Emotional reaction to pain as predictor of depression among selected Nigerians living with sickle cell disease in Ile-Ife
Bibliographic record
Abstract
This study examined the predictive role of emotional reaction to pain on depression and investigated if there are significant age differences in depression among people living with sickle cell disease. A cross-sectional design carried out at Obafemi Awolowo University Health Centre (OAUHC) in Osun State, Nigeria, was conveniently used to select 71 respondents (females = 70.4%), with a median age of 19 years (SD = 5.94). Beck Depression Inventory (BDI) and Short-Form McGill Pain Questionnaire (SF-MPQ) were used to collect data from the respondents from 11 January to 15 February 2019. Simple linear regression analysis revealed that emotional reaction to pain significantly predicts depression among individuals living with sickle cell disease (R2 = 0.16, F(1, 69) = 16.70, p < .05)). One-way ANOVA results also showed a significant influence of age on depression (F(2, 68) = 4.439; p <.05)). The study concluded that emotional reaction to pain and age play significant roles in depression among people living with sickle cell disease in the study setting.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".