SlideShare a Scribd company logo
1 of 1
Download to read offline
Background
Methods
Results
Discussion
Drexel University
Tinashe M.Tapera, Stephanie P. Goldstein BS, BrittneyC. Evans BS,
Evan Forman PhD
Does Ecological Momentary Assessment Data Reflect Baseline
Self-Report inWeight LossTreatment?
Contact:Tinashe M.Tapera, tmt85@drexel.edu
• Disordered eating behaviors are predicted by questionnaires
such as theThree Factor EatingQuestionnaire (TFEQ).
• Participants’ responses to weight loss (WL) treatment studies
can be predicted at baseline usingTFEQ scores.
• The advent of smartphone technology has enabled more
efficient and accurate collection of self-report data through
EMA:
• Dietary lapses can be recorded in real time;
• Participants can describe the external and internal
factors that trigger the lapse in diet.
• Triggers can be compared with predicted behaviors.
• Traditional self-report measures of eating behavior may not be
as accurate as real-world and real-time measurement.
• TFEQ was administered to 12 participants (BMI=27-45 kg/m2,
age=18-57) at the beginning of a WL study involving smartphone
use (Diet Alert SmartphoneApp).
• TFEQ was administered to n=12, BMI=27-45 kg/m2, age=18-57
participants at the beginning of aWL study involving
smartphone use (Diet Alert SmartphoneApp).
• Participants’TFEQ was scored on 3 subscales:
• Cognitive restraint (conscious restriction of intake)
• Internal disinhibition (sensitivity to internal eating
triggers)
• External disinhibition (sensitivity to external eating
triggers)
• TFEQ subscales were dichotomized along the median values,
and participants grouped into low and high scoring subscale
groups.
• Participants collected 6 weeks of EMA data via mobile app,
recording triggers and their causes.
• Groups’ means for each trigger were statistically compared
using SPSS to observe which groups more frequently reported
triggers.
• Low restraint group triggers (boredom, feeling they
deserve it, low motivation) are coherent with low
cognitive restraint.
• High external disinhibition group frequently reported
negative thoughts, an internal trigger.
• Mixed results indicate that baseline measurements may
not be accurate predictors of dietary behavior due to:
• Bias and misinterpretation on the part of the
participant
• Attribution bias of dietary lapse trigger
conditions.
• Future research should apply more vigorous statistical
modeling approaches such as cluster analyses to further
investigate discrepancies.
Aim: Statistically compare reported triggers in EMA against
predicted behaviors at baseline in aWL study.
Hypothesis: Participants will report triggers that do not reflect
their baseline predictions.
The means for each trigger were compared in an
independent samples t-test. Results revealed triggers that
were significantly more frequently reported than others for
particular groups:
1. Low Cognitive Restraint participants more frequently
reported:
“Boredom” (p = 0.04)
“Felt I deserved it” (p = 0.05)
“Lack of motivation” (p = 0.06)
2. High External Disinhibition participants more frequently
reported:
“Negative thoughts” (p = 0.02)

More Related Content

What's hot

Making evidence accessible to clinicians
Making evidence accessible to cliniciansMaking evidence accessible to clinicians
Making evidence accessible to clinicianscmaverga
 
Searching For The Evidence
Searching For The EvidenceSearching For The Evidence
Searching For The EvidenceBillie Anne Gebb
 
The drug effectiveness review project: governments collaborating to use syste...
The drug effectiveness review project: governments collaborating to use syste...The drug effectiveness review project: governments collaborating to use syste...
The drug effectiveness review project: governments collaborating to use syste...cmaverga
 
5.3.1 causal em
5.3.1 causal em5.3.1 causal em
5.3.1 causal emA M
 
The effects of self regulation education on use of inhaled anti-inflammatories
The effects of self regulation education on use of inhaled anti-inflammatoriesThe effects of self regulation education on use of inhaled anti-inflammatories
The effects of self regulation education on use of inhaled anti-inflammatoriesCenter for Managing Chronic Disease
 
Cancer Thriving and Surviving
Cancer Thriving and SurvivingCancer Thriving and Surviving
Cancer Thriving and Survivingyan_stanford
 
DNP Bound - Using the Library/Searching for the Evidence
DNP Bound - Using the Library/Searching for the EvidenceDNP Bound - Using the Library/Searching for the Evidence
DNP Bound - Using the Library/Searching for the EvidenceBillie Anne Gebb
 
Week 12 discussion research
Week 12 discussion researchWeek 12 discussion research
Week 12 discussion researchHaleyKnutson1
 
Introduction to behavioral economics
Introduction to behavioral economicsIntroduction to behavioral economics
Introduction to behavioral economicsDayOne
 
Confounding and Directed Acyclic Graphs
Confounding and Directed Acyclic GraphsConfounding and Directed Acyclic Graphs
Confounding and Directed Acyclic GraphsDarren L Dahly PhD
 
Listening to your audience qualitative research in malaria interventions c ch...
Listening to your audience qualitative research in malaria interventions c ch...Listening to your audience qualitative research in malaria interventions c ch...
Listening to your audience qualitative research in malaria interventions c ch...ACT Consortium
 
Comparing data accuracy between structured abstracts and full-text journal ar...
Comparing data accuracy between structured abstracts and full-text journal ar...Comparing data accuracy between structured abstracts and full-text journal ar...
Comparing data accuracy between structured abstracts and full-text journal ar...University of the Philippines Manila
 
5.1.1 sufficient component cause model
5.1.1 sufficient component cause model5.1.1 sufficient component cause model
5.1.1 sufficient component cause modelA M
 
Path a Manualized Program for HIV Prevention with Persons with Mental Illness...
Path a Manualized Program for HIV Prevention with Persons with Mental Illness...Path a Manualized Program for HIV Prevention with Persons with Mental Illness...
Path a Manualized Program for HIV Prevention with Persons with Mental Illness...Leonard Davis Institute of Health Economics
 
GS or BS? Good science or bad science
GS or BS?  Good science or bad scienceGS or BS?  Good science or bad science
GS or BS? Good science or bad scienceRon Lyon
 
5.1.2 counterfactual framework
5.1.2 counterfactual framework5.1.2 counterfactual framework
5.1.2 counterfactual frameworkA M
 

What's hot (18)

Making evidence accessible to clinicians
Making evidence accessible to cliniciansMaking evidence accessible to clinicians
Making evidence accessible to clinicians
 
Searching For The Evidence
Searching For The EvidenceSearching For The Evidence
Searching For The Evidence
 
The drug effectiveness review project: governments collaborating to use syste...
The drug effectiveness review project: governments collaborating to use syste...The drug effectiveness review project: governments collaborating to use syste...
The drug effectiveness review project: governments collaborating to use syste...
 
5.3.1 causal em
5.3.1 causal em5.3.1 causal em
5.3.1 causal em
 
The effects of self regulation education on use of inhaled anti-inflammatories
The effects of self regulation education on use of inhaled anti-inflammatoriesThe effects of self regulation education on use of inhaled anti-inflammatories
The effects of self regulation education on use of inhaled anti-inflammatories
 
Cancer Thriving and Surviving
Cancer Thriving and SurvivingCancer Thriving and Surviving
Cancer Thriving and Surviving
 
DNP Bound - Using the Library/Searching for the Evidence
DNP Bound - Using the Library/Searching for the EvidenceDNP Bound - Using the Library/Searching for the Evidence
DNP Bound - Using the Library/Searching for the Evidence
 
Week 12 discussion research
Week 12 discussion researchWeek 12 discussion research
Week 12 discussion research
 
Introduction to behavioral economics
Introduction to behavioral economicsIntroduction to behavioral economics
Introduction to behavioral economics
 
Confounding and Directed Acyclic Graphs
Confounding and Directed Acyclic GraphsConfounding and Directed Acyclic Graphs
Confounding and Directed Acyclic Graphs
 
Poster
PosterPoster
Poster
 
Listening to your audience qualitative research in malaria interventions c ch...
Listening to your audience qualitative research in malaria interventions c ch...Listening to your audience qualitative research in malaria interventions c ch...
Listening to your audience qualitative research in malaria interventions c ch...
 
Comparing data accuracy between structured abstracts and full-text journal ar...
Comparing data accuracy between structured abstracts and full-text journal ar...Comparing data accuracy between structured abstracts and full-text journal ar...
Comparing data accuracy between structured abstracts and full-text journal ar...
 
5.1.1 sufficient component cause model
5.1.1 sufficient component cause model5.1.1 sufficient component cause model
5.1.1 sufficient component cause model
 
Path a Manualized Program for HIV Prevention with Persons with Mental Illness...
Path a Manualized Program for HIV Prevention with Persons with Mental Illness...Path a Manualized Program for HIV Prevention with Persons with Mental Illness...
Path a Manualized Program for HIV Prevention with Persons with Mental Illness...
 
GS or BS? Good science or bad science
GS or BS?  Good science or bad scienceGS or BS?  Good science or bad science
GS or BS? Good science or bad science
 
5.1.2 counterfactual framework
5.1.2 counterfactual framework5.1.2 counterfactual framework
5.1.2 counterfactual framework
 
Tgfa studies 3
Tgfa studies 3Tgfa studies 3
Tgfa studies 3
 

Similar to TaperaT36'widex48'highUnmounted

DNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docx
DNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docxDNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docx
DNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docxgreg1eden90113
 
Local Determinants of Malnutrition: An Expanded Positive Deviance Study
Local Determinants of Malnutrition: An Expanded Positive Deviance StudyLocal Determinants of Malnutrition: An Expanded Positive Deviance Study
Local Determinants of Malnutrition: An Expanded Positive Deviance Studyjehill3
 
Vol.(0123456789)1 3Cognitive Therapy and Research (2019) .docx
Vol.(0123456789)1 3Cognitive Therapy and Research (2019) .docxVol.(0123456789)1 3Cognitive Therapy and Research (2019) .docx
Vol.(0123456789)1 3Cognitive Therapy and Research (2019) .docxjessiehampson
 
Kumar NSGC 2015 44x44@196%-PrintReady
Kumar NSGC 2015 44x44@196%-PrintReadyKumar NSGC 2015 44x44@196%-PrintReady
Kumar NSGC 2015 44x44@196%-PrintReadyKate Lee, MPH
 
nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...
nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...
nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...DerejeBayissa2
 
Cross sectional study overview
Cross sectional study overviewCross sectional study overview
Cross sectional study overviewherunyu
 
Neurodevelopmental Treatment and Cerebral Palsy- Research
Neurodevelopmental Treatment and Cerebral Palsy- ResearchNeurodevelopmental Treatment and Cerebral Palsy- Research
Neurodevelopmental Treatment and Cerebral Palsy- Researchda5884
 
BASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptxBASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptxardrianmalangen2
 
Survey procedures in dentistry
Survey procedures in dentistrySurvey procedures in dentistry
Survey procedures in dentistrydeepthiRagasree
 
Detecting flawed meta analyses
Detecting flawed meta analysesDetecting flawed meta analyses
Detecting flawed meta analysesJames Coyne
 

Similar to TaperaT36'widex48'highUnmounted (20)

DNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docx
DNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docxDNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docx
DNP-816 Analysis & Applic of Health Data for ANPSTATISTICS QUIZ.docx
 
Local Determinants of Malnutrition: An Expanded Positive Deviance Study
Local Determinants of Malnutrition: An Expanded Positive Deviance StudyLocal Determinants of Malnutrition: An Expanded Positive Deviance Study
Local Determinants of Malnutrition: An Expanded Positive Deviance Study
 
Vol.(0123456789)1 3Cognitive Therapy and Research (2019) .docx
Vol.(0123456789)1 3Cognitive Therapy and Research (2019) .docxVol.(0123456789)1 3Cognitive Therapy and Research (2019) .docx
Vol.(0123456789)1 3Cognitive Therapy and Research (2019) .docx
 
Kumar NSGC 2015 44x44@196%-PrintReady
Kumar NSGC 2015 44x44@196%-PrintReadyKumar NSGC 2015 44x44@196%-PrintReady
Kumar NSGC 2015 44x44@196%-PrintReady
 
nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...
nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...
nihms-1567381.pdf Linking Pre-Pregnancy Care and Pregnancy Care to Improve Ne...
 
Cross sectional study overview
Cross sectional study overviewCross sectional study overview
Cross sectional study overview
 
Neurodevelopmental Treatment and Cerebral Palsy- Research
Neurodevelopmental Treatment and Cerebral Palsy- ResearchNeurodevelopmental Treatment and Cerebral Palsy- Research
Neurodevelopmental Treatment and Cerebral Palsy- Research
 
Bias and error.final(1).ppt
Bias and error.final(1).pptBias and error.final(1).ppt
Bias and error.final(1).ppt
 
BASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptxBASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptx
 
Experimental study on alzhimer
Experimental study on alzhimerExperimental study on alzhimer
Experimental study on alzhimer
 
Reserch methodology
Reserch methodologyReserch methodology
Reserch methodology
 
Survey procedures in dentistry
Survey procedures in dentistrySurvey procedures in dentistry
Survey procedures in dentistry
 
Empirical Development of an Intervention Dose 6.16.10
Empirical Development of an Intervention Dose 6.16.10Empirical Development of an Intervention Dose 6.16.10
Empirical Development of an Intervention Dose 6.16.10
 
Detecting flawed meta analyses
Detecting flawed meta analysesDetecting flawed meta analyses
Detecting flawed meta analyses
 
Evidence based Practice in Emergency Medicine
Evidence based Practice in Emergency Medicine Evidence based Practice in Emergency Medicine
Evidence based Practice in Emergency Medicine
 
Critical Apprasial
Critical Apprasial Critical Apprasial
Critical Apprasial
 
Critic
CriticCritic
Critic
 
GROUP 2.pptx
GROUP 2.pptxGROUP 2.pptx
GROUP 2.pptx
 
Chapter 1
Chapter 1Chapter 1
Chapter 1
 
Chapter 1
Chapter 1Chapter 1
Chapter 1
 

TaperaT36'widex48'highUnmounted

  • 1. Background Methods Results Discussion Drexel University Tinashe M.Tapera, Stephanie P. Goldstein BS, BrittneyC. Evans BS, Evan Forman PhD Does Ecological Momentary Assessment Data Reflect Baseline Self-Report inWeight LossTreatment? Contact:Tinashe M.Tapera, tmt85@drexel.edu • Disordered eating behaviors are predicted by questionnaires such as theThree Factor EatingQuestionnaire (TFEQ). • Participants’ responses to weight loss (WL) treatment studies can be predicted at baseline usingTFEQ scores. • The advent of smartphone technology has enabled more efficient and accurate collection of self-report data through EMA: • Dietary lapses can be recorded in real time; • Participants can describe the external and internal factors that trigger the lapse in diet. • Triggers can be compared with predicted behaviors. • Traditional self-report measures of eating behavior may not be as accurate as real-world and real-time measurement. • TFEQ was administered to 12 participants (BMI=27-45 kg/m2, age=18-57) at the beginning of a WL study involving smartphone use (Diet Alert SmartphoneApp). • TFEQ was administered to n=12, BMI=27-45 kg/m2, age=18-57 participants at the beginning of aWL study involving smartphone use (Diet Alert SmartphoneApp). • Participants’TFEQ was scored on 3 subscales: • Cognitive restraint (conscious restriction of intake) • Internal disinhibition (sensitivity to internal eating triggers) • External disinhibition (sensitivity to external eating triggers) • TFEQ subscales were dichotomized along the median values, and participants grouped into low and high scoring subscale groups. • Participants collected 6 weeks of EMA data via mobile app, recording triggers and their causes. • Groups’ means for each trigger were statistically compared using SPSS to observe which groups more frequently reported triggers. • Low restraint group triggers (boredom, feeling they deserve it, low motivation) are coherent with low cognitive restraint. • High external disinhibition group frequently reported negative thoughts, an internal trigger. • Mixed results indicate that baseline measurements may not be accurate predictors of dietary behavior due to: • Bias and misinterpretation on the part of the participant • Attribution bias of dietary lapse trigger conditions. • Future research should apply more vigorous statistical modeling approaches such as cluster analyses to further investigate discrepancies. Aim: Statistically compare reported triggers in EMA against predicted behaviors at baseline in aWL study. Hypothesis: Participants will report triggers that do not reflect their baseline predictions. The means for each trigger were compared in an independent samples t-test. Results revealed triggers that were significantly more frequently reported than others for particular groups: 1. Low Cognitive Restraint participants more frequently reported: “Boredom” (p = 0.04) “Felt I deserved it” (p = 0.05) “Lack of motivation” (p = 0.06) 2. High External Disinhibition participants more frequently reported: “Negative thoughts” (p = 0.02)