Objectives Negative consequences of medical labelling have been reported in research literature¹ and differences in an individual’s intention to undertake further testing have been shown in studies that randomly assigned participants to labelled and unlabeled hypothetical medical scenarios.² When given information about overdiagnosis of polycystic ovary syndrome after medical scenarios, all groups (irrespective of whether the medical label was used) reduced their intention to have follow-up tests³. What is unknown, is how an individual’s psychological traits such the predisposition to seek medical care, emotional stability, extraversion, and locus of control and their perceptions of risk and stigma toward the health condition might impact a person’s decision to undertake further tests when exposed to either a labelled or unlabeled medical scenario.

Method A randomised controlled online survey was distributed to 256 participants aged 45–70 years in three countries (Australia, Ireland and Canada). Participants completed trait-based measures including health locus of control, regulatory focus (promotion/prevention), self-perceptions of medical usage, and health risk orientation. Participants were then randomised to receive two scenarios (stratified for age, gender and country). Scenarios described the outcome of a recent health test using either medical terms (‘labelled’) or condition descriptions (‘descriptive’). There were ‘labelled’ and ‘descriptive’ scenarios for four health conditions known for controversies over threshold changes (pre-diabetes, mild hypertension, mild hyperlipidaemia, and chronic kidney disease stage 3a). Each scenario informed participants they were close to the threshold and gave participants information about overdiagnosis. Post-scenario, participants rated their perception of illness risk and stigma. Between group differences for intentions to pursue a follow-up test was the primary outcome. We also assess what traits may have impacted their decision.

Results Preliminary analyses suggest that after adjusting for two scenarios per person, there was no significant difference between the ‘labelled’ (n=129) and ‘descriptive’ (n=127) groups in their intention to have follow-up tests (95% CI −0.77 to 0.33 points). In a multivariable regression model, there was a significant increase in intentions to pursue further tests when participants were: high users of medical interventions (p

Conclusions Previous research has consistently found a labelling effect, but the cause of the effect is unclear. Our findings both contrast and expand upon previous research. We analyzed four different health conditions with controversies around the threshold. All scenarios were ‘close to the cut-off’. It is unclear why our ‘labelled’ and ‘description’ scenarios did not produce significant differences in intentions to undertake further tests, as has been found in previous studies. It may be that by first eliciting psychological trait measures related to health we cued participants to think about their health, which counteracted labelling effects. Future studies might reverse the data collection order (respond to illness scenarios prior to answering trait-based measures) to explore whether the labelling effect reappears. If this were the case, it would suggest that how we communicate to people about their health is more challenging than whether we label the health condition or not.