Back

Online Misinformation Susceptibility Scale: An adapted version for health-related misinformation

Katsiroumpa, A.; Konstantakopoulou, O.; Gallos, P.; Moisoglou, I.; Mangoulia, P.; Galani, O.; Tsiachri, M.; Galanis, P. A.

2025-09-12 public and global health
10.1101/2025.09.11.25335589 medRxiv
Show abstract

OBJECTIVETo examine the validity and reliability of the adapted version of the Online Misinformation Susceptibility Scale (OMISS) for health-related misinformation. METHODWe examined the reliability of the Health-Related Online Misinformation Susceptibility Scale (HR-OMISS) by calculating Cronbach alpha and McDonald Omega. We examined the construct validity of the HR-OMISS by performing confirmatory factor analysis. We examined the concurrent validity of the HR-OMISS using the Trust in Scientists Scale, the single-item scientists confidence scale, the Conspiracy Mentality Questionnaire (CMQ), and the single item conspiracy belief. We examined known-groups validity of the HR-OMISS by comparing healthcare workers with a MSc diploma versus those without one. RESULTSWe found that the HR-OMISS had very good reliability since Cronbach coefficient alpha 0.920 and McDonald Omega was 0.922. We found that the adapted version of the OMISS for health-related misinformation (HR-OMISS) had a one-factor structure as the original version (OMISS). Concurrent validity of the HR-OMISS was very good since we found statistically significant negative correlation between the HR-OMISS and the Trust in Scientists Scale (r = -0.330, p-value < 0.001), and the single-item scientists confidence scale (r = -0.258, p-value < 0.001). Moreover, we found a positive correlation between the HR-OMISS and the CMQ (r = 0.118, p-value = 0.072) and the single item conspiracy belief (r = 0.074, p-value = 0.260). The HR-OMISS showed known-groups validity since the mean score for healthcare workers with a MSc diploma (25.6) was lower than those without a MSc diploma (29.6), (p-value = 0.002). CONCLUSIONSThe HR-OMISS is a valid and reliable tool to measure levels of health-related online misinformation susceptibility.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.