
==== Front
Eur J Phys Rehabil Med
Eur J Phys Rehabil Med
EJPRM
European Journal of Physical and Rehabilitation Medicine
1973-9087
1973-9095
Edizioni Minerva Medica

39007784
8268
10.23736/S1973-9087.24.08268-6
Article
The Spanish adaptation of the Tampa Scale for Kinesiophobia Heart: psychometric evidence in cardiac rehabilitation patients
COELLO-CREMADES Mercedes 1 2
MARTÍNEZ-MOLINA Agustín 3 *
FERRER-PEÑA Raúl 1 4 5
LERMA-LARA Sergio 1 2
1Department of Physical Therapy, Centro Superior de Estudios Universitarios La Salle, Universidad Autónoma de Madrid, Madrid, Spain; 2Instituto de Rehabilitación Funcional La Salle, Aravaca, Calle Ganímedes, Madrid, Spain; 3Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain; 4Clinico-Educational Research Group on Rehabilitation Sciences (INDOCLIN), Centro Superior de Estudios Universitarios La Salle, Madrid, Spain; 5Instituto de Investigación Sanitaria del Hospital Universitario La Paz (IdiPAZ), Madrid, Spain
* Corresponding author: Agustín Martínez-Molina, Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain. E-mail: agustin.martinez@uam.es
Authors’ contributions: All authors contributed to the study conception and design. Mercedes Coello-Cremades and Agustín Martínez-Molina performed the data acquisition, analysis, and interpretation. Mercedes Coello-Cremades wrote the first draft of the manuscript, all authors commented on previous versions of it, and Mercedes Coello-Cremades revised each version critically. All authors read and approved the final version of the manuscript.

15 7 2024
8 2024
60 4 691702
10 5 2024
04 3 2024
06 10 2023
2024 THE AUTHORS
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND) 4.0 License.
BACKGROUND

The factor structure of the Tampa Scale of Kinesiophobia Heart version has rarely been adequately analyzed. We aimed to evaluate the psychometric properties of this scale through a variety of exploratory and confirmatory factorial approaches.

AIM

To perform a translation, cross-cultural adaptation, and psychometric evaluation of the Spanish version of the Tampa Scale of Kinesiophobia Heart in patients attending Cardiac Rehabilitation (TSK-SPA).

DESIGN

Cross-sectional study.

SETTING

A Cardiac Rehabilitation unit.

POPULATION

Adults with the principal diagnosis of coronary artery disease (83%) who were referred to Cardiac Rehabilitation (N.=194; mean age, 64.28±9.2; 15% women).

METHODS

We performed a translation and a cross-cultural adaptation of the TSK-SPA. The psychometric properties of validity comprising the face, content, and construct validity were then tested. Five factorial models were proposed to analyze the data structure. We examined the validity evidence of the TSK-SPA based on the relationships with other analyzed variables using the SF12 quality of life Questionnaire, the International Physical Activity Questionnaire, the Hospital Anxiety and Depression Scale and the Beck Depression Inventory. The reliability tests included internal consistency and stability over time.

RESULTS

The results suggested a four-dimensional structure. Models with more than 1 dimension exhibited undesirable factor loadings or inadequate fit indices. Based on these results, a short version of the scale with 13 items is proposed. In terms of reliability, the TSK-SPA Heart was found internally consistent (α=0.79) and stable over time (test-retest = 0.82). An Exploratory Structural Equation Modeling (ESEM) analysis provided an acceptable fit for a hypothesized 4-factor model with the inclusion of a method factor: the root mean squared error of approximation was <0.05 (RMSEA = 0.046), and the comparative fit indices were >0.95 or close (CFI=0.994, TLI=0.934). Significant positive correlations were observed between the TSK-SPA scores and the measures of anxiety and depression, with correlation coefficients ranging from 0.35 to 0.48.

CONCLUSIONS

A best-fitting model was identified, and the proposed 13-item TSK-SPA Heart showed sufficient evidence of validity and reliability for Spanish patients with cardiovascular disease. The scale’s overall reliability is deemed acceptable, although the factor reliability could be further enhanced.

CLINICAL REHABILITATION IMPACT

Using this questionnaire on fear or avoidance of movement will improve our understanding of cognitive-behavioral factors in patients with cardiovascular disease, aiding their rehabilitation and optimizing their prognosis.

Key words:

Cardiac rehabilitation
Psychometrics
Surveys and questionnaires
Heart
Phobic disorders
Coronary artery disease
==== Body
pmcCardiac rehabilitation (CR) and exercise therapy have demonstrated their efficacy in primary and secondary cardiovascular disease (CVD) prevention, as well as their ability to reduce overall morbidity and mortality.1

However, recent studies have concluded that patient’s beliefs and cognitive processes, directly affect the prognosis and outcome of rehabilitation.2, 3

Irrational ideas and dysfunctional processing are related to health anxiety and hypochondriasis.4 Individuals with hypochondria often show excessive concern for their bodies and are in a constant fear of serious illnesses.5

Incorporating the biopsychosocial perspective of health has improved our understanding of factors contributing to successful rehabilitation. Cognitive behavioral therapy6 has shown a beneficial effect on self-regulation, controlling thoughts (rumination, worry), emotions (restlessness, fear, sadness), and avoidance behaviors associated with CVD.7

In the era of patient-centered medicine, it is important to include information from patient self-reported questionnaires as part of good clinical practice. Specific tools and reliable and validated questionnaires are therefore crucial for assessing the cognitive processes associated with health anxiety, such as fear avoidance beliefs and kinesiophobia.

Within the medical literature, the terms “kinesiophobia” and “fear of movement” are frequently used interchangeably, although there are subtle differences in their meanings.8 Kinesiophobia is described as “the excessive, irrational, and debilitating fear of physical movement and activity resulting from a feeling of vulnerability to painful injury or re-injury.”9 Kinesiophobia refers to the most severe manifestation of fear related to movement.

The Tampa Scale for Kinesiophobia (TSK) is a questionnaire developed to measure fear of movement, which Vlaeyen defined as “a specific fear of movement and physical activity that is (incorrectly) assumed to cause re-injury.”10 The TSK has been studied for more than 20 years in relation to musculoskeletal pain and, for nearly 10 years in relation to cardiovascular diseases.

In the acute phase after a cardiac event, fear might be regarded as a normal psychological reaction. In individuals experiencing chronic pain, it has been demonstrated that fear and subsequent avoidance behaviors serve as adaptive responses to injury.11 However, there are patients who cannot manage their fear and develop long-term avoidance behaviors.10, 12 These patients might exhibit elevated scores on certain items within the TSK.

The TSK for pain was adapted for cardiovascular diseases by Bäck et al. and designated The Tampa Scale for Kinesiophobia Swedish Version Heart13 (TSK-SV Heart). Thereafter, it has been translated and validated into Turkish,14 Dutch,15 Portuguese,16 and Polish.17

The initial effort to provide evidence of validity for the TSK17 Heart questionnaire by Bäck13 assumed a factor structure of the data without conducting an exploratory analysis to determine the underlying dimensions. Instead, a confirmatory factor analysis (CFA) was directly executed, resulting in four factors with no proper loadings. However, subsequent studies supported a three-component structure based solely on the principal component analysis (PCA) of the TSK Heart.15, 17

Although both the exploratory factor analysis and principal component analysis are variable reduction techniques, they are often mistaken in this type of questionnaire.18

The three-component structure of the TSK Heart has been unduly supported in various studies.14, 15, 17 The TSK Heart never obtained robust empirical support for the aforementioned three components in an exploratory factorial manner (although it did show components or composites, which is a different issue).19 Subsequent research deemed the 3-factor structure as the most appropriate. Nevertheless, this error in determining and estimating the number of factors can be attributed primarily to two main factors. Firstly, a number of researchers have tended to rely on default settings in data reduction software, (e.g., SPSS) without carefully considering the appropriate dimensionality. Secondly, there is a CFA misuse, given that its strict loading restrictions are often applied without addressing specific hypotheses.

In our case, one of the goals of the study was to establish a reliable factor structure for the questionnaire. To assess the data dimensionality, we employed a parallel analysis combined with an exploratory structural equation modeling (ESEM). If deemed suitable, a CFA can be subsequently conducted to validate the proposed structure.

Given the limitations of generalizing the results of previous studies, the aims of this study were as follows:

to perform a translation and cross-cultural adaptation of the TSK Heart (English to Spanish);

to assess the psychometric properties of the Spanish version of the TSK Heart (TSK-SPA) in patients with CVD referred to CR, i.e., its validity (in terms of its structure) and reliability (e.g., internal consistency and stability over time);

to analyze the validity tests in terms of relationships with other variables, considering anxiety, depression, physical activity levels and quality of life.

Our hypotheses testing for construct validity involves predicting the strength and direction of correlations between the subscales of the scale. Specifically, we hypothesize that fear of harm is positively correlated with perceived threat and avoidance of physical activity, given that individuals who fear harm may perceive greater threat and subsequently engage in more avoidance behaviors.20 Additionally, we anticipate a positive correlation between avoidance of physical activity and perceived self-dysfunction, as individuals who avoid physical activity may perceive greater physical limitations. These hypotheses were clinically grounded, as understanding the interplay between these constructs is crucial for effectively assessing and treating kinesiophobia.21 By elucidating these relationships, we aim to develop targeted interventions that address individual concerns and limitations related to physical exercise and rehabilitation.

Materials and methods

Study design

A cross-sectional study was conducted at our center’s CR Unit, with data collected during the admission to CR (T1) and 7 days post-admission (T2). The study was structured into two stages: 1) the implementation of a structured transcultural adaptation protocol to ascertain the scale’s content validity; and 2) the assessment of the scale’s psychometric properties.

Ethical considerations

All research procedures were established in accordance with the Declaration of Helsinki and were approved in advance by our university’s bioethics committee (CSEULS-PI-185/2017). Permission was sought from the original author of the TSK-Heart13 to obtain authorization for translation and cross-cultural adaptation.

Cross-cultural adaptation

The first phase of this study was conducted according to the International Test Commission guidelines for translating and adapting tests.22, 23

Step 1, translation: two native bilingual speakers with basic knowledge of the terminology employed in health sciences independently translated the original English version of the TSK17 Heart into Spanish;

step 2, review committee: a bilingual judging panel consisting of 8 healthcare professionals (including specialists in psychology, physiotherapy, nursing, and cardiology) evaluated, approved, and merged the 2 translations of the scale. Two native bilingual speakers, who were unaware of the original version, then back-translated the Spanish version of the TSK17 Heart into English. The committee verified the semantic equivalence and content validity of the retro-translated version and were requested to provide qualitative evaluations for each item, considering factors such as the level of comprehension and appropriateness of wording. Additionally, the committee was asked to provide quantitative assessments of the items based on their clarity, coherence, and relevance;

step 3, test of the prefinal version: once the information extracted from the committee was established and analyzed, a pretest was conducted to evaluate the understanding and clarity of the instrument in 30 patients with CVD;

step 4, completion with a final approval: the results of the pretest were employed to make final modifications to the instrument, concluding the linguistic adaptation process with the results of the final version to be employed in the second stage of the psychometric properties evaluation.

Sample

The sample size was based on the general guidelines provided by the European Federation of Psychologists’ Associations, and the International Test Commission guidelines for translating and adapting tests,22 which involved approximately 200 participants. On the other hand, other authors24 recommended a participant-item ratio of 10:1, corresponding to 170 for this 17-item questionnaire.

Our study comprised a final sample of 194 patients, with a mean age of 63.34±9.2 years of whom 30 (15%) were women. The primary inclusion criterion was a CVD such as coronary artery disease, valvular disease, or atrial fibrillation. This study employed a convenience sample design; All patients who were referred to CR between February 2020 and December 2021 were invited to participate in the study. Patients were referred to CR a median of 2.5 months (range 0.5-12 months) after the cardiac event or cardiac surgery. All patients completed the TSK-SPA Heart at T1. Seven days after the first visit (T2), the patients returned to CR Unit for the treadmill test to evaluate functional capacity, and a number of patients completed the TSK17 a second time. In total, 127 patients completed also the questionnaire at T2. After that, the CR intervention began.

The exclusion criteria included reluctance to participate, discharge from a hospital, or delayed enrollment in CR beyond a period of 12 months. Within our sample, there were patients who were more than 12 months post-event (N.=2), as well as individuals who exhibited an unwillingness to participate (N.=6).

Written informed consent was signed by all patients who participated. At T1, baseline and socio-demographic data and clinical characteristics were collected. Table I shows a summary of the participant’s baseline characteristics.

Table I —Descriptive and clinical characteristics of the study population (N.=194).

Characteristics	Value	
Age (range 36-86)	63.34±9.2	
<65 years	119±61	
>65 years	75±39	
Sex, women	30 (15%)	
Height, cm	172.48±8.1	
Weight, kg	82.11±13	
BMI, kg/m2	27.56±3.76	
LVEF, non-conserve	36 (19%)	
LVEF, conserve	156 (80%)	
Referral diagnosis		
STEMI	79 (41%)	
Non-STEMI	40 (21%)	
Unstable angina	6 (3%)	
Stable angina	39 (30%)	
Atrial fibrillation	12 (6%)	
Valvular disease	10 (5%)	
Ventricular aneurism	8 (4%)	
Intervention		
PCI	171 (88%)	
CABG	15 (8%)	
Peacemaker	4 (2%)	
Valve procedure	9 (5%)	
Ablation	2 (1%)	
CAD, non-revascularized	2 (1%)	
Comorbidities		
Hypertension	106 (55%)	
Diabetes	40 (21%)	
Ex-smoker	89 (46%)	
Sedentarism	81 (42%)	
Hypercholesterolemia	99 (51%)	
Alcoholism	4 (2%)	
Obesity	32 (16%)	
Family history	86 (44%)	
Other pathologies		
Musculoskeletal disorder	69 (36%)	
Oncological disease	25 (13%)	
Rheumatic disease	8 (4%)	
COPD	3 (2%)	
OSAS	21 (11%)	
COVID	32 (16%)	
Stroke	4 (2%)	
Others		
IPAQ category 1/2/3	29/70/95	
Physical component summery (SF12)	46.28±8.36	
Mental component summery (SF12)	50.55±9.67	
Anxiety (HADS)	6.24±3.7	
Depression (HADS)	4±3.4	
Functional capacity VO2 METS	7.54±1.57	
BMI: Body Mass Index; LVEF: left ventricle ejection fraction; STEMI: ST elevation myocardial infarction; PCI: percutaneous coronary intervention; CABG: coronary artery bypass grafting; CAD: coronary artery disease; COPD: chronic obstructive pulmonary disease; OSAS: obstructive sleep apnea syndrome; COVID: coronavirus disease; IPAQ: International Physical Activity Questionnaire; SF12: Short-Form 12; HADS: Hospital Anxiety and Depression Scale; MET: Metabolic Equivalents.

Instruments

Kinesiophobia

The TSK Heart version consists of 17 items with a 4-point answer scale. The statements are assessed on a Likert-type scale ranging from 1 (“Totally disagree”) to 4 (“Totally agree”), using the total points, each answer is worth and contributes what is marked, except for items 4, 8, 12 and 16, which are reverse coded and adds backwards. Higher values indicate more severe kinesiophobia. The original heart-specific TSK13 consisted of 4 domains: Perceived danger for heart problem, Fear of injury, Avoidance of exercise and Dysfunctional self.

Content validity

The TSK-SPA Heart was analyzed by a judging panel of 8 members to determine the items with the best properties. A psychometric content validity test (Aiken’s V) was employed to quantify the instrument’s analysis and assess the level of agreement. The experts were tasked with assessing each item’s clarity, coherence, and relevance, considering factors such as its understandability, appropriateness to the measured construct, and importance for inclusion.

In the first round, the judging panel made 26 comments, mainly regarding the formulation and interpretability of the items and five suggestions were made to improve the items. After the pretest study with 30 patients, the panel made 38 comments and seven suggestions regarding comprehensibility. After the last round, all the findings were reevaluated, and there were no further comments or suggestions. After a consensus was reached, the final version of the TSK-SPA Heart was developed.

Anxiety and depression

The Spanish version of the Hospital Anxiety and Depression Scale (HADS) comprises seven anxiety and seven depression items, from which separate anxiety and depression scores are calculated25 using a four-point Likert Scale (0-3). For the Spanish version, a score of 0-6 on the anxiety subscale is defined as “no anxiety disorder,” a score of 7-10 is defined as “possible anxiety disorder,” and a score of 11-21 is defined as “anxiety disorder that needs help.” For the depression subscale a score of 0-4 is defined as “no depression disorder,” a score of 5-10 is defined as “possible depression disorder,” and a score of 11-21 is defined as “depression disorder that needs help.” The HADS is a widely used tool to assess anxiety and depression in various patient groups.25

The Spanish version of the Beck Depression Inventory (BDI-II) is a 21-item self-report that assesses the presence and severity of the depressive symptoms listed in the Diagnostic and Statistical Manual of Mental Disorders-IV, which uses a 4-point Likert scale (0-3), with the minimum and maximum scores of 0 and 63. For the Spanish version,26 cut-off points have been established for classification into one of the following four groups: 0-13, minimal depression; 14-19, mild depression; 20-28, moderate depression; and 29-63, severe depression. The BDI-II is a widely recognized and validated tool that has been applied in a variety of settings and populations to assess depressive symptoms and to better understand depression in various groups.27

Physical activity

Physical activity was measured over a 7-day period. The categorical form of the international Physical activity questionnaire – Spanish version (IPAQ)28 was administered, identifying 3 levels of physical activity (1 = low, 2 = medium, 3 = high).

Health-related quality of life

The Spanish version of Short-Form 12 (SF-12 V.2) is a generic questionnaire that measures health-related quality of life across 8 dimensions, divided into two components. The Physical Component Summary (PCS) comprises physical functioning, physical role limitations, bodily pain, and general health perceptions. The Mental Component Summary (MCS) comprises vitality, social functioning, emotional role limitations, and mental health.29, 30

Procedure

Patients were referred by their cardiologist to the rehabilitation program and were included at a median of 2.5 months (range 0.5-10 months) after their hospital discharge. The nurse received them and conducted the clinical interview (T1), collected data from their medical history (age, sex, body mass index, cardiac disease history, cardiac diagnosis, and comorbidities), calculated the scores, gave the patients the informed consent document and asked them if they wanted to participate in our study.

If the patient was interested in participating in our study, an appointment was arranged in seven days with the physiotherapist to complete the TSK-SPA for the second time and perform the treadmill stress test with the cardiologist (T2). We implemented the Bruce protocol which was designed to gradually increase the exercise intensity in predefined intervals. The participant’s functional capacity was assessed by estimating the oxygen consumption estimation.31, 32

In this study, there were no missing values due to lack of participant response. Both the informed consent and the forms were reviewed at the time of submission. If any response was missing, the participant was asked to complete it if there was no inconvenience.

Statistical analysis

Data processing was performed using IBM SPSS software v. 28. The factorial models, CFA, ESEM and structural equation model (SEM), were computed using Mplus 8.10.33 A Parallel analysis was conducted using the O’Connor SPSS syntax (2000).

Factor analyses

Data dimensionality was assessed using Horn’s Parallel Analysis.34, 35 The construct validity of the given TSK scale version was examined through a series of factor models, including ESEM and CFA. A data modeling strategy was employed and endorsed within the framework of assessing construct validity during scale adaptation, as outlined by Martínez-Molina et al.36

The study’s data modeling strategy aimed to evaluate the indicated TSK factors of previous studies (in a confirmatory manner) and then continue with more flexible factorial approaches (in an exploratory manner). Five factorial models were tested: Model 1 (M1) was a CFA to evaluate the original theoretical model (e.g., four correlated factors); Model 2 (M2) was a CFA to evaluate the model but without a second-order factor; Model 3 (M3) proposed an ESEM. Since exploratory models have rarely been performed and are necessary, two other exploratory factor analyses were performed (M4 and M5) with second-order factor.

Range of fit indices were computed to evaluate the proposed model.37 Absolute fit measures included the Chi-Squared Test of Model Fit divided by the degrees of freedom and the Root Mean Square Error of Approximation (RMSEA). Relative fit measures, such as the Comparative Fit Index (CFI) and the Tucker-Lewis Index (TLI), were also calculated.

Due to the data’s ordinal nature, the weighted least squared mean variance (WLSMV) estimator was employed for each model, specifying an oblique rotation. The reliability of each factor was assessed with Cronbach’s alpha and McDonald’s omega coefficients.

Test-retest measurements were analyzed by asking the patients to repeat the questionnaire after a period of at least 7 days. Following an assessment of item-total correlation, test-retest agreement was determined by comparing the initial and retest scores.

Validity evidence based on relations with other variables

To add validity evidence based on the relationship between other variables and the study’s data, the correlations were computed using the Pearson’s correlations. The strength of the correlation was defined as small (0.00-0.29), moderate (0.30-0.49), or strong (0.50-1.00).38

We studied the correlation between the sum score of TSK-SPA Heart and the sum score of its factors (Perceived threat, Fear of harm, Avoidance of physical activity, and Dysfunctional self) and our collected assessments (HADS, BDI, IPAQ, SF12). We also included variables such as age, sex, time elapsed from the occurrence of the cardiac event to the start of rehabilitation, muscle skeletal disorders, left ventricular ejection fraction, and COVID-19 infection and studied their correlation.

A SEM was applied to describe the interrelationships among all the variables and scales in this study. We explored direct effects (the relationships between independent and dependent variables) and indirect effects (representing the influence of an independent variable on a dependent variable via one or more intermediary or mediating variables)39 (Figure 1).

Figure 1 Generic Mediation SEM Model Including Control Variables. N.=194; TSK=TSK Spanish version; TH=Perceived threat; HA=Fear of harm; AV=Avoidance of physical activity; DY=Dysfunctional self; Sex=self-referred sex dummy coded (0=male; 1=female); PCS=Physical component summary of quality of life; MCS=Mental component summary of quality of life; R2MCS=0.29; R2PCS=0.24; R2HA=0.19; R2DY=0.36; R2AV=0.18. Non significance regression weights o correlations are not shown (P>0.05). Although the effect was not significant, for theoretical interest the AV on DY regression is shown in a light gray dotted line. The rest of the sociodemographic and health variables in the study were excluded from the model because they did not present significant effects.

Given the limited knowledge regarding kinesiophobia in patients with CVD, a comprehensive approach was employed to investigate the association between baseline variables (sex, age, and BMI) and the dimensions of the kinesiophobia scale, as well as quality of life. The study examined the association between three demographic variables (age, sex, and BMI), the four psychological dimensions of the Kinesiophobia scale (Perceived threat, Fear of harm, Avoidance of physical activity, and Dysfunctional self), and two psychosocial variables (mental and physical quality of life). The categorical variable (sex) was recoded into dummy variables, whereas all other variables (age, BMI, kinesiophobia, psychological variables) were analyzed as continuous.

The data associated with this study are available at https://osf.io/8t4fp/

Results

Face and content validity

Cross-cultural validation

We determined the content validity of the pre-final version of the TSK-SPA Heart by employing the Aiken V test40 which produces values between 0 and 1. Values <0.70 are considered rejectable and could not be included.41 A qualitative and quantitative evaluation found that all items exceeded on average the cut-off point of 0.7 for clarity, coherence, and relevance, except for 1 item (item 7). Moreover, the review committee inquired about the comprehensiveness of the questionnaire to 30 patients. They concluded that certain items were redundant, and the 4 reverse items (4, 8, 12 and 16) tended to be confusing. However, once the vocabulary suggestions were incorporated, to make the questionnaire more understandable, the committee decided to include the original 17 items to determine how the performance of the original scale in its entirety in the Spanish cardiac population.

Psychometric Properties

Construct validity

A parallel analysis was conducted to determine the data dimensionality, revealing four dimensions for the 13 items of the TSK-SPA Heart questionnaire (Supplementary Digital Material 1: Supplementary Text File 1). Table II displays the factor loadings, correlations, and regressions of the proposed models. The fit indices for each model can be found in Table III.

Table II —Four-factor ESEM models of the TSK 13 items (Spanish version).

Parameters	M5. ESEM	
F1	F2	F3	F4	MF	
Perceived threat						
03. Body indications	-0.71*	-0.02	0.21	-0.06		
11. Heart suspicion	-0.72*	-0.01	-0.09	-0.01		
16. Heart problem - R	0.51*	0.24	0.09	-0.17	0.37*	
Fear of harm						
01. Fear of self-injury	0.42*	0.32*	0.06	0.08		
09. Accidental injury	0.25	0.45*	-0.33	0.14		
10. Preventive movements	-0.09	0.78*	0.26	-0.22		
14. Physical security	-0.17	0.73*	-0.14	0.17		
Avoidance of physical activity						
02. Heart condition	0.28	0.16	0.33*	0.34*		
04. Exercise benefits - R	0.16	0.02	0.70*	0.10	0.37*	
12. Exercise use - R	0.19	0.13	-0.58*	0.05	0.37*	
Dysfunctional self						
05. Incomprehension	0.11	0.32*	0.25	0.42*		
06. Chronicity/physical weakness	0.18	-0.14	0.16	0.73*		
15. Vulnerability/heart risk	0.38*	-0.03	0.11	-0.60*		
Factor correlations						
F1	−					
F2	0.39*	−				
F3	-0.01	0.17	−			
F4	0.26	0.29	0.01	−		
MF	0.00	0.00	0.00	0.00	−	
Population: N.=194 cases. D: theoretical dimension; MF: Method Factor (negative wording); Main loadings in italics; Loadings ≥0.30 in absolute value or P≤0.01(*).

Table III —Fit indices of the estimated models of the TSK.

Structure/model	i	χ2	df	χ2/df	RMSEA	CFI	TLI	
M1. CFA: 2nd KI; 1st (DA, FE, AV, DY) and MF	17	Did not converge	
M2. CFA: DA, FE, AV, DY	17	196.8	113	1.7	0.087	0.857	0.828	
M3. ESEM: DA, FE, AV, DY	17	115.6	113	1.0	0.076	0.929	0.869	
M4. ESEM: DA, FE, AV, DY and MF	17	109.3	114	1.0	0.072	0.938	0.884	
M5. ESEM: TR, HA, AV, DY and MF	13	37.2	31	1.2	0.045	0.984	0.959	
Population: N.=194 cases. i: number of items in the model; df: degrees of freedom; RMSEA: root mean square error of estimation; CFI: Comparative Fit Index; TLI: Tucker-Lewis Index; 2nd: hierarchical second order; 1st: first order; KI: kinesiophobia; DA: danger; FE: fear; AV: avoidance; DY: dysfunction; MF: method factor, orthogonal (wording); TH: perceived threat; HA: fear of harm; AV: avoidance of physical activity; DY: dysfunctional self; In bold, the best model fit.

The first 4-factor CFA model with a method factor for the reverse-coded items (M1) could not be estimated due to convergence issues, given that the proposed structure requires a distribution of variance estimate that could not be replicated within a large number of iterations (i.e., 1000). The inability to estimate this model suggests that M1 is not plausible. The second CFA model (M2) (without a method factor) demonstrated a poor fit to the data (i.e., RMSEA=0.087). M2 exhibited high interfactor correlations, primarily due to CFA restrictions.

Exploratory models M3 and M4 showed a slightly improved fit compared to Model M2, but they still did not meet the recommended criteria (i.e., RMSEA <0.05, CFI and TLI >0.95). Moreover, certain items (i.e., 7, 8, 13, and 17) exhibited primary low loadings in factors that were not theoretically related (<0.50).

Based on these factorial results, we carefully selected only those items that showed primary and adequate loadings on their respective theoretical factors and had content congruent with the theoretical definition of each dimension. As a result, we developed Model M5 (Table III), which excludes the four items with inadequate factor loadings (i.e., 7, 8, 13 and 17). Additionally, based on its factor loading and content, item 01 was assigned to the Fear of Harm factor, as it aligned more closely with that particular dimension. In our proposed model (M5), item 10 represents the dimension of harm most strongly and saturates that factor. In terms of model fit, M5 showed adequate or good fit values (RMSEA=0.045, CFI=0.984, and TLI=0.959). This model aligns with the theoretical framework of dimensions and supports a 4-factor structure (Table IV).

Table IV —Four-factor ESEM and CFA models of the TSK (Spanish version).

D	M2. CFA	M3. ESEM	M4. ESEM	
F1	F2	F3	F4	F1	F2	F3	F4	F1	F2	F3	F4	MF	
Danger														
03. Body indications	0.59*				-0.64*	-0.23	0.25	-0.04	-0.63*	-0.20	0.24	-0.04		
08. Chest discomfort - R	-0.72*				0.26	0.16	0.46*	0.20	0.24	0.19	0.42*	0.24	0.34*	
11. Heart suspicion	0.71*				-0.79*	-0.02	-0.04	-0.05	-0.81*	0.01	-0.06	-0.05		
16. Heart problem - R	-0.58*				0.50*	0.20	0.17	-0.18	0.49*	0.23	0.10	-0.18	0.34*	
Fear														
01. Self-injury		0.70*			0.42*	0.34*	0.15	0.04	0.42*	0.36*	0.13	0.05		
07. Heart-body correlation		-0.15			-0.05	-0.03	0.07	-0.30*	-0.05	-0.01	0.08	-0.30*		
09. Accidental injury		0.47*			0.24	0.59*	-0.27	0.12	0.24	0.54*	-0.27	0.13		
13. Heart self-regulation		0.64*			0.53*	0.14	0.21	-0.05	0.53*	0.17	0.21	-0.05		
Avoidance														
02. Heart condition			0.62*		0.25	0.08	0.43*	0.27	0.26	0.11	0.40*	0.28		
04. Exercise benefits - R			0.40*		0.08	-0.12	0.72*	-0.02	0.04	-0.05	0.68*	-0.01	0.34*	
12. Exercise use - R			0.11		0.23	0.34*	-0.48*	0.05	0.22	0.36*	-0.64*	0.07	0.34*	
14. Physical activity			0.51*		-0.06	0.61*	0.13	0.19	-0.06	0.62*	0.08	0.22		
17. Exercise conflict			0.04		0.13	-0.24	-0.24	0.10	0.14	-0.25	0.13	0.09		
Dysfunction														
05. Lack of consideration				0.71*	0.12	0.21	0.30*	0.38*	0.13	0.22	0.27	0.38*		
06. Physical weakness				0.54*	0.23	-0.07	0.15	0.55*	0.23	-0.07	0.14	0.54*		
10. Preventive movements				0.53*	-0.15	0.57*	0.46*	-0.20	-0.14	0.63*	0.41*	-0.18		
15. Heart risk				-0.08	0.34*	-0.01	0.07	-0.78*	0.33*	0.05	0.08	-0.80*		
Factor correlations														
F1	−				−				−					
F2	-0.94	−			0.28	−			0.29	−				
F3	-0.97	0.93	−		0.24	0.27	−		0.21	0.26	−			
F4	-0.61	0.71	10.07	−	0.17	0.21	0.15	−	0.19	0.23	0.15	−		
MF									0.00	0.00	0.00	0.00	−	
Population: N.=194 cases. D: theoretical dimension; MF: Method Factor (negative wording); Main loadings in italics; Loadings ≥0.30 in absolute value or P≤0.01(*). Items 8, 7, 13 and 17 in small caps that do not load, or whose main load is not in the corresponding theoretical factor.

The final version of the TSK Spanish scale contains three cognition-oriented constructs and 1 behavior-oriented construct. The first factor, which is related to the ability of interoception, is Perceived threat (TH), i.e., when patients listen to their body’s signals or when they interpret symptoms or sensations from their own body. TH corresponds to items 3 (body indications), 11 (heart suspicion) and 16 (heart problem) and are all related to body sensations.

The second factor, which is related with physical trauma, is Fear of harm (HA), referring to not wanting to hurt oneself. HA corresponds to items 1 (self-injury), 9 (accidental injury), 10 (preventive movements) and 14 (physical security). For example, item 10 in our model is loading on HA (factor 2), and not in Dysfunctional self (factor 4). This dimension which maintains 4 items, has the best reliability of all factors.

The third factor, which is related to caution, is Avoidance of physical activity (AV), referring to being cautious, and avoiding commitments. AV has a precautionary negative connotation and corresponds to items 2 (heart condition), 4 (exercise benefits) and 12 (exercise use).

The fourth factor, which is related to not being autonomous, neither independent, nor functional, is Dysfunctional self (DY), referring to a reduced feeling of worth and a chronic condition. DY corresponds to items 5 (lack of consideration or incomprehension), 6 (physical weakness or chronicity) and 15 (heart risk or vulnerability).

Construct validity related to external measures

The dependent variables shown in Supplementary Digital Material 2 (Supplementary Table I) with the four constructs of the TSK-SPA Heart are related to the changes in the explained variance. Certain specific bivariate patterns in the results are discussed below.

The higher the patients’ kinesiophobia, the lower the physical activity (r=-0.17), and the lower quality of life (r=-0.36, -0.39) and the higher the anxiety (r=0.45) and depression (r=0.47).

In our study, the women exhibited higher anxiety levels (as indicated by HADA [r=0.24]). increased depression (based on the BDI score [r=0.25]) and lower mental quality of life (according to SF12 [r=-0.23]) and were slightly more affected by the passage of time before the start of rehabilitation (r=0.20).

The PCS of the SF12 was influenced by the HA and DY factors. The MCS of the SF12 influenced the three cognition-oriented constructs.

The TH factor moderately correlated with the anxiety section of HAD (r=0.37). The HA correlated moderately to strongly with the anxiety section of HAD (r=0.41). The DY correlated moderately to strongly with the depression section of HAD (r=0.41), and negatively with the MCS (r=-0.40).

The TSK total score exhibited moderate to strong correlations with anxiety and depression scores (r=0.45 and r=0.46, respectively).

The distribution of the data for the TSK scale exhibited low skewness and kurtosis (-0.01 and -0.16), indicating a distribution close to normal. Consequently, we can discard the possibility of any ceiling or floor effects in his study.

Finally, a SEM analysis was performed to jointly describe the most relevant relationships of the TSK factors as mediators of quality of life. A Generic Mediation SEM Model included certain control variables (i.e., sex, age, and BMI). The model showed a perfect fit (RMSEA = 0.000, CFI = 1.000, TLI = 1.000) explaining the outcome quality of life variables in a 29% and 24% for MCS and PCS, respectively.

We observed slight effects of sex (β=-0.26) and age (β=0.14) on MCS. On the other hand, there were negative correlations with the PCS, BMI (β=-0.21), and being female (β=-0.20).

Among the four dimensions of the questionnaire, only one showed a correlation with enhanced quality of life. We observed moderate associations between DY and both the MCS (β=-0.36) and PCS (β=-0.21).

TH was connected to DY (β=0.35); HA was linked to AV (β=0.32); and there was a correlation between TH and HA (β=0.42).

Reliability

As shown in Supplementary Table I, the 13 item TSK-SPA Heart presented a general acceptable internal consistency (α=0.79, ω=0.78). The TSK-SPA Heart was stable over time, evaluated with a 7-day test-retest of the total score (r=0.82). However, the reliabilities of the factors were not adequate (ω ranged from 0.50 to 0.72).

Discussion

One of this study’s aims was to examine the validity of the TSK-SPA Heart by exploratory factor analysis, internal correlation coefficient and convergent validity based on the data gathered in the same study on physical activity, quality of life, anxiety, and depression. The results of this study provide evidence of validity for the TSK-SPA Heart questionnaire in the context of Spanish patients with CVD.

The reliability of the test with non-homogenous subsets was acceptable (r>0.70). The Cronbach’s alpha for the overall scale is also agreed with prior studies regarding the pain scale42, 43 and cardiac scale.13-15, 17

In our study, the reliability of each domain was low, rarely reaching .70, an issue that could have occurred in the original study.13 Bäck et al. achieved a Cronbach’s alpha value of 0.79 for the entire scale, but the reliability of the four dimensions was not reported.

We recommend reporting individual reliability of each factor because it contributes with relevant information.

It is important to analyze why factors result in low reliability. In this case, TSK Heart had a number of items that were certainly confusing. Several items had collinearity (i.e., they correlated with other items that expressed the same issue).

Normally, for items to score highly they have to be very clear and concise. Given that there are dimensions that have fewer than four items, it is understandable that low reliability can result.

Although the individual items showed only “fair” to “moderate” test-retest reliability, the total score of the TSK-SPA Heart in this study is substantial, indicating that the questionnaire is a reliable instrument and that kinesiophobia was stable over the chosen period of 1 week. Nonetheless, the scores on the individual items should be interpreted with caution. In this case, it would be advisable to either improve existing or dropped items, improve their comprehension and wording, or add more items.

Regardless, this result is consistent with the previously reported test-retest reliability of the TSK in patients with chronic pain,42, 43 and in relation to the cardiac scale.13-15, 17

According to the content validity, the review committee found certain items to be too similar.

Despite this, all of the original items were included in the CFA model for gaining knowledge of kinesiophobia.

This questionnaire is an adaptation of another scale that was created to measure fear of movement due to pain. We can therefore add to our recommendation to revise items to improve reliability, the recommendation to revise items to be more precise in the content adapted to the context of patients with CVD, who present different aspects from those of patients with chronic pain, e.g., a more hypochondriac behavior. A possible line of research may involve employing less technical and more colloquial expressions within the content of the items.

The exploratory factor structure of the TSK-SPA Heart in this study had an acceptable model fit, although certain items (i.e., 7, 8, 13, and 17) did not contribute significantly, with insufficient factor loadings in various models, and were not theoretically related enough.

Bäck13 also found certain items with some difficulties, while other authors later suggested removing items to achieve a good statistical fit.

As suggested by Bäck, we further examined why these items did not function as intended. Although it is not unusual to force the model by removing items, we believe is more advisable, to create or reformulate the items to return the needed information, so as to better understand or explain the sentences; however, items should not be removed just to make the model fit better.

In terms of the clinical implications, the constructs related to beliefs and mental imaginations, such as Perceived threat and Fear of harm, were more closely associated with anxiety than with depression, an observation that supports the notion that dysfunctional beliefs about illness played a role in the cognitive processes of health anxiety.4, 44

The negative correlation between Avoidance of physical activity and physical activity levels was considered reasonable.

The dimension Dysfunctional self was more correlated to depression than to anxiety. Among these four dimensions, Dysfunctional self emerged as the most influential in explaining quality of life. Additionally, Dysfunctional self was influenced by the two other concepts, Perceived threat and Fear of harm. Although there was no direct relationship between the four dimensions and quality of life, there was an indirect correlation involving at least two dimensions (Threat and Harm).

Applying the theoretical framework of the Fear-Avoidance Model by Vlaeyen45 and extrapolating the Fear-Avoidance Model from the patient with chronic pain to the patient with CVD, we can observe that fear and avoidance are human behaviors that occur in both types of patients.

In particular, the effects on participation and quality of life have been extensively studied, and there is a large body of literature describing this type of behavior in patients with chronic pain.12 We sought to provide more features on the behaviors of patients with CVD and describe the impact on their quality of life.

The diversity among patients, particularly the distinction between patients with CVD and those with chronic pain, is acknowledged. Patients with CVD may experience conditions like panic disorder, multiple phobias, and hypochondriasis46 and can be apprehensive or fearful of death, leading to chronic disability and a need for constant medical attention.47

The theoretical distinction between phobia and fear is highlighted, with a specific phobia diagnosed when there is an intense, persistent fear of a specific object or situation leading to avoidance or endurance with significant anxiety or discomfort.48 Fear is described by the Royal Spanish Academy as distress related to a real or imagined risk or harm.

There is a need to deepen the theoretical and philosophical understanding of the 4-concept model proposed by Bäck for detecting the perceptions and consequences of kinesiophobia.

Limitations of the study

Our study included patients who were already referred to CR. Studies have indicated that only 39% of eligible patients actually engage in CR.49 The presence of kinesiophobia might contribute to patients declining participation in CR.20 This potential selection bias might have led to a sample characterized by comparatively low levels of kinesiophobia.

Our study shows a 4-factor model to be the most adequate for the TSK-SPA Heart. This Spanish version of the TSK Heart excludes 4 questions due to low inter-item correlations. It is important to explore whether the need for improving construct validity could be addressed by modifying the wording of these items rather than eliminating them.

Finally, it is crucial to continue the development of this scale, reinforcing it with diagnostic validity evidence, such as logistic regression analysis paired with a ROC curve to demonstrate its discriminative capacity between different patient types.

Conclusions

This study describes the methods of cultural adaptation, factor analyses, and convergent validity analysis of the Spanish version of the TSK Heart, resulting in a four-factor, 13-item solution. The proposed model showed a good fit to the data, and the reliability of the scale was acceptable. However, there is room for improvement in the reliability of each individual factor. Further cultural adaptation could offer a continuation of this research. Efforts should be made to further adapt the scale to the patients with CVD and to improve the wording and readability of the items. Thus, the kinesiophobia of patients with CVD can be assessed using this shortened scale.

Supplementary Digital Material 1

Supplementary Text File 1

Tampa Scale for Kinesiophobia Heart Spanish Version 13 items

Supplementary Digital Material 2

Supplementary Table I

Basic descriptives, Pearson correlations, and reliability indices.

Acknowledgements

Authors would like to thank cardiologist Jose María Maroto, PhD, from the Instituto de Rehabilitación Funcional La Salle, for their help with data collection; and psychologists Nacho Montero, PhD, and Ana Calero, PhD, from the Universidad Autónoma de Madrid, for participating at the factor’s theoretical discussion.

Conflicts of interest: The authors certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

Funding: This study was supported by a grant (SPISAL034) from the Centro Superior de Estudios Universitarios La Salle, adscrito a la Universidad Autónoma de Madrid.
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References

1 Menezes AR Lavie CJ Milani RV O’Keefe J Lavie TJ . Psychological risk factors and cardiovascular disease: is it all in your head? Postgrad Med 2011;123 :165–76. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=21904099&dopt=Abstract 10.3810/pgm.2011.09.2472 21904099
2 Tyrer P. Recent Advances in the Understanding and Treatment of Health Anxiety. Curr Psychiatry Rep 2018;20 :49. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=29931576&dopt=Abstract 10.1007/s11920-018-0912-0 29931576
3 Tyrer P Salkovskis P Tyrer H Wang D Crawford MJ Dupont S Cognitive-behaviour therapy for health anxiety in medical patients (CHAMP): a randomised controlled trial with outcomes to 5 years. Health Technol Assess 2017;21 :1–58. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=28877841&dopt=Abstract 10.3310/hta21500
4 Norris A Marcus D. Cognition in Health Anxiety and Hypochondriasis: recent Advances. Curr Psychiatry Rev 2014;10 :44–9. 10.2174/1573400509666131119004151
5 Doherty-Torstrick ER Walton KE Barsky AJ Fallon BA . Avoidance in hypochondriasis. J Psychosom Res 2016;89 :46–52. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=27663110&dopt=Abstract 10.1016/j.jpsychores.2016.07.010 27663110
6 Olatunji BO Kauffman BY Meltzer S Davis ML Smits JA Powers MB . Cognitive-behavioral therapy for hypochondriasis/health anxiety: a meta-analysis of treatment outcome and moderators. Behav Res Ther 2014;58 :65–74. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=24954212&dopt=Abstract 10.1016/j.brat.2014.05.002 24954212
7 Kubzansky LD Park N Peterson C Vokonas P Sparrow D . Healthy psychological functioning and incident coronary heart disease: the importance of self-regulation. Arch Gen Psychiatry 2011;68 :400–8. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=21464364&dopt=Abstract 10.1001/archgenpsychiatry.2011.23 21464364
8 Lundberg M Grimby-Ekman A Verbunt J Simmonds MJ . Pain-related fear: a critical review of the related measures. Pain Res Treat 2011;2011 :494196. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=22191022&dopt=Abstract 10.1155/2011/494196 22191022
9 Kori SH Miller RP Todd DD . Kinesiophobia: A new view of chronic pain behavior. Pain Manag 1990;3 :35–43.
10 Vlaeyen JW Kole-Snijders AM Rotteveel AM Ruesink R Heuts PH . The role of fear of movement/(re)injury in pain disability. J Occup Rehabil 1995;5 :235–52. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=24234727&dopt=Abstract 10.1007/BF02109988 24234727
11 Philips HC . Avoidance behaviour and its role in sustaining chronic pain. Behav Res Ther 1987;25 :273–9. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=3662989&dopt=Abstract 10.1016/0005-7967(87)90005-2 3662989
12 Vlaeyen JW Linton SJ . Fear-avoidance model of chronic musculoskeletal pain: 12 years on. Pain 2012;153 :1144–7. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=22321917&dopt=Abstract 10.1016/j.pain.2011.12.009 22321917
13 Bäck M Jansson B Cider A Herlitz J Lundberg M . Validation of a questionnaire to detect kinesiophobia (fear of movement) in patients with coronary artery disease. J Rehabil Med 2012;44 :363–9. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=22366980&dopt=Abstract 10.2340/16501977-0942 22366980
14 Acar S Savci S Keskinoğlu P Akdeniz B Özpelit E Özcan Kahraman B Tampa Scale of Kinesiophobia for Heart Turkish Version Study: cross-cultural adaptation, exploratory factor analysis, and reliability. J Pain Res 2016;9 :445–51. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=27382331&dopt=Abstract 10.2147/JPR.S105766 27382331
15 Keessen P den Uijl I Visser B van den Berg-Emons H Latour C Sunamura M Fear of movement in patients attending cardiac rehabilitation: A validation study. J Rehabil Med 2020;52 :1–7. 10.2340/16501977-2653
16 Ghisi GL de M . Validation of the portuguese version of the tampa scale for kinesiophobia heart (TSK-SV heart). Rev Bras Med Esporte 2017;23 :227–31. 10.1590/1517-869220172303159416
17 Knapik A Dąbek J Gallert-Kopyto W Plinta R Brzęk A. Psychometric Features of the Polish Version of TSK Heart in Elderly Patients with Coronary Artery Disease. Medicina (Kaunas) 2020;56 :467. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=32933100&dopt=Abstract 10.3390/medicina56090467 32933100
18 Bascour-Sandoval C Albayay J Martínez-Molina A Opazo-Sepúlveda A Lacoste-Abarzúa C Bielefeldt-Astudillo D Psychometric Properties of the PCS and the PCS-4 in Individuals With Musculoskeletal Pain. Psicothema 2022;34 :323–31. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=35485547&dopt=Abstract 35485547
19 Widaman KF. Common factors versus components: Principals and principles, errors and misconceptions. In: Factor Analysis at 100: Historical Developments and Future Directions. Lawrence Erlbaum Associates Publishers; 2007. p. 177-203.
20 Bäck M Cider Å Herlitz J Lundberg M Jansson B. Kinesiophobia mediates the influences on attendance at exercise-based cardiac rehabilitation in patients with coronary artery disease. Physiother Theory Pract 2016;32 :571–80. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=27726471&dopt=Abstract 10.1080/09593985.2016.1229828 27726471
21 Bäck M Lundberg M Cider Å Herlitz J Jansson B. Relevance of Kinesiophobia in Relation to Changes Over Time Among Patients After an Acute Coronary Artery Disease Event. J Cardiopulm Rehabil Prev 2018;38 :224–30. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=28671936&dopt=Abstract 10.1097/HCR.0000000000000265 28671936
22 International Test Commission. International Guidelines on Computer-Based and Internet Delivered Testing; 2005 [Internet]. Available from: www.intestcom.org [cited 2024, May 10].
23 Muñiz J Elosua P Hambleton RK International Test Commission. Directrices para la traducción y adaptación de los tests: segunda edición. Psicothema 2013;25 :151–7. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=23628527&dopt=Abstract 23628527
24 Kline RB. Principles and Practice of Structural Equation Modeling. Fifth Edition. Guilford Press; 2016.
25 Herrero MJ Blanch J Peri JM De Pablo J Pintor L Bulbena A . A validation study of the hospital anxiety and depression scale (HADS) in a Spanish population. Gen Hosp Psychiatry 2003;25 :277–83. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12850660&dopt=Abstract 10.1016/S0163-8343(03)00043-4 12850660
26 Sanz J Perdigón AL Vázquez C . Adaptación española del Inventario para la Depresión de Beck-II (BDI-II): 2. Propiedades psicométricas en población general. Clin Salud 2003;14 :249–80.
27 Arevalo JJ Soto KA Caamaño B . Depression in acute coronary syndromes: Application of the Beck Depression Inventory. Rev Colomb Psiquiatr 2014;43 :2–6. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=26573250&dopt=Abstract 10.1016/S0034-7450(14)70036-8 26573250
28 Craig CL Marshall AL Sjöström M Bauman AE Booth ML Ainsworth BE International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35 :1381–95. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12900694&dopt=Abstract 10.1249/01.MSS.0000078924.61453.FB 12900694
29 Vilagut G Valderas JM Ferrer M Garin O López-García E Alonso J . Interpretación de los cuestionarios de salud SF-36 y SF-12 en España: componentes físico y mental. Med Clin (Barc) 2008;130 :726–35. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=18570798&dopt=Abstract 10.1157/13121076 18570798
30 Gandek B Ware JE Aaronson NK Apolone G Bjorner JB Brazier JE Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998;51 :1171–8. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9817135&dopt=Abstract 10.1016/S0895-4356(98)00109-7 9817135
31 Bruce RA . Exercise testing of patients with coronary heart disease. Principles and normal standards for evaluation. Ann Clin Res 1971;3 :323–32. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=5156892&dopt=Abstract 5156892
32 Bruce RA Kusumi F Hosmer D . Maximal oxygen intake and nomographic assessment of functional aerobic impairment in cardiovascular disease. Am Heart J 1973;85 :546–62. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=4632004&dopt=Abstract 10.1016/0002-8703(73)90502-4 4632004
33 Muthén LK, Muthén BO. Mplus User’s Guide; 2017 [Internet]. Available from: https://www.statmodel.com/download/usersguide/MplusUserGuideVer_8.pdf [cited 2024, May 10].
34 Horn JL . A rationale and test for the number of factors in factor analysis. Psychometrika 1965;30 :179–85. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=14306381&dopt=Abstract 10.1007/BF02289447 14306381
35 Garrido LE Abad FJ Ponsoda V . A new look at Horn’s parallel analysis with ordinal variables. Psychol Methods 2013;18 :454–74. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=23046000&dopt=Abstract 10.1037/a0030005 23046000
36 Martínez-Molina A Arias VB . Balanced and positively worded personality short-forms: Mini-IPIP validity and cross-cultural invariance. PeerJ 2018;6 :e5542. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=30225170&dopt=Abstract 10.7717/peerj.5542 30225170
37 Schreiber JB . Update to core reporting practices in structural equation modeling. Res Social Adm Pharm 2017;13 :634–43. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=27567146&dopt=Abstract 10.1016/j.sapharm.2016.06.006 27567146
38 Haynes SN, Smith GT, Hunsley JD. Scientific Foundations of Clinical Assessment. Routledge; 2018.
39 MacCallum RC Austin JT . Applications of structural equation modeling in psychological research. Annu Rev Psychol 2000;51 :201–26. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10751970&dopt=Abstract 10.1146/annurev.psych.51.1.201 10751970
40 Aiken LR . Three Coefficients for Analyzing the Reliability and Validity of Ratings. Educ Psychol Meas 1985;45 :131–42. 10.1177/0013164485451012
41 Penfield RD Giacobbi PR Jr . Applying a Score Confidence Interval to Aiken’s Item Content-Relevance Index. Meas Phys Educ Exerc Sci 2004;8 :213–25. 10.1207/s15327841mpee0804_3
42 Lundberg MK Styf J Carlsson SG . A psychometric evaluation of the Tampa Scale for Kinesiophobia — from a physiotherapeutic perspective. Physiother Theory Pract 2004;20 :121–33. 10.1080/09593980490453002
43 Swinkels-Meewisse IE Roelofs J Verbeek AL Oostendorp RA Vlaeyen JW . Fear of movement/(re)injury, disability and participation in acute low back pain. Pain 2003;105 :371–9. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=14499456&dopt=Abstract 10.1016/S0304-3959(03)00255-0 14499456
44 Melli G Carraresi C Poli A Bailey R . The role of metacognitive beliefs in health anxiety. Pers Individ Dif 2016;89 :80–5. 10.1016/j.paid.2015.10.006
45 Vlaeyen JW Kole-Snijders AM Boeren RG van Eek H . Fear of movement/(re)injury in chronic low back pain and its relation to behavioral performance. Pain 1995;62 :363–72. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8657437&dopt=Abstract 10.1016/0304-3959(94)00279-N 8657437
46 Lee JG Choi JH Kim SY Kim KS Joo SJ . Psychiatric Characteristics of the Cardiac Outpatients with Chest Pain. Korean Circ J 2016;46 :169–78. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=27014347&dopt=Abstract 10.4070/kcj.2016.46.2.169 27014347
47 Shekelle RB Vernon SW Ostfeld AM . Personality and coronary heart disease. Psychosom Med 1991;53 :176–84. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2031071&dopt=Abstract 10.1097/00006842-199103000-00007 2031071
48 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Fifth Edition. American Psychiatric Association; 2022.
49 Sunamura M Ter Hoeve N Geleijnse ML Steenaard RV van den Berg-Emons HJ Boersma H Cardiac rehabilitation in patients who underwent primary percutaneous coronary intervention for acute myocardial infarction: determinants of programme participation and completion. Neth Heart J 2017;25 :618–28. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=28917025&dopt=Abstract 10.1007/s12471-017-1039-3 28917025
