Alicia Chung

Dr. Alicia Chung

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 June 2021 in Journal of Medical Internet Research
Verified
Journal Article
Open access
ACAlicia Chung
Alicia Chung
DVDorice Vieira
Dorice Vieira
TDTiffany Donley
Tiffany Donley
NTNicholas Tan
Nicholas Tan
GJGirardin Jean-Louis
Girardin Jean-Louis
Azizi SeixasAzizi Seixas
Azizi Seixas
Background: The influence of social media among adolescent peer groups can be a powerful change agent. Objective: Our scoping review aimed to elucidate the ways in which social media use among adolescent peers influences eating behaviors. Methods: A scoping review of the literature of articles published from journal inception to 2019 was performed by searching PubMed (ie, MEDLINE), Embase, CINAHL, PsycINFO, Web of Science, and other databases. The review was conducted in three steps: (1) identification of the research question and clarification of criteria using the population, intervention, comparison, and outcome (PICO) framework; (2) selection of articles from the literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; and (3) charting and summarizing information from selected articles. PubMed’s Medical Subject Headings (MeSH) and Embase’s Emtree subject headings were reviewed along with specific keywords to construct a comprehensive search strategy. Subject headings and keywords were based on adolescent age groups, social media platforms, and eating behaviors. After screening 1387 peer-reviewed articles, 37 articles were assessed for eligibility. Participant age, gender, study location, social media channels utilized, user volume, and content themes related to findings were extracted from the articles. Results: Six articles met the final inclusion criteria. A final sample size of 1225 adolescents (aged 10 to 19 years) from the United States, the United Kingdom, Sweden, Norway, Denmark, Portugal, Brazil, and Australia were included in controlled and qualitative studies. Instagram and Facebook were among the most popular social media platforms that influenced healthful eating behaviors (ie, fruit and vegetable intake) as well as unhealthful eating behaviors related to fast food advertising. Online forums served as accessible channels for eating disorder relapse prevention among youth. Social media influence converged around four central themes: (1) visual appeal, (2) content dissemination, (3) socialized digital connections, and (4) adolescent marketer influencers. Conclusions: Adolescent peer influence in social media environments spans the spectrum of healthy eating (ie, pathological) to eating disorders (ie, nonpathological). Strategic network-driven approaches should be considered for engaging adolescents in the promotion of positive dietary behaviors.

15 July 2020 in Current Hypertension Reports
Verified
Journal Article
Closed access
PDF file
Azizi SeixasAzizi Seixas
Azizi Seixas
JMJesse Moore
Jesse Moore
ACAlicia Chung
Alicia Chung
RRRebecca Robbins
Rebecca Robbins
MGMichael Grandner
Michael Grandner
GJGirardin Jean-Louis
Girardin Jean-Louis

24 June 2020 in JMIR mHealth and uHealth
Verified
Journal Article
Open access
Azizi SeixasAzizi Seixas
Azizi Seixas
CCColleen Connors
Colleen Connors
ACAlicia Chung
Alicia Chung
TDTiffany Donley
Tiffany Donley
GJGirardin Jean-Louis
Girardin Jean-Louis
Patient nonadherence to healthy lifestyle behaviors and medical treatments (like medication adherence) accounts for a significant portion of chronic disease burden. Despite the plethora of behavioral interventions to overcome key modifiable/nonmodifiable barriers and enable facilitators to adherence, short- and long-term adherence to healthy lifestyle behaviors and medical treatments is still poor. To optimize adherence, we aimed to provide a novel mobile health solution steeped in precision and personalized population health and a pantheoretical approach that increases the likelihood of adherence. We have described the stages of a pantheoretical approach utilizing tailoring, clustering/profiling, personalizing, and optimizing interventions/strategies to obtain adherence and highlight the minimal engineering needed to build such a solution.

29 July 2025 in Annals of Internal Medicine
Verified
Journal Article
Closed access
CFCandace H. Feldman
Candace H. Feldman
LSLeah Santacroce
Leah Santacroce
IBIngrid V. Bassett
Ingrid V. Bassett
TTTanayott Thaweethai
Tanayott Thaweethai
RARZ Alicic
RZ Alicic
EKElizabeth W. Karlson
Elizabeth W. Karlson
Social determinants of health (SDoH) contribute to disparities in SARS-CoV-2 infection, but their associations with long COVID are unknown. To determine associations between SDoH at the time of SARS-CoV-2 infection and risk for long COVID. Prospective observational cohort study. 33 states plus Washington, DC, and Puerto Rico. Adults (aged ≥18 years) enrolled in RECOVER-Adult (Researching COVID to Enhance Recovery) between October 2021 and November 2023 who were within 30 days of SARS-CoV-2 infection; completed baseline SDoH, comorbidity, and pregnancy questionnaires; and were followed prospectively. Social risk factors from SDoH baseline questionnaires, ZIP code poverty and household crowding measures, and a weighted score of 11 or higher on the Long COVID Research Index 6 months after infection. Among 3787 participants, 418 (11%) developed long COVID. After adjustment for demographic characteristics, pregnancy, disability, comorbidities, SARS-CoV-2 severity, and vaccinations, financial hardship (adjusted marginal risk ratio [ARR], 2.36 [95% CI, 1.97 to 2.91]), food insecurity (ARR, 2.36 [CI, 1.83 to 2.98]), less than a college education (ARR, 1.60 [CI, 1.30 to 1.97]), experiences of medical discrimination (ARR, 2.37 [CI, 1.94 to 2.83]), skipped medical care due to cost (ARR, 2.87 [CI, 2.22 to 3.70]), and lack of social support (ARR, 1.79 [CI, 1.50 to 2.17]) were associated with increased risk for long COVID. Living in ZIP codes with the highest (vs. lowest) household crowding was also associated with greater risk (ARR, 1.36 [CI, 1.05 to 1.71]). Selection bias may influence observed associations and generalizability. Participants with social risk factors at the time of SARS-CoV-2 infection had greater risk for subsequent long COVID than those without. Future studies should determine whether social risk factor interventions mitigate long-term effects of SARS-CoV-2 infection. National Institutes of Health.

ACAlicia Chung
Alicia Chung
PJPeng Jin
Peng Jin
DKDimitra Kamboukos
Dimitra Kamboukos
RRRebecca S. Robbins
Rebecca S. Robbins
JBJudite Blanc
Judite Blanc
Azizi SeixasAzizi Seixas
Azizi Seixas
Our study examines the acceptability and feasibility of Moshi, an audio-based mobile application, among children 3–8 years old using a parent–child dyadic approach. Our 10-day within-subject pre–post study design consisted of five nights of a normal bedtime routine and a subsequent five nights exposed to one story on the Moshi application during the intervention. Each five-night period spanned three weeknights and two weekend nights. The Short-Form Children’s Sleep Habits Questionnaire (SF-CSHQ) was used to measure children’s sleep at baseline and post-intervention. The PROMIS, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were used to assess parents’ sleep. Among the 25 child–parent dyads, the mean child age was 4 (SD = 1.23) and 63% were male (n = 15). Mean parent age was 35 (SD = 5.83), 84% were female (n = 21), and 48.0% were Black (n = 12). For child-only comparisons, mean post-SF-CSHQ measures were lower compared to baseline. A trend in parent sleep is reported. This study shows the potential of an audio-based mobile sleep aid to improve sleep health in a racially diverse parent and child dyad sample.

22 March 2019 in JMIR Pediatrics and Parenting
Verified
Journal Article
Open access
ACAlicia Chung
Alicia Chung
BWBarbara Wallace
Barbara Wallace
Monica Stanton KokoMonica Stanton Koko
Monica Stanton Koko
Azizi SeixasAzizi Seixas
Azizi Seixas
GJGirardin Jean-Louis
Girardin Jean-Louis
Background: African American youth (aged 8-14 years) do not adhere to national dietary and physical activity guidelines. Nonadherence to these recommendations contributes to disproportionate rates of obesity compared with their white counterparts. Culturally tailored electronic health (eHealth) solutions are needed to communicate nutrition and physical activity messages that resonate with this target population. Methods: Statistical analysis included paired sample t tests to evaluate knowledge gains, self-efficacy, and readiness to change. Adapted items from Prochaska’s Stages of Change toward the following 4 behaviors were assessed with pre- and posttest surveys: (1) fruit and vegetable selection on my plate, (2) meal preparation, (3) fruit and vegetable selection outside of home, and (4) physical activity. Open-ended comments on videos from mother-child dyads were used to determine user acceptance. Observations of repeated responses during content analysis informed coding and development of key themes. Results: A final sample size of 93 mother-child dyads completed the study. Mothers reported significant improvement from precontemplation or contemplation stages to preparation or action stages for (1) fruit and vegetable selection on her plate (P=.03), (2) meal preparation for her family (P=.01), (3) fruit and vegetable selection outside the home (P<.001), and (4) physical activity (P<.001). Significant improvements were found in knowledge, stage of change, and self-efficacy for the 4 target behaviors of interest (P<.001). Children’s open-ended commentary reported vicarious learning and positive character identification with brown-skinned cartoons exhibiting healthful food and exercise behaviors. Mothers commented on the lack of accessible produce in their neighborhoods not depicted in the cartoon videos. Conclusions: Culturally adapted cartoons that incorporate tailored preferences by African American families, such as race or demography, may help increase adherence to target health behaviors when developing eHealth behavior solutions.