Abstract 7355: Understanding health belief profiles and their role in medication adherence and quality of life among cancer survivors: insights from a multimethod study

Abstract Background: More than half of cancer survivors don’t engage in taking oral anticancer medications (OAMs) due to negative perceptions, leading to relapse, hospitalizations, and higher medical costs. This multimethod study explored cancer survivors’ health belief schemas to understand their decision-making processes around OAM adherence and its impact on quality of life. Methods: This cross-sectional study surveyed 323 cancer survivors nationally to assess beliefs about cancer, OAM adherence, and health-related quality of life (HRQoL), using latent profile analysis to identify subgroups based on health beliefs. Hierarchical regression examined subgroup associations with adherence and HRQoL, while qualitative content analysis of eight interviews provided deeper insights into participants’ cancer experiences. Results: Three health belief profiles were identified: (1) optimistic and adaptive (n = 43, 13%), (2) conscious but hesitant (n = 99, 31%), and (3) overwhelmed and unaware (n = 181, 56%), with significant differences in belief patterns. Regression analysis showed that health belief profiles explained 49.1% of the variance in medication adherence and 28.6% in HRQoL, adjusted for clinical and demographic factors. Cancer survivors in Profile 3 had the lowest adherence (mean = 20.98, SD = 9.0, P<.001) and HRQoL (mean = 14.45, SD = 7.8, P<.001), with Risk of Recurrence (β = -.15, p = .01), Cancer Consequences (β = -.17, p = .01), and Personal Control (β = -.12, p = .05) as significant strong predictors of nonadherence. Qualitatively, participants reported key consequences of cancer including fatigue and medication side effects, social and structural barriers such as altered dynamics with friends and family, social isolation, and financial strain caused by unaffordable healthcare costs and reduced work capacity. Those who perceived a higher risk of recurrence showed greater tolerance for uncomfortable side effects and adhered more consistently to OAMs. Additionally, compared to the overwhelmed and unaware group, participants who maintained optimism and adaptability in managing their cancer, embraced positive thinking and actively engaged in self-management practices, such as maintaining a healthy diet, exercising, and setting alarms for medication taking. Conclusion: This study identified distinct health belief profiles among cancer survivors, highlighting their impact on medication adherence and HRQoL. Survivors with overwhelmed and unaware beliefs exhibited the lowest adherence and HRQoL, emphasizing the importance of addressing negative perceptions and enhancing personal control to improve outcomes. Tailored interventions targeting specific belief profiles, particularly those at higher risk of nonadherence, may foster better self-management and adherence, ultimately improving quality of life for cancer survivors. Citation Format: Meng-Jung Wen, Olayinka O. Shiyanbola. Understanding health belief profiles and their role in medication adherence and quality of life among cancer survivors: insights from a multimethod study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7355.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-7355
Primary Topic
Medication Adherence and Compliance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 7355: Understanding health belief profiles and their role in medication adherence and quality of life among cancer survivors: insights from a multimethod study

Olayinka O. Shiyanbola, Meng‐Jung Wen
Cancer Research
Medication Adherence and Compliance
article

Abstract 7355: Understanding health belief profiles and their role in medication adherence and quality of life among cancer survivors: insights from a multimethod study

Olayinka O. Shiyanbola, Meng‐Jung Wen
article en

Abstract

Abstract Background: More than half of cancer survivors don’t engage in taking oral anticancer medications (OAMs) due to negative perceptions, leading to relapse, hospitalizations, and higher medical costs. This multimethod study explored cancer survivors’ health belief schemas to understand their decision-making processes around OAM adherence and its impact on quality of life. Methods: This cross-sectional study surveyed 323 cancer survivors nationally to assess beliefs about cancer, OAM adherence, and health-related quality of life (HRQoL), using latent profile analysis to identify subgroups based on health beliefs. Hierarchical regression examined subgroup associations with adherence and HRQoL, while qualitative content analysis of eight interviews provided deeper insights into participants’ cancer experiences. Results: Three health belief profiles were identified: (1) optimistic and adaptive (n = 43, 13%), (2) conscious but hesitant (n = 99, 31%), and (3) overwhelmed and unaware (n = 181, 56%), with significant differences in belief patterns. Regression analysis showed that health belief profiles explained 49.1% of the variance in medication adherence and 28.6% in HRQoL, adjusted for clinical and demographic factors. Cancer survivors in Profile 3 had the lowest adherence (mean = 20.98, SD = 9.0, P<.001) and HRQoL (mean = 14.45, SD = 7.8, P<.001), with Risk of Recurrence (β = -.15, p = .01), Cancer Consequences (β = -.17, p = .01), and Personal Control (β = -.12, p = .05) as significant strong predictors of nonadherence. Qualitatively, participants reported key consequences of cancer including fatigue and medication side effects, social and structural barriers such as altered dynamics with friends and family, social isolation, and financial strain caused by unaffordable healthcare costs and reduced work capacity. Those who perceived a higher risk of recurrence showed greater tolerance for uncomfortable side effects and adhered more consistently to OAMs. Additionally, compared to the overwhelmed and unaware group, participants who maintained optimism and adaptability in managing their cancer, embraced positive thinking and actively engaged in self-management practices, such as maintaining a healthy diet, exercising, and setting alarms for medication taking. Conclusion: This study identified distinct health belief profiles among cancer survivors, highlighting their impact on medication adherence and HRQoL. Survivors with overwhelmed and unaware beliefs exhibited the lowest adherence and HRQoL, emphasizing the importance of addressing negative perceptions and enhancing personal control to improve outcomes. Tailored interventions targeting specific belief profiles, particularly those at higher risk of nonadherence, may foster better self-management and adherence, ultimately improving quality of life for cancer survivors. Citation Format: Meng-Jung Wen, Olayinka O. Shiyanbola. Understanding health belief profiles and their role in medication adherence and quality of life among cancer survivors: insights from a multimethod study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7355.

Cancer ResearchVol. 85(8_Supplement_1)
University of Wisconsin–Madison (US), University of Michigan (US)
Openalex Percentile: Top 90%
Medication Adherence and Compliance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.