See - Paper Answers

Critiquing Literature Reviews

This week we are discussing literature reviews and how to critique them. Within our article
below, locate the literature review. A good study will discuss how relevant literature was found
and analyzed and the data presented within the literature. This is usually done in quantitative
studies prior to the start of a study.

Interestingly, in qualitative studies, a literature review is done AFTER data collection and is used
to support findings of the study. We will learn more about this in future chapters.

Stephens J. D, Yager, A. M, & Allen J. (2017). Smartphone technology and text messaging for
weight loss in young adults (Links to an external site.): A randomized controlled trial. Journal of
Cardiovascular Nursing, 32(1), 39–46. https://doi.org/10.1097/JCN.0000000000000307 (Links
to an external site.)

1. Does the review seem thorough and up-to-date? Did it include major studies on the topic?
Did it include recent research?

2. Did the review rely mainly on research reports, using primary sources?

3. Did the review critically appraise and compare key studies? Did it identify important gaps in
the literature?

4. Was the review well organized? Is the development of ideas clear?

5. Did the review use appropriate language, suggesting the tentativeness of prior findings? Is
the review objective?

6. If the review was in the introduction for a new study, did the review support the need for the
study?

7. If the review was designed to summarize evidence for clinical practice, did it draw appropriate
conclusions about practice implications?

ORIGINAL POSTS ARE DUE

[ARTICLES: Obesity in Children and Young Adults]

The Journal of Cardiovascular Nursing
Issue: Volume 32(1), January/February 2017, p 39-46
Copyright: Copyright (C) 2017 Wolters Kluwer Health, Inc. All rights reserved
Publication Type: [ARTICLES: Obesity in Children and Young Adults]
DOI: 10.1097/JCN.0000000000000307
ISSN: 0889-4655
Accession: 00005082-201701000-00007
Keywords: self-efficacy, text messaging, weight loss, young adult

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Smartphone Technology and Text Messaging for Weight Loss in Young
Adults: A Randomized Controlled Trial
Stephens, Janna D. PhD, RN; Yager, Allison M. BS; Allen, Jerilyn RN, ScD, FAAN

Author Information
Janna D. Stephens, PhD, RN Assistant Professor, College of Nursing, Ohio State University, Columbus
Allison M. Yager, BS BSN Student, School of Nursing, Johns Hopkins University, Baltimore, Maryland.
Jerilyn Allen, RN, ScD, FAAN Professor, School of Nursing, Johns Hopkins University, Baltimore, Maryland.
Research in this publication was supported by the National Institute of Nursing Research of the National
Institute of Health under award numbers 1T32NR012704 (Cardiovascular Research Training Grant) and
F31NR013811 (National Research Service Award). The content is solely the responsibility of the authors and
does not necessarily represent the official views of the National Institutes of Health.
The authors have no conflicts of interest to disclose.
Correspondence Janna D. Stephens, PhD, RN, 5910 Kyles Station Rd, Hamilton OH 45011 (
Jsteph22@jhu.edu
).

Abstract

Background: Using smartphone technology and text messaging for health is a growing field. This type of
technology is well integrated into the lives of young adults. However, few studies have tested the effect of
this type of technology to promote weight loss in young adults

Objective: The purpose of this study is to test the effectiveness of a behaviorally based smartphone
application for weight loss combined with text messaging from a health coach on weight, body mass index
(BMI), and waist circumference in young adults as compared with a control condition.

Methods

: Sixty-two young adults, aged 18 to 25 years, were randomized to receive (1) a smartphone
application + health coach intervention and counseling sessions or (2) control condition with a counseling
session. All outcome measures were tested at baseline and 3 months. These included weight, BMI, waist
circumference, dietary habits, physical activity habits, and self-efficacy for healthy eating and physical
activity.

Results: The sample was 71% female and 39% white, with an average age of 20 years and average BMI of

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mailto:Jsteph22@jhu.edu

28.5 kg/m2. Participants in the smartphone + health coach group lost significantly more weight (P = .026)
and had a significant reduction in both BMI (P = .024) and waist circumference (P < .01) compared with controls.

Conclusion

s: The results of this weight loss trial support the use of smartphone technology and feedback
from a health coach on improving weight in a group of diverse young adults.

Overweight and obesity are major public health concerns in the United States. According to data published in
2014 by the National Health and Nutrition Examination Survey, more than one-half of US adults (60.3%) aged
20 to 39 years are overweight or obese with a body mass index (BMI) of 25 kg/m2 or greater.1 Weight gain is
specifically a concern in college-aged individuals. Although the common theory that college freshman gain 15
lb has been disproven on most accounts,2 studies have shown that many students do in fact gain weight.3,4 A
survey conducted in 2014 by the American College Health Association reported that more than 34% of
undergraduate students are overweight or obese, and this number increases to 40% when surveying graduate
students.5 Being overweight greatly increases one’s risk for stroke, heart disease, type 2 diabetes, and some
forms of cancer.6 Therefore, interventions to combat weight gain during these years are needed for healthy
outcomes later in life.

The behaviors of college-aged individuals put them at risk for weight gain. Specifically, poor eating habits,
decreased physical activity, decreased fruit and vegetable consumption, and increased alcohol consumption all
contribute to weight gain.7,8 The American College Health Association reports that 65% of students consume
less than 2 servings of fruit/vegetables combined per day and that more than 50% of students report
consuming alcohol in the past 9 days.5 Of those consuming alcohol, 24% of students reported having 7 or
more drinks the last time they drank.5

Technology is well integrated into the lives of young adults. Currently, 85% of young adults, aged 18 to 29
years, own a smartphone. Among those young adults owning a smartphone, 100% use their smartphone to
send and receive text messages.9 In addition, 77% of young adults have used their smartphone to look up
health information.9 A recent focus group study conducted by the first author identified that young adults are
interested in using smartphone technology for weight loss; however, they know very little about the availability
of different applications to assist with weight loss.10

Interventions for weight loss in this population have proven to be successful using various strategies. One
study used technology and showed greater weight loss in a group that received a social networking site and
text messages (-2.4 kg) compared with a social networking site alone (-0.63 kg).11 Another study using the
Internet reported increased fruit and vegetable consumption, although no differences in weight were noted.12

Smartphone technology can provide many tools to help one lose weight. However, there is limited knowledge
on the use of smartphone technology for weight loss in young adults. Therefore, the purpose of this study is to
test the effectiveness of a behaviorally based smartphone application combined with text messaging from a
health coach on weight, BMI, and waist circumference in young adults as compared with a control condition.

Methods

The Young Adult Weight Loss Study was a randomized, controlled trial in which participants were randomly
assigned to intervention or control. Assessments were completed at baseline and 3 months between 2014 and
2015. All participants provided informed written consent at baseline. The protocol was approved by the Johns
Hopkins University Institutional Review Board. Study data were collected via paper/pencil questionnaires and a
Web-based program for dietary recall. The Research Electronic Data Capture (REDCap), a secure, Web-based
application, was used to store data.

Setting and Participants
Participants were recruited in and around the Johns Hopkins University campuses using many strategies
including posters/flyers, Facebook, e-mail announcements, and word of mouth. Individuals between 18 and 25
years of age with a BMI between 25 and 40 kg/m2 who owned an iPhone or Android phone were eligible to
participate. Participants were not required to be a college undergraduate or graduate student. Interested
individuals contacted the primary investigator to set up a telephone screening; if the individual qualified, they
were asked to set up a baseline visit. Participants were excluded if they were currently participating in another
structured weight loss program, were taking weight loss medications, were diagnosed with type I diabetes, or
were currently pregnant or planning to become pregnant in the next 3 months. Individuals were also excluded if
they currently exercised more than 150 min/wk at moderate intensity or have had symptoms of disordered
eating in the previous 6 months. Symptoms of disordered eating were defined as answering yes to any
question assessing binging/purging, laxative/diet pill use, and treatment for an eating disorder from the Eating
Attitudes Test-26 (EAT-26) questionnaire.13 Randomization to smartphone + health coach or control by blocks
of 4 occurred after data were collected at the baseline visit. All participants received a $25 gift card for
participation.

Outcome Measures
Data on the outcome measures were collected on all participants at baseline and 3 months. Body weight was
measured using the Tanita BS-549 scale with the participant in light clothing. Height was measured using a
wall stick measurement. Body mass index was then calculated using weight in kilograms/height in meters
squared. Waist circumference was measured twice and then averaged according to the obesity guidelines.14

Physical activity was evaluated with the Godin Leisure-Time Exercise Questionnaire. The survey is self-
administered and assesses strenuous, moderate, and mild activity over a 7-day period.15 This survey method
has been proven to be both valid and reliable in adults, with test-retest scores ranging from 0.74 to 0.81.16
Nutrition data were collected using the National Cancer Institute’s Automated Self-Administered 24-hour Recall
(ASA-24). The ASA-24 is a Web-based, ASA 24-hour recall of foods and was filled out on the participant’s
computer. The ASA-24 provides analysis on calories, nutrients, and food group estimates.17 It has been
proven to be valid in an adult population, with the ASA-24 performing very close (87% matching) to
standardized interviewer-administered 24-hour food recalls.17 Information obtained from the ASA-24 included
caloric intake, food pyramid equivalents, and nutrients from all foods reported according to the Food and
Nutrient Database for Dietary Studies.17

Self-efficacy for healthy eating and exercise were evaluated with 2 questionnaires. Both of the self-efficacy
scales were self-administered by the participant. The Self-Efficacy for Healthy Eating is a 13-item questionnaire
that explores a person’s belief in their ability to make better food choices in given situations. A reliability
coefficient of 0.87 indicated high internal consistency on the scale tested in a group of adults, ages 19 to 64
years.18 Self-efficacy for physical activity was assessed using a 14-item questionnaire called the Self-Efficacy
for Exercise Scale. This questionnaire assesses individuals’ belief in their ability to exercise in given situations.
This scale was determined to be reliable and valid in a population of adults, with an internal consistency of 0.90
and a test-retest correlation of 0.67.19

Interventions
The behavioral intervention was based on self-efficacy theory, a construct of social cognitive theory, which was
used in our previous pilot study that focused on smartphone applications for weight loss in adults.20 The self-
efficacy theory states that there are 4 ways to increase one’s self-efficacy: mastery experience, social
modeling, social support, and verbal persuasion.21 These 4 mechanisms were built into the intervention, which
focused on increasing the participant’s self-efficacy to achieve better health outcomes related to weight loss.
The goals for both groups were to lose 1 to 2 lb per week and increase participation in physical activity.
Participants were encouraged to exercise at least 150 minutes per week at moderate intensity, which would
meet the Physical Activity Guidelines for Americans.22 Both groups received a 1-time counseling session
before randomization. This was a 20-minute session that discussed healthy eating, limiting alcohol and sugar-
sweetened beverages, and increasing physical activity. After this session, participants were randomized to 1 of
2 groups, control or smartphone + health coach (intervention) for the 3-month study period.

Smartphone + Health Coach Group

Participants in this group were given an additional 30- to-40-minute counseling session on energy balance,
nutrient density of foods, sugar-sweetened beverage consumption, and physical activity; therefore, they had 2
sessions total during their baseline visit. Participants were encouraged to identify specific goals that their
health coach could help them achieve.

Participants were also guided to download and use the Lose it! application. This application is a free,
commercially available smartphone application that is focused on nutrition and physical activity self-
monitoring. Participants were encouraged to log all food and exercise into the daily log in the application. They
were instructed to follow the caloric budget set by the application using the Mifflin equation. The application
also offered social networking through a “friend” feature, which allowed individuals to view peer weight loss
and physical activity participation and also allowed the interaction between peers. Participants were
encouraged to use this feature.

Individualized text messages were delivered to the participant’s smartphone from a health coach. The
participants were asked to not text their health coach back. Based on data from a focus group study
conducted by the first author, the participants could choose any frequency of messages they wanted to receive
from a health coach, anywhere from 1 time per week up to 3 times per day.9 The smartphone application
provided the health coach with the ability to monitor and track all participant progress on a real-time basis and
text messages focused on current diet or physical activity status (see Table 1). Texts were sent from the health
coach’s cell phone at the specified time and frequency of the participant.

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TABLE 1 Example Text Messages

Control Group

The control group was asked to not use any smartphone applications focused on weight loss for the duration
of the study. They received the Lose It! application with a training session at their 3-month visit.

Statistical Analysis

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The study was powered to detect statistically significant differences in weight loss between the 2 groups.
Using an effect size of 0.8, calculated from a similar study,10 an [alpha] of 0.05, and a power of 80%, the
sample size was determined to be 51. The sample size was increased by 15% to allow for attrition, to give a
total sample size of 60, or 30 per group. Group differences in baseline sociodemographic and anthropometric
characteristics were examined using Wilcoxon rank-sum tests and [chi]2 or Fisher exact tests. The primary
outcomes were changes from baseline to 3 months in weight in kilograms, BMI, and waist circumference in
centimeters. Secondary outcomes were changes in diet, physical activity, and self-efficacy for diet and physical
activity. A completers analysis was performed using generalized linear models, which were used to test for
group differences, time effects, and interactions between group*time. All statistical analyses were done using
Statistical Analysis System (SAS).

Results
Baseline Characteristics
Baseline characteristics of participants by group are shown in Table 2. Of the 62 participants enrolled, 71%
were female, 33.8% were Asian, and 12.9% were African American. The overall median age was 20.0 (18.0-
25.0) years and median BMI was 28.5 (25.0-40.4) kg/m2. Although the sample included both non-college and
college students, only 10% of study participants were not current undergraduate or graduate students. There
were no significant differences in baseline characteristics between the 2 groups.

TABLE 2 Baseline Sample Characteristics by Treatment Group

Recruitment and Retention
The Figure is the CONSORT diagram reporting the participant flow through the study. We assessed 87
individuals for eligibility.

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FIGURE. Study flow diagram.

A total of 66 individuals met the criteria to participate. Of those, 4 (6%) declined to participate. The primary
reason for refusal was lack of interest in participating in a study for 3 months. A total of 62 individuals were
randomized to 1 of the 2 groups, which represented 71% of those who originally expressed interest in
participating.

Fifty-nine (95%) returned at 3 months for follow-up measurements. Retention rates were similar in the 2
groups, 97% in the control group and 94% in the intervention group.

Weight, Body Mass Index, and Wait Circumference

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Changes from baseline to 3 months can be found in Table 3. The control group gained a slight amount of
weight (0.3 kg) from baseline to 3 months, whereas participants in the smartphone + health coach group lost a
significant amount (-1.8 kg, P < .01); the difference in weight change between groups was statistically significant (P = .026). The smartphone group also had a significant decrease in BMI (P < .01) and waist circumference (P < .01). The differences in BMI and waist circumference changes between groups were also statistically significant (P = .024 for BMI, P < .01 for waist circumference). Seven (24%) participants in the smartphone group who completed the study lost enough weight to change their weight status; 5 (17%) moved into the normal weight category and 2 (7%) went from the obese category to overweight.

TABLE 3 Preintervention and Postintervention Measurements of Body Size and Self-reported Behaviors

Self-reported Behaviors
Changes in self-reported behaviors can also be found in Table 3. The smartphone + health coach group
improved significantly in healthy eating self-efficacy (P = .032). They also improved in overall physical activity
performed (P < .01); however, the differences were not significant when compared with the control group. Although both groups showed improvement in self-efficacy for physical activity, neither change was statistically significant. A comparison of degree of change between groups was also performed (group x time interaction with all subjects) adjusting for self-efficacy for healthy eating and exercise. When adjusting for self-efficacy for healthy eating, the data show that it is a slight mediator for change in weight with a P value shifting from P =
.026 for nonadjusted to P = .052 when adjusted. Tests were also run for BMI and waist circumference, but
there was no shift in P value, suggesting that self-efficacy for healthy eating does not entirely account for the
treatment group effect.

A total of 37 (63%) participants completed the diet questionnaire at follow-up, 22 (73%) control and 15 (52%)
smartphone + health coach. Table 4 displays the results from the ASA-24. The smartphone group consumed
significantly more fiber than the control group did at follow-up (P = .049). There were no additional significant
differences between the 2 groups at follow-up. However, participants in the smartphone group consumed
slightly more protein, more vegetables, more fruit, fewer total carbohydrates, and fewer added sugars than did
participants in the control arm.

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TABLE 4 Diet Quality of Study Participants During Follow-Up

Application Use and Text Messaging
The number of text messages sent varied from 1 per day to 3 times per day. No participants requested less
than 1 message per day. Overall, 22 (71%) participants requested 3 messages per day, 4 (13%) requested 2
per day, and 5 (16%) requested 1 per day. All text messages were delivered to participants successfully; no
error messages were received and all messages were labeled as delivered. Also, no issues were reported by
participants.

All participants assigned to the smartphone group logged exercise and diet. Over the 3-month period, 6 (21%)
participants logged exercise on more than 50% of days and 18 (62%) logged diet on more than 50% of days.
Of those participants who logged on more than 50% of days, 3 (50%) logged physical activity on more than
75% of days and 7 (38%) logged diet on more than 75% of days. Table 5 displays the significant relationship
between number of physical activity days logged and weight loss (0.03 kg weight loss per additional day of
physical activity [PA] logging; P = .026). The 6 participants who logged PA more than 50% of the time lost 1.57
kg more than those who did not. When the threshold was reduced to 25% days logged, the 9 participants
logging PA 25% or more of the time lost 1.43 kg more than those logging PA less than 25% of the time. The
same directional trends were observed with increased logging frequency for food as well, but these were not
significant (P = .226), possibly because of overall good compliance with food logging.

TABLE 5 Relationships Between Logging Consistency and Weight Change

Discussion

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To date, to the authors’ knowledge, this is the first trial focused on young adults that used both individualized
text messages and a smartphone application for weight loss. This trial showed that the use of a smartphone
application combined with individualized text messages is successful in helping individuals to lose weight.
Individuals in the smartphone group lost significantly more weight, had a significant decrease in BMI, and
significantly decreased their waist circumference compared with the control group. However, many individuals
did not meet the recommended goal in the study to lose 1 to 2 lb per week. The mean weight loss in the
smartphone + health coach group was 4 lb over the 3-month trial. These results are promising when examining
other similar research. Although studies using technology or text messaging have seen improvements in
weight, many did not report any significant improvements when compared with a control condition.23,24 It is
possible that the combination of a smartphone application with text messaging led to significant improvements
in body weight in this group of young adults.

It is noteworthy that self-efficacy increased significantly for healthy eating (P = .03) in the smartphone + health
coach group and both groups experienced an increase in self-efficacy for exercise, although this was not
significant. It is possible that there were differences in self-efficacy between men and women or based on
racial category in this study; however, these differences were not tested. Recent studies conducted in college-
aged individuals reported implications for testing the differences in self-efficacy between men and women and
also indicate possible racial differences in self-efficacy for improving certain health behaviors. A study
published in 2015 by Bruce et al 25 reported significantly lower self-efficacy for changing sugar-sweetened
beverage consumption in African American college men compared with white college men. In addition, a study
examining Korean college students reported that self-efficacy for physical activity is a significant predictor of
physical activity in Korean men but not in Korean women.26 Future studies should include analyses on
differences in self-efficacy but should also examine other components of social cognitive theory, such as social
support or outcome expectations, which are known predictors of behaviors.21

An increase in logging into the smartphone application for both physical activity and diet led to better
outcomes with weight loss. It is therefore important that accountability be a focus in future interventions.
Accountability in this study was exhibited through the behavior of logging into an application; however,
accountability could be achieved many different ways in upcoming trials. In trials that use technology,
increasing compliance and accountability with smartphone logging could be achieved through a counselor
stressing the importance of logging during a session or more frequent reminders could be sent to participant
phones.

There are several strengths to note in this study. Strengths of the study include the randomized design
powered to detect significant differences between groups, use of a commercially available smartphone
application, and an attrition rate of only 5%. In addition, the study population was diverse: 38 (62%)
participants were from a minority group and 21 (33%) identified as Asian and 8 (13%) identified as African
American.

Study limitations include the small sample size and limited generalizability of the study population in that most
were attending college at a single university on the east coast. Also, the study was of short duration (3 months)
with no extended follow-up. Finally, it cannot be determined whether differences between groups were a result
of the health coach text messaging or the smartphone application.

Conclusion

This randomized controlled trial using a smartphone application for weight loss combined with individualized
text messages has provided valuable information that the combination of self-monitoring via an application and
feedback from a health coach is successful in helping young adults lose weight. The study had a meaningful
impact on weight, BMI, and waist circumference. In future trials, a sample that includes equal amounts of
individuals attending college and those not attending college could strengthen the generalizability of the
results. Smartphone technology seems to be an appropriate resource to use when working with the young
adult population and it has the potential to greatly impact the serious public health problem of obesity.

What’s New and Important

* This is the first study to examine use of smartphone technology and text messaging for weight loss in young
adults.
* This study shows that using smartphone technology and text messaging can help young adults lose weight.
* Increased logging of physical activity on a smartphone led to increases in weight loss.

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https://ovidsp.dc1.ovid.com/ovid-a/ovidweb.cgi?Link+Set+Ref=00005082-201701000-00007%7C00006826_1982_12_871_garner_psychometric_%7c00005082-201701000-00007%23xpointer%28id%28R13-7%29%29%7c60%7c%7covftdb%7c&P=87&S=INNJFPKMMGACNBIFKPOJMGMOPFLBAA00&WebLinkReturn=Full+Text%3dL%7cS.sh.27.28%7c0%7c00005082-201701000-00007

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https://ovidsp.dc1.ovid.com/ovid-a/ovidweb.cgi?Link+Set+Ref=00005082-201701000-00007%7C00001135_2006_21_i19_wilson_measurement_%7c00005082-201701000-00007%23xpointer%28id%28R19-7%29%29%7c70%7c%7covftdb%7c00055749-200612001-00003&P=93&S=INNJFPKMMGACNBIFKPOJMGMOPFLBAA00&WebLinkReturn=Full+Text%3dL%7cS.sh.27.28%7c0%7c00005082-201701000-00007

https://health.gov/paguidelines

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KEY WORDS: self-efficacy; text messaging; weight loss; young adult

IMAGE GALLERY

Table 1

Table 2

FIGURE. Study flow d…

Table 3
Table 4

Table 5

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https://ovidsp.dc1.ovid.com/ovid-a/ovidweb.cgi?Link+Set+Ref=00005082-201701000-00007%7C00009862_2014_27_322_hebden_intervention_%7c00005082-201701000-00007%23xpointer%28id%28R24-7%29%29%7c60%7c%7covftdb%7c00009862-201408000-00003&P=98&S=INNJFPKMMGACNBIFKPOJMGMOPFLBAA00&WebLinkReturn=Full+Text%3dL%7cS.sh.27.28%7c0%7c00005082-201701000-00007

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