful breathing exercise for daily 30-minute sessions at

home was as effective as cognitive appraisal practice in reducing test anxiety in undergraduates.

The breathing practice also induced a larger increase in positive automatic thoughts as compared

to cognitive appraisal and control conditions (Cho et al., 2016).

An investigation of a program based on Sudarshan Kriya Yoga was conducted with

patients diagnosed with generalized anxiety disorder or a depressive disorder (Doria et al., 2015).

The intervention consisted of an intense workshop of 10 sessions over 2 weeks, followed by

weekly follow-up sessions for 6 months. Sessions lasted approximately 2 hours and included

different forms of yogic rhythmic breathing techniques, brief chanting, and a simple yoga

stretching sequence. A simplified home based shorter version of the breathing practice was

introduced so that participants practice individually once a day in the morning for 6 days of the

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week (Doria et al., 2015). The study showed that this intervention was effective in reducing

levels of anxiety and depression in these outpatients whether or not they were being treated

pharmacologically. The improvements were also maintained at follow up, with reductions of

overall symptom and severity indices (Doria et al., 2015). Together, these studies suggest that

these breathing paradigms can be implemented as adjunctive or even primary treatment options

for anxiety and depression (Doria et al., 2015; Jerath et al., 2015; Lalande et al., 2012).

Specifically in depression, a coherent breathing paradigm was implemented in

conjunction with Iyengar yoga practice in a sample of adults with major depressive disorder

(MDD) (Streeter et al., 2017). Iyengar yoga involved a series of mostly inversion and backbend

postures, relaxation transitions, and breathing techniques, while the coherent breathing practice

consisted of gentle breathing at 5 breaths per minute to optimize HRV and sympatho-vagal

balance. The intervention consisted of 90-minute yoga and breathing sessions consisting of

approximately 60 minutes of yoga postures, 10 minutes of transition with deep breathing and

relaxation, and 20 minutes of coherent breathing. Individuals participated over the period of 12

weeks with assigned homework of postures and breathing (15 minutes each) guided by an

auditory recording (Streeter et al., 2017). This study additionally investigated whether there was

an optimal dose of yoga by incorporating a high-dose group where participants completed three

yoga classes and four homework sessions, and a low-dose group with two yoga sessions and

three homework exercises. The results showed a significant reduction in depressive

symptomatology at 12 weeks in patients with MDD regardless of medication status and of dosing

(Streeter et al., 2017).

This study further showed that this intervention of yoga and coherent breathing was

efficacious at both dosing conditions in decreasing symptoms of anxiety, sleep disturbance, and

26

fatigue, and increasing feelings of positivity, revitalization, and tranquility (Scott et al., 2019).

These improvements were seen both acutely after engaging in individual yoga sessions and

cumulatively over the course of 12 weeks. Improvements were also noted on an mid-study

assessment at week 4 (Scott et al., 2019), suggesting that a shorter period of intervention might

be as effective in improving wellbeing in individuals with MDD. In fact, a breathing relaxation

intervention in conjunction with CBT implemented during 12 sessions over a 4-week period in

acute inpatients with MDD and sleep disturbance resulted in significantly improved sleep quality

and heart rate variability parameters compared to a control group, with lasting effectiveness at

follow-up (Chien et al., 2015).

Breathing paradigms have shown mood enhancing effects in healthy young adult

populations. Two different forms of a deep and slow diaphragmatic breathing technique were

investigated in a healthy undergraduate sample from a university in Germany (Busch et al.,

2012). The first form was “attentive breathing” where participants breathed according to an ideal

respiratory curve cued by external feedback. The second consisted of “relaxing breathing” where

participants were directed to follow a respiration rate by verbal instruction from the experimenter

and instructed to turn their awareness to the experience of breathing while fixating their gaze on

a spot on the wall (Busch et al., 2012). The rate of breathing in both conditions was set to seven

cycles per minute, and participants completed a 20-minute training with three 5-minute breathing

blocks. Both breathing interventions showed a decrease in tension, anger, depressive mood, and

stress. Additionally, only the relaxed breathing paradigm, where the concentration and cognitive

control demands were minimal, resulted in a reduction in pain perception and decrease in skin

conductance levels indicating reduced sympathetic activity. This suggested that deep paced

breathing with relaxation modulated pain perception and sympathetic arousal, and that an

27

individualized approach to breathing paradigms may be effective in targeting different emotional

and physiological states (Busch et al., 2012).

An individualized training according to personalized resonant frequency was also

suggested in an HRV biofeedback intervention study (Steffen et al., 2017). In this investigation,

each participant’s resonant frequency was determined; one group of participants then completed

15 minutes of breathing at their unique resonant frequency while a second group breathed at their

resonant frequency + 1 breath per minute. An additional third group was the control with no

breathing instructions (Steffen et al., 2017). The participants who completed the unique resonant

frequency breathing showed the highest reported increase in positive mood and increased HRV

measures. These results suggested that breathing at an individualized rate corresponding to the

individual’s resonant frequency induced a healthier physiological response and greater

improvements in mood and stress (Steffen et al., 2017).

Limitations of the Breathing Studies

This review of the breathing literature reveals a wide variability in the nature,

methodology, and implementation of breathing interventions, with no homogeneity in protocols

across studies. Breathing training has been implemented at varied session lengths and over a

different number of weeks. Additionally, interventions were conducted in the research setting or

in participants’ homes, and some studies implemented a combination of both (Chen et al., 2017;

Doria et al., 2015). At-home practice was in fact not uniformly monitored for adherence to the

protocol. Also, many experimental conditions incorporated “mindfulness” or focused attention

components in the breathing paradigms (e.g., Ma et al., 2017), often implementing other

techniques such as body scan, muscle contraction and relaxation, and imagery (Iglesias et al.,

28

2012; Kimura et al., 2005). Thus, breathing is often entangled with other practices such as yoga,

meditation, and mindfulness.

Additionally, a large variety exists in the interventions and the methods used to

implement them, and whether they are based on varied yoga, meditation, or breathing

techniques. For instance, some studies implemented both slow and fast breathing exercises

within the same treatment condition (e.g., Doria et al., 2015; Peterson et al., 2017), thus blurring

any conclusions about the effectiveness of different rates or rhythms of breathing. For instance, it

has been noted that the duration of deep breathing conducive to impacting HRV remained

unknow (Cheng et al., 2019). As such, these factors hinder the ability to compare findings across

studies and to determine the unique contribution of each individual component on behavioral,

emotional, and physiological outcomes.

These studies are further limited by poor methodology, with many studies having small

sample sizes (e.g., Chicayban & Malagris, 2014), no control conditions (e.g., Doria et al., 2015;

Peterson et al., 2017; Streeter et al., 2017), or inappropriate control conditions such as inactive

control groups which do not set an appropriate standard for comparison or detection of a

meaningful result (Iglesias et al., 2012; Kimura et al., 2005; Perciavalle et al., 2017).

Additionally, a recent systematic review of the effectiveness of diaphragmatic breathing found

that the certainty of existing evidence was low given that the tools used to measure physiological

arousal including blood pressure, respiratory rate, and salivary cortisol were considered to be

indirect measurements of stress (Hopper et al., 2019).

Most of these interventions are also implemented in a laboratory setting, guided by senior

coaches or seasoned practitioners, or using breathing feedback devices (e.g., Ma et al., 2017),

and are therefore not readily accessible to many populations. On the other hand, some studies

29

were implemented with seasoned practitioners as participants, with potentially limited

generalizability of results to participants naïve to the training paradigm. A further barrier to the

potential use of possibly effective interventions involving biofeedback and use of medical

equipment such as ECG and EEG machines is the high expense and need for a specialized

setting. In fact, many of the training programs in these studies were implemented in the

laboratory setting over multiple sessions, often many times per week, which may also limit

accessibility and feasibility of their application in patient or other populations.

The Use of Mobile Devices

Most studies administered breathing training by expert trainers and through laboratory

equipment, and implemented home-based practice guided by audio recordings and monitored

through self-report diary sheets. In recent years, the availability and wide use of mobile smart

phones and their increasing versatility have provided a novel opportunity for redefining

breathing training (Chittaro & Sioni, 2014). Many mobile applications (apps) have been designed

to guide breathing exercise, many incorporating visualization and auditory feedback and

instructions to prompt specific breathing frequencies. All these methods were found to be

effective in inducing deep and slow breathing as well as useful instruction and relaxation effect,

with a slight advantage for applications that provide visualization (Chittaro & Sioni, 2014).

A review of mobile apps on iOS that implement evidence-based stress management

techniques found that out of a total of 60 evaluated apps, around 70% included evidence based

strategies (Coulon et al., 2016). The most common strategies featured were mindfulness and

meditation, followed by diaphragmatic breathing, social support seeking, and visualization and

imagery, with much less apps including active coping and behavioral activation, problem

solving, and cognitive restructuring techniques. Interestingly, all the apps had good functionality

30

and user-friendliness, making them a good resource for easy access to care in individuals with

chronic stress or other health conditions (Coulon et al., 2016).

Another novel avenue that has been explored for the delivery of health interventions is

mobile health (mHealth) and mHealth gaming (Pham et al., 2016). The “gamification” of

mHealth apps, which can involve adding engaging and enjoyable features such as badges,

leaderboards, points, levels, and challenges, has been shown to provide effective management of

health conditions including diabetes, asthma, and recovery during rehabilitation (Pham et al.,

2016). An mHealth app, “Flowy,” was developed to deliver breathing retraining exercises and

diaphragmatic breathing through a series of minigames with different themes and user

engagements interfaces. This app also provided a tutorial on diaphragmatic breathing and a

visual indicator of the breath rhythm as participants inhaled and exhaled while playing. A

randomized controlled trial targeting people with common mental health disorders including

depression, generalized anxiety disorder, panic disorder, obsessive-compulsive disorder,

posttraumatic stress disorder, and social anxiety disorder was implemented over four weeks

using this app as an intervention for anxiety (Pham et al., 2016). The study found that the app

was acceptable, feasible, and engaging as an intervention for anxiety, however, the clinical

efficacy was not established. The intervention group did demonstrate improvements in quality of

life suggesting a positive change in participants’ coping response to anxiety. The authors believe

the app could have potential broader applicability as a chronic health condition management tool

(Pham et al., 2016).

A systematic review of web-based tools and mobile applications aimed at reducing

burnout, depression, and suicidal thoughts in students and professionals in healthcare found that

very few of these resources were supported by evidence of efficacy and none targeted healthcare

31

professionals (Pospos et al., 2018). Nonetheless, the authors suggested that such mediums have

advantages in that they can reach a broad range of users and address barriers in obtaining

treatment (Pospos et al., 2018). Taken together, these findings indicate that the use of mobile

devices and applications for the implementation of breathing and relaxation interventions is

feasible, accessible, and cost effective.

Significance of the Current Study

The current study aims to address some of the limitations of the existing breathing

literature while making use of innovative and emerging technologies that have shown promise in

the implementation of stress management, breathing, and mindfulness techniques through mobile

applications. A breathing intervention administered through mobile devices can be an accessible,

cost effective, and easily implemented with potential positive effects on stress, anxiety, and

depression, as well as overall functioning. Further, the young adult population specifically has

been shown to experience an increased burden of psychological distress as well as persistent

barriers to obtaining treatment, including financial, psychosocial, and practical limitations.

Additionally, the literature on the increased burden of distress in young adults during the

COVID-19 pandemic and the added restrictions to treatment seeking imposed by physical

confinement and economic strain emphasize the need for home-based inexpensive and accessible

treatment paradigm to reduce stress in this population. It was therefore an opportune time to

investigate a mobile application based training program in young adults experiencing some

levels of stress during the COVID-19 pandemic. In fact, most young adults today are also

familiar with the use of smart phones and mobile applications, adding to the attractiveness of this

method.

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The current study also utilizes an experimental controlled longitudinal design that aims to

determine the contribution of resonant frequency breathing training independently of any other

physical or mental practice. Although a breathing practice is not entirely distinguishable from

focused attention or mindfulness, there were no instructions directly requiring participants to

manipulate their attention or guide their thoughts. Also, controlling the rate of breathing was

fully implemented through the mobile application, allowing participants to guide their breathing

with minimal executive engagement. This arguably resulted in more of a pure effect of breathing

independent from a focused attention effort. Lastly, participants in the current study completed

breathing training at their individualized resonant frequency, based on previous suggestions that

this tailoring might add to the beneficial effects of the practice (Steffen et al., 2017).

The Current Study

The current investigation is a single-blind, randomized, controlled study that aims to

investigate the feasibility and efficacy of a 4-week mobile application-guided individualized

resonant frequency breathing training to reduce stress and improve mood in a non-clinical

sample of young adults with elevated stress. Participant retention rates in intervention studies

essentially have bearing on the validity of the investigation’s conclusions, but also provide

indications for the feasibility of the intervention. For example, they are often used as objective

data on user engagement in mobile applications targeting mental health (Ng et al., 2019).

Expected attrition is usually set at 10-20% (Walters et al., 2017), and several studies have

reported cutoffs of 80% retention to determine the feasibility of the trial and intervention (e.g.,

Cassidy et al., 2019; Hawkins et al., 2019).

Particularly relevant for the current study, a review of RCTs of smartphone apps designed

to manage depression found a mean dropout rate of 26.2% which could be as large as 47.8%

33

when considering publication bias (Torous et al., 2020). These studies tended to have a longer

duration of follow up (e.g., 6 months), which could suggest that a lower attrition rate might be

expected for shorter trials. However, a previous 4-week study investigating an mHealth mobile

app for breathing training found attrition of 45% in the intervention group and 25% in control

participants (Pham et al., 2016). Similarly high dropout has been reported in other meditation

(Basso et al., 2019) and breathing intervention studies (Hopper et al., 2019), while other studies

failed to report these biases e.g., (Ma et al., 2017). In contrast, a few RCTs reported retention

rates as high as 88% and 94% (Scott et al., 2019).

While there is no universal standard for acceptable drop-out or retention rates in evidence

based medicine and RCTs, it has been suggested that less than 5% attrition may have an

insignificant impact on level of bias whereas 20% or greater loss to follow up may pose an

important threat to internal validity (Schulz & Grimes, 2002). It was further indicated that studies

with more than 20% loss of participants would be unlikely to overcome successfully the

challenges to its validity, while any attrition between 5-20% could lead to intermediate levels of

bias (Higgins et al., 2011; Sackett et al., 2000). Further, a review of trials funded and published

by the United Kingdom’s National Institute for Health Research (NIHR) Health Technology

Assessment (HTA) Programme (Walters et al., 2017) found that the median retention rate was

89% with interquartile range of 79-97%. Considering these various factors, a rate of retention of

80% could be considered appropriate to indicate validity and feasibility of the intervention in the

current study, as it has been shown that attrition rates tended to be high in investigations of

mobile applications in mental health.

Aims and Hypotheses

34

Aim 1. To determine the feasibility and tolerability of using a mobile breathing

application to complete breathing training at resonant frequency.

Hypothesis 1.1. It is expected that the mobile breathing application will be well tolerated

by participants, as evidenced by high retention rates defined by at least an 80% retention of

participants.

Hypothesis 1.2. It is expected that by the fourth week of training as compared to the first

week, participants will have higher reported ease of breathing and ability to breathe at the correct

rate, and lower reported distractibility while completing training sessions using the mobile

application.

Aim 2. To determine the effectiveness of a short-term (4 weeks) mobile-based resonant

frequency breathing training in reducing stress, anxiety, and depression symptoms.

Hypothesis 2. It is expected that the breathing group will demonstrate greater reductions

from baseline to post-training (week 4) in self-report measures of stress, anxiety, and depression

as compared to the waitlist control group.

Exploratory Aim 3. To determine the effectiveness of mobile-based resonant frequency

breathing training in improving weekly self-reported stress over 4 weeks of training.

Hypothesis 3. It is expected that the breathing group will demonstrate greater reductions

from week 1 to week 4 in weekly reported stress compared to the waitlist control group.

Exploratory Aim 4. To determine the effectiveness of mobile-based resonant frequency

breathing training in reducing the perceived impact of the COVID-19 pandemic on participants’

psychological wellbeing.

35

Hypothesis 4. It is expected that the breathing group will demonstrate greater reductions

from baseline to post-training (week 4) in the perceived impact of the COVID-19 pandemic on

their psychological wellbeing compared to the waitlist control group.

36

CHAPTER TWO

Methods

Participants

Eighty non-clinical, young adult participants aged 18-29 years with elevated stress were

recruited from the community and through the Queens College undergraduate psychology

research subject pool. Psychology subject pool participants were recruited through the Queens

College SONA system. Participants were recruited from the community through flyers posted in

the NY/NJ metro area and within Queens College and other CUNY campuses, email

announcements sent through CUNY listservs, and other social media services (e.g., Facebook,

Twitter, Craigslist, etc.). Recruitment took place between April and September 2020.

Participants recruited through the Queens College undergraduate participant pool

received research credit towards fulfillment of the research requirement for their introductory

psychology class. All participants who completed the full study received a $25 compensation

through their choice of PayPal payment or Amazon gift card. All participants provided electronic

informed consent for their participation. The study was approved by the Queens College

Institutional Review Board (IRB).

Inclusion criteria. Participants were required to be at least 18 years old and less than 30

years old, own a smartphone or tablet, and have English language proficiency. They were also

screened to have at least moderate levels of stress, as determined by a score higher than 13 on the

Perceived Stress Scale (PSS; Cohen, Kamarck, & Mermelstein, 1983; Cohen, 1988).

Exclusion criteria. Participants were excluded if they reported any neurological or

psychiatric condition or severe medical illness or taking any medication with a known negative

impact on cognition or autonomic nervous system arousal. Participants who endorsed active

37

suicidal ideation or plan or drug or alcohol abuse within the past year were excluded and

provided with the appropriate resources and referrals. Participants were also excluded if they

reported practicing any form of meditation, yoga, or breathing exercise regularly (i.e., at least 3

times per week).

Measures

Demographic and Screening Measures. Baseline demographic characteristics including

age, sex, race/ethnicity, language proficiency, education level, and marital status were collected.

Reported family income, as an indication of socioeconomic status, was obtained during the

follow up assessment. Participants were also asked to indicate at baseline whether they practice

any form of breathing, meditation, mindfulness, or yoga exercises currently or in the past, and

how frequently. They also indicated whether they currently do any form of exercise and its

frequency. Additionally, participants were assessed for past and current alcohol, tobacco, and

drug use and past and current psychiatric diagnoses and treatments, medical conditions, and

medications.

COVID-19 Perceived Impact. At baseline and post-training, participants indicated

whether they or someone close to them (e.g., family, friends, loved ones) have tested positive for

COVID-19. They also rated, on a Likert scale from 1-5 (1 = “not at all”; 2 = “mildly”; 3 =

“moderately”; 4 = “quite a bit”; and 5 = “severely”) the extent to which the COVID-19 pandemic

impacted their ability to complete schoolwork, motivation to complete schoolwork, and ability to

do their work/job, and the extent to which the COVID-19 pandemic affected them financially,

affected their social life/engagement, their mental/psychological health, and their physical health.

Self-Report Measures. The following self-report measures of stress, mood, and anxiety

were administered at baseline and at four weeks post training. Stress was assessed with the

38

Perceived Stress Scale (PSS) (S. Cohen et al., 1983). Mood was assessed with the Beck

Depression Inventory-II (BDI-II) (A. T. Beck et al., 1996) and anxiety was assessed with the

Beck Anxiety Inventory (BAI) (A. T. Beck, Epstein, et al., 1988) and State Trait Anxiety

Inventory (STAI) (Spielberger et al., 1983). These measures were chosen as they are easy to

complete, have been used extensively in research (Julian, 2011; Lee, 2012; Y.-P. Wang et al.,

2013), and have strong psychometric properties, as detailed below.

Perceived Stress Scale (PSS; Cohen et al., 1983). The 10-item version of the PSS

(PSS10) was administered in the current study. This scale measures the degree to which

situations in participant’s life in the past month are appraised as stressful based on whether they

are found to be unpredictable, uncontrollable, and overwhelming (S. Cohen & Williamson,

1988). The PSS10 has shown good internal reliability (alpha coefficient of .78) and to correlate

moderately with other measures of appraised stress and potential sources of stress such as

employment environment and physical illness. It was also recommended for use in research (S.

Cohen & Williamson, 1988).

State Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs,

1983). This scale measures state and trait anxiety on separate self-report scales. State anxiety is

defined as a temporary condition of worry and apprehension experienced in a certain situation,

whereas trait anxiety is a general tendency to perceive situations as threatening (McDowell,

2006). The state anxiety scale (S-Anxiety) consists of 20 items that assess current, in the

moment, affect whereas the trait anxiety (T-Anxiety) scale includes 20 items measuring how

participants “generally feel.” Each item is rated on a scale from 1 (“not at all”) to 4 (“very much

so”) with 10 and 11 reverse scored items for the S-Anxiety and T-Anxiety scales, respectively

(Spielberger et al., 1983). This scale has shown high internal consistency across numerous

39

studies (.91 to .95), with test-retest consistency higher for trait scores (.73 to .86) than for state

scores (.16 to .54), as would be expected conceptually (McDowell, 2006).

Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988). This is a 21-item

measure assessing somatic symptoms and subjective aspects of anxiety on a 4-point intensity

scale (0 = “not at all” to 3 = “severely”). The BAI has shown good internal consistency across

studies (coefficient alpha of .86 to .94) as well as good test-retest reliability (7-week: .62; 1-

week: .75) (McDowell, 2006).

Beck Depression Inventory-second version (BDI-II; Beck, 1967; Beck, Steer, & Brown,

1996; Beck, Steer, & Carbin, 1988). This self-report measure assesses 21 symptoms of

depression based on the fourth edition of the Diagnostic and Statistical Manual of Mental

Disorders (DSM-IV). Each item is ranked on a 4-point intensity scale ranging from 0 to 3. It has

been shown to have high internal consistency in outpatient and college student samples

(Cronbach’s alpha values of .92 and .93, respectively) and test-retest consistency ranging from

.60 to .83 (A. T. Beck, Steer, et al., 1988).

Power Analysis

A power analysis was conducted using R (R Core Team, 2017) and G*Power (Faul et al.,

2007). A sample size of 40 participants per group was adequate to detect a medium effect size

with .8 power at .05 significance level for the primary outcome measures.

Procedures

Participants were invited to participate in a 4-week resonant frequency breathing training

program administered via smartphone. Participants were contacted by email and telephone, and

all study questionnaires including consent, screening and demographic measures, and self-report

questionnaires were administered online via Google documents, with links sent to participants by

40

email. Electronic informed consent was obtained, and participants completed a brief screening

questionnaire as well as the PSS to determine eligibility. Eligible participants were contacted by

phone for an initial baseline session when they first completed a neuropsychological assessment

and responded to the self-reported questionnaires. They were then randomized to one of two

groups: (1) mobile resonant frequency breathing group or (2) waitlist control group.

Participants in the breathing condition were asked to download the “Breathing App” on

their smartphone and were trained on its use. They were guided on how to find their individual

resonant frequency based on an adaptation of the “Protocol for Heart Rate Variability

Biofeedback Training” (Lehrer et al., 2013) and the instructions provided through the “Breathing

App.” According to this protocol, during the initial phone session, participants randomized to the

breathing group were asked to take a deep inhalation and exhalation while comfortable and were

instructed not to strain the breath. Once participants found the ratio of deep breathing with which

they were comfortable, the time in seconds spent for inhalation and exhalation was set as their

resonant frequency ratio. They were then instructed to enter this ratio into their mobile phone on

the breathing application for smartphones, the “Breathing App” (http://ayny.org/breathing-app/).

They were also asked to set their breathing session time to 10 minutes. Participants were

instructed to practice resonant frequency breathing at this ratio during the four-week training

period twice a day for 10 minutes each, for five days a week. Participants in the waitlist control

did not receive any mobile platform training.

Blinding Procedure. The study member administering all measures and procedures at

each study time point was blinded to the participant’s group assignment. This was achieved by

having one member of the study team prepare the block randomization list and maintain

individual documents for each participant revealing their randomization. During the initial

41

assessment session, all measures and assessments were conducted with a different, blinded, study

member. At the end of this initial session, this study member accessed the document revealing

the participant’s group assignment, after which they instructed the participant on their group

requirements. This same study member was then responsible for all future correspondence to the

participant whom they assessed at baseline. All email correspondence was planned so that any

other study member who may have access to the lab’s emails cannot readily know participants’

randomization. During the follow up session for each participant, a different study member than

that who assessed them at baseline, and who had remained blinded to their group assignment,

conducted the assessment. Participants were instructed, at the beginning of the follow up, not to

inform the researcher of what group they were assigned until the end of the session, if needed.

Study team members were unblinded to the full participants only after all data collection was

finalized.

Mobile application. The “Breathing App” (https://eddiestern.com/the-breathing-app/)

was used to guide the breathing group’s practice. This mobile application for iOS and Android

allows participants to choose their resonant frequency, determined by a ratio of seconds to inhale

to seconds to exhale, and their practice time in minutes. Participants were instructed to use the

“breathing ball” to guide their breathing. This visual prompt follows the specified ratio and

grows larger as a cue to inhale and smaller as a cue to exhale. Participants were asked to not use

the other features or screens in the app which provide sound or time cues for the breathing.

Weekly Self Report and Compliance Monitoring. Participants’ breathing training was

tracked through brief questionnaires sent weekly in which participants report the amount of time

each day of the past week spent practicing breathing through the app. At the time of their

baseline assessments, participants were provided with calendars via electronic documents send

42

by email to keep track of their daily breathing sessions. To maintain group equivalence, the

waitlist control group participants were also sent weekly questionnaires in which they reported

the amount of time they spent using their smartphone and were provided with tracking calendars

for daily phone use.

All participants were also asked to respond to one question rating their stress level for the

past week on a 1-5 scale with 1 being the least stressed and 5 being the most stressed. Additional

questions were included for participants in the breathing group to measure their experience using

the Breathing App to complete the breathing sessions to further monitor for the training’s

tolerability as well as adherence to the protocol. Breathing group participants were asked to rate,

on a 1-5 rating scale, overall ease of the breathing training with 1 signifying “not easy at all” and

5 being “very easy”; their subjective level of distraction while completing the breathing sessions

with 1 being the least distracted and 5 the most distracted; whether they believed they were

breathing correctly at their assigned breathing frequency with 1 being “strongly disagree” and 5

being “strongly agree”; and whether they felt less stressed after completing the breathing

sessions with 1 being “strongly disagree” and 5 being “strongly agree.”

Statistical Analyses

All statistical analyses were conducted using R (R Core Team, 2017) and IBM SPSS

Version 27.0.1.0. Demographic characteristics at baseline were computed and compared across

groups. Multilevel linear models using maximum likelihood (ML) estimation were conducted to

analyze the change in outcome variables from baseline to post-training and compare the two

groups. A random intercept model was always chosen as the baseline model with the random

effect specifying the repeated measures predictor as time nested within participant. Time and

group were specified as fixed factors. Covariates were added to the models as fixed effects.

43

Models were built by starting with the random intercept model only and adding fixed effects one

at a time. Models were compared using analysis of variance and model comparison and fit were

assessed using -2log-likelihood (-2LL) as well as the Akaike Information Criterion (AIC) and

Bayesian Information Criterion (BIC) indices (Field et al., 2012). Outcomes of the multilevel

linear models were the self-report measures. Significance level was set at .05 for all primary

hypotheses.

44

CHAPTER THREE

Results

Demographics

A total of 80 participants were recruited with 40 randomized to the breathing group and

40 to the control group. Demographic characteristics at baseline are presented in Table 2. The

mean age of the sample was 21.09 years (SD = 2.86), and there was no significant difference in

age between the two groups (p > .05). The sample was predominantly female (66.3% in the total

sample) with no significant difference between groups in gender distribution. The ethnic/racial

distribution of the sample was predominantly Asian (31.3%) and Hispanic/Latino(a) (26.3%),

followed by White (18.8%), Black or African American (15%), and Mixed (8.8%). The two

groups were not significantly different in ethnic/racial distribution (p > .05) or in family income

earned (p > .05). The majority of participants reported that they were bilingual (67.5%), and this

was similar for both groups (p > .05), while all participants reported English as their primary

language.

Approximately half the participants in the sample reported doing some form of exercise

(48.8%) with no significant difference between groups (p > .05). Only one of the participants

reported having tested positive for COVID-19 and this participant was randomized to the

breathing group, while 40% of the total sample reported that someone close to them (family,

friend, loved one) has tested positive for COVID-19 with no significant difference between

groups (p > .05).

A total of 70 participants completed the four-week follow-up assessment, with 37

participants from the control group and 33 from the breathing group. Overall, 87.5% of the

sample was retained, with 82.5% retention within the breathing group and 92.5% retention in the

45

control group. This was consistent with Hypothesis 1.1., as there was no significant difference

between the two groups in rates of attrition, p = .31. Participants who dropped out were not

significantly different than the rest of the sample in group membership, gender, racial/ethnic

distribution, bilingual status, or exercise, all ps > .05. Participants who dropped out were more

likely to report smoking marijuana, c2(4) = 5.6, p = .04 with 40% reporting use as opposed to

only 11.4% of those who did complete the study. It was not possible to analyze the difference in

household income between participants who completed the study and those who dropped out due

to this data having been recorded at follow up.

Among participants who dropped out, 70% were female and the difference in gender was

not significant, c2(1) = .50, p = .63; 3 (30%) identified as Asian, 3 (30%) were Black or African

American, 2 (20%) were White, 1 (10%) Hispanic, and 1 (10%) was of mixed race, c2(4) = 4.44,

p = .35; 70% were bilingual, c2(1) = 2.74, p = .18; 60% reported doing some form of exercise,

c2(1) = 1.27, p = .5; 20% smoked tobacco; 40% reported smoking marijuana; none had tested

positive for COVID-19; and 30% had a close person test positive for COVID-19.

Baseline Outcome Variable Characteristics

Correlations. Pearson’s correlation coefficients between emotional and COVID-related

impact self-report variables at baseline are reported in Table 3. None of the correlations were

higher than r = .74, indicating that there was no evidence of multicollinearity that would impact

the inclusion of these variables in linear models. Total PSS score was significantly correlated

with all other emotional variables (i.e., positively correlated with BAI, STAI state anxiety, and

BDI) with moderate to large effect sizes. Total BAI score was also highly correlated with state

anxiety, and BDI. BDI was strongly positively correlated with STAI state anxiety.

46

Baseline Group Differences. Independent samples t-tests showed that there was no

significant difference at baseline between the control group and breathing group in total PSS,

BAI, state anxiety, BDI, or positive or negative affect (all ps > .05). Means and standard

deviations (SD) by group and time are reported in Table 4. Females reported significantly higher

scores on total PSS, t(78) = 4.12, p < .001, state anxiety, t(78) = 2.06, p = .04, and BDI, t(78) =

2.28, p = .03, than males but there was no significant difference between genders in BAI. Means

(SD) by gender are reported in Table 5.

Perceived Stress Scale (PSS)

Model parameters with PSS as outcome are reported in Table 6. The results of multilevel

linear models using ML estimation with PSS as outcome showed that there was a significant

main effect of time in predicting total PSS (p < .001) such that over time, perceived stress

significantly declined for the whole sample (p = .001). The main effect of group was not

significant. Contrary to prediction based on Hypothesis 2, the interaction effect of time and

group was also not significant (p = .9). Means (SD) of all self-report measures by group and time

are reported in Table 4. There was a significant correlation between the change in PSS scores

and baseline scores, r = -.66, p < .001.

Sex Differences in PSS. When gender was added as a predictor with PSS as outcome in

multilevel linear models, findings showed a significant difference between genders in total PSS,

c2 (5) = -453.64, p < .001, with females in both groups reporting higher perceived stress than

males, b = 3.29, t(80) = 3.81, p < .001 at both baseline and post-training. Means and SD per

gender are reported in Table 5. Time remained a significant predictor of perceived stress when

gender was added, c2 (6) = -443.26, p < .001, suggesting that perceived stress declined for both

genders. However, the interaction effect of gender and time was not significant (p = .08)

47

suggesting that males and females experienced a similar decline in PSS over time. There were no

significant group differences between genders and across time in predicting PSS.

State Trait Anxiety Inventory – State Anxiety

Model parameters with STAI state anxiety as outcome are reported in Table 7. The

results of multilevel linear models with STAI state anxiety as outcome showed that there was a

significant main effect of time suggesting that state anxiety declined from baseline to post-

training for all participants regardless of group membership. The main effect of group and the

interaction effect of group and time were not significant, ps > .05, which was not consistent with

Hypothesis 2.

Beck Depression Inventory (BDI)

Model parameters with total BDI as outcome are reported in Table 8. Multilevel linear

models with BDI as outcome showed a main effect of time in reported depression suggesting that

depression declined over time for the whole sample (p < .0001). The main effect of group and

the interaction effect of group and time were not significant (ps > .05), which was contrary to

Hypothesis 2.

Sex Differences in BDI. Adding gender as a predictor within multilevel linear models

predicting BDI showed a significant gender difference in total BDI, c2 (5) = -453.64, p < .001,

with females reporting higher depression than males regardless of time, b = 3.29, t(80) = 3.81, p

< .001. However, the interaction effect of gender and group was significant, c2 (7) = -546.21, p =

.02, with the females in the breathing group (M = 17.8, SD = 11.79) scoring significantly higher

than males (M = 8.11, SD = 5.98), t(38) = 3.36, p = .002 and no significant difference in

depression between genders in the control group.

48

Time remained a significant predictor of depression when considering gender, c2 (6) = -

541.99, p < .001. However, the interaction effect of gender and time was not significant, (p =

.27) suggesting that males and females experienced a similar decline in BDI over time.

Beck Anxiety Inventory (BAI)

Model parameters with total BAI as outcome are reported in Table 9. Multilevel models

predicting BAI showed that there was a significant main effect of time suggesting that anxiety

declined over time for the whole sample (p = .03). The main effect of group and the interaction

effect of group and time were not significant (ps > .05), contrary to prediction from Hypothesis

2.

Perception of the COVID-19 Pandemic’s Impact on Psychological Wellbeing

Model parameters with COVID-19 perceived psychological impact as outcome are

reported in Table 10. Results from multilevel models predicting ratings of the perceived

psychological impact of COVID-19 demonstrated that participants’ perception of the impact of

COVID-19 on their psychological wellbeing declined from baseline to post-training (p = .01).

The main effect of group was not significant. However, Hypothesis 4 was supported, as there

was a significant interaction effect of time and group in predicting the perception of COVID-19’s

psychological impact such that participants’ perceived impact of the pandemic on their

psychological wellbeing declined significantly for the breathing group, b = -0.75, t(32) = -3.55, p

= .001, but not for the control group, b = -0.09, t(34) = -0.4, p = .69.

Weekly Self Report

Weekly Changes in Self-Reported Breathing Training Experience. Multilevel linear

models predicting weekly ratings of breathing experience revealed that weekly self-reported ease

of breathing while using the app was significantly higher at week 3 and at week 4 as compared to

49

week 1, providing support for Hypothesis 1.2. Means (SD) for each week on all self-reported

weekly breathing questions and comparison test parameters are reported in Table 11. Also,

Hypothesis 1.2 was further supported as participants’ reported distractibility while practicing the

breathing session over a certain week was significantly lower at week 4 as compared to week 1.

Participants’ report of whether they were breathing correctly at their assigned frequency and of

whether they thought their stress declined after breathing practice did not significantly change

over the 4 weeks of training, all ps > .05, contrary to prediction based on Hypothesis 1.2.

Weekly Stress. Pearson’s correlations showed that reported stress at week 4 was

positively correlated with PSS (r = .33, p = .005) and STAIS state anxiety (r = .3, p = .01). The

results of multilevel linear models with weekly stress as outcome showed a main effect of group

in weekly report of stress, with the control group (M = 2.99, SD = 1.20) overall reporting

significantly higher stress than the breathing group (M = 2.48, SD = 1.04). Additionally,

Hypothesis 3 was supported, as there was a significant interaction effect of group with reported

stress at both week 3, b = -0.67, t(191) = -2.16, p = .03, and week 4, b = -0.62, t(191) = -2.02, p =

.045, with the breathing group reporting significantly reduced stress during these weeks. Means

(SD) for each group are reported in Table 12. In fact, post-hoc comparisons revealed that the

breathing group reported significantly less stress after the fourth week (M = 2.27, SD = 0.90) in

comparison to after the first week of training (M = 2.67, SD = 1.15), b = -0.63, t(90) = -2.53, p =

.01, suggesting a decline in stress that was not seen in the control group.

50

CHAPTER FOUR

Discussion

The current study sought to investigate the effects of a mobile guided resonant frequency

breathing intervention on psychological wellbeing of young adults reporting elevated perceived

stress. This was one of the few studies to date to implement a randomized controlled design to

explore the benefits of a breathing intervention (Hopper et al., 2019). Also, the breathing

manipulation in the current study was relatively unique in its context and the medium with which

it was delivered. First, few previous studies implemented a breathing training that was not in the

context of other practices such as yoga (Doria et al., 2015; Scott et al., 2019; Streeter et al., 2017;

Yadav et al., 2012) or mindfulness (A. R. Beck et al., 2017; Kraemer et al., 2016), or

accompanied by additional interventions such as meditation (Peterson et al., 2017), relaxation

and exercise (Kimura et al., 2005), or biofeedback (Meier & Welch, 2016; Prinsloo et al., 2013).

Second, the use of a mobile application to conduct the breathing and the implementation of the

entirety of the training at participants’ homes, including the first session where participants were

instructed on how to practice, were novel approaches not previously used in any study to the

author’s knowledge at this time.

The current investigation was also a fully online and phone study, adding to its potential

implications for the effectiveness of an accessible paradigm for improving mental health

especially during times of limited physical mobility. This can also increase and facilitate access

to care to individuals who may experience barriers due to anxiety or concern about exposure to

COVID-19, as well as those who may be living in remote areas. Lastly, the study population of

young adults, particularly those with elevated stress, has been considered among the more

vulnerable groups for developing increasing levels of psychological distress in general

51

(American Psychological Association, 2013) and possibly also during the COVID-19 pandemic

(Pierce et al., 2020).

The first main aim of the current study was to determine the feasibility of implementing a

breathing training at resonant frequency through a mobile application and to investigate

participants tolerability of this method. It was expected that the mobile breathing application

would be an acceptable and easy medium for young adults to complete breathing training. The

results showed that 33 out of 40 (82.5%) participants in the breathing group completed the four

weeks of training, and that the difference in dropout from the control and breathing group was

not significant. This suggests high retention relative to rates seen in previous studies of mobile

app interventions (Pham et al., 2016, 2016), indicating that the current intervention was tolerable

and feasible. Also, these participants reported that the breathing practice through the app became

easier after the third and fourth week of training as compared to the first week. By the fourth

week, they also experienced less subjective distractibility while completing the breathing

sessions. These findings suggest that the app was a plausible method for training breathing and

that as participants progressed through the practice, they were able to adhere better to the

demands of the breathing task.

It was not possible in the current study to objectively monitor adherence to the breathing

and study protocol or the effectiveness of the app to guide a correct practice directly by using

app data or observing participants as they complete the training. However, participants’ self-

report of increased ease and focus, although potentially less valid indirect and subjective

measures, are arguably important indicators of participants’ attitudes towards this intervention

and their acceptance of it. It is conceivable that with perceived easier use individuals will be

more willing to adhere to the practice. Additionally, although this was not designed as a focused

52

attention training, self-reported distractibility remains relevant as maintaining attention while

practicing breathing is arguably central to the practice and to obtaining its benefits (Herrero et

al., 2018). In fact, participants in the current study who smoked marijuana were more likely to

drop out than those who did not report cannabis use. It has been suggested that individuals who

use marijuana tend to have a lower ability to execute attentional control (Tang, 2017), and it can

thus be argued that their higher rate of attrition could reflect increased difficulty to complete a

task that requires focused attention. For these participants, a practice with more directed external

cues may be more appropriate than the current app paradigm, such as guided biofeedback or

verbal instruction (Brown et al., 2013), or practices of shorter session duration requiring less

focused attention (Ribeiro et al., 2018). It is also possible that by asking participants to rate their

distractibility weekly, they might have been indirectly prompted to exert more attentional control

despite this not being included as a prompt in the original instructions.

In fact, spontaneous breathing frequency in humans at rest can vary widely both inter-

and intra-individually (Benchetrit, 2000). Maintaining a steady rate of respiration at a specific

frequency requires attentional demands and cognitive control and monitoring, and it has been

shown that this executive control improves with practice (Singh & Mutreja, 2020). It has been

similarly proposed that breath regulation, which itself requires attentional control will in turn

improve arousal and focused attention to a degree, suggesting that more advanced practitioners

may exert less effort to control their attention as they exercise this system (Melnychuk et al.,

2018). These findings suggest that breathing is most effective with higher attentional control and

thus, less distractibility, while this executive control might become less effortful but more

efficient in expert practitioners. Of note, a caveat of the ratings of distractibility and ease of

53

breathing in the current study is the lack of a parallel to them in the control group, making it

difficult to determine if the changes were specific to the group manipulation.

In contrast, participants were also asked to report whether they believed they were

correctly breathing according to their resonant frequency. The ratings on this question did not

change over the four weeks. In fact, participants may have felt that they were breathing correctly

since the start of the study regardless of their actual accuracy, making this rating somewhat less

valid. In fact, the mean rating of this question at week 1 indicated that generally participants

agreed that they were breathing at their correct frequency. It is likely that, since the current

participants were novice practitioners of this paradigm, they would have exerted more effort in

attempting to adhere to the rate of breathing earlier in the training, which may have driven this

pattern of response. Further, they were later likely to have become better with practice at

following their breathing rate, which maintained their positive attitude about their accuracy

(Ribeiro et al., 2018; Tang, 2017).

The second main aim of this study was to investigate whether a 4-week resonant

frequency breathing intervention was effective in reducing stress, anxiety, and depression

compared to a waitlist control condition. It was hypothesized that after four weeks of breathing

training, the breathing group would show greater declines in perceived stress, anxiety, and

depression compared to the control group. The findings did not support this hypothesis as there

were no significant group differences in the change across time in these self-report measures. In

fact, there was a decline in perceived stress, state anxiety, general anxiety, and depression for all

participants from baseline to week 4.

The breathing intervention in this study was not found to decrease psychological distress

over and above the change seen in the control group. This is in line with a recent review that

54

concluded that the evidence for the effectiveness of diaphragmatic breathing was low (Hopper et

al., 2019). However, the studies in this review used physiological measures of arousal as

indicators of the stress response such as blood pressure, respiratory rate, and salivary cortisol

which are arguably indirect measurements (Hopper et al., 2019). The authors indeed suggested

that the use of a self-report tool such as the PSS could be a more reliable and valid outcome

measure.

In fact, a number of previous studies that measured perceived stress and mood using self-

report scales have found that breathing interventions improved these outcomes over time (Ma et

al., 2017; Perciavalle et al., 2017). However, many of these interventions were implemented for a

duration longer than 4 weeks, with some studies reporting 8 weeks of practice and as high as 12

week durations (A. R. Beck et al., 2017; Kraemer et al., 2016; Scott et al., 2019), and/or included

more intense sessions (Doria et al., 2015; Ma et al., 2017; Streeter et al., 2017). For example,

although one study conducted a breathing training during a brief 3-day retreat, participants also

engaged in other practices such as meditation and physical exercise (Peterson et al., 2017; Yadav

et al., 2012). Similarly, participants with high anxiety experienced a decline in anxiety after

completing a diaphragmatic breathing training in a hospital setting twice a week for 4 weeks then

once a week for an additional 4 weeks, in addition to a twice daily in-home practice (Chen et al.,

2017). It is therefore likely that the 4-week duration of the current study was too brief for the

breathing manipulation to exert a significant effect. In fact, a study implementing only one brief

(5 to 9 minutes) in-lab session followed by daily practice for 7 days found a greater decrease in

depression with increased breathing session length, however, anxiety and stress did not improve

(Cheng et al., 2019). It was similarly hypothesized that the short duration of the training could

have driven this result.

55

Other factors may have also played a role in limiting the effect seen in the breathing

group. The current sample was selected to have baseline elevated perceived stress, which might

have increased the likelihood that participants in the control group would also experience

declines in stress levels by mere regression to the mean (Rocconi & Ethington, 2009; Zhang

Xuyang & Tomblin J. Bruce, 2003). In fact, the findings showed that higher PSS scores at

baseline were highly correlated with a larger change from baseline to post-test. Given the

elevation in baseline stress in the sample, the strength of the overall decline could have

outweighed the effect of the breathing intervention, especially after a short training of 4 weeks. It

is also possible that the limited lower range in baseline PSS scores could have obscured a true

effect due to decreased variability in the pre-test measurement.

Indeed, perceived stress declined for both groups in this study, but this pattern was also

significant for measures of anxiety and depression, which were not sampled to be elevated at

baseline. This suggests that factors that caused a decline in psychological distress in the overall

sample, including regression to the mean and possibly different psychosocial factors related to

the pandemic (Kujawa et al., 2020), could have been stronger than the breathing manipulation. A

further methodological factor is the short duration between administration of the self-report

scales. It has been suggested that relatively short intervals between assessments may limit the

validity of detecting change in symptoms (Kujawa et al., 2020). It is also possible that the

variation in scores could be induced by a response shift bias whereby participants may have

responded to the same self-report scales from a different internal perspective at each timepoint

thus resulting in a change in their self-evaluations (Drennan & Hyde, 2008; Howard, 1980).

In fact, being enrolled in a study, regardless of group assignment, might have effects on

participants’ report of perceived psychological wellbeing (McCambridge et al., 2014). In the

56

current study specifically, all participants were contacted frequently by the study team by email

and asked to report their phone use or breathing app use. They also reported their stress levels

weekly. Study engagement and researcher interaction may have therefore positively influenced

participants subjective wellbeing (MacNeill et al., 2016). Additionally, it is likely that in the

setting of potentially constant preoccupation with information and worries about the COVID-19

pandemic and different sociopolitical events during the study period, the small break where

participants were able to momentarily detach and self-reflect may have been beneficial. In fact,

the current decline in psychological distress across time was not found to be dependent on the

month during which participants were in the study, suggesting that study factors might have had

a more prominent effect than outside situations. For example, participants recruited earlier in the

study (closer to April) might have still been faced with many unknowns and rising COVID-19

numbers whereas those recruited closer to September might have already habituated and adapted

to the situation, or on the other hand could have begun to experience more frustration due to

confinement.

In fact, this self-reflective weekly exercise, while brief, could have served as a type of

mindful practice. It has been suggested that engaging in expressive writing, starting a mindful

practice, and pausing from a constant stream of news and emails by performing other activities

can be effective in reducing stress in these situations (Boals & Banks, 2020). In fact, appraisal of

one’s own stress or mood symptoms could inherently induce an emotion regulation response

whereby an individual would adjust their coping mechanism (S. Schmidt et al., 2010). Further, a

tendency to have negative attention bias resulting in an increased preoccupation with negative

information such as death toll and confirmed cases of virus contamination could lead to a lower

ability to adaptively regulate emotions (Jiang et al., 2020). It is therefore possible that when

57

given a chance to disengage from this negative information, they were able to momentarily

suppress their rumination and as a result enhance their mood.

In addition to the above methodological and instrumentational factors contributing to the

current findings, some effects related to the COVID-19 pandemic could help explain findings of

reduced stress, anxiety, and depression in the current sample. This finding is consistent with

previous studies on psychological distress during the COVID-19 pandemic showing that

symptoms tended to decline over the study period, particularly in young adults. There was indeed

evidence in the current investigation that the study sample was likely motivated and predisposed

to more positive coping. In fact, approximately half of the sample reported exercising during the

pandemic. Additionally, many participants referenced implementing several coping strategies to

mitigate its impact, including self-care, walking and exercising, healthy eating, spending time

with family, and engaging in spiritual and mindful practice. Reduced stress and mood symptoms

in young adults have in fact been linked to the use of coping strategies such as keeping a daily

routine, positive reappraisal and reframing, physical activity, engaging in distractions,

acceptance, and staying in contact with family and friends even if online or via telephone (Boals

& Banks, 2020; Shanahan et al., 2020). Additionally, it is more likely for those that are more

distressed by the pandemic and lockdown to use such coping techniques, resulting in

improvements in psychological outcomes (Shanahan et al., 2020).

Previous studies have shown that although young adults might be at higher risk for

stressors during the pandemic due to factors including academic and occupational uncertainty,

loss of social connectedness, and reduced work life balance, other factors might have mitigated

their effects on wellbeing. For example, a survey in undergraduate students in Texas during the

month after the stay-at-home order showed that nearly half of the participants reported lower

58

stress levels related to academic pressure (Son et al., 2020). It was suggested that this might be

related to measures taken by the universities to offset the difficulties of remote learning, such as

reducing course load and easing grading and examination criteria. Some students might have also

enjoyed the family support and reduced social responsibilities afforded by returning to their

parental homes (Son et al., 2020). In fact, other studies found a decrease in social anxiety

symptoms that was uniquely associated with home confinement, suggesting that some young

individuals might have benefited from the release from social pressures during the pandemic

(Hawes et al., 2021).

Further, the decline in distress seen in these studies was contrasted with the preexisting

trend in recent decades of increasing stress and internalizing symptoms in contemporary Western

youth (Shanahan et al., 2020). In the context of a relatively lower risk of health complications

from COVID-19 and possibly relatively lower responsibilities, young adults may have a higher

potential to experience resilience and adaptation (Shanahan et al., 2020; Twenge & Joiner,

2020a). For instance, one study found that middle aged adults were more likely to experience

increased anxiety and depression during the pandemic, suggested to be due to having more

responsibilities such as child care, having to work from home, and worrying about their income

(van der Velden et al., 2020). Although it was not possible to make this comparison in the

current study, it is possible that stress levels in an older sample would have remained elevated.

Additionally, young adults are generally competent in the use of social media and mobile

technologies to maintain social connections (Shanahan et al., 2020). It was also found that

participants who experienced improved wellbeing during the pandemic reported welcoming the

chance to decelerate their life, spend more time with family and loved ones, sleep more, and

spend more time on hobbies (Shanahan et al., 2020). In fact, such activities were indicated by

59

participants in the current study, suggesting a potential link with the observed improvement in

stress and mood. It is likely that this was a protective factor against increased pandemic-related

distress for the current sample which was arguably at higher risk for stress. It was in fact found

that pre-pandemic emotional distress was the largest risk factor for perceived stress,

internalizing, and anger symptoms during the pandemic (Shanahan et al., 2020). This might be

true in the current sample, although participants did not indicate a history of psychological

disorders or treatments.

In contrast, some studies suggested that the psychological stressors of the pandemic and

quarantine, such as duration of confinement, frustration, boredom, inadequate resources, and

stigma could have lasting negative effects (Brooks et al., 2020). For example, college students

reported experiencing increases in stress, anxiety, and depression due to the COVID-19

pandemic and related worries about their health, loved ones, difficulty concentrating, loneliness,

powerlessness, and limited social relationships (Son et al., 2020). However, this sample of

undergraduates was noted to have more maladaptive methods of coping, which differentiates it

from the majority of the present sample. Of note, although the current findings indicated a

decline in perceived stress at post-test, mean PSS scores across groups would still be considered

elevated, suggesting that the decline might not be clinically or functionally relevant. This also

further provides evidence for regression to mean where scores appear to decline due to natural

variability. It also suggests that stress levels remained relatively high in this population,

indicating possible persistent psychological distress that warrants intervention.

The present findings were also in line with the literature showing a higher risk for

psychological distress in women (Hawes et al., 2021; Pierce et al., 2020). Women were more

likely to report higher stress than men at both timepoints. Some studies have suggested that the

60

gender gap in stress, anxiety, and depression may grow larger with persistent stressors such as

those imposed by the pandemic (Debowska et al., 2020). For example, women in the current

study might have faced the burden of taking on more home responsibilities than men. A 5-stage

study in Poland during March and April 2020 found that as the pandemic progressed and as

social distancing and isolation measures started being implemented, women experienced a higher

increase in depression suggesting a relationship between social disconnection and low mood

(Debowska et al., 2020). In contrast, some suggested that because men having been at higher risk

of contracting COVID-19, their psychological distress may have increased during the pandemic

(van der Velden et al., 2020). However, this narrowing of disparities was not seen in the current

study, suggesting that both genders may have had similar experiences during the pandemic.

Additionally, whereas women in the breathing group had higher depression scores at baseline

than those in the control group, they did not experience a greater decline in depression.

The third study aim was exploratory and sought to investigate weekly change in stress

based on a single-item question. It was hypothesized that weekly reported stress would decline in

the breathing group more than the control group. The findings supported this hypothesis, with

participants in the breathing group reporting a greater decline in stress after the third and fourth

week compared to the control group. These results contrast with the absence of an intervention

effect measured at baseline and week 4 using the PSS. One reason for this discrepancy might be

the higher sensitivity of the single item question in the current context to measure stress levels in

a particular week. Although short multi-item measures are generally considered to be more

sensitive and valid in evaluating constructs like stress (Bowling, 2005; Hopper et al., 2019), the

single item in this study might have had a higher ability to capture participants’ attitudes more

closely to when they occurred. In fact, while the PSS instructs participants to respond about their

61

experiences “in the last month”, the single item limits the response to the past week. Also, it is

likely that participants were more accurate in reporting on their stress over a shorter duration and

immediately after the week came to an end, which was when they were sent the questionnaire by

email.

Additionally, the PSS included items that measure several aspects of perceived stress,

such as feelings of nervousness and ability to cope with events happening in a respondent’s life.

On the other hand, the weekly stress question more broadly asked about stress during the past

week. Therefore, it is not possible to know what each participant may have brought to mind

when responding to this item, which may have resulted in substantial inter-individual and intra-

individual (week-to-week) variability. In fact, the correlation at week 4 between PSS and the

single item stress question was moderate, suggesting low concurrent validity between the two

measurements (H. Schmidt, 2018) signifying that they may be tapping into different aspects or

experiences of stress.

Nonetheless, weekly self-report showed a treatment effect for the breathing training,

suggesting that a more frequent assessment of the outcome could be useful in measuring the

effectiveness of intervention, especially when it has a short duration. Further, weekly self-report

also showed that participants consistently agreed that their stress levels declined after completing

the breathing sessions, suggesting that they had a positive overall impression of the breathing

training reducing their stress. In fact, it has been suggested that traditional tools for assessing

psychological symptoms may be less appropriate for use during the pandemic as they may over

or under represent the emergence of relevant symptoms (Ransing et al., 2020). This may suggest

that it is possible that other psychological processes related to the pandemic could have unfolded

during the study duration that the traditional scales used in the present study did not capture.

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The fourth study aim was also exploratory and investigated the perceived psychological

impact of the COVID-19 pandemic. It was hypothesized that participants perception of the extent

to which the pandemic had an effect on their psychological health would decline over time in the

breathing group more than the control group. This hypothesis was also supported by the findings,

with the breathing group reporting less impact of the pandemic at week 4 compared to baseline.

Interestingly, participants’ perception of the impact of the pandemic on other areas including

school and work, physical health, and social life did not change over time. This suggests that

although the breathing training may not have had an effect on self-report scales of stress, anxiety,

and depression, it mitigated to some extent participants’ response to psychological distress

caused by COVID-19. This effect also seemed to be specific to the emotional impact, suggesting

that breathing training could have indeed moderated people’s response to psychological stressors

specifically.

These findings indicate that, in addition to different coping and adaptation strategies

young adults might have used to lessen the effect of pandemic-related stress on their wellbeing, a

breathing intervention was likely a positive addition to these coping skills as seen in the

breathing group. This breathing paradigm can have the ability to enhance the stress system’s

response to internal and external challenges (Agorastos et al., 2019) and thus reduce short term

stress and activate positive emotion regulation (Abelson et al., 2010).

Significance and Future Directions

The current study showed that a short-term, mobile application based, free, and home-

based breathing training at resonant frequency was an acceptable and feasible intervention for

implementation in a young adult sample with elevated stress levels. This intervention also

showed some evidence for reducing weekly reported stress and perceived psychological impact

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of a the COVID-19 pandemic, a time that was unique for the current generation of young adults.

Accessible technologies such as smart phones and applications can be especially relevant for use

in situations where barriers to help seeking are high, such as in times of social and physical

isolation (Son et al., 2020). Specifically, young adults tend to be a more vulnerable population

with high rates of emotional distress but disproportionate treatment seeking with challenges to

obtaining quality mental care (Twenge & Joiner, 2020a). There has therefore been calls for

leveraging telehealth and technological approaches to healthcare, as well as mediums with free

and easy access (Every-Palmer et al., 2020).

These methods are also arguably increasingly important for individuals with no prior

mental health conditions, such as those in the present study, who develop symptoms in the

context of a pandemic (Holingue et al., 2020). Stress can occur in different situations and settings

and often impacts many domains of functioning, making it an important target for intervention.

Breathing techniques that can be easily taught and practiced anytime, anywhere using a mobile

application have promise in reducing the burden of mild to moderate emotional distress (Hopper

et al., 2019; Pham et al., 2016).

Based on the current findings, future studies may investigate mobile-based breathing

training for a duration longer than 4 weeks, which might reveal larger treatment effects than the

present study. Individuals may be more likely to discontinue mobile application based

interventions that entail long durations of practice (Ng et al., 2019; Torous et al., 2020),

especially if they have difficulties maintaining focused attentional control (Melnychuk et al.,

2018). The present findings demonstrated that participants become more effective in breathing

practice over time, with increased ability to adhere to the demands of this training. This

information might therefore be used as an incentive strategy that may motivate users of the app

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by indicating that breathing practice would become easier and more accurate. It might also be

valuable to conduct multiple outcome assessments which may provide more a sensitive outcome

change trajectory. Additionally, the development and use of scales that specifically assess

COVID-19 related psychosocial impacts such as stigma and traumatic stress might be

particularly relevant (Ransing et al., 2020) given the current findings of a change in perceived

psychological impact of the pandemic over time.

Limitations

Some limitations in the current study warrant consideration. This was an investigation of

the efficacy of breathing training at resonant frequency using a mobile application, the

“Breathing App,” in reducing psychological distress in young adults. A limitation of this

paradigm was the absence of a direct method of tracking adherence to the breathing protocol or

the required number and length of the breathing sessions. Although participants were asked to

self-report their app usage weekly, this is only a subjective method with likely limited accuracy

and validity. Participants may have under- or overreported their time spent completing breathing

training, due to acquiescence, desirability/impression management, and study demand biases. In

fact, the large majority of participants in the breathing group reported completing exactly the

number and duration of breathing sessions required, suggesting a possibility of response bias.

Additionally, the current study sample may have specific characteristics due to self-

selection bias. The majority of participants were also recruited through a research participation

system as part of an introductory psychology class. These factors limit the generalizability of the

present findings to other samples that may not be similarly aware of mental health and disposed

to practicing positive coping and self-care. Physical exercise has been known to contribute to

modulation of HRV acutely and chronically (Dong, 2016; Silva et al., 2015), and equal

65

proportions of participants in the control and breathing group in the current study reported

regular exercise. It is therefore likely that any effects of the breathing condition may have been

confounded by the potential impact of exercise on autonomic nervous system modulation and, as

a result, on any changes seen on psychological measures. It was also not possible to determine

whether during the study duration participants in the control group changed any of their

behaviors or increased their practice of other forms of meditation or mindfulness. Additionally,

given that this was advertised as an investigation of a breathing training to reduce stress, an

expectation bias for all participants may have caused a reduction of reported psychological

distress. Furthermore, the current study was single-blinded and therefore any improvements in

stress, mood, and anxiety in breathing group participants may have reflected a placebo effect. It

was also not possible given the current study design to control for this effect by including a

placebo control which thus may be warranted in future studies. For example, paradigms

including breathing at other respiratory frequencies or a different form of focused practice that

does not involve deep breathing might be considered. And lastly, all participants were provided

with a monetary incentive to complete the study, possibly influencing motivation to provide

accurate responses as well as rates of attrition. A combination of these factors may have in fact

obscured the treatment effects of the breathing intervention.

Another limitation of the current study was its relatively short duration. In fact,

improvements in stress and mood after breathing practice have been found in studies that

implemented longer intervention durations (A. R. Beck et al., 2017; Kraemer et al., 2016; Scott

et al., 2019), while other studies with durations as short as one week did not find such

improvements, suggesting that a longer training might be more effective (Cheng et al., 2019). It

is therefore possible that 4 weeks might be too short of a training period for detect improvement

66

on symptom inventories above and beyond normal variability (Drennan & Hyde, 2008; Kujawa

et al., 2020). It was also evident in the current data that weekly reported stress showed a decline

starting after the third week of training, suggesting that a shorter intervention duration may not

result in the expected improvements.

Further, the current sample was naïve to regular breathing practice which could have

attenuated any real treatment effects as it might have taken some time for these participants to

implement the breathing correctly. It was also not possible to directly assess their progress or

accuracy, limiting the conclusions that can be made about the breathing training. One method to

potentially support and confirm accurate practice at the outset of the training would be to

implement a single videoconferencing session with a trained member of the study team during

the baseline assessment session. This would help verify that each participant is well trained on

following the correct frequency of breathing and troubleshoot any difficulties related to the

practice or to the use of the app. Finally, this study was fully implemented during the COVID-19

pandemic. Although it provided useful insights into models of coping in young adults during a

globally impactful event, the current results may not apply to more common situations.

Conclusion

The current investigation provided evidence of feasibility and acceptability, in terms of

increased ease of use and engagement, of a smartphone application based resonant frequency

breathing training in young adults with elevated stress. This intervention was found to be

effective in reducing stress after the third and fourth week of training, and the perceived impact

of the COVID-19 pandemic on psychological wellbeing, as measured by weekly self-report.

However, there were no effects on stress, anxiety, or depression measured by pre- and post-

treatment scales. It was also found that overall, levels of psychological distress in this sample

67

declined over time, suggesting potential other mechanisms that could be driving these changes,

such as factors related to measurement error or researcher interaction, or others related to

lifestyle modifications implemented by or imposed upon youth during a global pandemic. These

findings suggest that a breathing intervention using a simple, free, and accessible mobile

application and practiced twice daily for 10 minutes may effectively at least lessen the perceived

burden of some stressors faced by young adults such as the psychological impact of the COVID-

19 pandemic, and result in lower stress levels. Such paradigms can be particularly valuable for

individuals who face barriers to care such as financial burden, logistical accessibility, stigma, and

other limitations inherent to the symptoms of psychological distress.

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TABLES

Table 1

Summary of HRV Measurements

Description Measures

Time Domain Measures Determine heart rate at any point

in time.

- IBI: intervals between successive normal complexes

on ECG

- N-N intervals: normal-to-normal intervals

69

Frequency Domain Measures

Estimate the distribution of power

as a function of frequency, where

power is the variance within a

frequency band.

Spectral components obtained with short-term HRV

recordings:

- Very low frequency (VLF)

- Low frequency (LF):

§ related to parasympathetic activity

§ at rest, reflects baroreflex activity

§ can be produced during slow respiration

through vagus influences

- High frequency (HF):

§ Reflects parasympathetic activity

§ Corresponds to RSA

Component obtained with long-term HRV recordings:

- Ultra-low frequency (ULF)

Note. HRV = Heart Rate Variability. IBI = interbeat intervals. ECG = electrocardiogram. RSA = respiratory sinus arrhythmia.

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Table 2

Baseline Demographics

All Control Group Breathing Group Test

N 80 40 40

Age (mean(sd)) 21.09 (2.86) 21.4 (.46) 20.78 (.45) t(78) = .98, p = .33

Gender (female) 53 (66.3%) 28 (70%) 25 (62.5%) c2(1) = .50, p = .63

Ethnicity

White/Caucasian 15 (18.8%) 7 (17.5%) 8 (20%)

c2(4) = 1.76

p = .78

Black or African

American

12 (15%) 6 (15%) 6 (15%)

Hispanic/Latino(a) 21 (26.3%) 11 (27.5%) 10 (25%)

Asian 25 (31.3%) 11 (27.5%) 14 (35%)

Mixed 7 (8.8%) 5 (12.5) 2 (5%)

Bilingual (yes) 54 (67.5%) 24 (60%) 30 (75%) c2(1) = 2.05, p = .23

Exercise (yes) 39 (48.8%) 18 (45%) 21 (52.5%) c2(1) = .45, p = .66

COVID-19 positive – self 1 (1.3%) 0 1 (2.5%)

COVID-19 positive – other 32 (40%) 19 (47.5%) 13 (32.5%) c2(1) = 1.88, p = .25

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Table 3

Baseline Pearson’s Correlations of Psychological Outcome Variables and COVID-19 Self-Report

Variable BAI

STAI –

State BDI

Motivation –

school a

Ability –

school a

Ability –

work/job a Psychological a Financial a Social a Physical a

PSS .35** .42*** .5*** .64*** .22 .46*** .47*** .05 .05 .26*

BAI .64*** .62*** -.05 .06 -.06 -.05 .02 -.08 -.09

STAI – State .74*** .07 .17 -.08 .13 .03 -.07 .13

BDI .1 .11 -.01 .13 .27* .02 .09

Motivation – school a .64*** .46*** .63*** .25* .24* .32**

Ability – school a .46*** .47*** .15 .21 .26*

Ability – work/job a .42*** .25* .3* .39**

Psychological a .23* .39*** .49***

Financial a .16 .22

Social a .36***

Note. PSS = Perceived Stress Scale. BAI = Beck Anxiety Inventory. STAI State = State Trait Anxiety Inventory – State Anxiety. BDI = Beck Depression

Inventory.

a These variables refer to participants’ perceived impact of the COVID-19 pandemic on the noted areas.

* <.05. ** < .01. *** <.001

72

Table 4

Mean (SD) of Self-Report Measures by Group by Time

Baseline Post-training

PSS

Control Group 23.3 (5.19) 19.81 (4.56)

Breathing Group 21.7 (4.86) 17.97 (4.94)

All Groups 22.5 (5.06) 18.94 (4.8)

STAI – State Anxiety

Control Group 43.5 (11.33) 42.19 (12.2)

Breathing Group 45.65 (11.08) 41 (10.18)

All Groups 44.58 (11.19) 41.63 (11.23)

BDI

Control Group 16.88 (9.37) 13.95 (9.22)

Breathing Group 16.75 (11.89) 11.15 (9.21)

All Groups 16.81 (10.64) 12.63 (9.25)

BAI

Control Group 11.78 (9.77) 9.16 (9.02)

Breathing Group 10.48 (9.18) 8.52 (10.15)

All Groups 11.13 (9.44) 8.86 (9.5)

Note. PSS = Perceived Stress Scale. STAI State = State Trait Anxiety Inventory – State

Anxiety. BDI = Beck Depression Inventory. BAI = Beck Anxiety Inventory.

73

Table 5

Mean (SD) of Self-Report Measures by Gender by Time

Baseline Post-training

PSS Females 24.02 (4.72) 19.59 (4.2)

Males 19.52 (4.41) 17.71 (4.8)

STAI – State Anxiety Females 46.38 (10.97) 42.93 (11.92)

Males 41.04 (10.96) 39.13 (9.5)

BDI Females 18.7 (10.65) 13.78 (9.38)

Males 13.11 (9.78) 10.42 (8.77)

BAI Females 11.75 (9.18) 9.59 (9.39)

Males 9.89 (10) 7.46 (9.77)

Note. PSS = Perceived Stress Scale. STAI State = State Trait Anxiety Inventory – State

Anxiety. BDI = Beck Depression Inventory. BAI = Beck Anxiety Inventory.

Table 6

Multilevel Linear Models Predicting Perceived Stress Scale (PSS)

b SE b 95% CI

Time a -3.52 1.03 -5.54, -1.5

Group b 1.61 1.09 -3.75, 0.54

Time x Group c -0.19 1.48 -3.1, 2.72

Note. Outcome variable was the Perceived Stress Scale (PSS).

a c2 (5) = -450.08, p < .001.

b c2 (6) = -448.14, p = .05.

74

c c2 (7) =-448.13, p = .9.

Table 7

Multilevel Linear Models Predicting STAI State Anxiety

b SE b 95% CI

Time a -1.20 1.83 -4.81, 2.41

Group b 2.27 2.5 -2.64, 7.18

Time x Group c -4.09 2.63 -9.27, 1.1

Note. Outcome variable was State Anxiety on the State Trait Anxiety

Inventory (STAI). Random intercept model: c2 (1) = -551.79, p < .001.

a c2 (1) = -564.37, p = .02.

b c2 (1) = -564.35, p = .84.

c c2 (1) = -563.15, p = .12.

Table 8

Multilevel Linear Models Predicting Beck Depression Inventory (BDI)

b SE b 95% CI

Time a -3.04 1.54 -6.08, 0.004

Group b 0.02 2.23 -4.35, 4.4

Time x Group c -3.15 2.22 -7.52, 1.22

Note. Outcome variable was the Beck Depression Inventory (BDI).

Random intercept model: c2 (1) = -551.79, p < .001.

75

a c2 (1) = -544.41, p = .0001.

b c2 (1) = -544.16, p = .48.

c c2 (1) = -543.15, p = .15.

Table 9

Multilevel Linear Models Predicting Beck Anxiety Inventory (BAI)

b SE b 95% CI

Time a -2.63 1.55 -5.67, 0.42

Group b -1.46 2.12 -5.62, 2.7

Time x Group c -.46 2.22 -3.91, 4.83

Note. Outcome variable was the Beck Anxiety Inventory (BAI).

Random intercept model: c2 (1) = -540.6, p < .001.

a c2 (5) = -538.31, p = .03.

b c2 (6) = -538.08, p = .5.

c c2 (7) = -538.05, p = .83.

76

Table 10

Multilevel Linear Models Predicting Psychological Impact of COVID-19

b SE b 95% CI

Time a -0.4 0.16 -0.53, 0.34

Group b -0.2 0.21 -0.39, 0.59

Time x Group c -0.65 0.32 -1.27, -0.02

Note. Outcome variable was the perceived impact of the COVID-19

pandemic on psychological wellbeing.

a c2 (5) = -227.99, p = .01.

b c2 (6) = -227.53, p = .34.

c c2 (7) = -225.43, p = .045.

77

Table 11

Mean (SD) of Self-Reported App Adherence/Tolerability by Week

Week 1 Week 2 Week 3 Week 4 Test

Breathing ease 2.58 (0.97) 2.97 (1.02) 3.23 (0.91) 3.27 (1.12) W1 vs W3: p = .002 a

W1 vs W4: p < .001 b

Distraction during

breathing 2.86 (0.96) 2.82 (1.04) 2.66 (1.11) 2.59 (1.01) W1 vs W4: p = .02 c

Correct frequency 4 (0.76) 3.79 (0.82) 3.8 (0.83) 3.76 (0.86) All comparisons ns

Stress decline after

breathing 3.69 (1.06) 3.48 (0.91) 3.51 (1.01) 3.43 (0.99) All comparisons ns

a b = 0.62, t(90) = 3.28, p = .002.

b b = 0.76, t(90) = 4.10, p < .001.

c b = -0.47, t(90) = -2.45, p = .02.

Table 12

Mean (SD) of Self-Reported Stress by Group by Week

Week 1 Week 2 Week 3 Week 4

Control Group 2.80 (1.08) 3.23 (1.17) 3.11 (1.35) 2.86 (1.21)

Breathing Group 2.67 (1.15) 2.76 (1.15) 2.26 (0.89) 2.27 (0.90)

78

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