The effectiveness of telemedicine on stigmatization and treatment burden in patients with health compromising lifestyles and chronic diseases: A critically appraised topic
Bibliographic record
Abstract
Objectives: To conduct a critical appraisal of peer reviewed articles on the effectiveness of telemedicine on stigmatization and treatment burden in patients with health compromising lifestyles and chronic diseases.Methods: This study critically appraised peer-reviewed article on the effectiveness of telemedicine on stigmatization and treatment burden in patients with health compromising lifestyles and chronic diseases. Treatments included e-health interventions, information and communication technologies used in health care, internet-based interventions for diagnosis and treatments that encouraged collaborative care for patients with chronic diseases. This paper critically appraised the full text of each relevant peer-reviewed article adapting the Occupational Therapy Critically Appraised Topics (CATs) template while using the Oxford Centre for Evidence-based Medicine- Levels of Evidence (2011) model to assess for best evidence or quality. Results: Initial internet search using Psychinformation; PubMed; Medline; ProQuest; CINAHL; OT seeker and the Cochrane Library generated over 1450 titles/abstracts. Following abstract appraisal, 30 articles were selected for full text assessment. Five of the final articles selected for this critical appraisal alluded to the effectiveness of telemedicine in reducing the treatment burden of stigmatization on patients with chronic diseases. Majority of the appraised articles indicated the effectiveness of telemedicine in changing behaviours.Conclusions: All the appraised articles alluded to the effectiveness of telemedicine in curbing some of the treatment burdens of stigmatization for patients with health compromising lifestyles and chronic diseases. However, it is evident that the use of other intervention methods such as government policy, public education and patient empowerment in conjunction with telemedicine would better reduce the effect of stigmatization and facilitate the medical interventions for patients with chronic diseases.
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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 | 0.077 | 0.371 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".