OBJECTIVES : Understanding individual’s treatment related decision and choice behavior critically influences strategic planning of Health Human Resource and equitable distribution of state medicine. Need based perception of healthcare utilization and demographic determinants in standard conceptual models loosely incorporated social and cognitive components and have not addressed personality trait. This study not only separately addresses these factors to understand their relative importance, but also tries to integrate them into a statistically valid structure.

METHODS : For this cross sectional study with sample size n=300, a 30 point questionnaire having 7 point Likert Scale and dichotomous scale has been used related to demographic variables, disease burden, social, cognitive and personality trait items, which are later factorised. Results are analyzed using IBM SPSS ver.23 and Amos ver. 20. Effect of individual factors is measured by logistic and multiple regression, as applicable. The integral model is formulated through path analysis including holistically significant factors only.

RESULTS : 40.3% responders prefer CAM with 51.3% actual usage. Male gender (p=0.026), higher education (p<0.001), low disease burden (p=0.043) and making decision in-group (p<0.001) choose CAM. Cognition of less adverse reaction and omnipotence of CAM is also decision driver. The integrated model developed through path analysis shows social effect has positive (R=0.87, p<0.001) and disease burden has negative (R=-0.99, p<0.001) likelihood estimate on CAM preference score. Among personality traits, Extraversion has positive (B=0.693, p<0.001) and Conscientiousness (B=-.306, p<0.001) has negative effect on CAM usage and also, similar effect is observed on individual’s preference score, in the integral model.

CONCLUSIONS : Separately demographic, cognitive, social factors, disease burden and personality traits influence individual’s treatment related decision making process but the integrated path model shows that personality trait, followed by social effect and disease burden are most significant. Such integrated treatment related decision making process will contribute to the betterment of existing conceptual models of healthcare utilization.