A qualitative study on the use of personal information technology by persons with spinal cord injury
Bibliographic record
Abstract
PURPOSE: Previous work has shown that information technology (IT), such as personal computers and other digital devices (e.g. tablets, laptops, etc.), software, online resources and hand-held communication tools (e.g. cellphones), has benefits for health and well-being for persons with chronic health conditions. To date, the ways that persons with spinal cord injury (SCI) use IT in their daily activities has not been fully explored. Thus, the purpose of the study was to obtain an in-depth perspective of how people with SCI regularly use IT to gain insight on ways IT can be used to support health and well-being in the community for this population. METHODS: Semi-structured interviews were conducted with community-dwelling persons with SCI (N = 10) who identified themselves as frequent-or-daily-users of IT. Qualitative content analysis was used to identify the ways that persons with SCI use personal IT. RESULTS: Ten themes related to IT use were identified: (1) Modifications allowing access to IT; (2) Convenience of IT and its perceived value; (3) IT as a scheduler/planner; (4) Challenges; (5) Contributions of IT to participation; (6) Access to information; (7) Influence of IT on well-being; (8) IT as a connector; (9) Issues of IT acquisition; and (10) Desires for future devices/technology. CONCLUSIONS: The findings suggest that IT use by people with SCI contributes to general health and well-being, by increasing access to SCI-related health information and opportunity for social participation. Despite the benefits offered by IT, persons with SCI have identified a degree of skepticism about the reliability and applicability of the health information they find online. Future work on developing and implementing IT for health and well-being post-SCI should take into account consumers' perspectives to facilitate uptake. Implications for Rehabilitation There is a need for a more refined understanding of how people with spinal cord injury (SCI) use information technology (IT) in their daily lives in order to understand how IT can support health and well-being post-injury in the community. IT use holds implications for the physical and mental well-being of persons with SCI. IT allows access to a variety of information, and facilitates participation in the community. The enthusiasm for the use of IT is tempered by a degree of skepticism about the reliability and applicability of the health information available online. This highlights the need to raise awareness of existing sources vetted for this population, and to develop content that meets the particular health needs for SCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".