Use of the Instagram Hashtags #winemom and #momjuice Among Mothers During the COVID-19 Pandemic: Descriptive, Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: The tendency of parents to consume alcohol during the COVID-19 pandemic is likely to be moderated by pandemic-related stress combined with the ongoing demands of childcare and home-based education, which are reported to be more burdensome for females than males. OBJECTIVE: The purpose of this study was to describe alcohol-related content posted by mothers on Instagram during the COVID-19 pandemic. METHODS: Using two popular hashtags, #momjuice and #winemom, 50 Instagram posts on each were collected from the "top posts" tab. The coding categories were created inductively and were as follows: displays alcohol (drinking/holding alcohol or alcohol itself), person is making alcoholic beverages, type of alcohol featured or discussed, highlights anxiety and/or depression/mental state, highlights struggling (in general), highlights parenting challenges, encourages alcohol consumption, discourages alcohol consumption, features a person wearing clothing or shows products promoting alcohol, promotes alcohol rehabilitation, highlights caffeine to alcohol daily transition throughout the day, and highlights other drugs besides caffeine and alcohol. RESULTS: Overall, the 100 selected posts had a total of 5108 comments and 94,671 likes. The respective averages were 51.08 (SD 77.94) and 946.71 (SD 1731.72). A majority (>50%) of the posts reviewed encouraged alcohol consumption (n=66) and/or displayed alcohol (n=56). Of the 66 that encouraged and/or displayed alcohol, the common type of alcohol discussed or featured was wine (n=55). Only 6 posts discouraged alcohol use and only 4 provided the audience with a disclaimer. None of the videos promoted or endorsed alcohol rehabilitation in any way. Only 37 posts highlighted struggle. However, these posts garnered more than a majority of the likes (n=50,034, 52.3%). Posts that showed struggle received an average of 1359.57 (SD 2108.02) likes. Those that did not show struggle had an average of 704.24 (SD 1447.46) likes. An independent one-tailed t test demonstrated this difference to be statistically significant (P=.0499). CONCLUSIONS: The findings of this investigation suggest that though these hashtags ostensibly exist to valorize excess alcohol consumption, they may be serving as a support system for mothers who are experiencing increased burdens and role stress during the pandemic. Given the strains placed on mothers overall and especially during the COVID-19 pandemic, efforts must be taken to increase access to and affordability of telehealth-based mental health care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".