Abstract
Objective
Medication non-adherence to immunosuppressants threatens allograft survival and function maintenance among solid organ transplant (SOT) recipients. This study aimed to investigate the prevalence of immunosuppressant medication non-adherence and associated factors during the COVID-19 reopening period among Chinese SOT recipients.
Design
Cross-sectional study.
Setting
South-central China.
Population
Adult patients who received SOT with functioning graft.
Methods
Sociodemographic questionnaire and scales to measure physical activity, depression and medication non-adherence were used to collect data. Logistic regression analysis was conducted to identify factors associated with medication non-adherence. Mediation and moderated mediation analyses were performed to examine the potential mechanisms influencing medication behaviour during the pandemic reopening period using SPSS PROCESS macro 4.3 software.
Results
A total of 1121 participants were recruited and the prevalence of medication non-adherence was 36.3% in this study. Recipients who were men, had a higher monthly income, lived alone, had received transplantation for a minimum of 3 years, had received COVID-19 vaccination and experienced depressive symptoms exhibited an increased risk of non-adherence. Contrarily, those who engaged in high-intensity physical activity exhibited a decreased risk. Physical activity was negatively associated with medication non-adherence (r=−0.124, p<0.001) with depression fully mediating this relationship (B=−0.014, 95% CI: −0.032 to –0.003). COVID-19 vaccination significantly moderated the relationship between physical activity and depression (B=−0.303, 95% CI: −0.515 to –0.090).
Conclusion
This study investigated the prevalence of medication non-adherence among SOT recipients during the COVID-19 reopening period in China, its associated factors and a potential mechanism. Depression fully mediated the association between physical activity and medication non-adherence, and COVID-19 vaccination moderated the relationship between physical activity and depression. These findings provide some insights for managing medication behaviour when confronting public health emergencies. However, relationships displayed in the moderated mediation model should be tracked after returning to normal life and other potential relationships should be explored to deeply understand medication non-adherent behaviour.
Keywords: COVID-19, transplant surgery, medication adherence, depression & mood disorders, public health
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The moderated mediation model provided a more nuanced understanding of relationships among physical activity, depression, medication non-adherence behaviour and COVID-19 vaccination during the COVID-19 reopening period among solid organ transplant recipients in China.
Cross-sectional study was limited in interpreting causal relationships between variables.
Measuring immunosuppressant medication behaviours solely through a self-reported questionnaire would introduce a certain risk of bias.
Introduction
Solid organ transplant (SOT) is an effective medical treatment for end-stage organ failure. After transplantation, strict adherence to long-term immunosuppressant therapy is critically important for allograft survival and function maintenance.1 Medication non-adherence refers to the situation in which patients fail to comply with prescribed medication therapy intentionally or unintentionally, consequently influencing the desired effect of drugs.2 Non-adherence to immunosuppressant medication is regarded as a significant risk factor for acute rejection, graft loss and allograft dysfunction following transplantation.2 3 Nonetheless, the prevalence of medication non-adherence in SOT recipients remains high worldwide. A longitudinal study in France identified 15% of kidney transplant patients exhibiting persistent low adherence to immunosuppressant medications during the 3 years of follow-up.4 In China, the prevalence varies between 23.2% and 54.9% among renal transplant patients.5 The high prevalence and severe adverse outcomes highlight the significance of identifying the risk factors and potential mechanisms influencing immunosuppressant medication non-adherence among SOT recipients.
Individuals’ behaviour can be influenced by their emotional state, and negative emotions often lead to a reduction in health-related behaviours.6 Numerous studies have consistently shown a connection between depression and medication behaviour in various populations. A meta-analysis demonstrated that depressed patients with chronic disease were an estimated 1.76 times more likely to be non-adherent to their medications than non-depressed patients.7 Additionally, this relationship was also observed in patients with mechanical heart valves, those diagnosed with multiple sclerosis and individuals with type 2 diabetes mellitus.8–10 In the study by Robiner et al,11 pre-transplant depression was found to be negatively related to post-transplant medication adherence. Another cross-sectional study found that depression was significantly correlated with medication adherence among kidney transplant recipients.12 Patients with depression often experience negative thoughts and emotions regarding their treatment and health, which can lead to a loss of motivation for self-management, resulting in medication non-adherence.
Physical activity is an important component of post-transplant rehabilitation, which benefits graft function, improves mental health and promotes recipients’ quality of life.13–15 Previous studies have demonstrated that physical activity is advantageous for preventing and alleviating depression. A dose–response meta-analysis revealed that, in comparison to adults who do not exercise, those who engage in half of the recommended amount of physical activity showed an 18% decrease in the risk of depression, while those who meet the full recommended amount had a 25% lower risk of depression.16 Physical activity can elicit its antidepressant effect by stimulating neuroplastic mechanisms, mitigating inflammation, counteracting oxidative and physiological stress (biological mechanisms), as well as through enhancing self-esteem, social support and self-efficacy (psychosocial mechanisms).17 Up to now, no study has examined the relationship between physical activity and medication adherence. Given that physical activity is reported to alleviate depression, and depression is related to medication non-adherence, our study intended to investigate whether physical activity impacts medication non-adherence among SOT recipients by reducing depression.
Since the end of 2019, COVID-19 has caused a prolonged impact on people’s health status. Fortunately, vaccines against the virus have been successfully developed to protect us from the COVID-19 infection. However, for special populations with compromised immunity, such as SOT recipients, the protective effect of vaccination is reduced.18 Given the uncertain protective effect of vaccination and the fear of COVID-19 infection, deciding whether or not to get vaccinated can be a stressful event for SOT recipients, thereby contributing to psychological burden. However, in the case of fear of being infected in the pandemic, getting vaccinated may be a psychological resource to reduce anxiety and depression in the population. In a prospective study conducted by Garcia-Llana et al, it was observed that the depression score post-vaccination was significantly lower than the pre-vaccination score among patients with chronic kidney diseases.19 In December 2022, China reopened and moved to a new phase of COVID-19. In this context, we hypothesised that COVID-19 vaccination might moderate the association between physical activity and depression.
The study aimed to investigate the prevalence and associated factors of immunosuppressant medication non-adherence during the COVID-19 reopening period among Chinese SOT recipients, and examine the relationship between physical activity and medication non-adherence. Moreover, the mediating role of depression and the moderating role of COVID-19 vaccination was examined as well. The hypothesised framework is presented in figure 1.
Figure 1.
Hypothesised framework.
Hypothesis 1 (H1): Physical activity is directly associated with medication non-adherence.
Hypothesis 2 (H2): Depression mediates the relationship between physical activity and medication non-adherence.
Hypothesis 3 (H3): COVID-19 vaccination moderates the path of physical activity to depression.
Methods
Design and sample
This cross-sectional study was conducted in Hunan province, China from February to March 2023. We used convenience sampling to recruit participants in the transplantation follow-up outpatient clinic of one comprehensive hospital. The inclusion criteria were defined as follows: (1) were aged 18 years and older; (2) received SOT and the graft was functioning and (3) voluntarily participated in this study and signed an informed consent form. Participants were excluded when they were: (1) diagnosed with psychiatric disorders or had cognitive impairment and (2) in a weak physical condition that could not complete the questionnaire. Structured online questionnaire was administered to collect the data. Participants scanned the quick response code to reach the online survey platform (Wen Juan Xing; https://www.wjx.cn/), which is convenient and widely used in China. To ensure questionnaire quality, all data were checked by two authors, and questionnaires with response time less than 350 s or inconsistent answers to identical questions were discarded. All excluded questionnaires were considered for relevance to depression. If the score of the depression measurement indicated definite clinical depression, the researchers would contact the respondent to facilitate a referral to an outpatient psychological clinic for further assistance. The sample size for this cross-sectional study was calculated to be 966 using PASS 2021 software with a power of 0.95, an effect size of 6% and a proportion of 32.4%.3 Considering the dropout rate of 10%, 1063 participants were needed in this study. Finally, a total of 1121 SOT recipients were included.
Ethical statement
The purpose and main contents of this study were explained and all participants provided informed consent before filling out the questionnaire. All transplanted organs in this study were derived from corresponding relatives or patients who died of cardiac diseases, and none of the organs were procured from executed prisoners or any other vulnerable populations. All donors were provided with the informed consent and authorisation. The authors have sent the documentation demonstrating this to the editors of BMJ Open. Meanwhile, all transplants were performed at the Third Xiangya Hospital of Central South University in Changsha, China, and were approved by the hospital’s Ethics Committee.
The online survey platform has implemented advanced technology measures to safeguard against data leaks, and the platform’s staff have strict rules and permissions for accessing user data and have committed to confidentiality agreements. Access to questionnaire results data is restricted to researchers with operational privileges only. Additionally, data were exported by specific personnel to remove any identifiable personal information before being used for data analysis.
Patient and public involvement statement
Neither the patients nor the public were involved in the design, conduct, reporting or dissemination plans of this study.
Measurements
Sociodemographic questionnaire
Sociodemographic characteristics included age, gender, body mass index, marital status, education, monthly income, living alone, residence, time since transplantation and COVID-19 vaccination.
Physical activity
Physical activity was measured by the International Physical Activity Questionnaire-Short Form. It contains seven items and measures three different intensities of physical activity, including vigorous intensity (8.0 metabolic equivalent (METs)), moderate intensity (4.0 METs) and low intensity (3.3 METs). Physical activity of a certain intensity is corresponding MET value×weekly frequency (days/week)×daily time (min/day).20 The total physical activity is determined by summing up the levels of these three intensities, where a higher value corresponds to a higher activity level.
Depression
Depression was assessed by the Hospital Anxiety and Depression Scale Depression subscale (HADS-D). The HADS-D consists of seven items, each of which is assigned a rating of 0, 1, 2 or 3. The overall score ranges from 0 to 21, with a score of ≥8 suggesting a probable presence of depression and ≥11 indicating definite cases of depression.21 22 In this study, we used the validated Chinese version of the assessment tool, which has been tested on Chinese cancer patients and their family caregivers. The results showed strong internal consistency, with Cronbach’s α values exceeding 0.85 for both patients and caregivers.23
Medication non-adherence
Basel Assessment of Adherence with Immunosuppressive Medication Scale (BAASIS) was developed by the Leuven-Basel Adherence Research Group to assess adherence to immunosuppressive medications in transplant recipients.24 This scale contains two dimensions: implementation (four items concerning dose taking; drug holidays; timing intake and dose reduction) and discontinuation (one item concerning complete medication cessation). Recipients are classified as non-adherent if they answer ‘Yes’ to any of these five items. The results of a meta-analysis showed good validity and reliability of the BAASIS.25 Though administering a self-reported scale to measure medication non-adherence would introduce a certain risk of bias, integrating BAASIS into clinical practice is a straightforward process.26 It would be better to employ a triangulation method that incorporates diverse measurement approaches such as drug concentration analysis, self-reported questionnaires and electronic monitoring to enhance the reliability and validity of non-adherence assessment.
Data analysis
Descriptive analysis was conducted to depict the sociodemographic characteristics and main variables. Number and percentage were used to describe discontinuous variables, while mean and SD were used to describe continuous variables. Binary logistic regression was employed to analyse the predictive factors for medication non-adherence (No=0, Yes=1) using the forced entry method. Multi-categorical independent variables were set as dummy variables before being included in the model. Additionally, Spearman correlation analysis was conducted to examine the relationships among physical activity, depression, COVID-19 vaccination and medication non-adherence. All these analyses were performed using SPSS V.26.0.
To further explore the role of physical activity, depression and COVID-19 vaccination on immunosuppressive medication non-adherence among SOT recipients, we used the SPSS PROCESS macro 4.3 software27–29 to test the hypothesised moderated mediation model. First, model 4 was applied to examine the mediating effect of depression on the relationship between physical activity and medication non-adherence. Second, model 7 was used to test the moderated mediation model with COVID-19 vaccination as moderator. The specific layout of the two models (model 4 and model 7) is detailed in the online supplemental file, figure 1. The bias-corrected 95% CIs were obtained by 5000 bootstrap samples. Statistical significance was considered when the two-sided p value was <0.05 and the 95% CI did not include zero. Significant variables in the logistic regression were included as covariates when conducting mediation and moderated mediation analyses.
bmjopen-2023-080998supp001.pdf (348.1KB, pdf)
Results
Medication behaviours during the COVID-19 reopening period
Among the 1121 SOT recipients included in our study, 407 (36.3%) recipients reported at least one ‘Yes’ to items of the BAASIS, which was identified as non-adherent. Across different dimensions of non-adherence, item 2 (timing intake) exhibited the highest frequency of non-adherence, with a rate of 25.2%, followed by item 1a (dose taking) with a rate of 18.5%. Figure 2 illustrates the proportion of non-adherence for each item of the BAASIS.
Figure 2.
Percentage of answering ‘Yes’ to items of the BASSIS. Note: Item 1a (dose taking), missing one dose; Item 1b (drug holidays), skipping two or more doses; Item 2 (timing intake), taking drug more than 2 hours before or after the recommended dosing time; Item 3 (dose reduction), altering the prescribed amount without doctor’s permission; Item 4 (complete medication cessation), stopping taking drugs completely without doctor’s permission. BAASIS, Basel Assessment of Adherence with Immunosuppressive Medication Scale.
Participant characteristics
Sociodemographic characteristics of the 1121 participants and results of logistic regression analysis for medication non-adherence are shown in table 1. Among them, 463 (41.3%) were women, 883 (78.8%) were married and only 97 (8.7%) lived alone. In addition, the COVID-19 vaccination rate was 19.0%. In descriptive and logistic regression analyses, physical activity and depression were set as category variables. Physical activity is classified into three categories: low, moderate and high intensity, based on criteria such as MET value, exercise intensity and weekly activity duration. In this study, the majority of participants engaged in low-intensity to moderate-intensity activities, comprising 92.8% of the total cohort. Using a cut-off value of ≥8, 323 participants (28.8%) were found to exhibit symptoms indicative of depression.
Table 1.
Sociodemographic characteristics and ORs on medication non-adherence using logistic regression analysis (n=1121)
| Characteristic | Respondents, n (%)/mean±SD |
Medication non-adherence, n (%) | β | P value | OR (95% CI) |
| Age (years) | |||||
| 18–40 | 420 (37.5) | 147 (35.0) | 1 | ||
| 41–60 | 639 (57.0) | 237 (37.1) | −0.042 | 0.787 | 0.959 (0.708 to 1.299) |
| >60 | 62 (5.5) | 23 (37.1) | −0.133 | 0.676 | 0.876 (0.470 to 1.631) |
| Gender | |||||
| Female | 463 (41.3) | 146 (31.5) | 1 | ||
| Male | 658 (58.7) | 261 (39.7) | 0.410 | 0.005 | 1.506 (1.131 to 2.007) |
| BMI (kg/m2) | |||||
| <18.5 | 122 (10.9) | 46 (37.7) | 1 | ||
| 18.5– | 708 (63.1) | 238 (33.6) | −0.300 | 0.190 | 0.741 (0.473 to 1.160) |
| 24.0– | 234 (20.9) | 98 (41.9) | −0.018 | 0.947 | 0.983 (0.587 to 1.645) |
| ≥28.0 | 57 (5.1) | 25 (43.9) | 0.254 | 0.481 | 1.289 (0.636 to 2.612) |
| Marital status | |||||
| Married | 883 (78.8) | 317 (35.9) | |||
| Single/separation/widowed/divorced | 238 (21.2) | 90 (37.8) | 0.111 | 0.550 | 1.117 (0.777 to 1.607) |
| Education | |||||
| Middle school or under | 235 (21.0) | 86 (36.6) | 1 | ||
| High school or secondary School | 381 (34.0) | 137 (36.0) | −0.008 | 0.967 | 0.992 (0.679 to 1.450) |
| Junior college or above | 505 (45.0) | 184 (36.4) | −0.265 | 0.199 | 0.768 (0.513 to 1.149) |
| Monthly income (¥) | |||||
| ≤3000 | 308 (27.5) | 100 (32.5) | 1 | ||
| 3001–4999 | 360 (32.1) | 122 (33.9) | 0.357 | 0.060 | 1.430 (0.986 to 2.074) |
| 5000–9999 | 327 (29.2) | 130 (39.8) | 0.733 | <0.001 | 2.082 (1.369 to 3.166) |
| ≥10 000 | 126 (11.2) | 55 (43.7) | 1.030 | <0.001 | 2.802 (1.655 to 4.744) |
| Living alone | |||||
| No | 1024 (91.3) | 359 (35.1) | 1 | ||
| Yes | 97 (8.7) | 48 (49.5) | 0.552 | 0.022 | 1.737 (1.083 to 2.785) |
| Residence | |||||
| City | 770 (68.7) | 281 (36.5) | 1 | ||
| Village | 351 (31.3) | 126 (35.9) | 0.244 | 0.142 | 1.277 (0.922 to 1.769) |
| Time since transplantation | |||||
| <1 year | 191 (17.0) | 39 (20.4) | 1 | ||
| 1 year– | 259 (23.1) | 66 (25.5) | 0.324 | 0.191 | 1.383 (0.851 to 2.248) |
| 3 years– | 482 (43.0) | 192 (39.8) | 1.036 | <0.001 | 2.819 (1.827 to 4.349) |
| ≥10 years | 189 (16.9) | 110 (58.2) | 1.717 | <0.001 | 5.567 (3.369 to 9.199) |
| COVID-19 vaccination | |||||
| No | 908 (81.0) | 318 (35.0) | 1 | ||
| Yes | 213 (19.0) | 89 (41.8) | 0.463 | 0.010 | 1.588 (1.117 to 2.258) |
| Physical activity | |||||
| Low intensity | 605 (54.0) | 246 (40.7) | 1 | ||
| Moderate intensity | 435 (38.8) | 147 (33.8) | −0.189 | 0.186 | 0.828 (0.626 to 1.095) |
| High intensity | 81 (7.2) | 14 (17.3) | −1.313 | <0.001 | 0.269 (0.140 to 0.518) |
| Depression | |||||
| No | 798 (71.2) | 238 (29.8) | 1 | ||
| Yes | 323 (28.8) | 169 (52.3) | −0.856 | <0.001 | 2.375 (1.778 to 3.174) |
BMI, body mass index.
Logistic regression analysis for medication non-adherence
As shown in table 1, the results of logistic regression analysis indicated that gender, monthly income, living alone, time since transplantation, COVID-19 vaccination, physical activity and depression were significantly associated with medication non-adherence. SOT recipients were men (OR=1.506, 95% CI: 1.131 to 2.007), lived alone (OR=1.737, 95% CI: 1.083 to 2.785), vaccinated (OR=1.588, 95% CI: 1.117 to 2.258) and had a higher level of medication non-adherence. Recipients with a higher monthly income were more likely to be non-adherent; when the income reached ¥10 000, the OR reached 2.802 (95% CI: 1.655 to 4.744). Moreover, recipients whose time since transplantation was ≥3 years were more likely to be non-adherent to immunosuppressants. The OR was 2.819 for 3–10 years (95% CI: 1.827 to 4.349) and 5.567 for ≥10 years (95% CI: 3.369 to 9.199). In the case of physical activity, high-intensity physical activity had a significantly low level of medication non-adherence (OR=0.269, 95% CI: 0.140 to 0.518). Depression predicted a higher risk of medication non-adherence with OR of 2.375 (95% CI: 1.778 to 3.174).
Correlations among examined variables
The mean±SD/number and correlation coefficients of physical activity, depression, COVID-19 vaccination and medication non-adherence are presented in online supplemental table 1. The mean level of physical activity was 921.39 (SD=1277.26) METs/min/week and the mean score of depression was 5.55 (SD=3.64). Only 213 (19.0%) of the participants got vaccinated with COVID-19 vaccines. Physical activity was negatively associated with depression (r=−0.212, p<0.001). Medication non-adherence was negatively related to physical activity (r=−0.124, p<0.001) and positively correlated with depression (r=0.216, p<0.001). The correlation between vaccination and depression was significant but appeared to be relatively weak (r=0.075, p<0.05).
Mediation and moderated mediation analyses
The mediation model was tested using model 4 in the SPSS PROCESS macro 4.3 software27–29 after controlling of gender, monthly income, living alone and time since transplantation. The results showed that the direct effect of physical activity on medication non-adherence was not significant. However, physical activity had a significant and negative effect on depression (B=−0.115, 95% CI: −0.197 to –0.033). In addition, depression significantly and positively predicted medication non-adherence (B=0.122, 95% CI: 0.085 to 0.159). Depression fully mediated the association between physical activity and medication non-adherence (B=−0.014, 95% CI: −0.032 to –0.003).
The moderating role of COVID-19 vaccination was tested using model 7. As shown in table 2, after the moderator was put into the model, physical activity was still significantly and negatively correlated with depression (B=−0.118, 95% CI: −0.200 to –0.037). Meanwhile, the interaction term of vaccination and physical activity significantly predicted depression (B=−0.303, 95% CI: −0.515 to –0.090). The result indicated that COVID-19 vaccination significantly moderated the relationship between physical activity and depression. The moderated mediation model is displayed in figure 3.
Table 2.
Mediating effect of depression and moderating effect of COVID-19 vaccination
| Outcome variable | Predictor | B | SE | t/Z | P value | LLCI | ULCI |
| Depression | Physical activity | −0.118 | 0.042 | −2.837 | 0.005 | −0.200 | −0.037 |
| COVID-19 vaccination | 0.254 | 0.279 | 0.912 | 0.362 | −0.293 | 0.801 | |
| Physical activity×COVID-19 vaccination | −0.303 | 0.108 | −2.794 | 0.005 | −0.515 | −0.090 | |
| Gender | 0.958 | 0.219 | 4.381 | <0.001 | 0.529 | 1.387 | |
| Monthly income | −0.440 | 0.109 | −4.052 | <0.001 | −0.654 | −0.227 | |
| Living alone | 0.532 | 0.377 | 1.412 | 0.158 | −0.208 | 1.272 | |
| Time since transplantation | 0.533 | 0.112 | 4.763 | <0.001 | 0.313 | 0.752 | |
| Medication non-adherence | Physical activity | −0.021 | 0.026 | −0.797 | 0.425 | −0.073 | 0.031 |
| Depression | 0.122 | 0.019 | 6.475 | <0.001 | 0.085 | 0.159 | |
| Gender | 0.389 | 0.138 | 2.824 | 0.005 | 0.119 | 0.659 | |
| Monthly income | 0.258 | 0.070 | 3.703 | <0.001 | 0.121 | 0.394 | |
| Living alone | 0.491 | 0.227 | 2.157 | 0.031 | 0.045 | 0.937 | |
| Time since transplantation | 0.576 | 0.075 | 7.674 | <0.001 | 0.429 | 0.723 |
B, unstandardised coefficients; LLCI, lower level of CI; ULCI, upper level of CI.
Figure 3.
The moderated mediation model of COVID-19 vaccination as moderator (*p<0.05; **p<0.01; ***p<0.001).
Discussion
In this study, we investigated the prevalence and associated factors of immunosuppressant medication behaviours among SOT recipients during the COVID-19 reopening period in China, and delved into a potential mechanism by considering the influence of physical activity and depression. Gender, monthly income, living alone, time since transplantation, COVID-19 vaccination, physical activity and depression were significantly related to medication non-adherence in the current study. Moreover, the results showed that the association between physical activity and medication non-adherence was fully mediated by depression, and COVID-19 vaccination moderated the relationship between physical activity and depression.
The prevalence of non-adherence was 36.3% in the present study, which is similar to previous studies’ results.3 4 Concerning specific patterns of non-adherence, delaying or taking medication 2 hours earlier is the most common non-adherence behaviour (25.2%), with missing one dose ranking second (18.5%). These findings of main non-adherence patterns are consistent with prior research using the same measurement.5 30 These data suggest that the prevalence of non-adherence to immunosuppressants remains high in the SOT recipients. Medication non-adherence could potentially trigger delayed acute rejection, leading to graft loss and subsequently escalating healthcare expenses for subsequent treatments.31 Therefore, it is imperative to identify the factors and develop targeted interventions.
Physical activity was negatively associated with depression, and depression showed a positive association with medication non-adherence in our study. Physical activity is known to have a beneficial effect in improving psychological distress and is recommended by the WHO for individuals with depression.32 Heissel et al conducted a huge meta-analysis with meta-regression and found physical activity has a moderate to major impact on depression symptoms.33 Meanwhile, the results showed depression was a risk factor for medication non-adherence, which is consistent with a previous study.4 12 A meta-analysis showed that depressed patients were three times more likely to manifest non-adherent behaviours.34 Being diagnosed with end-stage kidney disease is a major stressful event, which could lead to the generation of negative emotions such as depressive symptoms. As reported, the prevalence of depressive disorders was 12%–60% in the pre-transplantation stage and 13%–40% in the post-transplantation stage, respectively.35 Depressed recipients are more prone to underestimating the effects of medications and expressing concerns about potential side effects, which could be called negative beliefs about medications.8 In the study conducted by Hugon et al, negative general beliefs about medications were found to predict lower adherence independently in SOT recipients.36 Moreover, depression was observed to be associated with lower self-management in a previous study.37 Thus, based on these findings and the evidence from several systematic reviews, medication adherence of SOT recipients can be improved by psychological strategies targeting depression.38 39 Contrary to hypothesis 1, physical activity did not predict medication non-adherence directly but predicted it indirectly through the mediating effect of depression. This finding underscores the significance of enhancing recipients’ mental health to facilitate medication adherence and highlights the potential role of physical activity in promoting adherence by alleviating depression.
Amidst the backdrop of the threat posed by the COVID-19 pandemic, vaccination can serve as an emotional resource that helps mitigate anxiety and depression.19 However, given that the effectiveness of vaccines is diminished in immunosuppressed patients, particularly among SOT recipients, this psychological protection may be compromised.18 Our study investigated whether vaccination could influence the connection between physical activity and depression. According to the results, the interaction term of COVID-19 vaccination and physical activity negatively predicted depression, indicating vaccination could reinforce the negative effect of physical activity on depression. For SOT recipients who received vaccination, the impact of physical activity on depression was stronger than those who did not. This may be elucidated by the enhancement of physical activity on vaccination effectiveness and the improvement of getting vaccinated on psychological symptoms. Regular physical activity was observed to enhance individuals’ immune function and augment the impact of immunotherapy.40 A recent meta-analysis revealed that participation in a physical activity programme resulted in a notable increase in antibody concentration, underscoring its role in boosting the potency of vaccination.41 Moreover, a case–control study conducted by Collie et al demonstrated a higher level of physical activity was associated with an increased protective effect of the COVID-19 vaccine, as evidenced by a lower incidence of hospitalisation due to COVID-19.42 Combined with the vaccination improving patients’ confidence to face with pandemic as an emotional resource, the negative effect of physical activity on depression is stronger in patients getting vaccinated. In another way, vaccination in China is a voluntary practice, and individuals who actively participate in their healthcare decisions are more inclined to engage in physical activity for the maintenance of their well-being. Consequently, this proactive approach contributes to a decrease in the occurrence of depression.
These findings provide some valuable insights for managing medication non-adherence in SOT recipients when confronting public health emergencies. While physical activity may not have a direct impact on medication non-adherence, its indirect influence should not be overlooked. Meanwhile, physical activity stands as a pivotal component of post-transplant management and rehabilitation. Therefore, it is imperative to develop and implement tailored physical activity programmes for SOT recipients to enhance their medication adherence. Additionally, depression plays a moderating role in the correlation between physical activity and medication non-adherence. It is more closely associated with medication non-adherence than physical activity itself. This underscores the importance of interventions aimed at addressing depression, which are likely to yield more effective results. Strategies such as mindfulness-based therapy and cognitive-behavioural therapy should be applied to SOT recipients to mitigate negative emotions, ultimately reducing non-adherence to medications.
Limitations
Some limitations should be taken into account in this study. First, this study was conducted in a single outpatient clinic in south-central China, which resulted in a lack of representativeness in the sample. Second, it would be beneficial to include other variables related to medication non-adherence, such as illness perception and social support, to gain a more comprehensive understanding of the factors of recipients’ non-adherent behaviour. Third, we used the SPSS PROCESS macro for moderated mediation analysis, which cannot analyse latent variables and does not isolate measurement errors, making it less accurate compared with structural equation modelling for latent variables. Lastly, the relationships observed in the moderated mediation model were identified during a unique moment when recipients were dealing with the pandemic. Since medication non-adherence is a dynamic behaviour and evolves with time, it is important to monitor these relationships after returning to normal life to assess their stability. Despite these limitations, the present study demonstrated a full mediation model of the relationship between physical activity and medication non-adherence, thus providing additional insight into the understanding of recipients’ medication non-adherence.
Conclusion
Our study identified associated factors for immunosuppressant medication non-adherence and found that physical activity was negatively associated with medication non-adherence with depression fully mediating the relationship between them. Moreover, COVID-19 vaccination moderated the effect of physical activity on depression. These findings provide some suggestions for informing strategies to manage medication non-adherence when confronting public health emergencies. However, since the results stem from the COVID-19 reopening period in China, further testing is warranted to assess the stability of the relationships after returning to normal life.
Supplementary Material
Footnotes
ZZ and JL contributed equally.
Contributors: QZ contributed to conceptualisation, formal analysis and writing-original draft. LD and LW contributed to investigation and data curation. HZ and XZ contributed to methodology. ZZ contributed to validation and writing-review and editing. JL contributed to funding acquisition and writing-review and editing. All authors have read and approved the submitted version. JL is responsible for the overall content as guarantor.
Funding: This work was partly supported by the Scientific Research Program of Hunan Provincial Health Commission, China (grant number 202114051600), the Innovative Construction Project of Hunan Province, China (grant number 2022JJ30892), the Fundamental Research Funds for the Central Universities of Central South University (grant number 2023ZZTS0874) and Medical Discipline Young Backbone Talent Program of Hunan Provincial Health Commission (grant number N/A).
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request. The datasets analysed during the current study are available from the corresponding author (JL) on reasonable request.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This study involves human participants and was approved by the Ethics Committee of The Third Xiangya Hospital of Central South University (2020-S333). Participants gave informed consent to participate in the study before taking part.
References
- 1.Shi Y-X, Liu C-X, Liu F, et al. Efficacy of adherence-enhancing interventions for immunosuppressive therapy in solid organ transplant recipients: A systematic review and meta-analysis based on randomized controlled trials. Front Pharmacol 2020;11:578887. 10.3389/fphar.2020.578887 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Kuypers DRJ. From Nonadherence to adherence. Transplantation 2020;104:1330–40. 10.1097/TP.0000000000003112 [DOI] [PubMed] [Google Scholar]
- 3.Wang Y, Veltkamp DMJ, van der Boog PJM, et al. Illness perceptions and medication Nonadherence to immunosuppressants after successful kidney transplantation: A cross-sectional study. Transpl Int 2022;35:10073. 10.3389/ti.2022.10073 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Villeneuve C, Rousseau A, Rerolle J-P, et al. Adherence profiles in kidney transplant patients: causes and consequences. Patient Educ Couns 2020;103:189–98. 10.1016/j.pec.2019.08.002 [DOI] [PubMed] [Google Scholar]
- 5.Zhang P, Zhu X, Yan J, et al. Identification of immunosuppressive medication Nonadherence factors through a combined theory model in renal transplant recipients: 6-12. Front Pharmacol 2021;12:655836. 10.3389/fphar.2021.655836 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mesurado B, Vidal EM, Mestre AL. Negative emotions and behaviour: the role of regulatory emotional self-efficacy. J Adolesc 2018;64:62–71. 10.1016/j.adolescence.2018.01.007 [DOI] [PubMed] [Google Scholar]
- 7.Grenard JL, Munjas BA, Adams JL, et al. Depression and medication adherence in the treatment of chronic diseases in the United States: a meta-analysis. J Gen Intern Med 2011;26:1175–82. 10.1007/s11606-011-1704-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Park S, Jang I. Factors affecting medication adherence in patients with mechanical heart valves taking warfarin: the role of knowledge on warfarin, medication belief, depression, and self-efficacy. Int J Environ Res Public Health 2021;18:5214. 10.3390/ijerph18105214 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kołtuniuk A, Rosińczuk J. The levels of depression, anxiety, acceptance of illness, and medication adherence in patients with multiple sclerosis - descriptive and Correlational study. Int J Med Sci 2021;18:216–25. 10.7150/ijms.51172 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Gonzalez Heredia T, González-Ramírez LP, Hernández-Corona DM, et al. Anxious depression in patients with type 2 diabetes mellitus and its relationship with medication adherence and Glycemic control. Glob Public Health 2021;16:460–8. 10.1080/17441692.2020.1810735 [DOI] [PubMed] [Google Scholar]
- 11.Robiner WN, Petrik ML, Flaherty N, et al. Depression, quantified medication adherence, and quality of life in renal transplant candidates and recipients. J Clin Psychol Med Settings 2022;29:168–84. 10.1007/s10880-021-09792-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Gorevski E, Succop P, Sachdeva J, et al. Is there an association between immunosuppressant therapy medication adherence and depression, quality of life, and personality traits in the kidney and liver transplant population Patient Prefer Adherence 2013;7:301–7. 10.2147/PPA.S34945 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Masiero L, Puoti F, Bellis L, et al. Physical activity and renal function in the Italian kidney transplant population. Ren Fail 2020;42:1192–204. 10.1080/0886022X.2020.1847723 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Dunn MA, Rogal SS, Duarte-Rojo A, et al. Physical function, physical activity, and quality of life after liver transplantation. Liver Transpl 2020;26:702–8. 10.1002/lt.25742 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Wang RT, Sun J, Wei CY, et al. Exercise intervention in the rehabilitation of patients with lung transplantation:a Scoping review. Chinese J Nurs 2022:680–7. [Google Scholar]
- 16.Pearce M, Garcia L, Abbas A, et al. Association between physical activity and risk of depression: A systematic review and meta-analysis. JAMA Psychiatry 2022;79:550–9. 10.1001/jamapsychiatry.2022.0609 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Kandola A, Ashdown-Franks G, Hendrikse J, et al. Physical activity and depression: towards understanding the antidepressant mechanisms of physical activity. Neurosci Biobehav Rev 2019;107:525–39. 10.1016/j.neubiorev.2019.09.040 [DOI] [PubMed] [Google Scholar]
- 18.Lee ARYB, Wong SY, Chai LYA, et al. Efficacy of COVID-19 vaccines in immunocompromised patients: systematic review and meta-analysis. BMJ 2022;376:e068632. 10.1136/bmj-2021-068632 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Garcia-Llana H, Panizo N, Gandía L, et al. COVID-19 vaccination improved psychological distress (anxiety and depression scores) in chronic kidney disease patients: A prospective study. Vaccines (Basel) 2022;10:299. 10.3390/vaccines10020299 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Joseph KL, Dagfinrud H, Christie A, et al. Criterion validity of the International physical activity questionnaire-short form (IPAQ-SF) for use in clinical practice in patients with osteoarthritis. BMC Musculoskelet Disord 2021;22:232. 10.1186/s12891-021-04069-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Held U, Burgstaller JM, Deforth M, et al. Association between depression and anxiety on symptom and function after surgery for lumbar spinal stenosis. Sci Rep 2022;12:2821. 10.1038/s41598-022-06797-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361–70. 10.1111/j.1600-0447.1983.tb09716.x [DOI] [PubMed] [Google Scholar]
- 23.Li Q, Lin Y, Hu C, et al. The Chinese version of hospital anxiety and depression scale: Psychometric properties in Chinese cancer patients and their family Caregivers. Eur J Oncol Nurs 2016;25:16–23. 10.1016/j.ejon.2016.09.004 [DOI] [PubMed] [Google Scholar]
- 24.Leuven-Basel Research Group . Basel assessment of adherence to immunosuppressive medications scale. 2005. Available: https://baasis.nursing.unibas.ch/
- 25.Denhaerynck K, Dobbels F, Košťálová B, et al. Psychometric properties of the BAASIS: A meta-analysis of individual participant data. Transplantation 2023;107:1795–809. 10.1097/TP.0000000000004574 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Elias C, Cherukuri A. BAASIS for monitoring therapy Nonadherence in clinical transplantation: are we there yet Transplantation 2023;107:1673–4. 10.1097/TP.0000000000004575 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. Guilford Press, 2013. [Google Scholar]
- 28.Hayes AF. An index and test of linear moderated mediation. Multivariate Behav Res 2015;50:1–22. 10.1080/00273171.2014.962683 [DOI] [PubMed] [Google Scholar]
- 29.Hayes AF, Rockwood NJ. Regression-based statistical mediation and moderation analysis in clinical research: observations, recommendations, and implementation. Behav Res Ther 2017;98:39–57. 10.1016/j.brat.2016.11.001 [DOI] [PubMed] [Google Scholar]
- 30.Dong L, Zhu X, Zhao H, et al. Development and validation of a LASSO-based prediction model for immunosuppressive medication Nonadherence in kidney transplant recipients. Renal Failure 2023;45. 10.1080/0886022X.2023.2238832 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Denhaerynck K, Dobbels F, Cleemput I, et al. Prevalence, consequences, and determinants of Nonadherence in adult renal transplant patients: a literature review. Transpl Int 2005;18:1121–33. 10.1111/j.1432-2277.2005.00176.x [DOI] [PubMed] [Google Scholar]
- 32.Bull FC, Al-Ansari SS, Biddle S, et al. World health organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 2020;54:1451–62. 10.1136/bjsports-2020-102955 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Heissel A, Heinen D, Brokmeier LL, et al. Exercise as medicine for depressive symptoms? A systematic review and meta-analysis with meta-regression. Br J Sports Med 2023;57:1049–57. 10.1136/bjsports-2022-106282 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch Intern Med 2000;160:2101–7. 10.1001/archinte.160.14.2101 [DOI] [PubMed] [Google Scholar]
- 35.Zwaan M de, Erim Y, Kröncke S, et al. Psychosocial diagnosis and treatment before and after organ transplantation. Dtsch Arztebl Int 2023;120:413–6. 10.3238/arztebl.m2023.0087 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Hugon A, Roustit M, Lehmann A, et al. Influence of intention to adhere, beliefs and satisfaction about medicines on adherence in solid organ transplant recipients. Transplantation 2014;98:222–8. 10.1097/TP.0000000000000221 [DOI] [PubMed] [Google Scholar]
- 37.Schmitt A, Bendig E, Baumeister H, et al. Associations of depression and diabetes distress with self-management behavior and Glycemic control. Health Psychol 2021;40:113–24. 10.1037/hea0001037 [DOI] [PubMed] [Google Scholar]
- 38.Low JK, Williams A, Manias E, et al. Interventions to improve medication adherence in adult kidney transplant recipients: a systematic review. Nephrol Dial Transplant 2015;30:752–61. 10.1093/ndt/gfu204 [DOI] [PubMed] [Google Scholar]
- 39.De Bleser L, Matteson M, Dobbels F, et al. Interventions to improve medication-adherence after transplantation: a systematic review. Transpl Int 2009;22:780–97. 10.1111/j.1432-2277.2009.00881.x [DOI] [PubMed] [Google Scholar]
- 40.Nieman DC, Wentz LM. The compelling link between physical activity and the body’s defense system. J Sport Health Sci 2019;8:201–17. 10.1016/j.jshs.2018.09.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Chastin SFM, Abaraogu U, Bourgois JG, et al. Effects of regular physical activity on the immune system, vaccination and risk of community-acquired infectious disease in the general population: systematic review and meta-analysis. Sports Med 2021;51:1673–86. 10.1007/s40279-021-01466-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Collie S, Saggers RT, Bandini R, et al. Association between regular physical activity and the protective effect of vaccination against SARS-Cov-2 in a South African case-control study. Br J Sports Med 2023;57:205–11. 10.1136/bjsports-2022-105734 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2023-080998supp001.pdf (348.1KB, pdf)
Data Availability Statement
Data are available upon reasonable request. The datasets analysed during the current study are available from the corresponding author (JL) on reasonable request.