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

J Camosun Psyc Res. (2022). Vol. 4(1), pp. 76-96.
Submitted Fall 2021; accepted June 2022.

Biological Mechanisms of Attention Deficit Hyperactive
Disorder.
Authors: James Vandeweerd* and Jacob Miton
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: currently.not@live.com

ABSTRACT
In this paper, we sought to understand the biological mechanisms of Attention Deficit
Hyperactive Disorder (ADHD), so that we could learn how to benefit those with ADHD.
Previous research has found that ADHD symptoms can be mediated by variables such as body
mass index (BMI), consumption of refined sugar and polyunsaturated fatty acids (PUFA). In our
first (correlational) study, we tested the strength of these relationships by examining naturalistic
daily changes in their variables longitudinally over a one-week period. We measured weight and
BMI by using a weight scale, as well as a standard BMI calculator. We tracked food intake,
refined sugar intake, and PUFA intake through the MyFitnessPal application. We measured
ADHD symptoms using the Adult ADHD Self-Report Scale. Based on the strength of correlation
found between PUFA and ADHD symptoms in our correlational study, we then conducted a
second (experimental) study to test for a causal relationship between these two variables. Over a
one-week period, we randomly assigned participants each day to either a placebo condition or a
PUFA supplement condition using a double-blind procedure and measured the effect this
manipulation had upon ADHD self-report symptoms using the Adult ADHD Rating Scale. Data
pooled across participants in our correlational study failed to show significant correlations of
BMI, sugar intake, and PUFA intake with ADHD symptoms. However, data pooled across
participants in our experimental study showed that PUFA intake significantly reduced ADHD
Self-Report Scale scores. This data suggests that PUFA supplementation is beneficial in the
reduction of ADHD symptoms, both on their own and in conjunction with stimulant medication.
1. Introduction
1.1 Research Problem
ADHD is a psychopathological disorder
that compromises the individual’s ability to
function, which can lead to problematic
lifestyle behaviors. While stimulant
medication is currently in the forefront of
treatment options for those with this
disorder, we sought to find out if there are

alternatives which could help handle
ADHD’s symptoms either in concert with
stimulant medication or without. There are
many different ways of handling ADHD
symptoms and this paper sought to shine a
light on how small lifestyle choices can
impact the individual. Many of the current
pharmacological treatment options can have
adverse side effects for those seeking relief
of their symptoms, so finding alternative
methods of treatment can benefit both these
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individuals and the ADHD community as a
whole. Finding a new method of symptom
management for those living with ADHD
could bring new tools for both patients and
professionals in lessening the burden that
this disorder causes.
1.2 Literature Review
One factor previously found to predict
improved symptoms and behavior associated
with ADHD is simply decreasing the overall
BMI of ADHD patients, such as by reduced
carbohydrate intake. For example, in an
experimental study by Abd El Baaki et al.
(2021), researchers studied a group of 47
children newly diagnosed with ADHD, aged
six to nine years old, and subjected them to a
diet modification program which lasted five
weeks and had two phases. With phase one,
the baseline period, researchers recorded the
subjects as they adhered to their normal diet
and life for two weeks with no food
elimination. Phase two, the diet modification
phase, consisted of health education and diet
modification for five weeks. The results
were measured with the Connor parent’s
rating scale and a significant decrease in
impulsivity/hyperactivity and learning
problems were found after the diet
modification program. Based on these
results, the researchers suggested that diet,
in conjunction with healthy lifestyle choices
and proper education, can significantly lead
to better management of ADHD symptoms
and a more enjoyable quality of life for the
individual.
Another factor previously found to
predict a decrease in ADHD symptoms in
those who are unmedicated is having them
follow an elimination or “few foods” diet,
which also reduces refined sugar intake. For
example, in an experimental study by
Pelsser et al. (2009), researchers sampled 27
unmedicated children diagnosed with

ADHD, as outlined by the DSM-IV, and
separated them into a control group and an
experimental group. Children in the
experimental group were put on a diet
consisting of rice, turkey, lamb, fruits,
vegetables, margarine, vegetable oil, pear
juice, tea and water for a period of 5 weeks.
The control group continued eating their
usual diet. The children were all rated prior
to and following the diet on the Abbreviated
10-item Conners Scale (ACS) and the
ADHD rating scale (ARS). This study
showed that careful food control can
diminish ADHD symptoms to a point where
50% of the children in the experimental
group no longer met the required criteria for
ADHD according to the DSM-IV. In
contrast to this, those in the control group
showed no improvement of symptoms.
Based on these results, the researchers
suggested that a carefully controlled diet
with the reduction of refined sugar has
potential to improve the symptoms of those
affected with ADHD.
Lastly, also identified as a factor in
reducing ADHD symptoms is the
supplementation of polyunsaturated fatty
acids (PUFA) alongside a healthy diet. For
example, in an experimental study by Sinn
and Bryan (2007), researchers sampled 132
children diagnosed with ADHD who were
not on any form of stimulant medication.
After splitting the subjects into three groups,
one group was given PUFA supplements
alongside their regular diet, the second
group was given PUFA supplements as well
as a micronutrient supplement, and the third
group was given none of the interventions.
This trial lasted 15 weeks and at the end
their research showed that both groups who
took the PUFA had significant improvement
across the board as measured by the Conners
ADHD Rating Scales for ADHD symptoms,
with the micronutrient supplement showing
no significant difference from PUFA
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supplements alone. The placebo group
showed no marked improvement, but the
trial was continued an additional 15 weeks
with all groups now taking the PUFA
supplements and the original results of the
two PUFA groups were repeated with the
original placebo group as well. Based on
these results, researchers concluded that
PUFA supplementation could improve
symptoms of those living with ADHD.
1.3 Hypotheses
Based on the above literature review, we
predicted the following hypotheses:
Hypothesis #1: If BMI decreases then
ADHD symptoms will decrease.
Hypothesis #2: If refined sugar consumption
decreases then ADHD symptoms will
decrease.
Hypothesis #3: If intake of PUFA increases
then ADHD symptoms will decrease.
2. Methods
2.1 Participants
The two authors of this paper served as
the participants in its studies. The
participants ranged in age from 22 to 35
years old, with an average age of 28.5 years,
and included two cis-gendered males. The
participants were all undergraduate students
at Camosun College who completed the
current studies as an assignment for Psyc215
(“Biological Psychology”) and were
grouped together due to their mutual interest
in ADHD. One participant was medically
diagnosed at age 6 and has been taking
stimulant medication since, while the other
was self diagnosed in their late 20s and is
not currently taking medication.
2.2 Correlational Study Methods

We first 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
three variables: (1) weight and BMI, (2)
refined sugar intake, and (3) PUFA intake.
2.2.1 Weight and BMI
To measure weight and Body Mass Index
(BMI), we used a weight scale as soon as
participants awoke in the morning. BMI was
calculated using a standard BMI calculator,
provided by the National Lung, Heart, and
Blood Institute of the United States (See
Appendix B). This data was collected on a
daily basis and examined through the course
of one week.
2.2.2 Refined Sugar Intake
To measure refined sugar intake each
participant tracked their food intake after
each meal through the MyFitnessPal app and
noted their sugar intake in the daily
overview page within the app. This data was
collected and reported on a daily basis over
the course of one week.
2.2.3 Polyunsaturated Fatty Acids
To measure refined sugar intake each
participant tracked their food intake after
each meal through the MyFitnessPal app and
noted their PUFA intake in the daily
overview page within the app. This data was
collected and reported on a daily basis over
the course of one week.
2.2.4 ADHD Symptoms
To measure symptoms of ADHD within
the participants, we used the Adult ADHD
Self-Report Scale (ASRS-v1.1) (See
Appendix A) which is a self-assessment tool
that measures behavioral aspects of ADHD
symptoms. It is an instrument consisting of
the eighteen DSM-IV-TR criteria and is
consistent with the DSM-IV criteria for an
adult ADHD diagnosis. These symptoms
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were measured on a daily basis, with part A
of the test being scored out of 6, and part B
of the test being scored out of 12. Scores in
the range of 4-6 in part A are indicative
symptoms consistent with ADHD in adults.
While there is no numerical cut off for
scores in part B, higher numbers are more
consistent in adults with ADHD. The study
is scored by giving the participant one point
for each answer given in the range of
answers which are greyed out. To prevent
test bias, tests will be taken through an
online service where participants can not see
the threshold for earning points for that
category.
2.3 Correlational Study 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 BMI,
Refined sugar intake, and PUFA intake with
their outcome variable of ADHD symptoms.
For testing Hypothesis #1, we correlated
BMI with Adult ADHD Self-Report Scale
scores. For testing Hypothesis #2, we
correlated refined sugar intake with Adult
ADHD Self-Report Scale scores. For testing
Hypothesis #3, we correlated PUFA intake
with Adult ADHD Self-Report Scale Scores.
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).
2.4 Experimental Study Methods
Based on the strength of the correlation
between PUFA intake and ADHD
symptoms found in our correlational study,
we then chose to conduct an experimental
study to test for a causal relationship
between these two variables from
Hypothesis #3.
We manipulated the independent
variable, PUFA intake, over a one-week
period by alternating assignment of each
condition for the participants each day to
either a PUFA condition or a placebo
condition using a double-blind procedure.
We recruited 3rd party individuals to set up
a 7-day pill container alternating between
the PUFA supplement and a look alike
placebo. The participants took one pill per
day for the 7-day trial and then took the
ADHD self report test.
To avoid order effects, we ran an ABAB
alternating experiment with a blind trial set
up by 3rd party individuals unaware of the
proposed hypothesis.
For our PUFA condition, a 1200mg gel
cap containing a blend of Omega-3, Omega6 and Omega-9 was used. For the placebo
condition, the same 1200mg gel cap was
used, but without the PUFAs inside. The
placebo pill was drained of its contents using
a needle. This method of placebo retains
some of the signature fishy aftertaste that
can accompany the PUFA condition pill to
further obfuscate to the participant which
pill is being taken. The pills were
administered in the morning of each day by
the 3rd party individual, and the participants
were instructed to swallow the pill as fast as
possible without examining it. The
dependent variable, ADHD symptoms, was
then measured by the participant on each
experimental and control day using the same
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method described above in the correlational
study.
2.5 Experimental Study Planned Analyses
To assess the statistical significance of
differences seen in ADHD symptoms on
PUFA supplemented experimental days vs.
placebo control days, Student’s t-tests were
performed. We performed t-tests separately
for each participant as well as using data
pooled across all of the participants. For the
t-tests using pooled data, in addition to using
the raw data, we also performed t-tests 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. An average difference between
conditions was considered statistically
significant if, using a one-tailed distribution
(i.e., to determine if there is a difference
between groups in a specific direction), the
probability of its random occurrence (p) was
< .05 (i.e., less than 5% of the time expected
by chance alone).
3. Results
3.1 Correlational Study Results
After performing our week-long study,
we determined that there was a significant
correlation between PUFA intake and
ADHD self report score, with no other
significant results in the data from the
remaining procedures (see Table 1). The
correlation between BMI and ADHD
symptoms was nonsignificant for each
individual participant and when using either
the pooled raw data (r = -0.14, p = 0.647;
see Figure 1) or the pooled standardized data
(r = 0.17; p = 0.573; see Figure 2). The
correlation between sugar intake and ADHD
symptoms was nonsigificant for each

individual participant and when using either
the pooled raw data (r = 0.15, p = 0.612; see
Figure 3) or the pooled standardized data (r
= 0.11; p = 0.724; see Figure 4). The
correlation between PUFA and ADHD self
report score was statistically significant for
the unmedicated participant (Participant #1,
r = -0.83; p = 0.0183) but not for medicated
participant (Participant #2, r = 0.15; p =
0.760) and not when using either the pooled
raw data (r = 0.31; p = 0.292; Figure 5) or
the pooled standardized data (r = -0.34; p =
0.244; Figure 6).
3.2 Experimental Study Results
Participants participated in this
experiment for 7 days, with 3 of the pills for
each participant being placebo pills, and 4
pills being 1200mg PUFA supplements,
with a double-blind, alternating ABAB
procedure. Table 2 provides a summary of
the descriptive statistics. A statistically
significant difference between conditions
was found using both the pooled raw data (t
= 7.20, p = 0.003; see Figure 7) and the
pooled standardized data (t = 9.06, p <
0.001; see Figure 8). The findings from the
current study suggest that participants in the
experimental condition had lower ADHD
self-report scores, and therefore decreased
ADHD symptoms.
4. Discussion
4.1 Summary of Results
In our correlational study, no support was
found for any of our hypotheses when using
pooled data. However, the unmedicated
participant did show a significant negative
correlation between PUFA intake and
ADHD symptoms. In addition, the results of
our experimental study support our third
hypothesis in which increased PUFA intake
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causes a marked decrease in ADHD
symptoms.
4.2 Relation of Results to Past Research
The lack of relationship we found
between BMI and ADHD self-report
symptoms is not consistent with past
research. A study by Abd El Baaki et al.
(2021) indicated there exists a positive
correlation between obesity and ADHD
symptoms in adults. In addition to this, it has
been shown that the way that the brain’s
reward circuit functions is intrinsically tied
to ADHD-related behaviour (Volkow et al.,
2011). One methodological difference
between our correlational study and the
study of Abd El Baaki et al. (2021) that
might possibly indicate the discrepancy of
our results is that only half of our population
were being medicated for ADHD using
amphetamines while none of the participants
in the Abd El Baaki et al. (2021) study were
medicated. Future research on this topic
might benefit from a large sample size of
both medicated and unmedicated
participants.
The lack of relationship we found
between sugar intake and ADHD symptoms
is different from the results of past research.
In the Pelsser et al. (2009) study, it was
found that a diet with a lower sugar intake
would improve symptoms of ADHD in
unmedicated children. The major
methodological difference between that
study and our own was that half of our
participants were on stimulant medication,
while none of the participants in the Pelsser
et al. (2009) study were medicated. So,
while there may be a correlation between
sugar intake and ADHD symptoms, our
study did not support this idea across all
participants. Future research might look into
conducting a similar study with both
medicated and unmedicated participants in

separate groups to test the relationship
further.
In past research regarding PUFA intake
and ADHD symptoms, Sinn and Bryan
(2007) found that in unmedicated
participants there is an inverse relationship
between PUFA intake and ADHD
symptoms. While our study did support
these findings in our unmedicated
participant, our original hypothesis was
much broader and covered both medicated
and unmedicated individuals. In this regard,
our data found no significant correlation
between PUFA intake and the reduction of
ADHD symptoms across the spectrum of
individuals involved. Future research might
look into conducting a similar study with
both medicated and unmedicated
participants in separate groups to test the
efficacy further. Our experimental study
results for PUFA intake and ADHD
symptoms were statistically significant,
confirming the efficacy of PUFA
supplements in both types of participants.
4.3 Implications of Results
This study originally set out to find an
alternate means of lessening the impact of
ADHD symptoms in people with ADHD.
The results of this study have found that
there is a causal effect between PUFA
supplementation and the reduction of ADHD
symptoms in both people with and without
stimulant medication. These results suggest
that there is a positive benefit to
supplementing with PUFA for all people
struggling with ADHD symptoms.
Practical applications for our results
could include an alternative source of
symptom reduction for those whom
stimulant medication deems ineffective. This
result could also be used in conjunction with
stimulant medication to further reduce
ADHD symptoms.
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References
Abd El Baaki, O.M., Abd El Hamid, E.R.,
Zaki, S.T., El Din Alwakaad, E.S., Sabry,
R.N., & Elsheikh, E.M. (2021). Diet
modification impact on ADHD outcome.
Bulletin of the National Resource Center,
45, 15. https://doi.org/10.1186/s42269020-00466-x
Martins-Silva, T., Vaz, J.S., Genro, J.P.,
Hutz, M.H. Mola, C.R., Mota, N.R.,
Oliveira, I., Gigante, D.P., Pinheiro, R.T.,
Vitola, E., Grevet, E., Horta, B.L.,
Rohde, L.A., Tovo-Rodrigues, L. (2021).
Obesity and ADHD: Exploring the role of
body composition, BMI polygenic risk
score, and reward system genes. Journal
of Psychiatric Research, 36, 529-536,
https://doi.org/10.1016/j.jpsychires.2020.
10.026

Pelsser, L. M. J., Frankena, K., Toorman, J.,
Savelkoul, H. F. J., Pereira, R. R., &
Buitelaar, J. K. (2009). A randomised
controlled trial into the effects of food on
ADHD. European Child & Adolescent
Psychiatry, 18(1), 12–19. https://doiorg.libsecure.camosun.bc.ca:2443/10.100
7/s00787-008-0695-7
Sinn, N., Bryan, J., (2007) Effect of
supplementation with polyunsaturated
fatty acids and micronutrients on learning
and behavior problems associated with
child ADHD. Journal of Developmental
& Behavioral Pediatrics, 28(2), 82-91.
https://doi.org/10.1097/01.DBP.0000267
558.88457.a5
Volkow, N.D., Wang, G.-J., & Baler, R.D.
(2011). Reward, dopamine and the
control of food intake: implications for
obesity. Trends in Cognitive Science,
15(1) 37-4
https://doi.org/10.1016/j.tics.2010.11.001

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Table 1
Correlations for Study Variables

Variables

Participant #1

Participant #2

Pooled raw
data

Pooled
standardized
data
r

n

0.11

14

r

n

r

n

r

n

0.53

7

-0.31

7

0.15

-0.83*

7

0.15

7

-0.31

14

-0.34

14

0.46

7

-0.12

7

-0.14

14

0.17

14

Sugar intake and ADHD
Self-Report Score

14

Polyunsaturated Fatty
Acid Intake and ADHD
Self-Report Score
BMI and ADHD SelfReport Score

* p < .05.

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Table 2
Descriptive Statistics for ADHD Self-Report Score Results Across Different PUFA Intake
Conditions

Condition
1200mg PUFA
Supplement

Placebo

Statistic

Participant Participant
#1
#2

Pooled
raw
data

Pooled
standardized
data

M

6.00

9.25

7.63*

-0.75*

SD

0.82

1.71

2.13

0.32

n

4.00

4.00

8.00

8.00

M

15.00

15.67

15.33

1.00

SD

2.65

1.15

1.86

0.38

n

3.00

3.00

6.00

6.00

Note. M, SD, and n, represent mean, standard deviation, and sample size, respectively.
* p < .05 for comparison of PUFA supplement condition with its respective placebo condition.

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Figure 1
Association Between BMI and ADHD Symptoms Using Pooled Raw Data

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

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Figure 2
Association Between BMI and ADHD Symptoms Using Pooled Standardized Data

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

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Figure 3
Association Between Sugar Intake and ADHD Symptoms Self Report Score Using Pooled Raw
Data

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

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Figure 4
Association Between Sugar Intake and ADHD Symptoms Self Report Score Using Pooled
Standardized Data

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

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Figure 5
Association Between PUFA Intake and ADHD Symptoms Self Report Score Using Pooled Raw
Data

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

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Figure 6
Association Between PUFA Intake and ADHD Symptoms Self Report Score Using Pooled
Standardized Data

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

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Figure 7
Average ADHD Self-Report Score Results Across Different PUFA Intake Conditions Using
Pooled Raw Data

Notes. ADHD Self-Report scores are shown for PUFA supplement and placebo conditions using
pooled raw data from all participants. Error bars show ± 95% confidence levels. Red dots
indicate participant #1, Green dots indicate participant #2. Some data might not be visible due to
overlapping markers.

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Figure 8
Average ADHD Self-Report Score Results Across Different PUFA Intake Conditions Using
Pooled Raw Data

Notes. ADHD Self-Report scores are shown for PUFA supplement and placebo conditions using
pooled standardized data from all participants Error bars show ± 95% confidence levels. Red
dots indicate participant #1, Green dots indicate participant #2. Some data might not be visible
due to overlapping markers.

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Appendix A
Adult ADHD Self-Report Scale (ASRS-v1.1)

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Appendix B
Body Mass Index Table

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