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:

These form the POCI acronym.

2.3.1 The Population

All RQs study some population: the larger group of interest in the study.

Definition 2.3 (Population) The population is the group of individuals (or cases; or subjects if the individuals are people) from which the total set of observations of interest could be made, and to which the results will (hopefully) generalise.

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.’

The population in a RQ is not just those we end up studying. It is the whole group to which our results would generalise.

In contrast, the sample is the subset of the population that we actually end up studying, from which data are obtained.

Definition 2.4 (Sample) A sample is a subset of the population of interest which is actually studied, and from which data are collected.

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 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.

Definition 2.5 (Inclusion criteria) Inclusion criteria are characteristics that individuals must meet explicitly to be included in the study.
Example 2.6 (Inclusion criteria) A study of a certain bird species may only included sites where there has been a confirmed sighting within the last two years.
Example 2.7 (Inclusion criteria) A study of weight-loss methods may require people over a certain weight.

Definition 2.6 (Exclusion criteria) Exclusion criteria are characteristics that explicitly disqualify potential individuals from being included in the study.
Example 2.8 (Exclusion criteria) Concrete test cylinders with fissure cracks may be excluded from tests of concrete strength.
Example 2.9 (Exclusion criteria) People with severe asthma may be excluded from exercise studies.

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).

Definition 2.7 (Outcome) The outcome in a RQ is the result, output, consequence or effect of interest in a study, 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.
The outcome in a RQ summarises a *population**; it does not describe the individuals in the population.

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 distinct subsets of the population (that is, groups of individuals), or may explore a connection between the outcome and some other quantity that varies.

Definition 2.8 (Comparison) The comparison in the RQ identifies the small number of distinct subsets of the population between which the outcome is compared.

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.

Example 2.10 (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 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 difference between right- and left-arm blood pressure.’

In contrast, a study comparing the average blood pressure between females and males does have a comparison: two subsets (females and males) of the population (Australians) are compared.
Definition 2.9 (Connection) The connection in the RQ identifies another quantity of interest that varies, that may be related to the outcome.

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.

Definition 2.10 (Intervention) An intervention is a comparison or connection that the researchers have imposed upon those in the study, intending to change the outcome.

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 2.11 (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)?
Outcome: ‘average iron status’ (which would need an operational definition.) Comparison: between highly active and sedentary women. Intervention: Probably none; an intervention would mean the researchers tell each individual woman to be highly active or sedentary, which seems unlikely.