Hypothesis reporting in randomised controlled trials: A critical appraisal of IJA 2024 publications

The cornerstone of any robust research lies in a clearly stated, well-defined research question with objectives and hypotheses in randomised controlled trials (RCTs). Clearly stating the hypothesis ensures that the study has a specific objective, follows the appropriate methodology, and enables accurate interpretation of results. A precise hypothesis also helps design an intervention, accurately identify the sample size, and choose an appropriate statistical analysis. Despite its importance, many studies fail to explicitly state the hypothesis or present it in an unclear manner, resulting in ambiguity in methodology and challenges in drawing valid conclusions from the research studies. The purpose of this article is to assess whether the authors of published RCTs in the Indian Journal of Anaesthesia (IJA) explicitly stated the hypothesis and highlighted its importance. We assessed all the RCTs published in IJA in the year 2024. To assess the clarity of hypothesis statements, the following criteria were used: Explicit mention of ‘hypothesis’ in the manuscript Clarity in terms of variables, directionality, and scope: Whether the hypothesis specifies the expected relationship (e.g. ‘X reduces Y’ vs ‘X affects Y’). Whether the hypothesis stated aligns with the study objectives, methodology, and interpretation. In the IJA, 57 RCTs qualified for inclusion in this critical appraisal. The majority (~85%–90%) of RCTs explicitly stated a hypothesis,[1–48] while a minority of the studies (Yang X et al.[49] and Deb B et al.[50]) did not state a hypothesis explicitly; however, they defined variables and maintained consistency across sections. In some studies, such as Bhardwaj P et al.,[51] the term ‘hypothesis’ was not used, but the authors presented a well-defined objective. Over 80% of studies have a clear hypothesis, yet some, despite having research objectives, lack an explicit hypothesis, making them unclear or only partially clear. Almost all studies (nearly 100%) define their variables, even when the hypothesis is vague, indicating that researchers tend to establish their study parameters effectively. However, while most studies have a hypothesis, many do not explicitly state the expected direction of effect, such as the superiority of one treatment over another. Some studies, such as those by Hemantkumar et al.,[52] Gautam S et al.,[24] and Agarwal V et al.,[53] imply hypotheses but do not structure them explicitly. Others, such as Sakkanan NV et al.,[54] Efremov SM et al.,[55] Pal A et al.,[56] and Saha P et al.,[57] only partially define their hypotheses, lacking clarity or explicit directional expectations. This omission is more common in studies focusing on comparisons without predicting superiority. Some studies focus on defining objectives rather than framing them as hypotheses, resulting in unclear or unstated hypotheses that may affect the overall research direction and clarity. Despite these variations, most studies ensure internal consistency in their hypothesis across different sections of the paper. A well-formulated hypothesis serves as the foundation of research, guiding the study’s objectives, which must align with the process of testing the hypothesis. It delineates the relationship between variables and facilitates a focused investigation in a defined scope. The directionality of the hypothesis, whether directional or non-directional, further refines the study by predicting the nature of the association between the independent and dependent variables. A hypothesis must be closely aligned with the research objective and should maintain coherence and relevance, thereby guiding data collection and analysis with methodology. A well-structured hypothesis not only enhances the clarity and precision of research but also strengthens its validity, ensuring meaningful contributions to the field. A hypothesis consists of two components: the null hypothesis (H₀) and the alternative hypothesis (H₁). The null hypothesis represents the assumption of no effect or no difference between groups; the alternative hypothesis, on the contrary, proposes an observed effect or difference, challenging the null hypothesis.[58] Clearly defining both hypotheses is essential for appropriate study design, as statistical analysis aims to determine whether there is sufficient evidence to reject the null hypothesis in favour of the alternative. In the context of RCTs, a clearly stated hypothesis is indispensable to robust study design. Authors must explicitly define the variables under investigation and establish the expected direction of the relationship. Furthermore, consistency in hypothesis formulation throughout the study is essential, and any deviations should be thoroughly justified and explained. Authors should be actively encouraged to state their hypotheses and explicitly incorporate directionality in their RCTs. Providing structured guidelines or templates to authors for drafting clear and testable hypotheses would improve the quality and transparency of published research.