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Journal of library and information science in agriculture

   

A Study on the Influence Mechanism of Older Adults' Online Health Information Reception on Health Management from the Perspective of Triadic Reciprocal Determinism Theory

TU Zixuan1, LIU Shuangyuan1, CHEN Sisi1, SHENLining1,2,3()   

  1. 1. School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030
    2. Hubei Provincial Research Center for HealthTechnology Assessment, Wuhan 430030
    3. Research Center for Big Data & Data Science in Health and Healthcare, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030
  • Received:2025-06-24 Online:2026-08-20
  • Contact: SHENLining

Abstract:

[Purpose/Significance] Against the backdrop of China's aging population and advancing digitalization, the digital divide has created disparities in how efficiently older adults can access health information. This has emerged as a critical barrier to their health management. Existing studies have explored factors influencing older adults' health management but rarely focused on the digital divide within this group or deeply integrated individual traits, environmental factors, and health behaviors. Grounded in the Triadic Reciprocal Determinism Theory, this study investigates how exposure to online health information affects older adults' health management behaviors and uncovers how the digital divide manifests in this process. Its innovation lies in addressing gaps in previous research by systematically examining the heterogeneous impacts of online health information exposure on health management across different subgroups (e.g., urban vs. rural residents, those with varying digital skills). This enriches the theoretical system of older adults' health information behavior and health management, while offering practical guidance for tackling the key issue of enhancing older adults' health management and bridging the digital divide amid aging and digitalization. [Method/Process] Guided by the Triadic Reciprocal Determinism Theory, the study formulates hypotheses through literature review. It utilizes cross-sectional data from the 2020 Chinese Longitudinal Aging Social Survey (CLASS), with a valid sample of 3 118 adults aged 60 and above. Health management is influenced by older adults' attitudes toward handling minor illnesses and the frequency of their physical exercise. Online health information exposure is measured by three indicators: the convenience of accessing online health services, engagement in online health management, and ownership of smartwatches or bracelets. Control variables include gender, age, education, and household registration type. Multiple regression models are constructed to test hypotheses, supplemented by robustness tests (adding control variables and replacing dependent variables), heterogeneity analysis (stratified by smartphone proficiency), and mediating effect analysis (comparing urban and rural groups) to ensure result reliability. [Results/Conclusions] Key findings reveal that the convenience of accessing health services via the Internet and engagement in online health management both positively boost older adults' initiative to seek medical care when dealing with minor illnesses. Smart Wearable devices exert a "double-edged sword" effect: they have a negative impact on medical-seeking behavior for minor illnesses yet correlate positively with more frequent physical exercise. Older adults proficient in smartphone use show greater activity in health management. Significant urban-rural differences exist in reliance on social network information-rural older adults are more likely to enhance their health management initiative through family and friend networks, while their urban counterparts tend to obtain health information directly via the Internet. It is recommended that health information communication strategies be formulated in consideration of urban-rural differences, with targeted measures to improve older adults' digital health literacy and bridge the digital divide. Limitations of the study include data constraints, as CLASS data lacks in-depth exploration of older adults' motivations and resistance toward health information exposure, and incomplete measurement of the digital divide, excluding variables such as network speed and regional infrastructure. Future research should adopt mixed methods, integrating questionnaires and semi-structured interviews to supplement qualitative data, expand the measurement dimensions of health management behaviors, and explore the dynamic relationship between technology adoption and health behaviors from the perspective of older adults, providing a more solid basis for targeted interventions.

Key words: health management, Triadic Reciprocal Determinism, web-based health information, older adults, digital divide

CLC Number: 

  • R195

Fig.1

Framework of the influence mechanism of older adults' exposure to online health information on health management"

Fig.2

Research model on the mechanism of action of older adults' exposure to online health information on health management"

Table 1

Selection and explanation of variables"

变量类别 变量编号 变量名称 变量解释 赋值说明 平均值 标准差
被解释变量 B11 ill 受访者生小病如何处理 主动选择就诊就医赋值为1;不主动选择就医赋值为0 0.817 0.387
G2 frequence 受访者体育锻炼的频率 每周4~9次赋值为1;每周1~3次赋值为0 0.500 0.500
解释变量 D16-6 Convenience 互联网获取健康服务的便捷程度 问卷中便利1;不便利2;无影响3;说不上来4。本研究将便利赋值1;其他赋值0 0.357 0.479
D18-4-09 Management 上网是否会管理健康 是赋值1;否赋值0 0.073 0.260
D21-2-4 Watch 是否拥有智能手环/手表 是赋值1;否赋值0 0.195 0.396
控制变量 A1 gender 性别 男赋值1;女赋值2 1.478 0.500
A2 year 年龄 2020年调查的年龄结果 67.838 4.544
A10 hukou 户口类型 农业户口1;非农业户口2 1.702 0.542
A3 edu 文化程度 不识字赋值1;私塾赋值2;小学赋值3;初中赋值4;高中赋值5 3.755 1.211

Table 2

Results of benchmark regression"

变量名称 生小病处理态度影响模型
convenience 0.047 7***
(0.014 6)
Management 0.069 2***
(0.024 0)
watch -0.080 7***
(0.019 3)
gender 0.007 45
(0.013 9)
hukou -0.000 919 4
(0.012 5)
year 0.003 04**
(0.001 50)
Constant 0.595***
(0.110)
Observations 3 118
R-squared 0.011

Table 3

Results of robustness test incorporating education level"

变量名称 生小病处理态度影响模型
convenience 0.045 6***
(0.014 5)
Management 0.061 0**
(0.024 3)
watch -0.083 5***
(0.019 4)
gender 0.011 7
(0.013 9)
hukou -0.012 0
(0.012 8)
year 0.003 79**
(0.001 52)
edu 0.016 4***
(0.006 28)
Constant 0.497***
(0.115)
Observations 3 118
R-squared 0.013

Table 4

Test results after replacing the explained variable with frequency of physical exercise"

变量名称 生小病处理态度影响模型
convenience 0.036 9**
(0.018 6)
Management 0.235***
(0.028 9)
watch 0.074 9***
(0.022 4)
gender 0.014 7
(0.017 3)
hukou 0.143***
(0.017 4)
year -0.011 3***
(0.001 88)
Constant 0.958***
(0.137)
Observations 3 118
R-squared 0.076

Table 5

Heterogeneity analysis of proficiency in using smartphones"

变量名称 一般 熟练
生小病处理态度影响模型 生小病处理态度影响模型
convenience 0.032 3* 0.048 9**
(0.017 8) (0.024 6)
Management 0.037 7 0.123*
(0.025 7) (0.064 3)
watch -0.033 1 -0.218***
(0.021 2) (0.041 6)
gender -0.009 27 0.028 6
(0.017 8) (0.022 0)
hukou -0.003 21 -0.008 40
(0.016 8) (0.019 0)
year 0.000 861 0.007 03***
(0.001 87) (0.002 54)
Constant 0.787*** 0.293
(0.135) (0.184)
Observations 1 772 1 346
R-squared 0.004 0.039

Table 6

Results of mediating effect in rural group"

类型 中介效应 Observed coefficient

Bootstrap

Std.err.

z P>|z|

Normal-based

[95%conf.interval]

家庭网络 间接效应 0.215 3 0.006 5 3.29 0.001 0.008 7 0.343 6
直接效应 0.263 9 0.025 9 -10.18 0.000 -0.314 8 -0.213 1
朋友网络 间接效应 0.003 1 0.001 4 2.11 0.035 0.000 2 0.005 9
直接效应 0.024 2 0.007 2 3.37 0.001 0.010 1 0.038 2

Table 7

Results of mediating effect in urban group"

类型 中介效应 Observed coefficient

Bootstrap

Std.err.

z P>|z|

Normal-based

[95%conf.interval]

家庭网络 间接效应 0.000 8 0.003 7 0.21 0.083 -0.006 6 0.008 2
直接效应 0.275 6 0.017 8 -15.46 0.000 -0.310 6 -0.240 7
朋友网络 间接效应 -0.000 0 0.003 1 -0.42 0.678 -0.000 7 0.004 8
直接效应 0.017 1 0.007 4 2.31 0.021 0.002 6 0.031 7
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