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In other words, it is the extent to which the results of a study can generalize or transport to other situations, people, stimuli, and times. [2] [3] Generalizability refers to the applicability of a predefined sample to a broader population while transportability refers to the applicability of one sample to another target population. [2]
Given the complicated history of ethnography, "autoethnographers speak against, or provide alternatives to, dominant, taken-for-granted, and harmful cultural scripts, stories, and stereotypes" and "offer accounts of personal experience to complement, or fill gaps in, existing research." [23]: 3 As with other forms of qualitative research ...
Qualitative research is a type of research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation.
The term "ecological validity" is now widely used by researchers unfamiliar with the origins and technical meaning of the term to be broadly equivalent to mundane realism. [5] Mundane realism references the extent to which the experimental situation is similar to situations people are likely to encounter outside the laboratory.
Interpretative phenomenological analysis (IPA) is a qualitative form of psychology research. IPA has an idiographic focus, which means that instead of producing generalization findings, it aims to offer insights into how a given person, in a given context, makes sense of a given situation .
Generalizability theory, or G theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations. It is used to determine the reliability (i.e., reproducibility) of measurements under specific conditions.
In other words, the relevance of external and internal validity to a research study depends on the goals of the study. Furthermore, conflating research goals with validity concerns can lead to the mutual-internal-validity problem, where theories are able to explain only phenomena in artificial laboratory settings but not the real world. [13] [14]
Critical appraisal (or quality assessment) in evidence based medicine, is the use of explicit, transparent methods to assess the data in published research, applying the rules of evidence to factors such as internal validity, adherence to reporting standards, conclusions, generalizability and risk-of-bias.