The Role of Support and Sustainability Elements in the Adoption of a Self-management Support System for Chronic Illnesses
Bibliographic record
Abstract
The Canadian healthcare system, by design, has been historically oriented to delivering acute and symptom-driven care; however, the current cost of treating chronic disease has risen to an average of nearly 45% of direct costs of the national health budget. As a consequence more attention is being directed to the diagnosis and treatment of chronically ill patients who also may suffer from disabilities, illiteracy, impairment in judgment, depression, or multiple co-morbidities. This has also resulted in a new emphasis on health and disease self-management, to help patients to mitigate and manage the impacts of chronic diseases. This approach affects and involves the patient’s entire circle of care including the patient, healthcare providers, and the patient’s family and friends. This study discusses how support elements (i.e. decision support, education and training, family and community support) and sustainability elements (i.e. recreation and entertainment, rewards systems, online social networks) combined with online technological support can help to support and provide motivation for chronically ill patients to adopt self-management in a sustainable manner. The PLS (Partial Least Squares) statistical approach was used to validate a proposed SEM (Structural Equation Model) research model with data collected from 198 participants across North America without any prior exposure to our proposed system. The research model hypothesized that support and sustainability constructs have a strong positive influence on the willingness of users to adopt and use the proposed system. The model results in a very good fit for Behavioural Intention to Adopt for patients with no caregiver support (R2=0.71), and for patients with such support (R2=0.65). The results clearly validate our proposed model including a high predictive relevance for endogenous variables. This research provides useful theoretical and practical insights and understanding for design, development and promotion of chronic care self-management systems as well as the perceptions of users regarding the adoption and use of such systems.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".