The Effects of Positive Affect and Episodic Future Thinking on Temporal Discounting and Healthy Food Demand and Choice Among Overweight and Obese Individuals: Protocol for a Pilot 2×2 Factorial Randomized Controlled Study
Bibliographic record
Abstract
BACKGROUND: Unhealthy behaviors (eg, poor food choices) contribute to obesity and numerous negative health outcomes, including multiple types of cancer and cardiovascular and metabolic diseases. To promote healthy food choice, diet interventions should build on the dual-system model to target the regulation and reward mechanisms that guide eating behavior. Episodic future thinking (EFT) has been shown to strengthen regulation mechanisms by reducing unhealthy food choice and temporal discounting (TD), a process of placing greater value on smaller immediate rewards over larger future rewards. However, these interventions do not target the reward mechanisms that could support healthy eating and strengthen the impact of EFT-anchored programs. Increasing positive affect (PosA) related to healthy food choices may target reward mechanisms by enhancing the rewarding effects of healthy eating. An intervention that increases self-regulation regarding unhealthy foods and the reward value of healthy foods will likely have a greater impact on eating behavior compared with interventions focused on either process alone. OBJECTIVE: This study aimed to introduce a protocol that tests the independent and interactive effects of EFT and PosA on TD, food choice, and food demand in overweight and obese adults. METHODS: This protocol describes a factorial, randomized, controlled pilot study that employs a 2 (affective imagery: positive, neutral) by 2 (EFT: yes, no) design in which participants are randomized to 1 of 4 guided imagery intervention arms. In total, 156 eligible participants will complete 2 lab visits separated by 5 days. At visit 1, participants complete surveys; listen to the audio guided imagery intervention; and complete TD, food demand, and food choice tasks. At visit 2, participants complete TD, food demand, and food choice tasks and surveys. Participants complete a daily food frequency questionnaire between visits 1 and 2. Analyses will compare primary outcome measures at baseline, postintervention, and at follow-up across treatment arms. RESULTS: Funding notification was received on April 27, 2017, and the protocol was approved by the institutional review board on October 6, 2017. Feasibility testing of the protocol was conducted from February 21, 2018, to April 18, 2018, among the first 32 participants. As no major protocol changes were required at the end of the feasibility phase, these 32 participants were included in the target sample of 156 participants. Recruitment, therefore, continued immediately after the feasibility phase. When this manuscript was submitted, 84 participants had completed the protocol. CONCLUSIONS: Our research goal is to develop novel, theory-based interventions to promote and improve healthy decision-making and behaviors. The findings will advance decision-making research and have the potential to generate new neuroscience and psychological research to further understand these mechanisms and their interactions. TRIAL REGISTRATION: ISRCTN Registry ISRCTN11704675; http://www.isrctn.com/ISRCTN11704675 (Archived by WebCite at http://www.webcitation.org/760ouOoKG). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12265.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.053 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".