1. Randomization:
Randomization refers to the process of assigning participants to different study groups in a random and unbiased manner. It helps ensure that the groups being compared are similar at baseline, reducing the risk of confounding factors influencing the results. This item assesses whether proper randomization techniques were employed and if the process was adequately described in the study.
2. Allocation concealment:
Allocation concealment refers to keeping the treatment assignment hidden from the investigators involved in the study. It helps minimize selection bias and ensures that participants and researchers remain unaware of the treatment allocation until the intervention is assigned. This item evaluates whether proper measures were taken to conceal the allocation sequence.
3. Blinding:
Blinding, or masking, involves keeping participants, healthcare providers, and outcome assessors unaware of the treatment assignment. It helps minimize bias and ensures that the observed effects are not influenced by expectations or preconceived notions. This item examines whether blinding was implemented effectively and whether it was maintained throughout the study.
4. Sample size calculation:
Sample size calculation determines the number of participants needed to detect a meaningful difference or effect size with sufficient statistical power. It helps ensure that the study is adequately powered to detect a true treatment effect if one exists. This item assesses whether a sample size calculation was performed and if the sample size is appropriate to answer the research question.
5. Intent-to-treat analysis:
Intent-to-treat analysis involves including all participants in the groups to which they were originally allocated, regardless of their compliance with the assigned treatment. It helps preserve the randomization and avoids potential bias caused by participants dropping out or switching groups. This item examines whether an intent-to-treat analysis was conducted and reported appropriately.
6. Outcome measures:
Outcome measures are the variables used to assess the effectiveness or impact of the intervention being studied. This item evaluates whether the chosen outcome measures are appropriate, reliable, and valid. It also examines whether the methods of measuring and assessing the outcomes are clearly described.
7. Statistical analysis:
Statistical analysis involves the application of appropriate statistical tests to analyze the data collected in the study. This item assesses whether the statistical methods used are suitable for the study design and research question. It also examines whether the analysis is properly described and if any potential confounding factors or adjustments were considered.
8. Funding and conflicts of interest:
Funding sources and conflicts of interest can influence the design, conduct, and reporting of a study. This item examines whether the study's funding sources and potential conflicts of interest are disclosed. It helps ensure transparency and allows readers to assess any potential bias or influence that may affect the study's findings.
9. Adverse events and harms:
Adverse events refer to any unintended or undesirable effects that occur during or after the intervention. This item assesses whether the study adequately reports the occurrence of adverse events, their severity, and their relationship to the intervention. It helps evaluate the safety and potential risks associated with the treatment being investigated.
10. Generalizability:
Generalizability, also known as external validity, refers to the extent to which the study findings can be applied to a broader population or real-world setting. This item evaluates whether the study sample is representative of the target population and whether the findings can be reasonably generalized to other contexts or populations.