Evidence map›Paper›PMID 36995752›Full record

ArticleJMIR mental health2023

The Effectiveness of a Smartphone Intervention Targeting Suicidal Ideation in Young Adults: Randomized Controlled Trial Examining the Influence of Loneliness.

Lauren McGillivray, Nicholas Keng-Meng Hui, Quincy J J Wong, Jin Han, Jiahui Qian, Michelle Torok

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 28% 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.

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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Review
  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

6 authors at 3 institutions in 1 country.

Lauren McGillivray *Black Dog Institute, University of New South Wales, Sydney, Australia.ORCID 0000-0001-9022-0274
Nicholas Keng-Meng Hui *Faculty of Medicine and Health, University of New South Wales, Sydney, Australia.ORCID 0009-0000-2004-2193
Quincy J J WongSchool of Psychology, Western Sydney University, Sydney, Australia.ORCID 0000-0001-9393-4301
Jin HanBlack Dog Institute, University of New South Wales, Sydney, Australia.ORCID 0000-0001-7624-9468
Jiahui QianBlack Dog Institute, University of New South Wales, Sydney, Australia.ORCID 0000-0002-5173-5707
Michelle TorokBlack Dog Institute, University of New South Wales, Sydney, Australia.ORCID 0000-0003-3741-8075
Black Dog Institute · AUUNSW Sydney · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLoneliness is commonly reported by young people and has been shown to contribute to the rapid onset and escalation of depression and suicidal ideation during adolescence. Lonely people may also be particularly susceptible to disengaging from treatment early given the likelihood of their more complex clinical profiles leading to cognitive fatigue. While a smartphone intervention (LifeBuoy) has been shown to effectively reduce suicidal ideation in young adults, poor engagement is a well-documented issue for this therapeutic modality and has been shown to result in poorer treatment outcomes.

objectiveThis study aims to determine whether loneliness affects how young people experiencing suicidal ideation engage with and benefit from a therapeutic smartphone intervention (LifeBuoy).

methodsA total of 455 community-based Australian young adults (aged 18-25 years) experiencing recent suicidal ideation were randomized to use a dialectical behavioral therapy-based smartphone intervention (LifeBuoy) or an attention-matched control app (LifeBuoy-C) for 6 weeks. Participants completed measures of suicidal ideation, depression, anxiety, and loneliness at baseline (T0), post intervention (T1), and 3 months post intervention (T2). Piecewise linear mixed models were used to examine whether loneliness levels moderated the effect of LifeBuoy and LifeBuoy-C on suicidal ideation and depression across time (T0 to T1; T1 to T2). This statistical method was then used to examine whether app engagement (number of modules completed) influenced the relationship between baseline loneliness and suicidal ideation and depression across time.

resultsLoneliness was positively associated with higher levels of overall suicidal ideation (B=0.75, 95% CI 0.08-1.42; P=.03) and depression (B=0.88, 95% CI 0.45-1.32; P<.001), regardless of time point or allocated condition. However, loneliness did not affect suicidal ideation scores across time (time 1: B=1.10, 95% CI -0.25 to 2.46; P=.11; time 2: B=0.43, 95% CI -1.25 to 2.12; P=.61) and depression scores across time (time 1: B=0.00, 95% CI -0.67 to 0.66; P=.99; time 2: B=0.41, 95% CI -0.37 to 1.18; P=.30) in either condition. Similarly, engagement with the LifeBuoy app was not found to moderate the impact of loneliness on suicidal ideation (B=0.00, 95% CI -0.17 to 0.18; P=.98) or depression (B=-0.08, 95% CI -0.19 to 0.03; P=.14).

conclusionsLoneliness was not found to affect young adults' engagement with a smartphone intervention (LifeBuoy) nor any clinical benefits derived from the intervention. LifeBuoy, in its current form, can effectively engage and treat individuals regardless of how lonely they may be.

trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12619001671156; https://tinyurl.com/yvpvn5n8. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/23655.

Indexed as

appsdigital therapeuticslonelinesssmartphone interventionsuicidal ideationsuicide prevention

Identifiers

PMID36995752
PMCPMC10131597
OpenAlexW4321635994

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.