Understanding Mental Health Organizations’ Instagram Through Visuals: A Content Analysis

References

• Adami, E., & Jewitt, C. (2016). Social media and the visual. Visual Communication, 15(3), 263–270. https://doi.org/10.1177/1470357216644153
   Web of Science ®Google Scholar
• Alhabash, S., & McAlister, A. R. (2015). Redefining virality in less broad strokes: Predicting viral behavioral intentions from motivations and uses of Facebook and Twitter. New Media & Society, 17(8), 1317–1339. https://doi.org/10.1177/1461444814523726
   Web of Science ®Google Scholar
• Auxier, B., & Anderson, M. (2021, April 7). Social media use in 2021. Pew Research Center. https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/
   Google Scholar
• Beasley, L., Kiser, R., & Hoffman, S. (2020). Mental health literacy, self-efficacy, and stigma among college students. Social Work in Mental Health, 18(6), 634–650. https://doi.org/10.1080/15332985.2020.1832643
   Web of Science ®Google Scholar
• Blanco, C. F., Sarasa, R. G., & Sanclemente, C. O. (2010). Effects of visual and textual information in online product presentations: Looking for the best combination in website design. European Journal of Information Systems, 19(6), 668–686. https://doi.org/10.1057/ejis.2010.42
   Web of Science ®Google Scholar
• Box, G. E. P., & Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society, 26, 211–252. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x
   Google Scholar
• Cappella, J. N., Kim, H. S., & Albarracín, D. (2015). Selection and transmission processes for information in the emerging media environment: Psychological motives and message characteristics. Media Psychology, 18(3), 396–424. https://doi.org/10.1080/15213269.2014.941112
   PubMed Web of Science ®Google Scholar
• Centers for Decease Control and Prevention. (2021, October 13). COVID-19 toolkits. Retrieved December 12, 2021, from https://www.cdc.gov/coronavirus/2019- ncov/communication/social-media-toolkit.html
   Google Scholar
• Chalmers, A. W., & Shotton, P. A. (2016). Changing the face of advocacy? Explaining interest organizations’ use of social media strategies. Political Communication, 33(3), 374–391. https://doi.org/10.1080/10584609.2015.1043477
   Web of Science ®Google Scholar
• Chavira, D. A., Ponting, C., & Ramos, G. (2022). The impact of COVID-19 on child and adolescent mental health and treatment considerations. Behaviour Research and Therapy, 157, 1–8. https://doi.org/10.1016/j.brat.2022.104169
   Web of Science ®Google Scholar
• Cheng, H.-L., Wang, C., McDermott, R. C., Kridel, M., & Rislin, J. L. (2018). Self-stigma, mental health literacy, and attitudes toward seeking psychological help. Journal of Counseling & Development, 96(1), 64–74. https://doi.org/10.1002/jcad.12178
   Web of Science ®Google Scholar
• Crowe, A., Mullen, P. R., & Littlewood, K. (2018). Self-stigma, mental health literacy, and health outcomes in integrated care. Journal of Counseling & Development, 96(3), 267–277. https://doi.org/10.1002/jcad.12201
   Web of Science ®Google Scholar
• Eaton, N. R., Keyes, K. M., Krueger, R. F., Balsis, S., Skodol, A. E., Markon, K. E., Grant, B. F., & Hasin, D. S. (2012). An invariant dimensional liability model of gender differences in mental disorder prevalence: Evidence from a national sample. Journal of Abnormal Psychology, 121(1), 282–288. https://doi.org/10.1037/a0024780
   PubMed Web of Science ®Google Scholar
• Edelman. (2022, January 24). 2022 Edelman trust Barometer. Retrieved December 22, 2022, from https://www.edelman.com/trust/2022-trust-barometer
   Google Scholar
• Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58. https://doi.org/10.1111/j.1460-2466.1993.tb01304.x
   Web of Science ®Google Scholar
• Feuston, J. L., & Piper, A. M. (2018). Beyond the coded gaze: Analyzing expression of mental health and illness on instagram. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1–21. https://doi.org/10.1145/3274320
   Google Scholar
• Feuston, J. L., & Piper, A. M. (2019, May). Everyday experiences: Small stories and mental illness on Instagram. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1–14). https://doi.org/10.1145/3290605.3300495
   Google Scholar
• Fox, J., & Weisberg, S. (2019). An R companion to applied regression (3rd ed.). Sage.
   Google Scholar
• Friess, E., & Lam, C. (2018). Cultivating a sense of belonging: Using Twitter to establish a community in an introductory technical communication classroom. Technical Communication Quarterly, 27(4), 343–361. https://doi.org/10.1080/10572252.2018.1520435
   Web of Science ®Google Scholar
• Furnham, A., & Swami, V. (2018). Mental health literacy: A review of what it is and why it matters. International Perspectives in Psychology, 7(4), 240–257. https://doi.org/10.1037/ipp0000094
   Google Scholar
• Gibson, R., & Zillmann, D. (2000). Reading between the photographs: The influence of incidental pictorial information on issue perception. Journalism & Mass Communication Quarterly, 77(2), 355–366. https://doi.org/10.1177/107769900007700209
   Web of Science ®Google Scholar
• Griffith, F. J., Stein, C. H., Hoag, J. E., & Gay, K. N. (2021). # MentalHealthArt: How Instagram artists promote mental health awareness online. Public Health, 194, 67–74. https://doi.org/10.1016/j.puhe.2021.02.006
   PubMed Web of Science ®Google Scholar
• Guillén, U., Suh, S., Munson, D., Posencheg, M., Truitt, E., Zupancic, J. A., Gafni, A., & Kirpalani, H. (2012). Development and pretesting of a decision aid to use when counseling parents facing imminent extreme premature delivery. The Journal of Pediatrics, 160(3), 382–387. https://doi.org/10.1016/j.jpeds.2011.08.070
   PubMed Web of Science ®Google Scholar
• Gupta, R., & Ariefdjohan, M. (2021). Mental illness on Instagram: A mixed method study to characterize public content, sentiments, and trends of antidepressant use. Journal of Mental Health, 30(4), 518–525. https://doi.org/10.1080/09638237.2020.1755021
   PubMed Web of Science ®Google Scholar
• Hawkins, D., & Weisberg, S. (2017). Combining the Box-Cox power and generalized log transformations to accommodate nonpositive responses in linear and mixed-effects linear models. South African Statistics Journal, 51(2), 317–328. https://doi.org/10.37920/sasj.2017.51.2.5
   Google Scholar
• Hong, W., Thong, L., & Tamk, Y. (2004). Designing product listing pages on e-commerce websites: An examination of presentation mode and information format. International Journal of Human-Computer Studies, 61(4), 481–503. https://doi.org/10.1016/j.ijhcs.2004.01.006
   Web of Science ®Google Scholar
• Huang, Y. C., Lin, Y. P., & Saxton, G. D. (2016). Give me a like: How HIV/AIDS nonprofit organizations can engage their audience on Facebook. AIDS Education and Prevention, 28(6), 539–556. https://doi.org/10.1521/aeap.2016.28.6.539
   PubMed Web of Science ®Google Scholar
• “Instagram Demographics in 2022: Most Important User Stats for Marketers”. (2022, March 24). Social media marketing & management dashboard. https://bloghootsuite.com/instagram-demographics/
   Google Scholar
• Ivey-Stephenson, A. Z., Crosby, A. E., Jack, S. P., Haileyesus, T., & Kresnow-Sedacca, M. J. (2017). Suicide trends among and within urbanization levels by sex, race/ethnicity, age group, and mechanism of death—United States, 2001–2015. MMWR Surveillance Summaries, 66(18), 1–16. https://doi.org/10.15585/mmwr.ss6618a1
   PubMed Web of Science ®Google Scholar
• Jorm, A. F. (2012). Mental health literacy: Empowering the community to take action for better mental health. The American Psychologist, 67(3), 231–243. https://doi.org/10.1037/a0025957
   PubMed Web of Science ®Google Scholar
• Jorm, A. F. (2015). Why we need the concept of “mental health literacy”. Health Communication, 30(12), 1166–1168. https://doi.org/10.1080/10410236.2015.1037423
   PubMed Web of Science ®Google Scholar
• Jorm, A. F., Korten, A. E., Jacomb, P. A., Christensen, H., Rodgers, B., & Pollitt, P. (1997). “Mental health literacy”: A survey of the public’s ability to recognise mental disorders and their beliefs about the effectiveness of treatment. Medical Journal of Australia, 166(4), 182–186. https://doi.org/10.5694/j.1326-5377.1997.tb140071.x
   PubMed Web of Science ®Google Scholar
• Ju, R., Dong, C., & Zhang, Y. (2021). How controversial businesses communicate CSR on Facebook: Insights from the Canadian cannabis industry. Public Relations Review, 47(4), 102059. https://doi.org/10.1016/j.pubrev.2021.102059
   Web of Science ®Google Scholar
• Ju, R., Jia, M., & Cheng, J. (2021). Promoting mental health on social media: A content analysis of organizational Tweets. Health Communication. Advance online publication. https://doi.org/10.1080/10410236.2021.2018834
   Google Scholar
• Kearney, M. D., Selvan, P., Hauer, M. K., Leader, A. E., & Massey, P. M. (2019). Characterizing HPV vaccine sentiments and content on Instagram. Health Education & Behavior, 46(25), 375–485. https://doi.org/10.1177/1090198119859412
   Google Scholar
• Keib, K., Himelboim, I., & Han, J. Y. (2018). Important tweets matter: Predicting retweets in the# BlackLivesMatter talk on twitter. Computers in Human Behavior, 85, 106–115. https://doi.org/10.1016/j.chb.2018.03.025
   Web of Science ®Google Scholar
• Kim, H. C. (2021). Mediating effect of stigma on the relationship between mental health literacy and help-seeking attitudes among university students in South Korea. International Journal of Mental Health. Advance online publication. https://doi.org/10.1080/00207411.2021.1965397
   Web of Science ®Google Scholar
• Kim, H. S. (2015). Attracting views and going viral: How message features and news-sharing channels affect health news diffusion. Journal of Communication, 65(3), 512–534. https://doi.org/10.1111/jcom.12160
   PubMed Web of Science ®Google Scholar
• Kim, Y., & Kim, J. H. (2020). Using photos for public health communication: A computational analysis of the Centers for Disease Control and Prevention Instagram photos and public responses. Health Informatics Journal, 26(3), 2159–2180. https://doi.org/10.1177/1460458219896673
   PubMed Web of Science ®Google Scholar
• King, A. J. (2015). A content analysis of visual cancer information: Prevalence and use of photographs and illustrations in printed health materials. Health Communication, 30(7), 722–731. https://doi.org/10.1080/10410236.2013.878778
   PubMed Web of Science ®Google Scholar
• King, A. J. (2016). Visual exemplification and skin cancer: The utility of exemplars in promoting skin self-exams and atypical nevi identification. Journal of Health Communication, 21, 826–836. https://doi.org/10.1080/10810730.2016.1177143
   PubMed Web of Science ®Google Scholar
• King, A. J., & Lazard, A. J. (2020). Advancing visual health communication research to improve infodemic response. Health Communication, 35(14), 1723–1728. https://doi.org/10.1080/10410236.2020.1838094
   PubMed Web of Science ®Google Scholar
• Krippendorff, K. (2018). Content analysis: An introduction to its methodology. Sage publications.
   Google Scholar
• Kutcher, S., Wei, Y., & Coniglio, C. (2016). Mental health literacy: Past, present, and future. Canadian Journal of Psychiatry. Revue canadienne de psychiatrie, 61(3), 154–158. https://doi.org/10.1177/0706743715616609
   Google Scholar
• Lacy, S., Watson, B. R., Riffe, D., & Lovejoy, J. (2015). Issues and best practices in content analysis. Journalism & Mass Communication Quarterly, 92(4), 791–811. https://doi.org/10.1177/1077699015607338
   Web of Science ®Google Scholar
• Lama, Y., Chen, T., Dredze, M., Jamison, A., Quinn, S. C., & Broniatowski, D. A. (2018). Discordance between human papillomavirus Twitter images and disparities in human papillomavirus risk and disease in the United States: Mixed-methods analysis. Journal of Medical Internet Research, 20(9). https://doi.org/10.2196/10244
   Web of Science ®Google Scholar
• Lee, J., & Xu, W. (2018). The more attacks, the more retweets: Trump’s and Clinton’s agenda setting on Twitter. Public Relations Review, 44(2), 201–213. https://doi.org/10.1016/j.pubrev.2017.10.002
   Web of Science ®Google Scholar
• Lee, N., Buchanan, K., & Yu, M. (2020). Each post matters: A content analysis of #mentalhealth images on Instagram. Journal of Visual Communication in Medicine, 43(3), 128–138. https://doi.org/10.1080/17453054.2020.1781535
   PubMed Web of Science ®Google Scholar
• Lovejoy, K., & Saxton, G. D. (2012). Information, community, and action: How nonprofit organizations use social media. Journal of Computer-Mediated Communication, 17(3), 337–353. https://doi.org/10.1111/j.1083-6101.2012.01576.x
   Web of Science ®Google Scholar
• Luarn, P., Lin, Y.-F., & Chiu, Y.-P. (2015). Influence of Facebook brand-page posts on online engagement. Online Information Review, 39(4), 505–519. https://doi.org/10.1108/OIR-01-2015-0029
   Web of Science ®Google Scholar
• Martin, L., Turnquist, A., Groot, B., Huang, S., Kok, E., Thoma, B., & Merrienboer, J. (2019). Exploring the role of infographics for summarizing medical literature. Health Professions Education, 5(1), 48–57. https://doi.org/10.1016/j.hpe.2018.03.005
   Google Scholar
• McCosker, A., & Gerrard, Y. (2021). Hashtagging depression on Instagram: Towards a more inclusive mental health research methodology. New Media & Society, 23(7), 1899–1919. https://doi.org/10.1177/1461444820921349
   Web of Science ®Google Scholar
• McLachlan, S. (2022, March 24). Instagram demographic in 2023: Most important user stats for marketers. Hootsuite.https://blog.hootsuite.com/instagram-demographics/
   Google Scholar
• Men, L. R., & Tsai, W. H. S. (2012). How companies cultivate relationships with publics on social network sites: Evidence from China and the United States. Public Relations Review, 38(5), 723–730. https://doi.org/10.1016/j.pubrev.2011.10.006
   Web of Science ®Google Scholar
• Men, L. R., & Tsai, W. H. S. (2014). Perceptual, attitudinal, and behavioral outcomes of organization–public engagement on corporate social networking sites. Journal of Public Relations Research, 26(5), 417–435. https://doi.org/10.1080/1062726X.2014.951047
   Web of Science ®Google Scholar
• Mental and Behavioral Health - African Americans. (2021, May 18). U.S Department of Health and Human Services Office of Minority Health. Retrieved December 12, 2021, from https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=24
   Google Scholar
• Mental health by the numbers. (2019, September). https://www.nami.org/learn-more/mental-health-by-the-numbers
   Google Scholar
• Messaris, P. (1997). Visual persuasion: The role of images in advertising. Sage.
   Google Scholar
• Munzert, S., Rubba, C., Meißner, P., & Nyhuis, D. (2014). Automated data collection with R: A practical guide to web scraping and text mining. John Wiley & Sons.
   Google Scholar
• Nan, X., Iles, I. A., Yang, B., & Ma, Z. (2022). Public health messaging during the COVID-19 pandemic and beyond: Lessons from communication science. Health Communication, 37(1), 1–19. https://doi.org/10.1080/10410236.2021.1994910
   PubMed Web of Science ®Google Scholar
• Nobles, A. L., Leas, E. C., Noar, S., Dredze, M., Latkin, C. A., Strathdee, S. A., & Ayers, J. W. (2020). Automated image analysis of instagram posts: Implications for risk perception and communication in public health using a case study of# HIV. PLoS One, 15(5). https://doi.org/10.1371/journal.pone.0231155
   Web of Science ®Google Scholar
• Ophir, Y., Brennan, E., Maloney, E. K., & Cappella, J. N. (2019). The effects of graphic warning labels’ vividness on message engagement and intentions to quit smoking. Communication Research, 46(5), 619–638. https://doi.org/10.1177/0093650217700226
   Web of Science ®Google Scholar
• Paivio, A. (1986). Mental representations: A dual coding approach. Oxford University Press.
   Google Scholar
• Pavlova, A., & Berkers, P. (2022). “Mental health” as defined by Twitter: Frames, emotions, stigma. Health Communication, 37(5), 637–647. https://doi.org/10.1080/10410236.2020.1862396
   PubMed Web of Science ®Google Scholar
• Pirkis, J., Schlichthorst, M., King, K., Lockley, A., Keogh, L., Reifels, L., Spittal, M. J., & Phelps, A. (2019). Looking for the ‘active ingredients’ in a men’s mental health promotion intervention. Advances in Mental Health, 17(2), 135–145. https://doi.org/10.1080/18387357.2018.1526095
   Web of Science ®Google Scholar
• Pope, J. P., Pelletier, L., & Guertin, C. (2018). Starting off on the best foot: A review of message framing and message tailoring, and recommendations for the comprehensive messaging strategy for sustained behavior change. Health Communication, 33(9), 1068–1077. https://doi.org/10.1080/10410236.2017.1331305
   PubMed Web of Science ®Google Scholar
• Rodriguez, L., & Dimitrova, D. V. (2011). The levels of visual framing. Journal of Visual Literacy, 30(1), 48–65. https://doi.org/10.1080/23796529.2011.11674684
   Google Scholar
• Ross, S. G., Bruggeman, B., Maldonado, M., & Deiling, M. (2020). Examining personal, perceived, treatment, and self-stigma in college students: The role of parent beliefs and mental health literacy. Journal of College Student Psychotherapy, 34(3), 183–197. https://doi.org/10.1080/87568225.2019.1580657
   Web of Science ®Google Scholar
• Sadoski, M., & Paivio, A. (2004). A dual coding theoretical model of reading. In B. Ruddellr & J. Unraun (Eds.), Theoretical models and processes of reading (5th ed., pp. 1329–1362). International Reading Association.
   Google Scholar
• Saxton, G. D., & Waters, R. D. (2014). What do stakeholders like on Facebook? Examining public reactions to nonprofit organizations’ informational, promotional, and community-building messages. Journal of Public Relations Research, 26(3), 280–299. https://doi.org/10.1080/1062726X.2014.908721
   Web of Science ®Google Scholar
• Seelig, M. I., Millette, D., Zhou, C., & Huang, J. (2019). A new culture of advocacy: An exploratory analysis of social activism on the web and social media. Atlantic Journal of Communication, 27(1), 15–29. https://doi.org/10.1080/15456870.2019.1540418
   Web of Science ®Google Scholar
• Seventy-Fourth World Health Assembly. (2021). Comprehensive mental health action plan 2013-2030 (Agenda item 13.3). https://www.who.int/publications/i/item/9789240031029
   Google Scholar
• Sixty-Six World Health Assembly. (2013). Comprehensive mental health action plan 2013-2020 (Agenda item 13.3). https://www.who.int/mental_health/publications/action_plan/en/
   Google Scholar
• Tay, J. L., Tay, Y. F., & Klainin, Y. P. (2018). Effectiveness of information and communication technologies interventions to increase mental health literacy: A systematic review. Early Intervention in Psychiatry, 12(6), 1024–1037. https://doi.org/10.1111/eip.12695
   PubMed Web of Science ®Google Scholar
• United Nations. (2020, May 13). COVID-19 and the need for action on mental health; policy brief. https://unsdg.un.org/resources/policy-brief-covid-19-and-need-action-mental-health,2020
   Google Scholar
• Wei, Y., Baxter, A., & Kutcher, S. (2019). Establishment and validation of a mental health literacy measurement in Canadian educators. Psychiatry Research, 279, 231–236. https://doi.org/10.1016/j.psychres.2019.03.009
   PubMed Web of Science ®Google Scholar
• Wei, Y., McGrath, P. J., Hayden, J., & Kutcher, S. (2015). Mental health literacy measures evaluating knowledge, attitudes and help-seeking: A scoping review. BMC Psychiatry, 15(1), 291. https://doi.org/10.1186/s12888-015-0681-9
   PubMed Web of Science ®Google Scholar
• World Health Organization. (2022, March 2). Mental health and COVID-19: Early evidence of the pandemic's impact: Scientific brief. https://www.who.int/publications/i/item/WHO-2019-nCoV-Sci_Brief-Mental_health-2022.1
   Google Scholar
• Wynaden, D., Chapman, R., Orb, A., McGowan, S., Zeeman, Z., & Yeak, S. (2005). Factors that influence Asian communities’ access to mental health care. International Journal of Mental Health Nursing, 14(2), 88–95. https://doi.org/10.1111/j.1440-0979.2005.00364.x
   PubMed Web of Science ®Google Scholar
• Yang, A., & Kent, M. (2014). Social media and organizational visibility: A sample of Fortune 500 corporations. Public Relations Review, 40(3), 562–564. https://doi.org/10.1016/j.pubrev.2014.04.006
   Web of Science ®Google Scholar
• Yoo, W. (2016). The influence of celebrity exemplars on college students’ smoking. Journal of American College Health, 64(1), 48–60. https://doi.org/10.1080/07448481.2015.1074238
   PubMed Web of Science ®Google Scholar