Evidence map›Paper›PMID 22928095›Full record

ArticleDepression research and treatment2012

Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents?

Hans Christian B Vangberg, Kjersti R Lillevoll, Knut Waterloo, Martin Eisemann

Open access · hybridAbstract read
In one paragraph

Article in Depression research and treatment, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. 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

4 authors at 1 institution in 1 country.

Hans Christian B VangbergDepartment of Psychology, University of Tromsø, 9037 Tromsø, Norway.
Kjersti R Lillevoll
Knut Waterloo
Martin Eisemann
UiT The Arctic University of Norway · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background. Focus upon depression and prevention of its occurrence among adolescents is increasing. Novel ways of dealing with this serious problem have become available especially by means of internet-based prevention and treatment programs of depression and anxiety. The use of Internet-based intervention programs among adolescents has revealed some difficulties in implementation that need to be further elucidated. The aim of this study is to investigate the association between personality and adolescent depression and the characteristics of users of an Internet-based intervention program. Method. The Junior Temperament and Character Inventory (JTCI), the General Self-Efficacy scale (GSE) and the Centre for Epidemiological Studies-Depression scale (CES-D) have been administered to a sample (n = 1234) of Norwegian senior high-school students. Results. Multiple regression analysis revealed associations between depression and gender, and several JTCI domains and facets. In line with previous findings in adults, high Harm Avoidance and low Self-Directedness emerged as the strongest predictors of adolescent depressive symptoms. Further, in logistic regression analysis with the covariates JTCI, GSE and CES-D, the only significant variables predicting use/non-use were the CES-D and the temperament domain Reward Dependence. Conclusion. The results in this study revealed level of depressive symptoms as the strongest predictor of the use of the Internet based intervention and that personality might provide useful information about the users.

Identifiers

PMID22928095
PMCPMC3426188
OpenAlexW2110556129

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.