Cutting Edge HRV Training Stress Management and Biofeedback Services Counseling and Psychological Services CAPS Brigham Young University Faculty Training Maureen Rice Barbara Morrell Yoko Caldwell Meredith Pescatello Tristin Roney Louise Wheeler Lisa Leavitt ID: 779345
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Slide1
The Implications of CAPS Biofeedback Research on Treatment Strategies: Cutting Edge HRV Training
Stress Management and Biofeedback Services
Counseling and Psychological Services (CAPS)
Brigham Young University
Faculty Training
Maureen Rice, Barbara Morrell, Yoko Caldwell, Meredith Pescatello, Tristin Roney, Louise Wheeler, Lisa Leavitt,
Dianne Nielsen
Slide2www.themegallery.com
STUDY #1 – AAPBThe Efficacy of Stress Management and Biofeedback Training as an Adjunct to Psychotherapy for University StudentsMorrell, B., Nielsen, D., Rice, M., Erekson, D., Marvin, L., Brown, L.
Slide3OQ-45 Administered before every counseling sessionItems heavily loaded on stress and anxietyI tire quicklyI feel stressed at work/school.I feel fearfulI have difficulty concentrating.My heart pounds too much
I feel nervousI have trouble falling asleep or staying asleepI have headachesI have sore muscles
Slide4Therapy Outcome for CAPS Clients Receiving No Biofeedback, One session, and Multiple Sessions Significant differences were found between groups on total OQ-45 change from 2008 to 2012 (p = .018)
1 or less biofeedback sessions averaged 8 points of change2+ biofeedback sessions averaged 11 points of change
Slide5Additionally, a multilevel analysis of biofeedback and outcome on the OQ-45 from 1996 to 2012 found that the
total number of biofeedback sessions in a course of therapy predicted a faster decrease in OQ-45 scores (p = .005), controlling for initial severity on the OQ
Slide6www.themegallery.com
Study #2 – AAPBImpact of Resonant Frequency HRV Training in the Treatment of Depression and Resting-state fMRIYoko H. W. Caldwell
Brigham Young University
Dissertation
Slide7Depression & Brain Functioning
Structural & Functional dysfunctioning
Volume reduction – hippocampus & amygdala
(Drevets, 2001; Mervaala et al., 2000)
Decreased connectivity
Functional – prefrontal cortex & ACC
(Aizenstein et al., 2009)
Resting-state – ACC, hippocampus, amygdala, orbitofrontal & prefrontal cortex
(Anand et al., 2005; Lui et al., 2011)
Slide8MDD TxMeds
(Rush et al., 2006)Therapy(Butler, Chapman, Forman, & Beckm, 2006)
Adjunct Therapy
(Amr, El-Mogy, Shams, Vieira, & Lakhan, 2013; Tonhajzerova et al., 2009)
Slide9Heart-Rate Variability (HRV)
HRV & Health OutcomeSympathetic Parasympathetic activity (Beevers, Ellis, & Reid, 2011)Associated with positive health outcome
Cardiac morbidity
(Del Pozo et al., 2004)
Pulmonary function
(Lehrer et al., 2003)
Chronic pain
(Hallman, Olsson, Scheele, Melin, & Lyskov, 2011)
Depressive disorders
(Karavidas et al., 2007)
Slide10The Current StudyPurposeExamine impact of HRV training on depressive symptoms and resting-state connectivity
ROIs: ACC, hippocampus & amygdala
Slide11MethodParticipantsExclusion: age <18 or > 25 yrs, Hx of major illness, cardiovascular dx, substance abuse
Females (N = 32) MDD participants: BYU Counseling CenterHealthy participants: BYU campus
Excluded 2 participants
Final sample size: n = 30
$20 – each MRI visit; $10 – each HRV visit
Slide12Participants (cont’)
Age M = 20.09 M = 20.20 M = 20.64 SD = 1.81 SD = 1.47 SD = 1.29
Both Tx & HRV
Tx only
Active control
Slide13MeasuresPsychologicalM.I.N.I International Neuropsychiatric Interview
(Sheehan et al., 1998)Beck Depression Inventory-II (BDI-II) (Beck, Steer, & Brown, 1996)Outcome Questionnaire-45 (OQ45) (Lambert, 1994)
Physiological for HRV
Biofeedback system (J&J)
Standard deviation of normal-to-normal intervals (SDNN)
High frequency (HF)
Low frequency (LF)
LF/HF ratio
Slide14Physiological variablesSDNN Amount of variability in heartbeat interval across timeHF and LF
LF/HF ratio
0.15
0.4
0.05
Slide15MRI ScannerBYU MRI RFSiemens 3T Tim Trio MR scannerFunctional imagesStructural images
Slide16ProcedureRecruitment phaseM.I.N.IExperimental phase
Slide17Capture the Moments
Slide18Analytic StrategyRepeated measure ANOVA3 (Exp, TAU, Ch) x 2 (Baseline, follow-up)BDI-IIOQ-45All HRV variables (SDNN, LF, HF, LF/HF)LF, HF, LF/HF
Log10 transformationResting-state connectivity between each ROIs
Slide19Results- Baseline
Group differenceF(2, 27) = 14.65; p = .000
BDI Cutoffs
0-13
Minimal
14-19
Mild
20-28
Moderate
29-63
Severe
Mild -Moderate
Minimal
Slide20Results
OQ45 Cutoffs
<63
NOT clinical
distress
>64
Clinical distress
>14 pts change
Reliable
change
Above clinical cut-off
Below clinical cut-off
Group difference
F
(2, 27) = 11.26;
p
= .000
Slide21ResultsImaging data – no significant differences across each ROIs (ACC, Hipp., Amyg.) at baseline
Exp
(M,SD)
TAU
(M,SD)
C
h
(M,SD)
p-value
L ACC – L Hipp
0.19
(0.19)
0.75
(1.53)
0.12
(0.15)
0.185
L ACC – L Amyg
0.16
(0.22)
0.66
(1.42)
0.07
(0.13)
0.227
L Hipp – L Amyg
0.31
(0.12)
0.82
(1.44)
0.35
(0.19)
0.306
R ACC – R Hipp
0.20
(0.16)
0.73
(1.57)
0.15
(0.12)
0.216
R ACC – R Amyg
0.10
(0.16)
0.68
(1.44)
0.09
(0.09)
0.174
R Hipp – R Amyg
0.31
(0.07)
0.83
(1.38)
0.43
(0.16)
0.222
L ACC – R ACC
0.65
(0.15)
1.11
(1.55)
0.47
(0.15)
0.312
L Amyg – R Amyg
0.30
(0.13)
0.79
(1.41)
0.35
(0.12)
0.311
L Hipp – R Hipp
0.56
(0.13)
0.95
(1.62)
0.56
(0.13)
0.332
L ACC – R Hipp
0.15
(0.18)
0.69
(1.56)
0.13
(0.13)
0.225
L ACC – R Amyg
0.06
(0.14)
0.58
(1.47)
0.09
(0.11)
0.284
L Hipp – R ACC
0.20
(0.21)
0.77
(1.56)
0.16
(0.12)
0.190
L Hipp – R Amyg
0.25
(0.14)
0.76
(1.44)
0.29
(0.15)
0.244
L Amyg – R ACC
0.17
(0.19)
0.72
(1.42)
0.11
(0.08)
0.181
L Amyg – R Hipp
0.37
(0.10)
0.77
(1.43)
0.32
(0.13)
0.327
Slide22Results - Follow-up
BDI Cutoffs
0-13
Minimal
14-19
Mild
20-28
Moderate
29-63
Severe
Exp: A significant decrease from moderate to minimal level
Post-hoc Tukey:
M
baseline = 24.9;
M
follow-up = 12.00;
p
-value = .0003
TAU: A shift from mild to minimal level
Post-hoc Tukey:
M
baseline = 17.7;
M
follow-up = 12.10;
p
-value = .23
Ch: Stayed at the minimal level
Post-hoc Tukey:
M
baseline = 3.70;
M
follow-up = 2.50;
p
-value = .99
Slide23Results- Follow-up
OQ45 Cutoffs
<63
NOT clinical
distress
>64
Clinical distress
>14 pts change
Reliable
change
Exp: From above to below clinical cut-off (25 pts )
Post-hoc Tukey:
M
baseline = 84.20;
M
follow-up = 59.00
p
-value = .0002
TAU: Stayed above the clinical cut-off
Post-hoc Tukey:
M
baseline = 71.10;
M
follow-up = 63.20
p
-value = .61
Ch: Stayed below the clinical cut-off
Post-hoc Tukey:
M
baseline = 32.50;
M
follow-up = 33.60
p
-value = .99
Slide24Results- Follow-up
Exp: A significant increase (17.39 pts)
Post-hoc Tukey:
M
baseline = 42.93;
M
follow-up = 60.33;
p
-value = .002
Ch: No significant change
Post-hoc Tukey:
M
baseline = 56.74;
M
follow-up = 56.32;
p
-value = .99
TAU: No significant change
Post-hoc Tukey:
M
baseline = 50.01;
M
follow-up = 48.51;
p
-value = .99
Slide25Results- Follow-up
Exp: A significant increase
Post-hoc Tukey:
M
baseline = 2.74;
M
follow-up = 3.22;
p
-value = .009
TAU: No significant change
Post-hoc Tukey:
M
baseline = 2.97;
M
follow-up = 2.92;
p
-value = .99
Ch: No significant change
Post-hoc Tukey:
M
baseline = 3.15;
M
follow-up = 3.21;
p
-value = .99
Slide26Results- Follow-up
Exp: A significant increase
Post-hoc Tukey:
M
baseline = 1.08;
M
follow-up = 1.29;
p
-value = .01
TAU: No significant change
Post-hoc Tukey:
M
baseline = 1.00;
M
follow-up = 1.03;
p
-value = .99
Ch: No significant change
Post-hoc Tukey:
M
baseline = 1.07;
M
follow-up = 1.15;
p
-value = .70
Slide27Results- Follow-upImaging data - no significant differences across each ROIs (ACC, Hipp., Amyg.) between the two time points
Variables
df
MS
F
p
partial η2
L ACC – L Hipp
Time*Groups
2
0.03
0.03
0.973
0.00
L ACC – L Amyg
Time*Groups
2
0.02
0.02
0.980
0.00
L Hipp – L Amyg
Time*Groups
2
0.01
0.01
0.990
0.00
R ACC – R Hipp
Time*Groups
2
0.02
0.02
0.984
0.00
R ACC – R Amyg
Time*Groups
2
0.01
0.01
0.987
0.00
R Hipp – R Amyg
Time*Groups
2
0.08
0.07
0.933
0.00
L ACC – R ACC
Time*Groups
2
0.17
0.15
0.864
0.01
L Hipp – R Hipp
Time*Groups
2
0.11
0.08
0.921
0.00
L Amyg – R Amyg
Time*Groups
2
0.01
0.01
0.993
0.00
L ACC – R Hipp
Time*Groups
2
0.01
0.01
0.990
0.00
L ACC – R Amyg
Time*Groups
2
0.00
0.00
1.000
0.00
L Hipp – R ACC
Time*Groups
2
0.04
0.03
0.967
0.00
L Hipp – R Amyg
Time*Groups
2
0.03
0.03
0.974
0.00
L Amyg – R ACC
Time*Groups
2
0.02
0.02
1.000
0.00
L Amyg – R Hipp
Time*Groups
2
0.03
0.03
1.000
0.00
Slide28Discussion
Main findingsExp: significant decreases in total OQ45 score (25 pts) and total BDI-II score (moderate to minimal level) between the two time pointsExp: significant increases in SDNN (17.39 pts), LF, LF/HF between the two points
Imaging data – no significant difference between groups across the two time points
Gender
Age
# of depression episodes/depression duration
Slide29Limitations and Future DirectionsA very selected populationLongitudinal studyMaleNo active experimental condition in the control group
Comparing different psychotherapy approachesLong-term effect
Slide30ConclusionPilot study3 comparison groupsResults only partially followed predictionsThe need for additional studies on HRV biofeedback training at different stages of depression and how it might affect participants’ neurologically.
Slide31ReferencesAizenstein, H. J., Butters, M. A., Wu, M., Mazurkewicz, L. M., Stenger, V. A.,
Gianaros, P. J., … Carter, C. S. (2009). Altered functioning of the executive control circuit in late-life depression: Episodic and persistent phenomena. The American journal of Geriatric Psychiatry, 17, I30-42. Amr, M., El-Mogy, A., Shams, T., Vieira, K., & Lakhan, S. E. (2013). Efficacy of vitamin C as an adjunct to fluoxetine therapy in pediatric major depressive disorder: a randomized, double-blind, placebo-controlled pilot study. Nutrition Journal, 12, 1-8. Anand
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, C. G., Ellis, A. J., & Reid, R. M. (2011). Heart rate variability predicts cognitive reactivity to sad mood provocation.
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Butler, A. C. B., Chapman, J. E., Forman, E. M.,
Beckm
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Del
Pozo
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Gevirtz
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Slide32www.themegallery.com
STUDY #3 Heart Rate Variability: Biofeedback's Effect on Symptoms of Clients with Generalized Anxiety DisorderTristin Roney, Meredith Pescatello
Brigham Young University
Dissertation
Slide33The StudyPurpose: To determine if Heart Rate Variability (HRVB) is an effective treatment for GAD 60 participants with a diagnosis of GAD Prevalence of GAD in the US ~ 2-5%CAPS clients identifying anxiety as their top concern ~20% (Winter 2016)
Heart Rate Variability: the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.Measure of adaptability to stressLinked to several measures of health
Slide34The Process 6 week protocolMaximize Heart Rate VariabilityDiaphragmatic Breathing Resonance Frequency Breathing Rate
Synchronization of breathing and heart rate
Slide35How It Works
Slide36Preliminary Results First OQTAU: 87.08HRVB: 81.90Last OQTAU: 73.39
HRVB: 56.55Mean Change TAU: -13.69 (SD=13.29)HRVB: -24.35 (SD=18.73) Total: -20.76 (SD=17.55)HRVB—treatment groupTAU—treatment as usual
Slide37Moving Forward…Protocol consistency Lots of positive feedback from participantsMost of our participants are female Still need 10-20 more participants (especially TAU)
The importance of homework! Rationale Practice makes perfect Lasting effects?
Slide38www.themegallery.com
STUDY #4 AAPBStress Physiology and Psychotherapy:Implementation of an HRV Biofeedback Intervention to Improve Outcome in PsychotherapyAndrea De Barros, Tara Austin, Louise WheelerDoctoral Students
Slide39Previous Study ResultsParticipants reporting higher levels of distress (OQ > 62) had a more elevated physiological stress response and a longer physiological recovery after exposure to a stressor.
Stress reduction strategies may be a useful adjunct for those in psychotherapy ○ Particularly important for high distress groups
Slide40GOAL & HYPOTHESES
GOAL: Assess if a HRV biofeedback intervention can help improve the psychotherapy outcome of patients with increased stress reactivityHYPOTHESES:
1. Biofeedback participants will show a significant drop in OQ
scores over time
2. Biofeedback participants will show a significantly more
elevated stress physiology at baseline
3. Biofeedback participants will show less stress physiology
at 6-week follow-up
Slide41PARTICIPANTS
College students attending psychotherapy at university counseling center ○ Early treatment (first or second session) ○ Agreed on being contacted about research ○ Ages 18 to 30
Randomly assigned to groups
Slide42MAIN MEASURES
Trier Social Stress Test (TSST) ○ Two stress inducing tasks ○ Gold standardOQ-45
Slide43BIOFEEDBACK INTERVENTIONSession 1: Pre-measure of stress physiology and introduction of HRV training
○ TSST ○ Introduction of diaphragmatic breathing Session 2: Introduction of optimal rate of breathing Session 3-5: Practice of breathing at optimal rateSession 6: post-measure of stress physiology
○ TSST
Based on evidence-based protocol
(Lehrer, 2007)
Homework assignment and adherence
Slide44CONTROL CONDITION Session 1: Pre-measure of stress physiology
○ TSST Session 2-5: passive relaxationSession 6: post-measure of stress physiology
○ TSST
Slide45PRELIMINARY RESULTSHypothesis 1: Biofeedback participants will show a significant drop in OQ scores over time
Slide46RESULTS Hypothesis 2:
Biofeedback participants will show a significantly more elevated stress physiology at baseline ○ Treatment group has lower SDNN, RMSSD, and HFHypothesis 3:
Biofeedback participants will show less stress physiology
at 6-week follow-up
○ Unclear because of low N but appears promising
Slide47www.themegallery.com
STUDY #5 A Study to Determine the Efficacy of Integrating Heart Rate Variability Feedback with Psychotherapy TAULeavitt, L., Rice, M., Morrell, B.
Slide48Qualitative study looking at the impact of HRV used in session with clientsIt is a simple process:Become trained on the use of emWave and have it installed on your computer - takes about 20 minutes.It starts in one of two waysThe client approaches you and asks about it (fliers and posters at the front desk)
If you believe it would help the client you can suggest it to them as their therapistwww.themegallery.com
Slide49You administer the emwave HRV in session with the client, at least once.It typically takes up about 10-15 minutes of the session time, less once you have done it a few times.Once you have done one session you put the consent form in Lisa’s box with the client contact information on it.The client has a short interview about their experience and gets $15.00You have a short interview about your experience – unfortunately no $15.00 for us, we just get the satisfaction of knowing we helped out our client and a colleague!.Voila!! You are done!
www.themegallery.com
Slide50Biofeedback Integral Part of the CAPS for 40 Years
Adjunct to therapy General stress management Referrals from physicians
Class Assignments
Increasing Demand for Services – Our Role
Most students come to 1-2 biofeedback sessions
Many psychotherapy clients tend to come for multiple sessions – individual or open hours
Provide training so students learn skills they can practice at home – breathing strategies – cutting edge treatment
Slide51HRV – Heart Rate Variability BreathingDecrease depression
(Karavidas, et al, 2007)Decrease stress (Palomba, et al, 2011)
Improve cardiovascular functioning
(Del Pozo, Gevirtz, Scher, & Guarneri, 2004)
H/O on Breathing and Apps, Stress Cards
Stress the value of Breathing and the positive effects of HRV Breathing Training
Slide52Paced Breathing Resources Stress CardsBreathing H/OEZ-Air PacerSmart Phone Apps
My Calm Beat Breathe2RelaxAzumio Stress DoctorInner BalanceSleep TimeSleepytimeSleepcycles Websitescalm.comasoftmurmur.comStopbreathethink.org
Slide53What is and Why Teach and Train HRV Breathing For Autonomic Balance?Breathing is the fastest and most effective way to
calm down, reduce anxiety, attain peak performanceEmWave measures Heart Rate and Heart Rhythms Trains Autonomic Balance - balance between stress (sympathetic NS) and feeling calm (parasympathetic NS)
With slow diaphragmatic breathing HRV increases as the heart rate speeds up with inhalation and slows down with exhalation
Slide54Biofeedback HRV Training Results
Develops Sensory Awareness of tension/anxiety vs. relaxation/calmnessAids in the Learning Process of releasing tension and stressConditions the Relaxation Response to be easy and more automatic
This results in
Greater instant calmness and mental clarity
Positive mental and emotional focus
Improved heart health over time
Peak Performance
in:
Academics
Music
Sports
Social Interactions
Slide55Customized emWave license through the Heart Math Educational Division: Software loaded on all computers of counselors Use limited to number of sensorsAdvantagesIntegrate biofeedback with therapy Biofeedback is more effective way to teach diaphragmatic breathing
Helpful with students in crisis: Immediate skills for calmingUniversity students enjoy biofeedbackAlso in Career and Academic Success Center for student useBiofeedback for All Clinicians
Slide56Start & Stop buttons
Various Displays
Heart Rate
Variability
Wave
Heart Rate
Scale
Breath
Pacer
Coherence
Ratio
Games and Activities
Saved Session Data
Average Heart Rate
Gray Arrow
Changes
Display
Sound on/off
emWave Main Screen
Slide57Summary of Counseling and Psychological Services Biofeedback: Faculty and Student Dissertation Research 1. The Efficacy of Stress Management and Biofeedback Training as an Adjunct to Psychotherapy for University Students (Morrell, B., Nielsen, D., Rice, M., Erekson, D., Marvin, L., Brown, L.)
2. The Impact of Resonant Frequency HRV Training in the Treatment of Depression and Resting State fMRI (Caldwell, Y., Dissertation) 3. HRV Biofeedback’s Effect on Symptoms of Clients with Generalized Anxiety Disorder (Roney, T., Pescatello, M., Dissertation) 4. Stress Physiology and Psychotherapy: Implementation of an HRV Biofeedback intervention to improve outcome in psychotherapy (Barros, A., Austin, T., Wheeler, L. – AAPB) 5. The Efficacy of Integrating Heart Rate Variability Feedback with Psychotherapy (Leavitt, L., Rice, M., Morrell, B.)
www.themegallery.com
Slide58Kelly
McGonigal,Ph.D
.
Make Stress Your
Friend
TED TALK
THANK YOU...