Hrev_master Healthcare in Low-resource Settings 2025; volume 13:13966 The effectiveness of health belief model intervention on tuberculosis medication adherence in rural Indonesia: a pre-experimental study Ardenny, Ibnu Rusdi, Idayanti, Falinda Oktariani Department of Nursing, Health Polytechnic, Ministry of Health, Riau, Indonesia Abstract Tuberculosis treatment non-adherence remains a significant challenge in rural Indonesia, with Kampar District reporting below-target success rates. Therefore, this study aimed to evaluate the effectiveness of a Health Belief Model (HBM) intervention on medication adherence among tuberculosis patients in rural Indonesia. A pre-experimental study with a one-group pretest- posttest design was conducted among 45 purposively sampled TB patients in Kampar District. Data were collected using the validat- ed Health Belief Model Questionnaire and the Medication Adherence Rating Scale. The intervention consisted of a 3-month structured program including weekly sessions in the first month, bi-weekly sessions in the second month, and a monthly follow-up in the third month. Following the HBM intervention, significant improvements were observed in perceived benefits (31.33±4.447 to 32.80±4.341, p<0.001), perceived barriers (22.80±3.286 to 24.38±4.185, p=0.002), and perceived susceptibility (25.64±3.675 to 26.69±3.771, p=0.007). Moreover, medication adherence sig- nificantly improved from 5.40±1.156 to 6.20±0.944 (p<0.001). The HBM intervention effectively improved medication adher- ence through enhanced health beliefs among rural TB patients. Thus, integrating HBM-based interventions into TB treatment programs could improve treatment outcomes in resource-limited settings. However, further research with longer follow-up periods is recommended. Introduction Tuberculosis (TB) remains a serious health problem in Indonesia. According to the latest report from the World Health Organization (WHO) in 2023, TB is ranked as the 13th leading cause of death worldwide.1 Despite advancements in treatment, the disease continues to disproportionately impact low-income countries. The COVID-19 pandemic has exacerbated the chal- lenges posed by TB, disrupting healthcare services and limiting access to diagnosis and treatment.2 This disruption has led to a resurgence of TB cases in many regions, including Indonesia, where TB cases have significantly increased.3 The burden of TB in Indonesia is substantial. The WHO’s 2023 report reveals that Indonesia continues to face significant challenges in combating TB. Approximately 969,000 new TB cases are estimated to occur annually, resulting in 93,000 deaths.4 Additionally, the emergence of drug-resistant TB complicates TB control efforts in Indonesia. The prevalence of TB in Indonesia is influenced by various factors, including socioeconomic conditions and underlying health issues.5 Poverty, malnutrition, HIV/AIDS, and other chronic illnesses can increase an individual’s suscepti- bility to TB.6 These risk factors often intersect, creating a complex web of challenges for those affected. The Indonesian government has implemented various pro- grams to address the TB burden.7 These efforts include awareness campaigns to educate the public about TB prevention and symp- toms, free treatment programs to improve access to care, and ini- tiatives to strengthen the healthcare system. However, significant challenges remain, such as social stigma associated with TB, lim- ited access to healthcare services in rural areas, and a lack of pub- lic awareness about the disease.8 In Kampar District, the situation is particularly concerning. The treatment success rate in 2021 was only 75%, significantly below the national target of 85%.9 This resulted in three MDR-TB Correspondence: Ardenny, Department of Nursing, Politeknik Kesehatan Kementerian Kesehatan Riau, Jl. Melur No. 103 Sukajadi, Pekanbaru 28281, Indonesia. Tel.: +62.81372321907 E-mail: ardenny_2010@yahoo.co.id Key words: compliance; HBM model; TB medication; treatment adher- ence. Ethics approval: this research has complied with ethical principles and was approved by the Ethics Committee of the Ministry of Health Polytechnic of Riau (Approval No. LB.02.03/6/95/2024). Conflict of interest: the authors declare that they have no competing interests. Funding: none. Contributions: a conceptualized the research, designed the study method- ology, and was responsible for overall project coordination. IR con- tributed to the research design and supported data analysis. I assisted in data collection and helped with statistical analysis. FO provided techni- cal and administrative support, organized tables and figures, and assisted in manuscript preparation and editing. Availability of data and materials: data and materials used in this research are not publicly available. Acknowledgments: the authors thank the Health Polytechnic of the Ministry of Health Riau for providing technical assistance and adminis- trative support for this research. Received: 9 May 2025. Accepted: 2 October 2025. Early access: 25 November 2025. This work is licensed under a Creative Commons Attribution 4.0 License (by-nc 4.0). ©Copyright: the Author(s), 2025 Licensee PAGEPress, Italy Healthcare in Low-resource Settings 2025; 13:13966 doi:10.4081/hls.2025.13966 Publisher's note: all claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organi- zations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. [Healthcare in Low-resource Settings 2025;13:13966] [page 227] cases in 2022, representing a 50% increase from previous years.10 The district’s rural characteristics, with 70% of patients living more than 10 km from health facilities, low health literacy (only 35% understand TB transmission correctly), and an average monthly income below provincial minimum wage – create unique adherence challenges not addressed by standard TB programs. Patients with pulmonary tuberculosis often experience psycho- logical distress that can hinder treatment adherence.11 The Health Belief Model (HBM) provides a theoretical framework for addressing these psychological barriers by examining how individ- ual beliefs about disease – including perceived susceptibility, severity, benefits, and barriers – influence health behaviors. Despite the potential of HBM in addressing TB treatment adherence, critical gaps remain in its application. First, most HBM studies have focused on urban populations with better healthcare access, overlooking rural contexts where barriers are more com- plex. Second, existing HBM interventions rarely incorporate local cultural beliefs and family dynamics which are crucial in Indonesian rural contexts. Third, previous studies primarily meas- ured knowledge change rather than actual medication-taking behaviors. Fourth, no studies have specifically addressed the unique combination of geographical, economic, and cultural barri- ers present in districts like Kampar with documented low treatment success rates. This study addresses these gaps by developing and evaluating a culturally-adapted HBM intervention specifically designed for rural TB patients facing multiple structural barriers. To our knowledge, this is the first study to: i) apply HBM in Indonesian rural districts with documented treatment success rates below national targets, ii) incorporate local cultural beliefs and family involvement into the intervention design, and iii) measure both psychological constructs and actual medication adherence behaviors. Therefore, this study aims to evaluate the effectiveness of an HBM intervention on medication adherence among pul- monary TB patients in Kampar District, with the goal of providing evidence for scalable interventions that can improve treatment out- comes in resource-limited rural settings. Materials and Methods This pre-experimental study with a one-group pretest-posttest design was conducted from March to August 2024 at five commu- nity health centers in Kampar District. Sample size calculation indicated a minimum of 42 participants (80% power, 95% confi- dence level); 45 of 47 recruited participants completed the study. Study population The study population comprised all adult pulmonary TB patients registered in the District TB Control Program. Based on district health records, approximately 180 active TB patients were undergoing treatment, with 145 adults aged 21-60 years forming the accessible population. Purposive sampling was used to select adult pulmonary TB patients (21-60 years) currently receiving treatment. Inclusion cri- teria were confirmed pulmonary TB diagnosis, Kampar District residence, ability to communicate, and informed consent. Exclusion criteria were MDR-TB, severe comorbidities, cognitive impairment, or previous treatment default. Intervention protocol The 3-month HBM intervention was structured in three phases. The intensive phase (month 1) began with a baseline assessment and a 60-minute initial education, followed by weekly 45-minute individual counseling sessions focusing on TB knowledge, and perceived susceptibility and severity. The reinforcement phase (month 2) included bi-weekly 60-minute group sessions and one family involvement meeting, addressing treatment barriers and enhancing perceived benefits. The maintenance phase (month 3) consisted of 1-2 monthly follow-up sessions for adherence sustain- ment and peer support group formation. Educational materials included booklets, symptom diaries, and reminder tools. Data col- lection occurred at baseline (day 0) and post-intervention (day 90). Instruments Three validated instruments were used: i) a sociodemographic questionnaire capturing age, gender, education, occupation, income, and treatment duration; ii) the Health Belief Model Questionnaire (25 items, 5-point Likert scale) measuring perceived susceptibility, severity, benefits, and barriers (Cronbach’s α=0.87); and iii) the Medication Adherence Rating Scale (8 items, binary response, α=0.83). Data collection and analysis Five trained nurses collected data at baseline and at the 3- month endpoint. Data were analyzed using SPSS 25.0 with descriptive statistics (frequencies, means, standard deviations) and paired t-tests for pre-post comparisons (significance level p<0.05). Intention-to-treat analysis was applied for missing data. Ethical considerations The study received ethical approval from the Ethics Committee of the Health Polytechnic of the Ministry of Health Riau (No. LB.02.03/6/95/2024). All participants provided written informed consent, with voluntary participation and confidentiality assured. Results The respondent characteristics revealed that the largest age group was late adulthood (36-45 years), comprising 28.9% of the total sample. A substantial proportion was also in late adolescence (17-25 years) and in the elderly (>59 years), each accounting for 20.0% of participants. In terms of gender, males constituted the majority at 68.9%, while females made up 31.1%. Regarding edu- cation, the vast majority of respondents (84.4%) had completed senior high school. A small minority had only finished primary school (6.7%) or held a university degree (4.4%). The majority of participants were married (73.3%), with the remaining being single or widowed (13.3% each). Ethnically, the sample was predomi- nantly Malay (60.0%), followed by Minang (24.4%), Batak (8.9%), and Javanese (6.7%). Occupationally, farmers were the most common group (37.8%), followed by private sector workers (33.3%) and retirees (22.2%). In terms of income, 44.4% of respondents reported earning between 1 and 3 million IDR, while 40.0% earned less than 1 million IDR. A smaller proportion (15.6%) earned over 3 million IDR. The overwhelming majority of participants were Muslim (95.6%), with only 4.4% identifying as Christian. Lastly, regarding treatment duration, 26.7% of respon- dents had been in treatment for 2 months, followed by 24.4% for 1 month, and 17.8% for 6 months. A small proportion (2.2%) had been in treatment for 10 months (Table 1). Distribution of Health Beliefs and Adherence in Taking Medication. A comparison of pre- and post-intervention data on health beliefs and medication adherence revealed notable changes. Before Advancing Nursing Education and Practice for Future Global Health [page 228] [Healthcare in Low-resource Settings 2025;13:13966] the intervention, a substantial proportion of respondents (68.9%) held negative perceptions about the benefits of standard treatment. This number significantly decreased to 57.8% post-intervention, indicating an improvement of 11.1%. Similarly, negative percep- tions of treatment barriers decreased from 64.4% to 40.0%, repre- senting a substantial improvement of 24.4%. Perceived suscepti- bility to TB also showed an improvement, with negative percep- tions decreasing from 64.4% before the intervention to 53.3% afterward, reflecting an 11.1% positive change. Regarding medica- tion adherence, non-adherence decreased from 62.2% to 57.8%, indicating a 4.4% improvement. Overall, these findings suggest that the application of the Health Belief Model (HBM) positively influenced both respondents’ health beliefs and their adherence to medication regimens. On average, the intervention led to a 12.75% improvement across all measured domains (Table 2). The analysis of the Health Belief Model (HBM) implementa- tion on medication adherence revealed significant findings across various health belief dimensions. For perceived benefits, the mean score increased significantly from 31.33 (SD=4.447) pre-interven- tion to 32.80 (SD=4.341) post-intervention (p < 0.001). Similarly, Advancing Nursing Education and Practice for Future Global Health Table 1. Demographic characteristics of respondents (N=45). Characteristic Category Frequency (n) Percentage (%) Age group 17-25 years (Late adolescence) 9 20.0 26-35 years (Early adulthood) 8 17.8 36-45 years (Late adulthood) 13 28.9 46-55 years (Early elderly) 6 13.3 >59 years (Elderly) 9 20.0 Gender Male 31 68.9 Female 14 31.1 Education Primary school 3 6.7 Junior high school 2 4.4 Senior high school 38 84.4 University degree 2 4.4 Marital status Single 6 13.3 Married 33 73.3 Widowed 6 13.3 Ethnicity Malay 27 60.0 Minang 11 24.4 Batak 4 8.9 Javanese 3 6.7 Occupation Farmer 17 37.8 Private sector worker 15 33.3 Retired 10 22.2 Government employee 3 6.7 Income <1 million IDR 18 40.0 1-3 million IDR 20 44.4 >3 million IDR 7 15.6 Religion Muslim 43 95.6 Christian 2 4.4 Treatment duration 1 month 11 24.4 2 months 12 26.7 3 months 5 11.1 4 months 3 6.7 5 months 5 11.1 6 months 8 17.8 10 months 1 2.2 Table 2. Changes in health beliefs and medication adherence pre- and post-intervention (N=45). Variable Pre-Intervention Post-Intervention Change (%) Positive n (%) Negative n (%) Positive n (%) Negative n (%) Perceived benefits 14 (31.1) 31 (68.9) 19 (42.2) 26 (57.8) +11.1 Perceived barriers 16 (35.6) 29 (64.4) 27 (60.0) 18 (40.0) +24.4 Perceived susceptibility 16 (35.6) 29 (64.4) 21 (46.7) 24 (53.3) +11.1 Medication adherence 17 (37.8) 28 (62.2) 19 (42.2) 26 (57.8) +4.4 Average improvement +12.75   [Healthcare in Low-resource Settings 2025;13:13966] [page 229] the perception of barriers showed a significant improvement, with the mean score increasing from 22.80 (SD=3.286) to 24.38 (SD=4.185) (p=0.002). Regarding perceived susceptibility to TB, there was a slight but statistically significant increase from a pretest mean of 25.64 (SD=3.675) to a posttest mean of 26.69 (SD=3.771) (p=0.007). Finally, medication adherence also showed a significant improvement, with the mean score rising from 5.40 (SD=1.156) before the intervention to 6.20 (SD=0.944) afterward (p<0.001), further highlighting the positive impact of the HBM intervention. Overall, the data demonstrate a statistically signifi- cant effect of HBM implementation on improving medication adherence in patients with tuberculosis, as evidenced by the p-val- ues in each category being below the 0.05 threshold (Table 3). Discussion This study evaluates the effectiveness of an HBM intervention in improving medication adherence among rural TB patients. The demographic profile reveals patterns influencing treatment adher- ence, with working-age adults (36-45 years, 28.9%) comprising the largest group, consistent with Indonesian TB epidemiology.14 The male predominance (68.9%) aligns with global patterns attrib- uted to occupational exposures and gender-specific health-seeking behaviors.15 Economic factors emerge as significant adherence barriers. With 40% earning below 1 million IDR monthly and 37.8% work- ing as farmers, participants face substantial financial constraints affecting healthcare access and treatment continuation.16 This eco- nomic hardship, which has been documented to exacerbate non- adherence when treatment costs become unaffordable,17 under- scores the need for financial support mechanisms in TB programs. The predominantly Muslim population (95.6%) and diverse ethnic composition (Malay 60%, Minang 24.4%) highlight cultural considerations for intervention design. Religious beliefs influence illness perception and treatment-seeking behaviors,18 suggesting the importance of culturally aligned interventions. The varied treatment durations (24.4% at 1 month, 26.7% at 2 months) reflect different treatment phases, with longer durations associated with treatment fatigue that challenges sustained adherence.19 The HBM intervention achieves significant improvements across all measured constructs. Negative perceptions about treat- ment benefits decrease by 11.1%, indicating successful belief mod- ification toward recognizing the adherence value.20 The more sub- stantial 24.4% reduction in perceived barriers suggests effective effort in addressing of treatment obstacles including side effects, duration concerns, and accessibility issues.21 The 11.1% improve- ment in perceived susceptibility, while seemingly counterintuitive, may reflect increased patient empowerment and treatment confi- dence.22 Medication adherence improves from 5.40 to 6.20 (p<0.001), representing a 14.8% increase. While modest in absolute terms, this change is clinically significant in TB treatment contexts where consistent long-term adherence is crucial.23 The intervention’s 12.75% average improvement across all domains demonstrates the HBM’s effectiveness in resource-limited settings. Statistical analysis confirms the intervention effectiveness. Perceived benefits increased significantly (31.33 to 32.80, p<0.001), which is crucial for motivating behavioral change.24 Barrier reduction (22.80 to 24.38, p=0.002) makes treatment more manageable, encouraging greater adherence.24 The modest but sig- nificant increase in perceived susceptibility (25.64 to 26.69, p=0.007) reinforces the importance of treatment.25 Most important- ly, the significant adherence improvement directly addresses TB program goals, as consistent medication-taking prevents disease transmission and drug resistance development.26 Study limitations Several limitations warrant consideration. The pre-experimen- tal design without a control group limits causal inference, as improvements may reflect treatment progression, concurrent health education, or Hawthorne effects. The 3-month intervention, while capturing the intensive phase, does not assess complete 6- month treatment adherence or long-term sustainability. Self- reported adherence measures are susceptible to social desirability bias, potentially overestimating actual medication-taking by 10- 30%. Purposive sampling from a single rural district limits gener- alizability to urban populations or drug-resistant TB cases. The small sample size (n=45) may have limited the power for subgroup analyses. Conclusions The 3-month HBM intervention has significantly improved medication adherence among rural TB patients in Kampar District. Statistically significant improvements in perceived benefits (p<0.001), reduced barriers (p=0.002), and medication adherence scores (5.40 to 6.20, p<0.001) demonstrate the effectiveness of theory-based behavioral interventions in resource-limited settings. These findings are particularly relevant for districts with below- target treatment success rates. Integration of HBM-based approaches into standard TB programs can address the psycholog- ical and cultural factors affecting treatment adherence in rural pop- ulations. Future research should employ controlled designs with longer follow-up periods to establish causality and assess the sus- tainability of behavioral changes. Advancing Nursing Education and Practice for Future Global Health [page 230] [Healthcare in Low-resource Settings 2025;13:13966] Table 3. Comparison of mean scores before and after HBM intervention (N=45). Variable Pre-Intervention Post-Intervention Mean difference t-value p-value Mean ± SD Mean ± SD Perceived benefits 31.33±4.447 32.80±4.341 1.47 6.126 0.000* Perceived barriers 22.80±3.286 24.38±4.185 1.58 3.242 0.002* Perceived susceptibility 25.64±3.675 26.69±3.771 1.05 2.834 0.007* Medication adherence 5.40±1.156 6.20±0.944 0.80 4.264 0.000* *Statistically significant at p<0.05. References 1. World Health Organization. WHO consolidated guidelines on tuberculosis. Module 3: diagnosis–rapid diagnostics for tuber- culosis detection. World Health Organization; 2024. 2. Cioboata R, Biciusca V, Olteanu M, Vasile CM. COVID-19 and tuberculosis: Unveiling the dual threat and shared solu- tions perspective. J Clin Med 2023;12:4784. 3. Surendra H, Elyazar IR, Puspaningrum E, et al. Impact of the COVID-19 pandemic on tuberculosis control in Indonesia: a nationwide longitudinal analysis of programme data. Lancet Global Health 2023;11:e1412-21. 4. World Health Organization. Use of targeted next-generation sequencing to detect drug-resistant tuberculosis: rapid commu- nication, July 2023. World Health Organization; 2023. 5. Fahdhienie F, Mudatsir M, Abidin TF, Nurjannah N. Risk fac- tors of pulmonary tuberculosis in Indonesia: A case-control study in a high disease prevalence region. Narra J 2024;4:e943-e943. 6. Etim NG, Mirabeau Y, Olorode A, Nwodo U. Risk Factors of Tuberculosis and Strategies for Prevention and Control. Int J Innovative Healthcare Res 2024;12:1-13. 7. Iskandar D, Suwantika AA, Pradipta IS, Postma MJ, van Boven JF. Clinical and economic burden of drug-susceptible tuberculosis in Indonesia: national trends 2017-19. Lancet Global Health 2023;11:e117-25. 8. Harianto AV, Vitrianingsih Y, Issalillah F, Mardikaningsih R. Challenges and changes concerning national health develop- ment in Indonesia: legal perspectives, service access, and infectious disease management. Int J Service Sci Manag Engin Technol 2024;5:22-6. 9. Lasmaria R, Febrina N, Simanjutak AM. Characteristics of bacteriological pulmonary tuberculosis cases for the January– August 2021 period at Arifin Achmad Hospital, Riau Province. Jurnal Health Sains 2023;4:31-43. 10. Yenti S, Mitra M, Abidin Z, et al. The effectiveness of health education through whatsapp on increasing knowledge and atti- tudes of TB patients in prevention of pulmonary TB transmis- sion at the UPTD Puskesmas Tapung II. 2023. 11. Yuliyanti S. Beyond clinical outcomes: exploring the psy- chosocial and physical dimensions of quality of life in tubercu- losis patients receiving outpatient care. Open Access Indonesian J Med Rev 2024;4:738-53. 12. Sialino L, Wijnhoven H, Van Oostrom S, et al. Perspectives of older women in the Netherlands: identifying motivators and barriers for healthy lifestyles and determinants of healthy aging. BMC Public Health 2023;23:664. 13. Dabitao D, Bishai WR. Sex and gender differences in tubercu- losis pathogenesis and treatment outcomes. Sex Gender Differences Infect Treatments Infect Dis 2023;441:139-83. 14. Lazar M, Davenport L. Barriers to health care access for low income families: a review of literature. J Comm Health Nursing 2018;35:28-37. 15. Aibana O, Dauria E, Kiriazova T, et al. Patients’ perspectives of tuberculosis treatment challenges and barriers to treatment adherence in Ukraine: a qualitative study. BMJ Open 2020;10:e032027. 16. Abdul Wahab NA, Makmor Bakry M, Ahmad M, et al. Exploring culture, religiosity and spirituality influence on anti- hypertensive medication adherence among specialised popula- tion: a qualitative ethnographic approach. Patient Prefer Adherence 2021;2249-65. 17. Heckman BW, Mathew AR, Carpenter MJ. Treatment burden and treatment fatigue as barriers to health. Curr Opinion Psychol 2015;5:31-6. 18. Raynor D. The influence of written information on patient knowledge and adherence to treatment. In: Adherance to Treatment in Medical Conditions. CRC Press; 2020. page 83- 111. 19. Anderson RM, Funnell MM. Patient empowerment: myths and misconceptions. Patient Educ Counsel 2010;79:277-82. 20. Stang I, Mittelmark MB. Intervention to enhance empower- ment in breast cancer self-help groups. Nursing Inquiry 2010;17:47-57. 21. Pradipta IS, Houtsma D, van Boven JF, et al. Interventions to improve medication adherence in tuberculosis patients: a sys- tematic review of randomized controlled studies. NPJ Primary Care Respirat Med 2020;30:21. 22. Anuar H, Shah S, Gafor H, et al. Usage of Health Belief Model (HBM) in health behavior: A systematic review. Malaysian J Med Health Sci 2020;16:2636-9346. 23. Martela F, Hankonen N, Ryan RM, Vansteenkiste M. Motivating voluntary compliance to behavioural restrictions: Self-determination theory-based checklist of principles for COVID-19 and other emergency communications. Eur Rev Social Psychol 2021;32:305-47. 24. Iacobino A, Fattorini L, Giannoni F. Drug-resistant tuberculo- sis 2020: where we stand. Appl Sci 2020;10:2153. Martela F, Hankonen N, Ryan RM, Vansteenkiste M. Motivating voluntary Adherence to behavioural restrictions: Self-determi- nation theory-based checklist of principles for COVID-19 and other emergency communications. Eur Rev Soc Psychol 2021;32:305-47. 26. Iacobino A, Fattorini L, Giannoni F. Drug-resistant tuberculo- sis 2020: where we stand. Appl Sci 2020;10:2153. Advancing Nursing Education and Practice for Future Global Health [Healthcare in Low-resource Settings 2025;13:13966] [page 231]