the Relationship Between Executive Function and Diet Adherence in Patients With Type 2 Diabetes Mellitus
Study Details
Study Description
Brief Summary
Research Objectives This study aims to investigate the relationship between executive function and diet adherence in patients with type 2 diabetes mellitus (T2DM) from both subjective and objective perspectives and to clarify the effect of executive function intervention of inhibitory control training based on computer on diet adherence.
Research design This study includes three parts. In Part 1, the subjective measurement (questionnaire) and objective measurement (cognitive task performance) are combined to comprehensively explore the relationship between executive function and diet adherence in patients with type 2 diabetes. In the second part, ERP technology is used to investigate the neural mechanism of inhibitory control in type 2 diabetic patients with different diet adherence. Part III is a randomized controlled trial. The control group adopts non-food-related inhibitory control training, and the experimental group adopts food-related inhibitory control training.
Participants The inclusion criteria were as follows: T2DM patients who (1) have met the 1999 WHO diagnostic criteria for diabetes; (2) have a course of disease ≥6 months; (3) have an age ≥18 years old; (4) have good verbal communication and understanding skills; (5) have normal vision or corrected vision, no color blindness or color asthenia; (6) have normal finger function and ability to do key reactions; (7) have a MoCA score ≥25; and (8) have given informed consent and were willing to participate in the study. Patients who (1) have a history of cerebrovascular disease or other central nervous system injury and (2) have difficulty completing the questionnaire or the computer-based cognitive measurement tasks were excluded.
Sampling method and sample size In Part 1, convenience sampling method is used, and the sample size is calculated according to 10-15 times of the research indicators. A total of 23 research indicators were included in the analysis of this study, and at least 230 are needed. Considering the loss rate of 20%, a total of 276 subjects are needed. In the second part, convenience sampling method is also used. According to the literature reviewed, the effect size was 0.93, taking α=0.05, β=0.80, and the sample size was 40 cases calculated by GPower3.1.9.7 software. The sample size is increased by 20% considering the withdrawal of participants and sample loss. Finally, the sample size n1 (number of patients with high diet compliance) =n2 (number of patients with low diet compliance) =50 cases. In Part III, the convenience sampling method is used. The sample size was determined as 60 cases by referring to previous studies. Patients with type 2 diabetes who meet the inclusion criteria are numbered from 1 to 60. Starting from any row or column in the random number table, two digits are read in turn as a random number under the number, and then all the random numbers are sequenced from small to large. This study is a single-blind trial, and only the investigators themselves are aware of the group assignment, and the subjects are unaware of the group assignment.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
In Part 1, the Dietary Behavior Adherence Scale for Patients with Type 2 Diabetes Mellitus is used to measure participants' dietary adherence; the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) is used to subjectively measure participants' executive function; Stop signal task (SST) and Stroop task are used objectively measure participants' executive function. In the second part, ERP technology is used to investigate the neural mechanism of executive function in type 2 diabetic patients with different diet adherence. Part III is a randomized controlled trial. The control group adopts non-food-related inhibitory control training, and the experimental group adopts food-related inhibitory control training. Both training tasks are computer-based, with participants performing a simple keypress response.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: experimental group
|
Behavioral: Food-related inhibitory control training based on computer
Inhibitory control training tasks are performed using E-Prime 3.0 software to present stimuli based on computer. The Go/no-go task is used as the training task, and the stimulus materials are high-calorie and low-calorie food pictures. The training lasted for 5 days, once a day, and the total duration of each training is about 15 minutes.
|
| Placebo Comparator: control group
|
Behavioral: Non-food-related inhibitory control training based on computer
Inhibitory control training tasks are performed using E-Prime 3.0 software to present stimuli based on computer. The Go/no-go task is used as the training task, and the stimulus materials are non-food pictures. The training lasted for 5 days, once a day, and the total duration of each training is about 15 minutes.
|
Outcome Measures
Primary Outcome Measures
- diet adherence [before the intervention]
The scores of The Dietary Behavior Adherence Scale for Patients with Type 2 Diabetes Mellitus are reported, the minimum and maximum values are 23 and 115, respectively. And higher scores mean a better outcome.
- diet adherence [one month after the intervention]
The scores of The Dietary Behavior Adherence Scale for Patients with Type 2 Diabetes Mellitus are reported, the minimum and maximum values are 23 and 115, respectively. And higher scores mean a better outcome.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Clinical diagnosis of Type 2 Diabetes Mellitus
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Must have a course of disease ≥6 months
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Must have an age ≥18 years old
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Must have good verbal communication and understanding skills
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Must have normal vision or corrected vision, no color blindness or color asthenia
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Must have normal finger function and ability to do key reactions
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Must have a Montreal Cognitive Assessment (MoCA) score ≥25
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Must have given informed consent and were willing to participate in the study.
Exclusion Criteria:
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Have a history of cerebrovascular disease or other central nervous system injury
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Have difficulty completing the questionnaire or the computer-based cognitive measurement tasks
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Na Liu
Investigators
- Principal Investigator: Na Liu, Air Force Medical University
Study Documents (Full-Text)
None provided.More Information
Publications
- Adams RC, Button KS, Hickey L, Morrison S, Smith A, Bolus W, Coombs E, Randolph S, Hunt R, Kim D, Chambers CD, Lawrence NS. Food-related inhibitory control training reduces food liking but not snacking frequency or weight in a large healthy adult sample. Appetite. 2021 Dec 1;167:105601. doi: 10.1016/j.appet.2021.105601. Epub 2021 Jul 17.
- Ganor-Moscovitz N, Weinbach N, Canetti L, Kalanthroff E. The effect of food-related stimuli on inhibition in high vs. low restrained eaters. Appetite. 2018 Dec 1;131:53-58. doi: 10.1016/j.appet.2018.08.037. Epub 2018 Aug 31.
- Hagen E, Erga AH, Hagen KP, Nesvag SM, McKay JR, Lundervold AJ, Walderhaug E. Assessment of Executive Function in Patients With Substance Use Disorder: A Comparison of Inventory- and Performance-Based Assessment. J Subst Abuse Treat. 2016 Jul;66:1-8. doi: 10.1016/j.jsat.2016.02.010. Epub 2016 Mar 9.
- Liu Y, Yu D, Luo J, Cai S, Ye P, Yao Z, Luo M, Zhao L. Self-Reported Dietary Management Behaviors and Dietary Intake among Chinese Adults with Diabetes: A Population-Based Study. Nutrients. 2022 Dec 5;14(23):5178. doi: 10.3390/nu14235178.
- Luo X, Gu J, Zheng Y, Zhou X. Making a saccade enhances Stroop and Simon conflict control. Atten Percept Psychophys. 2022 Apr;84(3):795-814. doi: 10.3758/s13414-022-02458-7. Epub 2022 Mar 18.
- Oomen D, Grol M, Spronk D, Booth C, Fox E. Beating uncontrolled eating: Training inhibitory control to reduce food intake and food cue sensitivity. Appetite. 2018 Dec 1;131:73-83. doi: 10.1016/j.appet.2018.09.007. Epub 2018 Sep 10.
- Verbruggen F, Aron AR, Band GP, Beste C, Bissett PG, Brockett AT, Brown JW, Chamberlain SR, Chambers CD, Colonius H, Colzato LS, Corneil BD, Coxon JP, Dupuis A, Eagle DM, Garavan H, Greenhouse I, Heathcote A, Huster RJ, Jahfari S, Kenemans JL, Leunissen I, Li CR, Logan GD, Matzke D, Morein-Zamir S, Murthy A, Pare M, Poldrack RA, Ridderinkhof KR, Robbins TW, Roesch M, Rubia K, Schachar RJ, Schall JD, Stock AK, Swann NC, Thakkar KN, van der Molen MW, Vermeylen L, Vink M, Wessel JR, Whelan R, Zandbelt BB, Boehler CN. A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task. Elife. 2019 Apr 29;8:e46323. doi: 10.7554/eLife.46323.
- Wyckoff EP, Evans BC, Manasse SM, Butryn ML, Forman EM. Executive functioning and dietary intake: Neurocognitive correlates of fruit, vegetable, and saturated fat intake in adults with obesity. Appetite. 2017 Apr 1;111:79-85. doi: 10.1016/j.appet.2016.12.039. Epub 2016 Dec 29.
- Zhang X, Chen S, Chen H, Gu Y, Xu W. General and Food-Specific Inhibitory Control As Moderators of the Effects of the Impulsive Systems on Food Choices. Front Psychol. 2017 May 24;8:802. doi: 10.3389/fpsyg.2017.00802. eCollection 2017.
- K202301-06