27 recherche sur le mot-clé 'prediction'

Prediction in Autism Spectrum Disorder: A Systematic Review of Empirical Evidence / Jonathan CANNON in Autism Research, 14-4 (April 2021)  

Public ISBD [article]  inAutism Research > 14-4 (April 2021) . - p.604-630 Titre : Prediction in Autism Spectrum Disorder: A Systematic Review of Empirical Evidence Type de document : Texte imprimé et/ou numérique Auteurs : Jonathan CANNON, Auteur ; Amanda M. O'BRIEN, Auteur ; Lindsay BUNGERT, Auteur ; Pawan SINHA, Auteur Article en page(s) : p.604-630 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  brain  learning  perception  prediction Index. décimale : PER Périodiques Résumé : According to a recent influential proposal, several phenotypic features of autism spectrum disorder (ASD) may be accounted for by differences in predictive skills between individuals with ASD and neurotypical individuals. In this systematic review, we describe results from 47 studies that have empirically tested this hypothesis. We assess the results based on two observable aspects of prediction: learning a pairing between an antecedent and a consequence and responding to an antecedent in a predictive manner. Taken together, these studies suggest distinct differences in both predictive learning and predictive response. Studies documenting differences in learning predictive pairings indicate challenges in detecting such relationships especially when predictive features of an antecedent have low salience or consistency, and studies showing differences in habituation and perceptual adaptation suggest low-level predictive processing differences in ASD. These challenges may account for the observed differences in the influence of predictive priors, in spontaneous predictive movement or gaze, and in social prediction. An important goal for future research will be to better define and constrain the broad domain-general hypothesis by testing multiple types of prediction within the same individuals. Additional promising avenues include studying prediction within naturalistic contexts and assessing the effect of prediction-based intervention on supporting functional outcomes for individuals with ASD. LAY SUMMARY: Researchers have suggested that many features of autism spectrum disorder (ASD) may be explained by differences in the prediction skills of people with ASD. We review results from 47 studies. These studies suggest that ASD may be associated with differences in the learning of predictive pairings (e.g., learning cause and effect) and in low-level predictive processing in the brain (e.g., processing repeated sounds). These findings lay the groundwork for research that can improve our understanding of ASD and inform interventions. Autism Res 2021, 14: 604-630. © 2021 International Society for Autism Research and Wiley Periodicals LLC. En ligne : http://dx.doi.org/10.1002/aur.2482 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443 [article] Prediction in Autism Spectrum Disorder: A Systematic Review of Empirical Evidence [Texte imprimé et/ou numérique] / Jonathan CANNON, Auteur ; Amanda M. O'BRIEN, Auteur ; Lindsay BUNGERT, Auteur ; Pawan SINHA, Auteur . - p.604-630. Langues : Anglais (eng) in Autism Research > 14-4 (April 2021) . - p.604-630 Mots-clés : autism spectrum disorder  brain  learning  perception  prediction Index. décimale : PER Périodiques Résumé : According to a recent influential proposal, several phenotypic features of autism spectrum disorder (ASD) may be accounted for by differences in predictive skills between individuals with ASD and neurotypical individuals. In this systematic review, we describe results from 47 studies that have empirically tested this hypothesis. We assess the results based on two observable aspects of prediction: learning a pairing between an antecedent and a consequence and responding to an antecedent in a predictive manner. Taken together, these studies suggest distinct differences in both predictive learning and predictive response. Studies documenting differences in learning predictive pairings indicate challenges in detecting such relationships especially when predictive features of an antecedent have low salience or consistency, and studies showing differences in habituation and perceptual adaptation suggest low-level predictive processing differences in ASD. These challenges may account for the observed differences in the influence of predictive priors, in spontaneous predictive movement or gaze, and in social prediction. An important goal for future research will be to better define and constrain the broad domain-general hypothesis by testing multiple types of prediction within the same individuals. Additional promising avenues include studying prediction within naturalistic contexts and assessing the effect of prediction-based intervention on supporting functional outcomes for individuals with ASD. LAY SUMMARY: Researchers have suggested that many features of autism spectrum disorder (ASD) may be explained by differences in the prediction skills of people with ASD. We review results from 47 studies. These studies suggest that ASD may be associated with differences in the learning of predictive pairings (e.g., learning cause and effect) and in low-level predictive processing in the brain (e.g., processing repeated sounds). These findings lay the groundwork for research that can improve our understanding of ASD and inform interventions. Autism Res 2021, 14: 604-630. © 2021 International Society for Autism Research and Wiley Periodicals LLC. En ligne : http://dx.doi.org/10.1002/aur.2482 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443

Prediction learning in adults with autism and its molecular correlates / L. A. SAPEY-TRIOMPHE in Molecular Autism, 12 (2021)  

Public ISBD [article]  inMolecular Autism > 12 (2021) . - 64 p. Titre : Prediction learning in adults with autism and its molecular correlates Type de document : Texte imprimé et/ou numérique Auteurs : L. A. SAPEY-TRIOMPHE, Auteur ; J. TEMMERMAN, Auteur ; N. A. J. PUTS, Auteur ; J. WAGEMANS, Auteur Article en page(s) : 64 p. Langues : Anglais (eng) Mots-clés : Asd  Gaba  Glutamate  Glutathione  Magnetic resonance spectroscopy  Prediction  Prior  Probabilistic learning  Uncertainty  Volatility Index. décimale : PER Périodiques Résumé : BACKGROUND: According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. METHODS: Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA?+?and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). RESULTS: Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA?+?ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. LIMITATIONS: We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. CONCLUSIONS: Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA?+?in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. En ligne : http://dx.doi.org/10.1186/s13229-021-00470-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=459 [article] Prediction learning in adults with autism and its molecular correlates [Texte imprimé et/ou numérique] / L. A. SAPEY-TRIOMPHE, Auteur ; J. TEMMERMAN, Auteur ; N. A. J. PUTS, Auteur ; J. WAGEMANS, Auteur . - 64 p. Langues : Anglais (eng) in Molecular Autism > 12 (2021) . - 64 p. Mots-clés : Asd  Gaba  Glutamate  Glutathione  Magnetic resonance spectroscopy  Prediction  Prior  Probabilistic learning  Uncertainty  Volatility Index. décimale : PER Périodiques Résumé : BACKGROUND: According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. METHODS: Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA?+?and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). RESULTS: Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA?+?ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. LIMITATIONS: We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. CONCLUSIONS: Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA?+?in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. En ligne : http://dx.doi.org/10.1186/s13229-021-00470-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=459

Neurocognitive and observational markers: prediction of autism spectrum disorder from infancy to mid-childhood / Rachael BEDFORD in Molecular Autism, 8 (2017)  

Public ISBD [article]  inMolecular Autism > 8 (2017) . - 49p. Titre : Neurocognitive and observational markers: prediction of autism spectrum disorder from infancy to mid-childhood Type de document : Texte imprimé et/ou numérique Auteurs : Rachael BEDFORD, Auteur ; T. GLIGA, Auteur ; E. SHEPHARD, Auteur ; M. ELSABBAGH, Auteur ; A. PICKLES, Auteur ; Tony CHARMAN, Auteur ; M. H. JOHNSON, Auteur Article en page(s) : 49p. Langues : Anglais (eng) Mots-clés : Autism  Diagnosis  High risk  Infants  Neurocognitive  Prediction  Siblings Index. décimale : PER Périodiques Résumé : BACKGROUND: Prospective studies of infants at high familial risk for autism spectrum disorder (ASD) have identified a number of putative early markers that are associated with ASD outcome at 3 years of age. However, some diagnostic changes occur between toddlerhood and mid-childhood, which raises the question of whether infant markers remain associated with diagnosis into mid-childhood. METHODS: First, we tested whether infant neurocognitive markers (7-month neural response to eye gaze shifts and 14-month visual disengagement latencies) as well as an observational marker of emerging ASD behaviours (the Autism Observation Scale for Infants; AOSI) predicted ASD outcome in high-risk (HR) 7-year-olds with and without an ASD diagnosis (HR-ASD and HR-No ASD) and low risk (LR) controls. Second, we tested whether the neurocognitive markers offer predictive power over and above the AOSI. RESULTS: Both neurocognitive markers distinguished children with an ASD diagnosis at 7 years of age from those in the HR-No ASD and LR groups. Exploratory analysis suggested that neurocognitive markers may further differentiate stable versus lost/late diagnosis across the 3 to 7 year period, which will need to be tested in larger samples. At both 7 and 14 months, combining the neurocognitive marker with the AOSI offered a significantly improved model fit over the AOSI alone. CONCLUSIONS: Infant neurocognitive markers relate to ASD in mid-childhood, improving predictive power over and above an early observational marker. The findings have implications for understanding the neurodevelopmental mechanisms that lead from risk to disorder and for identification of potential targets of pre-emptive intervention. En ligne : http://dx.doi.org/10.1186/s13229-017-0167-3 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=329 [article] Neurocognitive and observational markers: prediction of autism spectrum disorder from infancy to mid-childhood [Texte imprimé et/ou numérique] / Rachael BEDFORD, Auteur ; T. GLIGA, Auteur ; E. SHEPHARD, Auteur ; M. ELSABBAGH, Auteur ; A. PICKLES, Auteur ; Tony CHARMAN, Auteur ; M. H. JOHNSON, Auteur . - 49p. Langues : Anglais (eng) in Molecular Autism > 8 (2017) . - 49p. Mots-clés : Autism  Diagnosis  High risk  Infants  Neurocognitive  Prediction  Siblings Index. décimale : PER Périodiques Résumé : BACKGROUND: Prospective studies of infants at high familial risk for autism spectrum disorder (ASD) have identified a number of putative early markers that are associated with ASD outcome at 3 years of age. However, some diagnostic changes occur between toddlerhood and mid-childhood, which raises the question of whether infant markers remain associated with diagnosis into mid-childhood. METHODS: First, we tested whether infant neurocognitive markers (7-month neural response to eye gaze shifts and 14-month visual disengagement latencies) as well as an observational marker of emerging ASD behaviours (the Autism Observation Scale for Infants; AOSI) predicted ASD outcome in high-risk (HR) 7-year-olds with and without an ASD diagnosis (HR-ASD and HR-No ASD) and low risk (LR) controls. Second, we tested whether the neurocognitive markers offer predictive power over and above the AOSI. RESULTS: Both neurocognitive markers distinguished children with an ASD diagnosis at 7 years of age from those in the HR-No ASD and LR groups. Exploratory analysis suggested that neurocognitive markers may further differentiate stable versus lost/late diagnosis across the 3 to 7 year period, which will need to be tested in larger samples. At both 7 and 14 months, combining the neurocognitive marker with the AOSI offered a significantly improved model fit over the AOSI alone. CONCLUSIONS: Infant neurocognitive markers relate to ASD in mid-childhood, improving predictive power over and above an early observational marker. The findings have implications for understanding the neurodevelopmental mechanisms that lead from risk to disorder and for identification of potential targets of pre-emptive intervention. En ligne : http://dx.doi.org/10.1186/s13229-017-0167-3 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=329

The adult outcome of children referred for autism: typology and prediction from childhood / Andrew PICKLES in Journal of Child Psychology and Psychiatry, 61-7 (July 2020)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 61-7 (July 2020) . - p.760-767 Titre : The adult outcome of children referred for autism: typology and prediction from childhood Type de document : Texte imprimé et/ou numérique Auteurs : Andrew PICKLES, Auteur ; James B. MCCAULEY, Auteur ; Lauren A. PEPA, Auteur ; Marisela HUERTA, Auteur ; Catherine LORD, Auteur Article en page(s) : p.760-767 Langues : Anglais (eng) Mots-clés : Childhood  Edx  adult outcome  autism spectrum disorders  prediction Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism Spectrum Disorder is highly heterogeneous, no more so than in the complex world of adult life. Being able to summarize that complexity and have some notion of the confidence with which we could predict outcome from childhood would be helpful for clinical practice and planning. METHODS: Latent class profile analysis is applied to data from 123 participants from the Early Diagnosis Study (Lord et al., Archives of General Psychiatry, 2006, 63, 694) to summarize in a typology the multifacetted early adult outcome of children referred for autism around age 2. The form of the classes and their predictability from childhood is described. RESULTS: Defined over 15 measures, the adult outcomes were reduced to four latent classes, accounting for much of the variation in cognitive and functional measures but little in the affective measures. The classes could be well and progressively more accurately predicted from childhood IQ and symptom severity measurement taken at age 2 years to age 9 years. Removing verbal and nonverbal IQ and autism symptom severity measurement from the profile of adult measures did not change the number of the latent classes; however, there was some change in the class composition and they were more difficult to predict. CONCLUSIONS: While an empirical summary of adult outcome is possible, careful consideration needs to be given to the aspects that should be given priority. An outcome typology that gives weight to cognitive outcomes is well predicted from corresponding measures taken in childhood, even after account for prediction bias from fitting a complex model to a small sample. However, subjective well-being and affective aspects of adult outcome were weakly related to functional outcomes and poorly predicted from childhood. En ligne : http://dx.doi.org/10.1111/jcpp.13180 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=429 [article] The adult outcome of children referred for autism: typology and prediction from childhood [Texte imprimé et/ou numérique] / Andrew PICKLES, Auteur ; James B. MCCAULEY, Auteur ; Lauren A. PEPA, Auteur ; Marisela HUERTA, Auteur ; Catherine LORD, Auteur . - p.760-767. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 61-7 (July 2020) . - p.760-767 Mots-clés : Childhood  Edx  adult outcome  autism spectrum disorders  prediction Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism Spectrum Disorder is highly heterogeneous, no more so than in the complex world of adult life. Being able to summarize that complexity and have some notion of the confidence with which we could predict outcome from childhood would be helpful for clinical practice and planning. METHODS: Latent class profile analysis is applied to data from 123 participants from the Early Diagnosis Study (Lord et al., Archives of General Psychiatry, 2006, 63, 694) to summarize in a typology the multifacetted early adult outcome of children referred for autism around age 2. The form of the classes and their predictability from childhood is described. RESULTS: Defined over 15 measures, the adult outcomes were reduced to four latent classes, accounting for much of the variation in cognitive and functional measures but little in the affective measures. The classes could be well and progressively more accurately predicted from childhood IQ and symptom severity measurement taken at age 2 years to age 9 years. Removing verbal and nonverbal IQ and autism symptom severity measurement from the profile of adult measures did not change the number of the latent classes; however, there was some change in the class composition and they were more difficult to predict. CONCLUSIONS: While an empirical summary of adult outcome is possible, careful consideration needs to be given to the aspects that should be given priority. An outcome typology that gives weight to cognitive outcomes is well predicted from corresponding measures taken in childhood, even after account for prediction bias from fitting a complex model to a small sample. However, subjective well-being and affective aspects of adult outcome were weakly related to functional outcomes and poorly predicted from childhood. En ligne : http://dx.doi.org/10.1111/jcpp.13180 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=429

Demographic and clinical correlates of autism symptom domains and autism spectrum diagnosis / Thomas W. FRAZIER in Autism, 18-5 (July 2014)  

Public ISBD [article]  inAutism > 18-5 (July 2014) . - p.571-582 Titre : Demographic and clinical correlates of autism symptom domains and autism spectrum diagnosis Type de document : Texte imprimé et/ou numérique Auteurs : Thomas W. FRAZIER, Auteur ; Eric A. YOUNGSTROM, Auteur ; Rebecca EMBACHER, Auteur ; Antonio Y. HARDAN, Auteur ; John N. CONSTANTINO, Auteur ; Paul LAW, Auteur ; Robert L. FINDLING, Auteur ; Charis ENG, Auteur Article en page(s) : p.571-582 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  autism symptoms  diagnosis  prediction Index. décimale : PER Périodiques Résumé : Demographic and clinical factors may influence assessment of autism symptoms. This study evaluated these correlates and also examined whether social communication and interaction and restricted/repetitive behavior provided unique prediction of autism spectrum disorder diagnosis. We analyzed data from 7352 siblings included in the Interactive Autism Network registry. Social communication and interaction and restricted/repetitive behavior symptoms were obtained using caregiver-reports on the Social Responsiveness Scale. Demographic and clinical correlates were covariates in regression models predicting social communication and interaction and restricted/repetitive behavior symptoms. Logistic regression and receiver operating characteristic curve analyses evaluated the incremental validity of social communication and interaction and restricted/repetitive behavior domains over and above global autism symptoms. Autism spectrum disorder diagnosis was the strongest correlate of caregiver-reported social communication and interaction and restricted/repetitive behavior symptoms. The presence of comorbid diagnoses also increased symptom levels. Social communication and interaction and restricted/repetitive behavior symptoms provided significant, but modest, incremental validity in predicting diagnosis beyond global autism symptoms. These findings suggest that autism spectrum disorder diagnosis is by far the largest determinant of quantitatively measured autism symptoms. Externalizing (attention deficit hyperactivity disorder) and internalizing (anxiety) behavior, low cognitive ability, and demographic factors may confound caregiver-report of autism symptoms, potentially necessitating a continuous norming approach to the revision of symptom measures. Social communication and interaction and restricted/repetitive behavior symptoms may provide incremental validity in the diagnosis of autism spectrum disorder. En ligne : http://dx.doi.org/10.1177/1362361313481506 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=233 [article] Demographic and clinical correlates of autism symptom domains and autism spectrum diagnosis [Texte imprimé et/ou numérique] / Thomas W. FRAZIER, Auteur ; Eric A. YOUNGSTROM, Auteur ; Rebecca EMBACHER, Auteur ; Antonio Y. HARDAN, Auteur ; John N. CONSTANTINO, Auteur ; Paul LAW, Auteur ; Robert L. FINDLING, Auteur ; Charis ENG, Auteur . - p.571-582. Langues : Anglais (eng) in Autism > 18-5 (July 2014) . - p.571-582 Mots-clés : autism spectrum disorder  autism symptoms  diagnosis  prediction Index. décimale : PER Périodiques Résumé : Demographic and clinical factors may influence assessment of autism symptoms. This study evaluated these correlates and also examined whether social communication and interaction and restricted/repetitive behavior provided unique prediction of autism spectrum disorder diagnosis. We analyzed data from 7352 siblings included in the Interactive Autism Network registry. Social communication and interaction and restricted/repetitive behavior symptoms were obtained using caregiver-reports on the Social Responsiveness Scale. Demographic and clinical correlates were covariates in regression models predicting social communication and interaction and restricted/repetitive behavior symptoms. Logistic regression and receiver operating characteristic curve analyses evaluated the incremental validity of social communication and interaction and restricted/repetitive behavior domains over and above global autism symptoms. Autism spectrum disorder diagnosis was the strongest correlate of caregiver-reported social communication and interaction and restricted/repetitive behavior symptoms. The presence of comorbid diagnoses also increased symptom levels. Social communication and interaction and restricted/repetitive behavior symptoms provided significant, but modest, incremental validity in predicting diagnosis beyond global autism symptoms. These findings suggest that autism spectrum disorder diagnosis is by far the largest determinant of quantitatively measured autism symptoms. Externalizing (attention deficit hyperactivity disorder) and internalizing (anxiety) behavior, low cognitive ability, and demographic factors may confound caregiver-report of autism symptoms, potentially necessitating a continuous norming approach to the revision of symptom measures. Social communication and interaction and restricted/repetitive behavior symptoms may provide incremental validity in the diagnosis of autism spectrum disorder. En ligne : http://dx.doi.org/10.1177/1362361313481506 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=233

Investigating Motor Preparation in Autism Spectrum Disorder With and Without Attention Deficit/Hyperactivity Disorder / Marta MIGO in Journal of Autism and Developmental Disorders, 52-6 (June 2022)  

Permalink

Predictive language processing in young autistic children / Kathryn E. PRESCOTT in Autism Research, 15-5 (May 2022)  

Permalink

Annual Research Review: Optimal outcomes of child and adolescent mental illness / E. Jane COSTELLO in Journal of Child Psychology and Psychiatry, 56-3 (March 2015)  

Permalink

Annual Research Review: Prevention of psychosis in adolescents - systematic review and meta-analysis of advances in detection, prognosis and intervention / Ana CATALAN in Journal of Child Psychology and Psychiatry, 62-5 (May 2021)  

Permalink

Annual Research Review: Universal and targeted strategies for assigning interventions to achieve population impact / Kenneth A. DODGE in Journal of Child Psychology and Psychiatry, 61-3 (March 2020)  

Permalink