MétaCan
Menu
← Retour à la cohorte
Enregistrement W2741029204

A comparison of two cohorts among child welfare investigations in Alberta: child, caregivers, household, & case risk factors

2015· article· en· W2741029204 sur OpenAlexaffvenueabout
Hee‐Jeong Yoo, Bruce MacLaurin, Morgan DeMone

Notice bibliographique

RevueJournal of undergraduate research in Alberta · 2015
Typearticle
Langueen
DomainePsychology
ThématiqueChild Abuse and Trauma
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésNeglectPopulationChild developmentWelfarePsychologyChild abuseChild neglectIntervention (counseling)Developmental psychologyEarly childhoodMedicineDemographySuicide preventionPoison controlPsychiatryEnvironmental health
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION In 2008, the province of Alberta reported children eleven years and younger made up 71% of all investigations [5]. More than 8,400 children five years of age or younger came to the attention of child welfare in Alberta in 2008 for allegations of child abuse and neglect, compared to approximately 7,700 children ages six to eleven years of age. Younger children are especially vulnerable to their surrounding environment and are heavily dependent on their caregivers to meet their basic needs; which inevitably provides the foundation for future developmental growth [6]. It is imperative for younger children to achieve critical developmental milestones such as language, brain development, emotional regulation, and attachment bonds [6]. Research indicates that younger children who experience maltreatment have an increased risk for health, behavior, and psychological functioning concerns in later life [2,5,6]. The accumulation of risk factors has been attributed to poorer internal and external behavioral trajectories in later childhood and adolescent years [1,3,6,8,9]. Examining child, caregiver, household, and case risk factors associated with these two cohorts will contribute to a greater understanding of the complex experiences between these child age groups. This paper seeks to provide researchers and practitioners with awareness concerning the impact of risk factors on this vulnerable population. METHODS This secondary analysis was conducted on data collected for the Alberta Incidence Study of Reported Child Abuse and Neglect (AIS-2008). The AIS-2008 collected 2,239 child maltreatment investigations from fourteen randomly selected child intervention services offices over a three month case selection period (October 1, 2008 to December 31, 2008). Offices were stratified by jurisdiction and size to ensure that all subpopulations were fairly represented in the study, with additional consideration for Aboriginal organizations. This article presents select comparisons of child, family, household, and case factors of child maltreatment investigations and risk of future maltreatment investigations. The analyses compares two child age cohorts: 0-5 years old and 6-11 years old. Bivariate analyses and Pearson’s chi-squared tests were used to examine differences in risk factors associated with the younger and older cohorts. This analysis was conducted using weighted estimates of 16,120 child investigations for incidents of maltreatment involving children 11 years of age and younger in Alberta. Of the total weighted estimate, 8,415 alleged child maltreatment  investigations involved children five years and younger and 7,705 maltreatment investigations involved children between six and 11 years of age. Analysis included substantiated, suspected and unfounded investigations for the two cohorts from the AIS-2008 data. For further information, refer to the methodology chapter of the AIS-2008: Major Findings Report [5]. RESULTS Figure 1 shows case risk factors for child investigations where a child 11 years old and younger was involved. Thirty-one percent of the 0-5 year old cohort remained open for on-going services and 9% of cases were streamed to differential or alternative response. Twenty-nine percent of the 6-11 cohort remained open for on-going services and of those, 10% of cases were streamed to differential or alternative response. Fifty-one percent of investigations of the 0-5 cohort were previously reported to child welfare for suspected maltreatment. For the older cohort, 61% of investigations were previously reported to child welfare for suspected maltreatment. Workers were asked to report on 6 housing safety concerns: accessible weapons, accessible drugs or drug paraphernalia, drug production or trafficking in the home, chemicals or solvents used in production, other home injury and health hazards. One or two of these household hazard risk factors were identified in 16% of investigations in the 0-5 cohort and 14% in the 6-11 cohort. For the 0-5 cohort, emotional harm was documented in 16% of investigations, whereas physical harm was noted in 7% of investigations. For the older cohort, emotional harm was documented in 30% of investigations and physical harm was documented in 5% of investigations. While 10% of the 0-5 cohort investigations were placed in a child welfare placement, 7% of 6-11 cohort investigations were placed in a child welfare placement. Figure 1. Case Risk Factors. Percentages of case characteristics include all child investigations for incidents of child maltreatment where a child 11 years or younger was involved (n=16,120), 0-5 years old cohort (n=8,415), and 6-11 years old cohort (n=7,705). DISCUSSION AND CONCLUSIONS This secondary analysis of the AIS-2008 dataset examined child, caregiver, household, and case risk factors associated with the two youngest cohorts investigated by the child protection system. Firstly, these findings support the need to focus on both the additive effects and breadth of risk factors pertaining to child investigations, rather than focusing on solely one risk factor during an investigation. Second, the present findings indicate that families with young children in the child welfare system are faced with many significant stressors or multiple risk factors, such as parental mental health, social isolation, drug or alcohol abuse, intimate partner violence, financial hardship, and may also have young children experiencing poor functioning in multiple areas of their development. Children eleven and under have longer sustained involvement and multiple involvement with child protection services. Lastly, the array of risk factors and protective factors identified by child welfare workers could potentially shape both prevention and intervention strategies in preventing rates of re-referral and increase overall positive outcomes for children and families. LIMITATIONS While the AIS-2008 dataset provides a unique opportunity to examine the child welfare response to reported maltreatment in Alberta, a number of considerations for this secondary analysis must be made when interpreting these findings. The AIS-2008 dataset; 1) only tracked reports investigated by child intervention services and did not include reports that were screened out, only investigated by police, and never reported; 2) is based on the assessments provided by the investigating child intervention workers and could not be independently verified; 3) is weighted using annual estimates which included counts of children investigated more than once during the year, therefore the unit of analysis for the weighted estimates was a child investigation; 4) as weighted estimates provided some instances where sample sizes were too small to derive publishable estimates [5].

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,150
Score d'incertitude au seuil0,301

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0050,005
Études des sciences et des technologies0,0030,001
Communication savante0,0020,001
Science ouverte0,0020,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,116
Tête enseignante GPT0,397
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission3
Résumé présentoui

Explorer davantage

Même revueJournal of undergraduate research in Alberta→Même sujetChild Abuse and Trauma→Travaux en français237 207→