Kinesiophobia and its associated factors among patients after transcatheter aortic valve replacement: a cross-sectional study based on latent profile analysis

Abstract

Background

Kinesiophobia, a significant barrier to daily activities, may contribute to adverse outcomes in patients following transcatheter aortic valve replacement (TAVR). This study aimed to assess the prevalence and identify factors associated with kinesiophobia in post-TAVR patients.

Methods

From January to December 2023, a cross-sectional survey was conducted using a convenience sampling method, involving patients from the cardiology department of a hospital in China. The study utilized several instruments: a general information questionnaire, the Tampa Scale for Kinesiophobia Heart (TSK-SV Heart), the Lubben Social Network Scale-6 (LSNS-6), the Exercise Social Support Scale (ESSS), the Physical Activity Rank Scale (PARS-3) and the Self-Efficacy for Exercise Scale (SEE). Latent profile analysis (LPA) was performed to classify patients into latent subgroups based on their levels of kinesiophobia. Additionally, multivariate logistic regression analysis was employed to identify the influencing factors of kinesiophobia among patients with varying characteristics.

Results

This study included a total of 290 participants. Based on the assessment of kinesiophobia, three profile models were identified by LPA: a high-level kinesiophobia group (21 participants, 7.2%), a moderate-level kinesiophobia group (189 participants, 65.2%), and a low-level kinesiophobia group (80 participants, 27.6%). Factors influencing the levels of kinesiophobia across the three latent profiles included education level, aortic stenosis flow type, number of comorbidities, postoperative NYHA cardiac function classification, preoperative physical activity level, social networks, and exercise self-efficacy.

Conclusion

Kinesiophobia levels in patients after transcatheter aortic valve replacement exhibit significant heterogeneity, primarily influenced by factors such as education level, aortic stenosis flow type, number of comorbidities, postoperative NYHA cardiac function classification, preoperative physical activity level, social networks, and exercise self-efficacy. In the future, healthcare professionals should identify postoperative patients at risk for kinesiophobia and consider the multifaceted factors affecting this condition. It is essential to encourage and stimulate patients’ thoughts about exercise and to provide targeted intervention strategies to reduce their levels of postoperative kinesiophobia.

Introduction

Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure that employs catheter-based techniques to replace a diseased valve and restore its normal function. it has emerged as a transformative therapy for severe aortic stenosis in high-risk surgical patients, demonstrating superior survival outcomes compared to medical management [1]. However, accumulating evidence reveals a paradoxical decline in physical activity levels following successful valve implantation [2]. Longitudinal studies report an average reduction of −126 kcal/week in habitual activity at 12-month follow-up [3], with van Erck et al. [4] documenting no significant improvement despite resolution of hemodynamic limitations. This persistent functional impairment underscores critical gaps in understanding post-TAVR recovery trajectories.

Kinesiophobia, also known as a maladaptive fear of movement, rooted in perceived vulnerability to injury may constitute a modifiable barrier to rehabilitation [5]. In cardiovascular populations, this construct demonstrates particular clinical relevance [6]: recent meta-analyses identify a 58.4–63.14% prevalence among heart failure patients [7, 8], a cohort with substantial pathophysiological overlap with TAVR patients [9]. Contemporary biopsychosocial models [10] posit that kinesiogenesis arises through complex interactions between biological determinants (e.g., fatigue severity [11], exertional dyspnea [12], and musculoskeletal pain [13, 14]) and psychosocial vulnerabilities, including depression [7], catastrophic illness perceptions [15], and diminished self-efficacy, et al. [14]. Although validated through the Tampa Scale for Kinesiophobia-Short Version (TSK-SV) in cardiac populations [16], this instrument remains unutilized in TAVR research.

Despite this understanding, the prevalence and factors associated with kinesiophobia among patients undergoing TAVR remain largely unexplored. This multicenter study therefore aims to: (i) establish the prevalence of kinesiophobia in TAVR patients; and (ii) identify the factors linked to kinesiophobia in individuals undergoing TAVR. Findings may inform targeted behavioral interventions to optimize postprocedural functional outcomes.

Methods

Study design

This study was a cross-sectional survey conducted in accordance with the STROBE guidelines.

Participants

Participants were enrolled from an inpatient cardiology unit from January 2023 to December 2023. Eligibility criteria encompassed individuals who had undergone TAVR and were scheduled for discharge within 24 h, possessed the ability to comprehend and converse in Mandarin, and had adequate auditory and visual capabilities to adhere to the study’s evaluation protocols. Exclusion criteria were based on unwillingness to participate, coexisting severe medical conditions such as acute infections, neoplasms, recent cerebrovascular accidents, or terminal illnesses, and the presence of significant psychiatric disorders.

Sample size

Based on the cross-sectional sample size estimation method, the TSK-SV Heart questionnaire comprises 17 items, necessitating a sample size that is 5 to 10 times the number of items. Taking into account a 20% rate of invalid responses, a minimum of 213 completed questionnaires is required. Ultimately, a total of 290 questionnaires were distributed for this study. For further details on the data collection process, please refer to Fig. 1.

Fig. 1.

Flow chart of patients screening and recruitment process

Data collection

Upon receiving approval from the relevant hospital department heads, the researcher ensured that informed consent was obtained individually from each participant. The process involved providing a detailed explanation of the study and addressing any questions to ensure full understanding of its purpose and procedures. For participants with lower education levels, the researcher personally interpreted and clarified each question. After participants provided their responses, the researcher recorded them and emphasized the strict confidentiality of the data. All participants who agreed to take part in the study signed the informed consent form beforehand. Nine patients declined to participate and, as a result, did not provide informed consent. Completed questionnaires were carefully reviewed and verified on-site before being immediately collected. Data entry was conducted by two individuals, with each entry being thoroughly cross-checked. Questionnaires with more than 20% missing items were considered invalid. At the same time, clinical data of the patients, such as echocardiographic parameters, cardiac function assessments, and comorbidities et al., were obtained by reviewing their medical records.

Instruments

Patients’ characteristics after TAVR was obtained through patient’s self-reported items and reviews of medical records. Kinesiophobia, self-efficacy for exercise, social support for exercise, social network and level of physical activity were assessed using self-reported questionnaires.

Socio-demographic characteristics and clinical conditions

We constructed a comprehensive questionnaire to assess factors associated with kinesiophobia, including demographic and medical details such as postoperative NYHA cardiac function classification and aortic stenosis flow type. Participants self-reported their demographic information, while medical and lab data were sourced from their records. The classification of aortic stenosis flow type was strictly adhered to the criteria specified in the 2021 ESC/EACTS Guidelines for the Management of Valvular Heart Disease [17]. Specifically, low-gradient AS was defined as a mean pressure gradient (ΔPm) less than 40 mmHg and a peak transvalvular velocity (Vmax) less than 4 m/s. Conversely, high-gradient AS was characterized by a ΔPm of 40 mmHg or greater, a Vmax of 4.0 m/s or greater, and a valve area of 1 cm² or less (or 0.6 cm²/m² or less when indexed to body surface area). The instrument’s quality was assured through a two-stage Delphi process, where 15 TAVR-experienced experts scored item appropriateness; those under 0.8 in content validity were removed. The second round achieved a 0.928 validity index, reflecting consensus. We also sought feedback from 18 patients on the questionnaire’s clarity, making essential refinements accordingly.

Kinesiophobia

The TSK-SV Heart questionnaire was employed in this study to assess the fear of physical activity among patients after TAVR. Validated for reliability and validity within the Chinese cardiovascular patient demographic [8], this instrument is comprised of 17 items that address concerns such as the risk of self-injury due to physical exertion or the exacerbation of heart conditions through activity. Responses are categorized on a four-point scale from ‘strongly disagree’ (assigned a score of 1) to ‘strongly agree’ (assigned a score of 4), with reverse scoring for items 4, 8, 12, and 16. The aggregate score varies from a minimum of 17 to a maximum of 68, with higher scores signifying greater apprehension towards movement. A threshold score of 38 or above is indicative of significant fear of movement and has been established for use among cardiovascular patient groups [8, 18–21]. This threshold is also applied in modified TSK scales, like the TSK-Fatigue and the TSK for chronic fatigue syndrome, to identify patients with heightened fear of movement [22, 23]. In the current analysis, the TSK-SV Heart demonstrated a Cronbach’s α coefficient of 0.801, indicating satisfactory internal consistency.

Self-efficacy for exercise

The Self-Efficacy for Exercise Scale (SEE) was developed by Resnick et al. [24] and the Chinese version of the scale was translated and culturally adapted by Lee et al. [25]. This scale is designed to measure the confidence of patients in engaging in physical activities across various situations. It consists of nine items, without any subscales, with each item scored on a scale from 0 to 10, reflecting the patient’s confidence in exercising in the face of obstacles. Higher scores indicate greater confidence and a higher level of exercise self-efficacy. In the current study, the Cronbach’s α for the SEE was 0.894.

Social support for exercise

Exercise Social Support Scale (ESSS): The ESSS was initially developed by Sallis et al. [26], requiring subjects to rate the frequency of exercise support provided by family and friends for each item. In 2012, Carlson et al. [27] adapted it into a simplified version, consisting of 5 items, with each item scored from 1 (never) to 5 (always), with higher scores indicating a higher degree of exercise social support. The simplified version has good reliability and validity, with confirmatory factor analysis supporting the construct validity of the scale, a comparative fit index (CFI) of 0.90, and a correlation coefficient of 0.96 with the original scale. In China, the simplified version of the ESSS has been effectively utilized to assess the exercise support status among patients who have suffered from acute myocardial infarction, demonstrating satisfactory reliability and validity in this context. In the current study, the Cronbach’s α for the SEE was 0.92.

Social network

The Lubben Social Network Scale-6 (LSNS-6) is a brief tool for assessing social support from family and friends [28]. It has six questions, scored 0 to 5, with a maximum score of 30. A score under 12 may indicate weak social ties. Studies confirm the LSNS-6’s suitability for elderly people across cultures, including in China, where it shows good reliability [28, 29]. It’s a useful tool for spotting older adults at risk of social isolation.

Physical activity

In this study, the Physical Activity Rank Scale (PARS-3), translated and revised by Chinese scholars was utilized to assess the physical activity levels of participants over the past month [30, 31]. The scale consists of one dimension and three items, which are exercise intensity (mild, light, moderate, vigorous, and extremely persistent vigorous), exercise duration (< 10 min, 11–20 min, 21–30 min, 31–59 min, > 60 min), and exercise frequency (≤ 1 time per month, 2–3 times per month, 1–2 times per week, 3–5 times per week, about once a day). Scores for exercise intensity and frequency range from 1 to 5, while scores for exercise duration range from 0 to 4. The total score is calculated as the product of the exercise intensity score, exercise duration score, and exercise frequency score, with a range of 0 to 100 points. A score below 19 indicates low physical activity, 20 to 42 indicates moderate physical activity, and above 43 indicates high physical activity. Higher scores suggest a higher level of physical activity in the past month. The scale has good reliability and validity, with a Cronbach’s α coefficient of 0.82 in the study.

Data analysis

Statistical software Mplus 8.3 and SPSS 26.0 were utilized for the construction of the latent profile model and for statistical analysis of the data, respectively. Initially, continuous variables were converted into categorical variables, which were then represented as frequency distributions and relative proportions. Latent Profile Analysis (LPA) was employed to classify participants into different latent subgroups based on their scores on the Kinesiophobia Scale for Heart Disease. A series of indices were used to assess the fit of each latent profile [1–5], including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), adjusted BIC (aBIC), Lo-Mendell-Rubin likelihood test (LMRT), bootstrap likelihood ratio test (BLRT), and entropy. A model was deemed to have a good fit when it exhibited low values for AIC, BIC, and aBIC, along with an entropy value greater than 0.8, indicating high classification accuracy [32]. Furthermore, the final number of categories was determined in conjunction with the practical significance of the classifications. After selecting the best-fitting model, multiple logistic regression analysis was conducted to explore the factors influencing patients’ levels of kinesiophobia.

Once the optimal number of latent profiles was determined, statistical analyses were conducted using SPSS 29.0. First, we performed univariate analyses, including one-way ANOVA and chi-square tests, to identify variables with statistically significant differences among the kinesiophobia subgroups. Variables that were statistically significant in the univariate analyses (p < 0.05, two-tailed) were included in the multinomial logistic regression model. A threshold of p < 0.05 was established for including variables in the final model.

Ethical considerations

This study was conducted in strict compliance with the ethical standards of the Declaration of Helsinki. The study received clearance from the Ethics Committee of Zhongshan Hospital affiliated with Fudan University (B2022-062). Prior to participant enrollment, the survey instrument was subjected to rigorous review and approval. Commencing the study, researchers furnished participants with an exhaustive information brochure, complemented by oral explanations, highlighting the voluntary aspect of participation and the option to disengage at any juncture without necessitating a justification. The brochure delineated the study’s objectives, importance, and anticipated benefits. Affirmative written consent was secured from all participants prior to their involvement. To ensure confidentiality, no personally identifiable demographic data were gathered.

Results

Participant characteristics

Among 290 participants, 156 (53.8%) were male. Most of the patients (47.2%) were 71–80 years old. Junior high school/senior high school/technical secondary school education accounted for the highest proportion. 48.6% of the respondents had three or more complications. It should be clarified that these comorbidities predominantly included pre-existing chronic conditions (e.g., hypertension, diabetes, chronic kidney disease) rather than acute postoperative complications. The inclusion of pre-existing comorbidities aligns with the study’s focus on preoperative risk factors influencing kinesiophobia. Detailed participant characteristics are listed in Table 1.

Table 1.

Socio-demographic characteristics of the sample (N = 290)

Variable	Number	Proportion (%)
Gender
Male	156	53.8
Female	134	46.2
Age(year)
<60	14	4.8
60–70	92	31.7
71–80	137	47.2
> 80	47	16.2
Marital status
Unmarried	0	0
Married	248	85.5
Divorced	4	1.4
Widowed	38	13.1
Education level
Illiteracy	34	11.7
Primary school	66	22.8
Junior high school/high school/technical secondary school	84	29.0
Junior college	63	21.7
Bachelor degree or above	43	14.8
Place of residence
Rural	195	67.2
Urban	95	32.8
Number of comorbidities
0	121	41.7
1–2	28	9.7
≥ 3	141	48.6
BMI
< 18.5	22	7.6
18.5–23.9	145	50
24–26.9	74	25.5
≥ 27	49	16.9
New York Heart Association
Level 1	67	23.1
Level 2	72	24.8
Level 3	81	27.9
Level 4	70	24.1

Descriptive statistics and correlations

Post-TAVR kinesiophobia was negatively correlated with exercise social support, social networks, exercise self-efficacy, and preoperative physical activity levels. The average kinesiophobia score was 42.77 (SD = 5.10), indicating moderate fear. The score for exercise social support was 11.17 (SD = 5.54), reflecting a low to moderate level; the social network score was 15.59 (SD = 6.16), categorized as moderate; the exercise self-efficacy score was 31.09 (SD = 22.50), indicating a low level; and the preoperative physical activity score was 7.72 (SD = 3.40), classified as moderate.

Exploratory latent profile analysis

In this study, 17 items of the TSK-SV Heart questionnaire were used as explicit variables, and 1–5 potential profile models were selected. The fitting results are shown in Table 2. Comprehensively comparing the fitting indicators among the model categories, the AIC, BIC and ABIC values of model 3 are relatively small, and the LMR and blrt tests have reached significant levels, and the entropy value is ≥ 0.8, so model 3 can be considered as the best fitting model. As shown in Fig. 2, group C1 and C3 had the highest and lowest scores, which were defined as “high-level fear of movement group” and “low-level fear of movement group”, accounting for 7.2% (21/290) and 27.6% (80/290), respectively. The scores of C2 group were all moderate, which was the moderate level movement fear group, accounting for 65.2% (189/290).

Table 2.

Fit indices of latent profile analysis of the kinesiophobia after TAVR (N = 290)

Model	AIC	BIC	aBIC	Entropy	Proportions	LMR(P)	BLRT(P)
1-profile	12288.200	12412.976	12305.156	——	——	——	——
2-profile	11802.751	11993.585	11828.683	0.808	0.392/0.608	0.4122	< 0.001
3-profile	11576.662	11833.554	11611.571	0.916	0.072/0.652/0.276	0.0369	< 0.001
4-profile	11453.201	11776.151	11497.087	0.908	0.297/0.079/0.421/0.203	0.3726	< 0.001
5-profile	11372.307	11761.314	11425.169	0.920	0.097/0.207/0.593/0.069/0.034	0.291	< 0.001

Fig. 2.

Different profiles of the kinesiophobia after TAVR

AIC Akaike information criterion, BIC Bayesian information criterion, aBIC adjusted BIC, LMR Lo-Mendell-Rubin, BLRT Bootstrap likelihood ratio test.

Characteristics of latent profile membership

Univariate analysis revealed significant differences among the three latent categories in terms of education level, number of comorbidities, postoperative NYHA cardiac function classification, preoperative physical activity level, social network level, exercise self-efficacy, and exercise social support. In the high exercise fear group, individuals with illiteracy and those classified as postoperative cardiac function grade III constituted a substantial proportion. The medium exercise fear group had the largest representation, primarily consisting of patients aged 71–80, with primary school education and three or more comorbidities. In contrast, the low exercise fear group mainly comprised individuals with junior high, high school, or technical secondary school education, no complications, and the highest number of patients classified as NYHA cardiac function grade II. Additionally, the low exercise fear group exhibited significantly higher scores in social network level, preoperative physical activity level, exercise self-efficacy, and exercise social support compared to both the high and medium exercise fear groups. Detailed information can be found in Table 3; Fig. 3.

Table 3.

Differences in patients with kinesiophobia after TAVR in demographics, exercise self-efficacy, social networks, exercise social support, and preoperative physical activity levels (n = 290)

Variable	High level kinesiophobia	Moderate level kinesiophobia	Low level kinesiophobia	χ²/F	P
Gender
Male	12(57.1%)	93(49.2%)	51(63.7%)	4.885	0.087
Female	9(42.9%)	96(50.8%)	29(36.3%)
Age(year)
<60	1(4.8%)	9(4.8%)	4(5.0%)	2.172	0.903
60–70	5(23.8%)	58(30.7%)	29(36.3%)
71–80	10(47.6%)	91(48.1%)	36(45.0%)
> 80	5(23.8%)	31(16.4%)	11(13.7%)
Marital status
Unmarried	0	0	0	1.977	0.740
Married	20(95.2%)	159(84.1%)	69(86.3%)
Divorced	0	3(1.6%)	1(1.3%)
Widowed	1(4.8%)	27(14.3%)	10(12.5%)
Education level
Illiteracy	6(28.6%)	23(12.2%)	5(6.3%)	17.675	0.024*
Primary school	5(23.8%)	49(25.9%)	12(15%)
Junior high school/high school/technical secondary school	3(14.3%)	48(25.4%)	33(41.3%)
Junior college	5(23.8%)	42(22.2%)	16(20%)
Bachelor’s degree or above	2(9.5%)	27(14.3%)	14(17.5%)
Place of residence
Rural	12(57.1%)	124(65.6%)	59(73.8%)	2.740	0.254
Urban	9(42.9%)	65(34.4%)	21(26.3%)
Aortic stenosis flow type
Low-gradient aortic stenosis	9(42.9%)	9(4.8%)	4(5.0%)	40.178	< 0.001*
High-gradient aortic stenosis	12(57.1%)	180(95.2%)	76(95.0%)
Number of comorbidities
0	3(14.3%)	72(38.1%)	46(57.5%)	57.309	< 0.001*
1–2	9(42.9%)	6(3.2%)	13(16.3%)
≥ 3	9(42.9%)	111(58.7%)	21(26.3%)
BMI(kg/m2)
< 18.5	0	17(9.0%)	5(6.3%)	7.421	0.284
18.5–23.9	14(50%)	90(47.6%)	41(51.2%)
24–26.9	3(25.5%)	54(28.6%)	17(21.3%)
≥ 27	4(16.9%)	28(14.8%)	17(21.3%)
New York Heart Association
Level 1	5(23.8%)	49(25.9%)	13(16.3%)	14.383	0.026*
Level 2	4(19%)	39(20.6%)	29(36.3%)
Level 3	8(38.1%)	59(31.2%)	14(17.5%)
Level 4	4(19%)	42(22.2%)	24(30%)
LSNS-6	15.90 ± 6.70	14.82 ± 5.81	17.31 ± 6.45	4.750	0.009*
PARS-3(preoperative)	5.33 ± 3.40	7.22 ± 3.32	9.51 ± 2.79	20.860	< 0.001*
SEE	12.86 ± 16.72	29.52 ± 20.85	39.60 ± 24.09	14.275	< 0.001*
ESSS	8.81 ± 4.56	10.90 ± 5.27	12.41 ± 6.15	4.232	0.015*

*p <.05

Fig. 3.

Distribution of kinesiophobia levels across different patient characteristics

Predictors of latent profile membership

Subsequently, we employed a multinomial logistic regression model for analysis, using the low kinesiophobia group as the reference category to validate the influencing factors across the three profiles. As shown in Table 4, compared to the low kinesiophobia group, patients in the high and moderate kinesiophobia groups were more likely to have lower educational attainment, low-gradient aortic stenosis and to have three or more comorbidities. Additionally, patients with lower levels of preoperative physical activity were more likely to be classified into the moderate and high kinesiophobia groups. Notably, patients classified as having New York Heart Association (NYHA) functional class I were more likely to fall into the moderate kinesiophobia group, while those with lower exercise self-efficacy were more likely to be categorized in the high kinesiophobia group. Furthermore, compared to moderate kinesiophobia patients, those with 1–2 comorbidities were more likely to be classified into the high kinesiophobia group.

Table 4.

Multinomial logistic regression analysis of the kinesiophobia after TAVR among three classes (N = 290)

Variables	Class 1 vs. Class 3a				Class 2 vs. Class 3a				Class 1 vs. Class 2a
	β	SE	P	OR	β	SE	P	OR	β	SE	P	OR
Constants	1.048	1.563	0.502	-	3.617	0.798	< 0.001	-	−2.569	1.415	0.070	-
Education level
Illiteracy	3.366	1.255	0.007*	28.960	1.429	0.699	0.041*	4.175	1.937	1.114	0.082	6.937
Primary school	1.281	1.297	0.286	3.600	1.531	0.563	0.007*	4.623	−0.250	1.237	0.840	0.779
Junior high school/high school/technical secondary school	−0.030	1.301	0.981	0.970	0.041	0.491	0.934	1.042	−0.071	1.259	0.955	0.931
Junior college	0.910	1.211	0.452	2.485	0.752	0.526	0.153	2.121	0.158	1.153	0.891	1.172
Bachelor’s degree or abovea
Aortic stenosis flow type
Low-gradient aortic stenosis	2.485	0.938	0.009*	11.681	−0.638	0.693	0.357	0.529	3.096	0.792	< 0.001*	22.100
High-gradient aortic stenosis a
Number of comorbidities
0	−2.025	0.920	0.028*	0.132	−1.235	0.347	< 0.001*	0.291	−0.790	0.876	0.367	0.454
1–2	0.980	0.920	0.286	2.666	−2.466	0.632	< 0.001*	0.085	3.446	0.889	< 0.001*	31.390
≥ 3 a
New York Heart Association
Level 1	0.213	1.077	0.843	1.237	1.050	0.475	0.027*	2.856	−0.837	1.032	0.413	0.433
Level 2	−0.256	0.996	0.797	0.774	−0.297	0.420	0.480	0.743	0.041	0.956	0.966	1.042
Level 3	0.667	0.917	0.467	1.949	0.617	0.459	0.179	1.853	0.051	0.851	0.953	1.052
Level 4a
LSNS-6	−0.010	0.055	0.854	0.990	−0.060	0.027	0.026*	0.941	0.050	0.051	0.321	1.052
PARS-3(preoperative)	−0.274	0.123	0.025*	0.760	−0.195	0.064	0.002*	0.823	−0.079	0.114	0.489	0.924
SEE	−0.045	0.021	0.035*	0.956	−0.003	0.008	0.707	0.997	−0.042	0.021	0.042*	0.959
ESSS	−0.036	0.078	0.646	0.965	−0.008	0.032	0.808	0.992	−0.028	0.075	0.708	0.972

^aReference group, Class 1 = High level kinesiophobia group, Class 2 = Medium level kinesiophobia group, Class 3 = Low level kinesiophobia group, LSNS-6: The Lubben Social Network Scale-6, PARS-3(preoperative). The physical activity rank scale(preoperative), SEESelf-Efficacy for Exercise Scale, ESSSExercise Social Support Scale

*p <.05

Discussion

In this study, the mean score of kinesiophobia among patients after TAVR at discharge was 42.77 ± 5.10. This value exceeded the established cut-off point for clinically significant kinesiophobia symptoms (38 points), indicating that kinesiophobia was prevalent at a relatively high level within this patient population. In this study, the average score of kinesiophobia in patients with CHD was 42.77 ± 5.10, which was higher than the cut-off value of kinesiophobia symptoms (38 points), and was at a relatively high level overall. Latent profile analysis revealed three distinct levels of kinesiophobia in patients after TAVR at discharge: low, medium, and high kinesiophobia groups. The results showed significant individual differences in exercise-related fear, with the medium kinesiophobia group being the largest (65.2%), followed by the low (27.6%) and high (7.2%) groups. This distribution follows an “olive shape,” with the largest proportion in the middle and smaller proportions at both ends. These findings are consistent with the results reported by Wang Z in a study of kinesiophobia in patients with coronary heart disease [12]. Notably, more than 70% of patients after TAVR at discharge exhibited medium to high levels of kinesiophobia, indicating that a significant number of TAVR patients are generally concerned about exercise. Previous research suggests that kinesiophobia levels can directly predict physical activity levels, which, in turn, can greatly affect patients’ quality of life and exercise adherence [33]. During our previous study, we also found that kinesiophobia is important barriers for patients to maintain physical activity [34]. Based on these findings, future research should focus on the status of kinesiophobia in TAVR patients before discharge and intervene as early as possible. Only in this way can we better promote the early rehabilitation of TAVR patients after discharge.

The results of the study indicate that education level, aortic stenosis flow type, the number of comorbidities, and postoperative NYHA cardiac function classification are significant factors influencing kinesiophobia in patients after TAVR at dischage. Although these factors may be difficult to intervene directly, they can help us efficiently identify individuals who are likely to experience kinesiophobia. For example, patients with lower education levels or those with more comorbidities may be at higher risk of developing kinesiophobia. By recognizing these risk factors early, healthcare providers can implement targeted interventions to mitigate the impact of kinesiophobia on patients’ rehabilitation and quality of life.

A systematic review also revealed that education level was an influencing factor of kinesiophobia [35]. A potential explanation may be that less-educated patients lacked awareness about the advantages of post-procedural exercise therapy, leading to exercise-related anxiety due to misconceptions that physical activity might worsen their condition or trigger recurrent symptoms. This finding also suggests that healthcare providers should pay particular attention to patients with lower education levels and offer tailored health education on the benefits of exercise rehabilitation post-TAVR. Aortic stenosis flow type serves as a crucial hemodynamic indicator for assessing preoperative cardiac function in TAVR candidates, reflecting both the severity of valvular obstruction and its systemic circulatory consequences. This study found that the incidence of kinesiophobia is relatively high among patients with low-gradient aortic stenosis. This phenomenon may result from the interplay of multiple factors. From a pathophysiological perspective, the low-flow state before TAVR leads to chronic tissue hypoperfusion, which in turn causes exercise intolerance [17]. From the clinical characteristics perspective, patients have long experienced symptoms of dyspnea, fatigue, and other discomforts associated with decreased cardiac function before TAVR, and these factors further exacerbate patients’ exercise-avoidant behaviors and kinesiophobia [34]. According to the results of this study, this fear of movement persists up to the time of discharge. Therefore, patients with low-gradient aortic stenosis should be given special attention to identify and intervene in their kinesiophobia in a timely manner, thereby improving rehabilitation outcomes. The number of comorbidities also significantly influences the level of kinesiophobia in patients after TAVR. Those with more comorbidities tend to experience higher levels of kinesiophobia, which can be attributed to several factors. Firstly, comorbidities often lead to a decline in cardiopulmonary function and decreased physical endurance, making patients feel uncomfortable or fatigued during exercise, which can foster resistance to physical activity [36]. Secondly, the presence of comorbidities is frequently associated with heightened psychological distress, including anxiety and depression, which further exacerbates fears related to exercise. Additionally, reduced confidence in their ability to recover, along with the pain and discomfort that may arise during postoperative recovery, can amplify their fear of exercise [37]. It is essential for clinical nursing care to consider the comprehensive conditions related to complications in patients post-TAVR, to develop personalized rehabilitation plans that effectively address exercise fear, promote recovery of physical function, and enhance quality of life. In our study, patients with NYHA Class I heart function exhibited higher levels of kinesiophobia than those with Class IV heart function, a finding that contradicts our initial expectations. The possible reasons are as follows: Although NYHA Class I patients have better cardiac function, they may have excessive concerns about their health status and are highly sensitive to mild discomfort during exercise, which amplifies their fear of movement. In contrast, patients with Class IV heart function, who have long experienced severe symptoms, have gradually adapted to these symptoms and are more reliant on guidance from the medical team, resulting in relatively lower levels of kinesiophobia. However, these are merely preliminary speculations by the research team, and the specific reasons need to be further explored and perfected in future studies.

Social support, preoperative level of physical activity, and self-efficacy play crucial roles in the kinesiophobia of patients after TAVR at discharge.This finding is consistent with the results of a previous systematic review [35]. Studies have shown that social support can promote self-efficacy, which in turn encourages physical activity [38]. Additionally, patients who engage in regular physical activity before TAVR are more likely to maintain physical activity after the procedure [34]. Higher levels of physical activity are strongly associated with enhanced exercise self-efficacy. Patients who engage in more physical activity tend to be more confident in their ability to navigate the postoperative rehabilitation process, resulting in a more positive attitude toward exercise challenges [39]. Therefore, interventions that enhance social support, improve self-efficacy, and encourage preoperative physical activity may help reduce kinesiophobia and promote better rehabilitation outcomes for patients after TAVR. Specifically, enhancing social support should focus on its quality and relevance to patients’ needs, rather than merely its presence. This can be achieved by providing emotional support through regular psychological counseling, offering informative support about the procedure and rehabilitation process, and encouraging the involvement of family and friends to provide practical and emotional assistance [40]. Improving self-efficacy can be facilitated by setting specific, achievable goals for patients, providing opportunities for small successes to build confidence, and offering consistent positive feedback from healthcare providers and family members [41]. Encouraging physical activity is also crucial. Personalized exercise plans tailored to patients’ physical conditions and preferences, such as walking or dancing, can be implemented. Behavioral interventions, including self-monitoring, goal setting, and stimulus control, can help patients gradually increase their physical activity levels. Ongoing support for exercise both before and after procedure can help patients maintain these healthy habits. By integrating these comprehensive interventions, we can effectively reduce kinesiophobia in TAVR patients and enhance their overall rehabilitation outcomes. In addition, in this study, exercise social support did not emerge as a significant influencing factor in the multiple logistic analysis. This finding may be attributed to the fact that the effects of exercise social support are likely moderated by various internal and external factors. These factors, which may include individual differences in patient motivation, the quality and relevance of the support provided, and the broader context of the patient’s social environment, warrant further exploration and refinement in future studies.

Limitations and prospects

First, as a cross-sectional study focused on identifying risk factors, this research did not implement any interventions. Therefore, further studies are warranted to validate effective interventions for reducing kinesiophobia in post-TAVR patients. Second, while the physical activity rank scale (PARS-3) was adopted for assessing physical activity levels-a self-reported measure that is more subjective than objective tools like pedometers—this approach was justified for two reasons: (1) Most post-TAVR patients in our study population lacked access to wearable activity trackers, and (2) PARS-3 remains an internationally recognized tool for physical activity assessment, consistent with methodologies employed in comparable studies. Third, the current analysis incorporated limited disease-related factors. Future research should comprehensively examine how clinical characteristics influence kinesiophobia development in this population. Finally, though our single-center study at Shanghai’s pioneering TAVR hospital (with nationally representative samples) provided robust sample size, regional limitations remain unavoidable. We propose future multicenter studies across diverse regions, incorporating longitudinal designs, qualitative methods, and additional variables (e.g., psychological trait analysis) to better understand and mitigate kinesiophobia, thereby optimizing post-TAVR exercise management.

Conclusions

This study utilized Latent Profile Analysis to evaluate levels of kinesiophobia in patients following TAVR. The results revealed distinct classification characteristics of kinesiophobia among these patients, which can be categorized into three latent groups: low, medium, and high level kinesiophobia groups. Factors influencing kinesiophobia included education level, number of comorbidities, postoperative NYHA cardiac function classification, preoperative physical activity level, social networks, and exercise self-efficacy. While no interventions were implemented in the current design, The stratification of patients into distinct kinesiophobia profiles enables precision interventions. For instance, high-risk subgroups (e.g., low education, low-gradient aortic stenosis) may benefit from simplified psychoeducation and supervised low-intensity regimens, while moderate-risk patients require peer-supported group activities. Integrating wearable technology for real-time monitoring and feedback can further personalize rehabilitation strategies. Future trials should evaluate the efficacy of these tailored approaches in reducing fear and improving functional outcomes.

Abbreviations

TAVR

Transcatheter aortic valve replacement

ANOVA

One-way analysis of variance

LMR

Lo-mendell-rubin

BLRT

Bootstrap likelihood ratio test

AIC

Akaike information criterion

BIC

Bayesian information criterion

SABIC

Sample-size-adjusted bayesian information criterion

LPA

Latent profle analysis

LSNS-6

The Lubben Social Network Scale-6

PARS-3(preoperative)

The physical activity rank scale(preoperative)

SEE

Self-Efficacy for Exercise Scale

ESSS

Exercise Social Support Scale

Authors’ contributions

Zhiyun Shen and Dandan Geng contributed equally to the conceptualization, design of the study, analysis of data, and drafting of the manuscript. Ying Lin and Yuxia Zhang contributed equally to the conceptualization, supervision, funding, and revising of the manuscript critically for important intellectual content. Daxin Zhou was involved in revising it critically for important academic content. Chenxu Huang and Xiaohua Xu were involved in the data collection. All authors approved the final version of the article to be published, agreed on the journal to which the article has been submitted, and agreed to be accountable for all aspects of the work.

Funding

This study was supported by Shanghai Three-Year Action Plan for Strengthening the Public Health System (2023–2025, Key Discipline, GWVI-11.1-46 — Health Education and Health Promotion — Direction 20: Health Education, Health Promotion, and Health Science Popularization Strategies, Research, and Evaluation under the Background of Media Convergence), and the Youth Fund of Zhongshan Hospital, Fudan University (2022ZSQN07). Additional sources of support for this research and manuscript development include the Shanghai Municipal Health Commission Special Project for Clinical Research in the Health Industry (20234Y0183), the Clinical Research Fund of Zhongshan Hospital, Fudan University (ZSLCYJ202358), and the Cardiovascular Nursing Program of Zhongshan Hospital, Fudan University (xk-082-011).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

In formulating this study, we engaged with patients from a diverse array of backgrounds to assess their comprehension and interpretation of the data collection instruments, thereby aiding in the selection of research materials. Throughout the execution of this study, all data were derived directly from patients. Written informed consent was obtained from all participants prior to enrollment, and they were fully informed of the study’s purpose. The study was approved by the Ethics Committee of Zhongshan Hospital, Fudan University (B2022-062R).

Consent for publication

Not applicable.

Clinical trial number

Not applicable.

Competing interests

The authors declare no competing interests.