Abstract
PURPOSE: This study aims to assess the prevalence of weight training content across various demographics as well as public attitudes toward weight training using social media as a proxy for organic sentiment. METHODS: A cross-sectional analysis was conducted using the hashtags #pregnancystrengthtraining (#PST) and #pregnancyweightlifting (#PWL). A new Instagram account was created, and two independent reviewers analyzed the first 100 posts under each hashtag. One hundred sixty-nine posts met inclusion criteria and were analyzed. Each post was evaluated for the demographics of the content creator (skin color, influencer type, professional background, and geographic region) and the sentiment of associated comments. FINDINGS: Sentiment analysis was performed using two natural language processors (NLP): ChatGPT-3.5 and MonkeyLearn. For both #PSL and #PWL, both NLPs were able to identify majority positive sentiment under analyzed posts. Posts from Europe and lighter skin toned influencers dominated top results, but posts were relatively well-distributed across the follower size and profession of the influencer. In general, analysis of #PWL yielded a lower percentage of positive-sentiment comments when compared to #PST. This trend held regardless of skin tone, occupation of influencer, follower count, or global region, though small sample sizes within each category limited statistical significance for these subgroups. DISCUSSION: Sentiment toward pregnancy-related weight training content on Instagram is largely positive across both hashtags. Given the demographic consistency shown in our results (despite lower sample sizes in some skin tones), social media attitudes may reflect larger societal beliefs regarding strength training during pregnancy as a positive endeavor. Because top posts did not have a significant correlation to follower count, providing hashtag-based health guidance may be an achievable way for the healthcare community to interact with pregnant women regarding healthy lifestyle behaviors.