Journal of Gerontological Nursing

Feature Article 

A Comprehensive Assessment of Risk Factors for Falls in Community-Dwelling Older Adults

Yunchuan (Lucy) Zhao, PhD, MPAff, RN; Jenny Alderden, PhD, RN; Bonnie K. Lind, PhD; Heejung Kim, PhD, GNP-BC, RN

Abstract

Falls in community-dwelling older adults are a complicated phenomenon that are attributed to sociodemographic characteristics, health conditions, functional problems, and environmental factors. The current cross-sectional and correlational study aimed to explore comprehensive risk factors for falls in community-dwelling older adults using a nationally representative data file (N = 5,930). Descriptive statistics were used and multiple logistic regression analyses were performed. Study findings showed that homebound or semi-homebound older adults were 50% more likely to experience a fall than non-homebound individuals. Impaired balance was the strongest predictor (odds ratio [OR] = 2.37, p < 0.001), followed by problems moving around in the home. Arthritis (OR = 1.39, p = 0.009) and depression or anxiety (OR = 1.28, p = 0.013) were additional risk factors. Community health or home health nurses need to assess these risk factors when planning fall intervention programs for older adults using evidence-based prevention strategies. [Journal of Gerontological Nursing, 44(10), 40–48.]

Abstract

Falls in community-dwelling older adults are a complicated phenomenon that are attributed to sociodemographic characteristics, health conditions, functional problems, and environmental factors. The current cross-sectional and correlational study aimed to explore comprehensive risk factors for falls in community-dwelling older adults using a nationally representative data file (N = 5,930). Descriptive statistics were used and multiple logistic regression analyses were performed. Study findings showed that homebound or semi-homebound older adults were 50% more likely to experience a fall than non-homebound individuals. Impaired balance was the strongest predictor (odds ratio [OR] = 2.37, p < 0.001), followed by problems moving around in the home. Arthritis (OR = 1.39, p = 0.009) and depression or anxiety (OR = 1.28, p = 0.013) were additional risk factors. Community health or home health nurses need to assess these risk factors when planning fall intervention programs for older adults using evidence-based prevention strategies. [Journal of Gerontological Nursing, 44(10), 40–48.]

Falls are a major public health concern in older adults. In the United States, approximately one third (35% to 40%) of community-dwelling older adults reported that they had experienced a fall within a given year (Centers for Disease Control and Prevention [CDC], 2016; Krulish & Anemaet, 2008). Falls have an adverse impact on older adults, their families, and public health. In addition to fall-related injuries, older adults may experience pain, reduced functional abilities, hospitalization, institutionalization, loss of independence, and decreased quality of life (Peel, 2011).

In the United States, falls account for more than 80% of all injury admissions to the hospital and are one cause of injury-related deaths in individuals older than 65 (CDC, 2016). In addition, the health care expenditure related to falls significantly increases societal burden. The average Medicare expenditure is approximately $10,000 per fall, and the cost doubles for individuals 72 and older. Medical costs for older adult falls are estimated to be $50 billion annually (Hoffman, Hays, Shapiro, Wallace, & Ettner, 2017). As the population ages, the number of falls, fall-related injuries, and costs of falls are anticipated to increase substantially (Houry, Florence, Baldwin, Stevens, & McClure, 2016).

Falls among community-dwelling older adults are a complicated phenomenon attributed to intrinsic and extrinsic factors simultaneously. Risk factors for falls in community-dwelling older adults are extensively identified in previous studies focusing on demographic, balance- and mobility-related, sensory, psychological, medical, and environmental factors (Ambrose, Paul, & Hausdorff, 2013; Deandrea et al., 2010). Previous studies have found that advanced age, female gender, impaired balance and mobility, visual impairments, depression, and certain chronic diseases (e.g., hypertension, Parkinson's disease, stroke) are associated with falls in older adults (Ambrose et al., 2013; Deandrea et al., 2010). Home environmental hazards, such as loose rugs and clutter, place older adults at increased risk for falls, whereas simple home modifications, including grab bars in the bathroom or shower seats, may decrease older adults' fall risk (Chase, Mann, Wasek, & Arbesman, 2012).

The current study focuses on home environment and mobility. Previous research suggests that older adults spend most of their daily life at home, and that approximately 20% of older adults are homebound or semi-homebound (Cohen-Mansfield, Shmotkin, & Hazan, 2012; Musich, Wang, Hawkins, & Yeh, 2015). Falls that occur at home are associated with the greatest mortality rates in older adults (Deprey, Biedrzycki, & Klenz, 2017). However, current literature addresses fall risk factors in community-dwelling older adults without examining important sociodemographic and mobility factors such as homebound status and mobility in the home. Given the consequence of falls in the home and prevalence of homebound status in older adults, it is essential to examine specific fall risk factors in home settings. The purpose of the current study is to examine comprehensive risk factors for falls among community-dwelling older adults by including homebound status, mobility at home, and home environmental factors in combination with other sociodemographic and medical and psychological factors.

Method

Design and Study Sample

The current secondary data analysis used a cross-sectional and correlational design via Round 6 (2016) data of the National Health and Aging Trends Study (NHATS) released in 2017 (Kasper & Freedman, 2017). The NHATS is a nationally representative survey conducted by Johns Hopkins University sponsored by the National Institute on Aging. Data are collected through personal interviews by trained personnel using instruments investigating social, health, and economic consequences of aging and disability (Freedman et al., 2011; Kasper & Freedman, 2017). The NHATS samples comprised mainly Medicare beneficiaries ages ≥65. Some subgroups, such as racial/ethnic (African American individuals) or old-older subgroups were oversampled to increase representativeness (Kasper & Freedman, 2017). For the purpose of the current study, the sample included only community-dwelling older adults; thus, individuals living in nursing homes or assisted living facilities were excluded from the study. The final sample comprised a total of 5,930 community-dwelling adults ages ≥65.

Measures

Outcome Variable. Falls within the past 1 month was the outcome variable. NHATS defines a fall as any fall, slip, or trip in which the participant loses balance and lands on the floor or ground or at a lower level than the one at which he/she started (Kasper & Freedman, 2017). Participants reported whether they had a fall (yes/no) in the past 1 month prior to the survey.

Independent Variables. Factors associated with falls were selected based on extensive literature review (Deandrea et al., 2010; Meucci, Gozalo, Dosa, & Allen, 2016; Wing, Burke, Clarke, Feng, & Skolarus, 2017) for multiple logistic regression analyses. These variables were collected in the NHATS Round 6, including personal conditions, environmental factors, and physical functioning and limitation factors (Kasper & Freedman, 2017). A conceptual framework was developed based on the NHATS disability conceptual framework (Kasper & Freedman, 2017) (Figure). Personal conditions included sociodemographic characteristics and health conditions. Environmental factors included factors in the bathroom and home environment. Physical functioning and limitations included activities of daily living (ADL) difficulties, instrumental activities of daily living (IADL) difficulties, and other physical problems that limited activities.

Factors associated with falls in community-dwelling older adults.Note. ADLs = activities of daily living; IADLs = instrumental activities of daily living.

Figure.

Factors associated with falls in community-dwelling older adults.

Note. ADLs = activities of daily living; IADLs = instrumental activities of daily living.

Sociodemographic characteristics included categorical variables such as age, race/ethnicity, education, home-bound status, gender, and living arrangement, as well as one continuous variable, body mass index (BMI). Ages reported in the NHATS survey were grouped into 5-year categories. Race and ethnicity were combined and categorized as non-Hispanic White, non-Hispanic Black, non-Hispanic other (including Asian and Pacific Islander), and Hispanic. Homebound status was classified into three groups based on measures developed by Ornstein et al. (2015): participants were considered (a) homebound if they never or rarely went out; (b) semi-homebound if they needed help going out and would not go out or experienced difficulty going out by themselves without help from others; and (c) non-homebound if they could leave the home on their own without difficulty. Gender (men and women) and living arrangement (living alone or with others) were dichotomized.

Chronic diseases comprised physical medical conditions and mental health problems. The eight medical conditions were classified as dichotomous variables based on participants' reports of whether they were diagnosed with the following conditions: heart disease, hypertension, arthritis, osteoporosis, diabetes, lung disease, stroke, or dementia. Depression was assessed using the calculated Patient Health Questionnaire (PHQ-2), and anxiety was assessed using the Generalized Anxiety Disorder Scale (GAD-2). Scores ≥3 on each scale indicated presence of the condition (Kroenke, Spitzer, Williams, & Löwe, 2010).

To investigate the relationship between falls and the home environment, 15 variables were examined, including four variables in bathroom modification (grab bar in shower or bathtub, grab bar near toilet, shower seat in shower or bathtub, and raised toilet or toilet seat); six inside-home problems (peeling paint, pests, broken furniture, flooring problems, tripping hazards, and clutter); and five outside environmental factors (litter on street, broken windows, crumbling foundation, missing bricks, and broken steps). These were dichotomous variables (yes/no) reported to the NHATS either by participants or based on the survey interviewers' observations (Kasper & Freedman, 2017).

Physical functioning was assessed based on difficulties with ADLs (i.e., eating, bathing, toileting, dressing activities) or IADLs (i.e., laundry, grocery shopping, meal preparation, banking or paying bills, medication tracking), and other physical limitations as outlined below. Each item in the ADLs and IADLs was coded into a dichotomous variable and the total ADL and IADL score was calculated. If participants had a little, some, or a lot of difficulty, or needed help performing the item on an ADL or IADL, they were identified as having ADL or IADL difficulty for the item. Otherwise, no ADL or IADL difficulty was identified. The total ADL (0 to 4) or IADL (0 to 6) diffi-culty score was then calculated, with 1 point given for each activity causing difficulty. These variables were continuous variables. Other physical functioning variables included: (a) limitations due to lack of lower body strength, (b) problems with balance and coordination, (c) pain, and (d) problems moving around the house. Each variable was coded as 1 if the variable was present, based on participant self-report, and 0 if the variable was not present.

Hearing or vision impairment was assessed based on self-report. Participants were classified as having hearing impairment if they were deaf, used a hearing aid, could not use a telephone due to hearing problem, or could not carry on a conversation with a radio or television on or in a quiet room. Participants were classified as having vision impairment if they wore glasses, contacts, or other vision aids; could not see well across the street; could not watch television across the room; or could not read newspaper print.

Data Analysis

The current secondary data analysis was conducted after acquiring the exempt status of the Institutional Review Board of the affiliated university. Descriptive statistics were used to examine the characteristics of the sample. Unweighted bivariate tests with chi-square were used to test the relationships between the outcome variable and each independent variable. Multiple logistic regression analyses were performed to identify factors associated with falls. Due to the large number of independent variables, a series of preliminary models were built for each group of independent variables: (a) sociodemographic characteristics; (b) chronic diseases; (c) home environmental factors, including bathroom modifications and inside-home problems; (d) outside-home environmental factors; and (e) physical functioning and limitation variables.

Based on results of the preliminary models, the independent variables with p values ≤0.20 from each group were included in the combined models. Using the Akaike information criterion (AIC) value and the receiver operating characteristic (ROC) curve as criteria, multiple combined models were tested, and the final model included nine significant or nearly significant predictor variables with the best goodness of fit statistics (AIC and area under ROC curve). Because of the exploratory nature of the current analysis, variables with p values <0.10 were retained in the final model. The final model included 5,824 of 5,930 individuals in the sample (98%). Education was the only factor with >5% missing data, and it was not a significant predictor of falls in either bivariate tests or preliminary models. Thus, any imputation for missing data was not conducted. All statistical analyses were conducted with STATA® 14. The sampling weights and design factors of NHATS were accounted for by using the svy command in STATA 14 and the replicate weights provided in the data file.

Results

Table 1 shows the results of descriptive statistics for the unweighted sample along with bivariate tests of relationships with falls (N = 5,930). Of 5,930 respondents, 683 (11.5%) reported experiencing a fall in the past 1 month prior to the interview. Most participants were Non-Hispanic White (68.4%) or female (57.2%). Hypertension (71.9%) was the most prevalent and stroke (2.4%) was the least prevalent problem among chronic disease conditions.

Sociodemographic, Medical, and Physical Variables of ParticipantsSociodemographic, Medical, and Physical Variables of ParticipantsSociodemographic, Medical, and Physical Variables of Participants

Table 1:

Sociodemographic, Medical, and Physical Variables of Participants

Approximately one third of participants lived alone and 23.2% were totally homebound or semi-homebound. Approximately one half of respondents reported having grab bars in their shower or bathtubs, 29.8% had clutter in the home, and 39.7% had broken steps outside the home. Among physical functioning and limitation factors, problems moving around inside the home (55.4%) was the most prevalent problem. Participants reported more IADL difficulties than ADL difficulties. The results of bivariate tests show significant relationships between falls in the past 1 month with most independent variables (Table 1), except for gender, race/ethnicity, and living arrangement as well as home modification with grab bar in bathroom, raised toilet/seat, paint peeling, pests inside home, broken furniture, and outside environmental factors (except for litter on street).

Table 2 lists the results of the logistic regression analysis. Homebound status was a significant predictor of falls. Totally homebound or semi-homebound older adults were more than 50% more likely to experience a fall (odds ratio [OR] = 1.50, p = 0.004; OR = 1.67, p = 0.047, respectively), whereas living alone was a protective factor (OR = 0.78, p = 0.042). Men were 31.4% (OR = 1.31, p = 0.035) more likely to fall than women. The strongest significant predictor was balance limiting activities (OR = 2.37, p < 0.001). Older adults whose balance problems limited activities were twice as likely to fall compared to those without balance problems. Problems moving around the home was another strong predicator. Participants with few problems moving around were 43% (OR = 1.43, p = 0.01) more likely to experience a fall, and participants with many problems moving around were 80% (OR = 1.80, p = 0.002) more likely to experience a fall compared to participants without problems moving around the home. Having arthritis or depression/anxiety placed older adults at increased risk for falls (OR = 1.39, p = 0.009; OR = 1.28, p = 0.013, respectively).

Results of Logistic Regression Analysis

Table 2:

Results of Logistic Regression Analysis

Discussion and Implications

The current study examined the comprehensive risk factors for falls among community-dwelling older adults. Several sociodemo-graphic and functioning characteristics were identified as significant risk factors. A significant difference was observed between homebound or semi-homebound older adults and non-homebound participants. Although no previous study has examined specific fall risk factors among homebound older adults as a vulnerable population, homebound older adults often have functional disabilities with multiple chronic diseases (Qiu et al., 2010; Vu, Dean, Mwamburi, Au, & Qiu, 2013), which can place them at high risk for falls (Deandrea et al., 2010). This finding has important clinical implications for public and community health nursing, especially home health nursing. When providing home health care for homebound older adults, home health nurses need to conduct thorough fall risk assessment and develop appropriate fall prevention strategies.

The association between living alone and decreased fall risk was unexpected. Findings from previous studies on the association between falls and living alone in older adults are inconsistent. Whereas living alone was identified as a risk factor for falls and recurrent falls in a systematic review and meta-analysis (Deandrea et al., 2010), Wing et al. (2017) found stroke survivors who lived alone were less likely to fall compared to those who lived with others. In a study examining the relationship between living alone and fall risks in community-dwelling middle age and older adults, individuals who lived alone reported more falls than those who lived with others, except for individuals ages 61 to 70 (Elliott, Painter, & Hudson, 2009). In the current study, men had a higher risk of falling than women, although female gender was identified as a risk factor in previous studies (Ambrose et al., 2013; Deandrea et al., 2010). The inconsistent findings regarding the relationships between falls and living arrangement and gender warrant further investigation.

In the current study, researchers found that having problems moving around in the home was strongly associated with falls. To the best of the researchers' knowledge, the current study is the first that examined and identified problems moving around in the home as a risk factor for falls in older adults. As older adults spend the majority of their time in the home, this finding has significant clinical implications. Public health or home health nurses need to identify older adults with problems moving around in the home and provide resources for these older adults to obtain assistance with mobility in the home, including obtaining mobility devices as needed.

Impaired balance was the strongest risk factor for falls. This finding is in line with previous studies (Ambrose et al., 2013; Muir, Berg, Chesworth, Klar, & Speechley, 2010; Tinetti & Kumar, 2010). Given the significant association between falls and impaired balance, it is imperative to assess older adults' balance function. To assess balance problems, home health nurses may use either a valid balance assessment tool such as the Berg Balance Scale (Pickenbrock, Diel, & Zapf, 2016) or self-reports of balance problems. Research shows that self-report of balance problems is a simple method to identify balance impairments associated with future fall risk. In a study conducted among community-dwelling older adults, self-report of balance problems demonstrated a significant association with future falls (relative risk [RR] = 1.58, 95% confidence interval [CI] [1.06, 2.35]) and injurious falls (RR = 1.95, 95% CI [1.15, 3.31]) (Muir et al., 2010).

The current study also found that having certain chronic health conditions, including depression or anxiety and arthritis, was associated with significantly increased risk for falls in older adults. These results support findings from previous studies. It is not surprising that arthritis was a risk factor, as older adults with arthritis often have mobility impairments, which increases risk for falls (Baker, Barbour, Helmick, Zack, & Al Snih, 2017). In a study that explored the association between falls and chronic health conditions, depression was identified as the strongest risk factor for falls and recurrent falls, and arthritis was another major risk factor (Paliwal, Slattum, & Ratliff, 2017). A systematic review and meta-analysis of studies on depression and fall risks revealed that older adults with depressive symptoms were at significantly increased risk for falls (Kvelde et al., 2013). High levels of anxiety were found to be associated with a 53% increased risk for falls among older adults in a meta-analysis of the association between anxiety and falls (Hallford, Nicholson, Sanders, & McCabe, 2017). This finding suggests that depression should be assessed and screened when assessing older adults' fall risks. Community health nurses and home health nurses should pay close attention to older adults with depressive symptoms and develop appropriate fall prevention strategies for these high-risk individuals.

Limitations

The current secondary data analysis has several limitations. The NHATS data are self-reported; therefore, recall bias and self-reporting errors may decrease the reliability of collected data. The generalizability of the study findings may be limited to community-dwelling older adults on Medicare. The results may not be generalizable to community-dwelling older adults younger than 65.

Conclusion

Each year, more than one third of community-dwelling older adults experience a fall, and 11.5% of the current study sample reported experiencing a fall in the past 1 month. The current comprehensive assessment study of fall risk factors revealed that several sociodemographic characteristics (i.e., homebound status and male gender), functional factors (i.e., problems moving around the home and impaired balance), and chronic health problems (i.e., depression or anxiety and arthritis) were significant factors contributing to falls among community-dwelling older adults. When performing fall assessment for community-dwelling older adults, nurses need to pay close attention to older adults who are totally home-bound or semi-homebound, and thoroughly assess older adults with chronic health problems and functional limitations. Further research on the association between falls among older adults and living arrangement and gender is needed to better understand the relationships between these variables.

References

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Sociodemographic, Medical, and Physical Variables of Participants

VariableN (%)Individuals Who Fell, n (%)Individuals Who Did Not Fall, n (%)p Value
Total5,930 (100)683 (11.5)5,247 (88.5)
Sociodemographic characteristics
  Age (years)0.03
    65 to 69706 (11.9)66 (9.7)640 (12.2)
    70 to 741,414 (23.8)160 (23.4)1,254 (23.9)
    75 to 791,367 (23.1)141 (20.6)1,226 (23.4)
    80 to 841,110 (18.7)132 (19.3)978 (18.6)
    85 to 89820 (13.8)115 (16.8)705 (13.4)
    ≥90513 (8.7)69 (10.1)444 (8.5)
  Gender0.18
    Female3,393 (57.2)370 (54.2)3,023 (57.6)
    Male2,537 (42.8)313 (45.8)2,224 (42.4)
  Race/ethnicity0.24
    Non-Hispanic White4,054 (68.4)473 (69.3)3,581 (68.3)
    Non-Hispanic Black1,235 (20.8)124 (18.2)1,111 (21.2)
    Hispanic357 (6.0)53 (7.8)304 (5.8)
    Non-Hispanic other277 (4.7)32 (4.7)245 (4.7)
  Education<0.001
    Less than high school1,244 (22.9)180 (28.8)1,064 (22.1)
    High school1,536 (28.3)168 (26.9)1,368 (28.5)
    Beyond high school2,650 (48.8)277 (44.3)2,373 (49.4)
  BMI (mean, SD)27.6 (6.26)27.3 (6.25)27.7 (6.25)0.18
  Living arrangement0.06
    Living with others4,107 (69.3)512 (74.9)3,595 (68.5)
    Living alone1,823 (30.7)171 (25.1)1,652 (31.5)
  Homebound status<0.001
    Non-homebound4,479 (76.8)379 (56.8)4,100 (79.3)
    Semi-homebound971 (16.6)202 (30.3)769 (14.9)
    Homebound385 (6.6)86 (12.9)299 (5.8)
Chronic diseases
  Hypertension4,264 (71.9)514 (75.3)3,750 (71.5)0.01
  Arthritis3,911 (65.9)513 (75.1)3,398 (64.8)<0.001
  Diabetes1,729 (29.2)235 (34.4)1,494 (28.5)0.002
  Osteoporosis1,615 (27.2)205 (30.0)1,410 (26.9)0.03
  Heart disease1,306 (22.0)193 (28.3)1,113 (21.2)<0.001
  Lung disease1,174 (19.8)169 (24.7)1,005 (19.2)<0.001
  Depression or anxiety1,041 (17.6)204 (29.9)837 (15.9)<0.001
  Dementia404 (6.8)92 (13.5)312 (6.0)<0.001
  Stroke139 (2.3)27 (4.0)112 (2.1)0.005
Environmental factors
  Bathroom modification
    Shower seat in shower/bathtub2,735 (46.1)387 (56.7)2,348 (44.8)<0.001
    Grab bar in shower/bathtub2,713 (45.8)293 (42.9)2,420 (46.1)0.51
    Raised toilet/toilet seat2,260 (38.1)296 (43.3)1,964 (37.4)0.08
    Grab bar near toilet1,326 (22.4)184 (26.9)1,142 (21.8)0.004
  Inside home problemsa
    Clutter in home1,549 (29.8)217 (35.8)1,332 (29.0)<0.001
    Tripping hazards491 (8.8)75 (11.7)416 (8.5)<0.001
    Flooring problem222 (4.0)36 (5.6)186 (3.8)0.005
    Paint peeling170 (3.1)24 (3.8)146 (3.0)0.47
    Pests114 (2.1)16 (2.5)98 (2.0)0.06
    Broken furniture108 (1.9)15 (2.3)93 (1.9)0.17
  Outside environment
    Broken steps2,353 (39.7)251 (36.8)2,102 (40.1)0.26
    Litter on street556 (9.4)78 (11.4)478 (9.1)0.02
    Missing bricks221 (3.7)21 (3.1)200 (3.8)0.35
    Crumbling foundation183 (3.1)16 (2.3)167 (3.2)0.68
    Broken windows139 (2.3)13 (1.9)126 (2.4)0.97
  Physical functioning and limitations
    Problems moving around in home3,289 (55.5)494 (72.3)2,795 (53.3)<0.001
    Pain limits activities1,721 (29.0)296 (43.3)1,425 (27.2)<0.001
    Lower body strength limits activities1,490 (25.1)301 (44.1)1,189 (22.7)<0.001
    Vision impairment1,441 (24.3)218 (32.0)1,223 (23.3)<0.001
    Balance limits activities1,038 (17.5)266 (39.0)772 (14.7)<0.001
    Hearing impairment996 (16.8)150 (22.0)846 (16.1)0.01
    Total ADL difficulties (mean, SD)0.47 (0.95)0.92 (1.24)0.41 (0.89)<0.001
    Total IADL difficulties (mean, SD)0.95 (1.52)1.55 (1.80)0.87 (1.46)<0.001

Results of Logistic Regression Analysis

VariableOdds Ratio (OR)SEt Testp Value95% CI for OR
Homebound status
  Non-homebound (Reference)
  Semi-homebound1.500.203.040.004*[1.15, 1.96]
  Homebound1.670.422.030.047*[1.01, 2.75]
Male1.310.172.160.035*[1.02,1.69]
African American0.800.11−1.640.106[0.61, 1.05]
Living alone0.780.10−2.080.042*[0.61, 0.99]
Depression or anxiety1.280.122.580.013*[1.06, 1.55]
Arthritis1.390.172.710.009*[1.09, 1.77]
Problems moving around
  None (Reference)
  Rarely/few1.430.192.660.010*[1.09, 1.88]
  Often/many1.800.333.230.002*[1.25, 2.60]
Balance limits activity2.370.316.570.000*[1.82, 3.08]
Hearing impairment1.260.181.650.11[0.95, 1.66]
Authors

Dr. Zhao is Assistant Professor, and Dr. Alderden is Assistant Professor, School of Nursing, Boise State University, Boise, Idaho; Dr. Lind is Research Assistant Professor, School of Public Health and Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon; and Dr. Kim is Assistant Professor, College of Nursing and Mo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Korea.

The authors have disclosed no potential conflicts of interest, financial or otherwise. This study was supported by a Faculty Research fund provided by the School of Nursing, Boise State University. Dr. Lind receives payment for statistical analysis from Boise State University.

Address correspondence to Heejung Kim, PhD, GNP-BC, RN, Assistant Professor, College of Nursing and Mo-Im Kim Nursing Research Institute, Yonsei University, Room 614 College of Nursing, 50-1 Yonseiro, Seodaemun-gu, Seoul, Korea, 03722; e-mail: hkim80@yuhs.ac.

Received: May 12, 2018
Accepted: July 23, 2018

10.3928/00989134-20180913-04

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