Examining the moderating effects of biopsychosocial factors on the relationship between HIV-related depression and cognitive function among adolescents living with HIV in Tanzania: A protocol for an analytical cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Adolescents living with HIV face unique challenges, including mental health issues such as depression and cognitive dysfunction. Despite this significant burden, there is a lack of evidence focusing on this population. This study therefore aims to examine the moderating effects of biopsychosocial factors on the bi-directional relationship between HIV-related depression and cognitive function among adolescents living with HIV in the Mbeya region, Tanzania. METHODS: The analytical cross-sectional study will be conducted in public healthcare facilities in the Mbeya region, involving 207 adolescents living with HIV who will be selected using a systematic random sampling technique. Depression will be assessed using a standardized PHQ-9 tool, while cognitive functioning will be evaluated using a validated Montreal Cognitive Assessment Tool Version 8.3. A biopsychosocial model will be used to guide this study. Descriptive statistics will be used to describe the frequency distribution of the study variables, a chi-square test will be used to describe the relationship between the variables and a binary logistic regression model will be used to predict the moderating effects of biopsychosocial factors on the relationship between HIV-related depression and cognitive function. The odds ratio and a 95% confidence interval will be reported, and the p-value of 0.05 will be considered statistical significance. This study is expected to be conducted for three months. The high prevalence of mental health issues among HIV-positive adolescents, the detrimental effect of HIV on cognitive development, and the lack of studies focused on this population raised the need to conduct this study. DISCUSSION: The findings of this study will inform the development of a comprehensive integrated care model that addresses both the mental and cognitive aspects of living with HIV during adolescence. Moreover, the identification of factors associated with depression and cognitive performance will help healthcare providers in identifying at-risk adolescents and proper management of the conditions. This study's results will also help reveal areas that need in-depth exploration that will lead to a better understanding of the responsible factors.
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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 | 0.033 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".