Step 3. Click on each question and our answers will appear. Step 4. Repeat with the other aspects of external validity and reliability. Questioning the Internal Validity: Randomisation : How were participants allocated to each group?
Did a randomisation process taken place? Participants were randomly assigned to either intervention or control in a one-to-one ratio with a computer generated randomization list with a block size of 4 using REDCap p.
Comparability of groups: How similar were the groups? Eg age, sex, ethnicity — is this made clear? Table 1 p. The two groups were quite similar only big differences were Cholesterol and Diastolic blood pressure p value of under 0. Blinding none, single, double or triple : Who was not aware of which group a patient was in?
Was it feasible for more blinding to have taken place? No mention if the researchers or those who weighed patients were blinded — they could have been. Equal Treatment of groups: Were both groups treated in the same way? At first until the intervention p. Then the interventions were very different p. Weight watchers — 45 minutes activation, free weekly sessions plus access to an app; Your Game Plan — booklet and 15 mins.
Attrition : What percentage of participants dropped out? Did this adversely affect one group? Has this been evaluated? Big difference so could have had an effect.
Discussed in the limitations section p. Overall Internal Validity: does the research measure what it is supposed to be measuring? Yes, it appears reasonable. Questioning the External Validity: Attrition: Was everyone accounted for at the end of the study?
Was any attempt made to contact drop-outs? No, there were drop-outs p. Yes, must have attempted to contact them as they give reasons for drop-out in Figure 1 p.
Sampling Approach: How was the sample selected? This link will open a PDF document. Strengthening the reporting of observational studies cohort, case-control, and cross-sectional.
Helpful for those working on a Mixed Methods Review. MetaQat - Meta-Tool for appraising all types of public health evidence.
These links will open a PDF document. Guidelines and Form. Quantitative Research Public Health Research. To evaluate the risk of bias and applicability of primary diagnostic accuracy studies. General Worksheets for Critical Appraisal of a variety of study designs:.
See all library locations. University Libraries. Search this Guide Search. What is a Rapid Review? What is a Scoping Review? What is a Mapping Review? The title should not normally exceed 15 words 2 and should attract the attention of the reader. These should provide information on both the ideas or concepts discussed in the paper and the subject area addressed in the article. These first steps can often influence your decision whether to read the entire paper.
Their qualification, both professional, for example, a nurse or physiotherapist and academic eg, degree, masters, doctorate.
Basically, do you want to read a paper on quantum physics written by a plumber? Methods including sample design, tests used and the statistical analysis of course! Remember we love numbers. The subheadings in the abstract will vary depending on the journal. An abstract should not usually be more than words but this varies depending on specific journal requirements.
If the above information is contained in the abstract, it can give you an idea about whether the study is relevant to your area of practice. However, before deciding if the results of a research paper are relevant to your practice, it is important to review the overall quality of the article.
This can only be done by reading and critically appraising the entire article. A well-structured introduction should gain the attention of the reader by making the subject area interesting.
The introduction should arouse your interest and curiosity and answer the question why should I bother reading this paper? Normally, the research question, aim, hypothesis and null hypothesis will be clearly stated in the introduction. An example of a hypothesis and null hypothesis can be seen in box 1. Box 1 Example: the effect of paracetamol on levels of pain My hypothesis is that A has an effect on B, for example, paracetamol has an effect on levels of pain.
My null hypothesis is that A has no effect on B, for example, paracetamol has no effect on pain. My study will test the null hypothesis and if the null hypothesis is validated then the hypothesis is false A has no effect on B.
This means paracetamol has no effect on the level of pain. If the null hypothesis is rejected then the hypothesis is true A has an effect on B. This means that paracetamol has an effect on the level of pain. The literature review should include reference to recent and relevant research in the area.
It should summarise what is already known about the topic and why the research study is needed and state what the study will contribute to new knowledge. In quantitative studies, the data analysis varies between studies depending on the type of design used. For example, descriptive, correlative or experimental studies all vary. A descriptive study will describe the pattern of a topic related to one or more variable. In experimental studies, the researchers manipulate variables looking at outcomes 8 and the sample is commonly assigned into different groups known as randomisation to determine the effect causal of a condition independent variable on a certain outcome.
This is a common method used in clinical trials. There should be sufficient detail provided in the methods section for you to replicate the study should you want to. To enable you to do this, the following sections are normally included:.
Data collection should be clearly explained and the article should discuss how this process was undertaken. Data collection should be systematic, objective, precise, repeatable, valid and reliable.
The sample size is central in quantitative research, as the findings should be able to be generalised for the wider population. From this analysis, results like mode, mean, median, p value, CI and so on are always presented in a numerical format.
The author s should present the results clearly. These may be presented in graphs, charts or tables alongside some text. You should perform your own critique of the data analysis process; just because a paper has been published, it does not mean it is perfect. Through critical analysis the reader may find an error in the study process that authors have not seen or highlighted. These errors can change the study result or change a study you thought was strong to weak.
To help you critique a quantitative research paper, some guidance on understanding statistical terminology is provided in table 1. Quantitative studies examine the relationship between variables, and the p value illustrates this objectively. If the p value is more than 0.
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