Effect of obesity on cognition in adults with and without a mood disorder: study design and methods
Bibliographic record
Abstract
INTRODUCTION: Obesity is a common medical illness that is increasingly recognised as conferring risk of decline in cognitive performance, independent of other comorbid medical conditions. Individuals with mood disorders (bipolar disorder (BD) or major depressive disorder (MDD)) display an increased prevalence of both obesity and risk factors for cardiovascular diseases. Moreover, BD and MDD are associated with impairment in cognitive functioning across multiple domains. The independent contribution of obesity to cognitive decline in this population has not been explored. This study examines the impact of obesity on cognition by comparing neuropsychological performance in obese individuals, with or without a mood disorder before and after undergoing bariatric surgery. METHODS AND ANALYSIS: This study compares measures of declarative memory, executive functioning and attention in obese individuals (body mass index >35 kg/m(2)) with BD or MDD, and 2 control populations (obese individuals without a psychiatric illness and healthy non-obese controls) prior to and following bariatric surgery. Participants (ages 18-60) receive a psychiatric diagnosis via the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; SCID). Mood ratings, physical measurements, nutritional and health questionnaires are also administered. A standardised battery of neuropsychological tests aimed at establishing performance in areas of declarative memory, executive functioning and attention are administered. Warrington's Recognition Memory Task (RMT) and an N-Back Task are performed in a 3 T functional MRI to investigate patterns of neural activation during cognitive performance. Additionally, anatomical MRI data are obtained to investigate potential changes in neural structures. Baseline data will be analysed for between-group differences and later compared with postsurgical data to investigate cognitive change. ETHICS AND DISSEMINATION: This study has been approved by the Hamilton Integrated Research Ethics Board (09-3254). Results will be available in peer-reviewed scientific publications and scientific meetings presentations, and released in lay form to media.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".