Identifying Positive Adaptive Pathways in Low-Income Families in Singapore: Protocol for Sequential, Longitudinal Mixed-Methods Design
Notice bibliographique
Résumé
BACKGROUND: This study aims to examine the adaptive process of children and mothers from multistressed low-income families in Singapore. It aims to bridge the knowledge gap left by existing poverty studies, which are predominately risk focused. Through a sequential longitudinal mixed-methods design, we will differentiate children and mothers who demonstrate varied social, developmental, and mental health trajectories of outcomes. Through utilizing the Latent Growth Curve Model (LGCM), we aim to detect the development and changes of the positive Family Agency and adaptive capacities of these families over time. The construct of Family Agency is underpinned by the theoretical guidance from the Social Relational Theory, which examines child agency, parent agency, relational agency, and the interactions among these members. It is hypothesized that positive Family Agency within low-income families may lead to better outcomes. The key research questions include whether the extent of positive Family Agency mediates the relationship among financial stress, resource utilization, home environment, and parental stress. OBJECTIVE: The study elucidates the Family Agency construct through interviews with mother-child dyads. It also aims to understand how financial stress and resources are differentially related to home environment, parent stress, and parent and child outcomes. METHODS: In phase 1, 60 mother-child dyads from families receiving government financial assistance and with children aged between 7 and 12 years will be recruited. In-depth interviews will be conducted separately with mothers and children. On the basis of 120 interviews, a measurement for the construct of Family Agency will be developed and will be pilot tested. In phase 2a, a longitudinal survey will be conducted over 3 time points from 800 mother-child dyads. The 3 waves of survey results will be analyzed by LGCM to identify the trajectories of adaptation pathways of these low-income families. In addition, 10 focus groups with up to 15 participants in each will be conducted to validate the LGCM results. RESULTS: This project is funded by the Social Science Research Thematic Grant (Singapore). The recruitment of 60 mother-child dyads has been achieved. Data collection will commence once the amendment to the protocol has been approved by the Institutional Review Board. Analysis of phase 1 data will be completed by the end of the first quarter of 2019, and the first set of results is expected to be submitted for publication by the second quarter of 2019. Phase 2 implementation will commence in the second quarter of 2019, and the project end date is in May 2021. CONCLUSIONS: Findings from this study can potentially inform social policy and programs as it refines the understanding of low-income families by distinguishing trajectories of adaptive capacities so that policies and interventions can be targeted in enhancing the adaptive pathways of low-income families with children. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/11629.
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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 | 0,055 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,039 | 0,007 |
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 ».