Functional Assessment of Currently Employed Technology Scale (FACETS)
Bibliographic record
Abstract
Introduction: Insurers, institutional and independent providers of health care have made increasing use of websites for patient communication, in the absence of data indicating that patients, especially older adults, utilize information technology (IT). The Functional Assessment of Currently Employed Technology Scale (FACETS) was designed to determine patient frequency of internet and IT utilization across age groups. FACETS is a 10-item questionnaire assessing 5 functional domains, with high internal consistency reliability, strong general factor validity, and strong factor validity for the five domains. FACETS data indicate that IT utilization declines significantly with increasing age beyond 60 years. Findings also indicate that people over age 65 are not a homogenous population with regard to IT use, nor is IT use a homogenous category. FACETS demonstrates that use of websites for communicating with older adult populations might create a barrier to access to health care. It is suggested that health care protocols for working with older adults should include internet and IT utilization as a specific area of assessment or treatment.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 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".