Factors associated with readmission in South African adolescents discharged from two inpatient psychosocial rehabilitation units

Pieterse, Deirdre; Temmingh, Henk; Vogel, W.

doi:10.2989/17280583.2016.1259165

Cited by 8 publications

(24 citation statements)

References 27 publications

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“…Although 20 family-related risk predictors were identified across all studies, only three predictors (primary caregiver, family psychiatric history, and history of child abuse or neglect) were measured in three or more studies and thus combinable via meta-analysis (Figure 1). Youths whose primary caregiver was a parent were at lower risk of readmission, compared with those with a nonparent caretaker (6,14,19), and this relationship approached significance (OR pooled =0.63, 95% confidence interval [CI]=0.38-1.04). Heterogeneity was very low (I 2 =0.0%).…”

Section: Sociodemographic Characteristicsmentioning

confidence: 98%

“…Demographic characteristics. In total, 17 studies provided a separate ES for the relationship between participant age and readmission (4,5,14,15,(17)(18)(19)(20)(21)(22)(23)(24)(40)(41)(42)(43). An ES for the relationship between gender and readmission was reported in 19 studies (3-6, 15, 17-24, 27, 40, 42-45), and ten studies provided an ES for race-ethnicity and readmission (5,15,17,18,21,23,27,43,46,47).…”

Section: Sociodemographic Characteristicsmentioning

confidence: 99%

“…Forest plots for significant diagnostic predictors are presented in Figure 3. In regard to serious mental illness, 10 studies measured the relationship between presence of a psychotic disorder and readmission (3,4,6,14,19,22,40,42,51,52). Youths with a psychotic disorder were at significantly higher risk of readmission, compared with those without a psychotic disorder (OR pooled =1.87, 95% CI=1.53-2.28).…”

Section: Clinical Characteristicsmentioning

confidence: 99%

“…Five studies measured the relationship between presence of bipolar disorder and readmission (4,14,19,40,51). Youths with bipolar disorder were at significantly higher risk of readmission, compared with those without bipolar disorder (OR pooled =1.44, 95% CI=1.…”

Section: Clinical Characteristicsmentioning

confidence: 99%

“…readmitted, whereas other studies find no relationship with age (17,18). Similarly, the posited relationships between readmission and gender (13,16,19), race-ethnicity (7,13,20), guardianship status (6,16,19,21), early life stress and child abuse (6), and socioeconomic status (16,22) are multidirectional. The role of disease severity also remains unclear, with variable findings regarding primary diagnosis and symptom severity (23), comorbidity (3), self-injury, and suicidality (5,6,23,24).…”

mentioning

confidence: 95%

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Psychiatric Readmission of Children and Adolescents: A Systematic Review and Meta-Analysis

Edgcomb¹,

Sorter²,

Lorberg³

et al. 2020

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Objective: To investigate predictors of psychiatric hospital readmission of children and adolescents, a systematic review and meta-analysis was conducted.Methods: Following PRISMA statement guidelines, a systematic literature search of articles published between 1997 and 2018 was conducted in PubMed/MEDLINE, Google Scholar, and PsycINFO for original peer-reviewed articles investigating predictors of psychiatric hospital readmission among youths (,18 years old). Effect sizes were extracted and combined by using random-effects meta-analysis. Covariates were investigated with meta-regression and subgroup analyses.Results: Thirty-three studies met inclusion criteria, containing information on 83,361 children and adolescents, of which raw counts of readmitted vs. non-readmitted youths were available for 76,219. Of these youths, 13.2% (N=10,076) were readmitted. The mean6SD study followup was 15.9615.0 months, and time to readmission was 13.1612.8 months. Readmission was associated with, but not limited to, suicidal ideation at index hospitalization (pooled odds ratio [OR pooled ]=2.35, 95% confidence interval [CI]=1.64-3.37), psychotic disorders (OR pooled =1.87, 95% CI=1.53-2.28), prior hospitalization (OR pooled =2.51, 95% CI=1.76-3.57), and discharge to residential treatment (OR pooled =1.84, 95% CI=1.07-3.16). There was evidence of moderate study bias. Prior investigations were methodologically and substantively heterogeneous, particularly for measurement of family-level factors.

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Section: Sociodemographic Characteristicsmentioning

confidence: 98%

Section: Sociodemographic Characteristicsmentioning

confidence: 99%

Section: Clinical Characteristicsmentioning

confidence: 99%

Section: Clinical Characteristicsmentioning

confidence: 99%

mentioning

confidence: 95%

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Psychiatric Readmission of Children and Adolescents: A Systematic Review and Meta-Analysis

Edgcomb¹,

Sorter²,

Lorberg³

et al. 2020

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Risk factors for readmission among a cohort of psychiatric inpatients in Lilongwe, Malawi

Barnett

Kusunzi

Magola

et al. 2019

International Journal of Psychiatry in Clinical Practice

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A situational analysis of child and adolescent mental health services and systems in the Western Cape Province of South Africa

Mokitimi

Schneider

Vries

2022

Child Adolesc Psychiatry Ment Health

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Background Even though child and adolescent mental health is a global health priority, services are very limited, particularly in low- and middle-income countries (LMIC), and therefore need comprehensive strengthening. This requires knowledge of the hardware elements of the system (human resources, financing, medicines, technology, organisational structure, service infrastructure, and information systems). This study sought to examine these elements of child and adolescent mental health (CAMH) services and systems in the Western Cape Province of South Africa. Methods The World Health Organization Assessment Instrument of Mental Health Systems (WHO-AIMS) version 2.2 of 2005 was adapted to identify key variables of interest in CAMH. Data were collected for the calendar year 2016 and focused on the public health sector. We outlined findings based on best available data across the six domains of the WHO-AIMS. Results In domain 1, we found no provincial CAMH policy or implementation plans to support the national CAMH policy and were unable to identify a CAMH-specific budget. In domain 2, there was no dedicated provincial leadership structure for CAMH, and no dedicated or ‘child- and adolescent-friendly’ mental health services at primary or secondary care levels. At tertiary level, there were only three specialist CAMH teams. The majority of CAMH resources were based in the City of Cape Town, with limited resources in the rural districts. Essential medicines were available in all facilities, and the majority of children and adolescents had access to free services. In domain 3, data were limited about the extent of training offered to primary healthcare staff, and little or no psychosocial interventions were available in primary care. Domain 4 identified a small and variable CAMH workforce across all levels of care. In domain 5, few public health campaigns focused on CAMH, and little evidence of formal intersectoral collaboration on CAMH was identified. Domain 6 identified significant limitations in health information systems for CAMH, including lack of child- and adolescent-specific and disaggregated data to establish baselines for policy development, monitoring, evaluation and CAMH research. Conclusions This study identified significant structural weaknesses in CAMH and presents a clear call for action to strengthen services and systems in the province and in South Africa. it would be important to expand research also to include provider and user perspectives for service strengthening.

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Factors associated with readmission in South African adolescents discharged from two inpatient psychosocial rehabilitation units

Cited by 8 publications

References 27 publications

Psychiatric Readmission of Children and Adolescents: A Systematic Review and Meta-Analysis

Psychiatric Readmission of Children and Adolescents: A Systematic Review and Meta-Analysis

Risk factors for readmission among a cohort of psychiatric inpatients in Lilongwe, Malawi

A situational analysis of child and adolescent mental health services and systems in the Western Cape Province of South Africa

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