Using the Health Belief Model to Assess the Impact of Latent Tuberculosis Infection  Health Education Video Towards Screening Adoption in Foreign-Born Persons Living in California

Using the Health Belief Model to Assess the Impact of Latent Tuberculosis Infection Health Education Video Towards Screening Adoption in Foreign-Born Persons Living in California | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Using the Health Belief Model to Assess the Impact of Latent Tuberculosis Infection Health Education Video Towards Screening Adoption in Foreign-Born Persons Living in California Juliana Uzoma Ojukwu, Tamara Stimatze This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3891838/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Tuberculosis (TB) disproportionately affects foreign-born persons from TB-endemic countries. Previous studies demonstrated that educational interventions effectively increased knowledge, perception, and latent tuberculosis infection (LTBI) screening in at-risk people. Given the high prevalence of LTBI and active TB cases and the large proportion of foreign-born individuals with low LTBI awareness residing in California, this study sought to evaluate the impact of video-based LTBI education in this population. Methods We evaluated the impact of a 5-minute LTBI educational video on participants using Health Belief Model (HBM) constructs using a pre- and post-test design. We enrolled 84 participants during the study period. Participants identified as (54%) women and 45% men, with 54.48 mean age, and participants identified as Asian (48%), White (37%), Hispanic/Latinx (13%), and Black/African American or Native Hawaiian/Pacific Islander (2%). Participants first completed the pre-survey, which consisted of the HBM LTBI Survey, followed by a demographic survey. Participants then watched the educational intervention video followed by the post-survey, which consisted of the HBM LTBI Survey. Results To assess the changes in HBM constructs, we ran six paired-sample t-tests and found a significant increase in perceived susceptibility, t (83) = 8.82, p < .001, perceived severity, t (83) = 2.06, p < .04, perceived benefits, t (83) = 3.33, p < .001 and behavioral intention, t (82) = 3.99, p < .001 with a significant decrease in perceived barriers, t (83) = -3.38, p < .001. To analyze the impact of the HBM constructs on behavioral intentions, we ran a multiple linear regression. Overall, the HBM accounted significantly in variance for behavioral intentions to engage in screening, F (5, 77) = 14.81, p < 0.001; with perceived susceptibility, t (81) = 2.64, p = 0.01, perceived severity t (81) = 2.69, p = 0.009, and self-efficacy t (81) = 3.05, p = 0.003 significantly predicting behavioral intentions for LTBI screening. Conclusions This project demonstrates the efficacy of health education videos in promoting awareness and screening for LTBI. The authors recommend using health educational videos in communities and healthcare facilities to create more knowledge, awareness, and engagement in LTBI screening. Latent tuberculosis infection. Video health education. Screening. Behavioral intentions. Health Belief Model. Foreign-born persons. Introduction Tuberculosis (TB) is a deadly bacterial infection, 2nd infectious killer after COVID-19, with about 2 billion people infected and 1.3 million deaths in 2020 globally [ 1 , 2 ]. TB cases declined significantly in the United States (US) from 10.4 per 100,000 persons in 1992 to 2.2 per 100,000 persons in 2020 [ 3 , 4 ]. Despite this progress, TB remains a public health concern that disproportionately impacts foreign-born persons, or "anyone who is not a US citizen by birth," in over 72% of TB cases, causing 526 deaths in 2019 and 7,174 new cases in 2020 [ 3 , 4 , 5 ]. Of these 7,174 cases, 1,703 were in California, recording an incidence rate of TB approximately 4.3 per 100,000 persons in 2020, about double the national average [ 6 ]. In addition to active disease, TB can be concealed, asymptomatic, and noncontagious, and this is called latent tuberculosis infection (LTBI). A person with LTBI does not have symptoms, cannot spread the disease to someone else, and is typically unaware of harboring the TB germ. Consequently, undiagnosed or untreated LTBI risks developing active TB [ 7 ], and LTBI is linked to 24.8% or 5.8 million of the newly diagnosed active TB cases, and 1.3 million died from TB in 2020 [ 2 , 1 ]. Over 80% of active TB cases in the US resulted from longstanding, untreated LTBI cases [ 3 ]. The National Health and Nutrition Examination Survey (NHANES) estimated that approximately 5% (16.5 million) of the US population has LTBI; about 21% are foreign-born persons [ 8 ]. According to Contra Costa Health Services (2021), more than 2 million Californians have LTBI, of which 1.8 million are foreign-born persons, of whom only 20% are aware of their LTBI, and only 12% are treated. The current estimate of LTBI burden indicates an extensive reservoir of individuals at risk of developing active TB. Untreated LTBI confers an estimated risk of reactivation to TB disease of 98 per 100,000 person-years among foreign-born persons [ 9 ]. Health Belief Model The HBM is a theoretical framework used to guide health education and designed to explain factors impacting the performance of health behaviors [ 10 , 11 ], such as cancer screening [ 12 ], exercise [ 13 ], healthy eating [ 14 ], and LTBI or active TB [ 15 , 16 , 17 , 18 , 19 , 20 ]. The HBM asserts that to engage in healthy behaviors, the groups must exhibit the simultaneous occurrence of perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action [ 21 ]. The HBM is utilized in designing health promotion and education materials and evaluating the impact of health education programs on changing health behaviors, such as TB and LTBI screening. Educational Interventions and Increased Screening Health education interventions are valuable programs designed to increase people's knowledge and understanding regarding health behaviors and outcomes. Many health education interventions address Health Belief Model (HBM) constructs [ 12 , 13 , 14 , 15 ]. These in-person and video-based interventions have proven effective in increasing healthy behavior (or decreasing risky health behaviors) in LTBI or active TB [ 15 , 16 , 17 , 18 , 19 , 20 ]. In-person health education interventions involve face-to-face interaction between the health educator and the primary audience. In-person interventions deliver health information and advice capable of raising awareness among the intended group and adopting behavior change. However, the reach is not broad, suitable for one-on-one and small audiences, and requires many human and material resources [ 16 , 19 ]. Video education is an alternative option when in-person education is challenging to complete. While videos are less personal, they are more accessible and can reach a wider audience. Video education for active TB and LTBI has effectively increased TB knowledge and screening rates [ 15 , 17 , 18 , 20 ], especially in rural or hard-to-reach communities [ 22 ]. Gao and colleagues (2018) conducted a study to evaluate the acceptability of online video content and tuberculosis knowledge scores at the two Provincial TB clinics in Greater Vancouver, Canada, where 80% of TB patients were foreign-born individuals from countries with high TB incidences. This study used an HBM framework to guide the educational content and assessments. In Gao and colleagues' study, participants accessed the LTBI educational video as part of the patient reminder system. The participants self-reported watching the video as "viewers" or not watching the videos as "non-viewers." The LTBI educational video contained information about HBM constructs, such as perceived benefits (e.g., "The benefit of treating LTBI is to prevent TB disease"), perceived barriers (e.g., "Do you think the BCG vaccine completely protects you from TB for your whole life?"), perceived severity (e.g., "Do you think active TB disease is a serious health concern?"), perceived susceptibility (e.g., travel history, country of origin, and immunosuppressive diseases such as cancer, diabetes, or HIV risks). The results significantly impacted perceived susceptibility, severity, benefits, and self-efficacy scores. Those who viewed the video indicated an increased perceived susceptibility, perceived severity, perceived benefits, and increased self-efficacy for treating LTBI. However, there was no change or significant change in perceived barrier scores between viewers and non-viewers. Eighty-four percent of viewers rated the video helpful, and 89% might recommend the video to others and facilitate behavior change toward LTBI screening. The authors concluded that the online educational video showed promise as a tool to supplement clinical care. Given the high prevalence of LTBI and active TB cases in California and the large proportion of foreign-born individuals living in California with low LTBI awareness, through this project and the previous results of online educational videos, this study sought to evaluate the impact video-based LTBI education for foreign-born individuals residing in California. We assessed the effect of the video-based LTBI education via the HBM constructs of perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and behavioral intentions for LTBI screening. A research question guided this project, "Does a video-based LTBI health education impact the perceived susceptibility, severity, benefits, barriers, and self-efficacy of the foreign-born individuals living in California?" We hypothesized: 1) a significant increase in perceived susceptibility, perceived severity, perceived benefits, and self-efficacy following the video-based LTBI education, 2) a significant decrease in perceived barriers following the video-based LTBI education, 3) a significant increase in behavioral intentions to adopt LTBI screening following the video-based education, and 4) that a model containing the HBM construct (e.g., perceived susceptibility, severity, benefits, barriers, and self-efficacy scores) would significantly predict behavioral intentions to get screened for LTBI in foreign-born individuals living in California. Methods Participants We recruited participants for this study through an online recruitment panel in Qualtrics. To be eligible for the study, participants had to be 18 years of age or older, foreign-born, living in California, of all genders, socioeconomic classes, and educational levels, and able to read and understand the English Language. Qualtrics targeted eligible participants identifying as foreign-born individuals residing in California from April 2023 to May 2023. Qualtrics uses various recruitment platforms, such as website intercept recruitment, member referrals, email lists, gaming sites, customer loyalty web portals, permission-based networks, and social media. Before joining the study, Qualtrics determined the compensation amount and type with eligible participants based on their reward preferences and the time to complete the survey. Participants chose the category of reward they wanted, such as Skye miles, points to their favorite retail stores, or gift cards. Participants accessed the questionnaires and video via Qualtrics after they read and signed the informed consent posted on the platform. Materials HBM LTBI Survey The HBM LTBI Survey is designed to measure five HBM constructs about LTBI. This survey was adapted from the "TB Clinical Patient Survey" [ 15 ] and the HBM Scale [ 23 ]. The survey included measures for perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and behavioral intentions to screen for LTBI. All survey items were rated on a five-point Likert scale, with one being "Strongly Disagree" and five being "Strongly Agree." The subscale for perceived susceptibility included five questions designed to measure how likely the participants are to contract LTBI, such as "I have an increased risk of having Sleeping TB because I was born outside of the United States." The subscale for perceived severity included six questions designed to measure the person's belief that LTBI is life-threatening and needs attention, such as "Sleeping TB may lead to death." The subscale for perceived benefits included five questions designed to measure a person's belief that adopting LTBI screening will reduce the possibility of acquiring tuberculosis disease, such as, "Screening can find Sleeping TB germs early before they develop into Active TB." The subscale for perceived barriers included eight questions designed to measure a person's belief that LTBI screening will not be too expensive or harmful or pose an obstacle to averting tuberculosis disease, such as, "People who had the BCG vaccine (a vaccine for TB and widely held barrier by foreign-born persons), are completely protected from TB for their whole life and do not need TB screening. " The subscale for self-efficacy included five questions designed to measure an individual's confidence in their ability to undergo and sustain LTBI screening with little or no help from others, such as, "I feel confident I can find a health center providing a Sleeping TB screening." The subscale for behavioral intentions included three questions designed to measure the person's willingness to adopt TB screening within a short time frame, such as, "I plan to receive a Sleeping TB screening in 3 months." Demographic Survey The demographic survey comprised 18 multiple-choice and fill-in-the-blank questions about participants' age, gender, marital status, race and ethnicity, income, education, country of birth, travel history outside the US, age at immigration into the US, and English proficiency. Others included past LTBI screening, diagnosis and-/or treatment of LTBI and-/or Active TB disease, family history of TB, and healthcare work history. LTBI Educational Video The LTBI Educational Video is a 5-minute video portraying cartoon-like graphics and narration covering content about LTBI and TB. The video discusses the differences between LTBI and Active TB disease, epidemiology, transmission, screening of LTBI and Active TB disease, key barriers such as prior BCG vaccine limiting LTBI screening, LTBI preventive measures, screening benefits, consequences of lack of screening, and information on where to get LTBI screening in CA. The LTBI Education Video was created by the research team members Juliana Ojukwu and Tamara Stimatze in collaboration with NMSU Creative Media Institute students Olvaro Oliva, TJ Rios, Edward Bakshi, and Derek Chase. Procedure Before conducting this study, the New Mexico State University Institutional Review Board reviewed and approved all recruitment procedures, materials, and experimental procedures. Once recruited, eligible participants read the informed consent and indicated consent by checking a box stating they consented. A pilot study of 10 participants was carried out to assess the clarity and feasibility of the study. The researchers corrected all errors in the survey flow and performed another small pilot of 10 participants. Qualtrics assigned every participant a unique identifier code to exclude duplicating surveys. Participants first completed the HBM LTBI survey, followed by the demographic survey. Afterward, the participants watched a 5-minute video on Sleeping TB (LTBI) and Active TB. After the video, the participants completed the same HBM LTBI survey. The research lasted approximately 30 minutes per participant. Survey recruitment began on April 4, 2023, and ended on April 25, 2023, and 84 participants completed the study. The recruited eligible participants read the informed consent (Appendix B) and indicated consent by checking a box stating they consent to participate and continuing to the next page. A pilot study of 10 participants was carried out to assess the clarity and feasibility of the study. Data Analysis The researchers used SPSS Software [ 24 ] to analyze survey data. We conducted descriptive analyses of the mean, median, standard deviation, and percentages for socioeconomic status and displayed the demographic data in a table. We used a p-value < 0.05 as a reference value to determine statistical significance. To assess the impact of the education video, we ran six paired-sample t-tests to evaluate the changes in perceived susceptibility, severity, benefits, barriers, self-efficacy, and behavioral intentions. We ran a multiple linear regression to analyze the impact of the health belief model constructs on behavioral intentions to engage in TB screening. We ensured all assumptions were met before running the multiple regression analysis. The predictors in the regression model consisted of post-scores for perceived susceptibility, perceived severity, perceived benefit, perceived barriers, and self-efficacy. Results Eighty-four participants were recruited for this study. As shown in Table 1 , forty-four participants (54%) were women, and 45% were men. Participants ranged in age from 21 to 86 years old, with a mean age of 54.48 years and a median of 64 years. Thirty-nine participants (48%) were Asian, 30 (37%) were White, 11 (13%) were Hispanic/Latinx, and an additional 2% were either Black/African American or Native Hawaiian/Pacific Islander. More than half (54.2%) were married, 27.7% were single, 8.4% divorced, and 4.8% were widowed or had domestic partners. Most participants (90%) had at least some college: 60% reported having four or more years of college, 6.0% had a high school diploma or GED, and 3.6% had a lower-than-high school education. Forty-six (56%) reported incomes between $ 35,000 and $ 100,000, while 20 (24%) reported incomes above $ 100,000, and 17 (20%) reported incomes below $ 35,000. 21.7% were within the highest annual income level (50,000–74,999 USD), and 3.6% were within the lowest (15,000–24,999 USD). Regarding country of birth, 32 countries were represented in our participant sample. As shown in Table 2 , 54 (65%) of the participants were born in countries with high risks/rates of TB, while the remaining 29 (35%) were born in countries with low risks/rates of TB. All participants completed the survey in English. Table 1 Sociodemographic characteristics of participants (N = 84) Participant characteristics Mean (SD) Median (Range) Age (years); N = 78 54.48 (18.08) 64 (21–86) Gender; N = 82 N (%) Female 44 (53.7) Male 37 (45.1) Transgender 1 (0.9) Race/Ethnicity; N = 82 N (%) Asian (e.g., Chinese, Filipino, Korean, Indian, etc.) 39 (47.6) White/Caucasian 30 (36.6) Hispanic or Latinx 11 (13.4) Black/African American 1 (1.2) Native Hawaiian/Pacific Islanders 1 (1.2) Marital status; N = 83 N (%) Married 45 (54.2) Single 23 (27.7) Divorced 7 (8.4) Widowed 4 (4.8) Domestic Partnership 4 (4.8) Educational Level; N = 84 N (%) College ≥ 4 years 50 (59.5) College 1–3 years 26 (31.0) Grade 12 or GED 5 (6.0) Others 2 (2.4) Grade 9–11 1 (1.2) Income Level; N = 83 N (%) 200,000 and over 5 (6.0) 150,000-199,999 8 (9.6) 100,000-149,999 7 (8.4) 75,000–99,999 16 (19.3) 50,000–74,999 18 (21.7) 35,000–49,999 12 (14.5) 25,000–34,999 10 (12.0) 15,000–24,999 3 (3.6) Under 15,000 4 (4.8) Table 2 Participant's Country of Birth (N = 83) Country of Birth; N = 83 High-risk countries; N = 54 Asian Countries; N = 40 N (%) The Philippines 13 (15.7) Taiwan 6 (7.2) China 5 (6.0) Hong Kong 5 (6.0) Vietnam 4 (4.8) Bangladesh 2 (2.4) India, Indonesia, Japan, Korea & Singapore (1 each) 5 (6.0) Central & South American Countries; N = 14 N (%) Mexico 6 (7.2) Argentina 2 (2.4) Venezuela 2 (2.4) Colombia, Costa Rica, Cuba & Jamaica (1 each) 4 (4.8) Low-risk countries; N = 29 European Countries; N = 27 N (%) Canada 4 (4.8) Russia 4 (4.8) Germany 3 (3.6) France 3 (3.6) Spain 3 (3.6) Sweden, Ukraine & United Kingdom (1 each) 3 (3.6) Hungary, Malta, Poland & Portugal (1 each) 3 (3.6) Middle East Countries; N = 2 Iran, Jordan (1 each) 2 (2.4) We saw significant results in five out of the six measures of interest (Table 3 ). We found a significant increase in perceived susceptibility, t (83) = 8.824, p < .001, perceived severity, t (83) = 2.057, p = .043, and perceived benefits, t (83) = 3.331, p < .001. Our analysis also showed a significant decrease in perceived barriers, t (83) = -3.383, p < .001. Behavioral intentions also increased after watching the video, t (82) = 3.994, p .05. Table 3 Paired sample t-test results of pre-and post-video scores, reported as mean differences Measure Mean Difference t df p -value Perceived susceptibility 0.70 8.82 83 < .001*** Perceived severity 0.12 2.06 83 < .043* Perceived benefits 0.25 3.33 83 < .001*** Perceived barriers -0.23 -3.38 83 < .001*** Self-efficacy 0.12 1.78 83 0.08 Behavioral intentions 0.34 3.99 82 < .001*** Significance values: * p < 0.05, ** p < 0.01, *** p < 0.001 We used multiple linear regression to assess the predictive value of HBM and constructs to behavioral intentions to engage in LTBI screening (Table 4 ). The model significantly predicted behavioral intentions to engage in LTBI screening, F(5, 77) = 14.81, p < 0.001. We found that perceived susceptibility, t(81) = 2.64, p = 0.01, perceived severity, t(81) = 2.69, p = 0.009, and self-efficacy, t(81) = 3.05, p = 0.003, significantly predicted behavioral intentions to engage in LTBI screening. Perceived benefits and barriers did not significantly predict behavioral intentions to engage in LTBI screening. Table 4 Multiple regression results showing the impact of HBM constructs on behavioral intentions toward LTBI screening Model Unstandardized B Coefficients Standard Error Standardized Coefficients B T p-value (Constant) -1.391 .612 -2.272 .026* Post Self Efficacy .557 .183 .357 3.047 .003** Post Perceived Barriers .218 .111 .172 1.954 .054 Post Perceived Benefits − .246 .197 − .165 -1.251 .215 Post Perceived Severity .423 .157 .301 2.686 .009** Post Perceived Susceptibility .381 .144 .292 2.638 .010** Significance values: * p < 0.05, ** p < 0.01, *** p < 0.001 Discussion The LTBI educational video proved an effective intervention to increase perceived susceptibility, perceived severity, and perceived benefits and decrease perceived barriers of LTBI. The educational video increases behavioral intentions to screen for LTBI in California's foreign-born populations. Lastly, the HBM proved an efficient and practical framework for assessing and predicting changes in behavioral intentions to screen for LTBI. These results provide further evidence of the efficacy of educational videos and their potential impact as tools to increase awareness and behavioral intentions to screen [ 15 , 17 , 18 , 20 , 25 ]. This study did not document a significant increase in scores on self-efficacy following the educational intervention. These findings are contrary to similar studies, which reported changes in self-efficacy after watching a health education video on LTBI [ 15 , 20 , 25 ]. This inconsistent result is likely due to different definitions and measurements around self-efficacy. Gao and colleagues (2018) assessed self-efficacy by asking attitudinal-based questions about gaining LTBI knowledge and LTBI treatment, whereas Wieland and colleagues (2013) assessed self-efficacy by asking participants yes and no questions, again measuring knowledge on accessing information and screening services for TB. This project defined self-efficacy as an individual's confidence in their ability to obtain and engage in LTBI screening [ 21 , 26 ]. This definition and approach may fail to consider external factors impacting one's ability to access and engage in screening, such as differential access to health care, availability and proximity to healthcare facilities, preferred language, and immigration status [ 27 ]. These external factors likely impacted participants' self-efficacy. Future research should carefully consider the role of external factors and measurement choices around self-efficacy to ensure an appropriate measure is selected. Overall, educational videos on LTBI show efficacy in increasing knowledge and intention to screen. While education videos are less personal, they are more accessible. Educational videos promise to reach a wider audience, including those living in hard-to-reach rural areas [ 17 , 22 ]. Educational videos are customizable, and information can be translated into various languages to increase accessibility further [ 15 ]. Additionally, video format can increase education uptake in individuals with low health literacy, special needs, youths and adolescents, and refugee and migrant communities [ 25 , 28 , 29 , 30 ] and provide standardized messages. Its delivery can be in various forms, including cartoon format, as in our study, or videos of real people talking about a health-related action via DVD, USB, media file, and streaming video [ 17 , 31 , 32 ]. Lastly, educational videos can provide essential health education in waiting areas, significantly increasing health knowledge [ 33 ] and allowing health providers to focus on other treatment areas without increasing the overburdening demands on healthcare staff and medical providers [ 34 ]. The waiting room is an unavoidable component of health care, which can provide an opportunity to deliver health education messages to patients. These results and additional considerations indicate that educational videos can be crucial in promoting TB and LTBI screening in foreign-born populations, which helps reduce TB infection and rates in the United States. Declarations Competing Interest. The authors have no competing interests to disclose. Ethical Approval. The Institutional Review Board of New Mexico State University approved the study. Consent to Participate. Informed consent was obtained from all participants. Authors' contributions JO conceived the study and design, conducted the literature review, participated in data collection, collaborated with data analysis, drafted the original manuscript, and participated in editing the final version. TS edited the literature review, supervised and assisted in data collection, and participated in and edited the original manuscript and final version. TS contributed and supervised the study design, collaborated with and conducted statistical analysis and interpretation, and provided overall guidance and supervision. All authors read and approved the final manuscript. Funding The research was a thesis project funded by the Public Health Sciences Department at New Mexico State University. The funder played no role in the conceptualization, design, data collection, analysis, and interpretation of the findings. 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Online J public health Inf. 2012;4(3). https://doi.org/10.5210/ojphi.v4i3.4321 . Hieftje K, Edelman EJ, Camenga DR, Fiellin LE. Electronic media–based health interventions promoting behavior change in youth: a systematic review. JAMA Pediatr. 2013;167(6):574–80. https://doi.org/10.1001/jamapediatrics.2013.1095 . Johnson C. Development and pilot testing of a healthy eating video-supported program for adults with developmental disabilities. Can J Diet Pract Res. 2014;75(3):140–4. https://doi.org/10.3148/cjdpr-2014-002 . O'Mara B. Social media, digital video and health promotion in a culturally and linguistically diverse Australia. Health Promot Int. 2013;28(3):466–76. https://doi.org/10.1093/heapro/das014 . Abed MA, Himmel W, Vormfelde S, Koschack J. Video-assisted patient education to modify behavior: a systematic review. Patient Educ Couns. 2014;97(1):16–22. https://doi.org/10.1016/j.pec.2014.06.015 . Tuong W, Larsen ER, Armstrong AW. Videos to influence: a systematic review of effectiveness of video-based education in modifying health behaviors. J Behav Med. 2014;37:218–33. https://doi.org/10.1007/s10865-012-9480-7 . McNab M, Skapetis T. Why video health education messages should be considered for all dental waiting rooms. PLoS ONE. 2019;14(7):e0219506. https://doi.org/10.1371/journal.pone.0219506 . Sabri S, Adiprabowo VDA. Visual narrative of the pandemic as a form of health communication in the digital age. COMMICAST. 2023;4(1):81–90. https://doi.org/10.12928/commicast.v4i1.7670 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3891838","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270398471,"identity":"ca6c2f6b-726a-46de-84d9-217308663ffa","order_by":0,"name":"Juliana Uzoma Ojukwu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYBACxgaGBCBmkGOQYGA8QJIWY6AWBogWNuK0MSQ2EK2Fub3hmeTMtsPp26UbGA78qLFJ3C7fY8D4peIwbht6DqRJbmw7nLtzzgGGgz3H0hJ3tvEYMMucwaNlRkKa5MNth3M33EhgOMDbcDhxwzGgFsm2NIJa0g2AWg7+JVrLxm2HE0BaDsNsYfzYZoPPL8mWM/+lG+6ckdhwWOZYmvGGY2kFhxnO4NZi2N6TeLPnjLW8uUTywYdvamxkNxw+vPHhjwoJ3FoaeBLADANw9IABh8FhHpwaGBjkGdgPQLXAAfsDxh94tIyCUTAKRsGIAwAaFWHh+0QNjgAAAABJRU5ErkJggg==","orcid":"","institution":"New Mexico State University","correspondingAuthor":true,"prefix":"","firstName":"Juliana","middleName":"Uzoma","lastName":"Ojukwu","suffix":""},{"id":270398472,"identity":"5f96de53-5eea-4882-ac6d-ed45ce2a0d19","order_by":1,"name":"Tamara Stimatze","email":"","orcid":"","institution":"New Mexico State University","correspondingAuthor":false,"prefix":"","firstName":"Tamara","middleName":"","lastName":"Stimatze","suffix":""}],"badges":[],"createdAt":"2024-01-23 18:44:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3891838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3891838/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66688652,"identity":"15c96cad-0a49-4c3f-aece-b19a5b856ca9","added_by":"auto","created_at":"2024-10-15 13:39:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":654935,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3891838/v1/3e94de5f-48c3-4a68-afb3-655c9dafdc8f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Using the Health Belief Model to Assess the Impact of Latent Tuberculosis Infection Health Education Video Towards Screening Adoption in Foreign-Born Persons Living in California","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTuberculosis (TB) is a deadly bacterial infection, 2nd infectious killer after COVID-19, with about 2\u0026nbsp;billion people infected and 1.3\u0026nbsp;million deaths in 2020 globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. TB cases declined significantly in the United States (US) from 10.4 per 100,000 persons in 1992 to 2.2 per 100,000 persons in 2020 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Despite this progress, TB remains a public health concern that disproportionately impacts foreign-born persons, or \"anyone who is not a US citizen by birth,\" in over 72% of TB cases, causing 526 deaths in 2019 and 7,174 new cases in 2020 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Of these 7,174 cases, 1,703 were in California, recording an incidence rate of TB approximately 4.3 per 100,000 persons in 2020, about double the national average [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to active disease, TB can be concealed, asymptomatic, and noncontagious, and this is called latent tuberculosis infection (LTBI). A person with LTBI does not have symptoms, cannot spread the disease to someone else, and is typically unaware of harboring the TB germ. Consequently, undiagnosed or untreated LTBI risks developing active TB [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and LTBI is linked to 24.8% or 5.8\u0026nbsp;million of the newly diagnosed active TB cases, and 1.3\u0026nbsp;million died from TB in 2020 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Over 80% of active TB cases in the US resulted from longstanding, untreated LTBI cases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe National Health and Nutrition Examination Survey (NHANES) estimated that approximately 5% (16.5\u0026nbsp;million) of the US population has LTBI; about 21% are foreign-born persons [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. According to Contra Costa Health Services (2021), more than 2\u0026nbsp;million Californians have LTBI, of which 1.8\u0026nbsp;million are foreign-born persons, of whom only 20% are aware of their LTBI, and only 12% are treated. The current estimate of LTBI burden indicates an extensive reservoir of individuals at risk of developing active TB. Untreated LTBI confers an estimated risk of reactivation to TB disease of 98 per 100,000 person-years among foreign-born persons [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eHealth Belief Model\u003c/h3\u003e\n\u003cp\u003eThe HBM is a theoretical framework used to guide health education and designed to explain factors impacting the performance of health behaviors [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], such as cancer screening [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], exercise [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], healthy eating [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and LTBI or active TB [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The HBM asserts that to engage in healthy behaviors, the groups must exhibit the simultaneous occurrence of perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The HBM is utilized in designing health promotion and education materials and evaluating the impact of health education programs on changing health behaviors, such as TB and LTBI screening.\u003c/p\u003e\n\u003ch3\u003eEducational Interventions and Increased Screening\u003c/h3\u003e\n\u003cp\u003eHealth education interventions are valuable programs designed to increase people's knowledge and understanding regarding health behaviors and outcomes. Many health education interventions address Health Belief Model (HBM) constructs [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These in-person and video-based interventions have proven effective in increasing healthy behavior (or decreasing risky health behaviors) in LTBI or active TB [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn-person health education interventions involve face-to-face interaction between the health educator and the primary audience. In-person interventions deliver health information and advice capable of raising awareness among the intended group and adopting behavior change. However, the reach is not broad, suitable for one-on-one and small audiences, and requires many human and material resources [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVideo education is an alternative option when in-person education is challenging to complete. While videos are less personal, they are more accessible and can reach a wider audience. Video education for active TB and LTBI has effectively increased TB knowledge and screening rates [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], especially in rural or hard-to-reach communities [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGao and colleagues (2018) conducted a study to evaluate the acceptability of online video content and tuberculosis knowledge scores at the two Provincial TB clinics in Greater Vancouver, Canada, where 80% of TB patients were foreign-born individuals from countries with high TB incidences. This study used an HBM framework to guide the educational content and assessments.\u003c/p\u003e \u003cp\u003eIn Gao and colleagues' study, participants accessed the LTBI educational video as part of the patient reminder system. The participants self-reported watching the video as \"viewers\" or not watching the videos as \"non-viewers.\" The LTBI educational video contained information about HBM constructs, such as perceived benefits (e.g., \"The benefit of treating LTBI is to prevent TB disease\"), perceived barriers (e.g., \"Do you think the BCG vaccine completely protects you from TB for your whole life?\"), perceived severity (e.g., \"Do you think active TB disease is a serious health concern?\"), perceived susceptibility (e.g., travel history, country of origin, and immunosuppressive diseases such as cancer, diabetes, or HIV risks). The results significantly impacted perceived susceptibility, severity, benefits, and self-efficacy scores. Those who viewed the video indicated an increased perceived susceptibility, perceived severity, perceived benefits, and increased self-efficacy for treating LTBI. However, there was no change or significant change in perceived barrier scores between viewers and non-viewers. Eighty-four percent of viewers rated the video helpful, and 89% might recommend the video to others and facilitate behavior change toward LTBI screening. The authors concluded that the online educational video showed promise as a tool to supplement clinical care.\u003c/p\u003e \u003cp\u003eGiven the high prevalence of LTBI and active TB cases in California and the large proportion of foreign-born individuals living in California with low LTBI awareness, through this project and the previous results of online educational videos, this study sought to evaluate the impact video-based LTBI education for foreign-born individuals residing in California. We assessed the effect of the video-based LTBI education via the HBM constructs of perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and behavioral intentions for LTBI screening. A research question guided this project, \"Does a video-based LTBI health education impact the perceived susceptibility, severity, benefits, barriers, and self-efficacy of the foreign-born individuals living in California?\" We hypothesized: 1) a significant increase in perceived susceptibility, perceived severity, perceived benefits, and self-efficacy following the video-based LTBI education, 2) a significant decrease in perceived barriers following the video-based LTBI education, 3) a significant increase in behavioral intentions to adopt LTBI screening following the video-based education, and 4) that a model containing the HBM construct (e.g., perceived susceptibility, severity, benefits, barriers, and self-efficacy scores) would significantly predict behavioral intentions to get screened for LTBI in foreign-born individuals living in California.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eWe recruited participants for this study through an online recruitment panel in Qualtrics. To be eligible for the study, participants had to be 18 years of age or older, foreign-born, living in California, of all genders, socioeconomic classes, and educational levels, and able to read and understand the English Language. Qualtrics targeted eligible participants identifying as foreign-born individuals residing in California from April 2023 to May 2023. Qualtrics uses various recruitment platforms, such as website intercept recruitment, member referrals, email lists, gaming sites, customer loyalty web portals, permission-based networks, and social media. Before joining the study, Qualtrics determined the compensation amount and type with eligible participants based on their reward preferences and the time to complete the survey. Participants chose the category of reward they wanted, such as Skye miles, points to their favorite retail stores, or gift cards. Participants accessed the questionnaires and video via Qualtrics after they read and signed the informed consent posted on the platform.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eHBM LTBI Survey\u003c/h2\u003e \u003cp\u003eThe HBM LTBI Survey is designed to measure five HBM constructs about LTBI. This survey was adapted from the \"TB Clinical Patient Survey\" [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and the HBM Scale [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The survey included measures for perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and behavioral intentions to screen for LTBI. All survey items were rated on a five-point Likert scale, with one being \"Strongly Disagree\" and five being \"Strongly Agree.\"\u003c/p\u003e \u003cp\u003eThe subscale for \u003cb\u003eperceived susceptibility\u003c/b\u003e included five questions designed to measure how likely the participants are to contract LTBI, such as \"I have an increased risk of having Sleeping TB because I was born outside of the United States.\" The subscale for \u003cb\u003eperceived severity\u003c/b\u003e included six questions designed to measure the person's belief that LTBI is life-threatening and needs attention, such as \"Sleeping TB may lead to death.\" The subscale for \u003cb\u003eperceived benefits\u003c/b\u003e included five questions designed to measure a person's belief that adopting LTBI screening will reduce the possibility of acquiring tuberculosis disease, such as, \"Screening can find Sleeping TB germs early before they develop into Active TB.\" The subscale for \u003cb\u003eperceived barriers\u003c/b\u003e included eight questions designed to measure a person's belief that LTBI screening will not be too expensive or harmful or pose an obstacle to averting tuberculosis disease, such as, \"People who had the BCG vaccine (a vaccine for TB and widely held barrier by foreign-born persons), are completely protected from TB for their whole life and do not need TB screening.\u003cb\u003e\"\u003c/b\u003e The subscale for \u003cb\u003eself-efficacy\u003c/b\u003e included five questions designed to measure an individual's confidence in their ability to undergo and sustain LTBI screening with little or no help from others, such as, \"I feel confident I can find a health center providing a Sleeping TB screening.\" The subscale for \u003cb\u003ebehavioral intentions\u003c/b\u003e included three questions designed to measure the person's willingness to adopt TB screening within a short time frame, such as, \"I plan to receive a Sleeping TB screening in 3 months.\"\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eDemographic Survey\u003c/h2\u003e \u003cp\u003eThe demographic survey comprised 18 multiple-choice and fill-in-the-blank questions about participants' age, gender, marital status, race and ethnicity, income, education, country of birth, travel history outside the US, age at immigration into the US, and English proficiency. Others included past LTBI screening, diagnosis and-/or treatment of LTBI and-/or Active TB disease, family history of TB, and healthcare work history.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eLTBI Educational Video\u003c/h2\u003e \u003cp\u003eThe LTBI Educational Video is a 5-minute video portraying cartoon-like graphics and narration covering content about LTBI and TB. The video discusses the differences between LTBI and Active TB disease, epidemiology, transmission, screening of LTBI and Active TB disease, key barriers such as prior BCG vaccine limiting LTBI screening, LTBI preventive measures, screening benefits, consequences of lack of screening, and information on where to get LTBI screening in CA. The LTBI Education Video was created by the research team members Juliana Ojukwu and Tamara Stimatze in collaboration with NMSU Creative Media Institute students Olvaro Oliva, TJ Rios, Edward Bakshi, and Derek Chase.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003eBefore conducting this study, the New Mexico State University Institutional Review Board reviewed and approved all recruitment procedures, materials, and experimental procedures. Once recruited, eligible participants read the informed consent and indicated consent by checking a box stating they consented. A pilot study of 10 participants was carried out to assess the clarity and feasibility of the study. The researchers corrected all errors in the survey flow and performed another small pilot of 10 participants. Qualtrics assigned every participant a unique identifier code to exclude duplicating surveys. Participants first completed the HBM LTBI survey, followed by the demographic survey. Afterward, the participants watched a 5-minute video on Sleeping TB (LTBI) and Active TB. After the video, the participants completed the same HBM LTBI survey. The research lasted approximately 30 minutes per participant. Survey recruitment began on April 4, 2023, and ended on April 25, 2023, and 84 participants completed the study. The recruited eligible participants read the informed consent (Appendix B) and indicated consent by checking a box stating they consent to participate and continuing to the next page. A pilot study of 10 participants was carried out to assess the clarity and feasibility of the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe researchers used SPSS Software [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] to analyze survey data. We conducted descriptive analyses of the mean, median, standard deviation, and percentages for socioeconomic status and displayed the demographic data in a table. We used a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as a reference value to determine statistical significance.\u003c/p\u003e \u003cp\u003eTo assess the impact of the education video, we ran six paired-sample t-tests to evaluate the changes in perceived susceptibility, severity, benefits, barriers, self-efficacy, and behavioral intentions. We ran a multiple linear regression to analyze the impact of the health belief model constructs on behavioral intentions to engage in TB screening. We ensured all assumptions were met before running the multiple regression analysis. The predictors in the regression model consisted of post-scores for perceived susceptibility, perceived severity, perceived benefit, perceived barriers, and self-efficacy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eEighty-four participants were recruited for this study. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, forty-four participants (54%) were women, and 45% were men. Participants ranged in age from 21 to 86 years old, with a mean age of 54.48 years and a median of 64 years. Thirty-nine participants (48%) were Asian, 30 (37%) were White, 11 (13%) were Hispanic/Latinx, and an additional 2% were either Black/African American or Native Hawaiian/Pacific Islander. More than half (54.2%) were married, 27.7% were single, 8.4% divorced, and 4.8% were widowed or had domestic partners.\u003c/p\u003e \u003cp\u003eMost participants (90%) had at least some college: 60% reported having four or more years of college, 6.0% had a high school diploma or GED, and 3.6% had a lower-than-high school education. Forty-six (56%) reported incomes between \u003cspan\u003e$\u003c/span\u003e35,000 and \u003cspan\u003e$\u003c/span\u003e100,000, while 20 (24%) reported incomes above \u003cspan\u003e$\u003c/span\u003e100,000, and 17 (20%) reported incomes below \u003cspan\u003e$\u003c/span\u003e35,000. 21.7% were within the highest annual income level (50,000\u0026ndash;74,999 USD), and 3.6% were within the lowest (15,000\u0026ndash;24,999 USD).\u003c/p\u003e \u003cp\u003eRegarding country of birth, 32 countries were represented in our participant sample. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, 54 (65%) of the participants were born in countries with high risks/rates of TB, while the remaining 29 (35%) were born in countries with low risks/rates of TB. All participants completed the survey in English.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics of participants (N\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipant characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian (Range)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years); N\u0026thinsp;=\u0026thinsp;78\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.48 (18.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (21\u0026ndash;86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender; N\u0026thinsp;=\u0026thinsp;82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (53.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (45.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransgender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace/Ethnicity; N\u0026thinsp;=\u0026thinsp;82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian (e.g., Chinese, Filipino, Korean, Indian, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (47.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite/Caucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (36.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic or Latinx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack/African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian/Pacific Islanders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status; N\u0026thinsp;=\u0026thinsp;83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (54.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (27.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (8.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDomestic Partnership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level; N\u0026thinsp;=\u0026thinsp;84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege\u0026thinsp;\u0026ge;\u0026thinsp;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (59.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege 1\u0026ndash;3 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (31.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade 12 or GED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade 9\u0026ndash;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome Level; N\u0026thinsp;=\u0026thinsp;83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200,000 and over\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150,000-199,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (9.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100,000-149,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (8.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75,000\u0026ndash;99,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (19.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50,000\u0026ndash;74,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (21.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35,000\u0026ndash;49,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (14.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,000\u0026ndash;34,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (12.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,000\u0026ndash;24,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnder 15,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant's Country of Birth (N\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry of Birth; N\u0026thinsp;=\u0026thinsp;83\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh-risk countries; N\u0026thinsp;=\u0026thinsp;54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAsian Countries; N\u0026thinsp;=\u0026thinsp;40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Philippines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (15.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (7.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHong Kong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVietnam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBangladesh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia, Indonesia, Japan, Korea \u0026amp; Singapore (1 each)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCentral \u0026amp; South American Countries; N\u0026thinsp;=\u0026thinsp;14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (7.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArgentina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVenezuela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia, Costa Rica, Cuba \u0026amp; Jamaica (1 each)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow-risk countries; N\u0026thinsp;=\u0026thinsp;29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEuropean Countries; N\u0026thinsp;=\u0026thinsp;27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRussia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweden, Ukraine \u0026amp; United Kingdom (1 each)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHungary, Malta, Poland \u0026amp; Portugal (1 each)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMiddle East Countries; N\u0026thinsp;=\u0026thinsp;2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIran, Jordan (1 each)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe saw significant results in five out of the six measures of interest (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We found a significant increase in perceived susceptibility, \u003cem\u003et\u003c/em\u003e (83)\u0026thinsp;=\u0026thinsp;8.824, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, perceived severity, \u003cem\u003et\u003c/em\u003e (83)\u0026thinsp;=\u0026thinsp;2.057, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.043, and perceived benefits, \u003cem\u003et\u003c/em\u003e (83)\u0026thinsp;=\u0026thinsp;3.331, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. Our analysis also showed a significant decrease in perceived barriers, \u003cem\u003et\u003c/em\u003e (83) = -3.383, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. Behavioral intentions also increased after watching the video, \u003cem\u003et\u003c/em\u003e (82)\u0026thinsp;=\u0026thinsp;3.994, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. However, there was no statistically significant difference between pre-and post-scores in self-efficacy, \u003cem\u003et\u003c/em\u003e (83)\u0026thinsp;=\u0026thinsp;1.775, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePaired sample t-test results of pre-and post-video scores, reported as mean differences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived susceptibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.043*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived benefits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived barriers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavioral intentions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSignificance values: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe used multiple linear regression to assess the predictive value of HBM and constructs to behavioral intentions to engage in LTBI screening (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The model significantly predicted behavioral intentions to engage in LTBI screening, F(5, 77)\u0026thinsp;=\u0026thinsp;14.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. We found that perceived susceptibility, t(81)\u0026thinsp;=\u0026thinsp;2.64, p\u0026thinsp;=\u0026thinsp;0.01, perceived severity, t(81)\u0026thinsp;=\u0026thinsp;2.69, p\u0026thinsp;=\u0026thinsp;0.009, and self-efficacy, t(81)\u0026thinsp;=\u0026thinsp;3.05, p\u0026thinsp;=\u0026thinsp;0.003, significantly predicted behavioral intentions to engage in LTBI screening. Perceived benefits and barriers did not significantly predict behavioral intentions to engage in LTBI screening.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple regression results showing the impact of HBM constructs on behavioral intentions toward LTBI screening\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnstandardized\u003c/p\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoefficients Standard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandardized Coefficients B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.026*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost Self Efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.003**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost Perceived Barriers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost Perceived Benefits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost Perceived Severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.009**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost Perceived Susceptibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.010**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSignificance values: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe LTBI educational video proved an effective intervention to increase perceived susceptibility, perceived severity, and perceived benefits and decrease perceived barriers of LTBI. The educational video increases behavioral intentions to screen for LTBI in California's foreign-born populations. Lastly, the HBM proved an efficient and practical framework for assessing and predicting changes in behavioral intentions to screen for LTBI. These results provide further evidence of the efficacy of educational videos and their potential impact as tools to increase awareness and behavioral intentions to screen [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study did not document a significant increase in scores on self-efficacy following the educational intervention. These findings are contrary to similar studies, which reported changes in self-efficacy after watching a health education video on LTBI [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This inconsistent result is likely due to different definitions and measurements around self-efficacy. Gao and colleagues (2018) assessed self-efficacy by asking attitudinal-based questions about gaining LTBI knowledge and LTBI treatment, whereas Wieland and colleagues (2013) assessed self-efficacy by asking participants yes and no questions, again measuring knowledge on accessing information and screening services for TB. This project defined self-efficacy as an individual's confidence in their ability to obtain and engage in LTBI screening [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This definition and approach may fail to consider external factors impacting one's ability to access and engage in screening, such as differential access to health care, availability and proximity to healthcare facilities, preferred language, and immigration status [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These external factors likely impacted participants' self-efficacy. Future research should carefully consider the role of external factors and measurement choices around self-efficacy to ensure an appropriate measure is selected.\u003c/p\u003e \u003cp\u003eOverall, educational videos on LTBI show efficacy in increasing knowledge and intention to screen. While education videos are less personal, they are more accessible. Educational videos promise to reach a wider audience, including those living in hard-to-reach rural areas [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Educational videos are customizable, and information can be translated into various languages to increase accessibility further [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, video format can increase education uptake in individuals with low health literacy, special needs, youths and adolescents, and refugee and migrant communities [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and provide standardized messages. Its delivery can be in various forms, including cartoon format, as in our study, or videos of real people talking about a health-related action via DVD, USB, media file, and streaming video [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Lastly, educational videos can provide essential health education in waiting areas, significantly increasing health knowledge [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and allowing health providers to focus on other treatment areas without increasing the overburdening demands on healthcare staff and medical providers [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The waiting room is an unavoidable component of health care, which can provide an opportunity to deliver health education messages to patients. These results and additional considerations indicate that educational videos can be crucial in promoting TB and LTBI screening in foreign-born populations, which helps reduce TB infection and rates in the United States.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interest.\u003c/strong\u003e The authors have no competing interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval.\u003c/strong\u003e The Institutional Review Board of New Mexico State University approved the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cstrong\u003eConsent to Participate.\u003c/strong\u003e Informed consent was obtained from all participants.\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJO conceived the study and design, conducted the literature review, participated in data collection, collaborated with data analysis, drafted the original manuscript, and participated in editing the final version.\u003c/p\u003e\n\u003cp\u003eTS edited the literature review, supervised and assisted in data collection, and participated in and edited the original manuscript and final version. TS contributed and supervised the study design, collaborated with and conducted statistical analysis and interpretation, and provided overall guidance and supervision.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was a thesis project funded by the Public Health Sciences Department at New Mexico State University. The funder played no role in the conceptualization, design, data collection, analysis, and interpretation of the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. (2021). End TB. 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Video health education. Screening. Behavioral intentions. Health Belief Model. Foreign-born persons.","lastPublishedDoi":"10.21203/rs.3.rs-3891838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3891838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTuberculosis (TB) disproportionately affects foreign-born persons from TB-endemic countries. Previous studies demonstrated that educational interventions effectively increased knowledge, perception, and latent tuberculosis infection (LTBI) screening in at-risk people. Given the high prevalence of LTBI and active TB cases and the large proportion of foreign-born individuals with low LTBI awareness residing in California, this study sought to evaluate the impact of video-based LTBI education in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e We evaluated the impact of a 5-minute LTBI educational video on participants using Health Belief Model (HBM) constructs using a pre- and post-test design. We enrolled 84 participants during the study period. Participants identified as (54%) women and 45% men, with 54.48 mean age, and participants identified as Asian (48%), White (37%), Hispanic/Latinx (13%), and Black/African American or Native Hawaiian/Pacific Islander (2%). Participants first completed the pre-survey, which consisted of the HBM LTBI Survey, followed by a demographic survey. Participants then watched the educational intervention video followed by the post-survey, which consisted of the HBM LTBI Survey.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTo assess the changes in HBM constructs, we ran six paired-sample t-tests and found a significant increase in perceived susceptibility, \u003cem\u003et\u003c/em\u003e(83)\u0026thinsp;=\u0026thinsp;8.82, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, perceived severity, \u003cem\u003et\u003c/em\u003e(83)\u0026thinsp;=\u0026thinsp;2.06, p\u0026thinsp;\u0026lt;\u0026thinsp;.04, perceived benefits, \u003cem\u003et\u003c/em\u003e(83)\u0026thinsp;=\u0026thinsp;3.33, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 and behavioral intention, \u003cem\u003et\u003c/em\u003e(82)\u0026thinsp;=\u0026thinsp;3.99, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 with a significant decrease in perceived barriers, \u003cem\u003et\u003c/em\u003e(83) = -3.38, p\u0026thinsp;\u0026lt;\u0026thinsp;.001. To analyze the impact of the HBM constructs on behavioral intentions, we ran a multiple linear regression. Overall, the HBM accounted significantly in variance for behavioral intentions to engage in screening, \u003cem\u003eF\u003c/em\u003e(5, 77)\u0026thinsp;=\u0026thinsp;14.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; with perceived susceptibility, \u003cem\u003et\u003c/em\u003e(81)\u0026thinsp;=\u0026thinsp;2.64, p\u0026thinsp;=\u0026thinsp;0.01, perceived severity \u003cem\u003et\u003c/em\u003e(81)\u0026thinsp;=\u0026thinsp;2.69, p\u0026thinsp;=\u0026thinsp;0.009, and self-efficacy \u003cem\u003et\u003c/em\u003e(81)\u0026thinsp;=\u0026thinsp;3.05, p\u0026thinsp;=\u0026thinsp;0.003 significantly predicting behavioral intentions for LTBI screening.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis project demonstrates the efficacy of health education videos in promoting awareness and screening for LTBI. The authors recommend using health educational videos in communities and healthcare facilities to create more knowledge, awareness, and engagement in LTBI screening.\u003c/p\u003e","manuscriptTitle":"Using the Health Belief Model to Assess the Impact of Latent Tuberculosis Infection Health Education Video Towards Screening Adoption in Foreign-Born Persons Living in California","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-02 11:33:10","doi":"10.21203/rs.3.rs-3891838/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d817fae9-fa28-4383-90fa-849edc08dadd","owner":[],"postedDate":"February 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-15T13:38:50+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-02 11:33:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3891838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3891838","identity":"rs-3891838","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}