Abstract Purpose: To identify within demographic features and theoretical models of health behavior, the variables demonstrating differences in the behaviors, beliefs, attitudes, associations, and capacities of sporadic (non-adherent) and persistent (adherent) mammographic screeners for the purpose of guiding future interventions to improve mammographic screening adherence. Procedures: A survey was designed and mailed to all screening-age women of one Bemidji Area tribe. The survey incorporated demographic questions, and questions designed to inform about salient features of respondents' health literacy, social networks, social support, social norms, planned behavior, and health beliefs. Prior to mailing, each survey was assigned a unique identifier and sealed in an envelope. Surveys were mailed to 1,554 women in manner that ensured anonymity of the women's responses and no potential for investigators to discern women's identity via their mailing addresses or other information. Self-report data from returned surveys was used to determine women's mammographic screening status as adherent with local screening guidelines (annual mammogram beginning at age 40 for women at average risk) or non-adherent. Responses for all demographic and theoretical models of health behavior were appropriately categorized and analyzed utilizing global tests of hypotheses. Inherent multicollinearity issues required a two-step process of factor analysis followed by a multivariate analysis of variance. Where themes (e.g., demographics, health literacy, etc.) and factors within themes were significant, a univariate analysis was conducted to ascertain specific questions and responses that significantly differentiated the non-adherent from adherent screeners. Summary of data: We found no significant differences in non-adherent and adherent screeners' responses to questions related to social networks or social norms. We did find that responses from these two groups did differ on demographic features as well as on aspects of health literacy, social support, planned behavior and health beliefs. o Demographic differences involved biopsy histories and employment status. o Differentiating health literacy variables involved recognition of certain terms (e.g., annual) and understanding concepts such as ultrasound and biopsy. o Social support variables that distinguished non-adherent from adherent screeners involved sources of information support, characteristics of providers of emotional support, and sources of emotional support (e.g., solitary or communal). o Planned behavior variables illuminating differences between the screening groups involved (in additions to self-reported screening behaviors): attitudes toward the behavior of obtaining mammograms, intentions to engage in screening, and control beliefs. o Health Beliefs variables distinguishing the two sets of screeners comprised responses to questions about perceived barriers, self-efficacy, and cues to action. Conclusions: Study findings point to opportunities for tribal health and Indian Health Service (IHS) providers and staff to intervene in two broad areas. 1. Some findings associated with social support, planned behavior, and health beliefs can be used to design patient intake forms to alert tribal health and IHS providers to current and potentially non-adherent. 2. Using this information, providers can design interventions to move non-adherent and potentially non-adherent women toward persistent mammographic screening participation. An intervention study will be funded by the Minnesota Department of Health through its Eliminating Health Disparities Initiative. Citation Format: Wesley O. Petersen, Ann M. Nicometo, Robert A. Vierkant, Corinna Sabaque. Elements of theoretical models of health behavior: Planning for breast cancer screening interventions in an American Indian tribe. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr B83.