Investigation of Possible Effects of a Lifestyle Product in a Double-blind Pre-Post-Between-Groups Study
Phase: NA
Conditions: Healthy Lifestyle
Sponsor: Waveguard GmbH

 
 
 
Statistical Analysis Plan (SAP) 
 
 
English Title of the Study: Investigation of Possible Effects of a Lifestyle Product in 
a Double-blind Pre- Post-Between-Groups Study 
 
German Title of the Study: Untersuchung möglicher Effekte eines Lifestyle-Produktes 
und Zusammenhänge von Persönlichkeits- und Intelligenzfaktoren mit paranormalen 
Überzeugungen in einer doppel-blinden Pre-Post-Between-Groups Studie 
 
 
 
 
 
 
 
 
 
 
NCT number 
 
 
not available 
Date 
 
 
 
20.09.2020, Stuttgart 
 
Principal Investigator 
 
Katharina Lingelbach, MSc 
 
 
 
 
University of Stuttgart and Fraunhofer IAO  
 
 
 
 
Stuttgart, Germany 
 
ClinicalTrials.gov Protocol ID 
WAVEGUARD STRESS HUMANS FR01 
Author   
 
 
Katharina Lingelbach, MSc 
Version  
 
 
Draft 0.0 
 
 
 

 
 
SIGNATURE PAGE 
 
 
 
Principal Investigator and Author  
 
 
 
 
 
 
 
 
 
 
 
Katharina Lingelbach (2020-09-02) 
 
 
 
 

 
 
Abbreviations 
 
EDA 
 
Electrodermal Activity 
EEG  
 
Electroenzephalography 
ECG 
 
Elecrocardiography 
FAA 
 
Frontal Alpha Asymmetry 
WHO   
World-Health-Organisation 
EHS 
 
Electromagnetische hypersensibility  
HRV 
 
Heart rate variability 
HF 
 
High Frequency 
LF 
 
Low Frequency 
EO  
 
Eyes open 
EC  
 
Eyes closed 
PSQI 
 
Pittsburgh Sleep Quality Index 
WMT-2 Vienna Matrices-Test –2 
PANAS  Positive and Negative Affect Schedule 
 
 
 
 

 
 
Table of content 
Table of content........................................................................................................................................ 4 
1. 
Introduction ...................................................................................................................................... 5 
2. 
Study design ..................................................................................................................................... 5 
2.1 Sample size calculation .................................................................................................................... 5 
3. 
Aims and objectives .......................................................................................................................... 5 
4. 
Outcome Measures ........................................................................................................................... 5 
4.1       Primary Outcome Measure ............................................................................................................ 6 
4.2 
Secondary Outcomes .................................................................................................................... 7 
5. 
Analyses ............................................................................................................................................ 8 
6. 
Missing data ..................................................................................................................................... 8 
 
 
 

 
 
1. Introduction 
The aim of the study is to investigate possible effects of the lifestyle product "Qi-Shield" on a subjective 
and (neuro-)physiological level.  
This statistical analysis plan (SAP) will give more detailed descriptions of the endpoints in the study and the 
corresponding analyses. 
 
2. Study design 
Participants will be recruited through the participant pool of the research institute and received a 
monetary reward to compensate for time and travel costs. The study is a double-blind pre-post-between-
groups design with an exposure time of 7 days between the two sessions. 90 test persons are to be 
assigned to the three groups. Two groups receive an intervention with (A) the real product (active 
treatment arm) and (B) a sham product without effectiveness representing the placebo treatment arm. A 
third group receives no intervention as a further control (no treatment arm). Regarding the effects of the 
product, we are particularly interested in effects on well-being, stress perception and the sleep quality as 
well as influencing factors like personality and beliefs. We will use established questionnaires and scales as 
well as (neuro-)physiological methods comprising electroencephalography (EEG), electrocardiogram (ECG) 
and skin conductance level measure (electrodermal activity, EDA) during a 20 mins resting state measure 
with alternating eyes open and closed.  During the exposure time, participants are asked to rate their 
subjective well-being and stress on a daily basis via an online survey.  
 
2.1 Sample size calculation 
For the calculation of the Falling Number, a power analysis with the software G*Power (Faul, Erdfelder, 
Lang, & Buchner, 2007) was calculated for an analysis of variance with measurement repetition and 
between-subject factor assuming a normal distribution. With a small to medium effect (Cohen's d = 0.35), 
an alpha level of 0.05 (Bortz & Döring, 2006; Eid, 2010), a statistical power of 80% and an assumed 
strong correlation between measurements (r=0.8), the resulting case number is N=90. For both 
neurophysiological and subjective responses, the 3 groups with n=30 each are statistically compared. 
 
3. Aims and objectives 
To study the effects of the product, we investigate neuro- and peripheral physiological correlates during 
rest as well as subjective measurements regarding subjective well-being, perceived stress and resilience, 
positive and negative emotional states and sleep quality. 
4. Outcome Measures 

 
 
This section will present the outcomes investigated to answer the study aims and objectives. The analyses 
are described in section 6 Analyses. 
4.1 Primary Outcome Measure 
Adapted Pittsburgh Sleep Quality Index (PSQI), Buysse et al. (1989) 
Hypothesis Sleep Quality: Lower values in the post - pre session delta for the real device group compared 
to the sham device group and no intervention group. 
WHO-5, WHO, Psychiatric Research Unit 
Hypothesis Subjective well-being: Higher values in the post - pre session delta for the real device group 
compared to the sham device group and no intervention group. 
State Trait Anxiety Inventory (Laux, Glanzmann, Schaffner & Spielberger (1981) 
Hypothesis STAI: Lower values in the post - pre session delta for the real device group compared to the 
sham device group and no intervention group. 
Positive and Negative Affect Schedule, PANAS, Breyer & Bluemke (2016) 
Hypothesis PANAS: Higher values in the post - pre session delta for positive adjectives and lower values in 
the post - pre session delta for negative adjectives in the real device group compared to the sham device 
group and no intervention group. 
Adapted Perceived Stress Scale, Schneider, Schönfelder, Domke-Wolf & Wessa (2020) 
Hypothesis Perceived Stress: Lower values in the post - pre session delta for the real device group 
compared to the sham device group and no intervention group. 
Brief Resilience Scale, Chmitorz et al (2018) 
Hypothesis Resilience: Higher values in the post - pre session delta for the real device group compared to 
the sham device group and no intervention group. 
EEG Alpha band power and connectivity 
Hypothesis: Higher alpha band power and functional connectivity for the delta between pre- and post-
session in the real device group compared to the sham device group and no intervention group. 
EEG Beta band power and connectivity 
Hypothesis: Higher beta band power and functional global connectivity for the delta between pre- and 
post-session in the real device group compared to the sham device group and no intervention group 
EEG: Frontal alpha band asymmetry (right side activity) 
Hypothesis: Lower right side alpha band power for the delta between pre- and post-session in the real 
device group compared to the sham device group and no intervention group. 
EEG: Frontal theta/beta band ratio 
Hypothesis: Higher frontal theta/beta band ratio for the delta between pre- and post-session in the real 
device group compared to the sham device group and no intervention group 
EDA: number of individual phasic responses and summed amplitude of phasic responses 
Hypothesis: Lower number of individual phasic responses and summed amplitude of phasic responses for 
the delta between pre- and post-session in the real device group compared to the sham device group and 
no intervention group. 
ECG: Low frequency response in the heart rate variability 

 
 
Hypothesis: Less low frequency responses in the heart rate variability for the delta between pre- and post-
session in the real device group compared to the sham device group and no intervention group. 
ECG: High frequency response in the heart rate variability 
Hypothesis: Increased high frequency responses in the heart rate variability for the delta between pre- and 
post-session in the real device group compared to the sham device group and no intervention group. 
ECG: Standard deviation of normal-to-normal intervals (SDNN) and heart rate 
Hypothesis: Increased standard deviation of normal-to-normal intervals (SDNN) and heart rate for the delta 
between pre- and post-session in the real device group compared to the sham device group and no 
intervention group. 
Satisfaction with Life Scale, Janke & Glöckner-Rist (2012) 
Hypothesis Life satisfaction: Higher values in the post - pre session delta for the real device group 
compared to the sham device group and no intervention group.  
4.2 Secondary Outcomes 
Complementary and Alternative Medicine (CAM) Health Belief Questionnaire, Lie & Boker, 2004 
Explorative Hypothesis: Higher values for participants exhibiting a placebo effect of the intervention. 
Values of the CAMHBQ are positively correlated with values in the Revised Paranomal Belief Scale and 
Adapted Paranormal Experience Scale and negatively correlated with responses in the Vienna matrix test. 
The Complementary and Alternative Medicine (CAM) Health Belief Questionnaire provides a control 
measurement for the comparability of the groups. 
Adapted Paranormal Experience Scale, Aubeck, 1989 
Explorative Hypothesis: Higher values for participants exhibiting a placebo effect of the intervention. 
Values of the Adapted Paranormal Experience Scale are positively correlated with values in the Revised 
Paranomal Belief Scale and Complementary and Alternative Medicine (CAM) Health Belief Questionnaire 
and negatively correlated with responses in the Vienna matrix test. The Adapted Paranormal Experience 
Scale provides a control measurement for the comparability of the groups. 
Revised Paranomal Belief Scale, Tobacyk, 2004 
Explorative Hypothesis: Higher values for participants exhibiting a placebo effect of the intervention. It is 
positively correlated with values in the Adapted Paranormal Experience Scale and Complementary and 
Alternative Medicine (CAM) Health Belief Questionnaire and negatively correlated with responses in the 
Vienna matrix test. The Revised Paranomal Belief Scale provides a control measurement for the 
comparability of the groups. 
Vienna matrix test -2, Formann, Waldherr & Piswanger, 2011 
Explorative Hypothesis: Higher values are negatively correlated with the paranormal belief scale and 
openness for paranormal and alternatives beliefs and experiences. The Vienna matrix test provides a 
control measurement for the comparability of the groups. 
Short version of the Big 5 Inventory, Rammstedt & John, 2005 
Explorative Hypothesis: Higher values in the factor openness to new experience are positively correlated 
with the paranormal belief scale and openness for paranormal and alternatives beliefs and experiences 
and negatively correlated with the Vienna matrix test. The short version of the Big 5 provides a control 
measurement for the comparability of the groups. 
Karolinska Sleepiness Scale, Akerstedt & Gillberg, 1990 
The KSS provides a control measure before the 20 min resting state recording. Participants revealing 
values > 8 will be excluded from the analysis. 

 
 
5. Analyses 
All outcomes will be presented using descriptive statistics; normally distributed data by the mean and 
standard deviation (SD) and skewed distributions by the median and interquartile range (IQR). Binary and 
categorical variables will be presented using counts and percentages. All data analyses will be performed 
with custom written or adapted scripts in pythonTM, JASP 0.13.1 (JASP, 2020) and IBM® SPSS® Statistics 
20.   
For the estimation of the power spectral density (PSD), we will apply fast fourier transformation (FFT) to 
the EEG resting state data. To reduce the variability of the spectral estimates a Welch’s method will be 
applied. For the statistical analysis the PSD data will be transformed to a dB scale. Since PSD of the scalp 
EEG can vary between different participants due to several factors (anatomical, age and gender 
characteristics) the data will be further normalized (z-score) before the statistical comparisons can be 
done. Furthermore, we will explore whether spectral smoothing, according to a multi-tapering approach, 
of the PSD data has any influence on the statistical outcome.  
To estimate functional connectivity (deviations from statistical independence between EEG time series) of 
the resting state EEG data we will explore several methods which are insensitive to volume conduction 
properties. The estimation will be done in the frequency domain (using fft and multi-tapering, see above). 
Here, several methods have been established to distinguish true physiological neuronal interactions from 
volume conduction effects. In our study, we will compare the 3 most dominant methods reported in the 
cognitive neuroscience literature, which are: the imaginary part of the coherence function (iCOH), Nolte et 
al. 2004 and it’s corrected version as suggested by Ewald et al. (2012), corrected version of the iCOH 
function (ciCOH), the Phase-Locking Value (PLV), Lachaux et al. (1999) and it’s corrected version as 
suggested by Bruña et al. (2018) corrected imaginary PLV (icPLV), and the Phase Lag Index (PLI), Stam et 
al. (2007) and it’s corrected version as suggested by Vinck et al. (2011) Weighted Phase Lag Index (WPLI).  
From the resting ECG measurements we will calculate heart rate variability (HRV) measures. First, the ECG 
is processed to acquire the inter-beat interval (IBI –the inverse of heart rate). For this purpose, the ECG is 
band-pass filtered between 5 and 15 Hz. Next, R-Peaks are detected following Pan and Tompkins method.  
Next, the IBI semi-time series is transformed into a time series. This is done by interpolating (quadratic 
spline interpolation) consecutive IBIs and then resampling the data to a particular sampling frequency. In 
this way, the IBI is transformed to heart rate (indicated heart beats per min) and can be used for further 
statistical analysis. From the heart time series, we will extract several statistical measures for the group 
statistical comparisons such as: the max, min and mean of the Amplitude, the skewnees, kurtosis, and std 
of the data, and the RMSSD (square root of the mean of the sum of successive differences between 
adjacent RR intervals); SDNN (standard deviation of the RR intervals); MeanNN (mean of the RR intervals); 
SDSD (standard deviation of the successive differences between RR intervals). We will furthermore 
characterize the heart rate variability in the frequency domain using fft. Here, low frequency band (0.04-
0.15Hz), high frequency band (0.15-0.4Hz) and the ratio of the two will be compared.  
For the analysis of the measured EDA resting state signal, the data will be decomposed into smaller phasic 
responses (individual rapid spontaneous responses – usually related to certain stimuli) and tonic 
components (longer lasting basic skin resistance level). From these two components several physiological 
measures will be extracted for the group statistical comparison such as: the number of individual phasic 
responses, summed amplitude of phasic responses; minimum, maximum and average of phasic responses; 
integral of phasic responses; tonic state of electrical conductivity.  
For all the calculated (neuro-)physiological measures of the resting state we will do the statistical 
comparison among the groups. In particular, we will use the delta of the outcomes off the pre- and 
postsession for the neurophysiological and subjective measurements. Either parametric or non-parametric 
statistical tests depending on the violation of the assumptions (i.e., normal-distribution of the dependent 
factor examined by the Shapiro-Wilk test) are used. P-values are corrected for multiple comparisons using 
the false discovery rate (FDR) with the Benjamini-Hochberg method. 
6. Missing data  
Participants with missing data are excluded for the respective outcome analysis. 

 
 
 
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