The Association between Types of COVID-19 Information Source and the Avoidance of Child Health Checkups in Japan: Findings from the JACSIS 2021 Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Setting
2.2. Measurements
2.3. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Weber, P.; Jenni, O. Screening in child health: Studies of the efficacy and relevance of preventive care practices. Dtsch. Arztebl. Int. 2012, 109, 431–435. [Google Scholar] [CrossRef] [PubMed]
- Healthy Parents and Children 21. Available online: https://sukoyaka21.mhlw.go.jp/ (accessed on 30 March 2022).
- Ministry of Health, Labour and Welfare. From Pregnancy through to Child-Rearing in Japan—Guide to Necessary Procedures and Available Services (Research and Study Project for the Promotion of Child and Child Rearing Support in 2019). Available online: https://www.mhlw.go.jp/content/11900000/guide_EN.pdf (accessed on 25 April 2022).
- Ministry of Health, Labour and Welfare. Summary of Reports on Community Health and Health Promotion Programs in 2019. Available online: https://www.mhlw.go.jp/toukei/saikin/hw/c-hoken/19/dl/R01gaikyo.pdf (accessed on 6 April 2022).
- Magnusson, M.; Persson, K.; Sundelin, C. The effectiveness of routine health examinations at 2, 6, 9 and 12 months of age: Experiences based on data from a Swedish county. Child Care Health Dev. 2001, 27, 117–131. [Google Scholar] [CrossRef] [PubMed]
- Mackrides, P.S.; Ryherd, S.J. Screening for developmental delay. Am. Fam. Physician 2011, 84, 544–549. [Google Scholar] [PubMed]
- Lebrun-Harris, L.A.; Sappenfield, O.R.; Warren, M.D. Missed and Delayed Preventive Health Care Visits Among US Children Due to the COVID-19 Pandemic. Public Health Rep. 2022, 137, 336–343. [Google Scholar] [CrossRef]
- Al-Kuwari, M.G.; Abdulmalik, M.A.; Al-Mudahka, H.R.; Bakri, A.H.; Al-Baker, W.A.; Abushaikha, S.S.; Kandy, M.C.; Gibb, J. The impact of COVID-19 pandemic on the preventive services in Qatar. J. Public Health Res. 2021, 10, 1910. [Google Scholar] [CrossRef]
- Mert Doğan, G.; Aslantürk, O. Does the COVID-19 pandemic cause late diagnosis and delay in treatment in developmental dysplasia of hip patients? Int. J. Clin. Pract. 2021, 75, e14572. [Google Scholar] [CrossRef]
- Watson, G.; Pickard, L.; Williams, B.; Hargreaves, D.; Blair, M. ‘Do I, don’t I?’ A qualitative study addressing parental perceptions about seeking healthcare during the COVID-19 pandemic. Arch. Dis. Child. 2021, 106, 1118–1124. [Google Scholar] [CrossRef]
- Zarocostas, J. How to fight an infodemic. Lancet 2020, 395, 676. [Google Scholar] [CrossRef]
- Liu, B.F.; Fraustino, J.D.; Jin, Y. Social Media Use During Disasters: How Information Form and Source Influence Intended Behavioral Responses. Commun. Res. 2015, 43, 626–646. [Google Scholar] [CrossRef] [Green Version]
- Dubey, S.; Biswas, P.; Ghosh, R.; Chatterjee, S.; Dubey, M.J.; Lahiri, D.; Lavie, C.J. Psychosocial impact of COVID-19. Diabetes Metab. Syndr. 2020, 14, 779–788. [Google Scholar] [CrossRef]
- Cinelli, M.; Quattrociocchi, W.; Galeazzi, A.; Valensise, C.M.; Brugnoli, E.; Schmidt, A.L.; Zola, P.; Zollo, F.; Scala, A. The COVID-19 social media infodemic. Sci. Rep. 2020, 10, 16598. [Google Scholar] [CrossRef] [PubMed]
- Gallegati, S.; Aquilanti, L.; Temperini, V.; Polinesi, G.; Rappelli, G. The Impact of Coronavirus Information-Seeking Behavior on Dental Care Access: A Cross-Sectional Questionnaire-Based Study. Int. J. Environ. Res. Public Health 2021, 18, 12050. [Google Scholar] [CrossRef] [PubMed]
- Alshareef, N.; Yunusa, I.; Al-Hanawi, M.K. The Influence of COVID-19 Information Sources on the Attitudes and Practices Toward COVID-19 Among the General Public of Saudi Arabia: Cross-sectional Online Survey Study. JMIR Public Health Surveill. 2021, 7, e28888. [Google Scholar] [CrossRef] [PubMed]
- Hosokawa, Y.; Okawa, S.; Hori, A.; Morisaki, N.; Takahashi, Y.; Fujiwara, T.; Nakayama, S.F.; Hamada, H.; Satoh, T.; Tabuchi, T. The prevalence of COVID-19 vaccination and vaccine hesitancy in pregnant women: An internet-based cross-sectional study in Japan. J. Epidemiol. 2022, 32, 188–194. [Google Scholar] [CrossRef]
- About Us Rakuten Insight. Available online: https://insight.rakuten.co.jp/en/aboutus.html (accessed on 17 July 2022).
- Ministry of Health, Labour and Welfare. Situation Report. Available online: https://www.mhlw.go.jp/stf/covid-19/kokunainohasseijoukyou_00006.html (accessed on 3 August 2022).
- Okubo, R.; Yoshioka, T.; Ohfuji, S.; Matsuo, T.; Tabuchi, T. COVID-19 Vaccine Hesitancy and Its Associated Factors in Japan. Vaccines 2021, 9, 662. [Google Scholar] [CrossRef]
- Zaitsu, M.; Hosokawa, Y.; Okawa, S.; Hori, A.; Kobashi, G.; Tabuchi, T. Heated tobacco product use and hypertensive disorders of pregnancy and low birth weight: Analysis of a cross-sectional, web-based survey in Japan. BMJ Open 2021, 11, e052976. [Google Scholar] [CrossRef]
- Special Site COVID-19. Available online: https://www3.nhk.or.jp/news/special/coronavirus/ (accessed on 6 April 2022).
- Shioda, T.; Matsuura, M.; Fukuda, Y.; Takahashi, K.; Yamaoka, K. Social and household factors affecting child health checkup attendance based on a household survey in Japan. Ind. Health 2016, 54, 488–497. [Google Scholar] [CrossRef] [Green Version]
- Moore, S.; Carpiano, R.M. Measures of personal social capital over time: A path analysis assessing longitudinal associations among cognitive, structural, and network elements of social capital in women and men separately. Soc. Sci. Med. 2020, 257, 112172. [Google Scholar] [CrossRef]
- Siette, J.; Pomare, C.; Dodds, L.; Jorgensen, M.; Harrigan, N.; Georgiou, A. A comprehensive overview of social network measures for older adults: A systematic review. Arch. Gerontol. Geriatr. 2021, 97, 104525. [Google Scholar] [CrossRef]
- Ide-Okochi, A.; Funayama, H.; Asada, Y. Pediatric dentists’ perspectives of children with special health care needs in Japan: Developmental disabilities, phobia, maltreatment, and multidisciplinary collaboration. BMC Pediatr. 2021, 21, 240. [Google Scholar] [CrossRef]
- Morrison, A.K.; Glick, A.; Yin, H.S. Health Literacy: Implications for Child Health. Pediatr. Rev. 2019, 40, 263–277. [Google Scholar] [CrossRef] [PubMed]
- Ishikawa, H.; Nomura, K.; Sato, M.; Yano, E. Developing a measure of communicative and critical health literacy: A pilot study of Japanese office workers. Health Promot. Int. 2008, 23, 269–274. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ministry of Health, Labour and Welfare. Don’t delay! Child Immunization and Infant Health Checkups’—Calls on People not to Delay Their Checkups Due to COVID-19. Available online: https://www.mhlw.go.jp/stf/newpage_11744.html (accessed on 6 April 2022).
- Japan Pediatric Society. Q and A about COVID-19. Available online: https://www.jpeds.or.jp/modules/activity/index.php?content_id=326 (accessed on 6 April 2022).
- Lazzerini, M.; Barbi, E.; Apicella, A.; Marchetti, F.; Cardinale, F.; Trobia, G. Delayed access or provision of care in Italy resulting from fear of COVID-19. Lancet Child Adolesc. Health 2020, 4, e10–e11. [Google Scholar] [CrossRef]
- Lee, J.J.; Kang, K.A.; Wang, M.P.; Zhao, S.Z.; Wong, J.Y.H.; O’Connor, S.; Yang, S.C.; Shin, S. Associations Between COVID-19 Misinformation Exposure and Belief With COVID-19 Knowledge and Preventive Behaviors: Cross-Sectional Online Study. J. Med. Internet Res. 2020, 22, e22205. [Google Scholar] [CrossRef] [PubMed]
- Basch, C.H.; Roberts, K.J.; Samayoa-Kozlowsky, S.; Glaser, D.B. Promoting weight loss methods in parenting magazines: Implications for women. Women Health 2016, 56, 119–128. [Google Scholar] [CrossRef]
- Jalloh, M.A.; Barnett, M.J.; Ip, E.J. Men’s Health-Related Magazines: A Retrospective Study of What They Recommend and the Evidence Addressing Their Recommendations. Am. J. Mens Health 2020, 14, 1557988320936900. [Google Scholar] [CrossRef]
- A Study of Infants and Children not Having Health Check-Up Carried out by a Public Health Center. Available online: https://www.jschild.med-all.net/Contents/private/cx3child/2005/006404/002/0527-0533.pdf (accessed on 15 May 2022).
- Eysenbach, G.; Wyatt, J. Using the Internet for surveys and health research. J. Med. Internet Res. 2002, 4, E13. [Google Scholar] [CrossRef]
Variables | Total (n = 5667) | Avoidance of Child Checkups (−) (n = 5285) | Avoidance of Child Checkups (+) (n = 382) | p-Value |
---|---|---|---|---|
Mean (SD) or N (%) | ||||
Child age upon answering | 0.003 | |||
Less than 3 months | 666 (11.7) | 639 (12.1) | 27 (7.1) | |
3–6 months | 808 (14.3) | 769 (14.5) | 39 (10.2) | |
Over 6 months | 4193 (74.0) | 3877 (73.4) | 316 (82.7) | |
Gestational age at delivery (weeks) | 38.7 (2.0) | 38.7 (1.9) | 38.4 (2.5) | 0.005 |
Nulliparity | 3056 (53.9) | 2849 (53.9) | 207 (54.2) | 0.92 |
Maternal age at delivery (year) | 32.2 (4.4) | 32.2 (4.4) | 31.9 (4.5) | 0.14 |
Living with Grandparents | 267 (4.7) | 251 (4.8) | 16 (4.2) | 0.62 |
Houseohld Income | 0.16 | |||
<3 million | 183 (3.2) | 166 (3.1) | 17 (4.5) | |
3 million to 6 million | 1614 (28.5) | 1489 (28.2) | 125 (32.7) | |
6 million to 10 million | 2252 (39.7) | 2112 (40.0) | 140 (36.7) | |
10 million or more | 750 (13.2) | 701 (13.3) | 49 (12.8) | |
Unknown | 868 (15.3) | 817 (15.5) | 51 (13.4) | |
Academic background | 0.40 | |||
Junior high school graduate | 30 (0.5) | 29 (0.6) | 1 (0.3) | |
High school graduate | 872 (15.4) | 818 (15.5) | 54 (14.1) | |
Junior college or technical school graduate | 1789 (31.6) | 1655 (31.3) | 134 (35.1) | |
University or higher | 2959 (52.2) | 2766 (52.3) | 193 (50.5) | |
Unknown | 17 (0.3) | 17 (0.3) | 0 (0.0) | |
Health Literacy * | 0.002 | |||
Low | 3523 (62.2) | 3257 (61.6) | 266 (69.6) | |
High | 2144 (37.8) | 2028 (38.4) | 116 (30.4) | |
Trust for neighbors | 0.007 | |||
Yes | 740 (13.1) | 688 (13.0) | 52 (13.6) | |
Partly | 3371 (59.5) | 3164 (59.9) | 207 (54.2) | |
Not so much | 1266 (22.3) | 1176 (22.3) | 90 (23.6) | |
Not at all | 290 (5.1) | 257 (4.9) | 33 (8.6) | |
Number of people to consult | 0.08 | |||
0 | 77 (1.4) | 72 (1.4) | 5 (1.3) | |
1–2 | 2109 (37.2) | 1943 (36.8) | 166 (43.5) | |
3–5 | 2786 (49.2) | 2625 (49.7) | 161 (42.2) | |
6–10 | 614 (10.8) | 570 (10.8) | 44 (11.5) | |
11–15 | 46 (0.8) | 44 (0.8) | 2 (0.5) | |
16–20 | 11 (0.2) | 9 (0.2) | 2 (0.5) | |
≥21 | 24 (0.4) | 22 (0.4) | 2 (0.5) |
Variables | Crude OR (95% CI) | Adjusted OR (95% CI) † | |||
---|---|---|---|---|---|
Total | Less than 3 Months (n = 666 (11.7%)) | 3–6 Months (n = 808 (14.3%)) | Over 6 Months (n = 4193 (74.0%)) | ||
Traditional Media | |||||
Magazine | 2.97 (1.92–4.58) * | 2.37 (1.31–4.28) * | – ‡ | 2.49 (0.23–26.69) | 3.19 (1.68–6.05) ** |
Book | 1.88 (1.12–3.15) * | 0.88 (0.45–1.74) | 44.47 (2.62–754.64) * | 9.56 (1.36–66.97) * | 0.49 (0.22–1.12) |
Newspaper | 1.20 (0.91–1.57) | 1.10 (0.79–1.53) | 0.71 (0.12–4.41) | 1.55 (0.43–5.55) | 1.13 (0.78–1.62) |
TV news | 0.84 (0.68–1.05) | 0.88 (0.68–1.14) | 0.69 (0.21–2.33) | 0.39 (0.15–1.06) | 0.94 (0.70–1.25) |
Radio | 1.89 (1.24–2.88) * | 1.50 (0.92–2.46) | 22.63 (0.71–721.49) | 2.05 (0.24–2.17) | 1.74 (1.03–2.95) * |
Online Media | |||||
Public website | 0.71 (0.58–0.89) | 0.62 (0.48–0.80) | 0.77 (0.21–2.82) | 2.05 (0.24–17.88) | 0.58 (0.43–0.77) ** |
University or scientific-society website | 1.30 (1.00–1.71) * | 1.48 (1.08–2.04) * | 5.62 (1.18–26.73) * | 0.89 (0.37–2.17) | 1.61 (1.13–2.30) * |
Web news | 0.91 (0.73–1.12) | 0.99 (0.77–1.27) | 0.43 (0.12–1.46) | 0.55 (0.14–2.15) | 1.03 (0.78–1.36) |
Social Media | |||||
Broadcast media (YouTube, TikTok, etc.) | 1.59 (1.19–2.12) * | 1.38 (0.98–1.93) | 0.08 (0.01–1.00) * | 0.96 (0.38–2.40) | 1.49 (1.01–2.18) * |
LINE | 1.10 (0.82–1.46) | 0.81 (0.57–1.15) | 1.18 (0.20–6.83) | 1.98 (0.54–7.35) | 0.81 (0.55–1.19) |
1.36 (1.08–1.72) * | 1.34 (1.01–1.77) * | 0.75 (0.17–3.38) | 0.44 (0.11–1.82) | 1.38 (1.00–1.89) * | |
1.59 (1.12–2.26) * | 1.23 (0.79–1.93) | 0.51 (0.04–6.73) | 2.29 (0.81–6.52) | 1.48 (0.90–2.42) | |
1.11 (0.87–1.42) | 0.88 (0.64–1.20) | 4.34 (1.01–18.64) * | 1.07 (0.35–3.33) | 0.71 (0.50–1.03) |
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Ojio, M.; Maeda, Y.; Tabuchi, T.; Fujiwara, T. The Association between Types of COVID-19 Information Source and the Avoidance of Child Health Checkups in Japan: Findings from the JACSIS 2021 Study. Int. J. Environ. Res. Public Health 2022, 19, 9720. https://doi.org/10.3390/ijerph19159720
Ojio M, Maeda Y, Tabuchi T, Fujiwara T. The Association between Types of COVID-19 Information Source and the Avoidance of Child Health Checkups in Japan: Findings from the JACSIS 2021 Study. International Journal of Environmental Research and Public Health. 2022; 19(15):9720. https://doi.org/10.3390/ijerph19159720
Chicago/Turabian StyleOjio, Masafumi, Yuto Maeda, Takahiro Tabuchi, and Takeo Fujiwara. 2022. "The Association between Types of COVID-19 Information Source and the Avoidance of Child Health Checkups in Japan: Findings from the JACSIS 2021 Study" International Journal of Environmental Research and Public Health 19, no. 15: 9720. https://doi.org/10.3390/ijerph19159720
APA StyleOjio, M., Maeda, Y., Tabuchi, T., & Fujiwara, T. (2022). The Association between Types of COVID-19 Information Source and the Avoidance of Child Health Checkups in Japan: Findings from the JACSIS 2021 Study. International Journal of Environmental Research and Public Health, 19(15), 9720. https://doi.org/10.3390/ijerph19159720