How accurately can we predict repeat teen pregnancy based on social ecological factors?

Harding, Jessica F.; Keating, Betsy; Walzer, Jennifer; Xing, Fei; Zief, Susan; Gao, Jessica

doi:10.1037/dev0001394

Cited by 4 publications

(2 citation statements)

References 35 publications

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“…The socio-ecological model was adapted to explain the multiple factors influencing recurrent teenage pregnancy [ 23 ] and the challenges comfronted by teenagers with recurrent pregnancy. The model indicates that people interact with different social and ecological factors at different levels, which influence their experiences and behaviors [ 24 ].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…The model indicates that people interact with different social and ecological factors at different levels, which influence their experiences and behaviors [ 24 ]. These levels consist of individual, interpersonal, and environmental factors [ 23 ]. At the individual level, the teenagers’ characteristics such as knowledge of contraceptives, use of contraceptives, early marriage, poverty, and low level of education [ 14 , 25 ] may influence the occurrence of recurrent pregnancy and would be confronted by challenges such as dropping-out of school, financial hardship, and depression [ 21 , 26 ].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

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A phenomenological study on recurrent teenage pregnancies in effutu municipality- Ghana.the experiences of teenage mothers

Boateng

Botchwey

Adatorvor³

et al. 2023

BMC Public Health

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Background Generally, recurrent teenage pregnancies are public health menaces that impede the quality of life of teenage mothers, their offspring, and society as a whole. However, there is paucity of information regarding factors influencing this social issue especially, in developing countries where Ghana is no exception. Moreover, this menace has been least investigated from the perspective of the teenager with multiple pregnancies. Hence, this study aimed at identifying the factors influencing recurrent teenage pregnancies and the challenges confronted by these teenage mothers. Method This study is a phenomenological qualitative study that was conducted in the Effutu Municipality in the Central Region of Ghana. Employing convenience and snowball sampling, 40 participants who were residents of the study area, had a child each, and were pregnant at the time of the study were included. Other participants included teenage mothers who had at least two (2) children. A face-to-face in-depth interview with the help of an interview guide was conducted. Proceedings were recorded, transcribed, and analysed using thematic analysis. Quotations were used in the result presentation. Results The results of the study revealed that factors influencing recurrent teenage pregnancies are multifactorial. It includes peer pressure, parental neglect, poverty, living with a partner, and inadequate knowledge of family planning. The teenager with recurrent pregnancy is confronted with financial difficulties and is faced with stigmatisation in the society where she finds herself. Conclusion To this effect, it is important to intensify education on family planning and good parental practices among parents with teenage mothers while providing a similar form of sensitization for members of the society about the harmful effects of stigmatisation on the teenage mother and her children. Again, a social support network for teenagers with recurrent pregnancies could be formed to help curb this public health menace.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Theoretical Frameworkmentioning

confidence: 99%

A phenomenological study on recurrent teenage pregnancies in effutu municipality- Ghana.the experiences of teenage mothers

Boateng

Botchwey

Adatorvor³

et al. 2023

BMC Public Health

View full text Add to dashboard Cite

show abstract

References

2024

The Multilevel Community Engagement Model

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Supervised machine learning for exploratory analysis in family research

Sun

2024

J of Marriage and Family

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ObjectiveThis article introduces supervised machine learning (ML) for conducting exploratory, discovery‐oriented family research in a transparent and systematic way.BackgroundSupervised ML can examine large numbers of variable simultaneously, identify key predictors, and explore patterns among predictors—an approach that may help address concerns in family research about lack of theoretical specificity and prevalence of unguided exploratory analysis.MethodFollowing an overview of supervised ML, example analyses drew on the National Longitudinal Study of Adolescent Health (Add Health) dataset across Waves I–IV (N = 5114 adolescents, 50.53% female, Mage = 15.94, SD = 1.77 at Wave I). From 143 articles using Add Health data Waves I through IV, 62 adolescent family variables from eight domains (e.g., socioeconomics, parenting, health) were identified as predictors of young adult (ages 24–32) educational attainment. Following benchmark regression models, ML models were trained using Lasso regression, decision tree, random forest, and extreme gradient boosting; these were tested separately from training data and interpreted through SHapley Additive exPlanations.ResultsThe random forest model performed best (R2 = .382 for the model with all the predictors): 14 variables were identified to be the key predictors of educational attainment. Patterns among these predictors, including directionality, nonlinearity and interactions emerged.ConclusionsSupervised ML research can be used to inform further confirmatory analyses and advance theory.

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How accurately can we predict repeat teen pregnancy based on social ecological factors?

Cited by 4 publications

References 35 publications

A phenomenological study on recurrent teenage pregnancies in effutu municipality- Ghana.the experiences of teenage mothers

A phenomenological study on recurrent teenage pregnancies in effutu municipality- Ghana.the experiences of teenage mothers

References

Supervised machine learning for exploratory analysis in family research

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