Short Answers on Research Study

1
1. (12 points) Short Answers
Q. Point
s
a. State the research
question behind this
study.
The research question behind this study was
based on the examination of the effect of health
warning levels (HWL) applied pictorially on the
waterpipe (WP) device on smoker’s
experience, behavior underlying puffing,
perception of harm and exposure to respiratory
toxicants (Maziak et al., 2019).
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b. Clearly state the
hypothesis of the study, in
the form of a null and an
alternative hypothesis.
Null hypothesis: The addition of pictorial HWL
on the WP will result in no reductions in the
puffing parameters, exposure to carbon
monoxide and positive experiences among
smokers, implying that, there is a statistically
insignificant relationship between pictorial
HWL and smoking behaviors.
Alternative hypothesis: The addition of
pictorial HWL on the WP will result in
signficant reductions in the puffing parameters,
exposure to carbon monoxide and positive
experiences among smokers, implying that,
there is a statistically significant relationship
between pictorial HWL and smoking behaviors
(Maziak et al., 2019).
4
c. What is/are the independent
(exposure) and dependent
(outcome) variables in this
study?
The independent, exposure variables in the
study were the inclusion of pictorial HWL on
the WP of the smoking devices. The dependant
outcome variables for the study were: the
amount of carbon monoxide exhaled, puff
topography (puff durations and intervals
between puffs, total puff volume), smoking
experiences (satisfaction, taste, puff) and harm
perception (Maziak et al., 2019).
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2.( 8 points) Classify the following variables according
to their type:
Quantitative/Qualitative/Nominal/Ordinal/interview/Ratio/binary/
polychotomous as applies

2
Perception of
Harm
Quantitative Variable: Ordinal variable (ranging from 1 to 7 point
scale – extremely harmful – not at all harmful).
Puff duration Quantitative variable - no ordering or categorization in variables
Total volume
inhaled
Quantitative Variable - no ordering or categorization in variables
Number of puffs Quantitative Variable - no ordering or categorization in variables

3
2. The design of this trial was a crossover design:
2a. (2 points) How would you repeat the same trial with a parallel design?
A parallel study is characterized by randomly assigning subjects to separate
groups where one group will receive a specific type of intervention (for
example intervention X) while the other group will receive another separate
type of intervention (for example intervention Y). Hence, considering the
study, instead of the same group of subjects receiving a multiple forms of
intervention in the form of a cross over design, a parallel design will involve
randomizing the subjects into two separate groups: one receiving one type
of HWL while the other group receiving a different type of HWL.
Additionally, control group will be required who will not be receiving the
HWL for the purpose of comparing the HWL effects on smoking behavior
(Grieve, 2016).
2b. (4 points) What types of considerations would you make to
minimize the effects of bias and confounding.
Participants with varied demographic characteristics such as
both males or females, or hailing from various educational
backgrounds must be incorporated to prevent generalizations
and prevent the effects of confounding variables such as
gender, education, employment etc. Further participants must
be blinded to the interventions of the study in order to prevent
biased responses. Researches must also be concealed and
blinded to the treatment and allocation sequences utilized
during intervention administration in order to prevent
researcher bias (Heale & Twycross, 2015).
2c. (4 points) If your study were indeed conducted as a parallel
trial, would you require the same/smaller/larger number of
participants for the same level of precision obtained in this
study? Justify your answer.
For the conductance of a the parallel design, a larger sample size
may be required during random allocation. This is due to the fact
that a smaller sample size in parallel designs such as
randomized controlled trials is more prone to bias and
generalization resulting in invalid results. Further, a larger
sample size ensures incorporation of varied participant
characteristics resulting in reduced confounding and increased
applicability in real-life scenarios (Bonett & Wright, 2015).
3. The authors state that “the study was not powered to detect
differences in outcome measures between the two HWLs”: