Modifiable Sociostructural and Environmental Factors That Impact the Health and Quality of Life of People With Spinal Cord Injury: A Scoping Review
Bibliographic record
Abstract
Objective: The objective of this scoping review was to identify the modifiable factors that impact the health and quality of life (QOL) of community-dwelling people with spinal cord injury (SCI). Methods: Empirical journal articles were identified using three academic databases: CINAHL Complete, MEDLINE with Full Text, and PsycINFO. Full-text journal articlesincluded studies of participants who were community-dwelling with traumatic or nontraumatic SCI and were over the age of 18 years without cognitive impairment; published between 2000 and 2021; focused on modifiable factors impacting health and QOL; and conducted inAustralia, Europe, orNorth America. A data table was used to extract article information including authors, year of publication, country, sample, design and methods, purpose/objectives, and main findings. Qualitative data analysis software was used to categorize major findings inductively through content analysis. Results: Thirty-one peer-reviewed articles consisting of qualitive, quantitative, and mixed-methods study design were included. This scoping review revealed modifiable factors that impact the health and QOL of community-dwelling people with SCI: sociostructural factors (social attitudes, health care access, information access, and funding and policies) and environmental factors (built environment, housing, transportation, assistive technology, and natural environment). Conclusion: Future research should examine the influence of the modifiable factors on health and QOL using qualitative inquiry, adopting a community-based participatory research approach, and considering the implications of individual characteristics and resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".