With high twin concordance and sibling recurrence risk, the influence of genetic factors in the etiology of autism is not disputed. The contribution of environmental risk to the etiology of autism is less well established. While the prevalence increase observed worldwide has fueled beliefs of an epidemic driven by environmental changes, the evidence for such interpretations of the secular change in prevalence is lacking (Fombonne, 2025). In epidemiological surveys, no clustering in time or space has been reported that could point to candidate exposures. Thus, observational (cohort and case–control) studies have been wide-ranging and exploratory rather than hypothesis-driven. In light of growing evidence of atypical development occurring in the first months of life (Dawson et al., 2023, Lancet Neurology, 22, 244), environmental risk research in autism has focused on prenatal or periconceptional exposures. In the last 20 years, a myriad of associations have been reported between autism risk and prenatal exposure to: pesticides, phthalates, air pollutants, maternal fever or infection during pregnancy, inter-pregnancy interval, lack of folic acid supplementation, vitamin D deficiency, maternal diet, advancing parental age, exposure to heavy metals, prenatal exposure to antidepressants, valproic acid, benzodiazepines, acetaminophen, maternal smoking, cannabis or alcohol use during pregnancy, maternal obesity and excessive gestational weight gain, prematurity, low birth weight, maternal immune activation, C-section, use of oxytocin, assisted reproductive technologies, and countless others. With few exceptions (advanced parental age, prenatal exposure to valproic acid), associations have not been replicated, or when they have, their causal nature has not been established.
{"title":"Editorial: The acetaminophen scare: association vs causation","authors":"Eric Fombonne","doi":"10.1111/jcpp.70064","DOIUrl":"10.1111/jcpp.70064","url":null,"abstract":"<p>With high twin concordance and sibling recurrence risk, the influence of genetic factors in the etiology of autism is not disputed. The contribution of environmental risk to the etiology of autism is less well established. While the prevalence increase observed worldwide has fueled beliefs of an epidemic driven by environmental changes, the evidence for such interpretations of the secular change in prevalence is lacking (Fombonne, 2025). In epidemiological surveys, no clustering in time or space has been reported that could point to candidate exposures. Thus, observational (cohort and case–control) studies have been wide-ranging and exploratory rather than hypothesis-driven. In light of growing evidence of atypical development occurring in the first months of life (Dawson et al., 2023, <i>Lancet Neurology</i>, 22, 244), environmental risk research in autism has focused on prenatal or periconceptional exposures. In the last 20 years, a myriad of associations have been reported between autism risk and prenatal exposure to: pesticides, phthalates, air pollutants, maternal fever or infection during pregnancy, inter-pregnancy interval, lack of folic acid supplementation, vitamin D deficiency, maternal diet, advancing parental age, exposure to heavy metals, prenatal exposure to antidepressants, valproic acid, benzodiazepines, acetaminophen, maternal smoking, cannabis or alcohol use during pregnancy, maternal obesity and excessive gestational weight gain, prematurity, low birth weight, maternal immune activation, C-section, use of oxytocin, assisted reproductive technologies, and countless others. With few exceptions (advanced parental age, prenatal exposure to valproic acid), associations have not been replicated, or when they have, their causal nature has not been established.</p>","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"66 11","pages":"1621-1626"},"PeriodicalIF":7.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acamh.onlinelibrary.wiley.com/doi/epdf/10.1111/jcpp.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145305452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Serena Defina, Charlotte A.M. Cecil, Janine F. Felix, Esther Walton, Henning Tiemeier
BackgroundDepressive symptoms and cardio‐metabolic risk factors often co‐occur. However, our understanding of the potential mechanisms and temporal dynamics underlying their co‐development remains elusive.MethodsThis population‐based cohort study examined bidirectional longitudinal associations between depressive symptoms and cardio‐metabolic risk factors from age 10 to 25 years, using prospective data from the ALSPAC Study. Participants with at least one (of six) follow‐up measurement for each outcome were included in the analyses. We measured depressive symptoms through self‐ as well as parent‐reports, and assessed several cardio‐metabolic risk factors (including adiposity measures, lipid profiles, and inflammation).ResultsAmong our 7,970 (47% male, 96% White) participants, we found bidirectional, within‐person associations between self‐reported depressive symptoms and adiposity (i.e., fat/lean mass index, but not body mass index), across the study period. Adiposity was more stable over time (β [range] = 0.75 [0.54; 0.84]), compared to depressive symptoms (0.26 [0.12; 0.38]), and it had a stronger prospective (i.e., cross‐lagged) association with future depressive symptoms (0.07 [0.03, 0.13]) compared to that between depressive symptoms and future adiposity (0.04 [0.03, 0.06]). The magnitude of these associations reached its peak between 14 and 16 years. We did not find evidence of cross‐lagged associations in either direction between depressive symptoms and waist circumference, insulin, triglycerides, LDL cholesterol, or C‐reactive protein.ConclusionsThese findings suggest a bidirectional relationship between depressive symptoms and cardio‐metabolic risk factors, particularly adiposity (i.e., fat/lean mass). Adiposity showed a stronger prospective association with future depressive symptoms than vice versa; however, their relationship revealed more reciprocal than previously thought.
{"title":"Longitudinal co‐development of mental and cardio‐metabolic health from childhood to young adulthood","authors":"Serena Defina, Charlotte A.M. Cecil, Janine F. Felix, Esther Walton, Henning Tiemeier","doi":"10.1111/jcpp.70065","DOIUrl":"https://doi.org/10.1111/jcpp.70065","url":null,"abstract":"BackgroundDepressive symptoms and cardio‐metabolic risk factors often co‐occur. However, our understanding of the potential mechanisms and temporal dynamics underlying their co‐development remains elusive.MethodsThis population‐based cohort study examined bidirectional longitudinal associations between depressive symptoms and cardio‐metabolic risk factors from age 10 to 25 years, using prospective data from the ALSPAC Study. Participants with at least one (of six) follow‐up measurement for each outcome were included in the analyses. We measured depressive symptoms through self‐ as well as parent‐reports, and assessed several cardio‐metabolic risk factors (including adiposity measures, lipid profiles, and inflammation).ResultsAmong our 7,970 (47% male, 96% White) participants, we found bidirectional, within‐person associations between self‐reported depressive symptoms and adiposity (i.e., fat/lean mass index, but not body mass index), across the study period. Adiposity was more stable over time (β [range] = 0.75 [0.54; 0.84]), compared to depressive symptoms (0.26 [0.12; 0.38]), and it had a stronger prospective (i.e., cross‐lagged) association with future depressive symptoms (0.07 [0.03, 0.13]) compared to that between depressive symptoms and future adiposity (0.04 [0.03, 0.06]). The magnitude of these associations reached its peak between 14 and 16 years. We did not find evidence of cross‐lagged associations in either direction between depressive symptoms and waist circumference, insulin, triglycerides, LDL cholesterol, or C‐reactive protein.ConclusionsThese findings suggest a bidirectional relationship between depressive symptoms and cardio‐metabolic risk factors, particularly adiposity (i.e., fat/lean mass). Adiposity showed a stronger prospective association with future depressive symptoms than vice versa; however, their relationship revealed more reciprocal than previously thought.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"28 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145306135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Increasing awareness of mental health problems, including that of young people, is generally seen as positive, and many interventions to increase awareness are underway internationally. Yet, a principled evaluation of the benefits and harms of increasing awareness is still lacking. Here, we present a conceptual framework for the evaluation of information interventions that are aimed at increasing public awareness of mental health problems. We borrow concepts from dynamic systems, such as infection spread and related population growth, to ask how benefits, but also harms of information on mental health, may accrue over time. We argue that as information spreads, several cascades of events are set off that involve members of the general public but also clinicians and healthcare services. These cascades entailinvolve positive and negative feedback loops. We discuss not only how increased diagnoses can lead to positive outcomes (e.g. increasing diagnostic rates and appropriate treatments in those who would otherwise have remained undiagnosed) but also how increased awareness can lead to decreases in diagnostic accuracy, to service overload, and how they may expose people to unnecessary or harmful treatments. We argue that the need for a framework founded on modelling societal dynamics is needed to ensure that both the benefits and the downsides of mental health information are accurately gauged and to help the planning of better public health campaigns.
{"title":"Editorial Perspective: How spreading mental health information can be (un-) helpful - a dynamic systems approach.","authors":"Daniele Marcotulli,Lucy Foulkes,Argyris Stringaris","doi":"10.1111/jcpp.70055","DOIUrl":"https://doi.org/10.1111/jcpp.70055","url":null,"abstract":"Increasing awareness of mental health problems, including that of young people, is generally seen as positive, and many interventions to increase awareness are underway internationally. Yet, a principled evaluation of the benefits and harms of increasing awareness is still lacking. Here, we present a conceptual framework for the evaluation of information interventions that are aimed at increasing public awareness of mental health problems. We borrow concepts from dynamic systems, such as infection spread and related population growth, to ask how benefits, but also harms of information on mental health, may accrue over time. We argue that as information spreads, several cascades of events are set off that involve members of the general public but also clinicians and healthcare services. These cascades entailinvolve positive and negative feedback loops. We discuss not only how increased diagnoses can lead to positive outcomes (e.g. increasing diagnostic rates and appropriate treatments in those who would otherwise have remained undiagnosed) but also how increased awareness can lead to decreases in diagnostic accuracy, to service overload, and how they may expose people to unnecessary or harmful treatments. We argue that the need for a framework founded on modelling societal dynamics is needed to ensure that both the benefits and the downsides of mental health information are accurately gauged and to help the planning of better public health campaigns.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"83 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145288530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Schools are important settings for intervention to improve mental health. Much school mental health research has focused on schools as an avenue to reach large numbers of young people with new interventions, added on top of what schools currently do. However, research is increasingly focused on changing the school system itself to improve mental health, with a growing emphasis on improving school climate. This article begins by exploring wider debates on the benefits and harms of school-based interventions, before focusing on school climate as a target for intervention. It reviews evidence from intervention studies and systematic reviews to understand effectiveness, how interventions reduce or amplify inequalities, and real-world impacts. School climate research has grown rapidly since the turn of the century. It remains difficult to define. Definitions vary in whether they include focus on physical environments and educational instruction. However, they converge on focus on positive relationships among a school community and safety. Several large trials of interventions to improve mental health, by improving school climate, have been conducted in a range of international contexts. While many have not been effective, recent trials provide evidence that interventions can improve school climate and mental health, as well as a range of risk behaviours. Few studies examine effects on inequalities in mental health, with tentative evidence that school climate interventions have been more effective for some groups than others (e.g., bigger effects for boys than for girls). Evidence on scalability and sustainability indicates that typically small effects from trials may not fully translate into real-world change. There is growing evidence that improving school climate interventions can improve child and adolescent mental health. More research is needed on how such interventions can contribute to reducing inequalities. Further work is needed to understand how effects translate into real-world public health impact.
{"title":"Annual Research Review: Improving school climate to improve child and adolescent mental health and reduce inequalities.","authors":"Graham Moore","doi":"10.1111/jcpp.70061","DOIUrl":"https://doi.org/10.1111/jcpp.70061","url":null,"abstract":"Schools are important settings for intervention to improve mental health. Much school mental health research has focused on schools as an avenue to reach large numbers of young people with new interventions, added on top of what schools currently do. However, research is increasingly focused on changing the school system itself to improve mental health, with a growing emphasis on improving school climate. This article begins by exploring wider debates on the benefits and harms of school-based interventions, before focusing on school climate as a target for intervention. It reviews evidence from intervention studies and systematic reviews to understand effectiveness, how interventions reduce or amplify inequalities, and real-world impacts. School climate research has grown rapidly since the turn of the century. It remains difficult to define. Definitions vary in whether they include focus on physical environments and educational instruction. However, they converge on focus on positive relationships among a school community and safety. Several large trials of interventions to improve mental health, by improving school climate, have been conducted in a range of international contexts. While many have not been effective, recent trials provide evidence that interventions can improve school climate and mental health, as well as a range of risk behaviours. Few studies examine effects on inequalities in mental health, with tentative evidence that school climate interventions have been more effective for some groups than others (e.g., bigger effects for boys than for girls). Evidence on scalability and sustainability indicates that typically small effects from trials may not fully translate into real-world change. There is growing evidence that improving school climate interventions can improve child and adolescent mental health. More research is needed on how such interventions can contribute to reducing inequalities. Further work is needed to understand how effects translate into real-world public health impact.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"11 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145277358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDThere is limited evidence from systematic nationwide studies evaluating the impact of cannabis legalization on cannabis-related exposures among the pediatric population. Using the National Poison Data System (NPDS), we calculated the effects of medical and recreational cannabis dispensaries on reported pediatric cannabis exposures.METHODSWe analyzed data from 36,161 reported cannabis-related exposures for individuals aged 2-20 between 2016 and 2021, comparing states with and without open medical cannabis dispensaries and states with open recreational cannabis dispensaries to states with open medical cannabis dispensaries. Using a difference-in-difference design, we estimated the effects of cannabis dispensary openings on semi-annual cannabis exposures by age group: young children (2-6 years old), children (7-11), adolescents (12-17), and young adults (18-20).RESULTSPatients aged 2-6 (96.3%) and 7-11 (82.4%) frequently incurred unintentional exposures, while patients aged 12-17 (79.9%) and 18-20 (77.5%) more often incurred intentional exposures. Medical cannabis dispensary openings were associated with a 52.3% increase (CI 37.5-67.0; p < .001) in cannabis-related exposure rates in individuals aged 2-6. However, we found a 42.4% decrease (95% CI: -62.2 to -22.6; p < .001) in the number of exposures occurring per 100,000 population when recreational dispensaries opened, relative to states with only medical cannabis dispensaries open. While we did not find statistically significant increases among children aged 7-11 following medical cannabis dispensary openings, we did see a 26.6% (95% CI: -45.1 to -8.1) decrease following recreational cannabis dispensary openings. We did not find statistically significant effects for other age groups.CONCLUSIONSOur findings indicate policymakers may need to invest in providing cannabis safety education when medical cannabis dispensaries open to avoid unintended exposures, though some of that effect appears to be mitigated by the time recreational dispensaries (eventually) open. Professionals that provide medical cannabis or provide care in medical cannabis states should consider providing education about how to safely use and store cannabis in the household to prevent cannabis-involved exposures.
{"title":"Cannabis and pediatric cannabis exposure - evidence from America's Poison Centers.","authors":"Shelby R Steuart,Victoria Bethel,W David Bradford","doi":"10.1111/jcpp.70058","DOIUrl":"https://doi.org/10.1111/jcpp.70058","url":null,"abstract":"BACKGROUNDThere is limited evidence from systematic nationwide studies evaluating the impact of cannabis legalization on cannabis-related exposures among the pediatric population. Using the National Poison Data System (NPDS), we calculated the effects of medical and recreational cannabis dispensaries on reported pediatric cannabis exposures.METHODSWe analyzed data from 36,161 reported cannabis-related exposures for individuals aged 2-20 between 2016 and 2021, comparing states with and without open medical cannabis dispensaries and states with open recreational cannabis dispensaries to states with open medical cannabis dispensaries. Using a difference-in-difference design, we estimated the effects of cannabis dispensary openings on semi-annual cannabis exposures by age group: young children (2-6 years old), children (7-11), adolescents (12-17), and young adults (18-20).RESULTSPatients aged 2-6 (96.3%) and 7-11 (82.4%) frequently incurred unintentional exposures, while patients aged 12-17 (79.9%) and 18-20 (77.5%) more often incurred intentional exposures. Medical cannabis dispensary openings were associated with a 52.3% increase (CI 37.5-67.0; p < .001) in cannabis-related exposure rates in individuals aged 2-6. However, we found a 42.4% decrease (95% CI: -62.2 to -22.6; p < .001) in the number of exposures occurring per 100,000 population when recreational dispensaries opened, relative to states with only medical cannabis dispensaries open. While we did not find statistically significant increases among children aged 7-11 following medical cannabis dispensary openings, we did see a 26.6% (95% CI: -45.1 to -8.1) decrease following recreational cannabis dispensary openings. We did not find statistically significant effects for other age groups.CONCLUSIONSOur findings indicate policymakers may need to invest in providing cannabis safety education when medical cannabis dispensaries open to avoid unintended exposures, though some of that effect appears to be mitigated by the time recreational dispensaries (eventually) open. Professionals that provide medical cannabis or provide care in medical cannabis states should consider providing education about how to safely use and store cannabis in the household to prevent cannabis-involved exposures.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"8 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145277360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDChildren with conduct problems are at elevated risk for negative psychosocial, educational, and behavioral outcomes. Identifying at-risk children can aid in providing timely intervention and prevention, ultimately improving their long-term outcomes. There is a need to develop screening tools to better identify at-risk children who may benefit from early intervention.METHODSData were collected from the longitudinal Adolescent Brain Cognitive Development (ABCD) Study. Children completed a baseline visit at age 9-10, then returned annually for 3 years (n = 3,517). We used machine learning classifiers (logistic regression, Naïve Bayes, support vector machine, and random forest) to predict conduct problems (i.e., conduct disorder or oppositional defiant disorder) in children after 1, 2, and 3 years.RESULTSThe best-performing model (the random forest classifier) predicted children at risk for conduct problems with an accuracy of 90% or greater (AUC = 0.98 at 1 year, AUC = 0.97 at 2 years, AUC = 0.97 at 3 years). A random forest classifier simplified to include only 10 features was able to predict conduct problems nearly as well (AUC = 0.97 at 1 year, AUC = 0.96 at 2 years, AUC = 0.97 at 3 years).CONCLUSIONSUsing factors previously linked to conduct problems, we built machine learning models to identify predictors of conduct problems in children over a 3-year period. A small number of self-report features can be used to predict persistent conduct problems with 90% or greater specificity and sensitivity up to 3 years after initial assessment. This suggests that parent and child self-report data, along with machine learning, can identify children at risk for persistent conduct problems.
{"title":"Machine learning prediction of conduct problems in children using the longitudinal ABCD study.","authors":"Kathryn Berluti,Paige Amormino,Alexandra Potter,Safwan Wshah,Abigail Marsh","doi":"10.1111/jcpp.70057","DOIUrl":"https://doi.org/10.1111/jcpp.70057","url":null,"abstract":"BACKGROUNDChildren with conduct problems are at elevated risk for negative psychosocial, educational, and behavioral outcomes. Identifying at-risk children can aid in providing timely intervention and prevention, ultimately improving their long-term outcomes. There is a need to develop screening tools to better identify at-risk children who may benefit from early intervention.METHODSData were collected from the longitudinal Adolescent Brain Cognitive Development (ABCD) Study. Children completed a baseline visit at age 9-10, then returned annually for 3 years (n = 3,517). We used machine learning classifiers (logistic regression, Naïve Bayes, support vector machine, and random forest) to predict conduct problems (i.e., conduct disorder or oppositional defiant disorder) in children after 1, 2, and 3 years.RESULTSThe best-performing model (the random forest classifier) predicted children at risk for conduct problems with an accuracy of 90% or greater (AUC = 0.98 at 1 year, AUC = 0.97 at 2 years, AUC = 0.97 at 3 years). A random forest classifier simplified to include only 10 features was able to predict conduct problems nearly as well (AUC = 0.97 at 1 year, AUC = 0.96 at 2 years, AUC = 0.97 at 3 years).CONCLUSIONSUsing factors previously linked to conduct problems, we built machine learning models to identify predictors of conduct problems in children over a 3-year period. A small number of self-report features can be used to predict persistent conduct problems with 90% or greater specificity and sensitivity up to 3 years after initial assessment. This suggests that parent and child self-report data, along with machine learning, can identify children at risk for persistent conduct problems.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"11 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145277359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tjeerd Rudmer de Vries,Signe Kær Bennetsen,Leonie K Elsenburg,Signe Hald Andersen,Bertina Kreshpaj,Karsten Thielen,Naja Hulvej Rod
BACKGROUNDChildhood adversity is associated with increased risks of long-term social welfare dependence in young adulthood. Mental health problems may mediate this relation, but evidence remains lacking.METHODS613,643 individuals from the Danish Life Course cohort (DANLIFE) were categorized into five trajectory groups based on their annual exposure to adversity: low adversity, early-life material deprivation, persistent material deprivation, loss or threat of loss, or high adversity. Mental health problems were identified through hospital contacts and psychotropic medication use. Long-term social welfare dependence was defined as receiving social benefits for at least 52 consecutive weeks within the follow-up period. We examined the contribution of differential exposure and susceptibility to mental health problems in relation to childhood adversity and long-term social welfare dependence through causal mediation analysis.RESULTSThe different childhood adversity groups saw 54-319 additional cases of long-term social welfare dependence per 1,000 individuals compared with the low adversity group. These associations were partly mediated through mental health problems. To illustrate, in the high adversity group, differential exposure to mental health problems accounted for 15.0% (95% CI: 14.4-15.6) of the total effect, while differential susceptibility accounted for an additional 9.8% (95% CI: 8.8-10.9).CONCLUSIONSMental health problems partly mediate the relation between childhood adversity and long-term social welfare dependence in young adulthood through both elevated exposure and increased susceptibility. Addressing mental health problems and increasing resilience among individuals with a history of childhood adversity may mitigate the risk of subsequent social welfare dependence.
{"title":"Trajectories of childhood adversity, social welfare dependence in young adulthood, and the mediating role of mental health problems: a Danish population-based cohort study.","authors":"Tjeerd Rudmer de Vries,Signe Kær Bennetsen,Leonie K Elsenburg,Signe Hald Andersen,Bertina Kreshpaj,Karsten Thielen,Naja Hulvej Rod","doi":"10.1111/jcpp.70062","DOIUrl":"https://doi.org/10.1111/jcpp.70062","url":null,"abstract":"BACKGROUNDChildhood adversity is associated with increased risks of long-term social welfare dependence in young adulthood. Mental health problems may mediate this relation, but evidence remains lacking.METHODS613,643 individuals from the Danish Life Course cohort (DANLIFE) were categorized into five trajectory groups based on their annual exposure to adversity: low adversity, early-life material deprivation, persistent material deprivation, loss or threat of loss, or high adversity. Mental health problems were identified through hospital contacts and psychotropic medication use. Long-term social welfare dependence was defined as receiving social benefits for at least 52 consecutive weeks within the follow-up period. We examined the contribution of differential exposure and susceptibility to mental health problems in relation to childhood adversity and long-term social welfare dependence through causal mediation analysis.RESULTSThe different childhood adversity groups saw 54-319 additional cases of long-term social welfare dependence per 1,000 individuals compared with the low adversity group. These associations were partly mediated through mental health problems. To illustrate, in the high adversity group, differential exposure to mental health problems accounted for 15.0% (95% CI: 14.4-15.6) of the total effect, while differential susceptibility accounted for an additional 9.8% (95% CI: 8.8-10.9).CONCLUSIONSMental health problems partly mediate the relation between childhood adversity and long-term social welfare dependence in young adulthood through both elevated exposure and increased susceptibility. Addressing mental health problems and increasing resilience among individuals with a history of childhood adversity may mitigate the risk of subsequent social welfare dependence.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"7 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145209212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jorien L Treur,Jentien M Vermeulen,Margot P van de Weijer
This editorial perspective focuses on the complex relationship of cigarette smoking and e-cigarette use ('vaping') with mental health problems. It is challenging to reliably determine the causal nature of these associations because both (e-)smoking and mental health problems generally arise during adolescence, and both are highly multifactorial in their aetiology. While there is now scientific consensus that cigarette smoking is a causal risk factor for mental health problems, there is still a scarcity of causal research and conclusions with respect to e-cigarette use. In order to more reliably determine whether and how (e-)smoking affects mental health, it is important to better understand the potential causal pathways. Here, we discuss the main biological mechanisms that might explain causal effects of smoking and e-cigarettes on mental health, including (neuro-)inflammation, oxidative stress and nicotine binding. We showcase informative studies that have been conducted using sophisticated causally informative study designs and identify in which areas robust causal knowledge is especially lacking. In future work, evidence 'triangulation', where different types of research methods are integrated to look for converging results, seems to be the most promising approach to obtain reliable causal evidence.
{"title":"Editorial Perspective: Smoking, vaping and mental health - a perspective on potential causal mechanisms.","authors":"Jorien L Treur,Jentien M Vermeulen,Margot P van de Weijer","doi":"10.1111/jcpp.70059","DOIUrl":"https://doi.org/10.1111/jcpp.70059","url":null,"abstract":"This editorial perspective focuses on the complex relationship of cigarette smoking and e-cigarette use ('vaping') with mental health problems. It is challenging to reliably determine the causal nature of these associations because both (e-)smoking and mental health problems generally arise during adolescence, and both are highly multifactorial in their aetiology. While there is now scientific consensus that cigarette smoking is a causal risk factor for mental health problems, there is still a scarcity of causal research and conclusions with respect to e-cigarette use. In order to more reliably determine whether and how (e-)smoking affects mental health, it is important to better understand the potential causal pathways. Here, we discuss the main biological mechanisms that might explain causal effects of smoking and e-cigarettes on mental health, including (neuro-)inflammation, oxidative stress and nicotine binding. We showcase informative studies that have been conducted using sophisticated causally informative study designs and identify in which areas robust causal knowledge is especially lacking. In future work, evidence 'triangulation', where different types of research methods are integrated to look for converging results, seems to be the most promising approach to obtain reliable causal evidence.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"78 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDNon-suicidal self-injury (NSSI) poses a significant mental health challenge among adolescents, necessitating accessible and effective interventions. While the development of technology offers new opportunities, higher costs remain a concern. In this context, digital psychological interventions such as text message intervention (SMS) present a convenient and low-cost delivery method that requires no face-to-face contact. However, the extent to which this method could function as a viable strategy remains underexplored.OBJECTIVETo evaluate the effectiveness of an SMS intervention specifically developed for NSSI among adolescents when combined with treatment as usual (TAU), compared to TAU alone.METHODSA randomized controlled trial (RCT) was conducted with 86 Chinese adolescents, randomly assigned to either the SMS intervention plus TAU or TAU alone. The SMS intervention, consisting of text messages addressing NSSI-related knowledge, distress tolerance skills, and emotion regulation strategies, was administered over 8 weeks. Assessments were conducted at baseline, 4 weeks, and 8 weeks.RESULTSParticipants in the intervention group showed a significant reduction in NSSI behavior at 4 weeks (RR = 0.43, p < .001), though this effect was not significant at 8 weeks (RR = 0.84, p = .265). No significant changes in NSSI ideation were observed at 4 weeks (RR = 0.87, p = .221) or 8 weeks (RR = 1.10, p = .437). Resistance to NSSI urges increased significantly at 8 weeks in the intervention group (RR = 1.93, p = .002), but not at 4 weeks (RR = 1.44, p = .063). Secondary outcomes showed no significant changes.CONCLUSIONSThe low cost, scalability, and accessibility of SMS interventions make them a potentially valuable complementary tool for supporting self-harm populations. However, further research is necessary to confirm their efficacy across diverse settings and to determine how best to integrate them with comprehensive treatment strategies.
背景：非自杀性自伤（NSSI）对青少年的心理健康构成了重大挑战，需要可获得和有效的干预措施。虽然技术的发展提供了新的机会，但更高的成本仍然是一个问题。在这种背景下，短信干预（SMS）等数字心理干预提供了一种方便、低成本、无需面对面接触的传递方法。然而，这种方法作为一种可行战略的作用程度仍未得到充分探讨。目的：评估专门针对青少年自伤开发的SMS干预与常规治疗（TAU）相结合的有效性，并与单独使用TAU进行比较。方法对86名中国青少年进行随机对照试验（RCT），随机分为短信干预加TAU和单独TAU两组。短信干预，包括短信解决自伤相关知识，痛苦容忍技能和情绪调节策略，进行了8周的管理。在基线、4周和8周时进行评估。结果干预组患者自伤行为在第4周显著减少（RR = 0.43, p < 0.05）。0.001)，但在8周时效果不显著（RR = 0.84, p = 0.265）。第4周时，自伤意念无明显变化（RR = 0.87, p =）。221)或8周（RR = 1.10, p = .437）。干预组对自伤冲动的抵抗在8周时显著增加(RR = 1.93, p =。002)，但在第4周时没有（RR = 1.44, p = 0.063）。次要结局无明显变化。结论短信干预具有低成本、可扩展性和可及性等特点，是支持自残人群的一种有潜在价值的辅助工具。然而，需要进一步的研究来证实它们在不同情况下的疗效，并确定如何最好地将它们与综合治疗策略结合起来。
{"title":"Brief digital psychological intervention to prevent relapse of non-suicidal self-injury behavior in adolescents: A randomized controlled trial.","authors":"Chang Zhang,Diyang Qu,Dennis Chong,Chang Lei,Yidong Shen,Xilong Cui,Yuqiong He,Yamin Li,Jianjun Ou,Runsen Chen","doi":"10.1111/jcpp.70054","DOIUrl":"https://doi.org/10.1111/jcpp.70054","url":null,"abstract":"BACKGROUNDNon-suicidal self-injury (NSSI) poses a significant mental health challenge among adolescents, necessitating accessible and effective interventions. While the development of technology offers new opportunities, higher costs remain a concern. In this context, digital psychological interventions such as text message intervention (SMS) present a convenient and low-cost delivery method that requires no face-to-face contact. However, the extent to which this method could function as a viable strategy remains underexplored.OBJECTIVETo evaluate the effectiveness of an SMS intervention specifically developed for NSSI among adolescents when combined with treatment as usual (TAU), compared to TAU alone.METHODSA randomized controlled trial (RCT) was conducted with 86 Chinese adolescents, randomly assigned to either the SMS intervention plus TAU or TAU alone. The SMS intervention, consisting of text messages addressing NSSI-related knowledge, distress tolerance skills, and emotion regulation strategies, was administered over 8 weeks. Assessments were conducted at baseline, 4 weeks, and 8 weeks.RESULTSParticipants in the intervention group showed a significant reduction in NSSI behavior at 4 weeks (RR = 0.43, p < .001), though this effect was not significant at 8 weeks (RR = 0.84, p = .265). No significant changes in NSSI ideation were observed at 4 weeks (RR = 0.87, p = .221) or 8 weeks (RR = 1.10, p = .437). Resistance to NSSI urges increased significantly at 8 weeks in the intervention group (RR = 1.93, p = .002), but not at 4 weeks (RR = 1.44, p = .063). Secondary outcomes showed no significant changes.CONCLUSIONSThe low cost, scalability, and accessibility of SMS interventions make them a potentially valuable complementary tool for supporting self-harm populations. However, further research is necessary to confirm their efficacy across diverse settings and to determine how best to integrate them with comprehensive treatment strategies.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"43 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liann Haham,Idan M Aderka,Daniel S Pine,Rany Abend,Tomer Shechner
BACKGROUNDGiven the long-term negative impact of exposure to military conflict, identifying its immediate psychological effects is crucial to develop prevention and intervention approaches, especially in adolescents, a group particularly vulnerable to mental health challenges.METHODSWe examined 198 war-exposed Israeli adolescents (Mage = 16.35 years; 131 females, 65 males), 1-3 months into the Israel-Hamas war (2023), using a multi-method approach combining mental health questionnaires with week-long momentary sampling throughout the day and nightly diary measures. We focused on risk and protective factors affecting mental health.RESULTSMost adolescents reported clinical levels of anxiety (MSCARED-c = 28.54, SD = 15.88) and trauma-related symptoms (MCPTCI = 46.78, SD = 15.61). Female gender, increased tiredness, and avoidant coping strategies constituted risk factors for lower psychological well-being; in-person social interaction and emotional and problem-focused coping strategies represented resilience factors.CONCLUSIONSBy providing comprehensive information on risk and protective factors, this study informs the development of targeted prevention and intervention approaches to support adolescent well-being in times of extreme stress.
{"title":"Adolescence under fire: a multi-method study of psychological vulnerability and resilience among adolescents impacted by war.","authors":"Liann Haham,Idan M Aderka,Daniel S Pine,Rany Abend,Tomer Shechner","doi":"10.1111/jcpp.70052","DOIUrl":"https://doi.org/10.1111/jcpp.70052","url":null,"abstract":"BACKGROUNDGiven the long-term negative impact of exposure to military conflict, identifying its immediate psychological effects is crucial to develop prevention and intervention approaches, especially in adolescents, a group particularly vulnerable to mental health challenges.METHODSWe examined 198 war-exposed Israeli adolescents (Mage = 16.35 years; 131 females, 65 males), 1-3 months into the Israel-Hamas war (2023), using a multi-method approach combining mental health questionnaires with week-long momentary sampling throughout the day and nightly diary measures. We focused on risk and protective factors affecting mental health.RESULTSMost adolescents reported clinical levels of anxiety (MSCARED-c = 28.54, SD = 15.88) and trauma-related symptoms (MCPTCI = 46.78, SD = 15.61). Female gender, increased tiredness, and avoidant coping strategies constituted risk factors for lower psychological well-being; in-person social interaction and emotional and problem-focused coping strategies represented resilience factors.CONCLUSIONSBy providing comprehensive information on risk and protective factors, this study informs the development of targeted prevention and intervention approaches to support adolescent well-being in times of extreme stress.","PeriodicalId":187,"journal":{"name":"Journal of Child Psychology and Psychiatry","volume":"319 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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