The law of attrition
Clicks: 614
ID: 114240
2005
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Steady Performance
30.0
/100
613 views
374 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
In an ongoing effort of this Journal to develop and further the theories, models, and best practices around eHealth research, this paper argues for the need for a "science of attrition", that is, a need to develop models for discontinuation of eHealth applications and the related phenomenon of parti …
Abstract Quality Issue:
This abstract appears to be incomplete or contains metadata (49 words).
Try re-searching for a better abstract.
| Reference Key |
g2005journalthe
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Eysenbach G;; |
| Journal | Journal of medical Internet research |
| Year | 2005 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
National Center for Biotechnology Information
NCBI
NLM
MEDLINE
medical informatics
humans
pubmed abstract
nih
national institutes of health
national library of medicine
patient dropouts
delivery of health care / organization & administration
pmid:15829473
pmc1550631
doi:10.2196/jmir.7.1.e11
gunther eysenbach
health services research* / statistics & numerical data
internet / statistics & numerical data*
medical informatics applications*
|
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.