Ignite Creation Date:
2025-12-25 @ 3:38 AM
Ignite Modification Date:
2026-03-06 @ 10:49 AM
Study NCT ID:
NCT03670602
Status:
COMPLETED
Last Update Posted:
2022-12-09
First Post:
2018-09-07
Is Gene Therapy:
True
Has Adverse Events:
True
Brief Title:
Weight Loss for Prediabetes Using Episodic Future Thinking
Sponsor:
Organization:
Raw JSON
{'hasResults': True, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011236', 'term': 'Prediabetic State'}, {'id': 'D015431', 'term': 'Weight Loss'}], 'ancestors': [{'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D001836', 'term': 'Body Weight Changes'}, {'id': 'D001835', 'term': 'Body Weight'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'resultsSection': {'moreInfoModule': {'pointOfContact': {'email': 'lhenet@buffalo.edu', 'phone': '716-829-3400', 'title': 'Leonard H. Epstein', 'organization': 'University at Buffalo'}, 'certainAgreement': {'piSponsorEmployee': False, 'restrictiveAgreement': False}}, 'adverseEventsModule': {'timeFrame': '24 weeks', 'eventGroups': [{'id': 'EG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.', 'otherNumAtRisk': 31, 'deathsNumAtRisk': 31, 'otherNumAffected': 0, 'seriousNumAtRisk': 31, 'deathsNumAffected': 0, 'seriousNumAffected': 1}, {'id': 'EG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.', 'otherNumAtRisk': 33, 'deathsNumAtRisk': 33, 'otherNumAffected': 0, 'seriousNumAtRisk': 33, 'deathsNumAffected': 0, 'seriousNumAffected': 0}], 'seriousEvents': [{'term': 'Torn Retina', 'notes': "Torn retina due to age, per participant's MD. Underwent emergency surgery within four days of event occurrence, 1 month recovery period.", 'stats': [{'groupId': 'EG000', 'numAtRisk': 31, 'numEvents': 1, 'numAffected': 1}, {'groupId': 'EG001', 'numAtRisk': 33, 'numEvents': 0, 'numAffected': 0}], 'organSystem': 'Eye disorders', 'assessmentType': 'SYSTEMATIC_ASSESSMENT'}], 'frequencyThreshold': '5'}, 'outcomeMeasuresModule': {'outcomeMeasures': [{'type': 'PRIMARY', 'title': 'Change From Baseline in Delay Discounting', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline Delay Discounting', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-5.92', 'spread': '2.33', 'groupId': 'OG000'}, {'value': '-6.11', 'spread': '3.14', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in Delay discounting at 12 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '29', 'groupId': 'OG000'}, {'value': '30', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-3.09', 'spread': '2.63', 'groupId': 'OG000'}, {'value': '-0.96', 'spread': '2.18', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in Delay discounting at 24 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '28', 'groupId': 'OG000'}, {'value': '31', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-2.79', 'spread': '2.31', 'groupId': 'OG000'}, {'value': '-1.33', 'spread': '2.04', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.0035', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment influenced improvements in delay discounting across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Treatment group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate.', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}, {'pValue': '<0.001', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if delay discounting improved across all three timepoints, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Treatment group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Delay Discounting will be assessed using an adjusting amount task where choices will be present between a larger, delayed amount of money ($100) and a smaller, immediate amount. The smaller, immediate amount will begin at $50 on the first trial and will be adjusted following each trial. Participants cues created during treatment will be displayed during the task. To calculate discount rates hyperbolic discounting model will be used V=A/1+kD where V is discounted value, A is reward amount, D is delay and k is a free parameter that indexes the rate of discounting. k values are transformed using natural log. Higher scores indicate more choices for immediate reward. Change is assessed using repeated measures.', 'unitOfMeasure': 'ln (k)', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'All participants were analyzed using mixed model methods, 5 participants did not complete DD measures at 12 weeks, and 5 participants did not complete DD measures at 24 weeks'}, {'type': 'PRIMARY', 'title': 'Change From Baseline in Weight', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline Weight', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '102.3', 'spread': '22.3', 'groupId': 'OG000'}, {'value': '104.2', 'spread': '23.2', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in weight at 12 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '29', 'groupId': 'OG000'}, {'value': '30', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-6.8', 'spread': '4.3', 'groupId': 'OG000'}, {'value': '-7.2', 'spread': '3.8', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in weight at 24 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '29', 'groupId': 'OG000'}, {'value': '31', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-9.8', 'spread': '6.5', 'groupId': 'OG000'}, {'value': '-9.8', 'spread': '5.6', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.85', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment differentially influenced weight across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}, {'pValue': '<0.001', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if time influenced changes in weight, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks, and 24 weeks', 'description': 'Weight measured in kilograms. Change is assessed using repeated measures.', 'unitOfMeasure': 'kilograms', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intent to Treat (ITT) and included all randomized participants, using mixed models. 5 participants did not complete week 12 measures and 4 participants did not complete 24 week height and weight measures'}, {'type': 'PRIMARY', 'title': 'Change From Baseline in Glycemic Control', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline hBa1c', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '5.90', 'spread': '0.29', 'groupId': 'OG000'}, {'value': '5.91', 'spread': '0.29', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline hBa1c at 12 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '29', 'groupId': 'OG000'}, {'value': '30', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-0.22', 'spread': '0.36', 'groupId': 'OG000'}, {'value': '-0.27', 'spread': '0.28', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline hBa1c at 24 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '29', 'groupId': 'OG000'}, {'value': '31', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-0.35', 'spread': '0.35', 'groupId': 'OG000'}, {'value': '-0.39', 'spread': '0.31', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.79', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment group influenced change in hBa1c across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}, {'pValue': '<0.001', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if hBa1c changed across timepoints, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Glycemic control will be measured as hemoglobin A1c (HbA1c), which is the percentage of glycated hemoglobin within total hemoglobin. Change is assessed using repeated measures.', 'unitOfMeasure': 'Percentage of glycosylated hemoglobin', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intention to Treat (ITT) and included all randomized participants. 5 participants did not complete 12 week measures, and 4 participants did not complete 24 week measures.'}, {'type': 'SECONDARY', 'title': 'Change in Medication Adherence', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline medication adherence', 'denoms': [{'units': 'Participants', 'counts': [{'value': '30', 'groupId': 'OG000'}, {'value': '31', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '84.3', 'spread': '21.0', 'groupId': 'OG000'}, {'value': '91.7', 'spread': '17.2', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in medication adherence at 12 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '28', 'groupId': 'OG000'}, {'value': '28', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '5.33', 'spread': '17.3', 'groupId': 'OG000'}, {'value': '-0.25', 'spread': '19.5', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in medication adherence at 24 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '27', 'groupId': 'OG000'}, {'value': '28', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '5.23', 'spread': '16.49', 'groupId': 'OG000'}, {'value': '0.09', 'spread': '9.5', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.201', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment differentially influenced medication adherence across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}, {'pValue': '0.315', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if timepoint influenced medication adherence across all timepoints, independent of treatment group. The threshold for statistical significance was p = 0.05.', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Adherence to prescribed medication for co-morbid hypertension and/or hyperlipidemia will be assessed using pill counts. Experimenter will count pills 2x and record number of pills, medication, dosage and fill date. Adherence percentage is calculated \\[(Quantity of pills dispensed - remaining)/(quantity prescribed per day\\*days since last refill)\\] \\*100. Change is assessed using repeated measures.', 'unitOfMeasure': 'percent medication adherence', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intention to Treat (ITT) and included all randomized participants, using mixed model analyses. 3 participants did not completed baseline (0) medication adherence measurements, an additional 5 participants did not complete week 12 medication adherence measurements (total missing for change score n =8) and an additional 6 participants did not complete 24 week medication adherence measures (total missing for change score n=9)'}, {'type': 'SECONDARY', 'title': 'Changes in Physical Activity', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline percent MVPA', 'categories': [{'measurements': [{'value': '5.61', 'spread': '2.4', 'groupId': 'OG000'}, {'value': '5.67', 'spread': '2.65', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in percent MVPA at 12 weeks', 'categories': [{'measurements': [{'value': '1.16', 'spread': '1.95', 'groupId': 'OG000'}, {'value': '0.82', 'spread': '1.77', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in percent MVPA at 24 weeks', 'categories': [{'measurements': [{'value': '0.91', 'spread': '2.71', 'groupId': 'OG000'}, {'value': '0.22', 'spread': '1.54', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.345', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment group influenced change in percent of time engaged in moderate-to-vigorous physical activity (MVPA) across all three timepoints. The threshold for statistical significance was p = 0.05', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants', 'nonInferiorityComment': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate'}, {'pValue': '0.0003', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if percent of time engaged in moderate-to-vigorous physical activity (MVPA) changed across timepoints, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Physical activity, as one index of behavioral health and a target of the behavioral weight loss treatment, was measured using an Actigraph Accelerometer. Participants will be asked to wear an Actigraph Accelerometer for at least 10 hours per day for approximately one week. Accelerometer data was filtered using ActiLife, for 90 minutes consecutive non-wear and by participants wear time diaries. The main outcome measure was percent of time engaged in moderate to vigorous activity (MVPA) (MET\\>3.00). Change is assessed using repeated measures.', 'unitOfMeasure': 'Percent of time', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intention to Treat (ITT) and included all randomized participants, using mixed model analysis.'}, {'type': 'SECONDARY', 'title': 'Change in Total Calories', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline total daily calorie intake', 'denoms': [{'units': 'Participants', 'counts': [{'value': '30', 'groupId': 'OG000'}, {'value': '32', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '1802.2', 'spread': '591.5', 'groupId': 'OG000'}, {'value': '1886.3', 'spread': '594.7', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in total daily calorie intake at week 12', 'denoms': [{'units': 'Participants', 'counts': [{'value': '26', 'groupId': 'OG000'}, {'value': '29', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-542.5', 'spread': '599.3', 'groupId': 'OG000'}, {'value': '-504.7', 'spread': '465.0', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in total daily calorie intake at week 24', 'denoms': [{'units': 'Participants', 'counts': [{'value': '25', 'groupId': 'OG000'}, {'value': '29', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-298.4', 'spread': '458.0', 'groupId': 'OG000'}, {'value': '-568.3', 'spread': '363.5', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.007', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment differentially influenced changes in calorie intake across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY'}, {'pValue': '<0.0001', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if time influenced changes in calorie intake, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Dietary intake, as an index of behavioral health and a target of the treatment, was measured using 3 automated self-administered 24-hour multi-pass food recalls. Total calories were averaged across the three sessions for each timepoint. Change was assessed using repeated measures.', 'unitOfMeasure': 'kilocalories', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intent to Treat (ITT) and included all randomized participants, using mixed models. 2 participants did not complete baseline measures, 9 participants did not complete week 12 measures and 10 participants did not complete week 24 measures. One participant did not complete measures at any timepoint.'}, {'type': 'SECONDARY', 'title': 'Changes in Working Memory', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline Backwards Corsi Total Score', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '44.6', 'spread': '12.0', 'groupId': 'OG000'}, {'value': '46.0', 'spread': '14.0', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in backwards Corsi total score at 12 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '28', 'groupId': 'OG000'}, {'value': '28', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '2.1', 'spread': '18.3', 'groupId': 'OG000'}, {'value': '1.6', 'spread': '18.5', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in Backwards Corsi Total score at 24 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '28', 'groupId': 'OG000'}, {'value': '31', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '6.9', 'spread': '17.6', 'groupId': 'OG000'}, {'value': '4.5', 'spread': '13.5', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.774', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment differentially influenced changes in working memory across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}, {'pValue': '0.019', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if time influenced changes in working memory, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Visuospatial working memory will be measured using the Backwards Corsi block-tapping task. The total score, or (number of trials completed correctly (out of 14 trials) x longest correctly reported block of items (2 - 8 items) ). Possible scores range from 0 (minimum) - (112) maximum. Higher scores indicate better working memory. Change is assessed using repeated measures', 'unitOfMeasure': 'score', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intent to Treat (ITT) and included all randomized participants, using mixed models. 8 participants did not complete week 12 measures and 5 participants did not complete 24 week measures'}, {'type': 'OTHER_PRE_SPECIFIED', 'title': 'Changes in Relative Reinforcing Efficacy of Unhealthy Food', 'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'OG000'}, {'value': '33', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'OG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'classes': [{'title': 'Baseline relative reinforcing efficacy of unhealthy food', 'denoms': [{'units': 'Participants', 'counts': [{'value': '30', 'groupId': 'OG000'}, {'value': '32', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '0.926', 'spread': '0.483', 'groupId': 'OG000'}, {'value': '0.998', 'spread': '0.375', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in relative reinforcing efficacy of unhealthy food at 12 weeks', 'denoms': [{'units': 'Participants', 'counts': [{'value': '28', 'groupId': 'OG000'}, {'value': '30', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-0.351', 'spread': '0.466', 'groupId': 'OG000'}, {'value': '-0.348', 'spread': '0.442', 'groupId': 'OG001'}]}]}, {'title': 'Change from baseline in relative reinforcing efficacy of unhealthy food at 24 weeks.', 'denoms': [{'units': 'Participants', 'counts': [{'value': '27', 'groupId': 'OG000'}, {'value': '31', 'groupId': 'OG001'}]}], 'categories': [{'measurements': [{'value': '-0.328', 'spread': '0.545', 'groupId': 'OG000'}, {'value': '-0.247', 'spread': '0.468', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.650', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the treatment group x time effect, or if treatment differentially influenced relative reinforcing efficacy of unhealthy food across all three timepoints. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}, {'pValue': '<0.0001', 'groupIds': ['OG000', 'OG001'], 'pValueComment': 'This is for the time effect, or if time influenced changes in relative reinforcing efficacy of unhealthy food, independent of treatment group. The threshold for statistical significance was p = 0.05', 'groupDescription': 'A mixed model ANCOVA with unstructured covariance and random effects of participant. Group and cohort were the between subject variables, weeks as the repeated measure and site as a covariate', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Analyses were Intention to Treat (ITT) and included all randomized participants'}], 'paramType': 'MEAN', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Relative Reinforcing efficacy of food is measured with a hypothetical purchasing task, in which number two foods are available and number of portions of food purchased at various prices ($0 - $20) is measured. Foods used were considered unhealthy snack foods, e.g. cookies, potato chips, etc. Intensity, the number of portions of food requested when the price is $0, was used as the outcome measure. Significant non-normality of the data required a log base 10 transformation (log (food portions + 1). Larger numbers represent more food portions, higher intensity and higher reinforcing efficacy. Change is assessed using repeated measures.', 'unitOfMeasure': 'log (food portions + 1)', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Analyses were Intent to Treat (ITT) and included all randomized participants, using mixed models. 2 participants did not complete baseline measures, 6 participants did not complete week 12 measures and 6 participants did not complete week 24 measures of relative reinforcing efficacy. Two participants did not complete any measures of relative reinforcing efficacy.'}]}, 'participantFlowModule': {'groups': [{'id': 'FG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'FG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}], 'periods': [{'title': 'Overall Study', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '31'}, {'groupId': 'FG001', 'numSubjects': '33'}]}, {'type': 'Received Intervention Treatment', 'achievements': [{'groupId': 'FG000', 'numSubjects': '30'}, {'groupId': 'FG001', 'numSubjects': '30'}]}, {'type': 'Completed Session 2 (Week 12)', 'comment': 'Completed Session 2 refers to participants who completed the follow up assessment measures for week 12', 'achievements': [{'groupId': 'FG000', 'numSubjects': '29'}, {'groupId': 'FG001', 'numSubjects': '30'}]}, {'type': 'Completed Session 3 (Week 24)', 'comment': 'Completed Session 3 refers to participants who were able to complete follow-up assessment measures at week 24', 'achievements': [{'groupId': 'FG000', 'numSubjects': '28'}, {'groupId': 'FG001', 'numSubjects': '31'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '30'}, {'groupId': 'FG001', 'numSubjects': '30'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '1'}, {'groupId': 'FG001', 'numSubjects': '3'}]}], 'dropWithdraws': [{'type': 'Lost to Follow-up', 'reasons': [{'groupId': 'FG000', 'numSubjects': '1'}, {'groupId': 'FG001', 'numSubjects': '0'}]}, {'type': 'Withdrawal by Subject', 'reasons': [{'groupId': 'FG000', 'numSubjects': '0'}, {'groupId': 'FG001', 'numSubjects': '3'}]}]}], 'recruitmentDetails': 'Participants with prediabetes (HbA1c) between 5.7 to 6.4% Participants had no prior or current diagnosis of diabetes, were not pregnant and were not taking medications that influenced their blood glucose.', 'preAssignmentDetails': 'Participants (n=933) completed a prescreen internet survey and n=294 were screened in our laboratory. N=72 participated in the initial weight loss and 8 participants declined or did not qualify to enroll in the randomized study. 64 participants were randomized between intervention and control groups.'}, 'baselineCharacteristicsModule': {'denoms': [{'units': 'Participants', 'counts': [{'value': '31', 'groupId': 'BG000'}, {'value': '33', 'groupId': 'BG001'}, {'value': '64', 'groupId': 'BG002'}]}], 'groups': [{'id': 'BG000', 'title': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.\n\nEpisodic Future Thinking: Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, {'id': 'BG001', 'title': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.\n\nDaily Check in: Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.'}, {'id': 'BG002', 'title': 'Total', 'description': 'Total of all reporting groups'}], 'measures': [{'title': 'Age, Continuous', 'classes': [{'categories': [{'measurements': [{'value': '55.0', 'spread': '10.4', 'groupId': 'BG000'}, {'value': '54.1', 'spread': '9.3', 'groupId': 'BG001'}, {'value': '54.6', 'spread': '9.8', 'groupId': 'BG002'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'Years', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Sex: Female, Male', 'classes': [{'categories': [{'title': 'Female', 'measurements': [{'value': '25', 'groupId': 'BG000'}, {'value': '26', 'groupId': 'BG001'}, {'value': '51', 'groupId': 'BG002'}]}, {'title': 'Male', 'measurements': [{'value': '6', 'groupId': 'BG000'}, {'value': '7', 'groupId': 'BG001'}, {'value': '13', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Race (NIH/OMB)', 'classes': [{'categories': [{'title': 'American Indian or Alaska Native', 'measurements': [{'value': '0', 'groupId': 'BG000'}, {'value': '0', 'groupId': 'BG001'}, {'value': '0', 'groupId': 'BG002'}]}, {'title': 'Asian', 'measurements': [{'value': '0', 'groupId': 'BG000'}, {'value': '2', 'groupId': 'BG001'}, {'value': '2', 'groupId': 'BG002'}]}, {'title': 'Native Hawaiian or Other Pacific Islander', 'measurements': [{'value': '0', 'groupId': 'BG000'}, {'value': '0', 'groupId': 'BG001'}, {'value': '0', 'groupId': 'BG002'}]}, {'title': 'Black or African American', 'measurements': [{'value': '6', 'groupId': 'BG000'}, {'value': '4', 'groupId': 'BG001'}, {'value': '10', 'groupId': 'BG002'}]}, {'title': 'White', 'measurements': [{'value': '21', 'groupId': 'BG000'}, {'value': '24', 'groupId': 'BG001'}, {'value': '45', 'groupId': 'BG002'}]}, {'title': 'More than one race', 'measurements': [{'value': '2', 'groupId': 'BG000'}, {'value': '2', 'groupId': 'BG001'}, {'value': '4', 'groupId': 'BG002'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '2', 'groupId': 'BG000'}, {'value': '1', 'groupId': 'BG001'}, {'value': '3', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Region of Enrollment', 'classes': [{'title': 'United States', 'categories': [{'measurements': [{'value': '31', 'groupId': 'BG000'}, {'value': '33', 'groupId': 'BG001'}, {'value': '64', 'groupId': 'BG002'}]}]}], 'paramType': 'NUMBER', 'unitOfMeasure': 'participants'}, {'title': 'Body Mass Index (BMI)', 'classes': [{'categories': [{'measurements': [{'value': '37.0', 'spread': '7.2', 'groupId': 'BG000'}, {'value': '38.0', 'spread': '6.9', 'groupId': 'BG001'}, {'value': '37.5', 'spread': '7.0', 'groupId': 'BG002'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'kg/m^2', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'HbA1c (%)', 'classes': [{'categories': [{'measurements': [{'value': '5.90', 'spread': '0.29', 'groupId': 'BG000'}, {'value': '5.91', 'spread': '0.29', 'groupId': 'BG001'}, {'value': '5.90', 'spread': '0.29', 'groupId': 'BG002'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'percentage of glycosylated hemoglobin', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Education', 'classes': [{'categories': [{'measurements': [{'value': '15.7', 'spread': '2.2', 'groupId': 'BG000'}, {'value': '15.5', 'spread': '2.3', 'groupId': 'BG001'}, {'value': '15.6', 'spread': '2.2', 'groupId': 'BG002'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'years', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Annual Household Income', 'classes': [{'categories': [{'measurements': [{'value': '37500', 'spread': '27335', 'groupId': 'BG000'}, {'value': '48889', 'spread': '35608', 'groupId': 'BG001'}, {'value': '43090', 'spread': '31892', 'groupId': 'BG002'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'US$', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Delay Discounting', 'classes': [{'categories': [{'measurements': [{'value': '-5.92', 'spread': '2.33', 'groupId': 'BG000'}, {'value': '-6.11', 'spread': '3.14', 'groupId': 'BG001'}, {'value': '-6.01', 'spread': '2.73', 'groupId': 'BG002'}]}]}], 'paramType': 'MEAN', 'description': 'Delay Discounting is assessed using an adjusting amount task with monetary choices between larger delayed ($100) and smaller immediate amounts. The immediate amount starts at $50 and is adjusted following each trial. Participants cues created during treatment will be displayed. To calculate discount rates hyperbolic discounting model will be used V=A/1+kD where V is discounted value, A is reward amount, D is delay and k is a free parameter that indexes the rate of discounting. k values are transformed using natural log (ln(K+1). Higher scores indicate more choices for immediate reward.', 'unitOfMeasure': 'ln (k)', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Site Enrollment', 'classes': [{'categories': [{'title': 'University at Buffalo', 'measurements': [{'value': '16', 'groupId': 'BG000'}, {'value': '17', 'groupId': 'BG001'}, {'value': '33', 'groupId': 'BG002'}]}, {'title': 'Virginia Tech Carillon', 'measurements': [{'value': '15', 'groupId': 'BG000'}, {'value': '16', 'groupId': 'BG001'}, {'value': '31', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'description': 'Enrollment at University at Buffalo site and Virginia Tech Carillon site.', 'unitOfMeasure': 'Participants'}, {'title': 'Timing of treatment with COVID-19 by cohort', 'classes': [{'categories': [{'title': 'Cohort 1; prior to COVID, in person', 'measurements': [{'value': '12', 'groupId': 'BG000'}, {'value': '13', 'groupId': 'BG001'}, {'value': '25', 'groupId': 'BG002'}]}, {'title': 'Cohort 2; before and during COVID; 50% in person 50% remote', 'measurements': [{'value': '10', 'groupId': 'BG000'}, {'value': '11', 'groupId': 'BG001'}, {'value': '21', 'groupId': 'BG002'}]}, {'title': 'Cohort 3 - during COVID, remote', 'measurements': [{'value': '9', 'groupId': 'BG000'}, {'value': '9', 'groupId': 'BG001'}, {'value': '18', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'description': 'Participants were run in three treatment cohorts, in which COVID influenced protocol implementation. One cohort was completed before COVID-19, one cohort was completed both before and during COVID-19 and one cohort was conducted completely remotely during COVID-19.', 'unitOfMeasure': 'Participants'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2021-01-15', 'size': 419206, 'label': 'Study Protocol and Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'Prot_SAP_000.pdf', 'typeAbbrev': 'Prot_SAP', 'uploadDate': '2022-11-10T10:52', 'hasProtocol': True}, {'date': '2021-01-15', 'size': 344807, 'label': 'Informed Consent Form', 'hasIcf': True, 'hasSap': False, 'filename': 'ICF_001.pdf', 'typeAbbrev': 'ICF', 'uploadDate': '2022-09-12T14:45', 'hasProtocol': False}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['OUTCOMES_ASSESSOR'], 'maskingDescription': "Research personnel who will be conducting assessment sessions, including weight measurements, will not be informed of participant's group assignment"}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Participants will engage in EFT or control while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 64}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2019-01-17', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-11', 'completionDateStruct': {'date': '2021-06-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-11-10', 'studyFirstSubmitDate': '2018-09-07', 'resultsFirstSubmitDate': '2022-09-12', 'studyFirstSubmitQcDate': '2018-09-12', 'lastUpdatePostDateStruct': {'date': '2022-12-09', 'type': 'ACTUAL'}, 'resultsFirstSubmitQcDate': '2022-11-10', 'studyFirstPostDateStruct': {'date': '2018-09-13', 'type': 'ACTUAL'}, 'resultsFirstPostDateStruct': {'date': '2022-12-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-06-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Changes in Relative Reinforcing Efficacy of Unhealthy Food', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Relative Reinforcing efficacy of food is measured with a hypothetical purchasing task, in which number two foods are available and number of portions of food purchased at various prices ($0 - $20) is measured. Foods used were considered unhealthy snack foods, e.g. cookies, potato chips, etc. Intensity, the number of portions of food requested when the price is $0, was used as the outcome measure. Significant non-normality of the data required a log base 10 transformation (log (food portions + 1). Larger numbers represent more food portions, higher intensity and higher reinforcing efficacy. Change is assessed using repeated measures.'}], 'primaryOutcomes': [{'measure': 'Change From Baseline in Delay Discounting', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Delay Discounting will be assessed using an adjusting amount task where choices will be present between a larger, delayed amount of money ($100) and a smaller, immediate amount. The smaller, immediate amount will begin at $50 on the first trial and will be adjusted following each trial. Participants cues created during treatment will be displayed during the task. To calculate discount rates hyperbolic discounting model will be used V=A/1+kD where V is discounted value, A is reward amount, D is delay and k is a free parameter that indexes the rate of discounting. k values are transformed using natural log. Higher scores indicate more choices for immediate reward. Change is assessed using repeated measures.'}, {'measure': 'Change From Baseline in Weight', 'timeFrame': 'Baseline (0 weeks), 12 weeks, and 24 weeks', 'description': 'Weight measured in kilograms. Change is assessed using repeated measures.'}, {'measure': 'Change From Baseline in Glycemic Control', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Glycemic control will be measured as hemoglobin A1c (HbA1c), which is the percentage of glycated hemoglobin within total hemoglobin. Change is assessed using repeated measures.'}], 'secondaryOutcomes': [{'measure': 'Change in Medication Adherence', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Adherence to prescribed medication for co-morbid hypertension and/or hyperlipidemia will be assessed using pill counts. Experimenter will count pills 2x and record number of pills, medication, dosage and fill date. Adherence percentage is calculated \\[(Quantity of pills dispensed - remaining)/(quantity prescribed per day\\*days since last refill)\\] \\*100. Change is assessed using repeated measures.'}, {'measure': 'Changes in Physical Activity', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Physical activity, as one index of behavioral health and a target of the behavioral weight loss treatment, was measured using an Actigraph Accelerometer. Participants will be asked to wear an Actigraph Accelerometer for at least 10 hours per day for approximately one week. Accelerometer data was filtered using ActiLife, for 90 minutes consecutive non-wear and by participants wear time diaries. The main outcome measure was percent of time engaged in moderate to vigorous activity (MVPA) (MET\\>3.00). Change is assessed using repeated measures.'}, {'measure': 'Change in Total Calories', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Dietary intake, as an index of behavioral health and a target of the treatment, was measured using 3 automated self-administered 24-hour multi-pass food recalls. Total calories were averaged across the three sessions for each timepoint. Change was assessed using repeated measures.'}, {'measure': 'Changes in Working Memory', 'timeFrame': 'Baseline (0 weeks), 12 weeks and 24 weeks', 'description': 'Visuospatial working memory will be measured using the Backwards Corsi block-tapping task. The total score, or (number of trials completed correctly (out of 14 trials) x longest correctly reported block of items (2 - 8 items) ). Possible scores range from 0 (minimum) - (112) maximum. Higher scores indicate better working memory. Change is assessed using repeated measures'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Weight loss, delay discounting'], 'conditions': ['PreDiabetes']}, 'descriptionModule': {'briefSummary': 'The goals of the UH3 are to assess the effectiveness of adding Episodic Future Thinking (EFT) to the investigators standard behavioral weight control program to improve weight loss, delay discounting (DD), working memory, glycemic control (HbA1c) and behavioral medication adherence over a 6 month period in persons with prediabetes and comorbid hypertension and/or hyperlipidemia. This will be accomplished by a randomized trial (N = 71 randomized) comparing the effects of EFT versus control that matches attention and use of technology.', 'detailedDescription': 'Participants in both groups will first attend weekly group meetings followed by monthly group meetings for up to 6 months. They will be provided general information on healthy diet, physical activity and medication adherence that the investigators will develop combining strengths of the investigators well validated family-based behavioral treatment for obesity and the Diabetes Prevention Program (DPP) lifestyle intervention for prediabetes. The behavioral treatment (BT) is a rigorously tested, multi-component intervention that targets diet, activity, and behavioral skills. The treatment will include: 1) a modified version of the Traffic Light Diet, which utilizes RED, YELLOW, GREEN labels for food to guide participants toward the goal of consuming low energy dense, low glycemic, high nutrient dense foods; 2) the Traffic Light Activity Program, which also utilizes RED, YELLOW and GREEN labels for different levels of caloric expenditure, and 3) a variety of behavioral techniques, including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food, and EFT. The investigators have used a traffic light-based intervention in combination with EFT in a pilot study to demonstrate therapeutic effects of EFT on BMI and dietary intake beyond the effects of BT alone.\n\nDuring treatment meetings, participants will be weighed and have a 30-60 minute group session (up to 20 per group) either preceded or followed by an individualized session with an interventionist. The group sessions review information about weight loss and maintenance and engage in group problem solving for participants who are struggling with behavior change. During the individual meeting with their interventionist, participants are taught behavior change techniques and review and address diet and activity self-monitoring and any barriers to adherence with the weight-loss behaviors. A study website will be developed that will be used to provide information about the intervention, downloadable manuals for the Traffic Light Diet and Activity Program, manage the EFT component of the intervention, and provide tools for cooking, and getting more physical activity. Quizzes to assess mastery of educational materials will be implemented on the study website, with multiple versions of quizzes on each module available to account for those participants who will acquire the information more slowly than others. Participants will have access to traditional paper and pencil self-monitoring, and consistent with current implementation of BT, after self-monitoring skill is acquired, participants can choose to use traditional or technology-based recording. Participants will have access to the study website for feedback, and interventionists will have access to the website to assess patient progress, assist with problem solving and to communicate with participants to structure solutions. The website will also contain password protected sections that are for internal use by study personnel. This section will be a repository for study documents and a communications hub for the study. The website will not contain protected health information.\n\nParticipants in both groups will meet with an interventionist to review progress. One group will be trained to implement EFT using the ecological momentary intervention (EMI) computer based program that the investigators have developed. This program can be accessed by smartphone, tablet or computer. This application stores self-generated EFT cues, prompts their use, asks questions about use, and records their use. EFT training will include developing individualized future event cues to use in implementing EFT in the natural environment. In the control group, participants may use non-future cues, recall previous events, and not use prospection.\n\nCues are stimuli that prompt engaging in EFT. Cues can be signs, reminder cards, audio cues, or physical cues. Subjects will practice using these cues and learn to envision that the "future is now" when making decisions in the laboratory as they are engaged in a variety of DD and food decision training tasks such as the opportunity to have a very enticing snack now or larger portions of healthier food later, earning a small amount of money now or more later, etc. In this way, participants will learn to generate episodic future cues and practice EFT skills in situations where they usually would choose the more immediate reward. Episodic future cues may include audio and written cues that can be accessed during tempting situations in the natural environment. During individual sessions interventionists will review habit changes and medication adherence, and use of EFT. In the control group participants be asked to log into the MAMRT web-app at the same frequency as the EFT group, but will see no cues prior to their daily questions.\n\nParticipants in both groups will be weighed at the beginning of each session, and height will also be collected at baseline. Data to be collected at baseline, 3 and 6 months include delay discounting tasks, working memory, measures of medication and behavioral adherence, weight, glycemic control, blood pressure and cholesterol, eating and activity.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '74 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Overweight or obese (BMI ≥ 25)\n* Prediabetes (HbA1c between 5.7 - 6.4%; 39-40 mmol/mol)\n\nExclusion Criteria:\n\n* Type 2 Diabetes\n* Use of diabetic drugs\n* Pregnancy\n* Not ambulatory\n* Intellectual impairment\n* Unmanaged mood disorders\n* Current substance use disorder (excluding nicotine and caffeine)\n* History of eating disorders (Except binge eating disorder)\n* Abnormal blood glucose related to medications'}, 'identificationModule': {'nctId': 'NCT03670602', 'acronym': 'MINDD4', 'briefTitle': 'Weight Loss for Prediabetes Using Episodic Future Thinking', 'organization': {'class': 'OTHER', 'fullName': 'State University of New York at Buffalo'}, 'officialTitle': 'Delay Discounting as a Target for Self-Regulation in Prediabetes', 'orgStudyIdInfo': {'id': '5UH3DK109543-05', 'link': 'https://reporter.nih.gov/quickSearch/5UH3DK109543-05', 'type': 'NIH'}, 'secondaryIdInfos': [{'id': '5UH3DK109543-05', 'link': 'https://reporter.nih.gov/quickSearch/5UH3DK109543-05', 'type': 'NIH'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Episodic Future Thinking (EFT)', 'description': 'Participants will generate positive future cues that will be accessed via an electronic app to engage in EFT.', 'interventionNames': ['Behavioral: Episodic Future Thinking']}, {'type': 'PLACEBO_COMPARATOR', 'label': 'Daily Check in (DCI)', 'description': 'Participants will be asked to access an electronic app daily, but will receive no cues.', 'interventionNames': ['Behavioral: Daily Check in']}], 'interventions': [{'name': 'Episodic Future Thinking', 'type': 'BEHAVIORAL', 'otherNames': ['EFT'], 'description': 'Participants will practice using these cues when making decisions about health choices. Participants will implement EFT while using The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, resetting rewarding mechanisms by reducing need for immediate gratification, finding behavioral substitutes for highly reinforcing food.', 'armGroupLabels': ['Episodic Future Thinking (EFT)']}, {'name': 'Daily Check in', 'type': 'BEHAVIORAL', 'otherNames': ['DCI'], 'description': 'Participants will be asked to access the electronic app at the same rate as the experimental group (e.g. daily). Participants will receive behavioral weight loss treatment including The Traffic Light Diet, The Traffic Light Activity Program, and a variety of behavioral techniques including stimulus control, self-monitoring, goal setting, problem solving, and finding behavioral substitutes for highly reinforcing food.', 'armGroupLabels': ['Daily Check in (DCI)']}]}, 'contactsLocationsModule': {'locations': [{'zip': '14214', 'city': 'Buffalo', 'state': 'New York', 'country': 'United States', 'facility': 'University at Buffalo, Department of Pediatrics, Division of Behavioral Medicine', 'geoPoint': {'lat': 42.88645, 'lon': -78.87837}}, {'zip': '24016', 'city': 'Roanoke', 'state': 'Virginia', 'country': 'United States', 'facility': 'Fralin Biomedical Research Institute, Virginia Tech Carilion', 'geoPoint': {'lat': 37.27097, 'lon': -79.94143}}], 'overallOfficials': [{'name': 'Leonard H Epstein, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'State University of New York at Buffalo'}, {'name': 'Warren K Bickel, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Virginia Polytechnic Institute and State University'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'State University of New York at Buffalo', 'class': 'OTHER'}, 'collaborators': [{'name': 'Virginia Polytechnic Institute and State University', 'class': 'OTHER'}, {'name': 'National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)', 'class': 'NIH'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Leonard Epstein', 'investigatorAffiliation': 'State University of New York at Buffalo'}}}}