A Systematic Review of Practice Standards and Research Ethics in Technology-Based Home Health Care Intervention Programs for Older Adults
Bibliographic record
Abstract
OBJECTIVE: The purpose of the review is to assess frequencies of reporting adherence to professional practice standards and research ethics in studies of technology-based home health care programs. METHODS: Key databases were searched to yield 2,866 abstracts that were independently rated by two reviewers using inclusion-exclusion criteria, resulting in 107 articles that were then reviewed for reports of practice standards and research ethics. RESULTS: Issues related to professional practice standards and research ethics were not well reported. When reported, adherence to practice standards included preintervention training, use of intervention protocols, supervision, and mechanisms for risk management. Research ethics most commonly reported were informed consent, REB/IRB approval, and protection of privacy. DISCUSSION: The results raise questions as to whether practice standards and research ethics are addressed sufficiently when health service delivery occurs in technology-based environments. Guidelines for professional accountability in e-health service delivery are needed.
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 | 0.167 | 0.467 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| 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".