2.3 Elements of RQs
A RQ must be written carefully so it can be properly answered. In this section, the four potential components of a RQ are studied:
- The Population;
- The Outcome;
- The Comparison or Connection;
- The Intervention.
These form the POCI acronym.
2.3.1 The Population
All RQs study some population: the larger group of interest in the study.
Individuals or cases do not just refer to people., though the words may be commonly used that way.
Similarly, population does not just mean people. In this context, a population is any group of interest; for example:
- all Australian males between 18 and 35 years of age.
- all bamboo flooring materials manufactured in Queensland.
- all elderly males with glaucoma in Canada.
- all Pinguicula grandiflora growing in Europe.
The population is not just those individuals from which the data are actually obtained. Indeed, all these elements of the population may not be accessible in practice.
The population represents all the ‘individuals’ to which the results are to be generalised. For example, when testing a new drug, the aim is to see if it works on people in general, including people not yet born. The population is ‘all people.’
In contrast, the sample is the subset of the population that we actually end up studying, from which data are obtained.
Example 2.5 (Samples) Consider a study of American college women, which aimed to:
…assess iron status […] in highly active (>12 hr purposeful physical activity per week) and sedentary (<2 hr purposeful physical activity per week) women…
— Woolf et al. (2009), p. 521.
The sample comprises 28 ‘active’ women and 28 ‘sedentary’ American college women, from which data are collected.
The population is all ‘active and sedentary’ American college women, not just the 56 in the study. The group of 56 subjects is the sample.Completely defining the population (Banerjee and Chaudhury 2010) sometimes requires refining or clarifying the population, using exclusion and/or inclusion criteria.
Exclusion and inclusion criteria clarify which individuals may be explicitly included or excluded from the population.
Exclusion and inclusion criteria should be explained when their purpose is not obvious. Both exclusion and inclusion criteria are not needed; none, one or both may be used.
Example 2.10 (Population and exclusion criteria) A study on the influenceze vaccine (Kheok et al. 2008) listed the Population as ‘health-care workers’ (Kheok et al. 2008p.466), and the sample they studied was:
All healthcare workers at the National University Hospital (NUH) and KK Women’s and Children’s Hospital (KKWCH)…
— Kheok et al. (2008), p. 466
The population was refined by exclusion criteria. The exclusion criteria were:
…declining to give consent, a history of egg protein allergy, and neurological or immunological conditions that are contraindications to the influenza vaccine.
— Kheok et al. (2008), p. 466
A study (Guirao et al. 2017) of the walking abilities of amputees used these inclusion and exclusion criteria:
Inclusion criteria were as follows: length of the femur of the amputated limb of at least 15 cm measured from the greater trochanter, use of the prosthesis for at least 12 months prior to enrollment and more than 6 h/day, ability to walk indoors with or without supervision, and with or without ambulation aids and unilateral femoral amputation.
The criteria for exclusion were the presence of cognitive impairment hindering the ability to follow instructions and/or perform the tests, body weight over 100kg, active oncologic pathologies, psychological disorders, previous residuum infection, active infection, residual femur length less than 15cm measured from the greater trochanter, pregnancy, and hip flexion deformity greater than 30o.
— Guirao et al. (2017), p. 27 (emphasis, line-break added)
2.3.2 The Outcome
All RQs study something about the population, called the outcome.
Because the RQ concerns a population, the outcome describes a population as a whole; hence, the outcome is usually an average, percentage, or general quantity numerically summarising the population (or subsets of the population).
The outcome may be (for example):
- average increase in heart rates.
- average amount of wear after 1000 hours of use.
- proportion of people whose pupils dilate.
- average weight loss after three weeks.
- percentage of seedlings that die.
2.3.3 The Comparison or Connection
In addition to having a population (P) and an outcome (O), some RQs may compare the outcome between a small number of different, distinct subsets of the population (that is, groups of individuals), or may explore a connection between the outcome and some other quantity that varies.
The outcome may be compared between two or more separate subsets of the population:
- Average amount of wear in floor boards (O) could be compared across two groups in the population: standard wooden flooring materials and bamboo flooring.
- Average heart rates (O) could be compared across three subsets of the population: those who received no dose of a drug, those who received a daily dose of the drug, and those who received a dose of the drug twice daily.
Be careful!
This definition requires that population can be separated into two (or more) subgroups, that have either imposed differences (for example, one group is given one dose of fertilizer per day, and another given two doses of fertilizer per day) or have existing differences (for example, one group of people aged under 30, and another group of people aged 30 or over).
If all individuals are treated in the same way, there is no comparison according to this definition.Example 2.11 (Comparison) Consider a study to compare the average blood pressure (the Outcome) in Australians (the Population), to see if the average blood pressure in the right arm is the same as the average blood pressure in the left arm.
There is no comparison: the Outcome (average blood pressure) is not compared in two different subsets of the population; every person is treated the same way.
Instead, the blood pressure is measured twice on every member of the population. The outcome might be best described as ‘the mean difference between right- and left-arm blood pressure.’
In contrast, a study comparing the average blood pressure between peoiple aged under 40 and people aged 40 or over does have a comparison: two subsets (females and males) of the population (Australians) are compared.As the value of the connection changes, the value of the outcome (potentially) changes:
- The connection between average heart rate (O) and exposure to various doses of caffeine (C) in mg.
- The connection between percentage germination (O) and hours of sunlight per day (C).
2.3.4 The Intervention
In addition to having a population (P), an outcome (O), and possibly a connection or comparison (C), some RQs also have an intervention.
The intervention may be:
- explicitly giving a new drug to patients.
- explicitly applying wear testing loads to two different flooring materials.
- explicitly exposing people to different stimuli.
- explicitly applying a different dose of fertiliser.
Example 2.12 (Interventions) A study comparing the average blood pressure (O) in female and male (C) Australians (P) measured blood pressure using a blood pressure machine (a sphygmomanometer).
The research team needs to interact with the participants and use a machine to measure blood pressure, but there is no intervention. Using the sphygmomanometer is just a way to measure blood pressure, to obtain the data. The sphygmomanometer is not used with the intent of changing the outcome.
There is no intervention, since the comparison is between females and males, and this cannot be imposed on the individuals by the researchers.Sometimes, it is not clear from the RQ if an intervention is present or not. If you are writing an interventional RQ, you should try to make it clear when an intervention is used.
Think 2.2 (POCI) A study of American college women aimed to:
…assess iron status […] in highly active (>12 hr purposeful physical activity per week) and sedentary (<2 hr purposeful physical activity per week) women…
— Woolf et al. (2009), p. 521.
In this study, what is the:
- Outcome?
- Comparison or Connection (if any)?
- Intervention (if any)?
Researchers examined numerous studies of chest compressions involving paramedics. For their study, they examined research papers in which the Population was patients who had experienced a cardiac arrest, and where manual chest compressions were compared with another method.
The table below shows the comparison and outcomes of interest:
| Interventions | Outcomes |
|---|---|
| Mechanical chest compression | Mean survival time to hospital discharge |
| Mechanical CPR | Percentage with a return of spontaneous circulation (ROSC) |
| Automated chest compressions | |
| Automated CPR | |
| Powered chest compressions | |
| Powered CPR |
The research concluded that:
Overall, the evidence analysed suggests that mechanical chest compression devices are statistically superior to manual chest compressions of a high quality, when up-to-date protocols and guidelines are followed.
— Williams et al. (2021), Table 1