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Natural Observation of Alcohol Price and Promotions at Bars: Implications for Alcohol Misuse Prevention.

Melissa J CoxMeredith MoskwiakBeth H ChaneyMadison Garrigues
Published in: Health education & behavior : the official publication of the Society for Public Health Education (2021)
Alcohol misuse among young adults remains a primary public health concern given the wide range of short- and long-term physical, social, and societal consequences of the behavior. On-premise drinking establishments, which allow alcohol consumption on site (i.e., bars), are frequent locations for young adult alcohol use. Risks for alcohol misuse within the bar setting are key factors to identify for prevention. Notably, alcohol price and promotions are associated with alcohol consumption among young adults. This study sought to develop and pilot test an observational protocol to assess the alcohol environment at on-premise drinking establishments. Following qualitative exploration of salient risk factors in these settings through focus groups with young adults, an observational tool was adapted and tested in a feasibility study. The refined tool was then pilot tested with two independent data collectors conducting natural observation at 13 establishments in the downtown nightlife district of a small, southeastern city. High interrater reliability was noted. Descriptive summary statistics of bar characteristics demonstrate low alcohol prices with variability across types of alcohol (e.g., beer, wine, and liquor), greater numbers of alcohol promotions inside rather than outside the building, and higher rates of manual versus electronic age verification procedures. Observational assessment of alcohol price and marketing at on-premise drinking establishments as described in this study is needed to inform prevention policy and programs to reduce harms associated with young adult alcohol misuse.
Keyphrases
  • alcohol consumption
  • young adults
  • public health
  • risk factors
  • healthcare
  • chronic pain
  • mental health
  • randomized controlled trial
  • cross sectional
  • artificial intelligence
  • childhood cancer
  • big data