Coping Resources for Persons With Traumatic Spinal Cord Injury in A Tanzania Rural Area
Bibliographic record
Abstract
BACKGROUND: Persons with traumatic spinal cord injury (TSCI) in Tanzanian rural settings face a variety of geographical and socioeconomic challenges that make life almost impossible for them. However, some have managed to live relatively long lives despite these difficult conditions. This study aimed at exploring secrets behind successful lives of persons with TSCI in typical resource-constrained rural Tanzanian settings.METHODS: A modified constructivist grounded theory was employed for the analysis of data from 10 individuals who have lived between 7 and 28 years with TSCI in typical Tanzanian rural area. The 10 were purposively selected from 15 interviews that were conducted in 2011. The analysis followed the constructivist approach in which data was first open and axial coded, prior to categories being constructed. The categories were frequently reviewed in light of the available literature to determine the over-arching core category that described or connected the rest.RESULTS: Nine categories (identified as internal and external coping resources) were constructed. The internal coping resources were: secured in God, increase in awareness on health risk, problem-solving skills and social skills. External coping resources were: having a reliable family, varying support from the community, a matter of possession and left without means for mobility. Acceptance was later identified as a core category that determines identification and utilization of the rest of the coping resources.CONCLUSION: Persons with traumatic spinal cord injury can survive for a relatively long time despite the hostile environment. Coping with these environments requires the employment of various coping resources, acceptance being the most important.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".