Evidence map›Paper›PMID 26188164›Full record

ReviewContemporary clinical trials2015

Crowdsourcing for conducting randomized trials of internet delivered interventions in people with serious mental illness: A systematic review.

John A Naslund, Kelly A Aschbrenner, Lisa A Marsch, Gregory J McHugo, Stephen J Bartels

Abstract readReview
In one paragraph

Review in Contemporary clinical trials, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 4 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

13 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Trial
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

5 authors.

John A NaslundThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States; Dartmouth Centers for Health and Aging, Lebanon, NH, United States. Electronic address: john.a.naslund@dartmouth.edu.
Kelly A AschbrennerThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States; Dartmouth Centers for Health and Aging, Lebanon, NH, United States; Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States.
Lisa A MarschDepartment of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States; The Center for Technology and Behavioral Health, Dartmouth College, Lebanon, NH, United States; Psychiatric Research Center, Dartmouth College, Lebanon, NH, United States.
Gregory J McHugoDepartment of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States; Psychiatric Research Center, Dartmouth College, Lebanon, NH, United States.
Stephen J BartelsThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States; Dartmouth Centers for Health and Aging, Lebanon, NH, United States; Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States; Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States.

Funding

Health Promotion and Disease Prevention Research CenterU48DP005018 · DP · DARTMOUTH COLLEGE · PI ADACHI-MEJIA, ANNA MARIA · 2014 to 2018
$5.6M
Self-Management Training and Automated Telehealth to Improve SMI Health OutcomesR01MH104555 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI BARTELS, STEPHEN J · 2014 to 2018
$3.0M
ACL HHS U48DP005018NCCDPHP CDC HHS U48 DP005018NIMH NIH HHS R01 MH104555
6 · The paper itself

Abstract

objectiveOnline crowdsourcing refers to the process of obtaining needed services, ideas, or content by soliciting contributions from a large group of people over the Internet. We examined the potential for using online crowdsourcing methods for conducting behavioral health intervention research among people with serious mental illness (SMI).

methodsSystematic review of randomized trials using online crowdsourcing methods for recruitment, intervention delivery, and data collection in people with SMI, including schizophrenia spectrum disorders and mood disorders. Included studies were completed entirely over the Internet without any face-to-face contact between participants and researchers. DATABASES AND SOURCES: Medline, Cochrane Library, Web of Science, CINAHL, Scopus, PsychINFO, Google Scholar, and reference lists of relevant articles.

resultsWe identified 7 randomized trials that enrolled N=1214 participants (range: 39 to 419) with SMI. Participants were mostly female (72%) and had mood disorders (94%). Attrition ranged from 14% to 81%. Three studies had attrition rates below 25%. Most interventions were adapted from existing evidence-based programs, and consisted of self-directed education, psychoeducation, self-help, and illness self-management. Six studies collected self-reported mental health symptoms, quality of life, and illness severity. Three studies supported intervention effectiveness and two studies showed improvements in the intervention and comparison conditions over time. Peer support emerged as an important component of several interventions. Overall, studies were of medium to high methodological quality.

conclusionOnline crowdsourcing methods appear feasible for conducting intervention research in people with SMI. Future efforts are needed to improve retention rates, collect objective outcome measures, and reach a broader demographic.

Indexed as

CrowdsourcingInterventionMental healthMobile healthOnlineSerious mental illness

Identifiers

PMID26188164
PMCPMC4715791

What OpenQuestion holds

Textmetadata
LicenceTDM
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.