Decision Tree Identified Risk Groups with High Suicidal Ideation in South Korea: A Population‐Based Study

Kim, Hyun Kyung; Kim, Ji Young; Kim, Jong Hyen; Hyoung, Hee Kyoung

doi:10.1111/phn.12219

Cited by 6 publications

(4 citation statements)

References 24 publications

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“…Within the domain of mental health, recent studies using decision trees have primarily examined associations with depression [14][15][16][17][18][19] and suicide risk. 15,[20][21][22][23][24][25][26][27][28] Two studies examined depression outcomes in youth populations specifically. Hill et al 16 found that, among students with subclinical depressive symptoms at baseline, friend support was protective against developing major depressive disorder by age 30, with anxiety disorder and substance use disorder increasing risk among those without friend support.…”

Section: Introductionmentioning

confidence: 99%

Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study

Battista

Diao

Patte

et al. 2023

Health Promot Chronic Dis Prev Can

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Introduction In population health surveillance research, survey data are commonly analyzed using regression methods; however, these methods have limited ability to examine complex relationships. In contrast, decision tree models are ideally suited for segmenting populations and examining complex interactions among factors, and their use within health research is growing. This article provides a methodological overview of decision trees and their application to youth mental health survey data. Methods The performance of two popular decision tree techniques, the classification and regression tree (CART) and conditional inference tree (CTREE) techniques, is compared to traditional linear and logistic regression models through an application to youth mental health outcomes in the COMPASS study. Data were collected from 74 501 students across 136 schools in Canada. Anxiety, depression and psychosocial well-being outcomes were measured along with 23 sociodemographic and health behaviour predictors. Model performance was assessed using measures of prediction accuracy, parsimony and relative variable importance. Results Decision tree and regression models consistently identified the same sets of most important predictors for each outcome, indicating a general level of agreement between methods. Tree models had lower prediction accuracy but were more parsimonious and placed greater relative importance on key differentiating factors. Conclusion Decision trees provide a means of identifying high-risk subgroups to whom prevention and intervention efforts can be targeted, making them a useful tool to address research questions that cannot be answered by traditional regression methods.

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Section: Introductionmentioning

confidence: 99%

Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study

Battista

Diao

Patte

et al. 2023

Health Promot Chronic Dis Prev Can

View full text Add to dashboard Cite

show abstract

“…These tools enable the automatic identification of patterns and similarities, facilitating the interpretation of large data volumes. 14 Kim et al 14 explain that, based on the analysis of the relationships between risk factors, the DT can predict groups that are at higher risk of developing a certain outcome. In addition, the tree format facilitates the understanding of how these relationships culminate in the risk levels.…”

Section: Introductionmentioning

confidence: 99%

“…Decision trees (DTs) can be used to overcome this difficulty. These tools enable the automatic identification of patterns and similarities, facilitating the interpretation of large data volumes 14 . Kim et al 14 .…”

Section: Introductionmentioning

confidence: 99%

Predictive model for temporomandibular disorder in adolescents: Decision tree

Waked,

de Aguiar,

Aroucha

et al. 2023

Int J Paed Dentistry

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BackgroundTemporomandibular disorders (TMD) do not only occur in adults but also in adolescents, with negative impacts on their development.AimTo propose a predictive model for TMD in adolescents using a decision tree (DT) analysis and to identify groups at high and low risk of developing TMD in the city of Recife, PE, Brazil.DesignThis cross‐sectional study was conducted in Recife on 1342 schoolchildren of both sexes aged 10–17 years. The analyses were performed using Pearson's chi‐squared test and Fisher's exact test, as well as the CHAID algorithm for the construction of the DT. The SPSS statistical program was used.ResultsThe prevalence of TMD was 33.2%. Statistically significant associations were observed between TMD and sex, depression, self‐reported orofacial pain, and orofacial pain on clinical examination. The DT consisted of self‐reported orofacial pain, orofacial pain on physical examination, and depression, with an overall predictive power of 73.0%.ConclusionThe proposed tree has a good predictive capacity and permits to identify groups at high risk of developing TMD among adolescents, such as those with self‐reported orofacial pain or orofacial pain on examination associated with depression.

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“…In the existing literature, the focus has predominantly converged on the repercussions of widowhood on mental health dimensions, such as depressive manifestations or suicidal tendencies in the older adults (14,21,22). Yet, a discernible research void persists regarding widowhood's bearing on facets like family support.…”

Section: Introductionmentioning

confidence: 99%

Relationship of widowhood with pulse pressure, fasting blood glucose, and mental health in older adults: a propensity matching score analysis

Zhang,

Chen,

Sun

et al. 2023

Front. Public Health

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BackgroundTransitioning from marriage to widowhood presents inevitable and significant challenges for many older adults. This study explored the impact of widowhood on a range of mental health outcomes, including pulse pressure and fasting blood glucose levels, among older adults in nursing homes.MethodsThis cross-sectional study utilized cluster random sampling to recruit participants, with data analyzed from 388 older Chinese adults. Psychosocial traits were assessed using the Perceived Social Support from Family scale (PSS-Fa) for family support, the Generalized Anxiety Disorder 7-item scale (GAD-7) for anxiety symptoms, and the 9-item Patient Health Questionnaire (PHQ-9) for depressive symptoms and suicidal ideation. Propensity score matching (PSM) was employed to control for confounding factors. A multivariate linear regression analysis was performed to explore the relationship between widowhood, mental health outcomes, pulse pressure, and fasting blood glucose levels.ResultsAfter applying PSM, the sample size was refined to 268 (N = 134 for both married and widowed groups) from the initial 388, excluding 120 unmatched cases. Widowed older adults were found to have notably lower family support (β = −0.81, p = 0.002), increased depressive symptoms (β = 1.04, p = 0.043), elevated pulse pressure (β = 8.90, p < 0.001), and higher fasting blood glucose levels (β = 3.22, p = 0.027). These associations exhibited greater beta values compared to pre-matching analysis.ConclusionOur findings revealed that widowed participants had reduced family support, an increased risk of depressive symptoms, heightened pulse pressure, and elevated fasting blood glucose in comparison to their married counterparts. Interventions focusing on social support, mental health, and cardiovascular well-being could be advantageous for this at-risk group.

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Decision Tree Identified Risk Groups with High Suicidal Ideation in South Korea: A Population‐Based Study

Abstract: Public health nurses and community mental health professionals should recognize risk groups with high suicidal ideation, and target these groups when implementing preventive interventions.

Cited by 6 publications

References 24 publications

Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study

Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study

Predictive model for temporomandibular disorder in adolescents: Decision tree

Relationship of widowhood with pulse pressure, fasting blood glucose, and mental health in older adults: a propensity matching score analysis

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