Evidence map›Paper›PMID 30855234›Full record

Trial reportJournal of medical Internet research2019

The Impact of Superfast Broadband, Tailored Booklets for Households, and Discussions With General Practitioners on Personal Electronic Health Readiness: Cluster Factorial Quasi-Randomized Control Trial.

Philip Abbott-Garner, Janet Richardson, Ray B Jones

2 registry-linked trialsAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

NCT00102401 nacompletednot on this map

Comparing the Effects of an Internet-Based to an Established Dyspnea Self-Management Program on Dyspnea, Exercise Behavior, and Pulmonary Exacerbations in Patients With COPD

TypeinterventionalSponsorRobert Wood Johnson FoundationRan2003 to 2007Enrolled50ConditionsChronic Obstructive Pulmonary DiseaseArmsInternet-based Dyspnea Self-Management Program, Face-to-face Dyspnea Self-Management Program
NCT02355808 naunknown statusnot on this map

Do Superfast Broadband and Tailored Interventions Improve Use of E-health and Reduce Health Related Travel?

TypeinterventionalSponsorUniversity of PlymouthRan2012 to 2015Enrolled1,044ConditionseHealthArmsTailored Leaflet, GP visit
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Philip Abbott-GarnerSchool of Nursing and Midwifery, University of Plymouth, Plymouth, United Kingdom.ORCID 0000-0003-4834-0859
Janet RichardsonSchool of Nursing and Midwifery, University of Plymouth, Plymouth, United Kingdom.ORCID 0000-0002-4759-9722
Ray B JonesSchool of Nursing and Midwifery, University of Plymouth, Plymouth, United Kingdom.ORCID 0000-0002-2963-3421

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic health (eHealth) may improve health outcomes, but many people remain digitally excluded. Personal readiness to use the internet for health may be limited by lack of internet infrastructure, personal skills, social support, service provision, and cost. The impact of interventions to reduce these barriers is unknown. From 2011, the British Government supported the implementation of "superfast" broadband (Superfast) across the rural county of Cornwall. This provided the opportunity to assess the impact of interventions at regional, practice, and household levels.

objectiveThis study aimed to assess the impact of 3 interventions on personal eHealth readiness: (1) regional-level implementation of Superfast, (2) practice-level discussions with general practitioners to encourage greater internet use in health service provision, and (3) household-level tailored booklets providing information to help improve personal skills in eHealth.

methodsThis was a cluster quasi-randomized factorial controlled trial. Implementation of Superfast was monitored, and postcodes were classified as having early or late availability. An algorithm selected 78 from 16,385 eligible postcodes to minimize the possibility of overlap between general practices and ensure a balance of urban and rural areas; 1388 households were randomly selected from the 78 postcodes and allocated to the 8 (2 × 2 × 2) study arms. A modified version of the Personal eHealth Readiness Questionnaire was used to compare scores (0 to 10) and 4 components (personal, provision, support, and economic) from baseline (August 2013) to the 18-month follow-up between the 8 arms, to assess the impact of interventions. We compared SDs of scores to assess changes in eHealth inequalities.

resultseHealth readiness improved over 18 months from 4.36 out of 10 to 4.59 out of 10 (t

conclusionsPeople in Cornwall became more ready to adopt eHealth services, increasing both their personal ability to use eHealth and their methods of access. The implementation of Superfast may have contributed to this; we are certain that our other 2 interventions did not. This increased eHealth readiness did not cause a larger digital divide. The study illustrates the complexity of conducting a randomized controlled trial to assess the impact of interventions at regional, practice, and household levels. Our method may be of use to others.

trial registrationClinicalTrials.gov NCT00102401; https://clinicaltrials.gov/ct2/show/NCT02355808 (Archived by WebCite at http://www.webcitation.org/75oEz0E1x).

Indexed as

FemaleGeneral PractitionersHumansInternetMaleMiddle AgedPamphletsResearch DesignSocial SupportSurveys and QuestionnairesTelemedicinebroadband implementationcluster trialdigital divideeHealtheHealth inequalitieseHealth readinessrandomized controlled trialtailored booklet

Identifiers

PMID30855234
PMCPMC6431827

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.