Inhaler Technique and Medication Adherence in COPD: Insights from a Nationwide Multicentre Study

Inhaler Technique and Medication Adherence in COPD: Insights from a Nationwide Multicentre Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Inhaler Technique and Medication Adherence in COPD: Insights from a Nationwide Multicentre Study Ahmet Melih Şahin, Elif Şen, Aylin Özgen Alpaydın, Derya Gökmen, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8302012/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Incorrect inhaler technique and poor adherence undermine COPD care, yet their joint determinants are incompletely defined. This study aimed to investigate the prevalence and determinants of critical inhaler errors and non-adherence, and their reciprocal association in COPD. Methods We conducted a nationwide multicentre cross-sectional study (July 2021–February 2022) in 10 tertiary outpatient pulmonary clinics across Turkey. Consecutive COPD patients aged ≥ 40 years using at least one inhaler for ≥ 3 months were included. Inhaler technique was assessed with device-specific checklists, and adherence with the Medication Adherence Report Scale–5 (MARS-5). Logistic regression was applied to identify independent predictors of critical errors and non-adherence. Results Among 358 patients (mean age, 66 years; 81% male), 39.7% had at least one critical error and 29.9% were non-adherent. Critical errors were associated with older age (adjusted OR [aOR], 1.04 per year; 95% CI, 1.01–1.08) and non-adherence (3.36; 1.83–6.18), and were less likely with prior inhaler training (0.23; 0.07–0.74) and uninterrupted medication access (0.32; 0.11–0.97). Non-adherence was less likely with dry-powder inhalers versus pressurised metered-dose inhalers (0.48; 0.28–0.82), prior training (0.38; 0.15–0.96), and uninterrupted access (0.35; 0.16–0.78), and more likely with any critical error (2.69; 1.62–4.46). Discrimination was acceptable (AUC, 0.75 for critical errors; 0.71 for non-adherence). Conclusions Inhaler misuse and medication non-adherence were common and bidirectionally associated. Standardised training and uninterrupted medication access independently lowered risk and represent high-leverage, implementable targets. Integration of digital adherence tools with routine education should be tested in pragmatic trials. COPD Administration Inhalation Medication Errors Medication Adherence Dry Powder Inhalers Pressurised Metered-Dose Inhalers Figures Figure 1 Background Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide and imposes a substantial clinical and socioeconomic burden. 1 Management of COPD is multifactorial, but pharmacological treatment, delivered predominantly via inhalers, remains the cornerstone of care. Inhaled therapy provides the advantage of high local drug concentrations with fewer systemic effects, making it essential in routine care. The effectiveness of these treatments, however, depends on correct inhaler technique. 2 Despite decades of clinical use, inhaler misuse is widespread and represents a modifiable barrier to optimal outcomes. Previous studies have shown that a large proportion of patients make errors when using inhaler devices. Among these, critical errors, defined as those that prevent adequate drug deposition in the lungs, are particularly detrimental and have been linked to reduced treatment effectiveness and worse clinical outcomes. 3 The reported prevalence of critical errors varies widely across studies, ranging from 14% to more than 80% reflecting heterogeneity in study populations and assessment methods. 4 – 6 Patients who make critical errors have higher rates of severe exacerbations compared with those who used inhalers correctly. 5 , 7 Although these issues are well recognized, inhaler misuse remains common, and the determinants of these errors are incompletely understood. 8 The World Health Organization defines adherence as “the extent to which a person’s behaviour—taking medication, following a diet, and/or executing lifestyle changes—corresponds with agreed recommendations from a healthcare provider”. According to WHO’s 2003 report, adherence among patients with chronic diseases in developed countries averages around 50%. 9 More recent systematic reviews have reported a wide range of adherence rates, typically between 30% and 77%, depending on disease context and measurement methods. 10 Poor adherence to medications in COPD is associated with inadequate symptom control, increased risk of exacerbations, greater utilization and costs, impaired quality of life, and higher mortality. 11 Although inhaled medications are central to COPD management, adherence to these therapies remains suboptimal. Although poor inhaler technique and low adherence are widely recognized worldwide as major contributors to adverse COPD outcomes, most studies have examined these issues separately rather than in combination. 8 , 12 , 13 In Turkey, the ADCARE study evaluated adherence and identified depression and low education as predictors, while other reports focused on inhaler errors without linking them to adherence or outcomes. 14 Moreover, previous investigations were often restricted to single devices or descriptive analyses; robust studies linking critical errors to clinical outcomes in multicentre settings are notably lacking. 15 , 16 To address these gaps, we conducted a large multicentre study to simultaneously evaluate inhaler technique, including critical errors, and medication adherence, and to determine the patient- and healthcare related factors associated with these outcomes. Methods Study Design and Setting We conducted a multicentre cross-sectional study (July 2021–February 2022) across 10 tertiary outpatient pulmonary clinics in Turkey. The protocol complied with the Declaration of Helsinki and received ethics approval from Ankara University (08.06.2021; I5-362-21). Consecutive patients attending routine follow-up visits were screened for eligibility. Participation was voluntary, and all participants provided written informed consent. Data privacy and confidentiality were ensured throughout the study in line with institutional data protection protocols. No personal identifiers were collected or stored. All data collection and inhaler technique evaluations were performed face-to-face by the patients’ treating physicians, each of whom had undergone standardised training in inhaler assessment procedures. Participants Inclusion criteria were: diagnosis of COPD based on GOLD 2021 criteria with persistent airflow limitation on prior spirometry (post-bronchodilator FEV₁/FVC < 0.70) 17 , age ≥ 40 years, use of at least one inhaler device for ≥ 3 months, ability to provide informed consent, and ability to complete study questionnaires. Exclusion criteria included known cognitive impairment or severe psychiatric illness, inability to perform inhaler maneuvers (e.g., due to physical disability), exclusive use of nebulized or oral respiratory medications, or any change in inhaler device within the previous 4 weeks, current acute exacerbation of COPD, and history of other chronic pulmonary diseases. Figure 1 summarises the study flow. Data Collection and Measures Demographic and clinical characteristics were recorded using a standardised case report form. Dyspnea severity was assessed using the modified Medical Research Council (mMRC) scale 18 , and health status using the COPD Assessment Test. 19 Spirometry was performed according to European Respiratory Society / American Thoracic Society (ERS/ATS) standards and referenced to Global Lung Function Initiative (GLI 2012) prediction equations. 20 , 21 Medication access was captured for the preceding 3 months and coded as ‘uninterrupted’ if patients reported obtaining all prescribed inhaled medications from a pharmacy without stock-outs or missed fills; otherwise ‘interrupted’. Adherence was assessed using the Medication Adherence Report Scale–5 (MARS-5), a brief validated self-report instrument for assessing non-adherence behaviours. 22 Non-adherence was defined as a MARS-5 score < 23, consistent with prior validation studies including the validated Turkish adaptation of the scale. 23 No study-specific questionnaire was developed for this research. Inhaler Technique Assessment Device-specific checklists derived from ERS and Turkish Thoracic Society (TTS) guidance were used; these checklists were not newly developed but adapted from existing published guidance. Checklists are provided in Supplement Table S1 . Critical errors were defined according to widely used criteria in previous systematic reviews and observational studies, namely errors that prevent adequate drug deposition in the lungs (e.g., failure to exhale before inhalation or poor actuation–inhalation coordination with MDIs). 5 All subjects were evaluated using their own inhaler device (DPI, pMDI). Assessments were performed by trained physicians at each centre, who participated in centralised training and periodic online monitoring and retraining. The presence of at least one critical error was considered positive for the outcome. Non-critical errors were recorded separately. Outcomes The primary outcomes were (1) the presence of at least one critical inhaler error, and (2) non-adherence to inhaled medication, defined as a MARS-5 score < 23. Statistical Analysis Analyses were performed with SPSS version 29.0.1 (IBM Corp). Categorical variables were summarized as counts and percentages, and continuous variables as mean (SD) or median (IQR) depending on Shapiro–Wilk test results. Between-group comparisons used χ² or Fisher’s exact tests for categorical variables and independent-samples t-tests or Mann–Whitney U tests for continuous variables. Missingness was < 2% across variables, and complete-case analyses were applied without imputation. Candidate predictors (p < 0.20 or clinically relevant) were identified by univariate logistic regression and entered into multivariable logistic regression. For categorical variables with more than two levels, dummy coding was used with the most clinically relevant or prevalent category as reference (e.g., pMDI for device type, physician for inhaler trainer). Because ‘inhaler trainer’ was nested within ‘inhaler technique explained (yes/no)’ and introduced collinearity, only the latter was retained. Potential confounding by medication class was assessed by comparing device-specific prevalence of critical errors within each class using χ² or Fisher’s exact test (Supplementary Table 2); classes represented by a single device type were described without statistical comparison. Continuous variables were modeled per unit increase (e.g., per year for age, per 100 mL for FEV₁). Odds ratios (ORs) with 95% confidence intervals (CIs) and exact p-values were reported, with significance set at two-sided p < 0.05. Multicollinearity was excluded (all variance inflation factors 1.07–1.67). Model performance was assessed by pseudo-R² (McFadden, Cox–Snell, Nagelkerke), area under the ROC curve (AUC), and Hosmer–Lemeshow test. The model for critical errors showed AUC = 0.76 (Hosmer–Lemeshow p = 0.420) and for non-adherence AUC = 0.73 (p = 0.580). Sensitivity analyses included re-specifying lung function as absolute FEV₁ rather than percent predicted, re-categorizing device type by drug class, and repeating models with selective removal or addition of covariates; effect estimates remained stable, confirming robustness. Reporting adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 24 Sample Size and Power Sample size was determined by the number of consecutively eligible patients recruited during the study period; no formal a priori calculation was performed. To assess adequacy, we retrospectively evaluated statistical precision. For the primary outcome (critical error), the observed prevalence of ~ 40% in 358 patients yielded a 95% confidence interval with a margin of error of approximately ± 5%. For the secondary outcome (non-adherence, ~ 30%), the margin of error was ± 4.8%. Both outcomes therefore approached the conventional target of ± 5% precision. In logistic regression analyses, 143 critical-error cases and 107 non-adherence cases permitted inclusion of up to 10–14 predictor parameters while maintaining ≥ 10 events per variable, thereby minimizing the risk of overfitting. Results Prevalence and Predictors of Critical Inhaler Error Among the 358 patients included in the study, 142 (39.7%) demonstrated at least one critical inhaler error (Table 1 ). In univariate analyses, critical errors were significantly associated with older age, lower education level, higher mMRC dyspnea scores, lower FEV₁, use of long-term oxygen therapy, home care support, not receiving inhaler technique instruction, limited medication access, and medication non-adherence. Additionally, patients who received inhaler education from pharmacists as compared with physicians had significantly higher odds of critical errors (OR, 3.02; 95% CI, 1.71–5.33; p < 0.001). Subgroup analyses showed no significant difference in critical error prevalence between device types within major medication classes (Supplementary Table 3). Table 1 Baseline Demographic, Clinical, and Inhaler-Related Characteristics of the Study Population (N = 358) Sociodemographic Variables Age, years 66.34 (8.56) Sex Female Male 67 (18.7) 291 (81.3) Education level Primary school 223 (62.2) Secondary/High school 94 (26.2) University or higher 41 (11.4) Clinical Characteristics Smoking status Current smoker 156 (43.6) Former/Never-smoker 202 (56.4) Comorbidity (≥ 1 condition) Present 264 (73.8) Absent 94 (26.2) GOLD Group GOLD A 77 (21.5) GOLD B 77 (21.5) GOLD E 204 (57) mMRC dyspnea score [median (IQR)] 2 (2) CAT total score [median (IQR)] 14 (13.3) Pulmonary function test (during stable period) FEV1, mL 1250 (949) FEV1, % predicted 48.6 (33) FEV1/FVC ratio (%) 58 (18.4) Long-term oxygen therapy Present 103 (28.8) Absent 255 (71.2) Home use of non-invasive ventilation Present 61 (17) Absent 297 (83) Home care support Present 176 (49.1) Absent 182 (50.9) Inhaler-Related Factors Number of inhaler devices currently used One device 96 (26.8) Two or more devices 262 (73.2) Device type • pMDI 111 (31) • DPI 220 (61.5) • DPI + pMDI 27 (7.5) Patient-reported explanation of inhaler technique Present 335 (93.5) Absent 23 (6.5) If yes, provider : • Doctor 236 (70.1) • Nurse 35 (10.6) • Pharmacist 64 (19.3) Uninterrupted medication access (past 3 months) Yes 322 (89.9) No 36 (10.1) MARS – 5 adherence score Adherent (23–25) 251 (70.1) Non-adherent (5–22) 107 (29.9) Presence of critical inhaler error At least one 142 (39.7) No error 216 (60.3) Note . Values are presented as mean (SD), median (IQR), or n (%), as appropriate. In the multivariable logistic regression analysis, four variables remained independently associated with critical inhaler errors: each one-year increase in age was associated with higher odds of error (OR, 1.04; 95% CI, 1.01–1.08; p = 0.018); patients who had received inhaler technique instruction had significantly lower odds of making a critical error (OR, 0.23; 95% CI, 0.07–0.74; p = 0.014); those with uninterrupted access to inhaled medications in the past 3 months also had lower odds (OR, 0.32; 95% CI, 0.11–0.97; p = 0.044); and medication non-adherence as defined by the MARS-5 scale was associated with increased odds of critical error (OR, 3.36; 95% CI, 1.83–6.18; p < 0.001) (Table 2 ). In subgroup analyses by medication class, the prevalence of critical errors did not differ significantly between device types (pMDI, DPI, or both) within LABA + LAMA + ICS and LABA + ICS regimens. For medication classes marketed exclusively in a single device type in Turkey (LAMA, LAMA + LABA, LABA, and SABA ± SAMA), only descriptive results are reported. Detailed distributions are provided in Supplementary Table 2. Table 2 Logistic Regression Analysis of Factors Associated With Critical Inhaler Errors in Patients with COPD OR (95% CI) P Adjusted OR (95% CI) P Sociodemographic Variables Age (years) 1.03 (1.00–1.06) 0.020 1.04 (1.01–1.08) 0.018 Sex (Male vs Female) 0.83 (0.49–1.42) 0.502 Education (University or higher vs primary/secondary school) 0.47 (0.30–0.75) 0.001 0.72 (0.40–1.28) 0.257 Clinical Characteristics Current smoker 1.47 (0.96–2.25) 0.077 1.33 (0.74–2.39) 0.343 Comorbidity (Yes) 1.15 (0.71–1.87) 0.575 GOLD A/B vs. E 1.36 (0.87–2.13) 0.172 mMRC dyspnea score 1.40 (1.14–1.73) 0.001 1.05 (0.75–1.46) 0.774 CAT total score 1.02 (0.99–1.04) 0.141 FEV1 (% predicted) 0.99 (0.98–1.00) 0.182 FEV1/FVC ratio (%) 0.99 (0.98–1.01) 0.430 FEV₁ (per 100 mL increase) 0.95 (0.92–0.99) 0.014 0.98 (0.93–1.03) 0.394 Long-term oxygen therapy (Yes) 1.77 (1.11–2.81) 0.016 1.86 (0.96–3.61) 0.066 Home use of NIV (Yes) 1.73 (1.00–3.01) 0.052 Home care support 2.23 (1.45–3.44) < 0.001 1.73 (0.98–3.06) 0.058 Inhaler-Related Factors Device type (reference: pMDI) └DPI 0.91 (0.57–1.44) 0.680 └DPI + pMDI 0.83 (0.35–1.98) 0.676 Number of inhalers (≥ 2 vs. 1) 1.20 (0.74–1.95) 0.453 Patient-reported explanation of inhaler technique (Yes) 0.27 (0.11–0.63) 0.003 0.23 (0.07–0.74) 0.014 Inhaler trainer (Reference: Doctor) └Nurse vs Doctor 0.95 (0.44–2.03) 0.888 └Pharmacist vs Doctor 3.02 (1.71–5.33) < 0.001 Medication access (Yes) 0.22 (0.10–0.47) < 0.001 0.32 (0.11–0.97) 0.044 Medication non-adherence 3.50 (2.18–5.61) < 0.001 3.36 (1.83–6.18) < 0.001 Note. Results are shown as unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Adjusted ORs were derived from multivariable logistic regression including variables with p < 0.20 in univariate analyses or deemed clinically relevant. Model performance: χ² = 70.2 (df = 10), p < 0.001; McFadden R² = 0.202, Cox–Snell R² = 0.169, Nagelkerke R² = 0.274; area under the curve (AUC) = 0.763. Abbreviations : OR = odds ratio; CI = confidence interval; mMRC = modified Medical Research Council dyspnea scale; CAT = COPD Assessment Test; FEV₁ = forced expiratory volume in 1 second; FVC = forced vital capacity; MARS-5 = Medication Adherence Report Scale; NIV = non-invasive ventilation; GOLD = Global Initiative for Chronic Obstructive Lung Disease. Prevalence and Predictors of Medication Non-Adherence Based on the MARS-5 scale, 107 patients (29.9%) were classified as non-adherent to their inhaled therapy. In univariate analyses, non-adherence was significantly associated with lower education level, current smoking status, not receiving inhaler technique instruction, limited medication access, use of DPI rather than pMDI, and the presence of at least one critical inhaler error. Furthermore, receiving inhaler instruction from nurses or pharmacists—compared with physicians—was associated with significantly higher odds of non-adherence. In the multivariable model, four variables remained independently associated with non-adherence: using a DPI rather than a pMDI was associated with lower odds of non-adherence (OR, 0.48; 95% CI, 0.28–0.82; p = 0.007); having previously received inhaler technique instruction was similarly protective (OR, 0.38; 95% CI, 0.15–0.96; p = 0.040); uninterrupted access to inhaled medications during the past 3 months was also protective (OR, 0.35; 95% CI, 0.16–0.78; p = 0.011); and the presence of at least one critical inhaler error was associated with increased odds of non-adherence (OR, 2.69; 95% CI, 1.62–4.46; p < 0.001) (Table 3 ). Device type was retained in the multivariable model for medication non-adherence because DPI use (vs pMDI) was significantly associated with the outcome in univariate analysis and was considered clinically relevant. Although lower education level and current smoking were significant in univariate analyses, they were not retained in the final multivariable model. Table 3 Logistic Regression Analysis of Factors Associated With Medication Non-Adherence According to the MARS Scale OR (95% CI) P Adjusted OR (95% CI) P Sociodemographic Variables Age (years) 0.99 (0.96–1.02) 0.698 Sex (Male) 1.00 (0.56–1.79) 0.994 Education (University or higher vs primary/secondary school) 0.50 (0.31–0.83) 0.007 0.65 (0.38–1.12) 0.122 Clinical Characteristics Current smoker 1.65 (1.05–2.61) 0.030 1.53 (0.93–2.53) 0.092 Comorbidity (Yes) 0.76 (0.46–1.27) 0.306 GOLD A/B vs. E 1.30 (0.80–2.10) 0.284 mMRC dyspnea score 1.05 (0.84–1.30) 0.641 CAT total score 0.99 (0.96–1.01) 0.509 FEV1 (% predicted) 1.00 (0.99–1.01) 0.831 FEV1/FVC ratio (%) 0.99 (0.97–1.01) 0.304 FEV₁ (per 100 mL increase) 0.98 (0.95–1.02) 0.505 Long-term oxygen therapy (Yes) 0.77 (0.46–1.29) 0.335 Home use of NIV (Yes) 1.17 (0.65–2.12) 0.587 Home care support 1.24 (0.78–1.95) 0.350 Inhaler-Related Factors Number of inhalers (≥ 2 vs. 1) 0.75 (0.45–1.23) 0.262 Device type (reference: pMDI) └DPI 0.44 (0.27–0.73) < 0.001 0.48 (0.28–0.82) 0.007 └DPI + pMDI 0.59 (0.24–1.47) 0.263 0.64 (0.24–1.70) 0.379 Patient-reported explanation of inhaler technique (Yes) 0.23 (0.10–0.54) < 0.001 0.38 (0.15–0.96) 0.040 Inhaler trainer (reference: Doctor) └Nurse 3.69 (1.77–7.71) < 0.001 └Pharmacist 3.24 (1.80–5.82) < 0.001 Medication access (Yes) 0.19 (0.09–0.41) < 0.001 0.35 (0.16–0.78) 0.011 Critical inhaler error (Yes) 3.49 (2.18–5.60) < 0.001 2.69 (1.62–4.46) < 0.001 Note. Results are shown as unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Adjusted ORs were derived from multivariable logistic regression including variables with p < 0.20 in univariate analyses or deemed clinically relevant. Model performance: χ² = 57.5 (df = 7), p < 0.001; McFadden R² = 0.211, Cox–Snell R² = 0.149, Nagelkerke R² = 0.159; area under the curve (AUC) = 0.733. Abbreviations : OR = odds ratio; CI = confidence interval; mMRC = modified Medical Research Council dyspnea scale; CAT = COPD Assessment Test; FEV₁ = forced expiratory volume in 1 second; FVC = forced vital capacity; MARS-5 = Medication Adherence Report Scale; NIV = non-invasive ventilation; GOLD = Global Initiative for Chronic Obstructive Lung Disease. Discussion In this nationwide multicentre study, we found that nearly 40% of patients with COPD committed at least one critical inhaler error and that almost one in three were non-adherent to their prescribed therapy. These high rates indicate that incorrect device use and inadequate adherence remain major challenges in routine COPD care. Our multivariable models showed that both outcomes were shaped by patient-level and system-level determinants and were strongly and bidirectionally associated. Together, these findings identify inhaler misuse and poor adherence as dual, interrelated barriers to effective COPD management. The prevalence of critical inhaler errors in our cohort (39.7%) is consistent with prior evidence showing that misuse is both common and consequential. In a systematic review, Chrystyn and colleagues reported error rates exceeding 50%, and Usmani et al. demonstrated direct associations with exacerbations and healthcare utilization. 5,12 Large outpatient cohorts and elderly populations have similarly highlighted age, education, and socioeconomic status as recurrent determinants, indicating that these problems are not confined to any single region or income setting. 4,13 In our analysis, older age, lack of structured training, pharmacist-delivered instruction, limited medication access, and non-adherence were independent predictors, whereas lung function, dyspnea severity, oxygen therapy, and home care support were not retained after adjustment. The association with pharmacist training should be interpreted cautiously, likely reflecting non-standardised instruction rather than provider-specific limitations. These findings underline that system-level factors are as influential as patient-level characteristics in determining inhaler technique. Device-related differences have been highlighted in prior work, though findings vary by population. The CRITIKAL study, conducted in more than 3,000 asthma patients, reported significant device-specific error patterns, but its results cannot be directly extrapolated to COPD. 25 In line with the multinational PIFotal study, our findings suggest that inhaler errors are ubiquitous across devices, and that their clinical impact is more likely amplified by inconsistent training and limited medication access rather than by device type itself. 26 Other investigations have reported frequent misuse but did not establish robust associations with adherence or outcomes. 27,28 Overall, these findings underscore that inhaler misuse persists across diverse contexts, while our study is one of the few to evaluate inhaler technique and adherence simultaneously and to identify both training-related factors and especially medication access as novel, independent determinants of critical errors. The prevalence of non-adherence in our study (29.9%) was comparable to that reported in major COPD cohorts, such as the TORCH post-hoc analysis (20%) and a German claims study (30%), although higher estimates of 40–70% have also been described depending on methodology. 29,30 Importantly, TORCH demonstrated that non-adherence was associated with increased exacerbations, hospitalizations, and mortality. 29 In our multivariable analysis, non-adherence was independently associated with device type, inadequate inhaler training, limited medication access, and the presence of critical errors, illustrating the reciprocal nature of these barriers. Although low education and smoking were associated with adherence in univariate analyses, they did not remain independent predictors after adjustment. The observed association with device type should be interpreted cautiously, as certain drug classes are marketed only in specific devices, limiting separation of molecule-related from device-related effects. While current GOLD recommendations emphasize simplifying treatment with a single inhaler whenever possible, the number of inhalers showed no consistent association with adherence in our cohort. 2 Across prior research, low education, smoking, and socioeconomic disadvantage have consistently emerged as risk factors, whereas structured training, patient engagement, and disease awareness appear protective. 10,11,31 Our findings highlight that system-level barriers, particularly structured education and uninterrupted medication access, are equally influential. Emerging tools such as digital monitoring and tailored interventions may further improve adherence, though adoption remains limited, especially in upper-middle-income settings such as Turkey where heterogeneous access may amplify these challenges. 32 To our knowledge, this is the first nationwide multicentre study to assess inhaler technique and adherence simultaneously in COPD, integrating sociodemographic, clinical, inhaler-related, and system-level determinants into a single analysis. The inclusion of geographically diverse tertiary centres and face-to-face assessments by trained physicians enhanced representativeness and internal validity. Device-specific checklists based on ERS and TTS guidance ensured methodological consistency. This study has several limitations. The tertiary-care setting may restrict generalisability to community practice; however, the high prevalence of both critical errors and non-adherence even in regularly monitored specialist populations underscores the pervasiveness of these problems. The cross-sectional design limits causal interpretation, and inhaler training procedures were not fully standardised across centres, which may have contributed to variation attributed to trainer type. Although socioeconomic and comorbidity data were collected, their influence could not be examined in sufficient detail. Inhaler technique was assessed at a single time point, preventing evaluation of longitudinal stability or the effect of repeated instruction. Finally, because consecutive sampling was employed and participation rates were extremely high, a complete pre-screening denominator could not be reconstructed, and device–drug class effects could not be fully disentangled, as certain treatments in Turkey are available only in a single device type. Conclusion Inhaler misuse and medication non-adherence remain common and mutually reinforcing barriers to effective COPD management. These outcomes are shaped not only by patient characteristics but also by health system determinants such as training quality and consistent medication access, underscoring the need for a multidimensional approach. Targeted interventions that combine standardised education with policy-level strategies to ensure uninterrupted access to inhaled therapies are both directly actionable and globally relevant. Furthermore, emerging innovations such as digital adherence monitoring and device-based feedback tools warrant integration into future care models, as they may complement traditional interventions and enhance long-term outcomes. Abbreviations AUC: Area under the curve CAT: COPD Assessment Test COPD: Chronic obstructive pulmonary disease DPI: Dry powder inhaler ERS: European Respiratory Society FEV₁: Forced expiratory volume in 1 second FVC: Forced vital capacity GOLD: Global Initiative for Chronic Obstructive Lung Disease mMRC: Modified Medical Research Council dyspnea scale MARS-5: Medication Adherence Report Scale–5 NIV: Non-invasive ventilation pMDI: Pressurised metered-dose inhaler ROC: Receiver operating characteristic Declarations Ethics approval: The study was approved by the Ankara University Faculty of Medicine Ethics Committee (approval number: I5-362-21). All participants provided written informed consent prior to enrolment. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments. Patient consent for publication: Not applicable. This manuscript does not contain any individual person’s identifiable data (including images, videos, or personal details). Data availability statement: De-identified participant data, the analysis code, and the device-specific checklists will be made available from the corresponding author upon reasonable request and subject to institutional approvals and a data-sharing agreement. Competing interests: The authors declare that they have no competing interests. Funding: The authors received no specific funding for this work. Authors’ contributions: Conceptualisation: A.M.Ş., E.Ş., A.O.A, N.K. Methodology: A.M.Ş., E.Ş., A.O.A, N.K. Investigation (site leads and recruitment): E.Ş, A.O.A., E.S, S.N., E.S.Ö., D.P.Y., O.B.T., S.Y., F.E.U., A.G., N.K., A.M., Y.V., A.B., M.P., A.Y., İ.C.,A.K Formal analysis: A.M.Ş, E.Ş, D.G. Data curation: A.M.Ş., site investigators. Writing—original draft: A.M.Ş. Writing—review & editing: A.M.Ş, E.Ş, All authors reviewed and approved the final manuscript. Supervision: E.Ş., A.O.A, N.K. Guarantor: A.M.Ş. Acknowledgements We thank all participating patients and the clinical staff at the ten tertiary outpatient pulmonary clinics for their collaboration. This study was conducted within the framework of the Turkish Thoracic Society COPD Assembly. References Chronic obstructive pulmonary disease (COPD). World Health Organization. Accessed 21 August 25. https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd ). Global Strategy for the Prevention, Diagnosis and Management of Chronic Obstructive Pulmonary Disease. 2025 Report, Global Initiative for Chronic Obstructive Lung Disease . Accessed August 24, 2025. https://goldcopd.org/2025-gold-report Mahler DA, Halpin DMG. Personalizing Selection of Inhaled Delivery Systems in Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc Oct. 2023;20(10):1389–96. 10.1513/AnnalsATS.202304-384CME . Bao LK, Khoa ND, Chi LTK, Anh NT. Prevalence and Factors Affecting Appropriate Inhaler Use in Elderly Patients with Chronic Obstructive Pulmonary Disease: A Prospective Study. J Clin Med. 2023;12(13):4420. 10.3390/jcm12134420 . Chrystyn H, Van Der Palen J, Sharma R, et al. Device errors in asthma and COPD: systematic literature review and meta-analysis. npj Prim Care Respiratory Med. 2017;27(1). 10.1038/s41533-017-0016-z . Lindh A, Theander K, Arne M, et al. Errors in inhaler use related to devices and to inhalation technique among patients with chronic obstructive pulmonary disease in primary health care. Nurs Open. 2019;6(4):1519–27. 10.1002/nop2.357 . Molimard M, Raherison C, Lignot S, et al. Chronic obstructive pulmonary disease exacerbation and inhaler device handling: real-life assessment of 2935 patients. Eur Respir J. 2017;49(2):1601794. 10.1183/13993003.01794-2016 . Sanchis J, Gich I, Pedersen S. Systematic Review of Errors in Inhaler Use. Chest. 2016;150(2):394–406. 10.1016/j.chest.2016.03.041 . Sabaté E. Adherence to long-term therapies: evidence for action. World Health Organization . 2003. Accessed August 29, 2025. https://iris.who.int/handle/10665/42682 Kardas P, Bennett B, Borah B, et al. Medication non-adherence: reflecting on two decades since WHO adherence report and setting goals for the next twenty years. Front Pharmacol. 2024;15doi. 10.3389/fphar.2024.1444012 . Turégano-Yedro M, Trillo-Calvo E, Navarro I, Ros F, et al. Inhaler Adherence in COPD: A Crucial Step Towards the Correct Treatment. Int J Chronic Obstr Pulm Dis. 2023;18:2887–93. 10.2147/copd.s431829 . Usmani OS, Lavorini F, Marshall J, et al. Critical inhaler errors in asthma and COPD: a systematic review of impact on health outcomes. Respir Res. 2018;19(1). 10.1186/s12931-017-0710-y . Wu J, Meng W, Ma Y, et al. Errors and Adherence to Inhaled Medications in Chinese Adults with COPD. J Gen Intern Med. 2024;39(1):69–76. 10.1007/s11606-023-08378-y . Kokturk N, Polatli M, Oguzulgen IK, et al. Adherence to COPD treatment in Turkey and Saudi Arabia: results of the ADCARE study. Int J Chronic Obstr Pulm Dis. 2018;13:1377–88. 10.2147/copd.s150411 . Öztürk C, Kaya A, Bi̇lgi̇n C, et al. Evaluation of inhaler technique and patient satisfaction with fixed-combination budesonide/formoterol dry-powder inhaler in chronic obstructive pulmonary disease (COPD): data on real-life clinical practice in Turkey. Tuberkuloz ve toraks. 2012;301–13. 10.5578/tt.4634 . Ocakli B, Ozmen I, Acarturk Tuncay E, et al. A comparative analysis of errors in inhaler technique among COPD versus asthma patients. Int J Chronic Obstr Pulm Dis. 2018;13:2941–7. 10.2147/copd.s178951 . Global Initiative for Chronic Obstructive Lung Disease, Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease 2021 Report . 2021. Mahler DA, Wells CK. Evaluation of clinical methods for rating dyspnea. Chest Mar. 1988;93(3):580–6. 10.1378/chest.93.3.580 . Jones PW, Harding G, Berry P, Wiklund I, Chen WH, Kline Leidy N. Development and first validation of the COPD Assessment Test. Eur Respir J Sep. 2009;34(3):648–54. 10.1183/09031936.00102509 . Quanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J Dec. 2012;40(6):1324–43. 10.1183/09031936.00080312 . Graham BL, Steenbruggen I, Miller MR, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med Oct. 2019;15(8):e70–88. 10.1164/rccm.201908-1590ST . Horne RW, Hankins J. M. The Medication Adherence Report Scale (MARS): a new measurement tool for eliciting patients’ reports of non-adherence. University College London; 1999. Sen ET, Berk ÖS, SIndel D. The Validity and Reliability Study of the Turkish Adaptation of Medical Adherence Report Scale. J Istanbul Fac Med. 2019;82(1):52–62. 10.26650/IUITFD.414117 . Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344–9. 10.1016/j.jclinepi.2007.11.008 . Price DB, Román-Rodríguez M, McQueen RB, et al. Inhaler Errors in the CRITIKAL Study: Type, Frequency, and Association with Asthma Outcomes. J Allergy Clin Immunology: Pract. 2017;5(4):1071–e10819. 10.1016/j.jaip.2017.01.004 . Kocks J, Bosnic-Anticevich S, Van Cooten J, et al. Identifying critical inhalation technique errors in Dry Powder Inhaler use in patients with COPD based on the association with health status and exacerbations: findings from the multi-country cross-sectional observational PIFotal study. BMC Pulm Med. 2023;23(1). 10.1186/s12890-023-02566-6 . Sriram KB, Percival M. Suboptimal inhaler medication adherence and incorrect technique are common among chronic obstructive pulmonary disease patients. Chronic Resp Dis. 2016;13(1):13–22. 10.1177/1479972315606313 . Duarte-De-Araújo A, Teixeira P, Hespanhol V, Correia-De-Sousa J. COPD: misuse of inhaler devices in clinical practice. Int J Chronic Obstr Pulm Dis. 2019;14:1209–17. 10.2147/copd.s178040 . van Boven JF, Chavannes NH, van der Molen T, Rutten-van Mölken MP, Postma MJ, Vegter S. Clinical and economic impact of non-adherence in COPD: a systematic review. Respir Med Jan. 2014;108(1):103–13. 10.1016/j.rmed.2013.08.044 . Mueller S, Wilke T, Bechtel B, Punekar YS, Mitzner K, Virchow JC. Non-persistence and non-adherence to long-acting COPD medication therapy: A retrospective cohort study based on a large German claims dataset. Respir Med. 2017;2017/01/01:122:1–11. https://doi.org/10.1016/j.rmed.2016.11.008 . Case MA, Eakin MN. Up-to-date guidance towards improving medication adherence in patients with chronic obstructive pulmonary disease. Expert Review of Respiratory Medicine . 2023/07/03 2023;17(7):539–546. 10.1080/17476348.2023.2239708 Aung H, Tan R, Flynn C, et al. Digital remote maintenance inhaler adherence interventions in COPD: a systematic review and meta-analysis. Eur Respiratory Rev. 2024;33(174):240136. 10.1183/16000617.0136-2024 . Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx SupplementaryTable2.docx Supplementary3.STROBEChecklist.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 Jan, 2026 Reviews received at journal 04 Jan, 2026 Reviewers agreed at journal 03 Jan, 2026 Reviewers agreed at journal 30 Dec, 2025 Reviewers invited by journal 19 Dec, 2025 Editor assigned by journal 11 Dec, 2025 Submission checks completed at journal 10 Dec, 2025 First submitted to journal 10 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8302012","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":563123849,"identity":"fc0abf8e-5f7c-4d9e-81b1-135e6c31ecd6","order_by":0,"name":"Ahmet Melih Şahin","email":"data:image/png;base64,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","orcid":"","institution":"Ankara University","correspondingAuthor":true,"prefix":"","firstName":"Ahmet","middleName":"Melih","lastName":"Şahin","suffix":""},{"id":563123850,"identity":"35e2ab46-7995-408b-8654-b573033ada33","order_by":1,"name":"Elif Şen","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Elif","middleName":"","lastName":"Şen","suffix":""},{"id":563123853,"identity":"cdd30915-cbcb-432f-bda6-5164267cfb66","order_by":2,"name":"Aylin Özgen Alpaydın","email":"","orcid":"","institution":"Dokuz Eylül University","correspondingAuthor":false,"prefix":"","firstName":"Aylin","middleName":"Özgen","lastName":"Alpaydın","suffix":""},{"id":563123855,"identity":"051ed930-714f-499c-9672-2ebfa7eeb6eb","order_by":3,"name":"Derya Gökmen","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Derya","middleName":"","lastName":"Gökmen","suffix":""},{"id":563123858,"identity":"2a409a86-fd54-4d74-a1a5-be155c10cc6a","order_by":4,"name":"Sibel Naycı","email":"","orcid":"","institution":"Mersin University","correspondingAuthor":false,"prefix":"","firstName":"Sibel","middleName":"","lastName":"Naycı","suffix":""},{"id":563123859,"identity":"aa68b6d4-dcf7-4ec9-918b-52c0d932fd9c","order_by":5,"name":"Eylem Sercan Özgür","email":"","orcid":"","institution":"Mersin University","correspondingAuthor":false,"prefix":"","firstName":"Eylem","middleName":"Sercan","lastName":"Özgür","suffix":""},{"id":563123860,"identity":"5e8b1daa-9fe5-4567-b514-716525b925cf","order_by":6,"name":"Demet Polat Yuluğ","email":"","orcid":"","institution":"Mersin University","correspondingAuthor":false,"prefix":"","firstName":"Demet","middleName":"Polat","lastName":"Yuluğ","suffix":""},{"id":563123863,"identity":"aec44438-f9ce-4d3b-afa3-d267fd0d340b","order_by":7,"name":"Oya Baydar Toprak","email":"","orcid":"","institution":"Cukurova University","correspondingAuthor":false,"prefix":"","firstName":"Oya","middleName":"Baydar","lastName":"Toprak","suffix":""},{"id":563123864,"identity":"3fa7e6bd-778e-4467-b167-1f4822b51cfb","order_by":8,"name":"Elif Selçuk","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Elif","middleName":"","lastName":"Selçuk","suffix":""},{"id":563123866,"identity":"1defadb5-e4ad-485c-8224-661592d95062","order_by":9,"name":"Salih Yiğit","email":"","orcid":"","institution":"Dokuz Eylül University","correspondingAuthor":false,"prefix":"","firstName":"Salih","middleName":"","lastName":"Yiğit","suffix":""},{"id":563123867,"identity":"abf2dff4-7ba3-4d30-9918-029add12bd73","order_by":10,"name":"Funda Elmas Uysal","email":"","orcid":"","institution":"Ege University","correspondingAuthor":false,"prefix":"","firstName":"Funda","middleName":"Elmas","lastName":"Uysal","suffix":""},{"id":563123868,"identity":"4ea157c9-51f6-439e-b3c4-15a2ecd81cc5","order_by":11,"name":"Alev Gürgün","email":"","orcid":"","institution":"Ege University","correspondingAuthor":false,"prefix":"","firstName":"Alev","middleName":"","lastName":"Gürgün","suffix":""},{"id":563123869,"identity":"47ce9cd7-485c-4a0c-83ff-e1baee0e9db4","order_by":12,"name":"Nurdan Köktürk","email":"","orcid":"","institution":"Gazi University","correspondingAuthor":false,"prefix":"","firstName":"Nurdan","middleName":"","lastName":"Köktürk","suffix":""},{"id":563123870,"identity":"9293c48d-fafd-4250-99ca-72b7fee2c43c","order_by":13,"name":"Ayshan Mammadova","email":"","orcid":"","institution":"Gazi University","correspondingAuthor":false,"prefix":"","firstName":"Ayshan","middleName":"","lastName":"Mammadova","suffix":""},{"id":563123871,"identity":"88a84604-8843-44b1-a055-8b301b7566b3","order_by":14,"name":"Yelda Varol","email":"","orcid":"","institution":"Dr. Suat Seren Göğüs Hastalıkları Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Yelda","middleName":"","lastName":"Varol","suffix":""},{"id":563123872,"identity":"d065d5da-bc41-4f98-91ea-cc44ad9d2c7f","order_by":15,"name":"Ayşe Baha","email":"","orcid":"","institution":"Near East University","correspondingAuthor":false,"prefix":"","firstName":"Ayşe","middleName":"","lastName":"Baha","suffix":""},{"id":563123875,"identity":"520dcd15-9abe-4b3e-be4a-90dddc864ad4","order_by":16,"name":"Mehmet Polatlı","email":"","orcid":"","institution":"Adnan Menderes University","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"","lastName":"Polatlı","suffix":""},{"id":563123877,"identity":"714ce805-66d8-47f1-ab5e-83e653625780","order_by":17,"name":"Aybüke Yaz","email":"","orcid":"","institution":"Adnan Menderes University","correspondingAuthor":false,"prefix":"","firstName":"Aybüke","middleName":"","lastName":"Yaz","suffix":""},{"id":563123879,"identity":"ad6cea38-98a9-418a-b6fb-15400ea14fb7","order_by":18,"name":"İpek Candemir","email":"","orcid":"","institution":"Ankara City Hospital","correspondingAuthor":false,"prefix":"","firstName":"İpek","middleName":"","lastName":"Candemir","suffix":""},{"id":563123881,"identity":"ff693edd-163b-4ddf-90e2-5b20e71d4edc","order_by":19,"name":"Ali Kocabaş","email":"","orcid":"","institution":"Cukurova University","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Kocabaş","suffix":""}],"badges":[],"createdAt":"2025-12-07 21:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8302012/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8302012/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99189881,"identity":"cf8bfe1a-4985-4278-a575-77957f0428c5","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"png","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":164309,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.Studyflow.png","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/baba968a384b310c1b7a522a.png"},{"id":99317109,"identity":"996b8f9c-4b36-476d-a90d-4ed0a18ed891","added_by":"auto","created_at":"2025-12-31 16:29:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":259989,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptupdated10.12.25.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/0af363f2971780b11e45711c.docx"},{"id":99189886,"identity":"08c74b7d-6679-4ee6-9254-0189a2af7413","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20129,"visible":true,"origin":"","legend":"","description":"","filename":"Table1..docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/83afb925e72b0b14e27a6798.docx"},{"id":99189883,"identity":"a5baf805-1149-45f5-a565-e5a93de2e946","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18463,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/eb3a31c84f8f46acb040bee9.docx"},{"id":99189889,"identity":"c21d835a-908e-47d2-a7f7-7a20f4dc4e72","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18248,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/799dc625ac6e19960b8b604b.docx"},{"id":99189893,"identity":"b363ee82-618f-4025-9d1c-186a1f38254c","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"json","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18670,"visible":true,"origin":"","legend":"","description":"","filename":"cb84688540374023b3adb8c5945136b3.json","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/0863f3a72354de12db08174c.json"},{"id":99316473,"identity":"c6ad0264-a953-45e4-9e91-853dd6c30e11","added_by":"auto","created_at":"2025-12-31 16:28:30","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":35753,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary3.STROBEChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/fb6c81b7c76bdd74c4e565e9.docx"},{"id":99189887,"identity":"fae40df5-f7bc-40ff-96a2-f6e84f331dc8","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":31747,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/a45913a10468b66d473d69f3.docx"},{"id":99189899,"identity":"939293f1-702b-47a6-8b2e-e9ad2fa3b1fb","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17155,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/cb9c188bc434fda8118e217a.docx"},{"id":99189895,"identity":"9066f81d-3e46-42c6-b337-892d80a1ecc2","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171973,"visible":true,"origin":"","legend":"","description":"","filename":"cb84688540374023b3adb8c5945136b31enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/82b7527e64e07a9460806c3c.xml"},{"id":99318363,"identity":"4111271d-f8f2-415b-a9ba-02e2dccee222","added_by":"auto","created_at":"2025-12-31 16:32:55","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":164309,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.Studyflow.png","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/e96dd0892ff709783fc83bc5.png"},{"id":99189896,"identity":"6d039e3d-dde5-41ed-b1ff-6145e0ded995","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":164309,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.Studyflow.png","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/43fd78eb73158aab1b342d7e.png"},{"id":99189894,"identity":"00b9be0a-930d-43bc-b8ef-a7d69e640baf","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90557,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.Studyflow.png","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/5394b6701e5b05b0435245a8.png"},{"id":99189891,"identity":"67d3abce-2773-4779-84ae-b86d4b4bde3a","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90557,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/e9f2a2295a7cbd31abcad882.png"},{"id":99189900,"identity":"517263fe-8b60-4bb8-961b-c9d7bf6fdfb6","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"xml","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":168714,"visible":true,"origin":"","legend":"","description":"","filename":"cb84688540374023b3adb8c5945136b31structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/1e570e2f342b7fed83cbad51.xml"},{"id":99189901,"identity":"6228b370-2a99-4a3f-9019-dc78ade8cc5c","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":190560,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/46d72dbbe462a19024cbe89a.html"},{"id":99189882,"identity":"1d23f104-9ef4-4c69-a198-a04c5cb79c47","added_by":"auto","created_at":"2025-12-30 00:48:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":226267,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow. Consecutive sampling at 10 tertiary clinics between July 2021 and February 2022. Reasons for exclusion are shown.\u003c/p\u003e","description":"","filename":"Figure1.Studyflow.png","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/89298c168c3a4d90b2ecf2dc.png"},{"id":99787981,"identity":"86b797cc-7fbb-4441-b6f6-2330351e4fca","added_by":"auto","created_at":"2026-01-08 12:42:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1924460,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/029fcff8-dd27-421f-89fd-2fc28b97e3b9.pdf"},{"id":99316749,"identity":"9992de03-a3c0-469c-8809-862a8899b0d0","added_by":"auto","created_at":"2025-12-31 16:29:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":31747,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/1e0b0aadd921502a94d1923d.docx"},{"id":99316917,"identity":"f118d73a-c8e2-4eae-a66e-878b6b0460ec","added_by":"auto","created_at":"2025-12-31 16:29:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17155,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/e4b7d45acedcc274a6752500.docx"},{"id":99316085,"identity":"651454ea-e44b-43f9-8b58-df8052e7e8ae","added_by":"auto","created_at":"2025-12-31 16:27:43","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":35753,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary3.STROBEChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-8302012/v1/0c90aeefeed55dae43295035.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inhaler Technique and Medication Adherence in COPD: Insights from a Nationwide Multicentre Study","fulltext":[{"header":"Background","content":"\u003cp\u003eChronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide and imposes a substantial clinical and socioeconomic burden.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Management of COPD is multifactorial, but pharmacological treatment, delivered predominantly via inhalers, remains the cornerstone of care. Inhaled therapy provides the advantage of high local drug concentrations with fewer systemic effects, making it essential in routine care. The effectiveness of these treatments, however, depends on correct inhaler technique.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Despite decades of clinical use, inhaler misuse is widespread and represents a modifiable barrier to optimal outcomes.\u003c/p\u003e \u003cp\u003ePrevious studies have shown that a large proportion of patients make errors when using inhaler devices. Among these, critical errors, defined as those that prevent adequate drug deposition in the lungs, are particularly detrimental and have been linked to reduced treatment effectiveness and worse clinical outcomes.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e The reported prevalence of critical errors varies widely across studies, ranging from 14% to more than 80% reflecting heterogeneity in study populations and assessment methods.\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Patients who make critical errors have higher rates of severe exacerbations compared with those who used inhalers correctly.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Although these issues are well recognized, inhaler misuse remains common, and the determinants of these errors are incompletely understood.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe World Health Organization defines adherence as \u0026ldquo;the extent to which a person\u0026rsquo;s behaviour\u0026mdash;taking medication, following a diet, and/or executing lifestyle changes\u0026mdash;corresponds with agreed recommendations from a healthcare provider\u0026rdquo;. According to WHO\u0026rsquo;s 2003 report, adherence among patients with chronic diseases in developed countries averages around 50%.\u003csup\u003e9\u003c/sup\u003e More recent systematic reviews have reported a wide range of adherence rates, typically between 30% and 77%, depending on disease context and measurement methods.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Poor adherence to medications in COPD is associated with inadequate symptom control, increased risk of exacerbations, greater utilization and costs, impaired quality of life, and higher mortality.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Although inhaled medications are central to COPD management, adherence to these therapies remains suboptimal.\u003c/p\u003e \u003cp\u003eAlthough poor inhaler technique and low adherence are widely recognized worldwide as major contributors to adverse COPD outcomes, most studies have examined these issues separately rather than in combination.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e In Turkey, the ADCARE study evaluated adherence and identified depression and low education as predictors, while other reports focused on inhaler errors without linking them to adherence or outcomes.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Moreover, previous investigations were often restricted to single devices or descriptive analyses; robust studies linking critical errors to clinical outcomes in multicentre settings are notably lacking.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e To address these gaps, we conducted a large multicentre study to simultaneously evaluate inhaler technique, including critical errors, and medication adherence, and to determine the patient- and healthcare related factors associated with these outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eWe conducted a multicentre cross-sectional study (July 2021\u0026ndash;February 2022) across 10 tertiary outpatient pulmonary clinics in Turkey. The protocol complied with the Declaration of Helsinki and received ethics approval from Ankara University (08.06.2021; I5-362-21). Consecutive patients attending routine follow-up visits were screened for eligibility. Participation was voluntary, and all participants provided written informed consent. Data privacy and confidentiality were ensured throughout the study in line with institutional data protection protocols. No personal identifiers were collected or stored. All data collection and inhaler technique evaluations were performed face-to-face by the patients\u0026rsquo; treating physicians, each of whom had undergone standardised training in inhaler assessment procedures.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eInclusion criteria were: diagnosis of COPD based on GOLD 2021 criteria with persistent airflow limitation on prior spirometry (post-bronchodilator FEV₁/FVC\u0026thinsp;\u0026lt;\u0026thinsp;0.70)\u003csup\u003e17\u003c/sup\u003e, age\u0026thinsp;\u0026ge;\u0026thinsp;40 years, use of at least one inhaler device for \u0026ge;\u0026thinsp;3 months, ability to provide informed consent, and ability to complete study questionnaires. Exclusion criteria included known cognitive impairment or severe psychiatric illness, inability to perform inhaler maneuvers (e.g., due to physical disability), exclusive use of nebulized or oral respiratory medications, or any change in inhaler device within the previous 4 weeks, current acute exacerbation of COPD, and history of other chronic pulmonary diseases. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the study flow.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eData Collection and Measures\u003c/h3\u003e\n\u003cp\u003eDemographic and clinical characteristics were recorded using a standardised case report form. Dyspnea severity was assessed using the modified Medical Research Council (mMRC) scale\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and health status using the COPD Assessment Test.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Spirometry was performed according to European Respiratory Society / American Thoracic Society (ERS/ATS) standards and referenced to Global Lung Function Initiative (GLI 2012) prediction equations.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Medication access was captured for the preceding 3 months and coded as \u0026lsquo;uninterrupted\u0026rsquo; if patients reported obtaining all prescribed inhaled medications from a pharmacy without stock-outs or missed fills; otherwise \u0026lsquo;interrupted\u0026rsquo;. Adherence was assessed using the Medication Adherence Report Scale\u0026ndash;5 (MARS-5), a brief validated self-report instrument for assessing non-adherence behaviours.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Non-adherence was defined as a MARS-5 score\u0026thinsp;\u0026lt;\u0026thinsp;23, consistent with prior validation studies including the validated Turkish adaptation of the scale.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e No study-specific questionnaire was developed for this research.\u003c/p\u003e\n\u003ch3\u003eInhaler Technique Assessment\u003c/h3\u003e\n\u003cp\u003eDevice-specific checklists derived from ERS and Turkish Thoracic Society (TTS) guidance were used; these checklists were not newly developed but adapted from existing published guidance. Checklists are provided in Supplement Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Critical errors were defined according to widely used criteria in previous systematic reviews and observational studies, namely errors that prevent adequate drug deposition in the lungs (e.g., failure to exhale before inhalation or poor actuation\u0026ndash;inhalation coordination with MDIs).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e All subjects were evaluated using their own inhaler device (DPI, pMDI). Assessments were performed by trained physicians at each centre, who participated in centralised training and periodic online monitoring and retraining. The presence of at least one critical error was considered positive for the outcome. Non-critical errors were recorded separately.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcomes were (1) the presence of at least one critical inhaler error, and (2) non-adherence to inhaled medication, defined as a MARS-5 score\u0026thinsp;\u0026lt;\u0026thinsp;23.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAnalyses were performed with SPSS version 29.0.1 (IBM Corp). Categorical variables were summarized as counts and percentages, and continuous variables as mean (SD) or median (IQR) depending on Shapiro\u0026ndash;Wilk test results. Between-group comparisons used χ\u0026sup2; or Fisher\u0026rsquo;s exact tests for categorical variables and independent-samples t-tests or Mann\u0026ndash;Whitney U tests for continuous variables.\u003c/p\u003e \u003cp\u003eMissingness was \u0026lt;\u0026thinsp;2% across variables, and complete-case analyses were applied without imputation. Candidate predictors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 or clinically relevant) were identified by univariate logistic regression and entered into multivariable logistic regression. For categorical variables with more than two levels, dummy coding was used with the most clinically relevant or prevalent category as reference (e.g., pMDI for device type, physician for inhaler trainer). Because \u0026lsquo;inhaler trainer\u0026rsquo; was nested within \u0026lsquo;inhaler technique explained (yes/no)\u0026rsquo; and introduced collinearity, only the latter was retained. Potential confounding by medication class was assessed by comparing device-specific prevalence of critical errors within each class using χ\u0026sup2; or Fisher\u0026rsquo;s exact test (Supplementary Table\u0026nbsp;2); classes represented by a single device type were described without statistical comparison. Continuous variables were modeled per unit increase (e.g., per year for age, per 100 mL for FEV₁). Odds ratios (ORs) with 95% confidence intervals (CIs) and exact p-values were reported, with significance set at two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eMulticollinearity was excluded (all variance inflation factors 1.07\u0026ndash;1.67). Model performance was assessed by pseudo-R\u0026sup2; (McFadden, Cox\u0026ndash;Snell, Nagelkerke), area under the ROC curve (AUC), and Hosmer\u0026ndash;Lemeshow test. The model for critical errors showed AUC\u0026thinsp;=\u0026thinsp;0.76 (Hosmer\u0026ndash;Lemeshow p\u0026thinsp;=\u0026thinsp;0.420) and for non-adherence AUC\u0026thinsp;=\u0026thinsp;0.73 (p\u0026thinsp;=\u0026thinsp;0.580). Sensitivity analyses included re-specifying lung function as absolute FEV₁ rather than percent predicted, re-categorizing device type by drug class, and repeating models with selective removal or addition of covariates; effect estimates remained stable, confirming robustness.\u003c/p\u003e \u003cp\u003eReporting adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample Size and Power\u003c/h3\u003e\n\u003cp\u003eSample size was determined by the number of consecutively eligible patients recruited during the study period; no formal a priori calculation was performed. To assess adequacy, we retrospectively evaluated statistical precision. For the primary outcome (critical error), the observed prevalence of ~\u0026thinsp;40% in 358 patients yielded a 95% confidence interval with a margin of error of approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;5%. For the secondary outcome (non-adherence, ~\u0026thinsp;30%), the margin of error was \u0026plusmn;\u0026thinsp;4.8%. Both outcomes therefore approached the conventional target of \u0026plusmn;\u0026thinsp;5% precision. In logistic regression analyses, 143 critical-error cases and 107 non-adherence cases permitted inclusion of up to 10\u0026ndash;14 predictor parameters while maintaining\u0026thinsp;\u0026ge;\u0026thinsp;10 events per variable, thereby minimizing the risk of overfitting.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003ePrevalence and Predictors of Critical Inhaler Error\u003c/h2\u003e\n \u003cp\u003eAmong the 358 patients included in the study, 142 (39.7%) demonstrated at least one critical inhaler error (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In univariate analyses, critical errors were significantly associated with older age, lower education level, higher mMRC dyspnea scores, lower FEV₁, use of long-term oxygen therapy, home care support, not receiving inhaler technique instruction, limited medication access, and medication non-adherence. Additionally, patients who received inhaler education from pharmacists as compared with physicians had significantly higher odds of critical errors (OR, 3.02; 95% CI, 1.71\u0026ndash;5.33; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Subgroup analyses showed no significant difference in critical error prevalence between device types within major medication classes (Supplementary Table\u0026nbsp;3).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eBaseline Demographic, Clinical, and Inhaler-Related Characteristics of the Study Population (N\u0026thinsp;=\u0026thinsp;358)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSociodemographic Variables\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e66.34 (8.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e291 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e223 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary/High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e94 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e41 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e156 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFormer/Never-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e202 (56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity (\u0026ge;\u0026thinsp;1 condition)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e264 (73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e94 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOLD Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOLD A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e77 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOLD B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e77 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOLD E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e204 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003emMRC dyspnea score [median (IQR)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAT total score [median (IQR)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e14 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary function test (during stable period)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1250 (949)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1, % predicted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e48.6 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1/FVC ratio (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e58 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLong-term oxygen therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e103 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e255 (71.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome use of non-invasive ventilation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e61 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e297 (83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome care support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e176 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e182 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhaler-Related Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of inhaler devices currently used\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOne device\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e96 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwo or more devices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e262 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDevice type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026bull; pMDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e111 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026bull; DPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e220 (61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026bull; DPI\u0026thinsp;+\u0026thinsp;pMDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e27 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient-reported explanation of inhaler technique\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e335 (93.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eIf yes, provider\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026bull; Doctor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e236 (70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026bull; Nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e35 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026bull; Pharmacist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e64 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUninterrupted medication access (past 3 months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e322 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMARS \u0026ndash; 5 adherence score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdherent (23\u0026ndash;25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e251 (70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-adherent (5\u0026ndash;22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e107 (29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresence of critical inhaler error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAt least one\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e142 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e216 (60.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e. Values are presented as mean (SD), median (IQR), or n (%), as appropriate.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eIn the multivariable logistic regression analysis, four variables remained independently associated with critical inhaler errors: each one-year increase in age was associated with higher odds of error (OR, 1.04; 95% CI, 1.01\u0026ndash;1.08; p\u0026thinsp;=\u0026thinsp;0.018); patients who had received inhaler technique instruction had significantly lower odds of making a critical error (OR, 0.23; 95% CI, 0.07\u0026ndash;0.74; p\u0026thinsp;=\u0026thinsp;0.014); those with uninterrupted access to inhaled medications in the past 3 months also had lower odds (OR, 0.32; 95% CI, 0.11\u0026ndash;0.97; p\u0026thinsp;=\u0026thinsp;0.044); and medication non-adherence as defined by the MARS-5 scale was associated with increased odds of critical error (OR, 3.36; 95% CI, 1.83\u0026ndash;6.18; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In subgroup analyses by medication class, the prevalence of critical errors did not differ significantly between device types (pMDI, DPI, or both) within LABA\u0026thinsp;+\u0026thinsp;LAMA\u0026thinsp;+\u0026thinsp;ICS and LABA\u0026thinsp;+\u0026thinsp;ICS regimens. For medication classes marketed exclusively in a single device type in Turkey (LAMA, LAMA\u0026thinsp;+\u0026thinsp;LABA, LABA, and SABA\u0026thinsp;\u0026plusmn;\u0026thinsp;SAMA), only descriptive results are reported. Detailed distributions are provided in Supplementary Table\u0026nbsp;2.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic Regression Analysis of Factors Associated With Critical Inhaler Errors in Patients with COPD\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSociodemographic Variables\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03 (1.00\u0026ndash;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.04 (1.01\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (Male vs Female)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83 (0.49\u0026ndash;1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation (University or higher vs primary/secondary school)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47 (0.30\u0026ndash;0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.72 (0.40\u0026ndash;1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent smoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.47 (0.96\u0026ndash;2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.33 (0.74\u0026ndash;2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15 (0.71\u0026ndash;1.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOLD A/B vs. E\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36 (0.87\u0026ndash;2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003emMRC dyspnea score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40 (1.14\u0026ndash;1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.05 (0.75\u0026ndash;1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAT total score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.99\u0026ndash;1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV1 (% predicted)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99 (0.98\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV1/FVC ratio (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99 (0.98\u0026ndash;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV₁ (per 100 mL increase)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 (0.92\u0026ndash;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.98 (0.93\u0026ndash;1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLong-term oxygen therapy (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.77 (1.11\u0026ndash;2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.86 (0.96\u0026ndash;3.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome use of NIV (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.73 (1.00\u0026ndash;3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome care support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.23 (1.45\u0026ndash;3.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.73 (0.98\u0026ndash;3.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhaler-Related Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDevice type (reference: pMDI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└DPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91 (0.57\u0026ndash;1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└DPI\u0026thinsp;+\u0026thinsp;pMDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83 (0.35\u0026ndash;1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of inhalers (\u0026ge;\u0026thinsp;2 vs. 1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20 (0.74\u0026ndash;1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient-reported explanation of inhaler technique (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27 (0.11\u0026ndash;0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.23 (0.07\u0026ndash;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhaler trainer (Reference: Doctor)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└Nurse vs Doctor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 (0.44\u0026ndash;2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└Pharmacist vs Doctor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.02 (1.71\u0026ndash;5.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication access (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22 (0.10\u0026ndash;0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.32 (0.11\u0026ndash;0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication non-adherence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.50 (2.18\u0026ndash;5.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.36 (1.83\u0026ndash;6.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cstrong\u003eNote.\u003c/strong\u003e Results are shown as unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Adjusted ORs were derived from multivariable logistic regression including variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 in univariate analyses or deemed clinically relevant. Model performance: \u0026chi;\u0026sup2; = 70.2 (df\u0026thinsp;=\u0026thinsp;10), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; McFadden R\u0026sup2; = 0.202, Cox\u0026ndash;Snell R\u0026sup2; = 0.169, Nagelkerke R\u0026sup2; = 0.274; area under the curve (AUC)\u0026thinsp;=\u0026thinsp;0.763.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: OR\u0026thinsp;=\u0026thinsp;odds ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval; mMRC\u0026thinsp;=\u0026thinsp;modified Medical Research Council dyspnea scale; CAT\u0026thinsp;=\u0026thinsp;COPD Assessment Test; FEV₁ = forced expiratory volume in 1 second; FVC\u0026thinsp;=\u0026thinsp;forced vital capacity; MARS-5\u0026thinsp;=\u0026thinsp;Medication Adherence Report Scale; NIV\u0026thinsp;=\u0026thinsp;non-invasive ventilation; GOLD\u0026thinsp;=\u0026thinsp;Global Initiative for Chronic Obstructive Lung Disease.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003ePrevalence and Predictors of Medication Non-Adherence\u003c/h2\u003e\n \u003cp\u003eBased on the MARS-5 scale, 107 patients (29.9%) were classified as non-adherent to their inhaled therapy. In univariate analyses, non-adherence was significantly associated with lower education level, current smoking status, not receiving inhaler technique instruction, limited medication access, use of DPI rather than pMDI, and the presence of at least one critical inhaler error. Furthermore, receiving inhaler instruction from nurses or pharmacists\u0026mdash;compared with physicians\u0026mdash;was associated with significantly higher odds of non-adherence.\u003c/p\u003e\n \u003cp\u003eIn the multivariable model, four variables remained independently associated with non-adherence: using a DPI rather than a pMDI was associated with lower odds of non-adherence (OR, 0.48; 95% CI, 0.28\u0026ndash;0.82; p\u0026thinsp;=\u0026thinsp;0.007); having previously received inhaler technique instruction was similarly protective (OR, 0.38; 95% CI, 0.15\u0026ndash;0.96; p\u0026thinsp;=\u0026thinsp;0.040); uninterrupted access to inhaled medications during the past 3 months was also protective (OR, 0.35; 95% CI, 0.16\u0026ndash;0.78; p\u0026thinsp;=\u0026thinsp;0.011); and the presence of at least one critical inhaler error was associated with increased odds of non-adherence (OR, 2.69; 95% CI, 1.62\u0026ndash;4.46; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Device type was retained in the multivariable model for medication non-adherence because DPI use (vs pMDI) was significantly associated with the outcome in univariate analysis and was considered clinically relevant. Although lower education level and current smoking were significant in univariate analyses, they were not retained in the final multivariable model.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic Regression Analysis of Factors Associated With Medication Non-Adherence According to the MARS Scale\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSociodemographic Variables\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.99 (0.96\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (Male)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.00 (0.56\u0026ndash;1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation (University or higher vs primary/secondary school)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.50 (0.31\u0026ndash;0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.65 (0.38\u0026ndash;1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent smoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.65 (1.05\u0026ndash;2.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.53 (0.93\u0026ndash;2.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.76 (0.46\u0026ndash;1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOLD A/B vs. E\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.30 (0.80\u0026ndash;2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003emMRC dyspnea score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.05 (0.84\u0026ndash;1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAT total score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.99 (0.96\u0026ndash;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV1 (% predicted)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.00 (0.99\u0026ndash;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV1/FVC ratio (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.99 (0.97\u0026ndash;1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV₁ (per 100 mL increase)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.98 (0.95\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLong-term oxygen therapy (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.77 (0.46\u0026ndash;1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome use of NIV (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.17 (0.65\u0026ndash;2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome care support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.24 (0.78\u0026ndash;1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhaler-Related Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of inhalers (\u0026ge;\u0026thinsp;2 vs. 1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.75 (0.45\u0026ndash;1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDevice type (reference: pMDI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└DPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.44 (0.27\u0026ndash;0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.48 (0.28\u0026ndash;0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└DPI\u0026thinsp;+\u0026thinsp;pMDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.59 (0.24\u0026ndash;1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.64 (0.24\u0026ndash;1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient-reported explanation of inhaler technique (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.23 (0.10\u0026ndash;0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.38 (0.15\u0026ndash;0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhaler trainer (reference: Doctor)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└Nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.69 (1.77\u0026ndash;7.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e└Pharmacist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.24 (1.80\u0026ndash;5.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication access (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.19 (0.09\u0026ndash;0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.35 (0.16\u0026ndash;0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCritical inhaler error (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.49 (2.18\u0026ndash;5.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.69 (1.62\u0026ndash;4.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\u003cstrong\u003eNote.\u003c/strong\u003e Results are shown as unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Adjusted ORs were derived from multivariable logistic regression including variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 in univariate analyses or deemed clinically relevant. Model performance: \u0026chi;\u0026sup2; = 57.5 (df\u0026thinsp;=\u0026thinsp;7), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; McFadden R\u0026sup2; = 0.211, Cox\u0026ndash;Snell R\u0026sup2; = 0.149, Nagelkerke R\u0026sup2; = 0.159; area under the curve (AUC)\u0026thinsp;=\u0026thinsp;0.733.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: OR\u0026thinsp;=\u0026thinsp;odds ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval; mMRC\u0026thinsp;=\u0026thinsp;modified Medical Research Council dyspnea scale; CAT\u0026thinsp;=\u0026thinsp;COPD Assessment Test; FEV₁ = forced expiratory volume in 1 second; FVC\u0026thinsp;=\u0026thinsp;forced vital capacity; MARS-5\u0026thinsp;=\u0026thinsp;Medication Adherence Report Scale; NIV\u0026thinsp;=\u0026thinsp;non-invasive ventilation; GOLD\u0026thinsp;=\u0026thinsp;Global Initiative for Chronic Obstructive Lung Disease.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this nationwide multicentre study, we found that nearly 40% of patients with COPD committed at least one critical inhaler error and that almost one in three were non-adherent to their prescribed therapy. These high rates indicate that incorrect device use and inadequate adherence remain major challenges in routine COPD care. Our multivariable models showed that both outcomes were shaped by patient-level and system-level determinants and were strongly and bidirectionally associated. Together, these findings identify inhaler misuse and poor adherence as dual, interrelated barriers to effective COPD management.\u003c/p\u003e\n\u003cp\u003eThe prevalence of critical inhaler errors in our cohort (39.7%) is consistent with prior evidence showing that misuse is both common and consequential. In a systematic review, Chrystyn and colleagues reported error rates exceeding 50%, and Usmani et al. demonstrated direct associations with exacerbations and healthcare utilization.\u003csup\u003e5,12\u003c/sup\u003e Large outpatient cohorts and elderly populations have similarly highlighted age, education, and socioeconomic status as recurrent determinants, indicating that these problems are not confined to any single region or income setting.\u003csup\u003e4,13\u003c/sup\u003e In our analysis, older age, lack of structured training, pharmacist-delivered instruction, limited medication access, and non-adherence were independent predictors, whereas lung function, dyspnea severity, oxygen therapy, and home care support were not retained after adjustment. The association with pharmacist training should be interpreted cautiously, likely reflecting non-standardised instruction rather than provider-specific limitations. These findings underline that system-level factors are as influential as patient-level characteristics in determining inhaler technique. Device-related differences have been highlighted in prior work, though findings vary by population. The CRITIKAL study, conducted in more than 3,000 asthma patients, reported significant device-specific error patterns, but its results cannot be directly extrapolated to COPD.\u003csup\u003e25\u003c/sup\u003e In line with the multinational PIFotal study, our findings suggest that inhaler errors are ubiquitous across devices, and that their clinical impact is more likely amplified by inconsistent training and limited medication access rather than by device type itself.\u003csup\u003e26\u003c/sup\u003e Other investigations have reported frequent misuse but did not establish robust associations with adherence or outcomes.\u003csup\u003e27,28\u003c/sup\u003e Overall, these findings underscore that inhaler misuse persists across diverse contexts, while our study is one of the few to evaluate inhaler technique and adherence simultaneously and to identify both training-related factors and especially medication access as novel, independent determinants of critical errors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe prevalence of non-adherence in our study (29.9%) was comparable to that reported in major COPD cohorts, such as the TORCH post-hoc analysis (20%) and a German claims study (30%), although higher estimates of 40\u0026ndash;70% have also been described depending on methodology.\u003csup\u003e29,30\u003c/sup\u003e Importantly, TORCH demonstrated that non-adherence was associated with increased exacerbations, hospitalizations, and mortality.\u003csup\u003e29\u003c/sup\u003e In our multivariable analysis, non-adherence was independently associated with device type, inadequate inhaler training, limited medication access, and the presence of critical errors, illustrating the reciprocal nature of these barriers. Although low education and smoking were associated with adherence in univariate analyses, they did not remain independent predictors after adjustment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe observed association with device type should be interpreted cautiously, as certain drug classes are marketed only in specific devices, limiting separation of molecule-related from device-related effects. While current GOLD recommendations emphasize simplifying treatment with a single inhaler whenever possible, the number of inhalers showed no consistent association with adherence in our cohort.\u003csup\u003e2\u003c/sup\u003e Across prior research, low education, smoking, and socioeconomic disadvantage have consistently emerged as risk factors, whereas structured training, patient engagement, and disease awareness appear protective.\u003csup\u003e10,11,31\u003c/sup\u003e Our findings highlight that system-level barriers, particularly structured education and uninterrupted medication access, are equally influential. Emerging tools such as digital monitoring and tailored interventions may further improve adherence, though adoption remains limited, especially in upper-middle-income settings such as Turkey where heterogeneous access may amplify these challenges.\u003csup\u003e32\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this is the first nationwide multicentre study to assess inhaler technique and adherence simultaneously in COPD, integrating sociodemographic, clinical, inhaler-related, and system-level determinants into a single analysis. The inclusion of geographically diverse tertiary centres and face-to-face assessments by trained physicians enhanced representativeness and internal validity. Device-specific checklists based on ERS and TTS guidance ensured methodological consistency.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. The tertiary-care setting may restrict generalisability to community practice; however, the high prevalence of both critical errors and non-adherence even in regularly monitored specialist populations underscores the pervasiveness of these problems. The cross-sectional design limits causal interpretation, and inhaler training procedures were not fully standardised across centres, which may have contributed to variation attributed to trainer type. Although socioeconomic and comorbidity data were collected, their influence could not be examined in sufficient detail. Inhaler technique was assessed at a single time point, preventing evaluation of longitudinal stability or the effect of repeated instruction. Finally, because consecutive sampling was employed and participation rates were extremely high, a complete pre-screening denominator could not be reconstructed, and device\u0026ndash;drug class effects could not be fully disentangled, as certain treatments in Turkey are available only in a single device type.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eInhaler misuse and medication non-adherence remain common and mutually reinforcing barriers to effective COPD management. These outcomes are shaped not only by patient characteristics but also by health system determinants such as training quality and consistent medication access, underscoring the need for a multidimensional approach. Targeted interventions that combine standardised education with policy-level strategies to ensure uninterrupted access to inhaled therapies are both directly actionable and globally relevant. Furthermore, emerging innovations such as digital adherence monitoring and device-based feedback tools warrant integration into future care models, as they may complement traditional interventions and enhance long-term outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC: Area under the curve\u003c/p\u003e\n\u003cp\u003eCAT: COPD Assessment Test\u003c/p\u003e\n\u003cp\u003eCOPD: Chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003eDPI: Dry powder inhaler\u003c/p\u003e\n\u003cp\u003eERS: European Respiratory Society\u003c/p\u003e\n\u003cp\u003eFEV₁: Forced expiratory volume in 1 second\u003c/p\u003e\n\u003cp\u003eFVC: Forced vital capacity\u003c/p\u003e\n\u003cp\u003eGOLD: Global Initiative for Chronic Obstructive Lung Disease\u003c/p\u003e\n\u003cp\u003emMRC: Modified Medical Research Council dyspnea scale\u003c/p\u003e\n\u003cp\u003eMARS-5: Medication Adherence Report Scale–5\u003c/p\u003e\n\u003cp\u003eNIV: Non-invasive ventilation\u003c/p\u003e\n\u003cp\u003epMDI: Pressurised metered-dose inhaler\u003c/p\u003e\n\u003cp\u003eROC: Receiver operating characteristic\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e The study was approved by the Ankara University Faculty of Medicine Ethics Committee (approval number: I5-362-21). All participants provided written informed consent prior to enrolment. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication:\u003c/strong\u003e Not applicable. This manuscript does not contain any individual person’s identifiable data (including images, videos, or personal details).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e De-identified participant data, the analysis code, and the device-specific checklists will be made available from the corresponding author upon reasonable request and subject to institutional approvals and a data-sharing agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Competing interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation: A.M.Ş., E.Ş., A.O.A, N.K.\u003c/p\u003e\n\u003cp\u003eMethodology: A.M.Ş., E.Ş., A.O.A, N.K.\u003c/p\u003e\n\u003cp\u003eInvestigation (site leads and recruitment): E.Ş, A.O.A., E.S, S.N., E.S.Ö., D.P.Y., O.B.T., S.Y., F.E.U., A.G., N.K., A.M., Y.V., A.B., M.P., A.Y., İ.C.,A.K\u003c/p\u003e\n\u003cp\u003eFormal analysis: A.M.Ş, E.Ş, D.G.\u003c/p\u003e\n\u003cp\u003eData curation: A.M.Ş., site investigators.\u003c/p\u003e\n\u003cp\u003eWriting—original draft: A.M.Ş.\u003c/p\u003e\n\u003cp\u003eWriting—review \u0026amp; editing: A.M.Ş, E.Ş, All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eSupervision: E.Ş., A.O.A, N.K.\u003c/p\u003e\n\u003cp\u003eGuarantor: A.M.Ş.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all participating patients and the clinical staff at the ten tertiary outpatient pulmonary clinics for their collaboration.\u0026nbsp;This study was conducted within the framework of the Turkish Thoracic Society COPD Assembly.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChronic obstructive pulmonary disease (COPD). World Health Organization. Accessed 21 August 25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eGlobal Strategy for the Prevention, Diagnosis and Management of Chronic Obstructive Pulmonary Disease. 2025 Report, Global Initiative for Chronic Obstructive Lung Disease\u003c/em\u003e. Accessed August 24, 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://goldcopd.org/2025-gold-report\u003c/span\u003e\u003cspan address=\"https://goldcopd.org/2025-gold-report\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahler DA, Halpin DMG. Personalizing Selection of Inhaled Delivery Systems in Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc Oct. 2023;20(10):1389\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1513/AnnalsATS.202304-384CME\u003c/span\u003e\u003cspan address=\"10.1513/AnnalsATS.202304-384CME\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBao LK, Khoa ND, Chi LTK, Anh NT. Prevalence and Factors Affecting Appropriate Inhaler Use in Elderly Patients with Chronic Obstructive Pulmonary Disease: A Prospective Study. J Clin Med. 2023;12(13):4420. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12134420\u003c/span\u003e\u003cspan address=\"10.3390/jcm12134420\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChrystyn H, Van Der Palen J, Sharma R, et al. Device errors in asthma and COPD: systematic literature review and meta-analysis. npj Prim Care Respiratory Med. 2017;27(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41533-017-0016-z\u003c/span\u003e\u003cspan address=\"10.1038/s41533-017-0016-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindh A, Theander K, Arne M, et al. Errors in inhaler use related to devices and to inhalation technique among patients with chronic obstructive pulmonary disease in primary health care. Nurs Open. 2019;6(4):1519\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/nop2.357\u003c/span\u003e\u003cspan address=\"10.1002/nop2.357\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMolimard M, Raherison C, Lignot S, et al. Chronic obstructive pulmonary disease exacerbation and inhaler device handling: real-life assessment of 2935 patients. Eur Respir J. 2017;49(2):1601794. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1183/13993003.01794-2016\u003c/span\u003e\u003cspan address=\"10.1183/13993003.01794-2016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanchis J, Gich I, Pedersen S. Systematic Review of Errors in Inhaler Use. Chest. 2016;150(2):394\u0026ndash;406. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chest.2016.03.041\u003c/span\u003e\u003cspan address=\"10.1016/j.chest.2016.03.041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSabat\u0026eacute; E. \u003cem\u003eAdherence to long-term therapies: evidence for action. World Health Organization\u003c/em\u003e. 2003. Accessed August 29, 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/handle/10665/42682\u003c/span\u003e\u003cspan address=\"https://iris.who.int/handle/10665/42682\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKardas P, Bennett B, Borah B, et al. Medication non-adherence: reflecting on two decades since WHO adherence report and setting goals for the next twenty years. Front Pharmacol. 2024;15doi. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fphar.2024.1444012\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2024.1444012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTur\u0026eacute;gano-Yedro M, Trillo-Calvo E, Navarro I, Ros F, et al. Inhaler Adherence in COPD: A Crucial Step Towards the Correct Treatment. Int J Chronic Obstr Pulm Dis. 2023;18:2887\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/copd.s431829\u003c/span\u003e\u003cspan address=\"10.2147/copd.s431829\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUsmani OS, Lavorini F, Marshall J, et al. Critical inhaler errors in asthma and COPD: a systematic review of impact on health outcomes. Respir Res. 2018;19(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12931-017-0710-y\u003c/span\u003e\u003cspan address=\"10.1186/s12931-017-0710-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Meng W, Ma Y, et al. Errors and Adherence to Inhaled Medications in Chinese Adults with COPD. J Gen Intern Med. 2024;39(1):69\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11606-023-08378-y\u003c/span\u003e\u003cspan address=\"10.1007/s11606-023-08378-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKokturk N, Polatli M, Oguzulgen IK, et al. Adherence to COPD treatment in Turkey and Saudi Arabia: results of the ADCARE study. Int J Chronic Obstr Pulm Dis. 2018;13:1377\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/copd.s150411\u003c/span\u003e\u003cspan address=\"10.2147/copd.s150411\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;zt\u0026uuml;rk C, Kaya A, Bi̇lgi̇n C, et al. Evaluation of inhaler technique and patient satisfaction with fixed-combination budesonide/formoterol dry-powder inhaler in chronic obstructive pulmonary disease (COPD): data on real-life clinical practice in Turkey. Tuberkuloz ve toraks. 2012;301\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5578/tt.4634\u003c/span\u003e\u003cspan address=\"10.5578/tt.4634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOcakli B, Ozmen I, Acarturk Tuncay E, et al. A comparative analysis of errors in inhaler technique among COPD versus asthma patients. Int J Chronic Obstr Pulm Dis. 2018;13:2941\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/copd.s178951\u003c/span\u003e\u003cspan address=\"10.2147/copd.s178951\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eGlobal Initiative for Chronic Obstructive Lung Disease, Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease 2021 Report\u003c/em\u003e. 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahler DA, Wells CK. Evaluation of clinical methods for rating dyspnea. Chest Mar. 1988;93(3):580\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1378/chest.93.3.580\u003c/span\u003e\u003cspan address=\"10.1378/chest.93.3.580\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones PW, Harding G, Berry P, Wiklund I, Chen WH, Kline Leidy N. Development and first validation of the COPD Assessment Test. Eur Respir J Sep. 2009;34(3):648\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1183/09031936.00102509\u003c/span\u003e\u003cspan address=\"10.1183/09031936.00102509\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J Dec. 2012;40(6):1324\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1183/09031936.00080312\u003c/span\u003e\u003cspan address=\"10.1183/09031936.00080312\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham BL, Steenbruggen I, Miller MR, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med Oct. 2019;15(8):e70\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1164/rccm.201908-1590ST\u003c/span\u003e\u003cspan address=\"10.1164/rccm.201908-1590ST\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorne RW, Hankins J. M. The Medication Adherence Report Scale (MARS): a new measurement tool for eliciting patients\u0026rsquo; reports of non-adherence. University College London; 1999.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSen ET, Berk \u0026Ouml;S, SIndel D. The Validity and Reliability Study of the Turkish Adaptation of Medical Adherence Report Scale. J Istanbul Fac Med. 2019;82(1):52\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.26650/IUITFD.414117\u003c/span\u003e\u003cspan address=\"10.26650/IUITFD.414117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jclinepi.2007.11.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jclinepi.2007.11.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrice DB, Rom\u0026aacute;n-Rodr\u0026iacute;guez M, McQueen RB, et al. Inhaler Errors in the CRITIKAL Study: Type, Frequency, and Association with Asthma Outcomes. J Allergy Clin Immunology: Pract. 2017;5(4):1071\u0026ndash;e10819. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jaip.2017.01.004\u003c/span\u003e\u003cspan address=\"10.1016/j.jaip.2017.01.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKocks J, Bosnic-Anticevich S, Van Cooten J, et al. Identifying critical inhalation technique errors in Dry Powder Inhaler use in patients with COPD based on the association with health status and exacerbations: findings from the multi-country cross-sectional observational PIFotal study. BMC Pulm Med. 2023;23(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12890-023-02566-6\u003c/span\u003e\u003cspan address=\"10.1186/s12890-023-02566-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSriram KB, Percival M. Suboptimal inhaler medication adherence and incorrect technique are common among chronic obstructive pulmonary disease patients. Chronic Resp Dis. 2016;13(1):13\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1479972315606313\u003c/span\u003e\u003cspan address=\"10.1177/1479972315606313\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuarte-De-Ara\u0026uacute;jo A, Teixeira P, Hespanhol V, Correia-De-Sousa J. COPD: misuse of inhaler devices in clinical practice. Int J Chronic Obstr Pulm Dis. 2019;14:1209\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/copd.s178040\u003c/span\u003e\u003cspan address=\"10.2147/copd.s178040\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Boven JF, Chavannes NH, van der Molen T, Rutten-van M\u0026ouml;lken MP, Postma MJ, Vegter S. Clinical and economic impact of non-adherence in COPD: a systematic review. Respir Med Jan. 2014;108(1):103\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.rmed.2013.08.044\u003c/span\u003e\u003cspan address=\"10.1016/j.rmed.2013.08.044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMueller S, Wilke T, Bechtel B, Punekar YS, Mitzner K, Virchow JC. Non-persistence and non-adherence to long-acting COPD medication therapy: A retrospective cohort study based on a large German claims dataset. Respir Med. 2017;2017/01/01:122:1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.rmed.2016.11.008\u003c/span\u003e\u003cspan address=\"10.1016/j.rmed.2016.11.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCase MA, Eakin MN. Up-to-date guidance towards improving medication adherence in patients with chronic obstructive pulmonary disease. \u003cem\u003eExpert Review of Respiratory Medicine\u003c/em\u003e. 2023/07/03 2023;17(7):539\u0026ndash;546. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/17476348.2023.2239708\u003c/span\u003e\u003cspan address=\"10.1080/17476348.2023.2239708\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAung H, Tan R, Flynn C, et al. Digital remote maintenance inhaler adherence interventions in COPD: a systematic review and meta-analysis. Eur Respiratory Rev. 2024;33(174):240136. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1183/16000617.0136-2024\u003c/span\u003e\u003cspan address=\"10.1183/16000617.0136-2024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COPD, Administration, Inhalation, Medication Errors, Medication Adherence, Dry Powder Inhalers, Pressurised Metered-Dose Inhalers","lastPublishedDoi":"10.21203/rs.3.rs-8302012/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8302012/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncorrect inhaler technique and poor adherence undermine COPD care, yet their joint determinants are incompletely defined. This study aimed to investigate the prevalence and determinants of critical inhaler errors and non-adherence, and their reciprocal association in COPD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a nationwide multicentre cross-sectional study (July 2021–February 2022) in 10 tertiary outpatient pulmonary clinics across Turkey. Consecutive COPD patients aged ≥ 40 years using at least one inhaler for ≥ 3 months were included. Inhaler technique was assessed with device-specific checklists, and adherence with the Medication Adherence Report Scale–5 (MARS-5). Logistic regression was applied to identify independent predictors of critical errors and non-adherence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 358 patients (mean age, 66 years; 81% male), 39.7% had at least one critical error and 29.9% were non-adherent. Critical errors were associated with older age (adjusted OR [aOR], 1.04 per year; 95% CI, 1.01–1.08) and non-adherence (3.36; 1.83–6.18), and were less likely with prior inhaler training (0.23; 0.07–0.74) and uninterrupted medication access (0.32; 0.11–0.97). Non-adherence was less likely with dry-powder inhalers versus pressurised metered-dose inhalers (0.48; 0.28–0.82), prior training (0.38; 0.15–0.96), and uninterrupted access (0.35; 0.16–0.78), and more likely with any critical error (2.69; 1.62–4.46). Discrimination was acceptable (AUC, 0.75 for critical errors; 0.71 for non-adherence).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInhaler misuse and medication non-adherence were common and bidirectionally associated. Standardised training and uninterrupted medication access independently lowered risk and represent high-leverage, implementable targets. Integration of digital adherence tools with routine education should be tested in pragmatic trials.\u003c/p\u003e","manuscriptTitle":"Inhaler Technique and Medication Adherence in COPD: Insights from a Nationwide Multicentre Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-30 00:48:08","doi":"10.21203/rs.3.rs-8302012/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-01-12T18:53:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T05:21:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326741181691069963236542097752053691459","date":"2026-01-04T04:35:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256125080368392890565426449900876872359","date":"2025-12-30T15:42:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-19T17:07:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-11T18:53:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-10T20:39:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2025-12-10T20:33:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"99c7d9c3-93bd-4c30-8b5b-fe28ae9d4c1a","owner":[],"postedDate":"December 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-30T00:48:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-30 00:48:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8302012","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8302012","identity":"rs-8302012","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}