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DTSTART:20241103T020000
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DESCRIPTION:Program: Health Informatics Information Technology Session: Ro
 und Table: Informatics and Telehealth Strategies Across Public Health Dis
 ciplines Author: Annie Ma See all authors and presenters → Abstract Backg
 round Cancer patients and caregivers often experience high levels of psyc
 hological distress\, yet scalable and context-appropriate mental health i
 nterventions remain limited\, particularly in low- and middle-income coun
 tries (LMICs) like Vietnam. Digital health applications offer a promising
  avenue to expand access to mental health and psychosocial support in the
 se settings. To address this critical gap\, we piloted a mobile app versi
 on of the World Health Organization’s Doing What Matters in Times of Stre
 ss: An Illustrated Guide. The app was designed to equip cancer-affected i
 ndividuals with foundational stress management skills. To optimize future
  implementation and ensure equitable reach\, we identified key participan
 t characteristics associated with greater psychological burden at baselin
 e. Objective To identify patient- and caregiver-level predictors of psych
 ological burden and cancer-related self-efficacy\, to inform the targetin
 g and tailoring of mHealth interventions in oncology contexts. Methods Pa
 rticipants were recruited through cancer networks\, clinics\, and online 
 outreach. Participants provided sociodemographic information during scree
 ning and completed baseline assessments measuring psychological distress 
 (NCCN Distress Thermometer)\, psychological adjustment such as “helplessn
 ess/hopelessness\,” “fighting spirit” (Mini-MAC)\, and self-efficacy (CBI
 B). Separate regression models for patients and caregivers were used to i
 dentify predictors of elevated psychological burden and maladaptive copin
 g profiles. Results Among patients (n=13)\, higher psychological distress
  and breast/gynecologic cancer (compared to other types) predicted greate
 r “helplessness and hopelessness”\; higher psychological distress and unm
 arried status predicted lower “fighting spirit”. Among caregivers (n=45)\
 , lower education and family caregiving roles were associated with reduce
 d self-efficacy. These predictors highlight distinct at-risk profiles wit
 hin each group. Conclusi ons These exploratory findings underscore the va
 lue of predictive analytics in implementing mHealth interventions. Identi
 fying high-burden subgroups can help optimize the design\, personalizatio
 n\, and outreach of interventions\, enhancing their impact and efficacy. 
 This approach supports a data-driven framework for scaling digital mental
  health tools in LMICs\, especially within the context of cancer care.\n\
 nSpeaker:\nAnnie Giman\n\nAdmission:\nRegistrationFees: APHA Event Regist
 ration is Required\n\nDetails URL:\nhttps://medicine.yale.edu/event/targe
 ting-psychosocial-support-through-mhealth-insights/\n
DTEND;TZID=America/New_York:20251105T100000
DTSTAMP:20260419T143913Z
DTSTART;TZID=America/New_York:20251105T083000
GEO:38.903500;-77.022987
LOCATION:801 Allen Y Lew Pl NW\, Washington\, DC\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:5029.1 - Targeting Psychosocial Support through mHealth: Insights 
 from a Mobile Stress Management App for Cancer-Affected Populations in Vi
 etnam
UID:609ada04-6d48-4aa6-823f-9df1645ea62f
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