Examining linking language and causal implications in observational psychological capital research : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Psychology at Massey University, Albany, New Zealand
The present study is a small-scale conceptual replication of Haber et al.'s (2022) study which examined how causal and associational language is used in observational health research, applied here to the domain of psychological capital. Psychological capital is an increasingly popular area of research in the industrial-organisational psychology (IO) field. We use this construct to examine whether the issues with implied causal inference identified by Haber et al. extend to the field of IO psychology. Specifically, we evaluate the causal strength of linking words, which are the words or phrases used to describe the nature of the connection between some defined independent variable and some defined outcome variable, linking sentences, which are the sentences that contain these linking words, and action recommendations. Causal language is that which implies one entity influences another. Our results highlight that both explicitly causal and non-causal linking words are commonly used in the observational psychological capital literature, including "relate", "influence", "impact", and "effect". The majority of primary linking sentences implied some level of causality, despite the fact that very few articles explicitly stated an intent to estimate causal effects and many explicitly warned against drawing causal inferences. Additionally, the majority of action recommendations had strong causal implications. No significant relationship was found between the causality implied in the linking sentences and the strength of causal implication of the action recommendations. Overall, causality appears to often be implied within the observational psychological capital literature, risking the overstatement of the evidence base. This has important implications for how research is implemented, and very real consequences for those who are the subject of such implementations. Recommendations are made for how authors, reviewers, and research consumers can support valid causal reasoning in observational research. Ultimately, through increased transparency and being cognisant of implied causality, we can ensure the credibility of the findings and the integrity of applications of the observational psychological capital literature.
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