Exploring Interrelationships between Mental Health Symptoms and Cognitive Impairment in Aging People Living with HIV in China
Bibliographic record
Abstract
INTRODUCTION: Mental health symptoms and cognitive impairment are highly prevalent and intertwined among aging people living with HIV (PLWH). This study aimed to assess the interrelationships and strength of connections between individual mental health symptoms and cognitive impairment. We sought to identify specific symptoms linking mental health and cognitive impairment in aging PLWH. METHODS: Participants in the Sichuan Older People with HIV Infections Cohort Study (SOHICS) were recruited between November 2018 and April 2021 in China. Mental health symptoms, including depression and anxiety, were assessed by the Patient Health Questionnaire (PHQ-9) and General Anxiety Disorder-7 (GAD-7), respectively. Cognitive impairment was assessed by the Montreal Cognitive Assessment-Basic (MoCA-B). Partial correlation networks were used to depict the interrelationships between mental health symptoms and cognitive impairment, and bridge strength was used to identify specific symptoms linking mental health and cognitive impairment. RESULTS: Of the 1,587 recruited participants with a mean age of 63.0 years old, 47.0% had mild or severe cognitive impairment. Network analysis revealed that cognitive function, visual perception, and problem-solving task of the MoCA-B were negatively correlated with appetite, energy, and motor of the PHQ-9, respectively. Based on their interrelationships, problem-solving task and motor acted as bridge symptoms. CONCLUSION: Problem-solving task and motor may be potential intervention targets to reduce the overall risk of mental health symptoms and cognitive impairment. Future research could assess the feasibility and effectiveness of specific interventions designed for the two symptoms of aging PLWH.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".