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Child Abuse Negl ; 121: 105262, 2021 11.
Article in English | MEDLINE | ID: covidwho-1347534

ABSTRACT

BACKGROUND: COVID-19 is likely to have negatively impacted foster families but few data sources are available to confirm this. OBJECTIVE: The current study used Reddit social media data to examine how foster families are faring in the pandemic. Discussion topics were identified and examined for changes before and after COVID-19. PARTICIPANTS AND SETTING: Comments were collected from three Reddit online discussion boards dedicated to foster families (N = 11,830). METHODS: We used machine learning techniques, including Latent Dirichlet Allocation, for topic modeling and textual analysis for qualitative coding of the Reddit comments. RESULTS: Results showed that three main topics had both significant quantitative and meaningful qualitative changes before and after COVID-19. There were significant increases in conversation about becoming a foster parent (F = 5.75, p = 0.02) and activities for foster children (F = 10.61, p = 0.001), whereas there was a significant decrease in discussing permanency (F = 9.46, p = 0.003) before and after the onset of COVID-19. Qualitative coding showed that regarding the topic of becoming a parent, excitement over approval of foster care license before COVID-19 shifted to foster families' increased anxieties about delays in their licensing cases after COVID-19. For permanency, content changed from the best interest of the child and reunifications before COVID-19 to concerns over family separations and permanency challenges after COVID-19. Regarding activities for foster children, content related to everyday activities before COVID-19 changed to specific activities foster children and families could do during lockdowns. Results suggest areas child welfare workers may focus on to better support foster families during and after the pandemic.


Subject(s)
COVID-19/psychology , Foster Home Care , Social Media/statistics & numerical data , COVID-19/epidemiology , Child , Communicable Disease Control , Humans , Pandemics , SARS-CoV-2
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