Aims, hypotheses, operationalisation of variables, demand characteristics and pilot studies
Aims are research objectives, exact statements of why studies are conducted, for instance to investigate whether differing amounts of sleep affect concentration levels. Aims should incorporate what is being studied and what studies are trying to achieve.
Hypotheses are more objectively precise than aims and are testable predictions of what is expected to happen. There are two types of hypotheses:
1 The experimental hypothesis, which predicts that differences in the DV will be outside the boundaries of chance (known as significant differences) as a result of manipulation of the IV. The term ’experimental hypothesis’ is used with experiments; other research methods refer to ’alternative hypotheses’. Example: ’that participants receiving 8 hours’ sleep last night will perform significantly better on a test of concentration than those receiving 4 hours’ sleep last night.’
2 The null hypothesis, which predicts that the IV will not affect the DV and that any differences found will not be outside the boundaries of chance, i.e. will not be significantly different. Example: ’that participants receiving 8 hours’ sleep last night will not perform significantly better on a test of concentration than those receiving 4 hours’ sleep last night. Any differences found will be due to chance factors.’
One of these two hypotheses will be supported by the findings and accepted while the other will be rejected.
There are two types of experimental/alternative hypotheses:
1 Directional (one-tailed) hypotheses, which predict the direction that the results will lie in. Example: ’that participants running 400 metres on an athletics track while being watched by an audience of their peers will run significantly quicker times than those running without an audience.’
2 Non-directional (two-tailed) hypotheses, which predict a difference in the results but not the direction in which the results will lie. Example: ’that there will be a significant difference in times achieved between participants running 400 metres on an athletics track while being watched by an audience of their peers and those running without an audience.’
Directional hypotheses are used when previous research gives an indication of which way findings will lay.
OPERATIONALISATION OF VARIABLES
Operationalisation concerns objectively defining variables in an easily understandable manner, so that an IV can be manipulated (altered between testing conditions) and its effect on a DV measured. For example, if researching the effect of sleep on concentration, the IV could be operationalised as the amount of sleep the previous night and the DV the score on a test of concentration. Without accurate operationalisation, results may be unreliable and invalid; therefore it is crucial to operationalise IVs and DVs accurately, but this can be difficult, for example how can ’anger’ be accurately operationalised?
Research involves social interactions between investigators and participants, which can influence and bias findings so that they are not valid. One such research effect is demand characteristics, where participants form impressions of the research purpose and unknowingly alter behaviour accordingly. Demand characteristics affect research findings in several ways:
1 Where participants guess the purpose of research and try to please researchers by giving them their expected results.
2 Where participants guess the purpose of research and try to sabotage it by giving non- expected results.
3 Where participants, out of nervousness or fear of evaluation, act unnaturally.
4 Where participants respond to a social desirability bias and give answers/exhibit behaviour that shows them in a socially acceptable manner.
Demand characteristics are reduced by the single-blind procedure, where participants are not aware of which testing condition they are in, for example in a drug trial not knowing whether they have swallowed a real pill or a placebo.
Investigator effects concern the ways in which researchers can unconsciously influence research in several ways:
1 Major physical characteristics such as the age and gender of researchers.
2 Minor physical characteristics like their accent and tone of voice.
3 Unconscious bias in the interpretation of data.
The double-blind technique reduces investigator effects by neither participants nor researchers knowing which conditions participants are in.
Fig 7.2 The physical appearance of an investigator can unconsciously affect the behaviour of participants in studies
Pilot studies are small-scale ’practice’ investigations allowing procedural improvements and removal of methodological errors. Participants can point out flaws, such as the presence of demand characteristics. Pilot studies show what kinds of results are expected and whether there is any possibility of significant results. Pilot studies permit the quality of research to be improved and help avoid unnecessary time and effort being wasted, for example by performing lengthy studies only to find that due to unexpected errors and problems, the results are invalid and the study will have to be altered and repeated.