Determinants of Medication Adherence for Pulmonary Tuberculosis Patients During Continuation Phase in Dalian, Northeast China

Factors associated with unsuccessful treatment outcome for tuberculosis in previously treated patients in Cali, Colombia, during the period 2015-2019

Introduction. The success rates in the treatment of tuberculosis are suboptimal. Objective. To identify associated factors with the lack of success of antituberculosis treatment in patients with a tuberculosis treatment history. Materials and methods. We performed a retrospective, analytical, observational, and cohort study of patients reentering the Mycobacterium program in Cali, Colombia. We included patients over 15 years old with pulmonary tuberculosis between 2015 and 2019 and a history of tuberculosis treatment. Patients with drug-resistant tuberculosis were excluded. Results. A total of 605 patients with a treatment history were included, 60% due to unfinished treatment and 40% due to relapse. Compared to patients reentering due to relapse (ORa=2.34, CI=1.62-3.38), the independent variables associated with treatment failure at discharge were homelessness (ORa=2.45, CI=1.54-3.89), substance dependence (ORa=1.95, CI=1.24-3.05), tuberculosis/HIV coinfection (ORa=1.69, CI=1.00-2.86), diabetes (ORa=1.89, CI=1.29-2.77), and unfinished previous tuberculosis treatment due to follow-up loss, abandonment, or other causes. Programmatic variables favoring treatment success were voluntary HIV testing counseling (p<0.001) and HIV testing (p<0.001). Conclusion. Homelessness, substance dependence, tuberculosis/HIV coinfection, diabetes, and incomplete previous treatment due to loss to follow-up, abandonment, or treatment failure hindered the success of antituberculosis. These characteristics should be identified and addressed during the initial care of patients reentering treatment for tuberculosis.

Social Support, Quality of Care, and Patient Adherence to Tuberculosis Treatment in Peru: The Mediating Role of Nurse Health Education

BACKGROUND

Peru is one of the countries with the highest burden of tuberculosis (TB) and multidrug-resistant tuberculosis (MDR-TB) in the Latin American region and globally. Health education provided by nurses reinforces social support and the quality of patient care allows a greater impact on adherence to TB treatment.

PURPOSE

This study evaluated the mediating effect of treatment education between social support, quality of care, and treatment adherence in TB patients.

METHODS

A cross-sectional study was carried out considering 162 adult TB patients from four health centers of the public sector located in the center of the city of Lima, Peru. Data were collected on variables, such as social support, quality of care, health education, and adherence to TB treatment. SmartPLS was used for data analysis.

RESULTS

The results showed that social support and quality of care significantly influence health education. Likewise, health education mediates social support and quality of care for better adherence to treatment.

CONCLUSION

It is recommended that hospitals take initiatives to provide better health education on TB treatment to ensure better adherence to treatment.

Detecting Medication-Taking Gestures Using Machine Learning and Accelerometer Data Collected Via Smartwatch Technology: A Feasibility Study (Preprint)

BACKGROUND

Medication adherence is a global public health challenge, as only approximately 50% of people adhere to their medication regimens. Medication reminders have shown promising results in terms of promoting medication adherence. However, practical mechanisms to determine whether a medication has been taken or not, once people are reminded, remain elusive. Emerging smartwatch technology may more objectively, unobtrusively, and automatically detect medication taking than currently available methods.

OBJECTIVE

This study aimed to examine the feasibility of detecting natural medication-taking gestures using smartwatches.

METHODS

A convenience sample (N=28) was recruited using the snowball sampling method. During data collection, each participant recorded at least 5 protocol-guided (scripted) medication-taking events and at least 10 natural instances of medication-taking events per day for 5 days. Using a smartwatch, the accelerometer data were recorded for each session at a sampling rate of 25 Hz. The raw recordings were scrutinized by a team member to validate the accuracy of the self-reports. The validated data were used to train an artificial neural network (ANN) to detect a medication-taking event. The training and testing data included previously recorded accelerometer data from smoking, eating, and jogging activities in addition to the medication-taking data recorded in this study. The accuracy of the model to identify medication taking was evaluated by comparing the ANN's output with the actual output.

RESULTS

Most (n=20, 71%) of the 28 study participants were college students and aged 20 to 56 years. Most individuals were Asian (n=12, 43%) or White (n=12, 43%), single (n=24, 86%), and right-hand dominant (n=23, 82%). In total, 2800 medication-taking gestures (n=1400, 50% natural plus n=1400, 50% scripted gestures) were used to train the network. During the testing session, 560 natural medication-taking events that were not previously presented to the ANN were used to assess the network. The accuracy, precision, and recall were calculated to confirm the performance of the network. The trained ANN exhibited an average true-positive and true-negative performance of 96.5% and 94.5%, respectively. The network exhibited <5% error in the incorrect classification of medication-taking gestures.

CONCLUSIONS

Smartwatch technology may provide an accurate, nonintrusive means of monitoring complex human behaviors such as natural medication-taking gestures. Future research is warranted to evaluate the efficacy of using modern sensing devices and machine learning algorithms to monitor medication-taking behavior and improve medication adherence.

Time Trend Analysis of Tuberculosis Treatment While Using Digital Adherence Technologies-An Individual Patient Data Meta-Analysis of Eleven Projects across Ten High Tuberculosis-Burden Countries

Worldwide, non-adherence to tuberculosis (TB) treatment is problematic. Digital adherence technologies (DATs) offer a person-centered approach to support and monitor treatment. We explored adherence over time while using DATs. We conducted a meta-analysis on anonymized longitudinal adherence data for drug-susceptible (DS) TB (n = 4515) and drug-resistant (DR) TB (n = 473) populations from 11 DAT projects. Using Tobit regression, we assessed adherence for six months of treatment across sex, age, project enrolment phase, DAT-type, health care facility (HCF), and project. We found that DATs recorded high levels of adherence throughout treatment: 80% to 71% of DS-TB patients had ≥90% adherence in month 1 and 6, respectively, and 73% to 75% for DR-TB patients. Adherence increased between month 1 and 2 (DS-TB and DR-TB populations), then decreased (DS-TB). Males displayed lower adherence and steeper decreases than females (DS-TB). DS-TB patients aged 15−34 years compared to those >50 years displayed steeper decreases. Adherence was correlated within HCFs and differed between projects. TB treatment adherence decreased over time and differed between subgroups, suggesting that over time, some patients are at risk for non-adherence. The real-time monitoring of medication adherence using DATs provides opportunities for health care workers to identify patients who need greater levels of adherence support.

Experience of adherence to treatment among patients with coronary artery disease during the COVID-19 pandemic: A qualitative study

Background: The coronavirus disease 2019 (COVID-19) pandemic has caused patients with chronic diseases to face various challenges. The present qualitative study aimed to explore adherence to treatment in patients with coronary artery disease (CAD) during the COVID-19 pandemic. Methods: This qualitative content analysis was conducted from September 2020 to February 2021. Online in-depth interviews were conducted with 15 patients with CAD after discharge from Nemazi and Al-Zahra heart hospitals, Shiraz, Iran. Data management was done via MAXQDA 12 software using conventional content analysis based on the method proposed by Graneheim and Lundman. Results: The results revealed three main categories, nine subcategories, and 431 primary codes. The first category was 'improved self-care in the shadow of COVID-19' (Improving self-care due to fear of COVID-19, 'utilization of alternative strategies, and reinforcement of self-care beliefs). The second category was 'redefinition of support systems' (need for a support system, seeking for alternative support systems, and changes in social interactions). The last category was 'barriers to treatment adherence' (shortage of financial resources, need to adjust with working conditions, and mental conflicts). Conclusion: The results indicated that the COVID-19 threats encouraged the patients with CAD to adhere to their care principles. Nonetheless, the restrictions resulting from the pandemic caused problems in adherence to treatment. Thus, redefinition of the support systems in accordance with the present conditions are recommended.

Factors Related to Complying with Anti-TB Medications Among Drug-Resistant Tuberculosis Patients in Indonesia

BACKGROUND

A variety of factors influenced the decision of tuberculosis (TB) drug-resistant patients to continue treatment. The study aimed to analyze factors that influence complying with anti-TB medications in patients with TB drug resistance in Indonesia.

PATIENTS AND METHODS

The study employed a cross-sectional approach and was conducted in various community health centers and polyclinics offering TB drug-resistant services in Bandung city, Indonesia. Participants were 79 patients with TB drug resistance who met the criteria during their treatment for TB drug resistance, were willing to be involved in the research, and accessed TB services in Bandung. Complying with anti-TB medications scale, TB Health Behaviors questionnaire, the family support questionnaire, the TB-Related Stigma Scale, and TB knowledge were used in this study. Data were analyzed using Spearman's Rho.

RESULTS

Health behavior (r = 0.36) was positively associated with complying with anti-TB medications, while family support, TB stigma, and knowledge were not related to treatment compliance.

CONCLUSION

Information on these factors will inform the development of models and modules for the prevention and control of TB drug resistance in Indonesia, which can later be used widely in Indonesia.

Investigating the Relationship between Knowledge and Hepatotoxic Effects with Medication Adherence of TB Patients in Banyumas Regency, Indonesia

Tuberculosis (TB) still remains the burden in Indonesia. One of the factors that may influence the treatment success of TB is patient's adherence. However, the hepatotoxicity of the TB medicine may decrease the patient's adherence. Our study's aim is to investigate the relationship between the patient's knowledge and the hepatotoxicity with medication adherence of TB patients in Banyumas Regency. This study was conducted at one Community Lung Health Center and two hospitals in Banyumas Regency, Purwokerto, Center of Java, Indonesia. The respondents were 91 TB patients with hepatotoxicity characterized by an increased aspartate transaminase (AST) and alanine aminotransferase (ALT). The level of the patients' knowledge about the hepatotoxicity effect was determined using a questionnaire. The patients' adherence was determined using the Medication Adherence Rating Scale -5 (MARS) questionnaire and pill count methods. Most of the patients were male (53.8%), the age was in the range of 18-29 years old (3.5%), they have no smoking history (59.3%), and their last education majorly was senior high school (46.2%). Most TB patients had poor knowledge (47.3%) and the hepatotoxic effect often appeared in grade 1 (61.5%). The TB patients with a good and moderate level of knowledge were 17.6% and 35.2%, respectively. The TB patients with moderate and severe hepatotoxicity were 39.4% and 1.1%, respectively. The measurement of the level of respondents' adherence using MARS-5 showed that 51.6% of patients had good adherence. We determined the rest of the drug-using pill count method, which resulted in 62.6% of patients adhering to taking antituberculosis drugs. TB patients with a sufficient knowledge and those with mild hepatotoxicity show the higher adherence (p < 0.001). There is a significant relationship between a high level of the patient's knowledge about hepatotoxicity effect, less severity of the hepatotoxic effect, and increased patient adherence in taking the medication.

Treatment Adherence among Tuberculosis patients: A Concept Analysis

BACKGROUND OF THE STUDY: The principal difficulty of long-term tuberculosis (TB) treatment is patient nonadherence. During pandemic, nonadherence of TB treatment affects mortality since TB patients are more vulnerable with Covid-19. AIM OF THE STUDY: The purpose of this concept analysis was to clarify and analyze the concept of treatment adherence. METHODOLOGY: Analysis concept was conducted using the Walker and Avant’s method from relevant studies published by EBSCO, PubMed, ProQuest, Wiley Online Library, and Springer between  2003 - 2021. RESULTS:  Five attributes characterizing the concept of treatment adherence from thirteen articles were identified: individual behavior, relationship, mutual participation, shared decision making, and agreement. CONCLUSION: This concept analysis revealed that TB treatment adherence involves many aspects, including the patient, family, society, health care professionals, and policy. These findings help to understand the contribution of major attributes, thereby promoting the body of knowledge on TB and contributing to its elimination during COVID-19 pandemic.

Rebuild doctor-patient trust in medical service delivery in China

Doctor–patient trust is not strong in China, but studies examining this factor remain insufficient. The present study aimed to explore the effect of doctor–patient communication, medical service quality, and service satisfaction on patient trust in doctors. Five hundred sixty-four patients with tuberculosis participated in this cross-sectional study in Dalian, China. They completed questionnaires assessing socio-demographic characteristics, doctor–patient communication, medical service quality, service satisfaction and patient trust in medical staff. A structural equation model was applied to examine the hypotheses, and all the study hypotheses were supported: (1) doctor–patient communication, medical service quality and service satisfaction were positively associated with building doctor–patient trust; (2) service quality positively mediated the relationship between doctor–patient communication and trust; (3) medical service satisfaction positively mediated the relationship between doctor–patient communication and trust; (4) medical service satisfaction positively mediated the relationship between medical service quality and doctor–patient trust; and (5) medical service quality and service satisfaction were the positively sequential mediators between communication and doctor–patient trust. Based on these findings, improvements in doctor–patient communication, medical service quality, and service satisfaction are the important issues contributing to the rebuilding of doctor–patient trust in medical service delivery.

Role of Treatment Adherence, Doctor-Patient Trust, and Communication in Predicting Treatment Effects Among Tuberculosis Patients: Difference Between Urban and Rural Areas

PURPOSE

China is the second highest tuberculosis (TB) burden in the world, and TB patients in the rural areas are about twice as many as urban patients. The purpose of present study was to explore the roles of medication adherence, doctor-patient trust and communication on treatment effects, and its inequality between urban and rural areas.

METHODS

There were 564 eligible TB patients, from four tuberculosis hospitals in China, participating in this cross-sectional study. They filled out questionnaires regarding socio-demographic characteristics, medication adherence, treatment effect, doctor-patient trust, and communication. The structural equation model (SEM) was applied to explore the hypotheses in this study. All statistical analysis was done by SPSS 25.0 and Mplus 7.0 statistical software.

RESULTS

This study included 267 (47.34%) urban and 297 (52.66%) rural eligible TB patients. The data fitted the research model well, and the urban TB patients reported better treatment effect than the rural ones (P=0.027). Overall, treatment adherence positively predicted treatment effect (Est.=0.353, P<0.001); doctor-patient communication positively influenced treatment adherence (Est.=0.214, P=0.002); and treatment adherence positively mediated the role of communication on treatment effect (Est.=0.076), 95% CI (0.026, 0.152). While in the grouping model, the urban patients' treatment effect was only influenced by adherence (Est.=0.286, P=0.003); for the rural patients, treatment adherence (Est.=0.464, P<0.001) and doctor-patient trust (Est.=0.382, P=0.019) directly predicted treatment effects, and treatment adherence positively mediated the role of doctor-patient communication on treatment effect (Est.=0.175, P=0.006).

CONCLUSION

The treatment effect of TB patients, from urban and rural China, was influenced by a different mechanism, among which rural TB patients need not only improve the treatment adherence but also establish good doctor-patient trust and communication to improve treatment effects. These findings provided a theoretical guide on treatment and control for rural TB patients.