Mixed messages: most spinal pain and osteoarthritis observational research is unclear or misaligned

We assessed authors’ language and methods to determine alignment between reported aims, methods, intent, and interpretations in observational studies in spinal pain or osteoarthritis. We searched five databases for observational studies that included people with spinal pain or osteoarthritis published in the last 5 years. We randomized 100 eligible studies, and classified study intent (aims and methods) and interpretations as causal, non-causal, unclear, or misaligned. Overall, 38% of studies were aligned regarding their intent and interpretation (either causally (22%) or non-causally (16%)). 29% of studies’ aims and 29% of study methods were unclear. Intent was misaligned in 16% of studies (where aim differed to method) and 23% of studies had misaligned interpretations (where there were multiple conflicting claims). The most common kind of aim was non-causal (38%), and the most common type of method (39%), intent (38%), and interpretations (35%) was causal. Misalignment and mixed messages are common in observational research of spinal pain and osteoarthritis. More than 6 in 10 observational studies may be uninterpretable, because study intent and interpretations do not align. While causal methods and intent are most common in observational research, authors commonly shroud causal intent in non-causal terminology. •Researchers' interpretations are misaligned with their intent in almost two-thirds of observational studies.•Causal intent and interpretations are most common in observational research.•Researchers often use methods that signal causal intent but use noncausal or ambiguous language to describe their intent.•Researchers commonly use causal language when interpreting their results, even when methods do not signal causal intent.What should change now?•Researchers should align their stated aims, methods, and interpretations.•Researchers should precisely express their aim in observational research.•Researchers should clearly explain their rationale behind study design elements like enrolling a control group or methods like covariate selection and confounding adjustment.•Researchers should unambiguously interpret their results, in alignment with the intent of their study.•End-users should beware that noncausal or ambiguous language is used to shroud causal intent in observational research.