Evidence map›Paper›PMID 26679295›Full record

ArticleJMIR research protocols2015

The Feasibility, Acceptability, and Efficacy of Delivering Internet-Based Self-Help and Guided Self-Help Interventions for Generalized Anxiety Disorder to Indian University Students: Design of a Randomized Controlled Trial.

Nitya Kanuri, Michelle G Newman, Josef I Ruzek, Eric Kuhn, M Manjula, Megan Jones, Neil Thomas, Jo-Anne M Abbott, Smita Sharma, C Barr Taylor

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02410265 (Using Technology to Address Anxiety and Stress in Indian University Students), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
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.

NCT02410265 nacompletednot on this map

Using Technology to Address Anxiety and Stress in Indian University Students

TypeinterventionalSponsorStanford UniversityRan2015 to 2016Enrolled193ConditionsAnxiety DisordersArmsLantern: Guided self-help program, Mental Health Online: Self-help program
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
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

10 authors at 6 institutions in 3 countries.

Nitya KanuriBehavioral Medicine Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States. nkanuri@stanford.edu.ORCID http://orcid.org/0000-0002-8708-4352
Palo Alto University · USSwinburne University of Technology · AUVA Palo Alto Health Care System · USBirla Institute of Technology and Science - Hyderabad Campus · INNational Institute of Mental Health and Neurosciences · INPennsylvania State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGeneralized anxiety disorder (GAD) is one of the most common mental disorders among university students; however, many students go untreated due to treatment costs, stigma concerns, and limited access to trained mental health professionals. These barriers are heightened in universities in India, where there are scant mental health care services and severe stigma surrounding help seeking.

objectiveTo evaluate the feasibility, acceptability, and efficacy of Internet-based, or "online," cognitive behavioral therapy (CBT)-based unguided and guided self-help interventions (using the programs GAD Online and Lantern, respectively) to reduce GAD symptoms in students with clinical and subthreshold GAD and, ultimately, reduce the prevalence and incidence of GAD among the student population.

methodsStudents will be recruited via 3 colleges in Hyderabad, India, and referred for a campus-wide online screening. Self-report data will be collected entirely online. A total of 300 qualifying students will be randomized in a 1:1:1 ratio to receive GAD Online, Lantern, or to be in a wait-list control condition, stratified by clinical and subthreshold GAD symptomatology. Students will complete a postintervention assessment after 3 months and a follow-up assessment 6 months later, at which point students in the wait-list control condition will receive one of the programs. The primary outcome is GAD symptom severity at 3 months postintervention. Secondary outcomes include GAD caseness at 9 months, other anxiety and depression symptoms, self-efficacy, and functional measures (eg, sleep, social functioning) at 3 and 9 months, respectively. Primary analyses will be differences between each of the intervention groups and the wait-list control group, analyzed on an intention-to-treat (ITT) basis using mixed-design ANOVA.

resultsThe study commenced in February 2015. The sample was recruited over a 3-week period at each college. The trial is expected to end in December 2015.

conclusionsThis trial will be the first to evaluate the use of Internet-based CBT programs compared with a wait-list control group for the treatment of GAD among students in Indian universities. If effective, these programs have the potential to reduce the mental health care treatment gap by providing readily accessible, private, and cost-effective evidence-based care to students with GAD who do not currently receive the treatment they need.

trial registrationClinicalTrials.gov NCT02410265 http://clinicaltrials.gov/ct2/show/NCT02410265 (Archived by WebCite at http://www.webcitation.org/6ddqH6Rbt).

Indexed as

college health screeningguided self-helpInternet-delivered cognitive behavioral therapy (iCBT), generalized anxiety disorderlow- and middle-income countriesquality of liferandomized controlled trial

Identifiers

PMID26679295
PMCPMC4704912
OpenAlexW2190289261

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.