Available online at:
https://cc.arcabc.ca/islandora/object/cc%3Apsycjournal

J Camosun Psyc Res. (2022). Vol. 4(1), pp. 1-13.
Submitted Fall 2021; accepted June 2022.

The Biological Effects of Trauma.
Authors: Mya Roy*, Noah Thomas, and Pallavi Bhalla
Supervising Instructor: Michael Pollock, Psyc 215 (“Biological Psychology”)
Department of Psychology, Camosun College, 3100 Foul Bay Road, Victoria, BC, Canada V8P 5J2
*Corresponding author email: cambrianexpo@gmail.com

ABSTRACT
In this paper, we sought to understand the effects of trauma through a biological lens so that
we could better learn how all the different expressions of mental unwellness, as a result of
trauma, affect our everyday lives. Previous research has predicted that the symptomatic
consequences of trauma can be identified and affected by variables such as platelet serotonin
concentrations, substance addiction, and cortisol levels. For our correlational study, we tested the
strength of these relationships by examining naturalistic daily changes in their variables over a
one-week period. We measured substance addiction by how many alcoholic drinks were
consumed each day, inferred cortisol levels by levels of water retention of the wrist each day,
serotonin concentrations by rating tiredness each day using a subjective scale, and inferred
traumatic symptoms by heart rate each day. Data pooled across participants in our correlational
study showed that alcohol intake, but not serotonin or cortisol levels, was significantly correlated
with our physiological measurement of trauma levels. Though a minute finding, this information
may be able to offer guidance and aid to future psychologists and healthcare providers in both
the furthering of their research and in the betterment of treatment plans for those who have
undergone trauma. These findings could also motivate councillors and therapists to inaugurate
more resources for combatting addiction into their practices.
1. Introduction
1.1 Research Problem
The goal of this research paper was
rooted in a shared interest in traumatic
encounters as well as the strain they put on
the livelihoods of the people that experience
them, transitionally we also put focus on the
various ways one can learn to adapt to the
consequences of living through or being
affected by traumatic events. Post-traumatic
Stress Disorder affects a vast amount of
people internationally and can materialize as
a consequence of many different kinds of

situations. In part, this paper was intended to
shed light onto the ways this disorder, and
others similar to it, symptomize and how
such symptoms can be made more bearable.
Intergenerational trauma affects thousands
of people per year, particularly in minority
communities. A better understanding of the
underlying characteristics of trauma can help
individuals living with intergenerational
trauma and its direct effects. A wide range
of people are affected by trauma every day
and every year. Understanding the
symptoms and limitations of stress and
trauma can help individuals to overcome the
difficulties associated with trauma. Research
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on this topic is essential for those who have
undergone trauma since not only does this
information educate those who may be
unaware of the internal contrivances of
trauma, but it also aids in informing afflicted
people of what to expect in the wake of a
traumatic experience and how to deal with
their feelings in a healthy way moving
forward.
1.2 Literature Review
One biologically-based symptom
commonly associated with Post-traumatic
Stress Disorder is a fluctuation in platelet
serotonin concentrations within the body.
For example, in a correlational study
executed by Grah et al. (2010), forty-six
adults that had been diagnosed with Posttraumatic Stress Disorder and had underwent
a suicide attempt, forty-one adults diagnosed
with Post-traumatic Stress Disorder without
a known suicide attempt and fifty
phenotypical subjects had their blood drawn.
This occurred on the second day of a
patient's hospitalization, during standardized
laboratory procedures. Samples were later
tested for platelet serotonin concentrations
by the competitive enzyme immunoassay in
an enzyme-linked, immunosorbent assay
test-ELISA test. Upon examination
researchers found that, in subjects with Posttraumatic stress disorder, platelet serotonin
levels were much lower in those that had
attempted suicide. Further, regardless of
whether or not a diagnosed patient had
endured suicide attempt, both saw a
statistically significant decrease in serotonin
levels when compared to that of the average
amount. Based on these results, the
researchers concluded that platelet serotonin
concentrations, while known to be lessened
in those with Post-traumatic Stress Disorder,
may very well also have a biological effect

on the intensity of its suicidogenic
symptoms.
Another element previously suggested to
be associated with survivors of traumatic
events is lower cortisol levels. For example,
in a correlational study conducted by
Yehuda et al. (2007), twenty-three adults of
holocaust survivors with PTSD, and ten
without, were collated with a control group
of sixteen adults with no linkage to the
holocaust. Each participant included in the
study, had a catheter inserted. For a period
of 24 hours, blood samples were obtained
from each participant every thirty minutes.
To control for major postprandial cortisol
spikes, each participant received the same
low-calorie meal at 9am, 12pm, and 6 pm
respectively. Cortisol levels in plasma were
measured using radioimmunoassay kits.
Based on the data collected, researchers
found that the mean cortisol levels of those
with parental PTSD were comparatively
lower than offspring without parental PTSD,
and offspring without any connection to the
holocaust.
A third biological factor associated with
Post-Traumatic stress disorder is alcohol
consumption. For example, a study was
conducted on 250 adult college
undergraduate students from a large urban
university in the United States who were
active alcohol drinkers for the past three
months and had signs of PTSD by giving
them online surveys and assessed with a
modified version of the Daily Drinking
Questionnaire (Tripp et al., 2015). The study
examined six facets of emotion
dysregulation as mediators between PTSD
and alcohol intake by sex. Based on the data
collected it was found that higher intake of
alcohol leads to higher emotion
dysregulation and higher PTSD symptoms
and other mental health disorders. It was
also suggested that gender-specific
interventions targeting emotion
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dysregulation may be effective in reducing
alcohol-related consequences in individuals
with PTSD.
1.3 Hypotheses
Based on the above literature review, we
predicted the following hypotheses:
Hypothesis #1: If trauma increases then
serotonin levels will decrease.
Hypothesis #2: If trauma increases then
cortisol levels will decrease.
Hypothesis #3: If trauma increases then
substance abuse will increase.
2. Methods
2.1 Participants
The three authors of this paper served as
the participants in its studies. This included
one male and two females, ranging from 1921 years of age, with a calculated, average
age of 20.66 years. The participants were all
undergraduate students at Camosun College
who completed this study as a research
assignment for the course, PSYCH-215001B (Biological Psychology), and were
grouped together due to their mutual interest
in the biological effects of trauma. One
participant, being an indigenous person, had
a family history of trauma, with regards to
residential schools and their imposition on
their immediate, and remote family. One of
the female participants had been clinically
diagnosed with Post-traumatic Stress
Disorder two years prior to the conduction
of this study.
2.2 Materials and Procedure
We performed a correlational study to
test concurrently all of our hypotheses by
examining naturalistic daily changes in their
variables longitudinally. Each participant

kept a study journal with them at all times
over this study’s one-week period in order to
record self-observations of the following
four variables: (1) serotonin levels, (2)
cortisol levels, (3) addiction levels, and (4)
trauma.
2.2.1 Serotonin Levels
Due to the directly immeasurable nature
of serotonin concentration at this level of
research practice, quantitative levels of
serotonin throughout the body were
measured using a subjective scale of
tiredness. This was done, primarily, on
account of serotonin’s classification as a
‘sleepiness-causing’ neurotransmitter. All
three participants were asked to complete a
single, ‘level of tiredness’ questionnaire
during the evening hours of 6pm-9pm, every
day, over the span of one week. As was
previously stated, this questionnaire worked
as an ordinal scale in which participants
could choose a number from 1-7 as a way of
documenting their daily degrees of tiredness
(1 = Incredibly tired, 2 = Pretty tired, 3 = I
could use a cup of coffee, 4 = Reluctantly
awake, 5 = Awake, 6 = Wide awake, 7 = I
could run a marathon). This was done to
provide us with an incremental, sensitive
score that determined the correlation
between an unaltered lifestyle and platelet
serotonin concentrations. Let it also be
known that this scale is meant to be
interpreted inversely, whereby the higher
one’s tiredness score is, the less tired they
are.
2.2.2 Cortisol Levels
Due to our inability to measure cortisol
directly, another measure was used. Higher
cortisol levels have been found to be linked
with higher water retention levels, while
lower levels are associated with lower water
retention levels. Therefore, water retention
was used as an indicator variable for cortisol
levels. In order to measure water retention,
each person measured their wrist
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circumference between 8pm and 11pm each
day.
2.2.3 Substance Addiction
Considering the factor that emotion
dysregulation is associated with substance
addiction. This will be done keeping in mind
that substance addiction (alcohol intake) can
lead to change in mood and behaviour. All
the participants will be asked a question
regarding their alcohol consumption for the
day stating; how many drinks containing
alcohol do you have in a day? The
participants will be asked to answer a simple
question about how many drinks they have
had. This will indicate the level of mood
fluctuations with alcohol consumption. The
participants will be asked to note the amount
of drinks they have had between 6pm to
9pm each day for a whole week. This will be
done to determine the correlation between
alcohol consumption and PTSD.
2.2.4 Trauma
In order to quantitatively measure trauma,
our group elected to have participants record
their normal, resting heart rate every day
over the span of a week-long research
conduction period. Participants were
instructed to place two fingers on the apple
of their wrist every night between the hours
of 8pm-11pm for a total time of sixty
seconds. Afterwards, they recorded the
number of times they were able to count a
heartbeat during the, aforementioned, one
minute interval.
2.3 Planned Analyses
To assess the strength and statistical
significance of associations between
variables predicted by our three hypotheses,
we performed Pearson product moment
correlations of their predictor variables
(trauma) with their outcome variables
(serotonin, cortisol, and substance abuse).
For testing Hypothesis #1, we correlated

daily ‘degrees of tiredness’ with a
participant’s daily recorded heart rate. For
testing Hypothesis #2, we correlated water
retention in the wrist with heart rate. And for
testing Hypothesis #3, we correlated the
number of alcoholic drinks consumed by a
participant throughout the day with the
participant's heart rate. We performed all of
the above correlations separately for each
participant as well as using data pooled
across all of the participants. For the
correlations using pooled data, in addition to
using the raw data, we also performed
correlations after we had first transformed
the data from each participant into z-scores
in order to standardize differences in
averages and variability seen between the
participants in their data and thus make them
more comparable. A correlation coefficient
was considered statistically significant if the
probability of its random occurrence (p) was
< .05 (i.e., less than 5% of the time expected
by chance alone).
3. Results
As is shown in Table 1, alcohol intake
was significantly correlated with heart rate.
Using both pooled raw data (r = -.35, p =.12,
see Figure 1) and pooled standardized data
(r = .30, p = .19, see Figure 2), water
retention and heart rate were found to have a
weak correlation that failed to reach the cutoff for statistical significance. Likewise,
using both pooled raw data (r = -.40, p =.07,
see Figure 3) and pooled standardized data (r
= -.30, p = .18, see Figure 4), tiredness was
not significantly correlated with heart rate.
In contrast, using both pooled raw data (r =
.59, p = .004, see Figure 5) and pooled
standardized data (r = .50, p = .02, see
Figure 6), alcohol intake was found to have
a moderately significant correlation with
heart rate. Based on a comparison of the
correlation coefficients using both pooled
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raw data and pooled standardized data,
alcohol intake showed the strongest
correlation with heart rate.
4. Discussion
4.1 Summary of Results
Hypothesis #1, which suspected that if
trauma worsens then serotonin levels will
decrease, was not supported by the results in
a significant manner. Hypothesis #2, which
supposed that if trauma increases then
cortisol levels will decrease, was also not
supported by the results in a significant
manner. However, Hypothesis #3, which
hypothesized that if trauma increases then
substance abuse will increase, was supported
by the results.
4.2 Relation of Results to Past Research
The results of this correlational study do
not align with the conclusions made by Grah
et al. (2010), in their correlational study of
trauma and serotonin levels. A participant’s
‘level of tiredness’, which was meant to be
an indicator of serotonin concentrations, was
not significantly correlated with the same
participant’s heart rate, which was meant to
be an indicator of trauma levels. Meanwhile,
the results of Grah et al.'s (2010) study
supported the notion that a low
concentration of serotonin in the
bloodstream was correlated with the
worsening of symptoms of trauma. In
regards to our study, this contrast could be
attributable to a lot of factors, including,
though not exclusively, the inability of our
‘tiredness’ scale to accurately and
specifically measure platelet serotonin
concentrations. Our sample size was also
much smaller than that of the study done by
Grah et al. (2010), as we were only able to
collect data from three participants, whereas

their team had 137 subjects, in total, to
acquire testable blood samples from. This
could have contributed to a decline in the
statistical significance of the results
pertaining to this particular hypothesis.
Our correlational study failed to confirm
the relationship between trauma and cortisol
levels. Yehuda et al. (2007) found that
cortisol levels measured using
radioimmunoassay kits were lower in those
that had survived traumatic encounters than
those that had not. Conversely, cortisol
levels did not seem to be as strongly
correlated within our correlational study.
The difference in methodologies between
our study and Yehuda et al. (2007) may
account for the disparity in the results. The
most obvious difference in our methodology
was our measurement of cortisol levels. Due
to our inability to obtain radioimmunoassay
kits, we instead used the measurement of the
wrist as an indicator of cortisol levels. While
wrist measurement may be indicative of
cortisol levels, it is not nearly as accurate as
a direct measurement of blood such as in the
study conducted by Yehuda et al.
Additionally, water retention, while
indicating differences in cortisol, may also
be a result of other things as well, such as
excess insulin, or diet. Thus, our
measurement of cortisol was likely less
accurate. Future studies should attempt to
control for sources of variance such as
insulin and salt intake, or instead use a direct
measurement of cortisol in blood.
Additionally, future research should increase
their sample size, as it would bring the
measurements closer to the true mean and
thus increase the validity of the results.
The results from this correlational study
aligned with the results obtained by Tripp et
al. (2015) in their correlational study done
on alcohol consumption and symptoms of
trauma. We, similarly, found high degrees of
correlation between these two variables.
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Participants' daily alcohol consumption was
correlated with trauma using both pooled
raw data and pooled standardized data.
4.3 Implications of Results
Hopefully, our results may be able to
provide other researchers with an incentive
to continue analysis on the correlations we
found between substance abuse and trauma.
With more research on the subject, we may
be able to learn to better help and advocate
for those struggling with the upkeep of their
mental health and addictive behaviours.
Parents and guardians could become further
aware of the precursors, signs and symptoms
of alcohol abuse in their children, or
therapists could learn to be more promotive
of rehabilitation facilities and substanceindependence with clients effected by Posttraumatic stress disorder.
The topic of this study was proposed due
to a shared interest in both the biological
effects of trauma and the improvement of
our systems of mental aid, whether it be for
those with Post-traumatic stress disorder,
intergenerational trauma, or otherwise. Our
findings support the idea that a greater
attention to substance abuse, in particular,
may be beneficial in the revolution of how
we talk, think and help those who have
experienced trauma.

References
Grah, M., Mihanovic, M., Restek-Petrovic,
B., Svrdlin, P., & Vuk Pisk, S. (2010).
Serotonin and cortisol as suicidogenic
factors in patients with PTSD. School of
Biological Anthropology, 34(4), 14331439. https://eds-a-ebscohostcom.libsecure.camosun.bc.ca:2443/eds/p
dfviewer/pdfviewer?vid=8&sid=5f8ec8a
b-922a-43b5-9047071eceebf62a%40sessionmgr4007
Tripp, J. C., McDevitt-Murphy, M. E.,
Avery, M. L., & Bracken, K. L. (2015).
PTSD symptoms, emotion dysregulation,
and alcohol-related consequences among
college students with a trauma history.
Journal of Dual Diagnosis, 11(2), 107117.
https://doi.org/10.1080/15504263.2015.1
025013
Yehuda, R., Teicher, M. H., Seckl, J. R.,
Grossman, R. A., Morris, A., & Biere, L.
M. (2007). Parental posttraumatic stress
disorder as a vulnerability factor for low
cortisol trait in offspring of Holocaust
survivors. Archives of General
Psychiatry, 64(9), 1040–1048. https://doiorg.libsecure.camosun.bc.ca:2443/10.100
1/archpsyc.64.9.1040

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Table 1
Correlations for Study Variables

Variables

Water retention &
heart rate
Tiredness & heart
rate
Alcohol Intake &
heart rate

Participant
#1

Participant
#2

Participant
#3

Pooled raw
data

Pooled
standardize
d data

r

n

r

n

r

n

r

n

r

n

.90*

7

-.54

7

.54

7

-.35

21

.30

21

-.40

7

-.35

7

-.16

7

-.40

21

-.30

21

.61

7

.71

7

.18

7

.59*

21

.50*

21

* p < .05.

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Figure 1
Association Between Water Retention and Heart Rate Using Pooled Raw Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
and yellow = participant #3. Some data might not be visible in the figure due to overlapping
markers.

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Figure 2
Association Between Water Retention and Heart Rate Using Pooled Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
and yellow = participant #3. Some data might not be visible in the figure due to overlapping
markers.

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Figure 3
Association Between Tiredness and Heart rate Using Pooled Raw Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
and yellow = participant #3. Some data might not be visible in the figure due to overlapping
markers.

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Figure 4
Association Between Tiredness and Heart Rate Using Pooled Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
and yellow = participant #3. Some data might not be visible in the figure due to overlapping
markers.

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Figure 5
Association Between Alcohol Intake and Heart Rate Using Pooled Raw Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
and yellow = participant #3. Some data might not be visible in the figure due to overlapping
markers.

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Figure 6
Association Between Alcohol Intake and Heart Rate Using Pooled Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
and yellow = participant #3. Some data might not be visible in the figure due to overlapping
markers.

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