Qualitative analysis of Korean immigrant women's alcohol use

The July 14, 2026 PLOS ONE scoping review identified only seven eligible primary studies, all U.S.-based, and three recurring sociocultural themes: acculturation, religion, and social networks.

Evidano is an AI-powered qualitative data analysis platform that ingests documents, extracts themes, compares segments, and exports visuals and clickable quotes to produce reproducible, stakeholder-ready evidence.

• Seven eligible primary studies were included, six published before 2014 and one in 2022; the database search was last run on May 20, 2025.
• Acculturation associations were inconsistent across studies because researchers operationalised acculturation with different measures (language, identity, time in country).
• Religion and congregational peer influence often appeared protective in some samples, but effects varied by denomination.
• A reproducible 8-step AI-enabled workflow can convert articles and transcripts into a validated codebook, cross-segment analyses, and exportable visuals and quotes within days.

The scoping review mapped peer-reviewed literature about alcohol use among Korean immigrant women and found only seven eligible primary studies. The scoping review reported three cross-cutting sociocultural influences: acculturation, religion, and social networks, and noted plausible but under-investigated contexts such as immigration stress, patriarchal norms, and structural discrimination.

• All included studies were U.S.-based despite a wider country scope in the search.
• Acculturation showed inconsistent associations, differences stem from varying operational definitions.
• Religion and congregational peer influence appeared protective in some samples but varied by denomination.
• Social rituals and proximity to Korean bars were reported as situational drivers for drinking.

The review can be operationalized with a reproducible 8-step AI-enabled workflow that turns documents and transcripts into actionable insights.

• 1) Gather corpus: import the seven articles, related gray literature, interview transcripts, and survey CSVs into Evidano.
• 2) Preprocess: auto-transcribe interviews with custom dictionary entries for Korean terms and redact personally identifiable information where needed.
• 3) Translate and normalize: run optional translation with a custom dictionary to maintain cultural terms like 'jeong' or 'baek-il'.
• 4) Initial coding: upload or create a seed codebook for Acculturation, Religion, Social networks, Immigration stress, and Gender norms.
• 5) AI-assisted coding: apply AI-assisted thematic coding across the corpus using the Evidano thematic engine, then manually validate and refine through iterative active learning.
• 6) Cross-segment analysis: compare themes by generation, denomination, and acculturation level using cross-segment frequency tables and co-occurrence networks.
• 7) Visualize and extract: generate word clouds, hierarchical theme→subcode trees, and export clickable quote sets for stakeholder briefs.
• 8) Deliver: produce an exportable report and a short slide deck highlighting evidence gaps, policy implications, and suggested interventions.

Ethics note: this post describes research workflows only. For primary data collection ensure informed consent, anonymisation, and culturally appropriate participant supports; outputs are for research and policy use, not clinical diagnosis.

The checklist lists minimum data items and metadata to collect to make analyses comparable and reusable.

• Participant nativity and generation (first, 1.5, second)
• Languages used regularly and at home
• Religious affiliation and level of congregational engagement
• Contextual notes on celebratory rituals and proximity to community venues
• Validated measures for acculturation and immigration-related stress
• Standardized timestamps and location metadata for geographic cross-comparisons

To wrap up, start with a reproducible corpus and a clear codebook that separates acculturation components when you synthesise the PLOS ONE scoping review or launch primary qualitative work. Use AI to accelerate coding while keeping community consultation in the loop to validate interpretations.

• Step 1: Download the review from PLOS ONE and list the key measures you need to harmonize.
• Step 2: Run a 2-week pilot in Evidano with a small set of transcripts and the seven articles to build and validate your codebook.
• Step 3: Produce a short stakeholder brief with clickable quotes and co-occurrence visuals for your community engagement session.

Ready to convert scattered studies and interviews into decision-ready evidence? Start a pilot and get a reproducible thematic and cross-segment analysis in days: Try Evidano for free.