The Reel Health Care Professionals of Instagram: A Systematic Review.
Krestina L AmonMelissa BrunnerAndrew J CampbellPublished in: Cyberpsychology, behavior and social networking (2024)
Social media and health research have covered the benefits for the public and patients as users. Specifically, this has focused on searching for health information, connecting with others experiencing similar health issues, and communicating with their health professionals. Recently, there has been a shift in research to focus on health care professionals as users as they participate in professional development, improve communication with patients, and contribute to health research and service. However, such research has predominantly focused on text-based platforms, namely Facebook and Twitter. The scope of this article is a systematic review of publications on health care professionals' use of the image-based platform Instagram, according to the preferred reporting items for systematic reviews and meta-analyses guidelines. This study, drawing from 51 articles, shows how health care professionals use Instagram, and reveals that these professionals utilize the platform to address health concerns that may not necessarily align with their specific expertise. Images were the common format of posts created by health care professionals, with six content types identified: (a) educational, (b) promotional, (c) patient experience, (d) personal, (e) emotion based, and (f) other. Three measures of post engagement were used by researchers, including (a) likes and comments, (b) use of hashtags, and (c) number of followers. This study also identified the dangers of misleading users, including (a) lack of credentials reported, (b) edited images, (c) quality of content, and (d) patient and client confidentiality issues. In conclusion, insights into the advantages of health care professionals' use of Instagram and ways in which they can maximize its use to reach and engage with their target audience are provided.
Keyphrases
- healthcare
- social media
- health information
- end stage renal disease
- systematic review
- chronic kidney disease
- newly diagnosed
- ejection fraction
- deep learning
- mental health
- prognostic factors
- randomized controlled trial
- risk assessment
- emergency department
- convolutional neural network
- depressive symptoms
- african american
- case report
- health insurance
- affordable care act