One-Year Course and Predictors of Outcome of Adolescent Depression

Karlsson, Linnéa; Kiviruusu, Olli; Miettunen, Jouko; Heilä, Hannele; Holi, Matti; Ruuttu, Titta; Tuisku, Virpi; Pelkonen, Mirjami; Marttunen, Mauri

doi:10.4088/jcp.v69n0519

Cited by 24 publications

(20 citation statements)

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“…2B, the course trajectories of the mean BDI scores are plotted. A linear mixed models analysis showed that the trajectories differed in mean severity levels (F = 45.6 [3,623]; P < .001) and not in terms of the trajectoryshapes (class × time: F = 0.61 [12,611]; P = .84). The "chronic" and "remission + recurrence" groups had the highest and the "early remission" group had the lowest scores.…”

Section: Trajectory Groups As Predictors Of 12-24 Month and 36 Followmentioning

confidence: 99%

“…[13] Notably, several studies have used mixture models in treatment trials [14][15][16][17][18][19] and cohort studies. [20] Despite the use of similar techniques, the number of identified course groups varied (2)(3)(4)(5). This could be explained by differences in numbers of follow-ups (7 [14] to 24 [20]), interval lengths (1 week [18] to 3 months [14]), and instruments.…”

Section: Introductionmentioning

confidence: 99%

“…[1] Unfortunately, it is hard to predict adverse course trajectories in individual patients. Previous research has shown several group-based predictors of poor prognosis, including factors such as high severity, [2] young age at onset, [3] long duration of the index episode, [2] and comorbidity. [4] These predictors have been observed in the population and cohorts of patients with a large severity range [2] and have important public health implications.…”

Section: Introductionmentioning

confidence: 99%

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Data-Driven Course Trajectories in Primary Care Patients With Major Depressive Disorder

2014

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Section: Trajectory Groups As Predictors Of 12-24 Month and 36 Followmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Data-Driven Course Trajectories in Primary Care Patients With Major Depressive Disorder

2014

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“…More detailed descriptions of the participants, procedures, and assessments are available elsewhere (Karlsson et al, , 2008.…”

Section: Methodsmentioning

confidence: 99%

Defense Mechanisms in Adolescence as Predictors of Adult Personality Disorders

Strandholm

Kiviruusu

Karlsson

et al. 2016

Journal of Nervous &Amp; Mental Disease

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Our study examines whether defense styles and separate defenses in depressed adolescent outpatients predict adult personality disorders (PDs). We obtained data from consecutive adolescent outpatients who participated in the Adolescent Depression Study at baseline and at the 8-year follow-up (N = 140). Defense styles were divided into mature, neurotic, image-distorting, and immature and a secondary set of analyses were made with separate defenses as predictors of a PD diagnosis. Neurotic, image-distorting, and immature defense styles in adolescence were associated with adulthood PDs. Neurotic defense style associated with cluster B diagnosis and image-distorting defense style associated with cluster A diagnosis. Separate defenses of displacement, isolation, and reaction formation were independent predictors of adult PD diagnosis even after adjusting for PD diagnosis in adolescence. Defense styles and separate defenses predict later PDs and could be used in the focusing of treatment interventions for adolescents.

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“…The screening and diagnostic procedure and the study population ( n = 218) of the ADS study have been described in more detail previously [3, 28]. In brief, of the 774 consecutive outpatients, 660 (85.3%) were considered eligible.…”

Section: Methodsmentioning

confidence: 99%

Differences in Characteristics and Treatment Received among Depressed Adolescent Psychiatric Outpatients with and without Co-Occuring Alcohol Misuse: A 1-Year Follow-Up Study

Pirkola

Pelkonen

Karlsson

et al. 2011

Depression Research and Treatment

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Objectives. We aimed at examining the differences between depressed psychiatric adolescent outpatients with and without cooccurring alcohol misuse in psychosocial background, clinical characteristics, and treatment received during one-year followup. Furthermore, we investigated factors related to nonattendance at treatment. Materials and Methods. Consecutive 156 adolescent (13–19 years) psychiatric outpatients with a unipolar depressive disorder at baseline were interviewed using structured measures at baseline and at 12 months. Alcohol misuse was defined as having an AUDIT score of 8 or more points. The outpatients received “treatment as usual” of clinically defined duration. Results. Among depressive outpatients, poor parental support, parental alcohol use and decreased attendance at treatment associated with alcohol misuse. The severity of alcohol use as measured by AUDIT-score was the strongest factor independently predicting nonattendance at treatment in multivariate analysis. Conclusions. Alcohol misuse indicates family problems, has a deleterious effect on treatment attendance, and should be taken into account when managing treatment for depressive adolescent outpatients.

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One-Year Course and Predictors of Outcome of Adolescent Depression

Cited by 24 publications

References 0 publications

Data-Driven Course Trajectories in Primary Care Patients With Major Depressive Disorder

Data-Driven Course Trajectories in Primary Care Patients With Major Depressive Disorder

Defense Mechanisms in Adolescence as Predictors of Adult Personality Disorders

Differences in Characteristics and Treatment Received among Depressed Adolescent Psychiatric Outpatients with and without Co-Occuring Alcohol Misuse: A 1-Year Follow-Up Study

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