The Effect of Tablet Size on Cognitive Performance: A Randomized Control Trial Using Caffeine
Phase: PHASE4
Conditions: Placebo Effect
Sponsor: University of Colorado, Denver

Running head: EFFECT OF TABLET SIZE 
 
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The Effect of Tablet Size on Cognitive Performance: 
A Randomized Control Trial Using Caffeine 
 
Daniel Hernandez Altamirano 
University of Colorado Denver 
 
Dr. Amy Wachholtz 
Dr. Lindsey Hamilton 
Dr. Joan Bihun 
 
 
July 9, 2018 
 
 

EFFECT OF TABLE SIZE 
 
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Abstract 
 
Background: A capsule’s physical design (e.g. shape, size, and color) affects 
individuals’ perception of drug efficacy; that is, how well a drug is likely to work. The goal of this 
study is to assess the effects tablet size may have on participant’s performance on cognitive 
testing since research has found differences between preparation methods. Method: 120 
participants will be randomly assigned to one of four groups: 1) 90 mg caffeine with a 1 mm 
diameter sucrose pillule; 2) no caffeine with the small sucrose pillule; 3) 90 mg caffeine with a 5 
mm sucrose pillule; 4) no caffeine with the large sucrose pillule. Participants will consume the 
designated placebo tablet with water (caffeinated or non-caffeinated); then, participants will 
provide weekly caffeine intake and complete the neutral portion of Velten’s Mood Induction 
Procedure until 30 minutes have passed to allow for caffeine activation. Participants will 
complete the Stroop test, Trial Making Tests A and B, and the Rey Auditory Verbal Learning 
Test. Previous literature, as far as the author knows, relied on evaluating drug efficacy based on 
appearance alone. This study aims to assess if tablet size, due to placebo effect, alters 
participants’ performance on cognitive tests after consuming caffeine. 
 
 

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The Effect of Tablet Size on Cognitive Performance: 
A Randomized Control Trial Using Caffeine 
Placebo effects are physiological changes in the brain and body brought about through 
treatments that have no active ingredient or active component (Geuter et al., 2017). 
Historically, placebo effects have been utilized as a marketing tool because the public’s beliefs, 
expectations, experiences, and perceptions made the proposed treatments and products 
appealing. For example, in the 1700s, Franz Anton Mesmer developed his theory of “animal 
magnetism” (Hammond, 2013). His theory asserted “mesmeric” (i.e. hypnotic) motions over a 
patient’s body would redistribute and realign magnetic fluids within the body, curing clients of 
their ailments. However, after much criticism, Mesmer’s claim was found to be unsupported by 
experimental evaluation. His peers concluded that the results from his treatments were more 
likely due to his clients’ imaginations than his theory on animal magnetism (Hammond, 2013). 
In other words, Mesmer took advantage of his clients’ susceptibility to mesmerism, or 
hypnotism, to create a physiological response during treatment.  
There are different methods to elicit a physiological response in individuals using 
placebos. Pseudo-pharmaceutical placebos include mixtures created from Galen’s 
Pharmacopeia, a recipe book that uses plants, bacteria, worms, reptiles, fish, human 
organs, tissue, bone powder, or excretion to create “medicinal remedies.” Before the 19th 
century, this recipe book was believed to provide cure all recipes for ailments (Czerniak & 
Davidson, 2012). If the patient died, then the ailment was incurable, and no remedy would have 
worked. Why have placebos endured throughout history? Literature suggests that one 
explanation could be how individuals perform perceptual decision making (Geuter et al., 2017). 

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Bayesian models of perceptual decision making suggest that creating biased perceptions in 
favor of expected values or outcomes results in outcomes that fulfill those expectations. For 
example, if an individual expects pain, introducing a placebo may create the expectation of 
experiencing less pain. If the placebo is successful, the individual will experience an analgesic 
effect without any active ingredient. These placebos can be applied in many different 
situations, where an individual’s perceptions or expectations influence the outcome of their 
treatment or intervention. 
In recent research, a placebo effect may have been responsible for differences in 
participant responses to experimental procedures. Initially, the placebo effect threatened the 
validity of previous research, because its effects were not well understood (Ross & Buckalew, 
1979) among the different scientific disciplines. The placebo effect in scientific literature was 
still an unintentional and unexplained effect; psychological and behavioral changes were 
observed in different studies repeatedly (Buckalew, 1979). As more evidence surfaced, the 
demand to better understand the placebo effect increased. Understanding the placebo effect 
would not only safeguard and improve research quality; the placebo effect showed promise to 
be manipulated to explore possible beneficial uses. 
Physical drug design 
Research since then suggests that the physical design of drugs influences an individual’s 
perception of a drug. Specifically, the color, shape, size and coating of the drug have been 
found to impact preferences, how strong an individual perceives a drug to be and the effect 
they believe a drug will have (e.g. tranquilizer, stimulant, etc.; Buckalew & Coffield, 1982).  

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Buckalew and Coffield’s research on the effects of capsule size on perceived drug 
strength suggests that larger capsules are believed to be stronger than small capsules 
(Buckalew & Coffield, 1982). In their study, college students were recruited to assess the 
relationship between perceptual characteristics of physical drug preparation forms (i.e. 
formulation) and expected effects. The influence of capsule size on perceived drug strength, the 
influences of color on expected drug effects, and the influence of formulation on expected drug 
strength were all visually assessed. Their findings suggest that certain colors are related to 
expected pharmacological effects. Furthermore, capsules are perceived to be stronger than 
tablets, and capsule size is significantly related to expected drug strength. Larger capsules are 
perceived to be stronger compared to smaller capsules. In tablets, the same pattern might 
persist; however, the opposite effect might also occur. Smaller tablet sizes might result in a 
stronger effect than larger tablet sizes. Buckalew and Coffield’s work relied on visual 
judgements of drug characteristics; however, this study will rely on quantitative data to 
evaluate tablet size’s effects on participants’ performances due to participant perception. 
Overgaard et al.’s study aimed to assess the preferences of oral dosage forms by size, 
formulation (i.e. gelatin capsule, tablet, or coated tablet), and shape (Overgaard et al., 2001). 
The study was designed in three phases, each assessing one of the previously mentioned 
factors. To assess how size affects swallowability and preference, participants were each asked 
to swallow five differently sized oblong tablets and verbally rate how easily they were able to 
swallow each pill according to a 5-point Likert scale. Smaller tablets were found easier to 
swallow compared to larger ones. To assess what formulation is preferred, participants were 
asked to swallow a gelatin capsule, tablet, and coated tablet and rate which was easier to 

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swallow. Gelatin capsules were easiest to swallow, followed by coated tablets and non-coated 
tablets. Lastly, to assess the preferable shape participants were asked to visually judge small, 
medium, and large white tablets that were circular or oblong on swallowability. Medium and 
large tablets were rated the easiest to swallow if they were oblong, while small tablets were 
rated easiest to swallow when they were round (Overgaard et al., 2001). Overgaard et al.’s 
work established preferences for physical drug designs. However, little is known if those 
physical characteristics can influence the placebo effect influencing the performance of the 
drug. This study will focus on one size, specifically in tablets, to assess if that characteristic can 
affect cognitive outcomes in a quantifiable manner. Despite extensive library searches, no 
research was found that analyzed tablet-based, physical design factors, like size, that could 
influence a placebo effect and consequently drug performance. 
Caffeine  
Caffeine is a psychostimulant with three main mechanisms ofaction : 1) mobilization of 
intracellular calcium, 2) inhibition of phosphodiesterases, and 3) antagonism of adenosine 
receptors (Nehlig et al., 1992). Caffeine stimulates the release and reuptake of calcium in 
neurons and muscle-tissue cells; an essential process in the central and peripheral nervous 
systems for neuronal communication and muscle contraction in the musculoskeletal system. 
Caffeine inhibits the breakdown of phosphodiesterases in the central nervous system. 
Caffeine’s molecular structure is like that of enzymes responsible for breaking down 
phosphodiesterases into molecules like cAMP, a messenger molecule. This action, though, 
occurs when there is a toxic concentration of caffeine in the blood. The mechanism of action 
associated with improving cognition after consuming caffeine is the antagonism of adenosine 

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receptors. Adenosine is responsible for dampening neuronal activity in the suprachiasmic 
nucleus (e.g. less electrical activity, less neurotransmitter release, etc.). The physiological 
response associated with uninhibited adenosine receptors (i.e. with no caffeine present) is 
feeling drowsy, sleepy, and less attentive. Caffeine has a high affinity for adenosine receptors 
(specifically the A1 receptor), so adenosine receptors are blocked by caffeine molecules (Nehlig 
et al., 1992). Consequently, individuals can experience the opposite physiological response: 
better attention, feeling awake, improved attentiveness, etc. The consequences of caffeine’s 
third mechanism of action have been thoroughly researched, making it a strong drug candidate 
for use in this study. 
Caffeine may be a good option for testing this phenomenon for three reasons: 1) 
previous research already supports caffeine’s improvements to cognitive functioning (EFSA, 
2011); 2) caffeine use among college students is very salient, given the prominence of the 
caffeine across various products like energy drinks (Pettit & DeBarr, 2011); 3) using self-report 
measures to collect data on weekly caffeine consumption habits will allow adjustments for 
tolerance effects (Beaumont, et al., 2017;2016). Research on caffeine use in healthy adults has 
already shown significant improvement to memory, executive functioning, and processing 
speed (EFSA, 2011). Caffeine lends itself well to a randomized controlled trial design, allowing 
the introduction of tablet size as an additional factor. Previous research supports an increase in 
cognitive functioning after consuming caffeine; memory, executive functioning, and processing 
speed are improved after consuming caffeine (EFSA, 2011). The European Food and Safety 
Administration conducted a meta-analysis that assessed the different claims associated with 
consuming caffeine like increased fat oxidation, increased energy expenditure, increased 

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alertness, and increased attention. Their findings suggest that there is not enough data to 
support causal claims for caffeine causing increased fat oxidation and increased energy 
expenditure. However, a causal relationship between caffeine and increased alertness and 
increased attention is supported (EFSA, 2011). Pettit and Debarr conducted a study analyzing 
the association between stress and energy drink consumption, and the association between 
energy drink consumption and GPA in 136 college students ages 18-24 (Pettit & DeBarr, 2011). 
Their results show a positive correlation between perceived stress and energy drink 
consumption, and a negative correlation between GPA and energy drink consumption. 
However, the results in Pettit and DeBarr’s study did not account for consumption of caffeine 
from other sources (e.g. coffee, tea, supplements, etc.). Heavy marketing for caffeinated 
products make caffeine an ideal substance to use for assessments when working with college 
students.  
Beaumont et al.’s research on tolerance development for low doses of caffeine 
emphasizes the need to adjust for tolerance effects in randomized controlled trials (Beaumont, 
et al., 2016; 2017;). Their research examined participant physical performance after consuming 
small doses of caffeine. Participants experienced significant decline in performance after 
consuming small doses of caffeine (1.5 mg of caffeine per kg of bodyweight) for 28 consecutive 
days compared to placebo. Beaumont et al.’s work highlights the importance of adjusting for 
participants’ caffeine consumption habits. Leaving scores unadjusted for caffeine consumption 
habits could be a confound to studies that involve participants consuming caffeine. 
Lastly, age is a significant factor in caffeine metabolism. Some hepatic enzymes 
(Cytochrome P450s, or CYPs) become less active as individuals age (Kinirons & O’Mahony, 

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2004). There are several different CYPs that metabolize different drugs. Caffeine is metabolized 
by CYPs in the 1A family, specifically 1A2 CYPs. Kinirons and O’Mahony’s literature analysis 
showed consistent decrease in enzyme activity as individuals age (Kinirons & O’Mahony, 2004). 
They suggest the decreases in certain enzyme activity are likely due to changes in liver size and 
blood flow. Livers in humans experience a size reduction and reduced blood flow with age. 
When conducting research that involves participants metabolizing caffeine, age should be 
considered. Caffeine is a good choice to examine the effects tablet size may have on 
participants’ performances on cognitive tests. 
Present Study 
Previous research relied heavily on participants’ perceptions to rate a drug’s 
effectiveness and purpose; this study was designed with randomized, placebo-controlled trials 
to evaluate the main goal using objective quantitative data. I will use neuropsychological testing 
to assess if tablet size affects participants’ short-term memory, executive function, and 
processing speed using caffeine as the drug of choice. Previous research has supported a 
significant cognitive boost in these cognitive functions for caffeine dosages of at least 75 mg 
(EFSA, 2011). If tablet size affects perceptions of how effective a dose of caffeine will be, 
despite doses remaining constant in the caffeinated groups, then I expect significant differences 
among the two tablet sizes for processing speed, executive functioning, and memory 
capabilities in participants. This study may prove foundational to better understanding more 
effective physical drug designs.  
Hypotheses 
There are three hypotheses for this experiment: 

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1) caffeine will significantly improve participant’s memory, executive function, and 
processing speed;  
2) there will be a significant difference in participant performance associated with 
tablet size;  
3) there will be an interaction effect between caffeine content and tablet size.  
 
 
 
 
 
 

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Method 
Participants 
120 participants, primarily Psychology students fulfilling a research participation 
requirement for Introduction to Psychology courses, will be recruited. Ambulatory participants 
that are fluent in written and spoken English will be used because they should be able to 
complete the neuropsychological tests.  
Participants that are allergic to sucrose and/or caffeine will be excluded because they 
are essential components to the procedure. Participants with cardiovascular disease or 
uncontrolled high blood pressure will be excluded because the use of caffeine may exacerbate 
these conditions. Participants with untreated or unresolved anxiety and/or depressive disorders 
will be excluded because caffeine may exacerbate symptoms related to these disorders as well. 
Participants that are pregnant will be excluded from this study. Lastly, participants that have a 
diagnosed learning disability will be excluded because the neuropsychological tests will only use 
scores normalized for the general population.  
Participants’ age will be limited to ages 18 years old through 40 years old because age is 
a significant factor in caffeine metabolism (Kinirons & O’Mahony, 2004). Individuals older than 
40 may experience different pharmacological effects due to age; thus, age will be controlled in 
this study. 
Measures 
Processing Speed. 
 
Stroop 1) Color and 2) Word tests. 

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The Color test asks participants to read the color of print on a page with columns of red, 
yellow, green, and blue X s. The Word test asks participants to read the printed words on a 
page with the words RED, YELLOW, GREEN, and BLUE printed in black ink. These tests are 
scored by timing, in seconds, how long participants take to correctly identify the 100 items in 
each test. Longer completion times indicate slower processing speed capabilities. The Stroop 
Test’s separate 1) Color and 2) Word tests (Appendix B) test-retest reliabilities are .83 and .74, 
respectively (Franzen, et al., 1987) 
 
Trail Making Task A. 
 
This test asks participants to connect a series of numbers that are randomly distributed 
on the test page. The goal of these tasks is to connect the series of numbers or numbers and 
letters in order (e.g. 1-2-3) as quickly as possible. Scoring is done by recording the time (in 
seconds) participants needed to complete the test. Longer completion times indicate slower 
processing speed capabilities. The Chronbach’s alpha reliability of Trail A is .86 (Smith, et al., 
2008). 
Executive Function. 
Stroop 3) Color-and-Word test. 
 
The Color-and-Word test asks participants to read the color of print for the words RED, 
YELLOW, GREEN, and BLUE when the print color and word conflict. This test is scored by timing, 
in seconds, how long it takes for participants to correctly read 100 items. Longer completion 
times indicate lower executive function capabilities because the conflict between the print 
color and printed word takes longer to overcome. The test-retest reliability of the Stroop Color-
and-Word Test is .67 (Franzen, et al., 1987). 

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Trail Making Task B. 
 
This test asks participants to connect a series of numbers and letters that are randomly 
distributed on the test page. The goal of these tasks is to connect the series of numbers and 
letters in order (e.g. 1-A-2-B-3-C) as quickly as possible (Appendix C). Switching between 
alphabetic and numeric sets and timing completion times, in seconds, is an effective measure of 
executive functioning capabilities. Longer completion times indicate lower executive function 
capabilities because participants take longer to switch between sets. The Cronbach’s alpha of 
Trail B is .88 (Smith, et al., 2008).  
Memory. 
Rey Auditory Verbal Learning Test (RAVLT). 
Participants are presented with 15 unrelated words and asked to recall as many as they 
can over five trials. This section assesses immediate recall ability. An additional 15 unrelated 
words are then introduced as an interference component. Participants must recall as many of 
the original 15 words as possible after being presented with interference. Lastly, after an 
interval of 30 minutes, participants are asked to recall the original 15 words again (Appendix D). 
The trials are scored by counting the correct number of words recalled, the % recalled (the final 
delayed-recall trial(A7) divided by the final immediate recall trial (A5)), and the number of 
intrusions (i.e. the number of incorrect words). A higher percentage of recall with little to no 
intrusions are considered better memory. The Cronbach’s alpha reliability of the Rey Auditory 
Verbal learning Test is .84 (Magalhaes, et al., 2012). 
Procedure 

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Materials for this procedure will need to be prepared beforehand. 90 mg packets of 
caffeine will be prepared from 200 mg pure caffeine powder capsules by opening capsules and 
measuring out the desired weight of caffeine using a scale that can measure accurately to the 
thousandths gram. The weight of each prepared packet will be recorded by hand in a notebook 
until it is used in a trial. Before participants arrive, the prepared caffeine packet will be mixed 
with distilled water and one pillule of each size will be placed into small paper cups marked A 
and B.  
Procedures will be explained to participants at first contact, and they will sign an 
informed consent form to confirm eligibility (Figure 2). Participants will be randomly assigned to 
one of the four groups (Figure 1). Based on a power analysis conducted at 0.80 power on 
Pasman et al.’s work on the effects of caffeine in a home-setting, 120 participants will need to 
be recruited in this study to successfully detect any significant effect (Pasman et al., 2017). 
Participants will be required to not have consumed caffeine the day of testing. 
Participants will be presented with 8 ounces of distilled water and the cups containing each 
sucrose placebo pill. They will be asked to drink the water and only one of the sucrose pillules 
(depending on the group they were placed in); half of the participants (n=60) will drink water 
mixed with 90 mg of dissolved caffeine (Figure 1). After consumption, participants will be asked 
to complete Velten’s Neutral Mood Induction Procedure (Appendix A) until 30 minutes have 
passed to allow for caffeine activation in the body (Institute of Medicine (US) Committee on 
Military Nutrition Research, 2001). Participants will then begin with the series of Stroop tests. 
After completing the three Stroop tests, participants will complete the first section of the Rey 
Auditory Verbal Learning test (immediate recall). During the 30-minute waiting period 

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participants will complete Trail Making Tasks A and B, and fill out a demographic survey 
designed to collect: 1) their weekly caffeine intake using the Caffeine Consumption 
Questionnaire (Appendix E); 2) sex; 3) age; 4) ethnicity and race; 5) year in school (i.e. 
freshman, sophomore, etc.); 6) GPA; and 7) academic major. The time of day the trial begins 
will also be recorded. The data collected in the survey will be used to adjust scores during data 
analyses. If students are unable to complete the survey and caffeine questionnaire within the 
30-minute waiting period allotted for the RAVLT, the survey materials will be set aside and 
completed after participants finish the second component of the RAVLT. After completing the 
second portion of the RAVLT participants will be debriefed, and the trial will conclude.  
Data Analysis 
Primary analysis will be done through a series of ANCOVAs, if a preliminary correlation 
analysis shows a significant relationship between weekly caffeine consumption and scoring for 
each cognitive component. If the preliminary correlation analysis does not show a significant 
relationship between weekly caffeine consumption and scores for each cognitive component, 
then a series of ANOVAs will be performed. 
Proposed Timeline 
 
Pending the approval of clinicaltrials.gov, materials will be gathered and prepared in 
early October. The UROP has been awarded and funds will be available once PRS has approved 
of this proposal. Recruitment will begin during the Fall semester. Recruitment and trials are 
expected to continue in through December and conclude as late as February. Course load will 
be kept to a minimum to allot enough time for trials every weekday during the morning. 

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Weekly caffeine consumption will be calculated for each participant from their reported 
caffeine consumption habits (Appendix E).  
 
Figure 1. Overall study design  
 

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Figure 2. CONSORT diagram 
 
 
  
The Effect of Tablet Size on Cognitive Performance: A RCT Using Caffeine 
 
Assessed for eligibility (n=) 
Excluded  (n=   ) 
   Not meeting inclusion criteria 
(caffeine consumed prior to testing) 
(n=  ) 
   Declined to participate (n=  ) 
   Other reasons (n=  ) 
Analysed  (n=  ) 
 Excluded from analysis (give reasons) (n=  ) 
Allocated to intervention: small 
tablet size, caffeine (n=30) 
 Received allocated 
intervention (n=  ) 
 Did not receive allocated 
intervention (n=  ) 
Analysed  (n=  ) 
 Excluded from analysis (give reasons) (n=  ) 
Allocation 
Analysis 
Randomized (n=120) 
Enrollment 
Allocated to intervention: large 
tablet size, caffeine (n=30) 
 Received allocated 
intervention (n=  ) 
 Did not receive allocated 
intervention (n=  ) 
Allocated to intervention: small 
tablet size, no caffeine (n=30) 
 Received allocated 
intervention (n=  ) 
 Did not receive allocated 
intervention (n=  ) 
Allocated to intervention: large 
tablet size, no caffeine (n=30) 
 Received allocated 
intervention (n=  ) 
 Did not receive allocated 
intervention (n=  ) 

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Appendix A 
Velten’s Neutral Mood Induction Procedure 
 
Eight of sixty neutral mood statements on Velten’s Neutral Mood Induction task. 
Participants will be presented one statement every thirty seconds.  
 
 

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Appendix B 
Stroop Color test 
 
 
 

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Stroop Word test 
 

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Stroop Color-and-Word test 
 
 
 
 
 
 

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Scoring sheet for the Stroop Color, Word, and Color-and-Word tests 
 
 
 
 
 
 

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Appendix C 
Trail Making Task A 
 
 
 
 
 
 
 
 
 

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Trail Making Task B 
 
 
 
 

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Appendix D 
Rey Auditory Verbal Learning Test 
 
 
 

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Appendix E 
Questionnaire to Collect Weekly Caffeine Consumption
 
 
Participants will be asked to fill in 7 sheets, one for each day of the week. 
 

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Appendix F 
Demographics Survey 
 

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