Barriers to accessing offline healthcare may discourage patients from undergoing mammography screening. Online patient–provider communication (OPPC) offers a supplementary health resource that can complement traditional medical encounters and facilitate mammography screening. This study examines how offline healthcare barriers influence mammography screening, taking into account OPPC as an independent variable and cancer fatalism and patient activation as two mediators. Data from the 2017, 2018, and 2020 iterations of the Health Information National Trends Survey were used for this study. Results showed that OPPC was positively linked to mammography screening. Offline healthcare barriers had a negative association with patient activation and subsequent mammography behaviors. Moreover, offline healthcare barriers and OPPC were associated with mammography screening through serial mediation of cancer fatalism and patient activation. This study has important implications for encouraging mammography screening.
AdegboyegaAWigginsATObielodanO, et al (2022) Beliefs associated with cancer screening behaviors among African Americans and Sub-Saharan African immigrant adults: A cross-sectional study. BMC Public Health22(1): 2219.
AndersonEETejadaSWarneckeRB, et al (2018) Views of low-income women of color at increased risk for breast cancer. Narrative Inquiry in Bioethics8(1): 53–66.
4.
BogdanovaAAndrawosCConstantinouC (2022) Cervical cancer, geographical inequalities, prevention and barriers in resource depleted countries. Oncology Letters23(4): 113.
5.
BørøsundECvancarovaMMooreSM, et al (2014) Comparing effects in regular practice of e-communication and web-based self-management support among breast cancer patients: Preliminary results from a randomized controlled trial. Journal of Medical Internet Research16(12): e295.
6.
Carter-HarrisLSlavenJEMonahanPO, et al (2019) Understanding lung cancer screening behaviour using path analysis. Journal of Medical Screening27(2): 105–112.
ChaeJLeeC-JKimK (2020) Prevalence, predictors, and psychosocial mechanism of cancer information avoidance: Findings from a national survey of U.S. adults. Health Communication35(3): 322–330.
10.
ChewSYNgLL (2021) Computer-mediated communication (CMC). In: ChewSYNgLL (eds) Interpersonal Interactions and Language Learning: Face-to-Face vs. Computer-Mediated Communication. Cham: Springer International Publishing, pp.27–52.
11.
ChoYYangRGongY, et al (2022) Use of electronic communication with clinicians among cancer survivors: Health Information National Trend Survey in 2019 and 2020. Telemedicine and e-Health29(6): 866–874.
12.
CohenMRosenfeldMGreenblatt-KimronL (2022) Associations between cancer fatalism, causal attributions, and perceptions of benefits and barriers to screening for colorectal cancer. International Journal of Behavioral Medicine29(3): 357–366.
13.
CorrarinoJE (2015) Barriers to mammography use for black women. The Journal for Nurse Practitioners11(8): 790–796.
14.
DowneyRGKingCV (1998) Missing data in Likert ratings: A comparison of replacement methods. The Journal of General Psychology125(2): 175–191.
15.
Espinosa de los MonterosKGalloLC (2011) The relevance of fatalism in the study of Latinas’ cancer screening behavior: A systematic review of the literature. International Journal of Behavioral Medicine18(4): 310–318.
16.
GoEYouK (2018) Health-related online information seeking and behavioral outcomes: Fatalism and self-efficacy as mediators. Social Behavior and Personality: An International Journal46(5): 871–879.
HanPKJMoserRPKleinWMP (2006) Perceived ambiguity about cancer prevention recommendations: Relationship to perceptions of cancer preventability, risk, and worry. Journal of Health Communication11(sup001): 51–69.
19.
HannaKArredondoBLChavezMN, et al (2022) Cancer screening among rural and urban clinics during COVID-19: A multistate qualitative study. JCO Oncology Practice18(6): e1045–e1055.
20.
HibbardJHStockardJMahoneyER, et al (2004) Development of the patient activation measure (PAM): Conceptualizing and measuring activation in patients and consumers. Health Services Research39(4p1): 1005–1026.
21.
IshiiK (2013) Culture and the mode of thought: A review. Asian Journal of Social Psychology16(2): 123–132.
22.
JiangS (2019) How does online patient-provider communication heal? Examining the role of patient satisfaction and communication experience in China. Health Communication34(13): 1637–1644.
23.
JiangSHongYA (2018) Mobile-based patient-provider communication in cancer survivors: The roles of health literacy and patient activation. Psycho-Oncology27(3): 886–891.
24.
JiangSLiuPChiaC (2023) Can online patient-provider communication improve emotional well-being? Examining the roles of social presence and patient empowerment. Cyberpsychology, Behavior, and Social Networking26(5): 366–370.
25.
KirubarajanALeungSLiX, et al (2021) Barriers and facilitators for cervical cancer screening among adolescents and young people: A systematic review. BMC Women’s Health21(1): 1–13.
26.
KobayashiLCSmithSG (2015) Cancer fatalism, literacy, and cancer information seeking in the American public. Health Education & Behavior43(4): 461–470.
27.
KooninLMHootsBTsangCA, et al (2020) Trends in the use of telehealth during the emergence of the COVID-19 pandemic - United States, January-March 2020. Morbidity and Mortality Weekly Report69(43): 1595–1599.
28.
LeeC-jChaeJ (2016) An initial look at the associations of a variety of health-related online activities with cancer fatalism. Health Communication31(11): 1375–1384.
29.
LeeC-jNiederdeppeJFreresD (2012) Socioeconomic disparities in fatalistic beliefs about cancer prevention and the Internet. Journal of Communication62(6): 972–990.
30.
LiuPLYeJFAoHS, et al (2023a) Effects of electronic personal health information technology on American women’s cancer screening behaviors mediated through cancer worry: Differences and similarities between 2017 and 2020. Digital Health9: 20552076231185271.
31.
LiuPLYeoTED (2021) How online patient-provider communication impacts quality of life: Examining the role of patient-centered care and health competence. Health Communication38(38): 562–567.
32.
LiuPLYeoTEDYeJF (2023b) Examining the intervening roles of patient-centered care and patient activation in the health impacts of offline healthcare obstacles and online health consultations among deaf and hard-of-hearing patients. Health Communication. Epub ahead of print 18 October 2023.
33.
LiuPLZhaoXYeJF (2022) The effects of the use of patient-accessible electronic health record portals on cancer survivors’ health outcomes: Cross-sectional survey study. Journal of Medical Internet Research24(10): e39614.
34.
LuLLiuJYuanYC (2022) Cultural differences in cancer information acquisition: Cancer risk perceptions, fatalistic beliefs, and worry as predictors of cancer information seeking and avoidance in the US and China. Health Communication37(11): 1442–1451.
35.
MagaiCConsedineNConwayF, et al (2004) Diversity matters: Unique populations of women and breast cancer screening. Cancer100(11): 2300–2307.
36.
MannDMChenJChunaraR, et al (2020) COVID-19 transforms health care through telemedicine: Evidence from the field. Journal of the American Medical Informatics Association27(7): 1132–1135.
37.
MarkovicMKesicVTopicL, et al (2005) Barriers to cervical cancer screening: A qualitative study with women in Serbia. Social Science & Medicine61(12): 2528–2535.
38.
MatengeTGMashB (2018) Barriers to accessing cervical cancer screening among HIV positive women in Kgatleng district, Botswana: A qualitative study. PLoS One13(10): e0205425.
NelsonDEKrepsGLHesseBW, et al (2004) The Health Information National Trends Survey (HINTS): Development, design, and dissemination. Journal of Health Communication9(5): 443–460.
NiederdeppeJLevyAG (2007) Fatalistic beliefs about cancer prevention and three prevention behaviors. Cancer Epidemiology, Biomarkers & Prevention16(5): 998–1003.
43.
OhKMAnKLeeM, et al (2023) Colorectal cancer screening disparities in Asian Americans: The influences of patient-provider communication and social media use. Cancer Causes & Control34: 813–827.
44.
OhuchiNSuzukiASobueT, et al (2016) Sensitivity and specificity of mammography and adjunctive ultrasonography to screen for breast cancer in the Japan Strategic Anti-cancer Randomized Trial (J-START): A randomised controlled trial. The Lancet387(10016): 341–348.
45.
Otero-SabogalRStewartSSabogalF, et al (2003) Access and attitudinal factors related to breast and cervical cancer rescreening: Why are Latinas still underscreened?Health Education & Behavior30(3): 337–359.
PeekMESayadJVMarkwardtR (2008) Fear, fatalism and breast cancer screening in low-income African-American women: The role of clinicians and the health care system. Journal of General Internal Medicine23(11): 1847–1853.
48.
PengMZhangY-PWuY, et al (2023) Analysis of the influential factors of the emotional health of patients with cancer based on the structural equation model: The role of social media and emotional support. Supportive Care in Cancer31(7): 1–12.
49.
PoweBD (1996) Cancer fatalism among African-Americans: A review of the literature. Nursing Outlook44(1): 18–21.
50.
PoweBDFinnieR (2003) Cancer fatalism: The state of the science. Cancer Nursing26(6): 454–465.
51.
RosenbergD (2023) Patient centeredness, independent health-related Internet use, and online communication with healthcare providers in later life: A cross-sectional study. Patient Education and Counseling117: 107971.
52.
ShirzadiSAllahverdipourHSharmaM, et al (2020) Perceived barriers to mammography adoption among women in Iran: A qualitative study. Korean Journal of Family Medicine41(1): 20–27.
53.
ShirzadiSNadrianHAsghari JafarabadiM, et al (2017) Determinants of mammography adoption among iranian women: What are the differences in the cognitive factors by the stages of test adoption?Health Care for Women International38(9): 956–970.
54.
SinghSEvansNTWilliamsM, et al (2018) Influences of socio-demographic factors and health utilization factors on patient-centered provider communication. Health Communication33(7): 917–923.
55.
SinkyTHFaithJLindlyO, et al (2018) Cancer fatalism and preferred sources of cancer information: An assessment using 2012 HINTS data. Journal of Cancer Education33(1): 231–237.
56.
SpoonerKKSalemiJLSalihuHM, et al (2017) eHealth patient-provider communication in the United States: Interest, inequalities, and predictors. Journal of the American Medical Informatics Association24(e1): e18–e27.
57.
StreetRLMakoulGAroraNK, et al (2009) How does communication heal? Pathways linking clinician–patient communication to health outcomes. Patient Education and Counseling74(3): 295–301.
58.
SunRWuLBarnettS, et al (2019) Socio-demographic predictors associated with capacity to engage in health care. Patient Experience Journal6(2): 35–41.
59.
TarverWLHaggstromDA (2019) The use of cancer-specific patient-centered technologies among underserved populations in the United States: Systematic review. Journal of Medical Internet Research21(4): e10256.
60.
TotzkayDSilkKJSheffSE (2017) The effect of electronic health record use and patient-centered communication on cancer screening behavior: An analysis of the Health Information National Trends Survey. Journal of Health Communication22(7): 554–561.
WaltherJB (1992) Interpersonal effects in computer-mediated interaction: A relational perspective. Communication Research19(1): 52–90.
64.
WelchJDEllisEM (2018) Sex differences in the association of perceived ambiguity, cancer fatalism, and health-related self-efficacy with fruit and vegetable consumption. Journal of Health Communication23(12): 984–992.
65.
World Health Organization (2023) Global breast cancer initiative implementation framework: Assessing, strengthening and scaling up of services for the early detection and management of breast cancer. Available at: https://www.who.int/initiatives/global-breast-cancer-initiative (accessed 2 December 2023).
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
