Chat with us, powered by LiveChat Please read the article by Kecojevic et al. on 'The impact of COVID-19 epidemic on mental health of undergraduate students in New Jersey, cross-sectional study' (available in t - Writeedu

Please read the article by Kecojevic et al. on ‘The impact of COVID-19 epidemic on mental health of undergraduate students in New Jersey, cross-sectional study’ (available in t


Please read the article by Kecojevic et al. on "The impact of COVID-19 epidemic on mental health of undergraduate students in New Jersey, cross-sectional study" (available in the Articles section). Identify, using the following attached word document format 6310-Week1-Assignment1_Format.docx

  • Gap in the literature that the study addresses
  • Research question(s)
  • Study design
  • Population studied
  • Predictor variable(s)
  • Outcome variable(s)
  • Results (provide answer to the research question(s) based on study findings).

 I encourage you to view the sample assignment and answers above to better understand what is expected for this assignment.

Week 1 – Assignment 1 Rubric

Kecojevic et al. The impact of COVID-19 epidemic on mental health of undergraduate students in New Jersey, cross-sectional study.



Points Earned

Gap in the literature


Research question


Study design


Population studied


Predictor variable(s)


Outcome variable(s)







Patient Education and Counseling 101 (2018) 2233–2240

Contents lists available at ScienceDirect

Patient Education and Counseling

journal homepage: www.elsevier .com/ locate /pateducou

Health insurance literacy and awareness of the Affordable Care Act in a vulnerable Hispanic population

Suad Ghaddara,*, Jihyun Byunb, Janani Krishnaswamic

a Department of Health and Biomedical Sciences, The University of Texas Rio Grande Valley, Edinburg, USA b School of Human Ecology, The University of Texas at Austin, Austin, USA c Department of Pediatrics and Preventive Medicine, The University of Texas Rio Grande Valley, Edinburg, USA


Article history: Received 2 March 2018 Received in revised form 25 August 2018 Accepted 29 August 2018

Keywords: Health insurance literacy Affordable Care Act

Objective: The Patient Protection and Affordable Care Act (ACA) has allowed millions of Americans to obtain coverage. However, many, especially minorities, remain uninsured. With mounting evidence supporting the importance of health insurance literacy (HIL), the purpose of this cross-sectional study is to examine the association between HIL and ACA knowledge. Methods: We conducted 681 in-person interviews with participants at a community health event along the Texas-Mexico border in 2015, after the conclusion of the ACA’s second enrollment period. To assess HIL, we used the Health Insurance Literacy Measure, reflecting consumers’ confidence to choose, compare, and use health insurance. We assessed ACA knowledge through the following question: “How much would you say you know about this health reform law?” Logistic regression was used to examine the association between HIL and ACA knowledge after controlling for several covariates. Results: Almost 70% of participants knew nothing/very little about the ACA. Multivariate analyses revealed that no/very little ACA knowledge was associated with low levels of confidence “choosing health insurance plans” (OR:0.55; 95%CI:0.40-0.75) (full sample) and “comparing plans” (OR:0.56; 95%CI:0.32- 0.96) (U.S.-born sub-sample). Conclusion: No/little ACA knowledge is associated with lower levels of HIL. Practice Implications: Promoting HIL is an essential step towards improving healthcare access.

© 2018 Elsevier B.V. All rights reserved.

1. Introduction

The United States’ health care system has faced an array of challenges, including high costs, health inequities, and high uninsured rates, among others. The Patient Protection and Affordable Care Act (ACA), a monumental health reform effort also known as Obamacare, aimed to address several of the system’s shortcomings, most importantly the high rate of the uninsured which stood at 17% of the population (51 million people) in 2009 [1]. The ACA’s passage in 2010 has allowed more than 20 million Americans to obtain coverage under its provisions [2]. These include expanding Medicaid (government health care coverage for low-income individuals) eligibility in certain states, providing subsidies for qualifying individuals to purchase private health

* Corresponding author at: Department of Health and Biomedical Sciences, The University of Texas Rio Grande Valley, 1201 W. University Dr., Edinburg, TX, 78539, USA.

E-mail addresses: [email protected] (S. Ghaddar), [email protected] (J. Byun), [email protected] (J. Krishnaswami). 0738-3991/© 2018 Elsevier B.V. All rights reserved.

insurance plans in the health insurance marketplaces, prohibiting barriers to enrollment based on pre-existing conditions, and increasing the cut-off age for young adults to stay on a parent’s plan to age 26. Many individuals, however, remain uninsured, especially among minority populations and particularly among Hispanics. Despite considerable outreach efforts and correspond- ing major enrollment gains, 28% of non-elderly Hispanics remain uninsured [2]. In comparison, and for the same time period, only 9% and 15% of non-elderly, non-Hispanic whites and blacks were, respectively, uninsured [2]. Several reasons and persistent challenges to the lack of health coverage remain, including low population awareness of the ACA law, its enrollment guidelines and provisions [3,4]. However, health insurance literacy may be an even more fundamental factor influencing coverage gaps [5–10].

Health insurance literacy (HIL) is defined as “the degree to which individuals have the knowledge, ability, and confidence to find and evaluate information about health plans, select the best plan for their own (or their family's) financial and health circumstances, and use the plan once enrolled [11].” Similar to the evidence supporting an association between low health literacy and poor health outcomes [12], research is starting to reveal that poor

2234 S. Ghaddar et al. / Patient Education and Counseling 101 (2018) 2233–2240

familiarity with a health insurance program, such as Medicare, is associated with a less effective utilization of healthcare services, and consequently poorer health outcomes [13]. Evidence is mounting supporting the importance of HIL in determining health insurance status, healthcare utilization, and health behaviors, among others [6,14,15]. However, few studies have explored HIL within the ACA context, or assessed HIL in Hispanic communities [14]. The purpose of this study is to assess health insurance literacy in a vulnerable Hispanic community and to examine whether ACA knowledge is associated with levels of health insurance literacy.

2. Methods

2.1. Study setting and data collection

Data for this study was collected from participants at Operation Lone Star (OLS), an annual public health emergency preparedness exercise along the Texas-Mexico border. The event is a collabora- tion between various organizations, including local departments of health, the Texas Department of State Health Services, the U.S. military, institutions of higher education, and a myriad of community organizations and volunteers. The event also provides free primary, dental, and vision healthcare services to community residents. In 2015, OLS events and services took place during the week of July 27–31 at five locations across the South Texas Border from Brownsville to Laredo. Data collection for this study took place at one of the locations in Hidalgo County (home to over 800,000 people) [16] which was attended by almost 3000 county residents (children and adults) over the course of the week. As in other Texas-Mexico border counties, the overwhelming majority of the population is of Hispanic or Latino origin (92%) [16]. The county is characterized by high poverty rates (a third of the population lives below the federal poverty level) and low educational attainment (36% of individuals 25 years and over do not have a high school degree) [16]. Lack of healthcare coverage is a main challenge with 43% of individuals 18–64 years old being uninsured in 2015 [17].

We employed a convenience sampling design. Data was collected in-person by trained student interviewers, some of whom were bilingual (English and Spanish). Students approached OLS attendees, who were waiting to receive health services at various stations, with information about the study and invited them to participate. Based on the participant’s preferred language, interviews were conducted in either English or Spanish. After completing the anonymous interview, participants were provided with educational material about diabetes and a bottle of water. All

Table 1 Health Insurance Literacy Measure18.

Selecting health insurance scales Scale 1. Confidence: Choosing a health plan How confident are you that . . . ? Six statements on which respondents rate their level of confidence choosing a hea 1: Not at all confident, 2: Slightly confident, 3: Moderately confident, 4: Very confi

Scale 2. Comparing health plans When comparing health insurance plans, how likely are you to . . . ? Seven statements on which respondents indicate the likelihood of a behavior relat 1: Not at all likely, 2: Somewhat likely, 3: Moderately likely, 4: Very likely

Using health insurance scales Scale 3: Confidence: Using a health plan How confident are you that . . . ? Four statements on which respondents rate their level of confidence about using h 1: Not at all confident, 2: Slightly confident, 3: Moderately confident, 4: Very confi

Scale 4: Being Proactive When using your health insurance plan, how likely are you to . . . ? Four statements on which respondents indicate the likelihood of being proactive w 1: Not at all likely, 2: Somewhat likely, 3: Moderately likely, 4: Very likely

study procedures were approved by the Institutional Review Board at The University of Texas-Pan American (now The University of Texas Rio Grande Valley).

2.2. Measurements

The survey instrument included questions assessing socio- demographic characteristics, knowledge of the ACA, health insurance literacy, ehealth literacy, and health status, among others. The survey instrument was translated to Spanish. We used existing Spanish translations when available (e.g., Census ques- tions). For those items where no Spanish translation was available, a Spanish native speaker translated the survey items. These were in turn reviewed and modified by a Spanish professor with broad academic knowledge and experience in the linguistic usage of both Spanish and English in the region as well as a deep cultural understanding of the target population.

2.2.1. Dependent variable: ACA knowledge We assessed ACA knowledge by the question “How much would

you say you know about this health reform law?” Response options included: nothing, very little, just some, a fair amount, or a great deal. We recoded the survey responses into a dichotomous variable (1, nothing/very little knowledge; 0, otherwise). The question mirrored that used in a nationally-representative sample [8] allowing us to compare our results to other studies.

2.2.2. Independent variable: health insurance literacy We utilized the Health Insurance Literacy Measure (HILM) [18]

to assess health insurance literacy. The HILM is a valid and reliable measure of “consumers’ ability to select and use private health insurance.” It includes 21 items divided into two scales: selecting insurance and using insurance, each of which encompasses two subscales (Table 1). We administered the using health insurance scales (Scales 3 and 4) only to those individuals who reported having healthcare coverage.

2.2.3. Covariates Our analysis controlled for several covariates. Sociodemographic characteristics. We used standard self- report U.S. Census measures to assess a range of sociodemographic characteristics. These included gender, age, ethnicity (being of Hispanic or Latino origin), country of birth, educational attainment, income, and health insurance status.

lth insurance plan. dent

ed to their behavior when choosing a health plan

ealth insurance. dent

hen using their health insurance.

S. Ghaddar et al. / Patient Education and Counseling 101 (2018) 2233–2240 2235 Health literacy. We used two health literacy measures assessing different aspects of the concept. For health literacy, we used the Single Item Literacy Screener [19] which helps identify limited reading ability, an important aspect of health literacy. Participants responded to the question: “How confident are you filling out forms by yourself?” Response options included: not at all, a little bit, somewhat, quite a bit, extremely. We considered those with “extreme” or “quite a bit” of confidence to have adequate levels of health literacy. We assessed eHealth literacy using eHEALS, an 8-item scale, designed to “measure consumers’ combined knowledge, comfort, and perceived skills at finding, evaluating, and applying electronic health information to health problems’’ [20]. Respondents indicated their level of agreement on a 5-point Likert-type scale (1 “Strongly disagree” to 5 “strongly agree”). Higher scores on the summation of responses reflect higher levels of eHealth literacy. The reliability and validity of eHEALS has been established in both English and Spanish [20,21]. Cronbach’s α for the scale was 0.96 for our Spanish-speaking subsample (N = 495) and 0.94 for our English-speaking subsample (N = 172). Health status. Given that poor health and the presence of chronic conditions may represent unmet healthcare needs and, thus, may generate more interest in health coverage as well as awareness of coverage options, we included two measures for health status. We assessed general health status using a validated

Table 2 Participant characteristics by ACA knowledge.

Sociodemographic variables n % Know som a fair am

ACA Knowledge 681 31% Interview language 681 English 177 26 44 Spanish 504 74 26 Of Hispanic/Latino origin 667 Yes 662 99 31 No 5 1 20 Country of birth 666 U.S.-born 172 26 41 Foreign-born 494 74 28 Gender 672 Male 133 20 38 Female 539 80 29 High school graduate 667 Yes 328 49 39 No 339 51 24 Income < $20K 653 Yes 548 84 27 No 105 16 54 Uninsured 680 Yes 79 12 43 No 601 88 29 Self-rated health status 647 Poor/fair 367 57 27 Good/very good/excellent 280 43 37 Diabetes diagnosis 644 Yes 111 17 39 No 533 83 30 Adequate health literacy 666 Yes 246 37 39 No 420 63 26 Political affiliation 651 Yes 219 34 38 No 432 66 27

n Mean (SD) Mean (SD)

Age (range 18–80) 666 38.78 (12.51) 37.35 (12.03)

eHeals (range 8–40) 667 21.30 23.91 (9.58) (10.03)

question from the Behavioral Risk Factor Surveillance System (BRFSS) [22] asking respondents to rate their health (excellent, very good, good, fair, poor). We recoded the health status question as a dichotomous variable (1, fair or poor health; 0, otherwise). We also checked whether participants had a diabetes diagnosis using the BRFSS question that asked whether they had ever been told by a health professional that they had diabetes. Political affiliation. Given the politicized nature of the health reform debate in the U.S., we asked about the political affiliation of participants. We expect that those with any type of affiliation (Republican, Democrat, Independent) will be more likely to know about the ACA relative to those with no affiliation.

2.3. Data analysis

We analyzed data using SPSS (Version 24) [23]. Descriptive analyses generated participant characteristics. We conducted bivariate tests (two-sided chi-square and t tests, where appropri- ate) to examine the association between ACA knowledge and different variables. To assess the internal reliability of the HILM scales in English and Spanish, we used the Cronbach’s alpha coefficient; a coefficient above 0.80 for basic research tools reflects adequate internal consistency [24]. We ran logistic regressions to examine the association between ACA knowledge and health

e, Know nothing or very little (%) p ount, or a great deal (%)

69% <.001

56 74

.592 69 80

.001 59 72

.058 62 71

<.001 61 76

<.001 73 45

.012 57 71

.005 73 63

.060 61 70

<.001 61 74

.006 62 73 Mean p (SD) 39.43 .048 (12.68) 20.15 <.001 (9.15)

2236 S. Ghaddar et al. / Patient Education and Counseling 101 (2018) 2233–2240

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