Health literacy research and practice · 2026
A Structural Model Linking Health Literacy to Quality of Life in Thai Adults.
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Poonthananiwatkul Benjawan, Yodkong Wonpen, Runlert Chadawan, Deelert Peera, Jirarattanasopa Paisit, Pakeekaow Apaporn Kritsanapan
Аннотация
BACKGROUND: Several factors affect Quality of Life (QoL) such as health literacy, health behaviors, and mental health.
OBJECTIVE: This quantitative study examined the relationships between health literacy (HL), health behaviors (HB), mental health (MH), and QoL among Thailand's working-age population.
METHODS: A total of 360 individuals were selected using multistage sampling. Seven of 13 health regions were randomly chosen, followed by random selection of one province, district, and agency per region. Participants age 15 to 59 years were purposively recruited. Data were collected from December 2024 to January 2025 by using four questionnaires consisting of HL, HB, MH, and QoL (rating scale 1 to 5). Structural equation modeling (SEM) was used for data analysis.
KEY RESULTS: Most participants demonstrated excellent health literacy (78.06%) and QoL (48.89%), with good HB (Mean = 3.82) and MH (Mean = 3.95). SEM showed HB and MH had significant direct positive effects on QoL (β = 0.315, p < .001; β = 0.860, p < .001), while HL exerted significant direct positive effects on both HB (β = 0.396, p < .001) and MH (β = 0.391, p < .001). HL indirectly influenced QoL (β = 0.464, p < .001) through these mediating variables. The model explained 92% of QoL variance and demonstrated excellent fit with empirical data (χ2 = 94.905, df = 76, χ2/df = 1.249, p = .070, RMSEA (root mean square error of approximation) = 0.026, RMR (root mean square residual) = 0.030, GFI (goodness-of-fit index)= 0.972, NFI (normed fit index) = 0.975, TLI (Tucker-Lewis Index) = 0.990, CFI (comparative fit index) = 0.995). A significant sequential pathway was observed (HL → HB → MH → QoL), with no significant direct path from HL to QoL.
CONCLUSION: These findings suggest two potential pathways for improving QoL among working-age Thais: directly enhancing MH and HB to prevent illness or promoting HL to indirectly improve health outcomes. Health care providers should develop programs targeting these factors, with particular emphasis on MH given its stronger influence.
OBJECTIVE: This quantitative study examined the relationships between health literacy (HL), health behaviors (HB), mental health (MH), and QoL among Thailand's working-age population.
METHODS: A total of 360 individuals were selected using multistage sampling. Seven of 13 health regions were randomly chosen, followed by random selection of one province, district, and agency per region. Participants age 15 to 59 years were purposively recruited. Data were collected from December 2024 to January 2025 by using four questionnaires consisting of HL, HB, MH, and QoL (rating scale 1 to 5). Structural equation modeling (SEM) was used for data analysis.
KEY RESULTS: Most participants demonstrated excellent health literacy (78.06%) and QoL (48.89%), with good HB (Mean = 3.82) and MH (Mean = 3.95). SEM showed HB and MH had significant direct positive effects on QoL (β = 0.315, p < .001; β = 0.860, p < .001), while HL exerted significant direct positive effects on both HB (β = 0.396, p < .001) and MH (β = 0.391, p < .001). HL indirectly influenced QoL (β = 0.464, p < .001) through these mediating variables. The model explained 92% of QoL variance and demonstrated excellent fit with empirical data (χ2 = 94.905, df = 76, χ2/df = 1.249, p = .070, RMSEA (root mean square error of approximation) = 0.026, RMR (root mean square residual) = 0.030, GFI (goodness-of-fit index)= 0.972, NFI (normed fit index) = 0.975, TLI (Tucker-Lewis Index) = 0.990, CFI (comparative fit index) = 0.995). A significant sequential pathway was observed (HL → HB → MH → QoL), with no significant direct path from HL to QoL.
CONCLUSION: These findings suggest two potential pathways for improving QoL among working-age Thais: directly enhancing MH and HB to prevent illness or promoting HL to indirectly improve health outcomes. Health care providers should develop programs targeting these factors, with particular emphasis on MH given its stronger influence.