Mad Dog Nutrition Program Consult: Effects on Dietary Self-Efficacy, Behaviors and Health Outcomes
Bibliographic record
Abstract
Prior research in our lab has shown the effect of diet in spinal cord injury (SCI) and multiple sclerosis (MS) populations for reducing inflammation and other subsequent negative health outcomes (Allison & Ditor, 2015;Allison et al., 2016).However, adherence to the diet greatly decreased after one year (Allison & Ditor, 2018).The decrease of adherence was attributed to a variety of barriers that were uncovered in interviews (Bailey et al., 2017).The present study investigated the effects of a 2-session dietary consult (the MAD DOG consult) designed towards minimizing identified barriers and improving participant self-efficacy, the likelihood of long-term adherence and selected secondary health complications.Task (p = .028)and barrier self-efficacy (p = .003)were significantly improved directly after the consult.When examined one month after the consult, participants had significant improvements in adherence to the Mad Dog diet (p = .001),reductions in depression (p = .038)and positive trends towards improving bowel general satisfaction (p = .072),task self-efficacy (p = .066)and barrier (p = .094)self-efficacy.Changes in CES-D scores were significantly negatively correlated with dietary adherence (r = -0.61;r 2 = 0.37; p = 0.045), and barrier self-efficacy (r = -0.77;r 2 = 0.59; p = 0.009).There were no significant changes in neuropathic pain or bowel function one month after the consult.Follow-up testing is warranted to determine how long improvements in selfefficacy and adherence to the Mad Dog persist following the consult, as well as improved health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".