Self-reported Legal Status in the California Health Interview Survey: An evaluation of data quality and application towards adolescent mental health
Notice bibliographique
Résumé
Legal status is an important social determinant of health for immigrants and children of immigrant parents, which is typically not measured in public health surveys. The sensitivity of legal status and presumed response behavior to relevant questions are primary reasons why this topic goes unmeasured. Changes in immigration enforcement likely impact the sensitivity of the topic and may compromise data quality, however, this is also likely when legal status matters most for health outcomes. This dissertation evaluates the response behavior to questions of citizenship and immigration status in the California Health Interview Survey and applies these data to identify mental health risks for Latino adolescents with an unauthorized parent.The first study, When we ask, do they answer? Item-nonresponse to questions of citizenship and immigration status in the California Health Interview Survey, examined foreign born survey participants who did not answer questions of citizenship and immigration statusbetween 2001 and 2015. Nonresponse was low overall, however, increased over time and was largely attributable to respondents who were born in Mexico. The second study, When they answer, should we listen? Examining the quality of self-reported citizenship and immigration status, evaluated potential misreporting of legal status among Mexican-born participants between 2003 and 2015. This study utilized indirect estimation strategies which have been developed to produce profiles of the unauthorized population from surveys which do not ask legal status. Nearly a quarter of all Mexican-born participants reported that they were a non-citizen without agreen card, and these participants were demographically similar to external profiles of the unauthorized population. Predicted probabilities of unauthorized status produced by the indirect estimation procedure indicated that the threat of extensive misreporting was low and consistent over time. These results, paired with the findings of low nonresponse, indicate that participants were willing to answer questions of citizenship and immigration status and that these data are fit for use. The third paper, Severe Psychological Distress Among Latino Adolescents with an Unauthorized Parent examined adolescent mental health using data from 2007 to 2016 disaggregated by parental nativity and legal status. Multivariate logistic models indicated that Latino adolescents with an immigrant mother were less likely to report severe psychological distress and that children with an unauthorized father were more likely to report severe psychological distress. These findings reveal important heterogeneity among children in immigrant households and demonstrates the value of measuring legal status in a population survey. It is critical that data used to monitor public health trends more fully incorporate immigrants and their children by measuring domains which are relevant to their health and wellbeing. In addition to measuring what needs to be measured, researchers should continue to critically evaluate quality and put data which are fit to use to meaningful and timely use.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,342 | 0,438 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,006 | 0,011 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».