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. Author manuscript; available in PMC: 2026 Apr 10.
Published in final edited form as: Med Sci Sports Exerc. 2025 Jan 9;57(6):1246–1256. doi: 10.1249/MSS.0000000000003642

Validity and Reliability of the Tampa Scale for Kinesiophobia for Adolescents with Heart Disease

DAVID A WHITE 1,2, WILLIAM R BLACK 3, EMILY CRAMER 2,4, LINDSEY MALLOY-WALTON 1,2, MOLLIE WALTON 1, LAURA MARTIS 1, BRANDY ENNEKING 1, KELLI M TESON 1,2, JESSICA S WATSON 1, JAMI GROSS-TOALSON 2,5
PMCID: PMC13063351  NIHMSID: NIHMS2078154  PMID: 39780347

Abstract

WHITE, D. A., W. R. BLACK, E. CRAMER, L. MALLOY-WALTON, M. WALTON, L. MARTIS, B. ENNEKING, K. M. TESON, J. S. WATSON, and J. GROSS-TOALSON. Validity and Reliability of the Tampa Scale for Kinesiophobia for Adolescents with Heart Disease. Med. Sci. Sports Exerc., Vol. 57, No. 6, pp. 1246–1256, 2025. Kinesiophobia (KP) is the fear of movement or physical activity (PA) that is related to a medical condition. In adolescents, KP is associated with depression, anxiety, and impaired quality of life (QoL). Adolescents with heart disease (HD) often avoid PA. Factors that may moderate PA avoidance, such as KP, have not been adequately studied in this population.

Purpose:

To assess the validity and reliability of a newly adapted Tampa Scale for KP for adolescents with HD (TSK-Heart-A).

Methods:

The TSK-Heart-A survey consists of 17 Likert scale items, producing a summary score (SS) ranging from 17 (low KP) to 68 (high KP). Following content and face validity, adolescents (age 12–18 yr) with arrhythmia disorders or Fontan palliation were recruited. The PROMIS pediatric anxiety and depression short forms, Pediatric Quality of Life Inventory (PedsQL) generic core and cardiac module, and a PA questionnaire for adolescents (PAQ-A) were used for criterion validity. The TSK-Heart-A was completed twice (20.4 ± 6.3 days apart) for assessment of internal and test–retest reliability. Pearson correlations and Cronbach’s alpha determined validity and reliability, respectively.

Results:

Adolescents (n = 63) were 15.5 ± 1.8 yrs old, 50.8% were female, and 69.8% had arrhythmia disorder. Mean TSK-Heart-A SS was 33.8 ± 7.8 (range, 20 to 56). The TSK-Heart-A SS correlated significantly with PROMIS T-scores (anxiety: 49.7 ± 12.2, r = 0.48; depression: 46.9 ± 12.7, r = 0.41), PedsQL score (generic QoL: 75.2 ± 18.9, r = −0.61; cardiac QoL: 74.7 ± 17.5, r = −0.56), and PAQ-A (score: 2.0 ± 0.7, r = −0.35). Test–retest and internal reliability had a total score of r = 0.77 (P = 0.89).

Conclusions:

The new TSK-Heart-A survey is valid and reliable and suggests that KP is present in some adolescents with HD.

Keywords: ARRHYTHMIA, FEAR, FONTAN, MENTAL HEALTH, PEDIATRIC, PHYSICAL ACTIVITY

Children and adolescents with congenital and other types of heart disease (HD) accumulate about half of the moderate-to-vigorous intensity physical activity (PA) as age- and sex-matched peers (1). Longitudinal studies suggest that reduced participation in PA in adolescence is a key contributor to increased risk of adopting a physically inactive lifestyle and developing cardiometabolic disease in adulthood (2–9). Likely exacerbated by physical inactivity in childhood/adolescence, adults with HD have a greater risk of developing cardiometabolic diseases such as type 2 diabetes, hypertension, and obesity compared with the general population (10–12). In addition, evidence suggests that there is a relationship between physical inactivity and adolescent mental and psychosocial health including elevations in anxiety and depression, and reduced self-esteem and quality of life (QoL) (13–15). Youth with HD often present with elevated rates of anxiety, depressive symptoms, and reduced QoL related to their lifelong cardiac diagnosis (16–19), which may be additive to the negative effects of a sedentary lifestyle on mental health and QoL (14,20).

Youth with HD are often instructed by medical providers to self-monitor for physical feelings and sensations that are associated with PA and exertion (e.g., feeling fast heart rates, chest and breathing discomfort, and fatigue) and seek medical attention if these symptoms arise (21). Thus, many adolescents with HD become hypervigilant to these physical sensations and often restrict themselves from participating in even moderate intensity PA due to fear of triggering a cardiac arrhythmia or “damaging their heart” (21,22). It is common for heart-focused anxiety to be reinforced by over-protective behaviors and overrestriction of PA by parents and family members, teachers, and coaches (19,21,23–28). In these cases, some adolescents may learn, via direct teaching and implicit learning, that PA is dangerous to their health, leading to elevated levels of anxiety, fear-avoidance behaviors, and disengagement from PA resulting in the adoption of an inactive and sedentary lifestyle.

In the chronic pain literature, the fear-avoidance model describes how individuals may respond to a threatening stimulus; develop heightened awareness of potentially threatening stimuli, interact with activities that cause anxiety, fear, and discomfort; and disengage from those activities perceived as being threatening (29–31). Kori (32) applied the fear-avoidance model to PA and termed it “kinesiophobia” (KP), defining it as an excessive, irrational, and debilitating fear of physical movement and activity resulting from a feeling of vulnerability to painful injury or reinjury. The most commonly used tool to measure KP is the Tampa Scale for KP (TSK), a 17-item questionnaire where patients rate their perceptions of fear, safety, and injury related to PA participation and their chronic pain (33). Bäck and colleagues (34) developed and validated a modified version of the TSK for older adults with coronary artery disease (TSK-Heart) where the survey items focus on the participant’s “heart problems” rather than feelings of pain. The authors found the TSK-Heart showed adequate construct validity against self-report measures of PA, anxiety and depression, and health-related QoL, and observed that elevated KP was associated with higher anxiety and depression, and lower fitness, PA, and cardiac rehabilitation attendance (34,35).

Although many adolescents with HD exhibit fear-avoidance behaviors related to PA, there have been no studies of KP or fear related to PA in youth with HD. Although the TSK and TSK-Heart are established tools for measuring KP, both were designed and validated for adult populations, and the original TSK survey items focus specifically on the influence of pain and injury on KP (33,34). As such, no validated or reliable tools exist to assess KP in children and adolescents with HD. The purpose of this study was to develop and determine the validity and reliability of a modified version of the TSK for adolescents with HD (TSK-Heart-A). We hypothesize that the TSK-Heart-A will demonstrate criterion validity using established measures of mental health, QoL, and PA, and both internal and test–retest reliability.

METHODS

The TSK-Heart-A was developed and tested across four sequential study phases: Phase I consisted of an initial modification of the adult TSK-Heart for our target population of adolescents with cardiac disease, Phase II established content validity of the modified questionnaire via content expert review, Phase III assessed the face validity via adolescent patient experts, and Phase IV assessed the reliability and validity of the TSK-Heart-A in a sample of adolescents with HD.

The study was approved by the Children’s Mercy Kansas City IRB. Content area experts provided consent to participate in the study. Adolescents and their parents or legally authorized representatives (LAR) provided assent and consent to participate in the study, respectively. All study procedures were in accordance with the Children’s Mercy Kansas City institutional research guidelines and the ethical standards of the 1964 Helsinki Declaration and its later amendments.

Phase I—Initial Translation of the TSK to the TSK-Heart-A

The original TSK is composed of 17 items where participants rate their agreement to the questions or statements presented on a Likert scale (score of 1—strongly disagree; score of 4—strongly agree) (33). As noted previously, the original TSK items are pain-focused, specifically connecting the relationship between pain and PA (e.g., “Pain lets me know when to stop exercising so that I don’t injure myself” and “I wouldn’t have this much pain if there weren’t something potentially dangerous going on in my body”) (33). The development of the initial TSK-Heart-A was performed using 1) the 17-item TSK (32), 2) the TSK-Heart developed by Bäck et al. (34) to understand how to integrate a heart/cardiac focus rather than a pain focus, and 3) verbiage/wording modifications to improve readability for youth.

Development of TSK-Heart-A version 1 was performed on an item-by-item basis by study team members (D. A. W., W. R. B., E. C., J. G. T.). Version 1 of the TSK-Heart-A consisted of 17 items with a total score ranging from 17 (low KP) to 68 (high KP). The four overarching constructs and survey items representing those constructs, described by Bäck et al. for the TSK-Heart, were retained and are as follows: fear of injury (items: 1, 7, 9, 13), avoidance of exercise (items: 2, 4, 12, 14, 17), perceived danger for heart problems (items: 3, 8, 11, 16), and dysfunctional self (items: 5, 6, 10, 15) (34).

Phase II—Content Validity

Version 1 of the TSK-Heart-A was provided to content experts for their review. Content area experts were professionals or academic researchers with expertise in the KP construct and TSK questionnaire or psychologists, cardiologists, or nurses with current advanced practice specialization in pediatric HD. Content area experts were identified through authorship in peer-reviewed journals, presentations at professional meetings, and professional organizations and were contacted via email. Following content validity recommendations, a target recruitment of at least five experts was set (36). None of the content area experts were from the same institution. Exclusion criteria included non-English speaking or professional conflict of interest. Content area experts were asked to review the TSK-Heart-A and rate the following for each of the 17 items: 1) whether the item is favorable to the measurement of KP (favorable, unfavorable), 2) if they believe the item matches/represents construct (yes, no), 3) if they believe reading level is appropriate for ages 12–18 yr (yes, no), and 4) if they had any additional comments related to the item that they wish to communicate to the investigators (free text). All measures were administered using REDCap (37). An informal interview (via phone or virtual meeting) was conducted with content area experts and a study team member (J. G. T.) where participants had the opportunity to expand upon their free-text comments, provide further review of scale items, and discuss any missing or unclear content. The content validity procedures informed modifications of version 1, producing version 2 of the TSK-Heart-A.

Adolescent Participants (Phase III and Phase IV)

For both Phase III (face validity) and Phase IV (criterion validity and reliability), adolescents with HD were recruited from pediatric cardiology clinics at a mid-western tertiary care children’s hospital (Children’s Mercy Kansas City). Participants were recruited with equal allocation by sex. Inclusion criteria included the following: 1) adolescents between the ages of 12 and 18 yr, and 2) diagnosed with one of several HD conditions: catecholaminergic polymorphic ventricular tachycardia, arrhythmogenic right ventricular cardiomyopathy, Wolff–Parkinson–White syndrome, Brugada syndrome, long-QT syndrome, complex supraventricular tachycardia, single ventricle physiology (Fontan), cardiomyopathy, ventricular tachycardia, or idiopathic sudden cardiac arrest. To test and validate the TSK-Heart-A, a wide distribution of responses (from low fear to high fear) was required. Based on the study team’s clinical experience, patients with these diagnoses often present with notable PA fear-avoidance behaviors and have an elevated risk (real or perceived) of adverse events associated with PA; thus, these diagnoses were targeted for inclusion.

Exclusion criteria included the following: non-English speaking, intellectual or developmental disability where they are unable to independently complete surveys, cardiac surgery or procedure within the past 1 month, curative cardiac electrophysiology procedure, or lacking a parent or LAR to provide consent. Additional exclusion criteria for Phase IV included inability to complete digital (REDCap) surveys outside of the hospital and participation in Phase III.

Phase III—Face Validity

Adolescents (n = 6) with HD participated in a 20- to 30-min in-person or virtual semistructured interview with study team members (J. G. T., W. R. B.), within1 month of their most recent cardiology clinic appointment. At this study visit, participants were presented with version 2 of the TSK-Heart-A. Participants were instructed to read and respond to each item of the survey in the presence of the study team member and provide feedback about the items in real time. Participants were prompted to tell the study team member what they thought the item was asking them and if they thought the item was confusing or easy to understand. Participants were able to ask the study team member for clarification on any item and were encouraged to provide feedback on any wording changes/modifications. Participant suggestions were recorded by study personnel. An option for a second adolescent face validity cohort (n = 6) was available if feedback from the first cohort did not establish saturation. All item-specific comments/suggestions were reviewed and discussed by the study team and version 3 of the TSK-Heart-A was finalized.

Phase IV—Criterion Validity and Reliability

Criterion validity and reliability of version 3 of the TSK-Heart-A was determined by asking adolescent participants to complete surveys at two timepoints: 1) initial assessment and 2) follow-up assessment. Surveys at both timepoints were administered electronically using REDCap (37). The initial assessment was performed either in-person during the participant’s clinic visit on a secured study-specific tablet computer or in-home via a link or QR code sent to the participant through an email. All follow-up assessments were performed in-home via a participant specific emailed link. Although adolescent participants were encouraged to complete the assessments on their own without influence by their parents/LAR, they were permitted to ask their parent/LAR if they needed help navigating the survey instruments. Completion of all survey items took approximately 20–30 min.

Criterion validity was determined using established measures collected at the initial assessment. The following constructs were chosen for criterion validity due to their evidence-based associations with the KP conceptual model such as mental health (anxiety and depression) (34,35,38–42), QoL (generic and disease specific) (34,35,39,40,43–45), and PA (34,35,46). Initial assessment measures included the following (in order of how they were presented to participants):

  • KP was assessed using the TSK-Heart-A (version 3).

  • Mental Health was assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS), Emotional Distress Pediatric Depressive Symptoms v2.0 (PROMIS-Dep), Short Form 8a, and Emotional Distress Pediatric Anxiety v2.0 (PROMIS-Anx) Short Form 8a (47–50). The PROMIS-Dep and PROMIS-Anx Short Forms are both eight-item surveys representing the past 7 d where participants respond to questions or statements with five answer selections, each ranging from “Never” to “Almost Always.” Raw scores for both measures range from 8 to 40 (lowest to highest anxiety or depression, respectively). Raw scores were converted to T-scores (PROMIS-Dep: range, 35.2–82.4; PROMIS-Anx: T-score range, 33.5–83.3) with standard error using normalized conversion tables provided in the PROMIS scoring manuals (51,52). A T-score of 50 represents the average for the reference population, and a higher T-score represents more of the concept being measured (i.e., more anxiety or more depression).

  • QoL (generic and disease-specific) were assessed with the teen versions of the Pediatric Quality of Life Inventory (PedsQL™), Generic Core Scale v4.0, and the PedsQL™ Cardiac Module v3.0 (53,54). The PedsQL™ Generic Core Scale consists of 23 items, consisting of four domains of functioning including physical, emotional, school, and social functioning. The PedsQL™ Cardiac Module consists of 22 items, consisting of six domains of functioning including heart problems and treatment, treatment (heart medications), perceived physical appearance, treatment anxiety, cognitive problems, and communication. Both scales represent the past month and ask participants to respond to statements using five answer selections ranging from “Never” to “Almost always.” Descriptive responses aligned with numeric values and were reverse scored and summed to elucidate an overall summary score and subscale scores as described in the scoring manual with a range from 0 to 100 (lowest to highest QoL, respectively) (55).

  • PA over the previous 7 d was estimated using the self-report Physical Activity Questionnaire for Adolescents (PAQ-A) (56,57). Voss and colleagues (58) established that the PAQ-A is reliable and valid in youth with HD, with the summary scores correlating with total PA assessed with a waist-worn ActiGraph device (r = 0.52). The eight-item PAQ-A is designed to assess participation in both recreational and school-based PA. The PAQ-A summary score is an average of each survey items ranging from 1 to 5 (lowest to highest PA, respectively).

Internal and test–retest reliability was determined at the follow-up assessment where participants were asked to complete the TSK-Heart-A (version 3) a second time (~14 d following the initial assessment). No other patient-reported outcomes were assessed at the follow-up assessment time point.

Demographics and Medical History

Adolescent participants’ demographics and medical/health history was obtained through a medical record review and reported in REDCap. Medical health history included the following: demographics (e.g., age, biological sex, race, ethnicity, and body mass index z-score), diagnosis information (e.g., primary cardiac diagnosis, presence of secondary cardiac diagnosis), active cardiac medications, cardiac procedural history, current cardiac devices (e.g., presence of a pacemaker, implanted cardioverter–defibrillator, implanted loop recorder), current or past history of requiring a LifeVest™, immediate family history of non-atherosclerotic HD, and presence of an individualized education plan or 504 education plan.

Statistical Analysis

Phase II.

Item Content Validity Index (I-CVI) and Scale Content Validity Index (S-CVI) scores were calculated (59). If the favorability score, construct score, or readability score was below 80% agreement, the free-text comments were reviewed and discussed by the study team and the item was modified according to the recommendations of the content experts. If no substantial changes were deemed appropriate, the item was removed. For each item, I-CVI was calculated as the average of 0/1 expert ratings (i.e., the % of expert agreement). The S-CVI score was be calculated as the average of I-CVI scores for the retained items (59). Items that were retained following content validity were then administered to adolescents, and the wording of each item was revised, as necessary, based on feedback from the adolescent group.

Phase III.

Criterion validity was evaluated by assessing the relationship between the TSK-Heart-A and evidence-based correlates (i.e., mental health, QOL, PA, etc.) of KP using the measures described above. Internal consistency was assessed using Cronbach’s alpha (60). Test–retest reliability was evaluated using stability coefficients, correlating scores on the initial survey and the 2-wk follow-up survey.

RESULTS

Participants

Participant demographics for Phases II, III, and IV are displayed in Table 1. Seven content area experts were approached, and six participated in content validity (Phase II). Of the content area experts, five specialized in pediatric and congenital HD (pediatric cardiologists, 3; pediatric exercise physiologist, 1; pediatric psychologists, 2), and one had expertise in KP (pediatric psychologist). Seven adolescents were approached, and six participated in the face validity (Phase III) procedures. The mean age was 13.9 yr (standard deviation (SD) = 1.35; range, 12.4–15.5 yr), and participants were mostly White, were non-Hispanic, and had arrhythmia conditions as their primary cardiac diagnosis.

TABLE 1.

Participant demographics (Phases II, III, and IV).

n (%)
Content area experts (Phase II); n = 6
 Expertise Ped cardiologist 3 (50.0)
Psychologist 2 (33.3)
Ped Ex physiologist 1 (16.7)
Adolescents, face validity (Phase III); n = 6
 Diagnosis VT 3 (50.0)
CPVT 1 (16.7)
Cardiomyopathy 1 (16.7)
LQTS 1 (16.7)
 Sex Male 3 (50)
Female 3 (50)
 Race White 5 (83.3)
Non-White 1 (16.7)
 Ethnicity Hispanic 0 (0.0)
Non-Hispanic 6 (100)
Adolescents, criterion validity, and reliability (Phase IV); n = 63
 Diagnosis Single ventricle 19 (30.2)
Cardiomyopathy 12 (19.1)
LQTS 10 (15.9)
Complex SVT 7 (11.1)
WPW 7 (11.1)
ARVC 3 (4.8)
VT 3 (4.8)
CPVT 1 (1.6)
ISCA 1 (1.6)
 Sex Male 32 (50.8)
Female 31 (49.2)
 Race White 50 (81.0)
Non-White 12 (19.0)
 Ethnicity Hispanic 4 (6.4)
Non-Hispanic 59 (93.7)
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ARVC, arrhythmogenic right ventricular cardiomyopathy; CPVT, catecholaminergic polymorphic ventricular tachycardia; Ex, exercise; ISCA, idiopathic sudden cardiac arrest; LQTS, long-QT syndrome; Ped, pediatric; SVT, supraventricular tachycardia; VT, ventricular tachycardia; WPW, Wolff–Parkinson–White syndrome.

For criterion validity and reliability (Phase IV), 428 adolescents were screened for inclusion over 12 months, and 147 (34.3%) met the criteria for inclusion. The most common factors for exclusion were having an ineligible cardiac diagnosis (n = 136), receiving a curative cardiac electrophysiology procedure (n = 65), intellectual or developmental disability preventing completion of study procedures (n = 30), and non-English speaking (n = 17). Of the 147 patients that met the criteria for inclusion, 58 did not respond to the survey invitation, 21 declined participation, and 5 consented but did not complete any survey items.

A total of 63 adolescents completed the initial assessment and 49 completed the follow-up assessment. The cohort was evenly split by sex, mostly White and non-Hispanic, and the mean age at the initial assessment was 15.5 yr (SD = 1.82; range, 12.2–18.7 years). Additional descriptive features of the Phase IV cohort including cardiac health history derived from medical record review are displayed in Table 2.

TABLE 2.

Adolescents (Phase IV), medical/health history.

n (%)
Presence of a secondary cardiac diagnosis Yes 19 (30.2)
No 44 (69.8)
Taking cardiac medications Yes 39 (61.9)
No 24 (38.1)
History of invasive cardiac procedures (lifetime) Yes 44 (69.8)
No 19 (30.2)
Implanted cardiac device (n = 61) (pacemaker, ILR, or ICD) Yes 12 (19.7)
No 49 (80.3)
Immediate family history of cardiac disease Yes 25 (39.7)
No 38 (60.3)
History of being provided a LifeVest™ (n = 62) Yes 2 (3.2)
No 60 (95.2)
IEP or 504 Education Plan (n = 62) Yes 19 (30.1)
No 43 (69.4)
Mean (SD)
BMI at assessment (z-score) 0.67 (1.82)
Age at diagnosis (yr) 6.26 (6.19)
OP cardiology clinic appts in the past year (count) 2.67 (2.86)
OP cardiology clinic appts in the past 5 yr (count) 7.70 (6.77)
CMH-KC ED visits (lifetime) 4.79 (8.14)
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Sample size is n = 63 unless otherwise noted.

appts, appointments; BMI, body mass index; CMH-KC, Children’s Mercy Kansas City Hospital; ED, emergency department; ICD, implanted cardioverter–defibrillator; IEP; individualized education plan; ILR, implanted loop recorder; OP, outpatient.

Phase II—Content Validity

Results from the content validity assessment are displayed in Table 3. In addition, item-specific free-text comments, highlights from content area expert interviews, and recommendations for changes in item verbiage can be found in the supplemental material (Supplemental Appendix 1, Supplemental Digital Content, http://links.lww.com/MSS/D170).

TABLE 3.

Item and Scale Content Validity Index of TSK-Heart-A (Version 1).

I-CVI Scores
Item No. Item Text Construct FS CS RS
1 “I am afraid that I might hurt myself if I do physical activity or exercise.” Fear of injury 83% 100% 100%
2 “If I tried to be physically active or exercise my heart condition would get worse.” Avoidance of exercise 100% 83% 100%
3 “My body is telling me that I have something seriously wrong when I do physical activity or exercise.” Perceived danger for heart problems 33% 50% 100%
4 “My heart condition would not be as bad if I was physically active/exercised.” Avoidance of exercise 67% 67% 100%
5 “People are not taking my heart condition seriously enough.” Dysfunctional self 100% 100% 100%
6 “My heart condition has made me physically weak for the rest of my life.” Dysfunctional self 100% 100% 100%
7 “Having a heart condition means that my body always has a problem.” Fear of injury 83% 50% 100%
8 “Just because something causes discomfort, does not mean that it is dangerous.” Perceived danger for heart problems 67% 83% 83%
9 “I am afraid that I might accidentally hurt myself when doing physical activity and exercise.” Fear of injury 100% 100% 100%
10 “The safest thing I can do to prevent my heart condition from worsening is to avoid unnecessary physical activity and exercise.” Dysfunctional self 83% 83% 100%
11 “My heart condition means that there is something potentially dangerous going on in my body.” Perceived danger for heart problems 83% 83% 100%
12 “Even with my heart condition, I would take better care of myself if I was physically active and exercised.” Avoidance of exercise 33% 67% 50%
13 “My heart tells me when I should stop being physically active and exercising so that I do not hurt myself.” Fear of injury 100% 100% 100%
14 “It is not safe for a person with my heart condition to be physically active or exercise.” Avoidance of exercise 100% 100% 100%
15 “I cannot do the same physical activities and exercises as others because it is too easy to hurt my heart.” Dysfunctional self 83% 83% 100%
16 “Even though something causes me heart or chest pain, I do not think it is actually dangerous.” Perceived danger for heart problems 33% 100% 100%
17 “No one should have to be physically active/exercise when they have a heart condition.” Avoidance of exercise 67% 83% 100%
S-CVI 77% 84% 96%
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CS, construct score; FS, favorability score; I-CVI, Item Content Validity Index; RS, readability score; S-CVI, Scale Content Validity Index.

Seven survey items (items: 3, 4, 7, 8, 12, 16, and 17) scored below 80% agreement on at least one content validity criterion and were modified in accordance with recommendations from content area experts. Several items (4, 8, 12, and 16), which were carried over from the original TSK, were reverse scored (e.g., “My heart condition would not be as bad if I was physically active”). There was consensus among content area experts that the reverse scored items should be reworded and transitioned to positively scored items aligning with the other 13 items in the survey. In addition to the content expert consensus, research has shown that reverse coding or negative wording items do not reduce respondent error and, in some cases, increases confusion, inattention, and response bias (61). Lastly, throughout the survey, the term “heart problem” was replaced with “heart condition.” The S-CVI was lowest for the favorability dimension (77%) and below the acceptable threshold, further justifying revision of the individual items. S-CVI for both the construct and readability dimensions was above the acceptable threshold (84% and 96%, respectively).

Phase III—Face Validity

Findings from the face validity interviews resulted in a major modification of item 12 from “Because of my heart condition, I take better care of myself when I limit physical activity” to “Because of my heart condition, limiting physical activity helps me take better care of my body.” Some participants provided minor recommendations for item verbiage, which were considered. Some of these recommendations resulted in survey items becoming grammatically incorrect. One participant’s recommendation to change item 15 from “I cannot do the same physical activities as others because it is too easy to hurt my heart” to “I should not do the same physical activities…” was not adopted as it would contradict the construct for that item of dysfunctional self. One participant noted that items 3, 4, 6, 7, 12, and 13 were “a little hard to understand” but was able to accurately interpret each item and provided no recommendations for how to modify those items. There was consensus among participants that items were generally easy to understand, and the study team waived the option for a second adolescent face validity cohort.

Phase IV—Criterion Validity and Reliability

Scores from the established criterion measures (anxiety, depression, QoL, and PA) and the TSK-Heart-A (version 3) summary score are presented in Table 4. Internal and test–retest reliability compared TSK-Heart-A scores between the initial and follow-up assessments. The mean time between initial and follow-up assessments (49 of 63 participants completed) was 20.4 d (SD = 6.3; range, 14–37 d). Findings from the internal and test–retest reliability analyses are displayed in Table 5. Internal consistency for total scale at both the initial assessment (α = 0.89), and follow-up was high (α = 0.91), although subscale alphas ranged from 0.60 (Danger Subscale) to 0.80 (Avoidance). The test–retest reliability for the full scale was also high (r = 0.79) and ranged from 0.66 (Avoidance and Danger) to 0.76 (Fear) for the subscales.

TABLE 4.

TSK-Heart-A and criterion measure summary scores.

Mean (SD) Range Min, Max
Independent variable
 TSK-Heart-A
Sum score
35.4 (8.0)
20.0, 56.0
Established criterion measures
 PROMIS, Ped Anxiety
T-score
49.7 (12.2)
33.5, 83.3
Raw score 16.5 (8.0) 8.0, 40.0
 PROMIS, Ped Depressive Symptoms T-score 46.9 (12.7) 35.2, 78.1
Raw score 14.3 (8.4) 8.0, 38.0
 PedsQL, Generic Core Scale Sum score 75.2 (18.9) 26.1, 100
 PedsQL, Cardiac Module Sum score 74.7 (17.5) 11.4, 98.1
 PAQ-A (n = 62) Sum score 2.0 (0.7) 0.99, 3.7
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Sample size is n = 63 unless otherwise noted.

Ped, pediatric.

TABLE 5.

Internal and test–retest reliability of the TSK-Heart-A.

Standardized Variables
Initial Assessment
 Follow-Up Assessment
TSK-Heart-A Item r to Total α if Deleted Test–Retest Coeff r to Total α if Deleted
Item 1 0.41 0.55 0.61 0.76 0.71
Item 7 0.34 0.60 0.44 0.54 0.82
Item 9 0.52 0.46 0.60 0.79 0.70
Item 13 0.34 0.60 0.59 0.49 0.84
Fear subscale α = 0.62 0.76 α = 0.82
Item 2 0.54 0.78 0.49 0.59 0.74
Item 4 0.69 0.73 0.64 0.68 0.71
Item 12 0.49 0.79 0.40 0.46 0.78
Item 14 0.57 0.77 0.18 0.52 0.76
Item 17 0.64 0.75 0.41 0.58 0.74
Avoidance subscale α = 0.80 0.66 α = 0.79
Item 3 0.43 0.50 0.62 0.52 0.55
Item 8 0.38 0.53 0.53 0.35 0.66
Item 11 0.24 0.63 0.47 0.41 0.62
Item 16 0.49 0.44 0.28 0.52 0.55
Danger subscale α = 0.60 0.66 α = 0.67
Item 5 0.60 0.67 0.69 0.41 0.73
Item 6 0.49 0.73 0.61 0.62 0.61
Item 10 0.55 0.70 0.52 0.42 0.73
Item 15 0.57 0.69 0.68 0.66 0.59
Dysfunction subscale α = 0.75 0.74 α = 0.73
Item 1 0.49 0.89 0.61 0.77 0.90
Item 2 0.68 0.88 0.49 0.76 0.90
Item 3 0.67 0.88 0.62 0.71 0.90
Item 4 0.79 0.88 0.64 0.72 0.90
Item 5 0.58 0.89 0.69 0.43 0.91
Item 6 0.50 0.89 0.61 0.64 0.90
Item 7 0.52 0.89 0.44 0.55 0.91
Item 8 0.32 0.90 0.53 0.36 0.91
Item 9 0.56 0.89 0.60 0.79 0.90
Item 10 0.61 0.89 0.52 0.63 0.91
Item 11 0.48 0.89 0.47 0.42 0.91
Item 12 0.52 0.89 0.40 0.60 0.91
Item 13 0.45 0.89 0.59 0.59 0.91
Item 14 0.57 0.89 0.18 0.39 0.91
Item 15 0.67 0.88 0.68 0.68 0.90
Item 16 0.35 0.89 0.28 0.43 0.91
Item 17 0.48 0.89 0.41 0.50 0.91
Summary score α = 0.89 0.79 α = 0.91
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Correlations between the TSK-Heart-A and established criterion measures are displayed in Figure 1. As expected, the TSK-Heart-A had strong positive associations with PROMIS Anxiety (r = 0.48, P < 0.001) and Depression T-Scores (r = 0.41, P = 0.009). Furthermore, TSK-Heart-A had a strong negative association with both general (r = −0.61, P < 0.001) and disease-specific QoL scores (r = −0.56, P < 0.001). Finally, the TSK-Heart-A had a moderate, negative association with PA (r = −0.35, P = 0.001). The magnitude and direction of these associations provide evidence of criterion validity (62–64). The complete and final version of the 17-item TSK-Heart-A can be found in Supplemental Appendix 2 (Supplemental Digital Content, http://links.lww.com/MSS/D170).

FIGURE 1— Correlations between TSK-Heart-A summary score and the following criterion measures: A, PROMIS anxiety T-score; B, PROMIS depressive symptoms T-score; C, PedsQL generic core scale QoL summary score; D, PedsQL cardiac module QoL summary score; and E, PAQ-A physical activity summary score. All sample sizes are n = 63 unless otherwise noted. Anx, anxiety; C-QoL, cardiac module quality of life; Dep, depressive symptoms; G-QoL, generic core scale quality of life; Sum, summary.

FIGURE 1—

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DISCUSSION

Children and adolescents with HD and chronic pain disorders present with many similarities related to PA avoidance. Both of these unique pediatric populations accumulate about half of the PA as matched peers and exhibit fear-avoidance behaviors related to PA, which may be associated with worsening of their disease condition, mental health, psychosocial functioning, and QoL (1,14,19,21,22,40,65–68). Drawing upon constructs built in the chronic pain literature, KP (i.e., fear of movement or PA associated with a medical condition) and its measure, the TSK, can aid in qualifying the degree of the PA fear-avoidance behaviors and how it relates to PA engagement (21,22,32,33). However, there are no validated tools for evaluating KP specifically for children and adolescents with HD. Therefore, this study developed and evaluated the initial validity and reliability of the TSK-Heart-A, a patient-reported outcome measure for assessing KP in adolescents with HD.

Shorter 11-item, 7-item, and 5-item versions of the TSK have been developed and validated in adults (42,69,70); however, we chose to rely upon the complete 17-item version of the TSK as the basis for the initial development (Phase I) as we were unaware how this population would identify with and respond to individual survey items. By keeping the TSK-Heart-A as similar to the other 17-item TSK measures as possible, we may be able to refer to other literature bases for how to shorten this measure in the future, if needed.

The content experts (Phase II) generally rated version 1 of the TSK-Heart-A to be readable and related to the construct being measured. Unsurprisingly, all the reverse scored items carried over from the original TSK (items 4, 8, 12, and 16) were identified by the content experts as problematic. Studies by Rosenbloom et al. (42) and Woby et al. (69) have reported that the TSK’s reverse scored items performed poorly for model fit in factor analysis and item total correlations, and have suggested that those items may perform better if they were scored similarly to the other items in the survey (42,69). These items were subsequently reworded in alignment with the other item’s valence (i.e., higher Likert scale selection = more KP).

Feedback from adolescents (Phase III—face validity) resulted in a modification to item 12 where the wording in the second part of the item was flipped. Overall, adolescent participants indicated that the items were easy to understand and complete, but unfortunately did not provide any other feedback that we felt was useful or improved the readability or grammatical correctness of the instrument.

Our results support that version 3 of the TSK-Heart-A demonstrated good criterion validity and internal and test–retest reliability. As hypothesized, the TSK-Heart-A summary score was positively correlated with PROMIS anxiety and depression T-scores; and negatively correlated with PedsQL generic and cardiac modules and self-reported PA. Our findings are comparable to others KP studies in pediatrics where TSK was correlated with anxiety (r = 0.3–0.35) (42), depression (r = 0.37) (42), PedsQL™ generic core scale (r = −0.64) (40), and PA (r = −0.1) (40). Bäck et al. (34,35), who developed the TSK-Heart for older adults with coronary artery disease, found significantly higher anxiety and depression, and lower QoL and PA in the high KP group compared with the low KP group.

The scale also demonstrated good overall internal and test–retest reliability with a Cronbach’s alpha of 0.89 at the initial assessment and α = 0.91 at the follow-up assessment. Interestingly, the TSK-Heart-A performed better for internal reliability compared with the TSK-Heart for adults (α = 0.78) (34) and the standard TSK, when completed by adolescents with idiopathic scoliosis undergoing spinal fusion surgery (α = 0.76) (71). In addition, the TSK-Heart-A test–retest stability coefficient was 0.79, which is comparable to the original TSK in a sample of adults with lower back pain (r = 0.78 and r = 0.79 when reverse scores items were deleted) (72), and the TSK-Heart for adults where the authors reported a total score intraclass correlation coefficient of 0.83.

The TSK-Heart-A summary scores in our sample of adolescents with HD are comparable to the TSK summary scores seen in the chronic pain population, where the KP construct was derived. The adolescents with HD in this study reported an average of TSK-Heart-A summary score of 35.4 ± 8.0, whereas TSK scores in adolescents with chronic pain were ~42 on the 17-item scale (67,68). Comparing these two populations suggests that adolescents with HD may be experiencing heart-related KP that is not dissimilar from the pain-related KP experienced by adolescents with chronic pain. In n = 332 older adults with coronary artery disease, Bäck et al. (35) observed a mean TSK-Heart summary score of 30.8. Using the threshold for high KP defined by Vlaeyen et al. (73) in two studies of adults with pain and disability (summary score >37), Bäck et al. (35) observed high KP in 20% of their sample, whereas high KP was observed in 41.3% of adolescents with HD. These comparisons may be limited by how well cutoff scores for adults translate to adolescents. However, much of the recent work in KP in adolescents with chronic pain have either relied on previously established cutoffs in adults or have utilized abbreviated versions of the TSK absent or reverse scored items (42). Additional work is needed to evaluate whether adult-derived cutoff scores are appropriate for adolescents, and to explore the factor structure of the TSK-Heart-A.

The close similarities in fear-based PA avoidance behaviors between pediatric HD and chronic pain suggest that other parallels between these populations may be drawn upon. KP is central to the fear-avoidance model of chronic pain, originally described by Lethem et al. (29) and further developed by Vlaeyen and Linton (31). The fear-avoidance model postulates that upon experiencing recurrent or chronic pain, some individuals perceive this pain as threatening, become hypervigilant to pain sensations and activities and conditions that elicit pain, and subsequently avoid those activities they believe may elicit or worsen their pain. This creates a cycle of activity avoidance, hyper-arousal of symptoms, and disengagement, which reenforces their pain-related fears and ultimately contributes to a reduction in QoL and functioning (30). The fear-avoidance model attempts to capture differences in how individuals respond to pain, and the interaction between participation in activities that cause anxiety, fear, and discomfort, and contribute to disability and disengagement from activities (29–31).

There may be utility in exploring the fear-avoidance model in pediatric HD and translating psychological intervention techniques from pediatric chronic pain to target KP in youth with HD (67,74). Adaptations to these intervention approaches may be needed in pediatric HD to address some of the unique moderators of PA engagement such as heart-focused anxiety and overprotective and restrictive behaviors among parents and family members, teachers, and coaches (19,21,23–28).

Limitation and future directions.

There are strengths of this study, including its integration of tools with a well-established evidence base to inform the design of this new instrument. This study utilized a stepwise and iterative process that incorporated feedback from content and patient experts. Based on feedback obtained, this likely resulted in the development of a measure that was better adapted for youth HD. Regarding limitations, this study was adequately powered for the purposes of an initial measure development, validation, and reliability assessment; however, it was not powered to complete factor analyses or other advanced techniques used in measure development (e.g., item-response theory). The face validity cohort was small and homogeneous. which may have limited the groups’ scope of feedback. Additional research with large sample sizes, potentially including multiple sites, will be needed to better assess the underlying factor structure of the measure and determine whether subscales can be utilized and if a shorter version of the TSK-Heart-A may be justified. It was beyond the scope of this study to assess for other constructs (e.g., catastrophizing) that are related to KP in chronic pain. Additional work is needed to better understand how the fear-avoidance model may be applied to PA and exercise avoidance in pediatric HD and inform the development of interventions to reduce KP and improve PA engagement.

CONCLUSIONS

This study developed and tested the validity and reliability of a new measure of KP for use in youth with HD (TSK-Heart-A). We observed that the TSK-Heart-A is valid and reliable, and adolescents with HD demonstrate comparable levels of KP as youth with chronic pain. The TSK-Heart-A may be sensitive to capturing KP in pediatric HD. Although the TSK has been modified for youth and utilized in pediatric pain, at the time of this study, these versions have not been validated. Thus, this is the first study to report validity and reliability data on a TSK scale modified for youth. The TSK-Heart-A could be a valuable tool in clinical and research contexts to better understand and identify targets for improving PA engagement in youth with HD.

Supplementary Material

Final TSK-Heart-A Questionnaire
Appendix 1

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.acsm-msse.org).

Acknowledgments

This study was funded by the Center for Children’s Healthy Lifestyles & Nutrition Pilot Research Grant through Children’s Mercy Kansas City and Kansas University Medical Center. The authors would like to recognize the support of our research team (Dara Watkins, Olivia Olson, Madeline Donnelli, and David Cloutier) and the Ward Family Heart Center. Most of all, we would like to acknowledge those who participated in this study including the content area experts and adolescents and their families. Dr. White receives salary support from the NIH through a K23 Career Development Award (HL159325) from the National Heart, Lung, and Blood Institute and the Additional Ventures Single Ventricle Foundation. Dr. Black receives salary support from the NIH through a K23 Career Development Award (AR078337) through the National Institute of Arthritis and Musculoskeletal and Skin Diseases. The authors have no professional relationships with companies or manufacturers who could benefit from the results of this study. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.

REFERENCES

  • 1.White DA, Willis EA, Panchangam C, et al. Physical activity patterns in children and adolescents with heart disease. Pediatr Exerc Sci. 2020;32(4):233–40. [DOI] [PubMed] [Google Scholar]
  • 2.Bélanger M, Sabiston CM, Barnett TA, et al. Number of years of participation in some, but not all, types of physical activity during adolescence predicts level of physical activity in adulthood: results from a 13-year study. Int J Behav Nutr Phys Act. 2015;12:76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Hallal PC, Victora CG, Azevedo MR, Wells JC. Adolescent physical activity and health: a systematic review. Sports Med. 2006;36(12):1019–30. [DOI] [PubMed] [Google Scholar]
  • 4.Telama R, Yang X, Laakso L, Viikari J. Physical activity in childhood and adolescence as predictor of physical activity in young adulthood. Am J Prev Med. 1997;13(4):317–23. [PubMed] [Google Scholar]
  • 5.Hernelahti M, Levalahti E, Simonen RL, et al. Relative roles of heredity and physical activity in adolescence and adulthood on blood pressure. J Appl Physiol (1985). 2004;97(3):1046–52. [DOI] [PubMed] [Google Scholar]
  • 6.Boreham C, Twisk J, Neville C, Savage M, Murray L, Gallagher A. Associations between physical fitness and activity patterns during adolescence and cardiovascular risk factors in young adulthood: the Northern Ireland Young Hearts Project. Int J Sports Med. 2002;23- (Supp 1):S22–6. [DOI] [PubMed] [Google Scholar]
  • 7.Khan K, McKay HA, Haapasalo H, et al. Does childhood and adolescence provide a unique opportunity for exercise to strengthen the skeleton? J Sci Med Sport. 2000;3(2):150–64. [DOI] [PubMed] [Google Scholar]
  • 8.Okasha M, McCarron P, Gunnell D, Davey Smith G. Exposures in childhood, adolescence and early adulthood and breast cancer risk: a systematic review of the literature. Breast Cancer Res Treat. 2003;78(2):223–76. [DOI] [PubMed] [Google Scholar]
  • 9.Karlsson MK. Physical activity, skeletal health and fractures in a long term perspective. J Musculoskelet Neuronal Interact. 2004;4(1):12–21. [PubMed] [Google Scholar]
  • 10.García-Cruz E, Manzur-Sandoval D, Gopar-Nieto R, et al. Cardiometabolic risk factors in Mexican adults with congenital heart disease. JACC Adv. 2023;2(8):100596. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Giannakoulas G, Dimopoulos K, Engel R, et al. Burden of coronary artery disease in adults with congenital heart disease and its relation to congenital and traditional heart risk factors. Am J Cardiol. 2009; 103(10):1445–50. [DOI] [PubMed] [Google Scholar]
  • 12.Awerbach JD, Krasuski RA, Camitta MG. Coronary disease and modifying cardiovascular risk in adult congenital heart disease patients: should general guidelines apply? Prog Cardiovasc Dis. 2018;61(3–4):300–7. [DOI] [PubMed] [Google Scholar]
  • 13.McDowell CP, MacDonncha C, Herring MP. Brief report: associations of physical activity with anxiety and depression symptoms and status among adolescents. J Adolesc. 2017;55:1–4. [DOI] [PubMed] [Google Scholar]
  • 14.Wu XY, Han LH, Zhang JH, Luo S, Hu JW, Sun K. The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: a systematic review. PLoS One. 2017;12(11):e0187668. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Biddle SJ, Ciaccioni S, Thomas G, Vergeer I. Physical activity and mental health in children and adolescents: an updated review of reviews and an analysis of causality. Psychol Sport Exerc. 2019;42:146–55. [Google Scholar]
  • 16.DeMaso DR, Calderon J, Taylor GA, et al. Psychiatric disorders in adolescents with single ventricle congenital heart disease. Pediatrics. 2017;139(3):e20162241. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Gonzalez VJ, Kimbro RT, Cutitta KE, et al. Mental health disorders in children with congenital heart disease. Pediatrics. 2021;147(2): e20201693. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Gupta S, Giuffre R, Crawford S, Waters J. Covert fears, anxiety and depression in congenital heart disease. Cardiol Young. 1998;8(4): 491–9. [DOI] [PubMed] [Google Scholar]
  • 19.Uzark K, Jones K, Slusher J, Limbers CA, Burwinkle TM, Varni JW. Quality of life in children with heart disease as perceived by children and parents. Pediatrics. 2008;121(5):e1060–7. [DOI] [PubMed] [Google Scholar]
  • 20.Hoare E, Milton K, Foster C, Allender S. The associations between sedentary behaviour and mental health among adolescents: a systematic review. Int J Behav Nutr Phys Act. 2016;13(1):108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Takken T, Giardini A, Reybrouck T, et al. Recommendations for physical activity, recreation sport, and exercise training in paediatric patients with congenital heart disease: a report from the Exercise, Basic & Translational Research Section of the European Association of Cardiovascular Prevention and Rehabilitation, the European Congenital Heart and Lung Exercise Group, and the Association for European Paediatric Cardiology. Eur J Prev Cardiol. 2012;19(5):1034–65. [DOI] [PubMed] [Google Scholar]
  • 22.Sweeting J, Ingles J, Ball K, Semsarian C. Challenges of exercise recommendations and sports participation in genetic heart disease patients. Circ Cardiovasc Genet. 2015;8(1):178–86. [DOI] [PubMed] [Google Scholar]
  • 23.Berger S, Carr M, Koenig P, Ward K. Commentary: exercise and congenital heart disease—a new era of “exercise advocacy” rather than exercise restriction. Semin Thorac Cardiovasc Surg. 2020; 32(4):917–9. [DOI] [PubMed] [Google Scholar]
  • 24.McCrindle BW, Williams RV, Mital S, et al. Physical activity levels in children and adolescents are reduced after the Fontan procedure, independent of exercise capacity, and are associated with lower perceived general health. Arch Dis Child. 2007;92(6):509–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Müller J, Christov F, Schreiber C, Hess J, Hager A. Exercise capacity, quality of life, and daily activity in the long-term follow-up of patients with univentricular heart and total cavopulmonary connection. Eur Heart J. 2009;30(23):2915–20. [DOI] [PubMed] [Google Scholar]
  • 26.Bergman AB, Stamm SJ. The morbidity of cardiac nondisease in schoolchildren. N Engl J Med. 1967;276(18):1008–13. [DOI] [PubMed] [Google Scholar]
  • 27.Meulenkamp TM, Tibben A, Mollema ED, et al. Predictive genetic testing for cardiovascular diseases: impact on carrier children. Am J Med Genet A. 2008;146A(24):3136–46. [DOI] [PubMed] [Google Scholar]
  • 28.Doroshow RW. The adolescent with simple or corrected congenital heart disease. Adolesc Med. 2001;12(1):1–22. [PubMed] [Google Scholar]
  • 29.Lethem J, Slade P, Troup J, Bentley G. Outline of a fear-avoidance model of exaggerated pain perception—I. Behav Res Ther. 1983;21(4): 401–8. [DOI] [PubMed] [Google Scholar]
  • 30.Leeuw M, Goossens ME, Linton SJ, Crombez G, Boersma K, Vlaeyen JW. The fear-avoidance model of musculoskeletal pain: current state of scientific evidence. J Behav Med. 2007;30(1):77–94. [DOI] [PubMed] [Google Scholar]
  • 31.Vlaeyen JW, Linton SJ. Fear-avoidance and its consequences in chronic musculoskeletal pain: a state of the art. Pain. 2000;85(3):317–32. [DOI] [PubMed] [Google Scholar]
  • 32.Kori S Kinesiophobia: a new view of chronic pain behavior. Pain Manage. 1990;3:35–43. [Google Scholar]
  • 33.Miller R, Kori S, Todd D. The Tampa Scale: a measure of kinesiophobia. Clin J Pain. 1991;7(1):51. [Google Scholar]
  • 34.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(4):363–9. [DOI] [PubMed] [Google Scholar]
  • 35.Bäck M, Cider Å, Herlitz J, Lundberg M, Jansson B. The impact on kinesiophobia (fear of movement) by clinical variables for patients with coronary artery disease. Int J Cardiol. 2013;167(2):391–7. [DOI] [PubMed] [Google Scholar]
  • 36.Yusoff MSB. ABC of content validation and content validity index calculation. Educ Med J. 2019;11(2):49–54. [Google Scholar]
  • 37.Patridge EF, Bardyn TP. Research electronic data capture (REDCap). J Med Libr Assoc. 2018;106(1):142. [Google Scholar]
  • 38.Debeer P, Commeyne O, De Cupere I, et al. The outcome of hydrodilation in frozen shoulder patients and the relationship with kinesiophobia, depression, and anxiety. J Exp Orthop. 2021;8(1):85. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Antunes RS, de Macedo BG, da Silva Amaral T, de Alencar Gomes H, Pereira LSM, Rocha FL. Pain, kinesiophobia and quality of life in chronic low back pain and depression. Acta Ortop Bras. 2013;21(1):27–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.McGarrigle L, Wesson C, DeAmicis L, Connoly S, Ferreira N. Psychological mediators in the relationship between paediatric chronic pain and adjustment: an investigation of acceptance, catastrophising and kinesiophobia. J Contextual Behav Sci. 2020;18:294–305. [Google Scholar]
  • 41.Chabot B, Sweatman H, Ocay DD, Premachandran S, Roy M, Ferland CE. Pain catastrophizing throughout the perioperative period in adolescents with idiopathic scoliosis. Clin J Pain. 2021;37(9):688–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Rosenbloom BN, Pagé MG, Isaac L, et al. Fear of movement in children and adolescents undergoing major surgery: a psychometric evaluation of the Tampa Scale for Kinesiophobia. Eur J Pain. 2020; 24(10):1999–2014. [DOI] [PubMed] [Google Scholar]
  • 43.Comachio J, Magalhães MO, Campos Carvalho E Silva APM, Marques AP. A cross-sectional study of associations between kinesiophobia, pain, disability, and quality of life in patients with chronic low back pain. Adv Rheumatology. 2019;58(1):8. [DOI] [PubMed] [Google Scholar]
  • 44.Luque-Suarez A, Martinez-Calderon J, Falla D. Role of kinesiophobia on pain, disability and quality of life in people suffering from chronic musculoskeletal pain: a systematic review. Br J Sports Med. 2019;53(9):554–9. [DOI] [PubMed] [Google Scholar]
  • 45.van Ittersum M, de Greef M, van Gelder I, Coster J, Brügemann J, van der Schans C. Fear of exercise and health-related quality of life in patients with an implantable cardioverter defibrillator. Int J Rehabil Res. 2003;26(2):117–22. [DOI] [PubMed] [Google Scholar]
  • 46.Miller MB, Roumanis MJ, Kakinami L, Dover GC. Chronic pain patients’ kinesiophobia and catastrophizing are associated with activity intensity at different times of the day. J Pain Res. 2020;13:273–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Irwin DE, Stucky B, Langer MM, et al. An item response analysis of the pediatric PROMIS anxiety and depressive symptoms scales. Qual Life Res. 2010;19(4):595–607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Varni JW, Magnus B, Stucky BD, et al. Psychometric properties of the PROMIS® pediatric scales: precision, stability, and comparison of different scoring and administration options. Qual Life Res. 2014;23(4):1233–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.PROMIS Health Organization and PROMIS Cooperatrive Group. LEVEL 2—Anxiety—Child Age 11–17 (PROMIS Emotional Distress —Anxiety—Pediatric Item Bank). 2012. Available from: http://www.psychiatry.org/practice/dsm/dsm5/online-assessment-measures. Accessed March 23, 2022.
  • 50.Quinn H, Thissen D, Liu Y, et al. Using item response theory to enrich and expand the PROMIS® pediatric self report banks. Health Qual Life Outcomes. 2014;12:160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.PROMIS Health Organization and PROMIS Cooperatrive Group. Anxiety Scoring Manual. PROMIS Research Group. 2023. Available from: https://www.healthmeasures.net/images/PROMIS/manuals/Scoring_Manual_Only/PROMIS_Anxiety_Scoring_Manual_08Sept2023.pdf. Accessed November 21, 2023.
  • 52.PROMIS Health Organization and PROMIS Cooperatrive Group. Depression Scoring Manual. PROMIS Research Group. 2023. Available from: https://www.healthmeasures.net/images/PROMIS/manuals/Scoring_Manual_Only/PROMIS_Depression_Scoring_Manual_08Sept2023.pdf. Accessed November 21, 2023.
  • 53.Varni JW, Burwinkle TM, Seid M, Skarr D. The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity. Ambul Pediatr. 2003;3(6):329–41. [DOI] [PubMed] [Google Scholar]
  • 54.Uzark K, Jones K, Burwinkle TM, Varni JW. The Pediatric Quality of Life Inventory™ in children with heart disease. Prog Pediatr Cardiol. 2003;18:141–9. [Google Scholar]
  • 55.Varni JW. Scaling and scoring for the acute and standard versions of the Pediatric Quality of Life Inventory. 2023. Available from: https://www.pedsql.org/PedsQL-Scoring.pdf. Accessed November 21, 2023.
  • 56.Kowalski KC, Crocker PRE, Donen RM. The Physical Activity Questionnaire for Older Children (PAQ-C) and Adolescents (PAQ-A) Manual. 2004. Available from: https://www.prismsports.org/UserFiles/file/PAQ_manual_ScoringandPDF.pdf. Accessed November 21, 2023.
  • 57.Kowalski KC, Crocker PR, Faulkner RA. Validation of the Physical Activity Questionnaire for Older Children. Pediatr Exerc Sci. 1997; 9(2):174–86. [Google Scholar]
  • 58.Voss C, Dean PH, Gardner RF, Duncombe SL, Harris KC. Validity and reliability of the Physical Activity Questionnaire for Children (PAQ-C) and Adolescents (PAQ-A) in individuals with congenital heart disease. PLoS One. 2017;12(4):e0175806. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Polit DF, Beck CT. The content validity index: are you sure you know what’s being reported? Critique and recommendations. Res Nurs Health. 2006;29(5):489–97. [DOI] [PubMed] [Google Scholar]
  • 60.McDonald RP. Test Theory: A Unified Treatment. 1st ed. New York (NY): Pychology Pess; 2013. [Google Scholar]
  • 61.van Sonderen E, Sanderman R, Coyne JC. Ineffectiveness of reverse wording of questionnaire items: let’s learn from cows in the rain. PLoS One. 2013;8(7):e68967. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Gignac GE, Szodorai ET. Effect size guidelines for individual differences researchers. Personal Individ Differ. 2016;102:74–8. [Google Scholar]
  • 63.Cohen J A power primer. Psychol Bull. 1992;112(1):155–9. [DOI] [PubMed] [Google Scholar]
  • 64.Cohen J Statistical Power Analysis for the Behavioral Sciences. 2nd ed. New York (NY): Routledge; 1988. [Google Scholar]
  • 65.Long AC, Palermo TM, Manees AM. Brief report: using actigraphy to compare physical activity levels in adolescents with chronic pain and healthy adolescents. J Pediatr Psychol. 2008;33(6):660–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Wilson AC, Palermo TM. Physical activity and function in adolescents with chronic pain: a controlled study using actigraphy. J Pain. 2012;13(2):121–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Sil S, Thomas S, DiCesare C, et al. Preliminary evidence of altered biomechanics in adolescents with juvenile fibromyalgia. Arthritis Care Res (Hoboken). 2015;67(1):102–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Kashikar-Zuck S, Black WR, Pfeiffer M, et al. Pilot randomized trial of integrated cognitive-behavioral therapy and neuromuscular training for juvenile fibromyalgia: the FIT Teens Program. J Pain. 2018;19(9):1049–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Woby SR, Roach NK, Urmston M, Watson PJ. Psychometric properties of the TSK-11: a shortened version of the Tampa Scale for Kinesiophobia. Pain. 2005;117(1–2):137–44. [DOI] [PubMed] [Google Scholar]
  • 70.Bisson EJ, Katz L, Vader K, Bossio JA, Wilson R, Duggan S. Pain-related fear in adults living with chronic pain: development and psychometric validation of a brief form of the Tampa Scale of Kinesiophobia. Arch Phys Med Rehabil. 2022;103(5):875–81.e1. [DOI] [PubMed] [Google Scholar]
  • 71.Ye DL, Plante I, Roy M, Ouellet JA, Ferland CE. The Tampa Scale of Kinesiophobia: structural validation among adolescents with idiopathic scoliosis undergoing spinal fusion surgery. Phys Occup Ther Pediatr. 2020;40(5):546–56. [DOI] [PubMed] [Google Scholar]
  • 72.Swinkels-Meewisse E, Swinkels R, Verbeek A, Vlaeyen J, Oostendorp R. Psychometric properties of the Tampa Scale for Kinesiophobia and the fear-avoidance beliefs questionnaire in acute low back pain. Man Ther. 2003;8(1):29–36. [DOI] [PubMed] [Google Scholar]
  • 73.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(4):235–52. [DOI] [PubMed] [Google Scholar]
  • 74.Bordeleau M, Vincenot M, Lefevre S, et al. Treatments for kinesiophobia in people with chronic pain: a scoping review. Front Behav Neurosci. 2022;16:933483. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Final TSK-Heart-A Questionnaire
NIHMS2078154-supplement-Final_TSK-Heart-A_Questionnaire.pdf (181KB, pdf)
Appendix 1
NIHMS2078154-supplement-Appendix_1.pdf (205.9KB, pdf)

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