Evidence map›Paper›PMID 28246068›Full record

ArticleJournal of medical Internet research2017

Issues for eHealth in Psychiatry: Results of an Expert Survey.

Jennifer Nicholas, Kit Huckvale, Mark Erik Larsen, Ashna Basu, Philip J Batterham, Frances Shaw, Shahbaz Sendi

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Internet-Delivered Cognitive Behavioral Therapy for Anxiety.Advances in psychiatry and behavioral health · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Connected Mental Health: Systematic Mapping Study.Journal of medical Internet research · 2020
    Review
  15. Review
  16. Article
  17. Toward Impactful Collaborations on Computing and Mental Health.Journal of medical Internet research · 2018
    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

7 authors.

Jennifer NicholasBlack Dog Institute, University of New South Wales Australia, Sydney, Australia.ORCID 0000-0003-1889-1107
Kit HuckvaleBlack Dog Institute, University of New South Wales Australia, Sydney, Australia.ORCID 0000-0001-9088-6682
Mark Erik LarsenBlack Dog Institute, University of New South Wales Australia, Sydney, Australia.ORCID 0000-0002-0272-2053
Ashna BasuSchool of Psychiatry, University of New South Wales Australia, Sydney, Australia.ORCID 0000-0002-6422-7576
Philip J BatterhamCentre for Mental Health Research, Australian National University, Canberra, Australia.ORCID 0000-0002-4547-6876
Frances ShawBlack Dog Institute, University of New South Wales Australia, Sydney, Australia.ORCID 0000-0001-8690-653X
Shahbaz SendiAffective Disorders Research Group, Center for Affective Disorders, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID 0000-0003-2115-436X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTechnology has changed the landscape in which psychiatry operates. Effective, evidence-based treatments for mental health care are now available at the fingertips of anyone with Internet access. However, technological solutions for mental health are not necessarily sought by consumers nor recommended by clinicians.

objectiveThe objectives of this study are to identify and discuss the barriers to introducing eHealth technology-supported interventions within mental health.

methodsAn interactive polling tool was used to ask "In this brave new world, what are the key issues that need to be addressed to improve mental health (using technology)?" Respondents were the multidisciplinary attendees of the "Humans and Machines: A Quest for Better Mental Health" conference, held in Sydney, Australia, in 2016. Responses were categorized into 10 key issues using team-based qualitative analysis.

resultsA total of 155 responses to the question were received from 66 audience members. Responses were categorized into 10 issues and ordered by importance: access to care, integration and collaboration, education and awareness, mental health stigma, data privacy, trust, understanding and assessment of mental health, government and policy, optimal design, and engagement. In this paper, each of the 10 issues are outlined, and potential solutions are discussed. Many of the issues were interrelated, having implications for other key areas identified.

conclusionsAs many of the issues identified directly related to barriers to care, priority should be given to addressing these issues that are common across mental health delivery. Despite new challenges raised by technology, technology-supported mental health interventions represent a tremendous opportunity to address in a timely way these major concerns and improve the receipt of effective, evidence-based therapy by those in need.

Indexed as

InternetData CollectionHumansPsychiatrySurveys and QuestionnairesTelemedicineeHealthmental healthtechnology adoption

Identifiers

PMID28246068
PMCPMC5350456

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.