The unappreciated relevance of auxiliary assumptions for evaluating theory-based interventions in health psychology

Abstract

The use of theory in health behavior change interventions has been recently questioned with mixed results found for theory-based intervention effectiveness. But theory testing in intervention depends on not only theoretical assumptions, but on auxiliary assumptions too. Specifically, auxiliary assumptions are required to traverse the distance from nonobservational terms in theories and observational terms at the level of the empirical hypotheses in interventions. We believe intervention failures are often due to flaws in auxiliary assumptions rather than assumptions at the theoretical level. We use the theory of planned behavior to illustrate how the consideration of these auxiliary assumptions is important to appraise the effectiveness of interventions informed by theory. We hope that bringing attention to the importance of auxiliary assumptions provides a more nuanced and accurate appraisal of theory utility.

Testing theory predictions and intervention mechanisms of action in sport and exercise psychology using meta-analysis.

“…Tests of theories 1 in sport and exercise psychology typically involves a priori specification of sets of predictions among measures of psychological constructs that represent mental processes (e.g., performance anxiety, self-efficacy, attitudes, personality) and key outcomes of interest (e.g., sport performance, rehabilitation adherence, physical activity participation). Such tests should conform to key empirical principles in theory building and testing, such as clearly defining constructs and outcomes and specifying effects among them, using of fit-for-purpose measures with high validity, and specification of clear grounds for falsifiability and any accompanying auxiliary assumptions and boundary conditions (for a comprehensive review of theory features in psychology and associated issues, see Davis et al, 2015; St Quinton & Trafimow, 2022). 2 Researchers have adopted experimental and nonexperimental study designs to test these predictions.…”

“…Theory enables researchers to summarize prior knowledge on a particular effect, pose risky but meaningful predictions, develop fit-for-purpose studies with appropriate research designs aimed at testing the predictions against observation, interpret the observations relative to predictions including support or falsification, and provide a basis for subsequent tests (e.g., Davis et al, 2015; Hagger et al, 2017; Trafimow, 2009). Consistent with the principles advocated by classic empiricists (e.g., Lakatos, 1978; Meehl, 1990), theory testing is a time-consuming and iterative process, with each study representing a data point that contributes to the accumulating body of evidence for the theory-predicted effect, bounded by the limitations and caveats of the methods adopted and associated auxiliary assumptions (St Quinton & Trafimow, 2022). The cumulative evidence garnered from these tests provides an opportunity to evaluate the utility of the theory as well as its sufficiency, assumptions, boundary conditions, and limitations, and serves as a basis for future research aimed at developing it further (Ajzen, 1991; Gonzalez-Mulé & Aguinis, 2018; Trafimow, 2022).…”

On the scope of scientific hypotheses

“…The TASI model is insightful and helpful in highlighting the distance between a theory and the observation that would corroborate/contradict it. Part of its utility is to bring auxiliary hypotheses into the foreground, to improve comparisons between studies and improve theory-based interventions [ 63 , 64 ].…”