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. 2026 Aug 28;26:1324. doi: 10.1186/s12877-026-08130-1

Motivational orientation and influencing factors of older adults with chronic obstructive pulmonary disease in community dwellings: a latent profile analysis

Luxin Wang 1, Yanfei Liu 2,✉, Xiaoyue Song 2,3, Han Su 2, Xiao Ruan 2, Xincan Zhou 2, Zhiyue Li 2, Weihong Zhang 1,✉
PMCID: PMC13685133  PMID: 42907974

Abstract

Background

Chronic obstructive pulmonary disease (COPD) poses a serious threat to older adults’ health. Promoting the adoption of health behaviors among community-dwelling patients is essential for improving prognosis, with motivational orientation serving as a key determinant of health behaviors. Therefore, this study aims to identify latent categories of motivational orientation and its influencing factors among community-based older adults with COPD.

Methods

This study was conducted between November 2024 and March 2025, with 246 patients from the communities at two community health centers in China. Data were collected using the general information questionnaire, the Behavioral Inhibition/ Activation System Scale, the Generalized Anxiety Disorder 7-item Scale and the Center for Epidemiological Studies Depression Scale. A latent profile analysis was performed to analyze latent categories of motivational orientation. Multiple logistic regression was used to analyze the influencing factors of their latent profiles.

Results

Three latent categories of motivational orientation among COPD patients were identified: ‘avoidance motivation dominated group’(10.2%), ‘conflict motivation group’ (29.7%) and ‘approach motivation dominated group’ (60.1%). The best-fitting model demonstrated robust fit indices: AIC = 4484.372, BIC = 4547.468, aBIC = 4490.409, Entropy = 0.983. Patients with higher depression scores were more likely to be in the ‘avoidance motivation dominated group’ than those in the ‘conflict motivation group’ (OR = 1.506, 95% CI: 1.230–1.842). Patients with younger age (OR = 0.480, 95% CI: 0.288–0.802), higher income (OR = 3.257, 95% CI: 1.486–7.140), and shorter duration of illness (OR = 0.608, 95% CI: 0.377–0.982) were more likely to be in the ‘approach motivation dominated group’.

Conclusion

In clinical practice, older COPD patients present significant variations in motivational orientation, these differences are influenced by individual characteristics such as age, long disease duration, and psychological factors. Healthcare professionals should provide individualized psychological support and health education programs to promote the development of proactive health behaviors.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12877-026-08130-1.

Keywords: Chronic obstructive pulmonary disease, Motivational orientation, Community dwellings, Older adults, Latent profile analysis

Introduction

As an important global health issue, chronic obstructive pulmonary disease (COPD) is characterized by high morbidity, high mortality and high disease burden, which affects up to 392 million people worldwide and causes 3.23 million deaths [1]. As the body ages, older adults have a higher risk of developing COPD due to the aging of the respiratory system and reduced physiological functions [2]. Owing to chronic dyspnea, lung compression and increasing age, older COPD patients always are at risk of a range of complications, such as lung cancer, cognitive impairment, frailty, and so on [3]. Recurrent and acute exacerbations of the disease raise readmission and disability rates, with substantial economic burden and a negative impact on patient quality of life [1, 4].

Promoting the adoption of health behaviors among patients in the community is a cost-effective non-pharmacological intervention that is effective in improving dyspnea, physical functioning and quality of life [5]. Health behaviors are influenced by various factors such as cognition, psychological status and illness experience, and outcome efficacy is one of the most important predictors of behavior. Individuals will accept behaviors when they believe that the recommended behavior will achieve the desired outcome [6]. Motivational orientation influences patients’ behavior in response to different external stimuli, playing an important role in promoting health behaviors in patients [7]. Jiang et al. [8] demonstrated that individuals with high avoidance motivation can be more effectively promoted for health behaviors in a loss information framework, and individuals with high approach motivation can be more effectively promoted for health behaviors in a gain information framework. Furthermore, motivational orientation can mediate the effects of health information on individual behaviors. Therefore, clarifying the status of motivational orientation in community-dwelling older adults with COPD is important for promoting health behaviors.

Motivational orientation refers to the intrinsic motivational tendency of an individual in the face of a goal, task, or situation, which can be divided into two aspects: approach motivation and avoidance motivation [9]. Approach motivation is the motivational state that occurs when a positive outcome goal is pursued, also known as the behavioral activation system (BAS); while avoidance motivation is the motivational state that occurs when a negative outcome goal is avoided, which is also known as the behavioral inhibition system (BIS) [10]. Individuals with high approach motivation are more sensitive to rewarding or incentive cues, and individuals with high avoidance motivation are more sensitive to punishing or threatening cues [11]. The distinction between motivational orientation is an important development of classical motivation theory and provides a new perspective for an in-depth exploration of the complex human motivational system.

Previous research on motivational orientation has focused on patients suffering from chronic pain, fibromyalgia and emotional disorders [12–14]. It has been shown that anxiety and depression can have an impact on approach and avoidance motivation through core dysfunction in brain circuits [15]. Due to the potential role of biological factors such as inflammation, hypoxia, and corticosteroid use, COPD patients have a high prevalence of depression and anxiety [16], which affects individuals’ motivational orientation. However, few studies have explored the categories of motivational orientation and the influencing factors among community-dwelling older COPD patients.

Determining the potential characteristics of the motivational orientation of older COPD patients and their proportions in the population through latent profile analysis (LPA) can investigate the characteristics of different latent categories in depth [17]. Therefore, grounded in Gray’s Reinforcement Sensitivity Theory (RST) [18, 19] and the heterogeneity of older adults with chronic conditions, this study explores the potential categories of motivational orientation and the influencing factors in community-dwelling older adults with COPD, aiming to inform the development of targeted educational programs for community healthcare workers, and testing the following explicit hypotheses: (1) Community-dwelling older adults with COPD will be classified into 3 to 4 distinct latent profiles based on varying combinations of motivational orientation. (2) Negative psychological states, specifically elevated anxiety and depression, will positively predict membership in avoidance-dominant profiles, whereas higher levels of physical functionality and perceived health resources will positively predict membership in approach-dominant profiles.

Method

Study design

This study is a cross-sectional study, following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement reporting guidelines [20].

Setting and participants

Between November 2024 and March 2025, older adults with COPD were recruited using convenience sampling from the communities at two community health centers in Zhengzhou, Henan Province, China. Inclusion criteria: (1) age ≥ 60 years old, resident in the community (had established health records and had lived for more than 6 months); (2) diagnosed with COPD by the attending physician; (3) could communicate rationally with researchers; (4) informed consent and voluntary participation in this study. Exclusion criteria: (1) suffering from serious physical diseases, acute exacerbation or terminal stage of chronic diseases or combined with serious diseases; (2) currently participating in other intervention research.

Sample size

The G-power 3.1.9.7 version was used to calculate a sufficient sample size. Under a significance level of 0.05, a power value of 0.95, an effect size of 0.15, and 14 predictors, a minimum sample of 194 participants was needed to run a multiple regression analysis [21]. In consideration of the invalid questionnaires, the sample size was increased by an additional 15%. Therefore, the recommended sample size should be a minimum of 221.

Measurement

General information questionnaire

A general information questionnaire was used based on the literature review that includes gender, age, body mass index (BMI), occupation, education level, marital status, income, disease duration, residential situation, complications, comorbidities, and modified Medical Research Council (mMRC). The English version of the questionnaire is provided in the Supplementary File (Part Ⅰ).

Behavioral Inhibition/Activation System Scale (BIS/BAS scale)

The BIS/BAS scale, originally developed by Carver and White [22], was adapted into Chinese and revised to 18 items by Li et al. [23] to measure approach and avoidance motivation. It contains one subscale for measuring the BIS (5 items) and three subscales for evaluating the BAS (13 items in total): BAS-reward responsiveness (4 items), BAS-drive (4 items), and BAS-fun seeking (5 items). A four-point Likert scale was used for each item, with scores ranging from 1 to 4 for the levels ‘strongly disagree’ to ‘strongly disagree’. The scale demonstrates good reliability and validity, with a Cronbach’s α coefficient of 0.83 and a test-retest reliability of 0.69 [24]. In this study, the Cronbach’s α was 0.80, indicating good reliability.

Generalized Anxiety Disorder 7-item Scale (GAD-7)

GAD-7 was developed by Spitzer et al. [25] and was translated by He et al. [26] to assess anxiety symptoms. Previous research [27] has reported that Cronbach’s α coefficient was 0.90 and the test-retest reliability was 0.76, indicating high consistency and reliability of the scale. The 7-item scale is scored on a 4-point Likert scale, and the total score ranges from 0 to 21. A score of 4 or less indicates no anxiety, a score between 5 and 9 suggests mild anxiety, a score between 10 and 14 reflects moderate anxiety, and a score of 15 or more signifies severe anxiety. In this study, the Cronbach’s α coefficient of the questionnaire was 0.93.

Center for Epidemiological Studies Depression Scale (CES-D)

Depression was measured by the Chinese version of CES-D, originally developed by Radloff [28] and revised by Santor and Coyne [29]. The Cronbach’s α coefficient of the scale was 0.81 and the test-retest reliability was 0.81, demonstrating high internal consistency among older adults [30]. Responses range from 0 (below 1 day) to 3 (above 5 days). Total scores could range from 0 to 30, with a higher value indicating a greater level of depression. The Cronbach’s α coefficient was 0.93 in the present sample.

Data collection

Community healthcare workers, acting as research assistants, screened older adults diagnosed with COPD from residents’ health records and then referred them to the research team. Researchers explained the background, objectives, and significance of the study to potential participants who met the inclusion criteria. If patients agreed to participate in the study, the investigator distributed an informed consent form and a structured questionnaire with uniform instructions and explanations to the participants. For those who were unable to write, the researcher asked the questionnaire items and filled in the questionnaire based on their responses. All questionnaires were retrieved on the spot and checked for incomplete and incorrect responses to promptly ask the study participants to supplement. During the data entry stage, the researcher carefully checked the questionnaires to ensure that the data were entered accurately. In case of inconsistency or unusual data, it was verified retrospectively and corrected.

Data analysis

Data analysis was conducted using IBM SPSS Statistics 25.0 and Mplus 7.4. Qualitative information was summarized as frequency and percentage. Quantitative data with normal distribution were presented as mean and standard deviation (SD), while non-normally distributed data were described as median and interquartile range (IQR).

The average scores of items from the four dimensions of the BIS/BAS scale were treated as explicit variables for latent profile analysis. Models ranging from one to seven profiles underwent evaluation based on the fit indices, and the optimal model was selected based on statistical and practical considerations [31]. The Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and adjusted Bayesian Information Criterion (aBIC) were used to evaluate the classification accuracy. Lower values indicated a better model fit. Moreover, the entropy value ranges from 0 to 1, and higher entropy values (> 0.8) were indicative of improved model fit. The Lo–Mendell–Rubin (LMR) test and bootstrap likelihood ratio test (BLRT) were utilized to compare the fit of the model with k categories and k-1 categories. Statistically significant p-values suggested that the current model outperforms the previous model. Differences in demographic characteristics between different latent categories were tested by the chi-square test. Given the non-normally distributed data, the Kruskal–Wallis H test was conducted to examine the discrepancy in emotional variations across potential categories. Statistically significant variables from the univariate analyses were included in the multivariate logistic regression analysis to explore influencing factors of motivational orientation categories of community-dwelling older adults with COPD. The statistical test significance level was P < 0.05.

Common method deviation test

Reverse-coded items and varied response formats were adopted to mitigate common method bias originating from self-reported measurements [32]. The unmeasured latent method construct (ULMC) technique was applied to examine common method bias for the BIS/BAS scale, GAD-7, and CES-D [33]. A baseline confirmatory factor analysis model was compared with an extended bifactor model containing a global latent method factor. The variations in model fit indices were negligible: Δ Root Mean Square Error of Approximation (RMSEA)=-0.015, Δ Standardized Root Mean‑square Residual (SRMR)=-0.034, Δ Comparative Fit Index (CFI) = 0.044, Δ Tucker‑Lewis Index (TLI) = 0.036. The addition of the method factor did not significantly boost model fit, which demonstrated that the measurement model built on parceled indicators had no obvious common method bias.

Ethical approval

This study was approved by the Ethics Committee of Zhengzhou University for Life Sciences (approval number: ZZUIRB202510). Data collection surveys were conducted by researchers only after consent was obtained from the participants.

Results

Participant characteristics

A total of 260 participants participated in our study, 246 valid questionnaires were obtained, and 14 questionnaires were excluded due to incomplete or non-compliant submission, with an effective response rate of 94.62%. The primary demographic characteristics with statistically significant differences are presented in Table 1, while the complete characteristics involving all variables are detailed in the Supplementary File (Supplementary Table 1). The average age of patients was 72.91 (SD = 9.18, range 60–93) years. Among these patients with COPD, 144 (58.54%) were males, 204 (82.9%) were married, 8 (3.25%) had mild anxiety, 12 (4.88%) had moderate anxiety, 9 (3.66%) had severe anxiety, and 50 (20.33%) had depression. The Kolmogorov-Smirnov test revealed that anxiety and depression scores were non-normally distributed (P < 0.05). The characteristics are presented in Table 2.

Table 1.

Univariate analysis of demographic and clinical variables by latent profiles

Variable All participants (N = 246, %) Class 1
(n = 25, %)		 Class 2
(n = 73, %)		 Class 3
(n = 148, %)		 X2 P
Age
 60–69 years 99 (40.2) 4 (16.0) 21 (28.8) 74 (50.0) 23.828 < 0.001**
 70–79 years 81 (32.9) 10 (40.0) 22 (30.1) 49 (33.1)
 ≥ 80 years 66 (26.8) 11 (44.0) 30 (41.1) 25 (16.9)
Marital status
 Married 204 (82.9) 15 (60.0) 60 (82.2) 129 (87.2) 11.184 0.004*
 Other (Divorced/Widowed) 42 (17.1) 10 (40.0) 13 (17.8) 19 (12.8)
Household monthly income per capita (RMB)
 < 4000 63 (25.6) 8 (32.0) 28 (38.4) 27 (18.2) 10.977 0.004*
 ≥ 4000 183 (74.4) 17 (68.0) 45 (61.6) 121 (81.8)
Disease duration (years)
 0–5 149 (60.6) 9 (36.0) 39 (53.7) 101 (68.2) 20.409 < 0.001**
 6–10 58 (23.6) 7 (28.0) 16 (21.9) 35 (23.6)
 ≥ 11 39 (15.9) 9 (36.0) 18 (24.7) 12 (8.1)
Had complications
 Yes 49 (19.9) 8 (32.0) 22 (30.1) 19 (12.8) 11.718 0.003*
 No 197 (80.1) 17 (68.0) 51 (69.9) 129 (87.2)
mMRC score
 0 115 (46.7) 8 (32.0) 23 (31.5) 84 (56.8) 30.000 < 0.001**
 1 96 (39.0) 7 (28.0) 35 (47.9) 54 (36.5)
 2 35 (14.2) 10 (40.0) 15 (20.5) 10 (6.8)
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mMRC modified Medical Research Council

*P < 0.05, **P < 0.001

Table 2.

Univariate analysis of emotional variables by latent profiles

Variable All participants
M (P25, P75)		 Class 1
M (P25, P75)		 Class 2
M (P25, P75)		 Class 3
M (P25, P75)		 H P
Anxiety 1.0 (0.0, 3.0) 4.0 (3.0, 8.5) 2.0 (1.0, 4.0) 1.0 (0.0, 1.0) 81.613 < 0.001**
Depression 4.0 (2.0, 8.0) 12.0 (10.0, 15.0) 5.0 (2.0, 14.0) 2.0 (0.0, 4.0) 76.883 < 0.001**
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*P < 0.05, **P < 0.001

Approach and avoidance motivation scores among older adults with COPD

Approach and avoidance motivation scores are shown in Table 3, which were confirmed to be normally distributed by the Kolmogorov-Smirnov test (P > 0.05). The total BIS score of COPD patients was 10.98 ± 5.37 and the total BAS score was 40.71 ± 10.91.

Table 3.

Mean scores for three motivational orientation categories (N = 246)

Dimensions All participant (x ± s) Class 1 (x ± s) Class 2 (x ± s) Class 3 (x ± s) F P
Behavioral Inhibition System 10.98 ± 5.37 18.32 ± 1.73 12.78 ± 4.04 8.86 ± 4.93 56.788 < 0.001**
Behavioral Activation System-Reward Responsiveness 12.98 ± 3.36 5.04 ± 1.37 11.26 ± 1.60 14.94 ± 1.10 702.326 < 0.001**
Behavioral Activation System-Drive 12.61 ± 3.46 4.96 ± 1.27 10.53 ± 1.45 14.93 ± 1.08 864.651 < 0.001**
Behavioral Activation System-Fun Seeking 15.26 ± 4.47 5.68 ± 1.15 12.48 ± 2.04 18.24 ± 1.64 699.928 < 0.001**
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*P < 0.05, **P < 0.001

Latent profile analysis for motivational orientation categories in older adults with COPD

Results of latent profile analysis

The study utilized the four dimensions of the BIS/BAS scale as indicators, examining 1 to 7 different latent profile models. The model fit indices are presented in Table 4. As the number of latent categories increased, the values of AIC, BIC and aBIC gradually decreased, while the entropy value stayed above 0.8, indicating a high classification accuracy. The p-values of LMRT and BLRT for the 4-profile were more than 0.05 and for the 3-profile were less than 0.05, indicating that 3-profile was significantly better than the other models. Therefore, the 3-profile model emerged as the best-fit model for our study.

Table 4.

Comparison of fit indices between models

Number of classes AIC BIC aBIC Entropy LMRT (p-value) BLRT (p-value) Probability of category
1 5575.043 5603.086 5577.726 - - - 1
2 4989.584 5035.153 4993.944 0.932 0.0022 0.0000 0.313/0.687
3 4484.372 4547.468 4490.409 0.983 0.0000 0.0000 0.102/0.297/0.601
4 4378.196 4458.818 4385.909 0.958 0.1059 0.0000 0.102/0.134/0.297/0.467
5 4278.333 4376.482 4287.724 0.968 0.0155 0.0000 0.081/0.455/0.102/0.216/0.146
6 4239.473 4355.149 4250.541 0.969 0.2431 0.0000 0.041/0.081/0.199/0.451/0.085/0.142
7 4178.309 4311.511 4191.053 0.969 0.0969 0.0000 0.069/0.081/0.415/0.114/0.146/0.069/0.106
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AIC Akaike information criterion, BIC Bayesian information criterion, aBIC adjusted Bayesian information criterion, LMRT Lo-Mendell-Rubin test, BLRT Bootstrap likelihood ratio test

Naming of three potential motivational orientation categories

The differentiation between the identified motivational orientation subgroups across the four measured dimensions is shown in Fig. 1. Profile 1, comprising 25 individuals (10.2%), with BIS scores higher than the other two categories and BAS scores for each dimension lower than the other two categories, was named the ‘avoidance motivation dominated group’. Profile 2, composed of 73 individuals (29.7%), with BIS and BAS scores in the middle of the other two categories, was labeled as the ‘conflict motivation group’. Profile 3 has a higher BAS score for each dimension than the other two categories and a lower BIS score than the other two categories, designated as the ‘approach motivation dominated group’ with 148 people (60.1%).

Fig. 1.

Fig. 1

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Scores of three different latent classes of motivational orientation. Note: Three distinct profiles were identified: the avoidance motivation dominated group (10.2%, high BIS, low BAS), conflict motivation group (29.7%, moderate BIS and BAS), and approach motivation dominated group (60.1%, low BIS, high BAS across all sub‑facets)

Univariate analysis of latent motivational orientation categories

Indicators with statistically significant differences in univariate analyses across the three latent profiles of motivational orientation were age (X2 = 23.828, P < 0.001), marriage (X2 = 11.184, P = 0.004), income (X2 = 10.977, P = 0.004), disease duration (X2 = 20.109, P < 0.001), complications (X2 = 11.718, P = 0.003), mMRC score (X2 = 30.000, P < 0.001), anxiety (H = 81.613, P < 0.001), and depression (H = 76.883, P < 0.001). See Tables 1 and 2 for details.

Multiple logistic regression analysis of latent motivational orientation categories

Multiple logistic regression analyses were conducted to investigate the predictive effects of the statistically significant variables in the univariate analysis of variance on each of the three potential categories of motivational orientation as dependent variables. The ‘conflict motivation group’ was used as the reference group for comparison among the groups. Multiple logistic regression analyses revealed that anxiety showed significant differences (P < 0.05) among the three motivational potential categories. Patients with higher depression scores were more likely to ‘avoidance motivation dominated group’ than those in the ‘conflict motivation group’ (OR = 1.506, 95% CI: 1.230–1.842). Patients with younger age (OR = 0.480, 95% CI: 0.288–0.802), higher income (OR = 3.257, 95% CI: 1.486–7.140), and shorter duration of illness (OR = 0.608, 95% CI: 0.377–0.982) were more likely to be in the ‘approach motivation dominated group’ (Table 5).

Table 5.

Multiple logistic regression analysis of three categories of motivational orientation

Variables β P OR 95% CI
Class 1 (ref. class 2)
 Anxiety 0.381 0.001* 1.463 1.160–2.862
 Depression 0.409 < 0.001** 1.506 1.230–1.842
Class 3 (ref. class 2)
 Age -0.733 0.005* 0.480 0.288–0.802
 Household monthly income per capita 1.181 0.003* 3.257 1.486–7.140
 Disease duration -0.497 0.042* 0.608 0.377–0.982
 Anxiety -0.607 0.014* 0.545 0.336–0.884
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*P < 0.05, **P < 0.001

Discussion

Motivational orientation and latent profiles in older adults with COPD

Our study findings showed three motivational orientation categories in older adults with COPD: the ‘avoidance motivation dominated group’ (10.2%), the ‘conflict motivation group’ (29.7%), and the ‘approach motivation dominated group’ (60.1%). The mean score of items in the BIS scale for community-aged COPD was 2.20 ± 1.07, the BAS score was 3.13 ± 0.84, and the approach motivation score was higher than the avoidance motivation score. It suggests that community-dwelling older adults with COPD are more sensitive to the BAS than the BIS, which may be related to disease characteristics and psychological state, consistent with the findings of Sun et al. [34]. The majority of the patient group recruited for this study were married, had a shorter disease duration, had lower levels of dyspnea, and generally had a better emotional state, with 79.67% of them showing no anxiety or depression. These characteristics suggested that the majority of patients were psychologically healthier, possessed greater psychological resilience, were able to cope more effectively with the stresses and challenges of the disease, and were more sensitive to rewarding information.

Impact of emotional factors on motivational orientation

Patients with high anxiety scores were likely to belong to the ‘avoidance motivation dominated group’, and patients with low scores were likely to belong to the ‘approach motivation dominated group’. Approach motivation is triggered by positive stimuli, causing individuals to tend to retain actions that are beneficial and desirable; avoidance motivation is triggered by negative stimuli, causing individuals to tend to avoid actions that are undesirable and harmful [35]. Higher levels of anxiety were associated with stronger avoidance motivation and weaker approach motivation. Compared to the ‘conflict motivation group’, patients with high depression scores are more likely to belong to the ‘avoidance motivation dominated group’.

This differentiated motivational distribution pattern can be jointly interpreted from three levels of mechanisms. First, the shared neuropsychological basis of people with anxiety and depression — amygdala overactivation [36], prefrontal cortex regulatory dysfunction [37], and hippocampal structural and functional damage [38]. The three factors collectively alter the activation intensity of the BIS and BAS, leading individuals to continuously overattend to threat cues and form a biased underestimation of reward information. Second, long-term chronic intermittent hypoxia and persistent low-grade systemic inflammation will further amplify the hyperexcitability of the amygdala [39], down-regulate dopamine receptor expression in the mesolimbic reward pathway, and eventually induce the core pathological feature of ‌reward desensitization‌. Third, the above pathways fully conform to the core assumptions of RST and reinforcement learning theory [19, 40].COPD patients under anxiety and depression will simultaneously show significantly increased threat sensitivity and markedly decreased reward sensitivity [41, 42], which ultimately leads to persistent BIS hyperactivation and insufficient BAS activation, forming the three-category motivational orientation distribution pattern observed in this study.

Sociodemographic factors associated with motivational orientation

Younger patients were more likely to be assigned to the ‘approach motivation dominated group’. The reason might be that older adults were more prone to somatic depressive symptoms resulting in high avoidance motivation [43], and it has been demonstrated [44] that increasing age was associated with a higher risk of avoidance behavior. Consistent with previous research [45], patients with lower socioeconomic levels and lower overall incomes were more motivated towards avoidance than patients with higher socioeconomic levels and higher independence. On the one hand, the lower the socioeconomic status and the lower the income, the higher the prevalence of depression and anxiety [46], leading to a strong avoidance motivation in patients. On the other hand, patients with low socioeconomic status lack motivation to try to succeed, have difficulty putting in sustained effort, are often targets of stereotyping and discrimination, have difficulty being motivated by positive messages, and have low approach motivation [47].

Patients with shorter disease duration were more likely to be assigned to the ‘approach motivation dominated group’. The longer the disease duration, the more the patient’s symptoms of depression and anxiety increase [48], the more the patient’s knowledge about the disease increases, and the more the patient’s sensitivity to information about potential threats increases. Additionally, a decrease in grey matter volume in the anterior cingulate cortex was negatively correlated with prolonged disease duration [49], which is not only involved in the neural processing of dyspnea, but also closely associated with the processing of avoidance behaviors [50].

Comparison with previous studies

Most previous studies [12–14] based on RST have adopted an analytical approach that independently interprets BIS and BAS scores, while neglecting the scenario where BAS and BIS coexist simultaneously. This limitation makes it difficult to fully reveal the inherent motivational heterogeneity among older adults with chronic diseases. Using LPA, the present study categorized community-dwelling older adults with stable COPD into three motivational orientation profiles. The “approach motivation group” accounts for the highest proportion in this population, which is highly consistent with the preliminary findings of Sun et al. [34]. A plausible explanation is that all participants recruited in this study are community-dwelling home-based patients with stable disease conditions and mild dyspnea. The steady disease trajectory and continuous family care support can effectively buffer the negative stimuli induced by the disease, enabling individuals to more easily establish a stable positive health coping pattern [48].

In terms of the predictive effect of negative emotions on motivational orientation, the present study confirms that elevated levels of both anxiety and depression can significantly and positively predict avoidance motivation, which is consistent with the previous findings [15]. However, existing relevant studies can only verify the overall association between negative emotions and BIS scores, and fail to distinguish the differential effects of two core negative emotions, anxiety and depression, on distinct latent profiles of motivational orientation. The study reveals that anxiety can simultaneously affect both the ‘avoidance motivation dominated group’ and ‘conflict motivation group’, while depression acts as a specific emotional factor that drives individuals to develop a single pure avoidance tendency. This critical difference can be jointly explained from two dimensions: the neuropsychological mechanisms corresponding to RST and the long-term mind-body interaction characteristics in chronic diseases. Essentially, anxiety is a generalized state of risk concern, where individuals maintain sustained high vigilance towards various potential negative events. People with moderate anxiety can simultaneously perceive the dual possibilities of potential losses and positive development, which leads to the co-activation of the BIS and BAS systems, and ultimately forms a balanced motivation characterized by approach-avoidance conflict. When anxiety progresses to a severe level, the perception of danger completely overwhelms positive expectations, the BIS system remains persistently hyperactivated, and individuals eventually exhibit a single avoidance tendency [19]. In contrast, the core pathological alteration of depression is the blunting of the brain’s reward circuit and the reduced activity of the dopaminergic reward pathway. Individuals completely lose their perception of various positive gains and positive feedback, show no contradictory psychology of approach-avoidance trade-off, and only present the characteristic of unidirectional behavioral inhibition. Therefore, depression can only specifically predict avoidance motivation [51].

Strengths and limitations

This study describes and explains the current status of the motivational orientation of older adults with COPD in the community and uses LPA to identify the three motivational orientation categories of the patients as well as the influence of socio-demographic and emotional factors on them, which provides valuable evidence for caregivers to develop individualized intervention strategies based on the different characteristics of the patients. However, some limitations should also be acknowledged in this study. Firstly, this study used a self-reported questionnaire, which may be susceptible to social desirability bias and recall bias. This concern was effectively controlled by procedural controls during data collection, and subsequent ULMC analysis confirmed no severe common method bias. Secondly, this study was conducted exclusively in one region in Henan Province, China, limiting the representativeness and generalizability of the samples. Finally, it was a cross-sectional study, which may not make it possible to determine the causal relationship between variables. Therefore, a multicenter longitudinal study with a large sample is recommended to track the trajectory of patients’ motivational orientation as the disease course progresses.

Recommendations for further research and practice

The results of this study extended the existing literature on potential categories of motivational orientation and the influencing factors on them in community-aged COPD patients. Future research should incorporate more indicators for a multicenter longitudinal study with a large sample size to further explore the positive and negative consequences of different motivational categories for community-dwelling older COPD patients as well as other influencing indicators of approach and avoidance motivation. Additionally, some emotional regulation strategies and psychological therapies are considered effective interventions for regulating patients’ emotions and avoiding avoidance motivation. Future research can explore the relationship between emotional regulation skills, motivational orientation, and emotions, developing interventions to enhance emotional regulation ability in order to improve patients’ positive emotions and reduce high avoidance motivation.

Additionally, this study implicated that community caregivers can reduce patients’ high avoidance motivation through emotion regulation, behavioral activation and other methods of enhancing patients’ mood. Secondly, it is crucial to develop targeted intervention strategies for patients with different motivational orientation profiles. Psychological support and emotional regulation should be strengthened for patients with high avoidance motivation. Meanwhile, patients in the approach motivation-dominated group are sensitive to positive benefit information with stable intrinsic exercise motivation. The core challenge is to prevent late-stage motivation decay. Gain-framed health education and phased long-term exercise goals are recommended. Mobile health check-ins guide patients to self-record exercise benefits, and regular peer sharing sessions enhance self-efficacy, helping them build a long-term independent exercise self-management mode without strong external supervision. Patients in the avoidance motivation-dominated group are highly alert to disease risks with widespread exercise fear. Conventional education easily triggers BIS hypervigilance and reinforces avoidance behaviors. Prioritize eliminating exercise avoidance: apply loss-framed warnings focusing on sedentary hazards, start with ultra-light breathing and stretching training, and combine family accompaniment, home follow-ups, and low-threshold illustrated materials to gradually lower the exercise fear threshold and establish basic daily activity self-management habits. Patients in the conflict motivation group show simultaneous bidirectional activation of approach and avoidance motivations, with fluctuating compliance and high dropout risk. Single-mode education cannot meet their needs. A flexible self-management system is required: use mixed-frame information covering both exercise benefits and sedentary risks, split long-term goals into weekly small tasks, and combine group education with one-on-one communication to reduce decision-making friction, turning vague exercise intentions into stable autonomous self-management behaviors [52].

Conclusions

Our study identified three potential categories of motivational orientation in community-dwelling older COPD patients: avoidance motivation dominated group, conflict motivation group, and approach motivation dominated group. Additionally, these patterns showed significant associations with age, income, disease duration, anxiety, and depression. Community caregivers should provide psychological support and emotional regulation for patients belonging to the ‘avoidance motivation dominated group’ according to the characteristics of different motivation categories.

Supplementary Information

Supplementary Material 1. (37.3KB, docx)
Supplementary Material 2. (42.4KB, docx)

Acknowledgements

The authors express gratitude to all the patients who participated in this cross-sectional study.

Abbreviations

aBIC

Adjusted bayesian information criterion

AIC

Akaike information criterion

BAS

Behavioral activation system

BIC

Bayesian information criterion

BIS

Behavioral inhibition system

BLRT

Bootstrap likelihood ratio test

BMI

Body mass index

CES-D

Center for epidemiological studies depression

CFI

Comparative fit index

COPD

Chronic obstructive pulmonary disease

GAD-7

Generalized anxiety disorder 7-item

IQR

Interquartile range

LMR

Lo–Mendell–Rubin test

LPA

Latent profile analysis

mMRC

Modified medical research council

RMSEA

Root mean square error of approximation

RST

Reinforcement sensitivity theory

SD

Standard deviation

SRMR

Standardized root mean‑square residual

STROBE

Strengthening the reporting of observational studies in epidemiology

TLI

Tucker‑Lewis index

ULMC

Unmeasured latent method construct

Authors’ contributions

Luxin Wang, Yanfei Liu and Weihong Zhang contributed to conceptualization. Luxin Wang and Weihong Zhang designed the methodology. Luxin Wang, Han Su and Ruan Xiao participated in investigation. Luxin Wang and Weihong Zhang wrote the original draft. Yanfei Liu, Xiaoyue Song, Han Su, Ruan Xiao, Xincan Zhou and Zhiyue Li contributed to writing—review and editing. Luxin Wang and Han Su performed data curation. Yanfei Liu, Xiaoyue Song and Weihong Zhang supervised the study. All authors reviewed and approved the final manuscript.

Funding

This work was supported by National Natural Science Foundation of China (approval number: 72574200), Henan Province Science and Technology Research and Development Project (approval number: 262102210074) and Henan University Science and Technology innovation team support plan (project approval number: 22IRTSTHNO27).

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Zhengzhou University Ethics Committee for Life Sciences (approval number: ZZUIRB202510) and conducted in accordance with the Helsinki Declaration. All patients participating in the study signed the informed consent form.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Yanfei Liu, Email: yanfeifei2018@163.com.

Weihong Zhang, Email: zwhong306@zzu.edu.cn.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (37.3KB, docx)
Supplementary Material 2. (42.4KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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