Factor Structure of the Multidimensional Health Perceptions Questionnaire in English- and Spanish-speakers

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Juengst, Angelle M. Sander, Marlene Vega, Maria Boix Braga, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3873462/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 Objective: To determine the factor structure of the Multidimensional Health Perceptions Questionnaire (MHPQ), a self-reported multidimensional assessment of health perceptions, in English-speakers and Spanish-speakers in the U.S with and without various health conditions (general population). Methods: The MHPQ previously demonstrated excellent content validity (content validity index=98.1%) and conceptual equivalence in English and Spanish, with a reading grade level of < 8 th grade in both languages. We administered the original 93-item MHPQ as an anonymous survey (REDCap™) to participants in the general population (items rated on a 1=Strongly disagree to 5=Strongly agree response scale). Results: N=357 participants completed the MHPQ (n=331 English, n=26 Spanish). The sample was 74.2% women, 18-82 years old, 24.1% Hispanic/Latino, predominantly White (68.9%), and highly educated (52.1% with at least an Associate degree). Exploratory Factor Analysis resulted in 65 final items with a multidimensional structure and good internal consistency reliabilities, with the following seven health perceptions domains (% variance, Cronbach’s α): Anticipated Discrimination and Judgement (18.9%, α=.92); Spiritual Health Beliefs (8.6%, α=.89); Social and Emotional Well-being (5.5%, α=.71); Confidence in Healthcare Providers and Medicine (3.5%, α=.85); Health Self-Efficacy (2.9%, α=.79); Trust in Social Health Advice (2.8%, α=.74); and Health Literacy (2.2%, α=.86). Conclusions: Results suggest that the MHPQ may be a valid and reliable measure for comprehensively characterizing health beliefs in the general population. Future work should validate the MHPQ in specific populations. Psychology Health Belief Model Psychometrics Health Literacy Locus of Control Exploratory Factor Analysis Figures Figure 1 Introduction The World Health Organization defines social determinants of health (SDoH) as “the conditions in which people are born, grow, live, work, and age, and the wider set of forces and systems shaping the conditions of daily life” [ 1 ]. SDoH include social and economic factors that can impact health outcomes, including education, employment, income, family and social support, and community safety. These factors can lead to inequality in access to health care, and are also associated with stigma, systemic discrimination, and bias that create inequality in access to care and in ability to understand and implement healthcare recommendations [ 2 ]. SDoH have also been shown to be strong predictors of health outcomes across the United States, as well as in Europe [ 2 , 3 ], and unmet SDoH needs in particular are associated with poorer physical and mental health and with less utilization of health services [ 4 , 5 ]. SDoH can shape the health perceptions of individuals, which can further indirectly impact their openness to and likelihood to benefit from health care treatments and recommendations. According to the Centers for Disease Control, SDoH include social norms and attitudes, such as perceived discrimination, racism, and distrust of government., and both literacy and cultural norms [ 6 ]. Culturally competent, patient-centered, and evidence-based clinical practice requires that healthcare providers understand and account for the health beliefs and perceptions of their patients/clients when making treatment decisions [ 7 – 9 ]. Not only do health perceptions affect treatment adherence, health outcomes, and satisfaction with care across populations [ 10 – 12 ], but they are grounded in personal and cultural values central to an individual’s identity and in the experiences individuals have had in the healthcare system, such as discrimination or poor care because of systemic inequities [ 8 , 13 , 14 ]. Understanding health perceptions among racial and ethnic minorities is especially critical to reducing health care disparities and disability burden associated with preventable conditions or complications. Yet, existing health perceptions measures are limited to narrowly defined health beliefs (e.g., locus of control alone) and are often specific to health conditions (e.g., stroke health beliefs). They do not capture health literacy, health self-efficacy, or anticipated discrimination, all of which a provider needs to know to tailor their interpersonal interactions, communication, and recommendations to each person they care for. When it comes to managing debilitating conditions, like dementia or traumatic injuries, caregiver health perceptions are often equally important because health management ultimately falls on caregivers. When measures only focus on specific health conditions, comparison across clinical populations and across caregivers is impossible. Furthermore, measures need to be developed and validated for the Hispanics, who make up the largest ethno-racial minority group in the US, many of whom are primarily Spanish-speaking (nearly 14% of those age 5 and older speak Spanish at home) [ 15 ]. A broad, multidimensional measure of health perceptions that is agnostic to health condition and available in English and Spanish is a critically needed tool to improve patient-centered and culturally competent care. To meet this need, we previously developed the Multidimensional Health Perceptions Questionnaire (MHPQ) using patient-centered outcomes research techniques [ 16 ]. The initial items for the MHPQ, referred to henceforth as the MHPQ β , has excellent content validity for assessing health perceptions, agnostic to specific health condition [ 16 ]. The objectives of this study were to determine the multidimensional factor structure of the MHPQ and to evaluate the internal consistency reliabilities of each factor in a general population sample. Materials and Methods Design and Participants. We conducted a cross-sectional anonymous survey study of community-dwelling adults in the general population, including both English and Spanish speakers. Participants had to be ≥ 18 years old and be fluent in either English or Spanish. As this was an electronically collected survey sent to participants via email or through social media posts, participants also had to have access to a device with internet access. Recruitment primarily occurred via emails sent to participants in the Community Research Registry (community-dwelling adults from the general population) from the Department of Population and Data Sciences and the Acquired Brain Injury Research Registry (individuals with acquired neurological conditions or care partners of individuals with acquired neurological conditions) from the Department of Physical Medicine & Rehabilitation at UT Southwestern Medical Center in Dallas, TX. A brief description of the study and link were also posted publicly to social media accounts (Twitter, Facebook, Instagram), employing a snowball recruitment approach, particularly to recruit primarily Spanish-speaking participants. All data collection and storage occurred using REDCap™. Participants provided assent to participate in accordance with a protocol approved by the UT Southwestern Human Research Protection Program (Institutional Review Board). Sample size determination. There are several approaches to determining the sample size required for factor analysis, with recommendations based on either absolute number of participants (ranging from 100 to 500) or participants-to-variables ratio (ranging from 2:1 to 20:1)[ 17 ]. In cases where there will be at least 3–6 variables (e.g., items) per factor, lower ratios are necessary [ 17 ]. Given the 92 items in the MHPQ β and our anticipation of more than 3 (and most likely more than 6) items per factor, we set a minimum sample size of n = 276 (roughly halfway between the recommended range of 100 to 500 and providing a 3:1 participant-to-item ratio). Measures. Participants completed a brief demographic questionnaire, including English and/or Spanish language fluency, preferred language, Hispanic/Latino ethnicity (Yes/No followed by country of origin if Yes), race, gender, education, employment status, living in an urban, rural, or suburban setting, and if there was a place they go when they are sick or need medical advice (Yes/No). They were also asked an open-ended question about diagnosed health conditions. The MHPQ β had 92 items developed using patient-centered outcomes techniques, including content expert panel review and rating of content validity and cognitive interviews probing broader concepts and individual item working [ 16 ]. Additionally, all MHPQ β items underwent a rigorous translation and language validation process. The MHPQ β items and instructions have a modified SMOG reading level of 6th grade in English and 8th grade in Spanish [ 16 ]. All items are rated on a 1–5 point agreement scale (1 = Strongly Disagree to 5 = Strongly Agree). Instructions for all items were as follows: Please rate how much you agree with each of the following statements. "Healthcare providers" include doctors, nurses, therapists, or any other professional who you see for medical or healthcare services. "Health" refers to how you feel, how well or not well you are, and any specific health conditions that you have. For the final nine items probing anticipated discrimination in healthcare, this additional prompt was provided: Because of my race, ethnicity, gender, age, religion, physical appearance, sexual orientation, or other characteristics… Data Analysis. We calculated summary statistics (means, standard deviations, frequencies, and percentiles) to describe our sample. We then conducted an Exploratory Factor Analysis (EFA) using Statistical Packages for the Social Sciences (SPSS; IBM SPSS Statistics, v26) to determine the factor structure of the MHPQ and the items to retain for inclusion in the finalized measure. We selected Principal Axis Factoring with oblique rotation (direct Oblimin rotation with delta = 0), as we hypothesized, based on our conceptual model, that the MHPQ factors would correlate [ 18 ]. The Kaiser-Meyer-Olkin measure of sampling adequacy (> .80 is “meritorious” and > .90 is “marvelous”) and Bartlett’s Test for Sphericity measured appropriateness of factor analysis in the dataset [ 19 ]. We first set a threshold to retain all factors with eigenvalues > 1 and examined the resulting Scree plot. Then, we iteratively reduced the numbers of forced factors so that each factor included at least 3 items and removed items with pattern matrix factor loadings < .300 (except in the instance where an item was below the .300 threshold, but experts deemed it to be too clinically relevant to omit). A final factor solution was selected based on balancing number of factors, number of items within a factor, and conceptual consistency within and across factors when examining the pattern matrix. After finalizing the factor structure, we calculated Cronbach’s alpha coefficients within each factor to evaluate internal consistency reliabilities, with α > .7 = Acceptable, α > .8 = Good, α > .9 = Excellent [ 20 ], though α > .6 is considered acceptable for exploratory studies such as this [ 21 , 22 ]. So as not to remove items that may be potentially relevant to Spanish-speakers by conducting EFA in English-speakers only, and because we previously established the conceptual equivalence of all items across language, we pooled our sample for EFA. However, we calculated Cronbach’s alpha coefficients overall and within each language group. Lastly, we conducted exploratory analyses, using Spearman’s rho correlations, to assess whether select personal factors were associated with health perceptions domains (average scores across all items in that factor) and how health perceptions domains inter-relate with one another. Results Participants . We sent emails with the survey link to n = 4,198 English-speakers and n = 587 Spanish-speakers, and n = 600 individuals opened the survey from the link. A total of n = 357 participants (n = 331 English-speaking, n = 26 Spanish-speaking) completed the MHPQ (59.5% response rate for those who opened the link). A detailed breakdown of survey response numbers is provided in Fig. 1 . A summary of participant characteristics for the n = 357 included in analyses, both overall and by primary language spoken, is presented in Table 1 . Participants ranged in age from 18–82 years old and reported having a wide variety of health conditions (see Supplemental Fig. 1 ). Participants whose preferred language was Spanish more often had less than a high school (or equivalent) education, were employed more often part-time or were “homemakers”, and more often lived in rural or urban (vs suburban) communities compared to those whose preferred primary language was English. Factor Structure Exploratory factor analysis yielded a 7-factor solution with 65 final items ( Table 2 ). The Kaiser-Meyer-Olkin = .867 (“meritorious” sampling adequacy) and Bartlett’s Test of Sphericity (p < .001) indicating appropriateness of factor analysis in this sample. Final items explained 44.5% of the total variance; factors all included at least 6 items, except Factor 6 which contained 4 items. We named the seven factors: 1) Anticipated Discrimination and Judgement, 2) Spiritual Health Beliefs, 3) Social and Emotional Well-Being Beliefs, 4) Confidence and Trust in Healthcare Providers and Medicine, 5) Health Self-Efficacy (Internal LOC), 6) Trust in Social Health Advice, 7) Health Literacy. One item, “I can manage the health of my loved ones” was not included in any of the seven factors but was kept for its potential clinical relevance when working with caregivers. Internal Consistency Reliabilities Cronbach’s alpha coefficients indicated acceptable to excellent internal consistency for all factors (see Table 3 ). We separated those who completed the measure in English and Spanish and calculated Cronbach’s alpha’s separately (also presented in Table 3 ). Internal consistency was acceptable to excellent in each primary language group for all factors as well. Exploratory Analyses Correlations among subscales are presented in Table 4 , and Table 5 presents subscale means across demographic factors. Age did not demonstrate any correlations > .20 with any MHPQ subscale score, indicating that age was not associated with health perceptions in any domain. Education was similarly not correlated with any subscale, though given the skew towards high education in this sample, these results are likely only applicable to those with more than a high school education. Discussion We identified a seven-factor structure for the MHPQ, which maps well to the Multidimensional Health Perceptions Model upon which it was based [ 16 ]. However, the model addresses beliefs about the causes and consequences of health conditions and the benefits and barriers to doing something about one’s health, which are not reflected as separate factors within the MHPQ. These two beliefs represent very global aspects of health. None of the items specifically addresses the causes and consequences of health conditions, possibly due to being an agnostic measure that does not address specific conditions. In addition, the MHPQ addresses beliefs related to Social and Emotional Well-being and Trust in Social Health Advice , which are not specifically the components of multidimensional health perceptions. The Trust in Social Health Advice factor focuses on the role that the beliefs of others and media play in health perceptions, which is aligned with social influence theory [ 23 ]. Another area not reflected in the MHPQ is the role of fear or perceived threat. From theories of health communication, such as the Extended Parallel Processing Model, we understand how individuals’ health perceptions may be influenced by perceived threat and susceptibility, which is modulated by one’s efficacy in using strategies to manage one’s health [ 24 ]. This may also be due to the condition agnostic nature of the MHPQ, as perceived threat and susceptibility differs by specific conditions [ 25 ]. The Exploratory Factor Analysis revealed that some items cross-loaded to multiple factors, which indicates the item may reflect multiple components of health perceptions. For example, the item “I am embarrassed by my health” primarily loaded on the Anticipated Discrimination and Judgement factor and on the Social and Emotional Well-Being Beliefs and Health Self-Efficacy factors. This item reflects judgement by others, but also has the emotional component of embarrassment and suggests the opposite of someone who has strong health self-efficacy (i.e., negative factor loading). Two items were unexpectedly cross loaded, “I believe my healthcare provider will respect me” and “I can manage the health of my loved ones.” The belief that their healthcare provider shows respect cross-loaded on the Health Literacy factor. It could be that this item also taps into the health communication and shared decision-making aspect of health literacy. Lastly, it is possible that the respondents were not certain on how to respond to whether they can manage the health of their loved ones. Some individuals may not have the responsibility of being a caregiver or they may be sharing the roles with other individuals. This item was not included in any of the final seven factors, but we recommend maintaining it as a stand-alone item relevant to experiences of informal caregivers. Of note, most of the subscales were weakly correlated with one another. The Anticipated Discrimination and Judgement factor was negatively associated with the Confidence and Trust in Healthcare Providers and Medicine and Health Literacy factors. This finding suggests that addressing patient health literacy and their trust in providers could reduce the perception of discrimination or judgement. The COVID-19 pandemic is an excellent example of how many public health efforts targeting increasing public knowledge regarding the disease, use of personal protective equipment (e.g., masks) and vaccinations can increase people’s trust in healthcare providers and reduce discriminatory behaviors and violence towards others. Discrimination and other systemic factors are barriers to health literacy and provision of culturally competent care [ 26 , 27 ]. Health Literacy was also associated with Health Self-Efficacy , which are both key components of self-management of chronic diseases [ 28 ]. The Spiritual Health Beliefs factor was correlated moderately with the Trust in Social Health Advice factor. This could reflect that individuals with strong spiritual beliefs are more likely to trust information from external sources, such as friends, family, and health information mediums, that from their own healthcare providers. We did not identify any significant demographics that were associated with health perceptions using the MHPQ. More work is needed to further explore the role of socio-cultural factors that are associated with health perceptions using the MHPQ, since age and education have previously been found to be associated with health perceptions in patients with chronic diseases [ 29 ]. The MHPQ provides a summary of an individual’s beliefs about their health and their perceptions of a variety of factors that may impact their health, including anticipated discrimination, trust in healthcare providers, and self-perceived health literacy. These concepts are all included under the broad umbrella of social determinants of health (SDoH) known to affect health outcomes. Clinicians should consider SDoH when communicating with patients and providing education and recommendations for maintaining health. The Human Genome Project was completed in April 2003 and ushered in an era of personalized medicine. Scientific advances have allowed providers to customize care plans to the patient’s unique clinical presentation, genetic factors, and environment to more fully address that patient’s condition and ensure successful treatment [ 30 ]. So far, personalized medicine has left out psychosocial factors, including cultural, religious, and economic factors and other SDoH. Healthcare is still not accessible to many for these reasons. Patients may avoid seeing the doctor because they do not know how to communicate the side effects they are having from a medication or what the consequences may be if they do not take the medication. They may think that the doctor does not care about their religious beliefs around specific treatments or diagnoses. Understanding the health perceptions captured on the MHPQ and how they affect each patient will allow us to find specific ways to address them in healthcare settings and communication. These changes can then be incorporated into healthcare practices to treat patients more effectively and truly provide personalized care that is specific to each person’s values, preferences, and experiences. These changes can also improve healthcare facilities performance on quality indicators and outcomes, and reduce costly complications that result with low treatment adherence. The MHPQ has the potential to be useful as a tool to help guide clinicians in communicating with patients in a manner that incorporates the patients’ perceptions and values, making it more likely that recommendations will be assimilated into the patient’s life. For example, for an individual who scores high on the Spiritual Health Beliefs and Trust in Social Health Advice factors and low on the Confidence and Trust in Healthcare Providers and Medicine factor, a health provider may spend more time establishing trust and rapport, engage spiritual leaders (e.g., a hospital chaplain) in communicating healthcare recommendations and/or incorporate spiritual activities into the recommendations, and work with family members to help ensure recommendations are followed at home. Interacting with patients with respect to their health perceptions has the potential to improve uptake of health recommendations, thus improving overall health outcomes. Currently, the Hispanic/Latino community is the largest ethnographic-racial minority group in the United States. Despite their significant presence in our communities, factors that can affect their healthcare engagement, treatment adherence and outcomes have not yet been adequately studied and understood at the patient-, family, and culture-specific levels. Considering relevant health literacy and health self-efficacy, as well as allowing for specific tailoring of interpersonal communication, interactions, and recommendations in the context of culture and language, is expected to lead to a better understanding (by healthcare providers) of such factors and to allow for adaptation of evidenced-based practice for this community. This could consequently reduce healthcare disparities and disability burden associated with preventable conditions or complications within the Hispanic/Latino population. This can be achieved by providing researchers and clinical providers alike with improved understanding of the health perception domains that may be impacting an individual’s engagement, compliance, and adherence to the recommended interventions, particularly when differences in cultural and language background between providers and the individual may be present. Limitations Though we had a robust sample size overall (factors loadings should be > .364 in a sample of 200 for results to be considered significant)[ 31 ], the sample size for primarily Spanish-speaking individuals was small and did not allow us to run the EFA in this group separately. However, we did examine internal consistency reliabilities separately to provide some psychometric evidence among Spanish-speakers specifically and to flag items for future investigation in a Spanish-speaking sample. Reliabilities were all acceptable to excellent among Spanish speakers in all but one factor that should be evaluated more closely in future studies. We strongly recommend further psychometric evaluation of the MHPQ in a larger primarily Spanish-speaking sample and additional cognitive interviewing for items in some of the less-well performing subscales prior to widespread use of this measure in Spanish to examine functional, item, and measurement equivalence. Perhaps the most consequential limitation of this study was the highly educated and still predominantly White sample. As such, we strongly recommend validation of the MHPQ in a sample that specifically oversamples minoritized groups and other under-represented groups (e.g., those with low literacy) to ensure that the measure validly captures health perceptions that may not be as prevalent in the highly educated and White majority in the present sample. Further, while we intentionally targeted a diverse general population sample, since the MHPQ is neutral to health condition, we do advise evaluating the psychometric properties of the measure in specific clinical populations in accordance with the Standards for Educational and Psychology Testing [ 32 ]. Conclusions The MHPQ has a psychometrically strong and clinically meaningful factor structure in a diverse sample of both English and Spanish speakers who are primarily well educated. An individual’s factor scores may guide health provider communication of healthcare recommendations in ways that may enhance their uptake. Future validation of the MHPQ in more diverse samples is needed. Declarations Author ORCID IDs and Contributions: Shannon B. Juengst, PhD (ORCID ID: 0000-0003-4709-545X): Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing (original draft, review & editing) Angelle M. Sander, PhD (ORCID ID: 0000-0001-7494-0298): Writing (original draft, review & editing) Marlene Vega, PsyD (ORCID ID: 0000-0003-4504-8983): Conceptualization, Investigation, Methodology, Writing (original draft, review & editing) Maria Boix-Braga, PhD: Conceptualization, Investigation, Writing (original draft, review & editing) Alka Khera, MD (ORCID ID: 0000-0002-8584-3909): Writing (original draft, review & editing) Monique R. Pappadis, PhD (ORCID ID: 0000-0003-4742-4380): Writing (original draft, review & editing) Acknowledgements Ethics approval and consent to participate All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All procedures were approved by the UT Southwestern Medical Center Human Protections Research Office (IRB). Consent for publication Informed consent was obtained from participants; no identifiable data were included in this publication. Availability of supporting data The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors have no relevant financial or non-financial interests to disclose. Funding This study was not funded. 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BMC public health , 21 (1), 1047. https://doi.org/10.1186/s12889-021-11065-4 Chan, I. S., & Ginsburg, G. S. (2011). Personalized Medicine: Progress and Promise. Annual Review of Genomics and Human Genetics , 12 (1), 217–244. https://doi.org/10.1146/annurev-genom-082410-101446 Stevens, J. P. (2009). Applied Multivariate Statistics for the Social Sciences, Fifth Edition (5 edition.). New York: Routledge. The Standards for Educational and Psychological Testing. (n.d.). http://www.apa.org . Retrieved April 19, 2016, from http://www.apa.org/science/programs/testing/standards.aspx Tables 1-4 Tables 1 to 4 are available in the Supplementary Files section Table 5 Table 5 is not available with this version. Additional Declarations The authors declare no competing interests. Supplementary Files Tables.docx HealthconditionsSFig0001.tif 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3873462","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267679545,"identity":"0d745722-beb5-4ae8-a962-1c5de07435a7","order_by":0,"name":"Shannon B. Juengst","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-4709-545X","institution":"TIRR Memorial Hermann","correspondingAuthor":true,"prefix":"","firstName":"Shannon","middleName":"B.","lastName":"Juengst","suffix":""},{"id":267679546,"identity":"0a55c8a1-e760-4f9f-b540-02e83195fb84","order_by":1,"name":"Angelle M. Sander","email":"","orcid":"https://orcid.org/0000-0001-7494-0298","institution":"TIRR Memorial Hermann","correspondingAuthor":false,"prefix":"","firstName":"Angelle","middleName":"M.","lastName":"Sander","suffix":""},{"id":267679547,"identity":"36ec4a12-a193-48e4-9075-47f42d81e156","order_by":2,"name":"Marlene Vega","email":"","orcid":"https://orcid.org/0000-0003-4504-8983","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marlene","middleName":"","lastName":"Vega","suffix":""},{"id":267679548,"identity":"86d817a2-f6a0-4855-b8d7-d9b15e8f0e45","order_by":3,"name":"Maria Boix Braga","email":"","orcid":"","institution":"Baylor Scott \u0026 White","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Boix","lastName":"Braga","suffix":""},{"id":267679549,"identity":"e20d8d1f-671e-4946-ac17-fa824d1448a0","order_by":4,"name":"Alka Khera","email":"","orcid":"https://orcid.org/0000-0002-8584-3909","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alka","middleName":"","lastName":"Khera","suffix":""},{"id":267679550,"identity":"c8cf06fd-3ac1-44b7-bfde-5b7cd86d352d","order_by":5,"name":"Monique R. Pappadis","email":"","orcid":"https://orcid.org/0000-0003-4742-4380","institution":"University of Texas Medical Branch","correspondingAuthor":false,"prefix":"","firstName":"Monique","middleName":"R.","lastName":"Pappadis","suffix":""}],"badges":[],"createdAt":"2024-01-17 17:32:47","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3873462/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3873462/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49884330,"identity":"8eb4216b-680a-45fe-a978-3d5db637eafc","added_by":"auto","created_at":"2024-01-19 17:03:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":120781,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Participant Inclusion\u003c/p\u003e\n\u003cp\u003eFlowchart of Participant requirement and survey completion\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3873462/v1/a9101637762b36ce78fe0289.png"},{"id":49884712,"identity":"f51033b0-5cdd-42d3-9543-4ece1415865a","added_by":"auto","created_at":"2024-01-19 17:11:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":438652,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3873462/v1/3bd451bf-dd57-474d-a896-cb5b191a4a58.pdf"},{"id":49884329,"identity":"da458c92-6dfc-4c18-abcb-0d5b8d38f1df","added_by":"auto","created_at":"2024-01-19 17:03:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":63040,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-3873462/v1/ee5d88ac37fbc13cf1d53f9d.docx"},{"id":49884331,"identity":"ddbf28bf-983e-4601-a6fc-964561617674","added_by":"auto","created_at":"2024-01-19 17:03:35","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1735262,"visible":true,"origin":"","legend":"","description":"","filename":"HealthconditionsSFig0001.tif","url":"https://assets-eu.researchsquare.com/files/rs-3873462/v1/e4323e4b4db89295da7ead71.tif"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eFactor Structure of the Multidimensional Health Perceptions Questionnaire in English- and Spanish-speakers\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe World Health Organization defines social determinants of health (SDoH) as \u0026ldquo;the conditions in which people are born, grow, live, work, and age, and the wider set of forces and systems shaping the conditions of daily life\u0026rdquo; [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. SDoH include social and economic factors that can impact health outcomes, including education, employment, income, family and social support, and community safety. These factors can lead to inequality in access to health care, and are also associated with stigma, systemic discrimination, and bias that create inequality in access to care and in ability to understand and implement healthcare recommendations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. SDoH have also been shown to be strong predictors of health outcomes across the United States, as well as in Europe [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and unmet SDoH needs in particular are associated with poorer physical and mental health and with less utilization of health services [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. SDoH can shape the health perceptions of individuals, which can further indirectly impact their openness to and likelihood to benefit from health care treatments and recommendations. According to the Centers for Disease Control, SDoH include social norms and attitudes, such as perceived discrimination, racism, and distrust of government., and both literacy and cultural norms [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCulturally competent, patient-centered, and evidence-based clinical practice requires that healthcare providers understand and account for the health beliefs and perceptions of their patients/clients when making treatment decisions [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Not only do health perceptions affect treatment adherence, health outcomes, and satisfaction with care across populations [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], but they are grounded in personal and cultural values central to an individual\u0026rsquo;s identity and in the experiences individuals have had in the healthcare system, such as discrimination or poor care because of systemic inequities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Understanding health perceptions among racial and ethnic minorities is especially critical to reducing health care disparities and disability burden associated with preventable conditions or complications. Yet, existing health perceptions measures are limited to narrowly defined health beliefs (e.g., locus of control alone) and are often specific to health conditions (e.g., stroke health beliefs). They do not capture health literacy, health self-efficacy, or anticipated discrimination, all of which a provider needs to know to tailor their interpersonal interactions, communication, and recommendations to each person they care for. When it comes to managing debilitating conditions, like dementia or traumatic injuries, caregiver health perceptions are often equally important because health management ultimately falls on caregivers. When measures only focus on specific health conditions, comparison across clinical populations and across caregivers is impossible. Furthermore, measures need to be developed and validated for the Hispanics, who make up the largest ethno-racial minority group in the US, many of whom are primarily Spanish-speaking (nearly 14% of those age 5 and older speak Spanish at home) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A broad, multidimensional measure of health perceptions that is agnostic to health condition and available in English and Spanish is a critically needed tool to improve patient-centered and culturally competent care.\u003c/p\u003e \u003cp\u003eTo meet this need, we previously developed the Multidimensional Health Perceptions Questionnaire (MHPQ) using patient-centered outcomes research techniques [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The initial items for the MHPQ, referred to henceforth as the MHPQ\u003csub\u003eβ\u003c/sub\u003e, has excellent content validity for assessing health perceptions, agnostic to specific health condition [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The objectives of this study were to determine the multidimensional factor structure of the MHPQ and to evaluate the internal consistency reliabilities of each factor in a general population sample.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cb\u003eDesign and Participants.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe conducted a cross-sectional anonymous survey study of community-dwelling adults in the general population, including both English and Spanish speakers. Participants had to be \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;18 years old and be fluent in either English or Spanish. As this was an electronically collected survey sent to participants via email or through social media posts, participants also had to have access to a device with internet access. Recruitment primarily occurred via emails sent to participants in the Community Research Registry (community-dwelling adults from the general population) from the Department of Population and Data Sciences and the Acquired Brain Injury Research Registry (individuals with acquired neurological conditions or care partners of individuals with acquired neurological conditions) from the Department of Physical Medicine \u0026amp; Rehabilitation at UT Southwestern Medical Center in Dallas, TX. A brief description of the study and link were also posted publicly to social media accounts (Twitter, Facebook, Instagram), employing a snowball recruitment approach, particularly to recruit primarily Spanish-speaking participants. All data collection and storage occurred using REDCap\u0026trade;. Participants provided assent to participate in accordance with a protocol approved by the UT Southwestern Human Research Protection Program (Institutional Review Board).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample size determination.\u003c/b\u003e There are several approaches to determining the sample size required for factor analysis, with recommendations based on either absolute number of participants (ranging from 100 to 500) or participants-to-variables ratio (ranging from 2:1 to 20:1)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In cases where there will be at least 3\u0026ndash;6 variables (e.g., items) per factor, lower ratios are necessary [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Given the 92 items in the MHPQ\u003csub\u003eβ\u003c/sub\u003e and our anticipation of more than 3 (and most likely more than 6) items per factor, we set a minimum sample size of n\u0026thinsp;=\u0026thinsp;276 (roughly halfway between the recommended range of 100 to 500 and providing a 3:1 participant-to-item ratio).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasures.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eParticipants completed a brief demographic questionnaire, including English and/or Spanish language fluency, preferred language, Hispanic/Latino ethnicity (Yes/No followed by country of origin if Yes), race, gender, education, employment status, living in an urban, rural, or suburban setting, and if there was a place they go when they are sick or need medical advice (Yes/No). They were also asked an open-ended question about diagnosed health conditions.\u003c/p\u003e \u003cp\u003eThe MHPQ\u003csub\u003eβ\u003c/sub\u003e had 92 items developed using patient-centered outcomes techniques, including content expert panel review and rating of content validity and cognitive interviews probing broader concepts and individual item working [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, all MHPQ\u003csub\u003eβ\u003c/sub\u003e items underwent a rigorous translation and language validation process. The MHPQ\u003csub\u003eβ\u003c/sub\u003e items and instructions have a modified SMOG reading level of 6th grade in English and 8th grade in Spanish [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. All items are rated on a 1\u0026ndash;5 point agreement scale (1\u0026thinsp;=\u0026thinsp;Strongly Disagree to 5\u0026thinsp;=\u0026thinsp;Strongly Agree). Instructions for all items were as follows:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePlease rate how much you agree with each of the following statements. \"Healthcare providers\" include doctors, nurses, therapists, or any other professional who you see for medical or healthcare services. \"Health\" refers to how you feel, how well or not well you are, and any specific health conditions that you have.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eFor the final nine items probing anticipated discrimination in healthcare, this additional prompt was provided:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBecause of my race, ethnicity, gender, age, religion, physical appearance, sexual orientation, or other characteristics\u0026hellip;\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis.\u003c/h2\u003e \u003cp\u003eWe calculated summary statistics (means, standard deviations, frequencies, and percentiles) to describe our sample. We then conducted an Exploratory Factor Analysis (EFA) using Statistical Packages for the Social Sciences (SPSS; IBM SPSS Statistics, v26) to determine the factor structure of the MHPQ and the items to retain for inclusion in the finalized measure. We selected Principal Axis Factoring with oblique rotation (direct Oblimin rotation with delta\u0026thinsp;=\u0026thinsp;0), as we hypothesized, based on our conceptual model, that the MHPQ factors would correlate [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The Kaiser-Meyer-Olkin measure of sampling adequacy (\u0026gt;\u0026thinsp;.80 is \u0026ldquo;meritorious\u0026rdquo; and \u0026gt;\u0026thinsp;.90 is \u0026ldquo;marvelous\u0026rdquo;) and Bartlett\u0026rsquo;s Test for Sphericity measured appropriateness of factor analysis in the dataset [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. We first set a threshold to retain all factors with eigenvalues\u0026thinsp;\u0026gt;\u0026thinsp;1 and examined the resulting Scree plot. Then, we iteratively reduced the numbers of forced factors so that each factor included at least 3 items and removed items with pattern matrix factor loadings\u0026thinsp;\u0026lt;\u0026thinsp;.300 (except in the instance where an item was below the .300 threshold, but experts deemed it to be too clinically relevant to omit). A final factor solution was selected based on balancing number of factors, number of items within a factor, and conceptual consistency within and across factors when examining the pattern matrix. After finalizing the factor structure, we calculated Cronbach\u0026rsquo;s alpha coefficients within each factor to evaluate internal consistency reliabilities, with α\u0026thinsp;\u0026gt;\u0026thinsp;.7\u0026thinsp;=\u0026thinsp;Acceptable, α\u0026thinsp;\u0026gt;\u0026thinsp;.8\u0026thinsp;=\u0026thinsp;Good, α\u0026thinsp;\u0026gt;\u0026thinsp;.9\u0026thinsp;=\u0026thinsp;Excellent [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], though α\u0026thinsp;\u0026gt;\u0026thinsp;.6 is considered acceptable for exploratory studies such as this [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. So as not to remove items that may be potentially relevant to Spanish-speakers by conducting EFA in English-speakers only, and because we previously established the conceptual equivalence of all items across language, we pooled our sample for EFA. However, we calculated Cronbach\u0026rsquo;s alpha coefficients overall and within each language group. Lastly, we conducted exploratory analyses, using Spearman\u0026rsquo;s rho correlations, to assess whether select personal factors were associated with health perceptions domains (average scores across all items in that factor) and how health perceptions domains inter-relate with one another.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eParticipants\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eWe sent emails with the survey link to n\u0026thinsp;=\u0026thinsp;4,198 English-speakers and n\u0026thinsp;=\u0026thinsp;587 Spanish-speakers, and n\u0026thinsp;=\u0026thinsp;600 individuals opened the survey from the link. A total of n\u0026thinsp;=\u0026thinsp;357 participants (n\u0026thinsp;=\u0026thinsp;331 English-speaking, n\u0026thinsp;=\u0026thinsp;26 Spanish-speaking) completed the MHPQ (59.5% response rate for those who opened the link). A detailed breakdown of survey response numbers is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A summary of participant characteristics for the n\u0026thinsp;=\u0026thinsp;357 included in analyses, both overall and by primary language spoken, is presented in \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e. Participants ranged in age from 18\u0026ndash;82 years old and reported having a wide variety of health conditions (see \u003cb\u003eSupplemental Fig.\u0026nbsp;1\u003c/b\u003e). Participants whose preferred language was Spanish more often had less than a high school (or equivalent) education, were employed more often part-time or were \u0026ldquo;homemakers\u0026rdquo;, and more often lived in rural or urban (vs suburban) communities compared to those whose preferred primary language was English.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFactor Structure\u003c/h2\u003e \u003cp\u003eExploratory factor analysis yielded a 7-factor solution with 65 final items (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e). The Kaiser-Meyer-Olkin\u0026thinsp;=\u0026thinsp;.867 (\u0026ldquo;meritorious\u0026rdquo; sampling adequacy) and Bartlett\u0026rsquo;s Test of Sphericity (p\u0026thinsp;\u0026lt;\u0026thinsp;.001) indicating appropriateness of factor analysis in this sample. Final items explained 44.5% of the total variance; factors all included at least 6 items, except Factor 6 which contained 4 items. We named the seven factors: 1) Anticipated Discrimination and Judgement, 2) Spiritual Health Beliefs, 3) Social and Emotional Well-Being Beliefs, 4) Confidence and Trust in Healthcare Providers and Medicine, 5) Health Self-Efficacy (Internal LOC), 6) Trust in Social Health Advice, 7) Health Literacy. One item, \u0026ldquo;I can manage the health of my loved ones\u0026rdquo; was not included in any of the seven factors but was kept for its potential clinical relevance when working with caregivers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eInternal Consistency Reliabilities\u003c/h2\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha coefficients indicated acceptable to excellent internal consistency for all factors (see \u003cb\u003eTable\u0026nbsp;3\u003c/b\u003e). We separated those who completed the measure in English and Spanish and calculated Cronbach\u0026rsquo;s alpha\u0026rsquo;s separately (also presented in \u003cb\u003eTable\u0026nbsp;3\u003c/b\u003e). Internal consistency was acceptable to excellent in each primary language group for all factors as well.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eExploratory Analyses\u003c/h2\u003e \u003cp\u003eCorrelations among subscales are presented in \u003cb\u003eTable\u0026nbsp;4\u003c/b\u003e, and \u003cb\u003eTable\u0026nbsp;5\u003c/b\u003e presents subscale means across demographic factors. Age did not demonstrate any correlations\u0026thinsp;\u0026gt;\u0026thinsp;.20 with any MHPQ subscale score, indicating that age was not associated with health perceptions in any domain. Education was similarly not correlated with any subscale, though given the skew towards high education in this sample, these results are likely only applicable to those with more than a high school education.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe identified a seven-factor structure for the MHPQ, which maps well to the Multidimensional Health Perceptions Model upon which it was based [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the model addresses beliefs about the causes and consequences of health conditions and the benefits and barriers to doing something about one\u0026rsquo;s health, which are not reflected as separate factors within the MHPQ. These two beliefs represent very global aspects of health. None of the items specifically addresses the causes and consequences of health conditions, possibly due to being an agnostic measure that does not address specific conditions. In addition, the MHPQ addresses beliefs related to \u003cem\u003eSocial and Emotional Well-being\u003c/em\u003e and \u003cem\u003eTrust in Social Health Advice\u003c/em\u003e, which are not specifically the components of multidimensional health perceptions. The \u003cem\u003eTrust in Social Health Advice\u003c/em\u003e factor focuses on the role that the beliefs of others and media play in health perceptions, which is aligned with social influence theory [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Another area not reflected in the MHPQ is the role of fear or perceived threat. From theories of health communication, such as the Extended Parallel Processing Model, we understand how individuals\u0026rsquo; health perceptions may be influenced by perceived threat and susceptibility, which is modulated by one\u0026rsquo;s efficacy in using strategies to manage one\u0026rsquo;s health [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This may also be due to the condition agnostic nature of the MHPQ, as perceived threat and susceptibility differs by specific conditions [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Exploratory Factor Analysis revealed that some items cross-loaded to multiple factors, which indicates the item may reflect multiple components of health perceptions. For example, the item \u0026ldquo;I am embarrassed by my health\u0026rdquo; primarily loaded on the \u003cem\u003eAnticipated Discrimination and Judgement\u003c/em\u003e factor and on the \u003cem\u003eSocial and Emotional Well-Being Beliefs and Health Self-Efficacy\u003c/em\u003e factors. This item reflects judgement by others, but also has the emotional component of embarrassment and suggests the opposite of someone who has strong health self-efficacy (i.e., negative factor loading). Two items were unexpectedly cross loaded, \u0026ldquo;I believe my healthcare provider will respect me\u0026rdquo; and \u0026ldquo;I can manage the health of my loved ones.\u0026rdquo; The belief that their healthcare provider shows respect cross-loaded on the \u003cem\u003eHealth Literacy\u003c/em\u003e factor. It could be that this item also taps into the health communication and shared decision-making aspect of health literacy. Lastly, it is possible that the respondents were not certain on how to respond to whether they can manage the health of their loved ones. Some individuals may not have the responsibility of being a caregiver or they may be sharing the roles with other individuals. This item was not included in any of the final seven factors, but we recommend maintaining it as a stand-alone item relevant to experiences of informal caregivers.\u003c/p\u003e \u003cp\u003eOf note, most of the subscales were weakly correlated with one another. The \u003cem\u003eAnticipated Discrimination and Judgement\u003c/em\u003e factor was negatively associated with the \u003cem\u003eConfidence and Trust in Healthcare Providers and Medicine\u003c/em\u003e and \u003cem\u003eHealth Literacy\u003c/em\u003e factors. This finding suggests that addressing patient health literacy and their trust in providers could reduce the perception of discrimination or judgement. The COVID-19 pandemic is an excellent example of how many public health efforts targeting increasing public knowledge regarding the disease, use of personal protective equipment (e.g., masks) and vaccinations can increase people\u0026rsquo;s trust in healthcare providers and reduce discriminatory behaviors and violence towards others. Discrimination and other systemic factors are barriers to health literacy and provision of culturally competent care [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. \u003cem\u003eHealth Literacy\u003c/em\u003e was also associated with \u003cem\u003eHealth Self-Efficacy\u003c/em\u003e, which are both key components of self-management of chronic diseases [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The \u003cem\u003eSpiritual Health Beliefs\u003c/em\u003e factor was correlated moderately with the \u003cem\u003eTrust in Social Health Advice\u003c/em\u003e factor. This could reflect that individuals with strong spiritual beliefs are more likely to trust information from external sources, such as friends, family, and health information mediums, that from their own healthcare providers. We did not identify any significant demographics that were associated with health perceptions using the MHPQ. More work is needed to further explore the role of socio-cultural factors that are associated with health perceptions using the MHPQ, since age and education have previously been found to be associated with health perceptions in patients with chronic diseases [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe MHPQ provides a summary of an individual\u0026rsquo;s beliefs about their health and their perceptions of a variety of factors that may impact their health, including anticipated discrimination, trust in healthcare providers, and self-perceived health literacy. These concepts are all included under the broad umbrella of social determinants of health (SDoH) known to affect health outcomes. Clinicians should consider SDoH when communicating with patients and providing education and recommendations for maintaining health. The Human Genome Project was completed in April 2003 and ushered in an era of personalized medicine. Scientific advances have allowed providers to customize care plans to the patient\u0026rsquo;s unique clinical presentation, genetic factors, and environment to more fully address that patient\u0026rsquo;s condition and ensure successful treatment [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. So far, personalized medicine has left out psychosocial factors, including cultural, religious, and economic factors and other SDoH. Healthcare is still not accessible to many for these reasons. Patients may avoid seeing the doctor because they do not know how to communicate the side effects they are having from a medication or what the consequences may be if they do not take the medication. They may think that the doctor does not care about their religious beliefs around specific treatments or diagnoses. Understanding the health perceptions captured on the MHPQ and how they affect each patient will allow us to find specific ways to address them in healthcare settings and communication. These changes can then be incorporated into healthcare practices to treat patients more effectively and truly provide personalized care that is specific to each person\u0026rsquo;s values, preferences, and experiences. These changes can also improve healthcare facilities performance on quality indicators and outcomes, and reduce costly complications that result with low treatment adherence.\u003c/p\u003e \u003cp\u003eThe MHPQ has the potential to be useful as a tool to help guide clinicians in communicating with patients in a manner that incorporates the patients\u0026rsquo; perceptions and values, making it more likely that recommendations will be assimilated into the patient\u0026rsquo;s life. For example, for an individual who scores high on the \u003cem\u003eSpiritual Health Beliefs\u003c/em\u003e and \u003cem\u003eTrust in Social Health Advice\u003c/em\u003e factors and low on the \u003cem\u003eConfidence and Trust in Healthcare Providers and Medicine\u003c/em\u003e factor, a health provider may spend more time establishing trust and rapport, engage spiritual leaders (e.g., a hospital chaplain) in communicating healthcare recommendations and/or incorporate spiritual activities into the recommendations, and work with family members to help ensure recommendations are followed at home. Interacting with patients with respect to their health perceptions has the potential to improve uptake of health recommendations, thus improving overall health outcomes.\u003c/p\u003e \u003cp\u003eCurrently, the Hispanic/Latino community is the largest ethnographic-racial minority group in the United States. Despite their significant presence in our communities, factors that can affect their healthcare engagement, treatment adherence and outcomes have not yet been adequately studied and understood at the patient-, family, and culture-specific levels. Considering relevant health literacy and health self-efficacy, as well as allowing for specific tailoring of interpersonal communication, interactions, and recommendations in the context of culture and language, is expected to lead to a better understanding (by healthcare providers) of such factors and to allow for adaptation of evidenced-based practice for this community. This could consequently reduce healthcare disparities and disability burden associated with preventable conditions or complications within the Hispanic/Latino population. This can be achieved by providing researchers and clinical providers alike with improved understanding of the health perception domains that may be impacting an individual\u0026rsquo;s engagement, compliance, and adherence to the recommended interventions, particularly when differences in cultural and language background between providers and the individual may be present.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThough we had a robust sample size overall (factors loadings should be \u0026gt;\u0026thinsp;.364 in a sample of 200 for results to be considered significant)[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], the sample size for primarily Spanish-speaking individuals was small and did not allow us to run the EFA in this group separately. However, we did examine internal consistency reliabilities separately to provide some psychometric evidence among Spanish-speakers specifically and to flag items for future investigation in a Spanish-speaking sample. Reliabilities were all acceptable to excellent among Spanish speakers in all but one factor that should be evaluated more closely in future studies. We strongly recommend further psychometric evaluation of the MHPQ in a larger primarily Spanish-speaking sample and additional cognitive interviewing for items in some of the less-well performing subscales prior to widespread use of this measure in Spanish to examine functional, item, and measurement equivalence.\u003c/p\u003e \u003cp\u003ePerhaps the most consequential limitation of this study was the highly educated and still predominantly White sample. As such, we strongly recommend validation of the MHPQ in a sample that specifically oversamples minoritized groups and other under-represented groups (e.g., those with low literacy) to ensure that the measure validly captures health perceptions that may not be as prevalent in the highly educated and White majority in the present sample. Further, while we intentionally targeted a diverse general population sample, since the MHPQ is neutral to health condition, we do advise evaluating the psychometric properties of the measure in specific clinical populations in accordance with the \u003cem\u003eStandards for Educational and Psychology Testing\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe MHPQ has a psychometrically strong and clinically meaningful factor structure in a diverse sample of both English and Spanish speakers who are primarily well educated. An individual\u0026rsquo;s factor scores may guide health provider communication of healthcare recommendations in ways that may enhance their uptake. Future validation of the MHPQ in more diverse samples is needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eAuthor ORCID IDs and Contributions:\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eShannon B. Juengst, PhD (ORCID ID: 0000-0003-4709-545X): Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing (original draft, review \u0026amp; editing)\u003c/p\u003e\n\u003cp\u003eAngelle M. Sander, PhD (ORCID ID: 0000-0001-7494-0298): Writing (original draft, review \u0026amp; editing)\u003c/p\u003e\n\u003cp\u003eMarlene Vega, PsyD (ORCID ID: 0000-0003-4504-8983): Conceptualization, Investigation, Methodology, Writing (original draft, review \u0026amp; editing)\u003c/p\u003e\n\u003cp\u003eMaria Boix-Braga, PhD: Conceptualization, Investigation, Writing (original draft, review \u0026amp; editing)\u003c/p\u003e\n\u003cp\u003eAlka Khera, MD (ORCID ID: 0000-0002-8584-3909): Writing (original draft, review \u0026amp; editing)\u003c/p\u003e\n\u003cp\u003eMonique R. Pappadis, PhD (ORCID ID: 0000-0003-4742-4380): Writing (original draft, review \u0026amp; editing)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All procedures were approved by the UT Southwestern Medical Center Human Protections Research Office (IRB).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from participants; no identifiable data were included in this publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of supporting data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003cbr\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis study was not funded. \u0026nbsp;Dr. Pappadis contributions to this work were supported under grants from the National Institute on Aging [NIA grant number K01AG065492] and the National Institute on Minority Health and Health Disparities [NIMHD contract number L60MD009326L].\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSocial determinants of health. 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Personalized Medicine: Progress and Promise. \u003cem\u003eAnnual Review of Genomics and Human Genetics\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 217\u0026ndash;244. https://doi.org/10.1146/annurev-genom-082410-101446\u003c/li\u003e\n \u003cli\u003eStevens, J. P. (2009). \u003cem\u003eApplied Multivariate Statistics for the Social Sciences, Fifth Edition\u003c/em\u003e (5 edition.). New York: Routledge.\u003c/li\u003e\n \u003cli\u003eThe Standards for Educational and Psychological Testing. (n.d.). \u003cem\u003ehttp://www.apa.org\u003c/em\u003e. Retrieved April 19, 2016, from http://www.apa.org/science/programs/testing/standards.aspx\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables 1-4","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section\u003c/p\u003e"},{"header":"Table 5","content":"\u003cp\u003eTable 5 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"UT Southwestern Medical Center","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"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},"keywords":"Health Belief Model, Psychometrics, Health Literacy, Locus of Control, Exploratory Factor Analysis","lastPublishedDoi":"10.21203/rs.3.rs-3873462/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3873462/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eObjective: \u003c/strong\u003e\u003c/em\u003eTo determine the factor structure of the Multidimensional Health Perceptions Questionnaire (MHPQ), a self-reported multidimensional assessment of health perceptions, in English-speakers and Spanish-speakers in the U.S with and without various health conditions (general population). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e\u003c/em\u003eThe MHPQ previously demonstrated excellent content validity (content validity index=98.1%) and conceptual equivalence in English and Spanish, with a reading grade level of \u003cu\u003e\u0026lt;\u003c/u\u003e8\u003csup\u003eth\u003c/sup\u003e grade in both languages. We administered the original 93-item MHPQ as an anonymous survey (REDCap™) to participants in the general population (items rated on a 1=Strongly disagree to 5=Strongly agree response scale). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003c/em\u003eN=357 participants completed the MHPQ (n=331 English, n=26 Spanish). The sample was 74.2% women, 18-82 years old, 24.1% Hispanic/Latino, predominantly White (68.9%), and highly educated (52.1% with at least an Associate degree). Exploratory Factor Analysis resulted in 65 final items with a multidimensional structure and good internal consistency reliabilities, with the following seven health perceptions domains (% variance, Cronbach’s α): Anticipated Discrimination and Judgement (18.9%, α=.92); Spiritual Health Beliefs (8.6%, α=.89); Social and Emotional Well-being (5.5%, α=.71); Confidence in Healthcare Providers and Medicine (3.5%, α=.85); Health Self-Efficacy (2.9%, α=.79); Trust in Social Health Advice (2.8%, α=.74); and Health Literacy (2.2%, α=.86). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003e\u003c/em\u003eResults suggest that the MHPQ may be a valid and reliable measure for comprehensively characterizing health beliefs in the general population.\u0026nbsp; Future work should validate the MHPQ in specific populations.\u003c/p\u003e","manuscriptTitle":"Factor Structure of the Multidimensional Health Perceptions Questionnaire in English- and Spanish-speakers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-19 17:03:30","doi":"10.21203/rs.3.rs-3873462/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":"f115a983-6b69-42b9-8d81-4a7f0271d2df","owner":[],"postedDate":"January 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28205131,"name":"Psychology"}],"tags":[],"updatedAt":"2024-01-19T17:03:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-19 17:03:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3873462","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3873462","identity":"rs-3873462","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}