ArticleJournal of medical Internet research2005
Reducing the cancer burden of lifestyle factors: opportunities and challenges of the Internet.
Article in Journal of medical Internet research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 34 citations in OpenAlex.
- Baseline Characteristics and Generalizability of Participants in an Internet Smoking Cessation Randomized Trial.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2016Trial
- Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol.BMJ open · 2016Trial
- Reliability of internet- versus telephone-administered questionnaires in a diverse sample of smokers.Journal of medical Internet research · 2008Trial
- Internet-based self-help smoking cessation and alcohol moderation interventions for cancer survivors: a study protocol of two RCTs.BMC cancer · 2018Article
- Enhancing skin cancer screening through behavioral intervention.JAMA dermatology · 2014Article
- Online social networks and smoking cessation: a scientific research agenda.Journal of medical Internet research · 2011Article
- Boosting population quits through evidence-based cessation treatment and policy.American journal of preventive medicine · 2010Article
- Critical issues in eHealth research.American journal of preventive medicine · 2007Article
- Characterizing Internet searchers of smoking cessation information.Journal of medical Internet research · 2006Article
- Creating a framework for online cancer services research to facilitate timely and interdisciplinary applications.Journal of medical Internet research · 2005Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
This paper focuses on the Internet as a tool for enhancing behavior and lifestyle changes to reduce the burden of cancer at a population level. The premise of this paper is that the Internet can and should be leveraged to bridge the chasm between basic science, clinical trials, and public health. Our focus is specifically on the opportunity to disseminate effective behavioral science interventions via the Internet in order to decrease the prevalence of behavioral risk factors for cancer. The examples herein are primarily drawn from tobacco use to illustrate issues that can be applied more generally to other behavioral risk factors for cancer. Four areas will be addressed: (1) the scientific basis and rationale for delivering lifestyle behavior change interventions via the Internet; (2) the need to determine the quality of Internet interventions; (3) methodological considerations in conducting evaluations of Internet interventions; and (4) recommendations for a transdisciplinary approach to Internet intervention development and evaluation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.