Thesis Defense-2

Effectiveness of a Weight Loss Program for Nurses

byAmanda HarrisEffectiveness of a Weight Loss Program for Nurses

BackgroundNurses make up a large percentage of the U.S. workforce (United States Department of Health and Human Services (USDHHS), 2010)

Research pertaining to the health and wellness of the nursing population indicates that a majority of nurses are overweight (Nahm, 2012; Miller, 2008)

Couple different populations, 55% of nurses studied were at least overweight (Miller, 2008; Han, 2011)

Nurses often care for others, but not themselves (USDHHS, 2010)

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BackgroundDietAlmost 2/3 did not get at least five servings of fruits and vegetables combined (Malik et al., 2011)Exercise48.6% of nurses did not participate in at least 30 minutes of exercise 5 days/week (Malik et al., 2011)

Why not exercising regularly?66.7%-not enough time39.5%-too tired33.6%-cannot afford29.6%-no motivation (Malik et al., 2011)

Background

Healthy Nurse Campaign

Standards of Practice of the American Holistic Nurses Association-there is a need for self-care, self-responsibility, spirituality, and reflection among the nursing population (McElligott et al., 2009)

Enter, self-monitoring:Self-monitoring is a technique in which participants observe and record their own behavior (Noland, 1989, p. 216)

BackgroundWhen diet and exercise are recorded, there is a higher awareness of caloric intake and expenditure; leading to a better managed body weight (Archarya et al., 2011; Akers et al., 2012; Carels et al., 2005; Carter et al., 2013; Haapala et al., 2009; Helsel et al., 2007; Turner-McGrievy et al., 2013; Vanwormer et al., 2012; & Wang et al., 2012)

What happens when nurses self-monitor diet and physical activity?

ObjectiveTo study the effectiveness of a weight loss program for hospital staff nurses by utilizing the MyFitnessPal phone application to log dietary intake and physical activity.

MethodsNarrative ReviewDesignInclusion CriteriaWritten in English languageParticipants comparative to general populationSelf-monitoring technique was utilized for at least dietStudy published between 2004-2015Weight loss was primary outcomeCinahl, Medline, AltHealthwatch, PubMed, SportDiscusSelf-monitoring, weight loss, diet, obesityCompare these techniques to our conducted study

MethodsExperimental studyParticipants-InclusionNurses in the Premier Health NetworkClinical, administrative, educationalDesire to lose weight>18 years oldWorks 30 hours/weekOwns a Smartphone deviceBMI >27kg/m

MethodsParticipants-ExclusionPregnancyChronic diseasePhysically impairedParticipating in another weight loss programUsing another self-monitoring technique for more than 2 months

MethodsDesignTwelve week randomized-controlled trial78 Nurses5 HospitalsHypothesisSelf-monitoring will yield more significant resultsWeight lossWaist circumferenceDietary habitsParticipation in physical activityHigher adherence

MethodsMeasurementsRandom number generator, order of arrival determined group

Day and time assignments were made for each facilityAn early morning and an evening time at each campus

Height, weight, waist circumference, questionnairesPortable stadiometerTanita scaleGulick measuring tape

SMART goal and signed informed consent required prior to measurements

MethodsEveryone, both experimental and control, participated in measurements and completing questionnaires

Rate Your Plate27 questions, higher score equaled better nutrition habitsInternational Physical Activity Questionnaire7 questions, higher score equaled greater physical activity participation

Both available through hyperlinks in sent emails

MethodsControl group goal: To achieve SMART goal by end of 12 week periodReceived weekly emails with wellness information and text message encouragementsExperimental group goal: Self-monitor diet to see if there were additional benefits for weight lossReceived same emails and textsHad to use MyFitnessPal for twelve weeks. Record 4 out of 7 days of week and at least 50% of calculated caloric intake to be deemed adherent to program.Instructed on how to log exercise, but was not required to be considered adherent.

MethodsStatitical AnalysisIndependent samples T-test showed no differences between intervention and control prior to study (p=0.05)

Frequency test run for those who did not complete the study

Paired samples T-test for within group analysis of changes in those who completed

Independent samples T-test run again for baseline statistics, but to assess for differences between those who completed and those who did not complete the study

ResultsNarrative ReviewPaper journalsFrequency of self-monitoring produced most significant results (Burke et. al, 2008; Helsel et. al, 2007; Bartfield et. al, 2011)PDAsSelf-monitoring and weight loss have strong correlation (Yon et. al, 2007)Weight loss higher for those who use trackers over paper records (Burke et. al, 2011 & Wang et. al, 2012)Technology could be an issue (Yon et. al, 2007)

ResultsNarrative ReviewWebsitesHigher percentage of weight loss for those who utilized the website tracker more frequently (Anton et. al, 2012)Men lost more weight than women, but they monitored more whereas women spent more time in accountability than monitoring (Johnson et. al, 2011)AppsTurner-McGrievyGiven choice of monitoring methodFrequency of self-monitoring with each method did not differ (p=0.63)More monitoring suggest greater weight loss (p=0.001)

ResultsNarrative ReviewAppsRetention rates: App group (93%), website (55%), diary (53%)Intent-to-treat analysis resultsApp group weight loss: 4.6kg, website: 1.3kg, diary: 2.9kgChange in weight significant between app and website (p=0.04)27.3% had clinically significant (p=0.05) weight loss

Baseline DemographicsTable 1-ABaseline Demographics (n=78)Weight (kg)96.518.4Body Mass Index (kg/m)35.85.9Waist Circumference (cm)107.113.6Rate Your Plate (out of 81 possible points)55.17.3

ResultsExperimentStarted with 40 nurses in intervention and 38 in control

After 12 weeks, enrollment dropped15 in intervention11 in control

Those who did not finish were labeled as non-completers (n=52)

Completers did record exercise in addition to diet, but IPAQ pre and post results were invalid for obtaining a statistical analysis

ResultsIntervention vs. ControlControlMean increase body mass index and waist circumferenceNo significant RYP score changeInterventionMean decrease in body mass index and waist circumferenceSignificant increase in RYP score (p=