Cross-sectional analysis: interpretation of non-statistically significant results in randomised controlled clinical trials in rehabilitation
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Introduction
Despite the CONSORT guidelines, which aim to improve the quality of studies, authors often formulate conclusions based on the dichotomous distinction of the p-value, declaring differences between ‘statistically significant’ and ‘non-significant’. This approach confuses the identification of the real efficacy of the studied treatment. To solve this problem, CONSORT guidelines recommend using confidence intervals, which offer a more complete view of possible effects. However, authors’ conclusions often remain based on a binary approach, confusing the absence of evidence with the evidence of absence. This error can influence clinical practice and future research, leading to the identification of ‘negative’ treatments based on ‘statistical insignificance’, which reflects a lack of evidence of absence, not the absence of evidence.
Objectives
To assess the prevalence of misinterpretation of non-statistically significant results, both in the abstract and in the article, in a sample of all randomised controlled trials (RCTs) with non-statistically significant primary outcomes published in 5 rehabilitation journals with the highest impact factor (IF) published between 2019 and 2023 and to assess whether the primary outcome result is reported according to CONSORT guidelines.
Methods
We will conduct a cross-sectional analysis of all Rcts with non-statistically significant primary outcomes in 5 general rehabilitation journals with the highest IF published between 2019 and 2023. We will determine the prevalence of trials in which non-significance is interpreted as absence of evidence, evidence of absence, or advice to use the intervention in clinical practice in the abstract and article conclusions, and the prevalence of trials that adhered to CONSORT guidelines for reporting the primary outcome.
