Journal of Professional Nursing 42 (2022) 290–300
Contents lists available at ScienceDirect
Journal of Professional Nursing
journal homepage: www.elsevier.com/locate/jpnu
Positive and negative psychosocial factors related to healthy and unhealthy
weight control among nursing students
Jennifer L. Barinas, M.A. a, *, Ryon C. McDermott, Ph.D. b, Susan G. Williams, Ph.D., RN c,
Sharon M. Fruh, Ph.D., RN, FNP-BC, FAANP c, Caitlyn Hauff, Ph.D. d, Geoffrey M. Hudson, Ph.D.,
CSCS d, Rebecca J. Graves, Ph.D., NP-C c, Bernadette Mazurek Melnyk, Ph.D., APRN-CNP,
FAANP, FNAP, FAAN e
a
Department of Psychology, University Commons 1000, University of South Alabama, Mobile, AL 36608, United States of America
Department of Counseling and Instructional Sciences, University Commons 3800, University of South Alabama, Mobile, AL 36688, United States of America
c
College of Nursing, 5721 USA Drive North, University of South Alabama, Mobile, AL 36688, United States of America
d
Department of Health, Kinesiology, and Sport, Suite 1016, University of South Alabama, Mobile, AL 36688, United States of America
e
College of Nursing, 1585 Neil Avenue, The Ohio State University, Columbus, OH 43210, United States of America
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Nursing student health
Weight management
Anxiety
Self-efficacy
Background: Although nursing students are educated on the importance of exercising regularly and maintaining a
well-balanced diet, many do not practice healthy weight management behaviors, and some even use unhealthy
weight loss methods. Yet, little research has examined both positive and negative psychosocial variables related
to weight control among nursing students.
Purpose: The present study aimed to identify the most salient psychosocial variables related to healthy and
unhealthy weight control among nursing students.
Method: Using survey data from 241 nursing students, structural equation modeling was conducted to examine
the relative contributions of eight interrelated psychosocial variables, including constructs from a strengths
perspective (health-specific hope, health self-efficacy, social support, and body satisfaction) and from a deficit
perspective (depression, anxiety, weight perception, and barriers to physical activity).
Results: Results showed that the degree to which individuals perceive themselves to be overweight was related to
both healthy and unhealthy weight control. Aside from weight perception, health self-efficacy produced the
strongest association with healthy weight control, and anxiety produced the strongest association with unhealthy
weight control. The structural model explained 23 % of the variance in healthy weight control and 29 % of the
variance in unhealthy weight control.
Conclusions: These findings emphasize the need for tailored, integrated weight management interventions for
nursing students that equip them with effective anxiety management skills and build self-efficacy.
Nursing students face distinct challenges in managing their health
and well-being (Bartlett et al., 2016; Fronteira & Ferrinho, 2011; Graves
et al., 2020; McDermott et al., 2020; Mills et al., 2020; Pulido-Martos
et al., 2012; Tung et al., 2018; Younas, 2017). Maintaining a healthy
weight is especially difficult in a fast-paced and stressful learning
environment with little time for self-care (Lehmann et al., 2014; Phiri
et al., 2014; Stanton et al., 2021). Indeed, up to 45 % to 65 % of nursing
students have a body mass index (BMI) that is classified as overweight or
obese (Gormley & Melby, 2020; Miller et al., 2008; Williams et al., 2018;
Zapka et al., 2009). The negative health effects associated with obesity
(such as increased risk for cardiovascular disease, type II diabetes,
mental health issues, orthopedic conditions, and cancer) are widely
known (Bray, 2004; Cheng et al., 2016; Pi-Sunyer, 2002; Rajan &
Menon, 2017). Thus, understanding weight control behaviors in nursing
students may provide critical information to inform health promotion
efforts in this population.
A central goal of health promotion is to increase healthy behaviors
while simultaneously decreasing unhealthy behaviors. Unfortunately,
many nursing students do not practice healthy weight management
behaviors, such as engaging in routine physical activity and eating meals
* Corresponding author at: Department of Psychology, University Commons 1000, University of South Alabama, Mobile, AL 36608, United States of America.
E-mail address: jlb1922@jagmail.southalabama.edu (J.L. Barinas).
https://doi.org/10.1016/j.profnurs.2022.07.017
Received 17 November 2021; Received in revised form 21 July 2022; Accepted 25 July 2022
Available online 10 August 2022
8755-7223/© 2022 Published by Elsevier Inc.
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
meeting the recommended nutritional content (Blake et al., 2011;
Graves et al., 2020; Ross et al., 2017). Furthermore, nursing students
may use unhealthy methods of losing weight such as restricting portions,
skipping meals, and using diet pills (Levinson et al., 2020; Stanton et al.,
2021). These unhealthy weight control behaviors can often be pre­
cursors to eating disorders, such as anorexia or bulimia (Graham et al.,
2020; Hazzard et al., 2021; Jebeile et al., 2021).
To provide a nuanced perspective of nursing students' healthy and
unhealthy weight control behaviors, the present study drew upon a
variety of psychological (e.g., mental health and well-being; Emmer
et al., 2020; Mata & Hertwig, 2018), behavioral (e.g., diet and exercise;
Johns et al., 2014), and social factors (e.g., social support and
accountability; McGill et al., 2020; Wadden et al., 2020). Additionally,
the present investigation recognizes that such factors (referred to as
psychosocial variables from this point forward) can be either positive
(psychosocial strengths) or negative (risk factors). While addressing
nursing students' psychosocial deficits provides potentially important
information about which factors need to be reduced, such a deficit
perspective does not yield information about what should be enhanced.
By contrast, a positive or strengths-based perspective provides infor­
mation about which variables could be harnessed or enhanced to help
nursing students thrive. Accordingly, the aim of the present study was to
examine how a variety of positive and negative psychosocial variables
were related to healthy and unhealthy weight control behaviors among
nursing students.
comprehensive reviews). For instance, in a particularly large sample of
college students (N = 2265), researchers found that greater levels of
global hope were positively associated with more frequent exercising
and attempts to limit fat intake (Berg et al., 2011). To date, researchers
have yet to examine health-specific hope (i.e., agency and pathways
thinking for health goals) in relation to healthy and unhealthy weight
control. Nevertheless, the rich body of research linking global hope to
health behaviors suggests that health-specific hope should be positively
associated with healthy weight management behaviors.
Health self-efficacy
Self-efficacy is a strengths-based construct from social cognitive
theory that has been identified to be a strong predictor of health
behavior, including weight control behavior (Foreyt & Goodrick, 1994).
Health self-efficacy refers to the belief in one's capacity to engage in
behaviors or implement changes to improve one's health (Bandura,
1977; Lee et al., 2008). Prior research has shown the health-promoting
effects of increased health self-efficacy. For example, one study
involving young adults found that enhancing self-efficacy was associ­
ated with improved eating habits and greater weight loss (Roach et al.,
2003). For these reasons, nursing students with greater health selfefficacy may be especially well-equipped to manage their weight using
healthy methods, in part due to an increased likelihood to: (a) initiate
healthy behavior change, and (2) persist despite challenges or setbacks
(Schwarzer & Warner, 2013).
Psychosocial factors
There is a dearth of literature pertaining to psychosocial factors and
weight control behaviors among nursing students in the United States
(U.S.). Indeed, weight control behaviors have been more widely studied
in other populations (i.e., general college student or adolescent samples,
individuals diagnosed with eating disorders; Allan & Goss, 2014; Ken­
nedy et al., 2019; Lyzwinski et al., 2018; Nagata et al., 2018). A smaller
number of studies have focused on weight control behaviors among
nursing students (Blake, Stanulewicz, & Griffiths, 2017; Chan, 2014;
Ham & Lim, 2017; Jeong, 2020; Lee & Kim, 2020), with the majority
conducted outside of the U.S. (e.g., South Korea, China, and the United
Kingdom). Due to contextual differences in diet, rates of overall obesity,
and training, the findings from these studies may not generalize to
nursing students in the U.S. Additionally, most of these studies have
focused on behavioral aspects rather than psychological or social con­
tributors and few have examined the relative contributions of both
health promoting factors and health risk factors in one model of weight
management behavior.
Given the paucity of research on specific psychosocial factors of U.S.
nursing students in the extant literature, the present study advanced
several variables that, in theory, may be especially relevant to weight
control behaviors in this population from a strengths perspective: (a)
health-specific hope, (b) health self-efficacy, (c) social support, and (d)
body satisfaction. Additionally, we proposed a variety of psychosocial
variables from a deficit perspective: (a) depression, (b) anxiety, (c)
weight perception, and (d) barriers to physical activity. In the following
sections, research supporting the links between each of these variables
and nursing students’ healthy and unhealthy weight management be­
haviors are briefly reviewed.
Social support
The majority of prior research has found social support to be posi­
tively related to healthy weight management (Lemstra et al., 2016;
Verheijden et al., 2005). As such, social support has often been used to
enhance weight management interventions, most commonly involving
family or support groups (Verheijden et al., 2005). Social support can
benefit healthy weight control in a variety of ways: accountability;
emotional support (encouragement, positive reinforcement); informa­
tion and problem-solving (advice, strategies); instrumental support
(help with cooking healthy meals); and contextual changes (stocking the
home with healthier food options) (Reading et al., 2019; Verheijden
et al., 2005). The relationship between social support and healthy
nutrition and physical activity has also been observed in nursing student
samples (Blake, Stanulewicz, & Griffiths, 2017; Suherman et al., 2018).
However, no studies to our knowledge have examined the relative
contribution of social support in the context of other relevant variables
such as self-efficacy or hope.
Depression
Depression is prevalent among nursing students, with a recent metaanalysis of 27 studies finding a pooled depression prevalence of 34.0 %
among U.S. and international nursing students (Tung et al., 2018).
Depression can often serve as a barrier to healthy weight control and
lead to unhealthy weight-related practices. Many of the hallmark
symptoms of depression, including feelings of sadness, hopelessness, low
energy, lack of interest in activities, and appetite changes (American
Psychiatric Association, 2013), can make engaging in healthy weight
control even more challenging (Glowacki et al., 2017). Thus, depressed
nursing students may be especially likely to avoid healthy weight con­
trol behaviors that involve being active (e.g., exercising or preparing
healthy meals). Further, nursing students who are depressed may also be
more likely to engage unhealthy strategies to manage their weight.
Supporting this later possibility, disordered eating is a common feature
among depressed college women (Allgöwer et al., 2001; Gitimu et al.,
2016; Harring et al., 2010).
Health-specific hope
Snyder (1994, 2000) defined global hope as two interrelated di­
mensions of positive thinking: agency and pathways (Snyder et al.,
1991). Agency thinking reflects beliefs that one can meet specific goals,
and pathways thinking corresponds to perceptions that one can over­
come goal-blocking obstacles. Higher levels of global hope are robustly
associated with greater psychological well-being and proactive health
behaviors (see Rand & Cheavens, 2009; Rasmussen et al., 2018 for
291
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
Anxiety
The present study
Anxiety is another commonly reported mental health concern in
nursing students (Chernomas & Shapiro, 2013; Cowen et al., 2016;
Villeneuve et al., 2018). During the COVID-19 pandemic, studies found
that over half of nursing students (55.9 %) reported moderate or severe
symptoms of anxiety (Savitsky et al., 2020). Researchers have suggested
that nursing students may be susceptible to anxiety due to academic
demands and facing new, often high-stress situations in clinical settings
(Duty et al., 2016; Kim, 2003; Wang et al., 2019). In the extant litera­
ture, anxiety and physical activity research has primarily consisted of
exercise intervention studies (Conn, 2010; Rebar et al., 2015). However,
Thome and Espelage (2004) found that college students with anxiety
were more likely to engage in exercise only if disordered eating was
present. College students without anxiety were less likely to engage in
exercise (Thome & Espelage, 2004). Thus, depending on contextual
factors, anxiety may lead to unhealthy weight control behaviors such as
over-exercising or skipping meals. Anxiety is often comorbid with
depression, and thus, the same factors that may steer nursing students
away from healthy eating behaviors (e.g., lack of time and energy) may
also be present for students with greater anxiety symptomology.
Our review of the literature revealed several positive and negative
psychosocial variables that may be relevant to healthy and unhealthy
weight control behaviors. However, comparatively little research exists
with these constructs in relation to weight control behaviors among
nursing students specifically. While the available evidence suggests that
each of these constructs could be relevant to weight control behavior
among any college-aged individual, researchers have noted that nursing
students may have unique mental health profiles compared to other
students (McDermott et al., 2021). Therefore, a central goal of the pre­
sent study was to examine the possible utility of these constructs as
potential intervention targets by assessing each construct's relationship
with healthy and unhealthy weight control behaviors in a nursing stu­
dent sample.
It also is important to note that the eight psychological, behavioral,
and social variables reviewed for this study do not exist in isolation. For
example, depression symptoms are often comorbid with anxiety symp­
toms (Pollack, 2005). Although conceptually distinct constructs (Rand,
2018), hope and self-efficacy are also positively correlated (O'Sullivan,
2011). Likewise, social support has been negatively associated with
anxiety and depression (Gariépy et al., 2016). In other words, each of the
eight psychosocial variables reviewed are likely interrelated. Therefore,
a second goal of the present study was to understand which variables
were the most salient correlates of healthy and unhealthy weight control
behaviors. Such information will help identify the critical intervention
targets that can be reduced (psychosocial deficits) or enhanced (psy­
chosocial strengths) to help nursing students maintain a healthy weight
in a healthy way.
Two primary hypotheses (one for each set of psychosocial constructs)
guided our analyses. First (Hypothesis 1), we expected health-specific
hope, health self-efficacy, social support, and body satisfaction to be
positively associated with healthy weight control behaviors and nega­
tively associated with unhealthy weight control behaviors. Second
(Hypothesis 2), we also predicted that depression, anxiety, barriers to
physical activity, and perceiving oneself as overweight would be nega­
tively associated with healthy weight control behaviors and positively
associated with unhealthy weight control behaviors. Given the lack of
research on the present psychosocial variables among nursing students,
we did not advance any hypotheses specific to which of these constructs
would be most relevant to either healthy or unhealthy weight control.
Barriers to physical activity
Exercise has been shown to be an essential component in many
weight control strategies due to its numerous mental and physical health
benefits (Pascoe et al., 2020; Zhang et al., 2021). While healthy physical
activity does not burn a significant number of calories to contribute to
short-term weight loss, it is a very strong predictor of success with longterm weight control (6–24 months; Franz et al., 2007; Ostendorf et al.,
2018; Rojo-Tirado et al., 2021). As a result, barriers to physical activity,
such as limited time or motivation, are critical factors influencing
overall weight management. It is a logical proposition that nursing
students who perceive barriers in this domain will also engage in fewer
healthy weight control behaviors. In addition, barriers to physical ac­
tivity may lead to unhealthy weight control practices that are perceived
as easier to implement (e.g., diet pills, disordered eating practices).
Body appraisals
Our last category of psychosocial variables encompasses two con­
structs related to body appraisals. The first, body satisfaction, has been
conceptualized as positive body image or having respect and acceptance
for one's body (Tiggemann & McCourt, 2013; Tylka, 2011; Tylka &
Wood-Barcalow, 2015b). Positive body image has been linked to higher
levels of intuitive eating and psychological well-being, specifically selfesteem and coping, and lower levels of disordered eating behaviors
among women (Tylka & Wood-Barcalow, 2015a). Additionally, WoodBarcalow et al. (2010) reported that individuals presenting with positive
body image are more likely to care for their appearance through physical
activity and healthy eating.
In addition to an overall positive body image, one's weight perception
(i.e., how much one believes they conform to or deviate from an
appropriate weight) may be particularly relevant to weight control be­
haviors. Indeed, the eating disorder literature has shown that weight
perception plays an important role in driving weight control behaviors
(Alcaraz-Ibáñez et al., 2021; Harring et al., 2010). Inaccurate percep­
tions of body weight, when individuals perceive themselves to be
overweight, underweight, or of ideal weight, can result in vastly
different outcomes. For example, studies have found that college stu­
dents who had weight perceptions higher than their actual weight were
more likely to engage in unhealthy weight control compared to those
with accurate weight perceptions (Harring et al., 2010; Wharton et al.,
2008). However, to our knowledge, no studies have focused on exam­
ining weight perceptions among nursing students in the U.S.
Method
Design
A cross-sectional online survey design was used to examine how
various psychosocial variables related to healthy and unhealthy weight
control among nursing students.
Procedures and participants
With approval from the University of South Alabama's institutional
review board, we recruited via email a randomly selected sample of 500
junior and senior nursing students enrolled at a university located in the
southeastern U.S. Data for the present study was collected as part of the
first wave of an ongoing longitudinal mixed-methods research project
examining nursing student health at the same institution. Although an
accurate response rate could not be determined since the number of
students who accessed the recruitment email is unknown, 56 % (N =
279) of students who were sent the survey link participated in the online
survey. To protect participant anonymity, participants were not asked to
provide identifying information as part of the online survey and, instead,
a unique ID was created for each participant. Following the survey,
participants were directed to a website (separate and unrelated to the
survey website) where they entered their email to receive study
292
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
compensation (a $10 gift card). The final sample included 241 nursing
students.
nutrition (5 items) and physical activity (5 items) scales were used.
Participants were asked to rate how certain they felt they could over­
come barriers related to eating healthy foods and carrying out exercise
intentions. Response options range from 1 (very uncertain) to 4 (very
certain). A composite score was generated from the physical activity and
nutrition scales. Scores ranged from 10 to 40, with higher scores indi­
cating a greater degree of health self-efficacy. Prior research has shown
good internal consistency with a Cronbach's α of 0.88 for exercise and
0.87 for nutrition (Schwarzer & Renner, 2009). For the current study,
Cronbach's alpha was 0.94 for the exercise subscale and 0.93 for the
nutrition subscale.
Measures
Healthy and unhealthy weight control
Healthy and unhealthy weight control behaviors were assessed using
instruments from the Project Eat-III Survey (Larson et al., 2011). The
healthy weight control measure consisted of 6 items which asked par­
ticipants to rate how often (1 = never to 4 = on a regular basis) within the
past year they engaged in six recommended weight management prac­
tices (i.e., exercising, eating more fruits and vegetables, eating less highfat foods). Scores ranged from 6 to 24 with higher scores indicating more
frequent practice of healthy weight control. The unhealthy weight
control measure consisted of 9 items. Participants indicated whether or
not they had engaged in unhealthy methods of losing weight or main­
taining their weight (i.e., using laxatives, using a food substitute, skip­
ping meals, etc.) within the past year. These responses were totaled to
create a score ranging from 0 to 9. In the current study, Cronbach's alpha
was 0.90 for healthy weight control and 0.71 for unhealthy weight
control.
Weight perception
Weight perception was measured using a single item from the Project
EAT III Survey (Larson et al., 2011). Participants were asked to indicate
how they viewed their weight status on a five-point scale ranging from 1
(very underweight) to 5 (very overweight).
Social support
The Multidimensional Scale of Perceived Social Support (MSPSS;
Zimet et al., 1988) consists of 12 items assessing perceived availability of
social support (including emotional and practical support). For the
purposes of the current study, two MSPSS subscales were used to assess
support from family (4 items) and friends (4 items), while the significant
other subscale was excluded. Participants rated the degree to which they
agreed with each statement on a scale from 1 (very strongly disagree) to 7
(very strongly agree). Scores ranged from 8 to 56. The average of ratings
was used to generate an overall score. Internal consistency for the
sample was excellent (Cronbach's α = 0.93).
Anxiety
Anxiety was assessed using the Generalized Anxiety Disorder-2 scale
(GAD-2; Kroenke et al., 2007), which consists of two items from the
GAD-7 scale (Spitzer et al., 2006). The items describe the following
anxiety symptoms: “feeling nervous, anxious, or on edge” and “not being
able to stop or control worrying.” For each item, participants rated how
frequently they had experienced the anxiety symptoms within the past
two weeks. Response options ranged from 0 (not at all) to 3 (nearly every
day). Ratings were summed to produce a total score, with higher scores
indicating higher severity anxiety, and a score of 3 or greater indicating
clinically significant anxiety symptoms. For the present study, Cron­
bach's alpha was 0.85.
Barriers to physical activity
This was assessed using a six-item measure from the Project Eat-III
Survey (Larson et al., 2011). Items assessed how often a series of bar­
riers (e.g., weather, time, concerns about fatigue or injury, embarrass­
ment related to appearance) interfered with physical activity. Response
options ranged from 1 (never) to 5 (very often) and scores ranged from 6
to 30, with higher scores indicating more frequent barriers to physical
activity. Cronbach's alpha for this measure was 0.72.
Depression
The Patient Health Questionnaire-2 (PHQ-2; Kroenke et al., 2003), a
two-item screening questionnaire, was used to assess depression in the
sample. Participants were asked how often in the previous two weeks
they had experienced the following: “little interest or pleasure in doing
things” and “feeling down, depressed, or hopeless.” Response options
ranged from 0 (not at all) to 3 (nearly every day). Scores were summed to
produce a depression severity score, which ranged from 0 to 6. A score of
3 or greater suggests clinically significant symptoms of depression. This
measure has been shown to have a sensitivity of 83 % and a specificity of
92 % for Major Depressive Disorder (Kroenke et al., 2003). In the present
study, Cronbach's alpha was 0.85.
Body satisfaction
Body satisfaction was assessed using a modified version of a survey
by Neumark-Sztainer et al. (2006), which was used in the Project Eat III
Survey (Larson et al., 2011) and based on the Body Shape Satisfaction
Scale (Pingitore et al., 1997). The modified survey assessed satisfaction
with the following body parts and features: weight, height, complexion,
face, stomach, breasts, buttocks, hips, upper thighs, general muscle tone,
and overall body size and shape. Items assessing satisfaction with body
build, shoulders, chest, and overall body fat were not included in our
study. Response options ranged from 1 (extremely dissatisfied) to 6
(extremely satisfied). Items were summed for a possible score between 11
and 66, with higher scores indicating more body satisfaction. Cronbach's
alpha was 0.90.
Health-specific hope
The Goal-Specific Hope Scale (Feldman et al., 2009) was modified to
assess hopefulness in the context of health goals. For example, an item
from the original measure reads, “My past experiences have prepared me
well for trying to attain this goal.” The modified version in our study
used the same statement, but instead of ending with “this goal,” the
statement referred to “my health goal.” In addition, a seventh item was
added, which asked participants to rate the degree to which the
following statement describes them, “I've been pretty successful in
meeting my health goals in the past.” Items were rated on a scale from 1
(definitely false) to 8 (definitely true) and ratings were summed to produce
a total score, with scores ranging from 7 to 56. Internal consistency for
the current study was excellent (Cronbach's α = 0.94).
Analysis plan
Structural equation modeling (SEM) was used to explore relation­
ships between the 8 psychosocial factors and healthy and unhealthy
weight control behaviors. SEM is broad family of statistical methods
used to measure and analyze the relationships of observed (i.e., actual
observations or scores on an instrument that contain measurement
error) and latent variables (i.e., a person's true scores without mea­
surement error). SEM provides the most rigorous test available of the
relationships between constructs because it removes measurement error
(Kline, 2016) that can otherwise significantly bias results (Cole &
Preacher, 2014).
Our analyses were conducted using Mplus Version 8 (Muthén et al.,
Health self-efficacy
The Health Self-Efficacy scales by Schwarzer and Renner (2009)
consist of 13 items that measure self-efficacy in the context of nutrition,
physical activity, and alcohol resistance. For the present study, only the
293
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
2017) and consisted of two steps based on recommended practice (Kline,
2016). First, a measurement model was tested to determine whether
latent variables were adequately represented by each of their respective
measured indicators. Second, a structural model was evaluated in which
regression paths were specified from each psychosocial factor to the two
dependent variables of healthy and unhealthy weight control, respec­
tively. Evaluating both the measurement and structural models allowed
us to identify differences between correlations at the measurement
model level (i.e., correlations without controlling for any of the other
psychosocial predictors) and regression paths at the multivariate level (i.
e., controlling for the contributions of the other psychosocial
predictors).
The following fit indices and corresponding thresholds (Kline, 2016)
were used to evaluate each model: the Root Mean Square Error of
Approximation (RMSEA) with 90 % confidence intervals [CI] (values of
0.06 or less indicate a good fit); the Comparative Fit Index (CFI) and the
Tucker Lewis Index (TLI) (values close to 0.95 indicate a good fit); and
the standardized root-mean-square residual (SRMR; values of 0.08 or
less indicate a good fit). The chi-square test statistic was also evaluated,
with a non-significant value indicating a perfect fit to the data (Kline,
2016). Full Information Maximum Likelihood (FIML) methodology was
used to address missing data, and a maximum likelihood estimator with
robust standard errors (MLR) was used to correct for the influence of
non-normality on indices of fit.
Table 1
Demographic characteristics of the nursing student sample (N = 241).
Gender
Female
Male
Other
Race/ethnicity
African American/Black
Native American
Asian American/Asian
Hispanic/Latino(a)
White non-Hispanic
Multiracial/Other
Academic level
Junior
Senior
No classification provided
Employment
Full time
Part time
Unemployed
Other
Body mass index
Underweight
Healthy weight
Overweight or obese
PHQ-2 score > 3
GAD-2 score > 3
Currently receiving mental health treatment
Results
Preliminary analyses
n
%
217
23
1
90.0
9.5
0.4
32
1
8
10
182
8
13.3
0.4
3.3
4.1
75.5
3.3
108
123
10
44.8
51.0
4.1
6
109
125
1
2.5
45.2
51.9
0.4
7
122
112
64
147
48
2.9
50.6
46.5
26.6
61.0
19.9
measuring the same constructs. Measures consisting of a single item
were retained as manifest variables. A measurement model Confirma­
tory Factor Analysis (CFA) had the resulting indices of fit (χ2 [255] =
343.89, p < .001; RMSEA = 0.038, [90 % CI = 0.027, 0.048]; CFI =
0.980; TLI = 0.975; SRMR = 0.042). Although the chi-square value was
significant, the CFI and TLI values were >0.95, and the RMSEA and
SRMR were within the recommended cutoffs for good fit to the data.
Thus, the measurement model suggested acceptable fit.
Additionally, the constructs in the model were adequately assessed,
as evidenced by large significant factor loadings for each of their
respective latent variables (ranging from 0.61 to 0.99 as shown in
Table 3). Bivariate correlations of all variables of interest with healthy
and unhealthy weight behaviors from the measurement model are dis­
played in Table 4. Anxiety, depression, weight perception, and barriers
to physical activity had moderate positive correlations with unhealthy
weight control. Body satisfaction had a moderate negative correlation
with unhealthy weight control. Weight perception, health self-efficacy,
and health-specific hope had moderate positive correlations with
healthy weight control.
Prior to conducting our analyses, data were screened for missing
values, univariate and multivariate outliers, and non-normality. In the
original sample of 279 participants, the unhealthy weight control and
healthy weight control measures had 20 % or more missing data for 9.3
% (n = 26) and 1.8 % (n = 5) of cases, respectively. As such, these
participants were removed from the sample. An additional 6 partici­
pants (2.2 %) were removed from the sample due to having extreme
values on one of the following measures: health-related hope (n = 2),
weight discrepancy (n = 3), and social support (n = 1). Since only three
multivariate outliers were identified based on the Mahalanobis distances
measure, no additional cases were removed from the sample, as rec­
ommended by Meyers et al. (2017). A small percentage of participants
were still missing values in the final sample of 241. A series of
Bonferroni-adjusted t-testes revealed that individuals missing some (i.e.,
<20 %) of responses on healthy weight and unwealthy weight control
items reported less health self-efficacy than individuals with complete
data on these dependent variables. Thus, data were likely missing at
random, indicating a need for FIML in our primary analysis (Schlomer
et al., 2010). Participants had a mean age of 23 years (SD = 5.29). The
sample was predominately female (90 %) and Caucasian (76 %), and
almost half (47 %) had a BMI in the overweight or obese range. Please
see Table 1 for a summary of sample characteristics.
Several study variables evidenced large positive or negative skew­
ness; however, the residuals from multivariate regressions screening
tests were normally distributed. Finally, multicollinearity diagnostics
indicated that there was not a linear dependency among factors (i.e.,
tolerance ranged from 0.57 to 0.82, and variance inflation ranged from
1.2 to 1.9). Means, standard deviations, and correlations between all
variables are shown in Table 2.
Structural model
After evaluating the measurement model, we assessed a structural
model of the combined effect of the eight selected psychosocial domains
in predicting healthy and unhealthy weight control behaviors (see Fig. 1
for a conceptual depiction of the structural model). Specifically, the
structural model was formed with predictive paths from each psycho­
social latent and manifest variable to the two healthy and unhealthy
weight control latent variables. The structural model evidenced
acceptable fit, χ2 (255) = 343.89, p < .001; CFI = 0.980; TLI = 0.975;
RMSEA = 0.038 [90 % CI = 0.027, 0.048]; SRMR = 0.042. However,
after controlling for each other, several of the significant bivariate as­
sociations from the measurement model became non-significant. Among
the positive psychosocial predictors, non-significant associations
included the paths from social support and body satisfaction to each
outcome variable and the path from health-self-efficacy to unhealthy
weight control. Among the negative psychosocial predictors, the paths
from depression and barriers to physical activity to each outcome
Measurement model
Following procedures described by Little et al. (2002), measures
comprised of six or more items were parceled to preserve statistical
power, with each latent variable consisting of three manifest parcels to
ensure model identification. This process allowed us to condense the
items from unidimensional measures into a smaller set of item parcels all
294
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
Table 2
Bivariate correlations, means, and SDs among the measured research variables.
1. Unhealthy weight control
2. Healthy weight control
3. GAD-2
4. PHQ-2
5. Health-specific hope
6. Health self-efficacy
7. Social support
8. Body satisfaction
9. Weight perception
10. Barriers to physical activity
1
2
3
4
5
6
7
8
1.00
0.33**
1.00
0.27**
− 0.01
1.00
0.27**
− 0.01
0.59**
1.00
− 0.14*
0.22**
− 0.22**
− 0.33**
1.00
− 0.07
0.33**
− 0.27**
− 0.28**
0.61**
1.00
− 0.14*
0.08
− 0.13*
− 0.31**
0.33**
0.26**
1.00
−
−
−
−
0.37**
0.01
0.31**
0.24**
0.41**
0.31**
0.20**
1.00
9
10
M
SD
0.35**
0.24**
0.01
0.06
− 0.28**
− 0.14*
0.03
− 0.43**
1.00
0.20**
− 0.14*
0.32**
0.31**
− 0.40**
− 0.51**
− 0.15*
− 0.39**
0.11
1.00
2.06
15.93
3.49
1.80
5.79
26.67
5.78
23.10
3.71
16.56
1.94
4.93
1.90
1.69
1.46
6.14
1.11
7.57
0.80
4.68
Note. N = 241. M = mean; SD = standard deviation.
*
p < .05.
**
p < .01.
Table 3
Factor loading of the measured indicators on the latent variables in the mea­
surement model.
Variable
Unhealthy weight
control
Parcel 1
Parcel 2
Parcel 3
Healthy weight
control
Parcel 1
Parcel 2
Parcel 3
Health-specific hope
Parcel 1
Parcel 2
Parcel 3
Health self-efficacy
Parcel 1
Parcel 2
Parcel 3
Social support
Parcel 1
Parcel 2
Parcel 3
Body satisfaction
Parcel 1
Parcel 2
Parcel 3
Barriers to physical
activity
Parcel 1
Parcel 2
Parcel 3
Depression
PHQ-2 Item 1
PHQ-2 Item 2
Anxiety
GAD-2 Item 1
GAD-2 Item 2
***
Unstandardized factor
loading
SE
Table 4
Correlations with weight control behaviors at the bivariate, measurement model
level.
Standardized factor
loading
1.00
1.18
0.96
–
0.19
0.12
0.73***
0.68***
0.61***
1.00
1.09
1.06
–
0.05
0.05
0.86***
0.87***
0.91***
1.00
1.13
1.11
–
0.05
0.06
0.90***
0.95***
0.90***
1.00
1.01
1.02
–
0.03
0.03
0.94***
0.96***
0.90***
1.00
1.07
1.01
–
0.03
0.03
0.99***
0.97***
0.94***
1.00
1.07
1.04
–
0.04
0.05
0.88***
0.95***
0.92***
1.00
1.22
0.89
–
0.21
0.07
0.79***
0.76***
0.65***
1.00
1.11
–
0.08
0.83***
0.90***
1.00
1.05
–
0.07
0.87***
0.85***
Variable
GAD-2
PHQ-2
Health-specific hope
Health self-efficacy
Social support
Body satisfaction
Weight perception
Barriers to physical
activity
Unhealthy weight control
behaviors
−
−
−
−
0.36***
0.34***
0.18*
0.08
0.18*
0.39***
0.41***
0.29**
Healthy weight control
behaviors
− 0.00
− 0.01
0.25***
0.37***
0.09
− 0.02
0.25***
− 0.15
Note. N = 241.
*
p < .05.
**
p < .01.
***
p < .001.
weight perception, and anxiety emerged as the most significant pre­
dictors in the model. In partial support of our first hypothesis, results
from the structural model revealed that health self-efficacy had a sig­
nificant positive association with healthy weight control (B = 0.38, SEB
= 0.12, β = 0.30, p = .001). By contrast, weight perception (B = 0.08,
SEB = 0.02, β = 0.42, p < .001) and anxiety (B = 0.06 SEB = 0.02, β =
0.34, p < .001) emerged as factors contributing to unhealthy weight
control. Consistent with hypothesis 2, weight perception and anxiety
were positively associated with unhealthy weight control. Unexpect­
edly, weight perception also had a statistically significant positive as­
sociation with healthy weight control (B = 0.32, SEB = 0.06, β = 0.34, p
< .001). Please see Table 5 for regression path coefficients for the final
model. The structural model explained 23 % of the variance in healthy
weight control and 29 % of the variance in unhealthy weight control.
Discussion
In the present study we examined a number of positive and negative
psychosocial factors in relation to weight control behaviors. We sought
to identify which of these factors would be most strongly related with
healthy versus unhealthy weight control. Based on prior research we had
expected (Hypothesis 1) strength-based or health-promoting factors
(including health-specific hope, health self-efficacy, social support, and
body satisfaction) to be positively associated with healthy weight con­
trol and negatively associated with unhealthy weight control. We also
predicted that (Hypothesis 2) depression, anxiety, barriers to physical
activity, and weight perception would be positively associated with
unhealthy weight control and negatively associated with healthy weight
control. Since this study was in part exploratory, no hypotheses were
advanced regarding which factors would be the most salient to healthy
versus unhealthy weight control.
p < .001.
variable, and the path from anxiety to healthy weight control were not
significant.
Given the large number of non-significant paths, we tested if a more
parsimonious model could be fit to the data by constraining nonsignificant paths to zero. The trimmed model produced good fit, χ2
(265) = 360.48, p < .001; CFI = 0.979; TLI = 0.974; RMSEA = 0.039
[90 % CI = 0.028, 0.048]; SRMR = 0.051. As a result, the more parsi­
monious model held, with a scaled chi-square indicating the trimmed
model was not significantly different from the unconstrained model, Δχ2
(10) = 16.66, p = .082.
The results of the trimmed model showed that health self-efficacy,
295
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
Health
Self-Efficacy
Health-Specific
Hope
Perceived Social
Support
Healthy Weight
Control
Weight Perception
Barriers to
Physical Activity
Unhealthy Weight
Control
Body Satisfaction
Anxiety
Depression
Fig. 1. Conceptual model interrelating eight psychosocial factors with healthy and unhealthy weight control. Bolded arrows represent paths that remained sig­
nificant after controlling for all other psychosocial variables. Dashed arrows represent the paths that became non-significant after controlling for the other psy­
chosocial variables.
significant positive correlations with unhealthy weight control. Still,
only barriers to physical activity had a negative (weak) correlation with
healthy weight control, and weight perception had an unexpectedly
positive correlation with healthy weight control in our measurement
model.
Although many psychosocial variables were associated with healthy
and unhealthy weight control in our measurement model (i.e., when we
did not control for the other predictors in the models), the multivariate
model allowed us to identify which of these variables were the most
salient for weight control behaviors. We found that three of the eight
psychosocial variables examined had the greatest influence on weight
control behavior in our structural model when controlling for the other
psychosocial predictors. Moreover, given that the trimmed (more
parsimonious) model was an equal fit to the data as the model with all
eight predictors included, our results indicate that anxiety, health selfefficacy, and weight perceptions accounted for all of the predictive
work of the other five psychosocial variables combined.
In the trimmed structural model, only weight perception emerged as
a predictor of both healthy and unhealthy weight control behaviors.
These results were consistent with prior research which has shown that
perceptions about one's weight status is an important factor influencing
weight management behaviors (Haynes et al., 2018; Lemon et al., 2009).
The majority of prior research has linked weight perception with un­
healthy weight control behaviors, such as disordered eating (AlcarazIbáñez et al., 2021; Kennedy et al., 2019). However, there is also
research that suggests that assessing one's weight status accurately can
help motivate the initiation of healthy weight control behaviors like
regular physical activity (Edwards et al., 2010). While we were unable to
Table 5
Unstandardized and standardized regression path coefficients from the struc­
tural model.
Variable
GAD-2➔
PHQ-2➔
Health specific
hope➔
Health selfefficacy➔
Social support➔
Body satisfaction➔
Weight
perception➔
Barriers to physical
activity➔
Unhealthy weight control
Healthy weight control
B
SEB
β
B
SEB
β
0.061
–
–
0.015
–
–
0.342***
–
–
–
–
–
–
–
–
–
–
–
–
–
–
0.379
0.116
0.304**
–
–
0.080
–
–
0.016
–
–
0.417***
–
–
0.319
–
–
0.063
–
–
0.341***
–
–
–
–
–
–
Note. N = 241.
**
p < .01.
***
p < .001.
The results of the present study partially supported these hypotheses.
At the bivariate level, there was greater support for the proposed hy­
potheses. For example, as predicted in hypothesis 1, health-specific
hope, health self-efficacy, social support, and body satisfaction were
all negatively correlated with unhealthy weight control. However, only
health self-efficacy and health-specific hope were positively correlated
with healthy weight control. As predicted in hypothesis 2, anxiety,
depression, weight perception and barriers to physical activity all had
296
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
evaluate how accurate the weight perceptions were in the current model
due to not weighing and measuring participants directly, our results do
provide some clues as to why weight perceptions may be important to
both unhealthy and healthy weight control among nursing students.
Consistent with research that has shown that weight perceptions
could lead to either healthy or unhealthy weight control behaviors, our
findings revealed that weight perceptions combined with anxiety may
lead to greater unhealthy weight control. Anxiety can be characterized
by worries about current or future stressors and negative evaluations of
one's ability to manage these stressors (Bandura, 1988). These negative
evaluations may translate to low self-efficacy and avoidance behaviors
in the context of healthy weight management practices (Bandura, 1988).
As such, nursing students experiencing anxiety may be less likely to
engage in healthy weight management practices, especially those they
perceive as time-consuming (Blake, Stanulewicz, & Mcgill, 2017) or
costly (Grant-Smith & de Zwaan, 2019). It is also possible that nursing
students who reported higher levels of anxiety may have more difficulty
managing their distress in the context of academic and training de­
mands, leaving fewer resources (i.e., time and energy) for them to
engage in healthy behaviors, such as preparing healthy meals or exer­
cising. Furthermore, there is some evidence that suggests some in­
dividuals use unhealthy eating as a way to self-regulate their negative
emotions, such as anxiety (Braden et al., 2018; Evers et al., 2018). As a
result of these barriers, nursing students may turn to unhealthy weight
control behaviors that may be perceived as easier in the short-term (e.g.,
diet pills, skipping meals, or diuretics; Levinson et al., 2020; Stanton
et al., 2021).
While unhealthy weight control was best predicted by a combination
of perceiving oneself as overweight and experiencing symptoms of
anxiety, similar weight perceptions were associated with healthy weight
control behaviors when combined with greater health self-efficacy.
Nursing students who reported a higher sense of self-efficacy may
have a positive evaluation of themselves and their ability to implement
healthy behavior change. Given that prior research has shown nursing
students face challenges in managing their health, these findings provide
useful insights regarding the most salient psychosocial facilitators and
barriers to healthy weight management among nursing students.
for future research by this team.
Implications
The findings of this study have important implications for in­
terventions aiming to improve the health and wellbeing of nursing
students. The results revealed that anxiety, above and beyond all other
psychosocial factors, played a significant role in unhealthy weight
control. Similarly, health self-efficacy was the most critical factor related
to healthy weight control. For these reasons, to improve the efficacy of
intervention efforts among nursing students, addressing anxiety, and
increasing self-efficacy should be prioritized.
This can be accomplished by going beyond teaching nursing students
about healthy eating and exercise habits. The need for health and
wellbeing programs that normalize self-care practices and use evidencebased strategies has been noted across nursing programs nationwide
(Melnyk et al., 2016; Melnyk et al., 2021). Cognitive behavioral in­
terventions are an ideal approach to help nursing students cope with
anxiety and stress more effectively, as they involve skill development in
relation to problem-solving; relaxation; and turning unhelpful or nega­
tive automatic thoughts into more adaptive ones (van der Riet et al.,
2018). The MINDSTRONG© program developed Melnyk et al. (2020) is
an example of a cognitive behavioral skills program designed for nursing
students that has been shown to reduce both depression and anxiety.
Furthermore, health self-efficacy can be enhanced by helping nursing
students develop the skills needed to: a) establish, plan for, and monitor
achievable health behavior goals and b) address or work around barriers
to managing their health (Pekmezi et al., 2009). Mc Sharry and Timmins
(2016) provide an example of an integrated intervention for nursing
students, which consists of the following: evidence-based information
about healthy habits and ways of promoting mental health; motivational
interviewing strategies; and hands-on fitness workshops. Integrative
approaches to weight management interventions, like those described
above, would be a more comprehensive way to promote the health and
wellbeing of our nursing students, who are indeed the future of nursing.
Conclusion
Limitations
The present study sought to explore the relationships between a
variety of psychosocial factors and healthy and unhealthy weight con­
trol behaviors among nursing students. The findings showed that while
weight perception was related to weight control behavior in general,
anxiety and health self-efficacy above all other factors were the most
important in differentiating students who engaged in healthy versus
unhealthy weight management strategies. Such findings suggest that to
support nursing students in managing their weight effectively, in­
terventions should incorporate anxiety management skills to reduce the
risk of unhealthy weight control, as well as enhance health self-efficacy
to increase healthy weight management strategies.
The present study had a few limitations. First, data from one wave of
a longitudinal study was used; thus, it was correlational and crosssectional in nature. Therefore, we are unable to determine the tempo­
ral order of variables or make conclusions about causality. In addition,
self-report measures were used for constructs that may be particularly
susceptible to recall and self-presentation bias. To address these limi­
tations, future research in this area should implement longitudinal and
experimental designs to better understand how psychosocial variables
such as anxiety affect weight control behaviors in this population over
time. Given that our model explained <30 % of the variance in our
outcomes, it is important to continue exploring other relevant variables
that may help explain weight control behavior.
There were also limitations related to specific measures. Weight
perceptions were assessed using only a single item in our study, which
likely did not fully capture the construct. Relatedly, social support and
health self-efficacy were assessed using only two of three subscales from
the measures selected. For this reason, it is important to note that future
studies may benefit from using more comprehensive measures for each
construct. Furthermore, participants for the study were recruited from a
single nursing program in the southern United States and the overall
sample lacked diversity with regard to race and gender. For these rea­
sons, the findings of this study may not generalize to U.S. nursing stu­
dents more broadly. Future studies would benefit from using broader
recruitment strategies to improve the representativeness of their
research samples. Finally, the accuracy of weight perception was not
validated by measuring the BMI of participants, which is a consideration
Funding acknowledgements
This work was completed with support of an internal grant from the
University of South Alabama.
Declaration of competing interest
None.
References
Alcaraz-Ibáñez, M., Paterna, A., Sicilia, Á., & Griffiths, M. D. (2021). A systematic review
and meta-analysis on the relationship between body dissatisfaction and morbid
exercise behaviour. International Journal of Environmental Research and Public Health,
18(2), 585. https://doi.org/10.3390/ijerph18020585
297
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
Allan, S., & Goss, K. (2014). Eating disorder beliefs and behaviours across eating disorder
diagnoses. Eating Behaviors, 15(1), 42–44. https://doi.org/10.1016/j.
eatbeh.2013.10.002
Allgöwer, A., Wardle, J., & Steptoe, A. (2001). Depressive symptoms, social support, and
personal health behaviors in young men and women. Health Psychology, 20(3),
223–227. https://doi.org/10.1037/0278-6133.20.3.223
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental
Disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
Bandura, A. (1988). Self-efficacy conception of anxiety. Anxiety Research, 1(2), 77–98.
https://doi.org/10.1080/10615808808248222
Bartlett, M. L., Taylor, H., & Nelson, J. D. (2016). Comparison of mental health
characteristics and stress between baccalaureate nursing students and non-nursing
students. The Journal of Nursing Education, 55(2), 87–90. https://doi.org/10.3928/
01484834-20160114-05
Berg, C., Ritschel, L. A., Swan, D. W., An, L. C., & Ahluwalia, J. S. (2011). The role of
hope in engaging in healthy behaviors among college students. American Journal of
Health Behavior, 35(4), Article 4. https://doi.org/10.5993/AJHB.35.4.3
Blake, H., Malik, S., Mo, P. K., & Pisano, C. (2011). ‘Do as I say, but not as I do’: Are next
generation nurses role models for health? Perspectives in Public Health, 131(5),
231–239.
Blake, H., Stanulewicz, N., & Griffiths, K. (2017). Healthy lifestyle behaviors and health
promotion attitudes in preregistered nurses: A questionnaire study. Journal of
Nursing Education, 56(2), 94–103. https://doi.org/10.3928/01484834-20170123-06
Blake, H., Stanulewicz, N., & Mcgill, F. (2017). Predictors of physical activity and
barriers to exercise in nursing and medical students. Journal of Advanced Nursing, 73
(4), 917–929. https://doi.org/10.1111/jan.13181
Braden, A., Musher-Eizenman, D., Watford, T., & Emley, E. (2018). Eating when
depressed, anxious, bored, or happy: Are emotional eating types associated with
unique psychological and physical health correlates? Appetite, 125, 410–417.
https://doi.org/10.1016/j.appet.2018.02.022
Bray, G. A. (2004). Medical consequences of obesity. The Journal of Clinical Endocrinology
& Metabolism, 89(6), 2583–2589. https://doi.org/10.1210/jc.2004-0535
Chan, J. C.-Y. (2014). Psychological determinants of exercise behavior of nursing
students. Contemporary Nurse, 49, 60–67.
Cheng, H. L., Medlow, S., & Steinbeck, K. (2016). The health consequences of obesity in
young adulthood. Current Obesity Reports, 5(1), 30–37. https://doi.org/10.1007/
s13679-016-0190-2
Chernomas, W. M., & Shapiro, C. (2013). Stress, depression, and anxiety among
undergraduate nursing students. International Journal of Nursing Education
Scholarship, 10(1), 255–266. https://doi.org/10.1515/ijnes-2012-0032
Cole, D. A., & Preacher, K. J. (2014). Manifest variable path analysis: Potentially serious
and misleading consequences due to uncorrected measurement error. Psychological
Methods, 19(2), 300–315. https://doi.org/10.1037/a0033805
Conn, V. S. (2010). Anxiety outcomes after physical activity interventions: Meta-analysis
findings. Nursing Research, 59(3), 224–231. https://doi.org/10.1097/
NNR.0b013e3181dbb2f8
Cowen, K. J., Hubbard, L. J., & Hancock, D. C. (2016). Concerns of nursing students
beginning clinical courses: A descriptive study. Nurse Education Today, 43, 64–68.
https://doi.org/10.1016/j.nedt.2016.05.001
Duty, S. M., Christian, L., Loftus, J., & Zappi, V. (2016). Is cognitive test-taking anxiety
associated with academic performance among nursing students? Nurse Educator, 41
(2), 70–74. https://doi.org/10.1097/NNE.0000000000000208
Edwards, N. M., Pettingell, S., & Borowsky, I. W. (2010). Where perception meets reality:
Self-perception of weight in overweight adolescents. Pediatrics, 125(3), e452–e458.
https://doi.org/10.1542/peds.2009-0185
Emmer, C., Bosnjak, M., & Mata, J. (2020). The association between weight stigma and
mental health: A meta-analysis. Obesity Reviews, 21(1). https://doi.org/10.1111/
obr.12935
Evers, C., Dingemans, A., Junghans, A. F., & Boevé, A. (2018). Feeling bad or feeling
good, does emotion affect your consumption of food? A meta-analysis of the
experimental evidence. Neuroscience & Biobehavioral Reviews, 92, 195–208. https://
doi.org/10.1016/j.neubiorev.2018.05.028
Feldman, D. B., Rand, K. L., & Kahle-Wrobleski, K. (2009). Hope and goal attainment:
Testing a basic prediction of Hope theory. Journal of Social and Clinical Psychology, 28
(4), 479–497. https://doi.org/10.1521/jscp.2009.28.4.479
Foreyt, J. P., & Goodrick, G. K. (1994). Impact of behavior therapy on weight loss.
American Journal of Health Promotion, 8(6), 466–468. https://doi.org/10.4278/08901171-8.6.466
Franz, M. J., VanWormer, J. J., Crain, A. L., Boucher, J. L., Histon, T., Caplan, W.,
Bowman, J. D., & Pronk, N. P. (2007). Weight-loss outcomes: A systematic review
and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up.
Journal of the American Dietetic Association, 107(10), 1755–1767. https://doi.org/
10.1016/j.jada.2007.07.017
Fronteira, I., & Ferrinho, P. (2011). Do nurses have a different physical health profile? A
systematic review of experimental and observational studies on nurses’ physical
health. Journal of Clinical Nursing, 20(17–18), 2404–2424. https://doi.org/10.1111/
j.1365-2702.2011.03721.x
Gariépy, G., Honkaniemi, H., & Quesnel-Vallée, A. (2016). Social support and protection
from depression: Systematic review of current findings in Western countries. The
British Journal of Psychiatry, 209(4), 284–293. https://doi.org/10.1192/bjp.
bp.115.169094
Gitimu, P. N., Jameson, M. M., Turel, T., Pohle-Krauza, R., Mincher, J., Rowlands, Z., &
Elias, J. (2016). Appearance issues, depression, and disordered eating among college
females. Cogent Psychology, 3(1), 1196512. https://doi.org/10.1080/
23311908.2016.1196512
Glowacki, K., Duncan, M. J., Gainforth, H., & Faulkner, G. (2017). Barriers and
facilitators to physical activity and exercise among adults with depression: A scoping
review. Mental Health and Physical Activity, 13, 108–119. https://doi.org/10.1016/j.
mhpa.2017.10.001
Gormley, N., & Melby, V. (2020). Nursing students’ attitudes towards obese people,
knowledge of obesity risk, and self-disclosure of own health behaviours: An
exploratory survey. Nurse Education Today, 84, Article 104232. https://doi.org/
10.1016/j.nedt.2019.104232
Graham, M. R., Tierney, S., Chisholm, A., & Fox, J. R. E. (2020). The lived experience of
working with people with eating disorders: A meta-ethnography. International
Journal of Eating Disorders, 53(3), 422–441. https://doi.org/10.1002/eat.23215
Grant-Smith, D., & de Zwaan, L. (2019). Don’t spend, eat less, save more: Responses to
the financial stress experienced by nursing students during unpaid clinical
placements. Nurse Education in Practice, 35, 1–6. https://doi.org/10.1016/j.
nepr.2018.12.005
Graves, R. J., Williams, S. G., Hauff, C., Fruh, S. M., Sims, B., Hudson, G. M.,
McDermott, R. C., Sittig, S., Shaw, T., Campbell, M., Barinas, J. L., & Hall, H. R.
(2020). Undergraduate versus graduate nursing students: Differences in nutrition,
physical activity, and self-reported body mass index. Journal of American College
Health. https://doi.org/10.1080/07448481.2020.1842421
Ham, M.-Y., & Lim, S.-H. (2017). Effects of obesity stress and health belief on weight
control behavior among nursing students. Journal of the Korea Academia-Industrial
Cooperation Society, 18(11), 459–468. https://doi.org/10.5762/
KAIS.2017.18.11.459
Harring, H. A., Montgomery, K., & Hardin, J. (2010). Perceptions of body weight, weight
management strategies, and depressive symptoms among U.S. College students.
Journal of American College Health, 59(1), 43–50. https://doi.org/10.1080/
07448481.2010.483705
Haynes, A., Kersbergen, I., Sutin, A., Daly, M., & Robinson, E. (2018). A systematic
review of the relationship between weight status perceptions and weight loss
attempts, strategies, behaviours and outcomes. Obesity Reviews, 19(3), 347–363.
https://doi.org/10.1111/obr.12634
Hazzard, V. M., Simone, M., Austin, S. B., Larson, N., & Neumark-Sztainer, D. (2021).
Diet pill and laxative use for weight control predicts first-time receipt of an eating
disorder diagnosis within the next 5 years among female adolescents and young
adults. International Journal of Eating Disorders, 1–6. https://doi.org/10.1002/
eat.23531
Jebeile, H., Lister, N. B., Baur, L. A., Garnett, S. P., & Paxton, S. J. (2021). Eating disorder
risk in adolescents with obesity. Obesity Reviews, 22(5), Article e13173. https://doi.
org/10.1111/obr.13173
Jeong, G.-S. (2020). The differences of self-efficacy, self-esteem and vitality according to
the physical exercise, thinking about health of nursing students. Journal of the Korea
Academia-Industrial Cooperation Society, 21(4), 117–125. https://doi.org/10.5762/
KAIS.2020.21.4.117
Johns, D. J., Hartmann-Boyce, J., Jebb, S. A., & Aveyard, P. (2014). Diet or exercise
interventions vs combined behavioral weight management programs: A systematic
review and meta-analysis of direct comparisons. Journal of the Academy of Nutrition
and Dietetics, 114(10), 1557–1568. https://doi.org/10.1016/j.jand.2014.07.005
Kennedy, A. K., Schneiderman, J. U., & Ramseyer Winter, V. (2019). Association of body
weight perception and unhealthy weight control behaviors in adolescence. Children
and Youth Services Review, 96, 250–254. https://doi.org/10.1016/j.
childyouth.2018.11.053
Kim, K. H. (2003). Baccalaureate nursing students' experiences of anxiety producing
situations in the clinical setting. Contemporary Nurse, 14(2), 145–155. https://doi.
org/10.5172/conu.14.2.145
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.).
Guilford publications.
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2003). The patient health Questionnaire2: Validity of a two-item depression screener. Medical Care, 41(11), 1284–1292.
https://doi.org/10.1097/01.MLR.0000093487.78664.3C
Kroenke, K., Spitzer, R., Williams, J., Monahan, P., & Löwe, B. (2007). Anxiety disorders
in primary care: Prevalence, impairment, comorbidity, and detection. Annals of
Internal Medicine, 146(5), 317–325.
Larson, N., Neumark-Sztainer, D., Story, M., van den Berg, P., & Hannan, P. J. (2011).
Identifying correlates of young adults' weight behavior: Survey development.
American Journal of Health Behavior, 35(6), 712–725.
Lee, E.-S., & Kim, B. (2020). A convergence study on effects of nutrition knowledge,
dietary habits, and dietary self-efficacy on dietary behavior in nursing students.
Journal of the Korea Convergence Society, 11(2), 341–350. https://doi.org/10.15207/
JKCS.2020.11.2.341
Lee, S. Y., Hwang, H., Hawkins, R., & Pingree, S. (2008). Interplay of negative emotion
and health self-efficacy on the use of health information and its outcomes.
Communication Research, 35(3), 358–381. https://doi.org/10.1177/
0093650208315962
Lehmann, F., Von Lindeman, K., Klewer, J., & Kugler, J. (2014). BMI, physical inactivity,
cigarette and alcohol consumption in female nursing students: A 5-year comparison.
BMC Medical Education, 14(1), Scopus. https://doi.org/10.1186/1472-6920-14-82
Lemon, S. C., Rosal, M. C., Zapka, J., Borg, A., & Andersen, V. (2009). Contributions of
weight perceptions to weight loss attempts: Differences by body mass index and
gender. Body Image, 6(2), 90–96. https://doi.org/10.1016/j.bodyim.2008.11.004
Lemstra, M., Bird, Y., Nwankwo, C., Rogers, M., & Moraros, J. (2016). Weight loss
intervention adherence and factors promoting adherence: A meta-analysis. Patient
Preference and Adherence, 10, 1547.
298
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
Pingitore, R., Spring, B., & Garfieldt, D. (1997). Gender differences in body satisfaction.
Obesity Research, 5(5), 402–409. https://doi.org/10.1002/j.1550-8528.1997.
tb00662.x
Pi-Sunyer, F. X. (2002). The obesity epidemic: Pathophysiology and consequences of
obesity. Obesity Research, 10(S12), 97S–104S. https://doi.org/10.1038/
oby.2002.202
Pollack, M. H. (2005). Comorbid anxiety and depression. The Journal of Clinical
Psychiatry, 66(Suppl. 8), 22–29.
Pulido-Martos, M., Augusto-Landa, J. M., & Lopez-Zafra, E. (2012). Sources of stress in
nursing students: A systematic review of quantitative studies. International Nursing
Review, 59(1), 15–25. https://doi.org/10.1111/j.1466-7657.2011.00939.x
Rajan, T., & Menon, V. (2017). Psychiatric disorders and obesity: A review of association
studies. Journal of Postgraduate Medicine, 63(3), 182. https://doi.org/10.4103/jpgm.
JPGM_712_16
Rand, K. L. (2018). Hope, self-efficacy, and optimism: Conceptual and empirical
differences. In M. W. Gallagher, & S. J. Lopez (Eds.), The Oxford handbook of hope
(pp. 45–58). Oxford University Press.
Rand, K. L., & Cheavens, J. S. (2009). Hope theory. In S. J. Lopez, & C. R. Snyder (Eds.),
Oxford handbook of positive psychology (2nd ed., pp. 323–333). Oxford University
Press.
Rasmussen, H. N., O’Byrne, K. K., Vandament, M., & Cole, B. P. (2018). Hope and
physical health. In M. W. Gallagher, & S. J. Lopez (Eds.), The Oxford handbook of hope
(pp. 159–168). Oxford University Press.
Reading, J. M., Buhr, K. J., & Stuckey, H. L. (2019). Social experiences of adults using
online support forums to lose weight: A qualitative content analysis. Health Education
& Behavior, 46(2_suppl), 129S–133S. https://doi.org/10.1177/1090198119859403
Rebar, A. L., Stanton, R., Geard, D., Short, C., Duncan, M. J., & Vandelanotte, C. (2015).
A meta-meta-analysis of the effect of physical activity on depression and anxiety in
non-clinical adult populations. Health Psychology Review, 9(3), 366–378.
Roach, J. B., Yadrick, M. K., Johnson, J. T., Boudreaux, L. J., Forsythe, W. A., & Billon, W.
(2003). Using self-efficacy to predict weight loss among young adults. Journal of the
American Dietetic Association, 103(10), 1357–1359. https://doi.org/10.1016/S00028223(03)01072-1
Rojo-Tirado, M. A., Benito, P. J., Ruiz, J. R., Ortega, F. B., Romero-Moraleda, B.,
Butragueño, J., Bermejo, L. M., Castro, E. A., & Gómez-Candela, C. (2021). Body
composition changes after a weight loss intervention: A 3-year follow-up study.
Nutrients, 13(1), 164. https://doi.org/10.3390/nu13010164
Ross, A., Bevans, M., Brooks, A. T., Gibbons, S., & Wallen, G. R. (2017). Nurses and
health-promoting behaviors: Knowledge may not translate into self-care. AORN
Journal, 105(3), 267–275. https://doi.org/10.1016/j.aorn.2016.12.018
Savitsky, B., Findling, Y., Ereli, A., & Hendel, T. (2020). Anxiety and coping strategies
among nursing students during the COVID-19 pandemic. Nurse Education in Practice,
46, Article 102809. https://doi.org/10.1016/j.nepr.2020.102809
Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data
management in counseling psychology. Journal of Counseling Psychology, 57(1), 1–10
(Supplemental) https://doi-org.libproxy.usouthal.edu/10.1037/a0018082.supp.
Schwarzer, R., & Renner, B. (2009). Health-Specific Self-Efficacy Scales. Freie Universität
Berlin. https://userpage.fu-berlin.de/~health/healself.pdf.
Schwarzer, R., & Warner, L. M. (2013). Perceived self-efficacy and its relationship to
resilience. In S. Prince-Embury, & D. Saklofske (Eds.), Resilience in children,
adolescents, and adults (pp. 139–150). Springer. https://doi.org/10.1007/978-14614-4939-3_10.
Snyder, C. R. (1994). The psychology of hope: You can get there from here. Free Press.
Snyder, C. R. (2000). Hypothesis: There is hope. In C. R. Snyder (Ed.), Handbook of hope:
Theory, measures, and applications (pp. 3–21). Academic Press. https://doi.org/
10.1016/B978-012654050-5/50003-8.
Snyder, C. R., Harris, C., Anderson, J. R., Holleran, S. A., Irving, L. M., Sigmon, S. T.,
Yoshinobu, L., Gibb, J., Langelle, C., & Harney, P. (1991). The will and the ways:
Development and validation of an individual-differences measure of hope. Journal of
Personality and Social Psychology, 60(4), 570–585. https://doi.org/10.1037/00223514.60.4.570
Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for
assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166
(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092
Stanton, R., Best, T., Williams, S., Vandelanotte, C., Irwin, C., Heidke, P., Saito, A.,
Rebar, A. L., Dwyer, T., & Khalesi, S. (2021). Associations between health behaviors
and mental health in australian nursing students. Nurse Education in Practice, 53,
Article 103084. https://doi.org/10.1016/j.nepr.2021.103084
Suherman, H., Peninoy, D., Vingco, A., & Rey, K. A. M. (2018). Social support affecting
personal health practices among nursing students. Journal of Health Sciences, 1(2),
34–43.
Thome, J., & Espelage, D. L. (2004). Relations among exercise, coping, disordered eating,
and psychological health among college students. Eating Behaviors, 5(4), 337–351.
https://doi.org/10.1016/j.eatbeh.2004.04.002
Tiggemann, M., & McCourt, A. (2013). Body appreciation in adult women: Relationships
with age and body satisfaction. Body Image, 10(4), 624–627. https://doi.org/
10.1016/j.bodyim.2013.07.003
Tung, Y.-J., Lo, K. K. H., Ho, R. C. M., & Tam, W. S. W. (2018). Prevalence of depression
among nursing students: A systematic review and meta-analysis. Nurse Education
Today, 63, 119–129. https://doi.org/10.1016/j.nedt.2018.01.009
Tylka, T. L. (2011). Positive psychology perspectives on body image. In Body image: A
handbook of science, practice, and prevention. Guilford Press.
Tylka, T. L., & Wood-Barcalow, N. L. (2015a). The body appreciation Scale-2: Item
refinement and psychometric evaluation. Body Image, 12, 53–67. https://doi.org/
10.1016/j.bodyim.2014.09.006
Levinson, J. A., Sarda, V., Sonneville, K., Calzo, J. P., Ambwani, S., & Austin, S. B. (2020).
Diet pill and laxative use for weight control and subsequent incident eating disorder
in US young women: 2001–2016. American Journal of Public Health, 110(1),
109–111. https://doi.org/10.2105/AJPH.2019.305390
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to
parcel: Exploring the question, weighing the merits. Structural Equation Modeling: A
Multidisciplinary Journal, 9(2), 151–173. https://doi.org/10.1207/
S15328007SEM0902_1
Lyzwinski, L. N., Caffery, L., Bambling, M., & Edirippulige, S. (2018). The relationship
between stress and maladaptive weight-related behaviors in college students: A
review of the literature. American Journal of Health Education, 49(3), 166–178.
https://doi.org/10.1080/19325037.2018.1449683
Mata, J., & Hertwig, R. (2018). Public beliefs about obesity relative to other major health
risks: Representative cross-sectional surveys in the USA, the UK, and Germany.
Annals of Behavioral Medicine, 52(4), 273–286. https://doi.org/10.1093/abm/
kax003
Mc Sharry, P., & Timmins, F. (2016). An evaluation of the effectiveness of a dedicated
health and well being course on nursing students' health. Nurse Education Today, 44,
26–32. https://doi.org/10.1016/j.nedt.2016.05.004. Scopus.
McDermott, R. C., Fruh, S. M., Williams, S., Hauff, C., Graves, R. J., Melnyk, B. M., &
Hall, H. R. (2020). Nursing students' resilience, depression, well-being, and academic
distress: Testing a moderated mediation model. Journal of Advanced Nursing, 76(12),
3385–3397. https://doi.org/10.1111/jan.14531
McDermott, R. C., Fruh, S. M., Williams, S., Hauff, C., Sittig, S., Wright, T., Riley, B.,
Swanzy, D., Graves, R. J., & Hall, H. (2021). Characteristics of negative and positive
mental health among nursing students in the United States. Journal of the American
Psychiatric Nurses Association, 27(1), 44–53. https://doi.org/10.1177/
1078390319865322
McGill, B., O’Hara, B. J., Phongsavan, P., Bauman, A., Lawler, L., & Grunseit, A. C.
(2020). “I’m still on track”: A qualitative exploration of participant experiences of a
weight loss maintenance program. Healthcare, 8(1), 21. https://doi.org/10.3390/
healthcare8010021
Melnyk, B. M., Hoying, J., & Tan, A. (2020). Effects of the MINDSTRONG© CBT-based
program on depression, anxiety and healthy lifestyle behaviors in graduate health
sciences students. Journal of American College Health, 1–9. https://doi.org/10.1080/
07448481.2020.1782922
Melnyk, B. M., Hsieh, A. P., Tan, A., Gawlik, K., Hacker, E. D., Ferrell, D.Badzek, L., …
(2021). The state of mental health and healthy lifestyle behaviors in nursing,
medicine and health sciences faculty and students at big 10 universities with
implications for action. Journal of Professional Nursing, 27(6), 1167–1174. https://
doi.org/10.1016/j.profnurs.2021.10.007
Melnyk, B. M., Slevin, C., Militello, L., Hoying, J., Teall, A., & McGovern, C. (2016).
Physical health, lifestyle beliefs and behaviors, and mental health of entering
graduate health professional students: Evidence to support screening and early
intervention. Journal of the American Association of Nurse Practitioners, 28(4),
204–211. https://doi.org/10.1002/2327-6924.12350
Meyers, L. S., Gamst, G., & Guarino, A. J. (2017). Applied multivariate research: Design and
interpretation (3rd ed.). SAGE.
Miller, S. K., Alpert, P. T., & Cross, C. L. (2008). Overweight and obesity in nurses,
advanced practice nurses, and nurse educators. Journal of the American Academy of
Nurse Practitioners, 20(5), 259–265. https://doi.org/10.1111/j.17457599.2008.00319.x
Mills, A., Ryden, J., & Knight, A. (2020). Juggling to find balance: Hearing the voices of
undergraduate student nurses. British Journal of Nursing, 29(15), 897–903. https://
doi.org/10.12968/bjon.2020.29.15.897
Muthén, B. O., Muthén, L. K., & Asparouhov, T. (2017). Regression and mediation analysis
using. MPlusMuthén & Muthén.
Nagata, J. M., Garber, A. K., Tabler, J. L., Murray, S. B., & Bibbins-Domingo, K. (2018).
Differential risk factors for unhealthy weight control behaviors by sex and weight
status among U.S. Adolescents. Journal of Adolescent Health, 63(3), 335–341. https://
doi.org/10.1016/j.jadohealth.2018.03.022
Neumark-Sztainer, D., Paxton, S. J., Hannan, P. J., Haines, J., & Story, M. (2006). Does
body satisfaction matter? Five-year longitudinal associations between body
satisfaction and health behaviors in adolescent females and males. Journal of
Adolescent Health, 39(2), 244–251. https://doi.org/10.1016/j.
jadohealth.2005.12.001
Ostendorf, D. M., Lyden, K., Pan, Z., Wyatt, H. R., Hill, J. O., Melanson, E. L., &
Catenacci, V. A. (2018). Objectively measured physical activity and sedentary
behavior in successful weight loss maintainers: Physical activity in weight loss
maintainers. Obesity, 26(1), 53–60. https://doi.org/10.1002/oby.22052
O’Sullivan, G. (2011). The relationship between hope, eustress, self-efficacy, and life
satisfaction among undergraduates. Social Indicators Research, 101(1), 155–172.
https://doi.org/10.1007/s11205-010-9662-z
Pascoe, M., Bailey, A. P., Craike, M., Carter, T., Patten, R., Stepto, N., & Parker, A.
(2020). Physical activity and exercise in youth mental health promotion: A scoping
review. BMJ Open Sport & Exercise Medicine, 6(1), Article e000677. https://doi.org/
10.1136/bmjsem-2019-000677
Pekmezi, D., Jennings, E., & Marcus, B. H. (2009). Evaluating and enhancing self-efficacy
for physical activity. ACSMs Health & Fitness Journal, 13(2), 16–21. https://doi.org/
10.1249/FIT.0b013e3181996571
Phiri, L. P., Draper, C. E., Lambert, E. V., & Kolbe-Alexander, T. L. (2014). Nurses’
lifestyle behaviours, health priorities and barriers to living a healthy lifestyle: A
qualitative descriptive study. BMC Nursing, 13(1), 1–11. https://doi.org/10.1186/
s12912-014-0038-6
299
J.L. Barinas et al.
Journal of Professional Nursing 42 (2022) 290–300
Williams, S. G., McDermott, R., Fruh, S., Graves, R., Hall, H., Wright, T., Swanzy, D., &
Carter, C. (2018). Nursing student satisfaction with daily life: A holistic approach.
Journal of Nursing Education, 57(12), 751–755. https://doi.org/10.3928/0148483420181119-09
Wood-Barcalow, N. L., Tylka, T. L., & Augustus-Horvath, C. L. (2010). “But I like my
body”: Positive body image characteristics and a holistic model for young-adult
women. Body Image, 7(2), 106–116. https://doi.org/10.1016/j.bodyim.2010.01.001
Younas, A. (2017). Self-care behaviors and practices of nursing students: Review of
literature. Journal of Health Sciences, 7(3), 137–145. https://doi.org/10.17532/
jhsci.2017.420
Zapka, J. M., Lemon, S. C., Magner, R. P., & Hale, J. (2009). Lifestyle behaviours and
weight among hospital-based nurses. Journal of Nursing Management, 17(7),
853–860. https://doi.org/10.1111/j.1365-2834.2008.00923.x
Zhang, Y., Zhang, B., Gan, L., Ke, L., Fu, Y., Di, Q., & Ma, X. (2021). Effects of online
bodyweight high-intensity interval training intervention and health education on the
mental health and cognition of sedentary young females. International Journal of
Environmental Research and Public Health, 18(1), 302. https://doi.org/10.3390/
ijerph18010302
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional
scale of perceived social support. Journal of Personality Assessment, 52(1), 30–41.
https://doi.org/10.1207/s15327752jpa5201_2
Tylka, T. L., & Wood-Barcalow, N. L. (2015b). What is and what is not positive body
image? Conceptual foundations and construct definition. Body Image, 14, 118–129.
https://doi.org/10.1016/j.bodyim.2015.04.001
van der Riet, P., Levett-Jones, T., & Aquino-Russell, C. (2018). The effectiveness of
mindfulness meditation for nurses and nursing students: An integrated literature
review. Nurse Education Today, 65, 201–211. https://doi.org/10.1016/j.
nedt.2018.03.018
Verheijden, M. W., Bakx, J. C., van Weel, C., Koelen, M. A., & van Staveren, W. A. (2005).
Role of social support in lifestyle-focused weight management interventions.
European Journal of Clinical Nutrition, 59, S179–S186. https://doi.org/10.1038/sj.
ejcn.1602194
Villeneuve, P., Heale, R., Rietze, L., & Carter, L. (2018). Exploring self-perceptions of
anxiety among nursing students in the clinical setting and select demographics.
International Journal of Nursing Education Scholarship, 15(1). https://doi.org/
10.1515/ijnes-2017-0042
Wadden, T. A., Tronieri, J. S., & Butryn, M. L. (2020). Lifestyle modification approaches
for the treatment of obesity in adults. American Psychologist, 75(2), 235–251. https://
doi.org/10.1037/amp0000517
Wang, A. H., Lee, C. T., & Espin, S. (2019). Undergraduate nursing students' experiences
of anxiety-producing situations in clinical practicums: A descriptive survey study.
Nurse Education Today, 76, 103–108. https://doi.org/10.1016/j.nedt.2019.01.016
Wharton, C. M., Adams, T., & Hampl, J. S. (2008). Weight loss practices and body weight
perceptions among US college students. Journal of American College Health, 56(5),
579–584. https://doi.org/10.3200/JACH.56.5.579-584
300