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Abstract

Background

Evidence on the psychometric properties of satisfaction scales in telerehabilitation is limited, especially in specific populations such as caregivers of children.

Objective

To determine the psychometric properties of a physiotherapy care satisfaction scale using telerehabilitation in caregivers of pediatric patients during the COVID-19 pandemic.

Methods

A total of 155 caregivers were evaluated between June and December 2020. Approximately 91% (141) were women. Evidence of content validity for the scale was obtained through evaluation by three expert judges, who confirmed the adaptation of the University of Washington Telemedicine Patient Satisfaction Survey, in which the word “telemedicine” was replaced with “telerehabilitation” and “physician” with “physical therapist.”

Results

For the confirmatory factor analysis, two models were tested. The first one-factor model with nine items did not fit satisfactorily based on the goodness-of-fit indices (χ²/df = 13.96, comparative fit index [CFI] = 0.963, non-normed fit index [NNFI] = 0.951, root mean square error of approximation [RMSEA] = 0.290 [0.265, 0.316], and standardized root mean square residual [SRMR] = 0.178). In contrast, the second one-factor model, which involved respecification of Items 6 and 7, was considered acceptable (χ²/df = 1.60, CFI = 0.998, NNFI = 0.998, RMSEA = 0.062 [0.021, 0.096], and SRMR = 0.057). Reliability was acceptable, with a value of 0.888. Additionally, network analysis confirmed the direct relationship between the items, with Item 7 showing the greatest strength centrality.

Conclusion

The instrument demonstrated sufficient evidence of validity and reliability in the Peruvian context, supporting its use with pediatric patients.

Keywords

COVID-19 pediatrics patient satisfaction reproducibility of results telerehabilitation

Introduction

During the COVID-19 pandemic, the implementation of mobility restrictions and social distancing measures posed significant challenges to accessing medical and therapeutic services. In this context, telerehabilitation (TR) emerged as a key alternative for maintaining the continuity of medical services, including physiotherapy care.¹ According to the Pan American Health Organization (PAHO), this model of care facilitates continuity of care for patients through remote consultations, ensuring greater protection for vulnerable groups, including those with physical and functional limitations.²

In Peru, the adoption of TR has grown steadily. According to EsSalud's National Telemedicine Center, the number of TR sessions has significantly increased, reaching 3200 sessions per year and covering various areas of care.^3,4 The effectiveness of TR in pediatric patients relies on tools that enable physical therapists to conduct personalized assessments, monitor patient progress, and provide real-time feedback.⁵ This approach ensures that patients can continue their rehabilitation process without the need for the therapist's physical presence.

Existing evidence suggests that TR is effective for children requiring physical therapy for various health conditions.⁶ In this scenario, the role of caregivers, such as parents or guardians, becomes pivotal. Their active involvement and positive perception of the care provided are essential, as these factors can significantly influence clinical outcomes, particularly for children with neurodevelopmental conditions.⁷

Patient and caregiver satisfaction is a critical indicator of the quality and effectiveness of TR interventions. Several studies have reported high levels of satisfaction with TR, assessed through various measurement instruments.^8,9 One widely used instrument, adapted to Spanish, is the UW Telemedicine Patient Satisfaction Survey, which is easy to administer and consists of a small number of items.^10,11 In the context of TR, this scale demonstrates strong internal consistency, with a Cronbach's alpha coefficient of 0.805, indicating its reliability and suitability for different study contexts.^12,13

Despite the widespread use of this instrument in other countries, its application and psychometric evaluation in Peru remain unexplored. Given its demonstrated validity and reliability in assessing caregiver satisfaction for pediatric patients with disabilities, further analysis is necessary to enhance its methodological contribution. Such an analysis could validate the instrument specifically for the field of physical therapy in Peru, where its psychometric properties have yet to be assessed.

Therefore, this study aims to determine the psychometric properties of a scale measuring satisfaction with physiotherapy care delivered via TR to caregivers of pediatric patients during the COVID-19 pandemic.

Materials and method

Design

The study employed an instrumental design,¹⁴ as it focused on reviewing the psychometric properties of a measurement instrument. In addition, the study was quantitative, as it involved the analysis of numerical data. Additionally, data were collected using a single telephone survey, meaning all data were gathered at a single point in time.

Participants

The study population consisted of 280 caregivers of pediatric patients at Clínica San Juan, a private clinic in Lima. The patients, diagnosed with orthopedic and neurological pathologies, received TR care via videoconference, with an average of 10 sessions, one per week, each lasting approximately 30 min. From this population, a sample of 155 participants was obtained. They completed the virtual questionnaire via Google Forms after attending the 10 TR sessions, with data collected between June and December 2020. Among those surveyed, 91% (141) were women; 56.1% (87) were aged between 30 and 39 years; 37.4% (58) had completed secondary school; and 23.2% (36) lived in central Lima. Additionally, the sample size adhered to Kline's¹⁵ criteria, which suggest that for a factorial analysis, the minimum sample size should be 10 participants per item on the instrument or more than 100 participants. The sampling method was non-probabilistic and based on convenience, as participants met the following inclusion criteria: caregivers of legal age, caregivers of pediatric patients who received care between June and December 2020, caregivers who voluntarily agreed to participate, and caregivers who completed the survey in full. Exclusion criteria included caregivers of pediatric patients who did not answer the phone call, caregivers who had changed their phone number, and caregivers who were responsible for more than one child at a time.

Instrument

The Patient Satisfaction Survey on Physiotherapy Care through Telerehabilitation (ESPAFT) was adapted from the University of Washington's Telemedicine Patient Satisfaction Survey. This instrument has been translated into Spanish and is freely available, as documented in several studies.^10,12,13 In this adaptation, the term “telemedicine” was replaced with “telerehabilitation.” The instrument consists of nine questions that assess patient satisfaction during TR, using a Likert-type scale with five response options: very dissatisfied (1), dissatisfied (2), neutral (3), happy (4), and very happy (5). Additionally, the original instrument includes a closed question regarding the continuity of care through TR, with “yes” or “no” answers, as well as two open-ended questions inviting suggestions for improving care and any additional comments on the service provided (Supplemental File 1).

Procedure

The instrument was adapted from the University of Washington Telemedicine Patient Satisfaction Survey, with “telemedicine” changed to “telerehabilitation” and “physician” replaced by “physical therapist.”

To demonstrate content validity, the instrument was evaluated by a panel of experts. Three experts in the field, who were research advisors at a national rehabilitation institute and were pursuing a Master's degree in Biomedical Informatics in Global Health, assessed the instrument based on criteria such as objectivity, clarity, consistency, relevance, coherence, methodology, and sufficiency. They also evaluated the survey items for their representativeness and adequacy to the construct under study, resulting in an Aiken's V of 0.83, indicating adequate agreement among the judges.

Data analysis

The data analysis was conducted in four stages. In the first stage, a descriptive analysis of the nine ESPAFT items was performed, calculating values such as mean (M), standard deviation (SD), and the percentage distribution of responses for each item. This was done to assess the presence of possible floor or ceiling effects. Additionally, item–test correlations were calculated to evaluate homogeneity (r_i−t< 0.20) and multicollinearity (r_i−t> 0.95).¹⁵

In the second stage, the internal structure of the ESPAFT was assessed using confirmatory factor analysis (CFA) with a weighted least square mean and variance adjusted (WLSMV) estimator and a polychoric correlation matrix, given the ordinal nature of the scale. The fit indices used to evaluate the factor structure were as follows: χ²/df < 5, comparative fit index (CFI) ≥ 0.95, non-normed fit index (NNFI) ≥ 0.95, root mean square error of approximation (RMSEA) ≤ 0.06, and standardized root mean square residual (SRMR) ≤ 0.08. Two models were tested: a nine-item single-factor model (M1) and a re-specified single-factor model adjusting Items 6 and 7 (M2).

Consequently, in the third stage, the internal consistency reliability of the M2 model was calculated using McDonald's omega coefficient, which is evaluated based on the factor loadings of the internal structure. Values above 0.70 are considered acceptable.¹⁶ Additionally, the average variance extracted should account for more than 50% of the total variance.¹⁷

Finally, in the fourth stage, a psychometric network analysis was conducted for the nine items of the ESPAFT. In this analysis, each item is represented as a node (depicted as circles), and the relationships between items, called edges, are represented by lines connecting the nodes. These lines are color coded: blue for positive relationships and red for negative relationships.¹⁸ To conduct the network analysis in this study, the EBICglasso estimator was used, as it helps identify the most significant connections between nodes. Strength centrality was employed to estimate the indicator with the greatest interconnection with other items (Figure 1).¹⁹

Figure 1.

Psychometric network analysis and strength centrality of the ESPAFT. (a) The network analysis of the items that make up the instrument. (b) The strength centrality analysis for each item. p1 = How well did the physical therapist explain your child's treatment plan?; p2 = How well did this service meet your child's physical therapy care needs?; p3 = Overall quality of care your child received; p4 = How easy was it to communicate with the physical therapist through this medium?; p5 = How well did you understand the guidance provided by the physical therapist?; p6 = How clearly could you see the image on the screen?; p7 = How clearly could you hear what the physical therapist was saying?; p8 = How courteous and attentive were the clinic's providers?; p9 = Your overall impression of communicating with the physical therapist in this way.

The open-access software R Studio (v. 3.6.0) was used to report the descriptive results of the items, assess validity based on the internal structure, and evaluate reliability using McDonald's omega coefficient. The open-access software JASP (v. 0.17.2.1) was used to analyze the structure of the ESPAFT network and its centrality.

Ethical considerations

The research was reviewed and approved by the Institutional Research Ethics Committee of BLINDED (Resolution N° 000071-20210000011). Written informed consent was obtained from each participant in accordance with the Declaration of Helsinki. Consent was collected through a question included in the Google Forms virtual survey.

Results

Sociodemographic results

The sociodemographic results of the 155 caregivers surveyed indicate a higher proportion of male respondents (53%), caring for children older than 6 years (26.5%) and with congenital hip deformities (39.4%). For a detailed visualization of the results, refer to Table 1.

Table 1.

Sociodemographic results of the sample.

Variable	Category	N	%
Sex	Male	82	53
	Female	73	47
Age (years)	<2	18	11.6
	2	30	19.4
	3	24	15.5
	4	17	11.0
	5	12	7.7
	6	13	8.4
	>6	41	26.5
Diagnostic	Congenital hip deformities	61	39.4
	Cerebral palsy	26	16.7
	Disorders of muscle tone in newborns	12	7.7
	Other congenital musculoskeletal deformities	9	5.8
	Congenital foot deformities	9	5.8
	Other specific joint disorders	8	5.2
	Others	30	19.4
Patient's condition for physical therapy	Continuing	136	87.7
Patient's condition for physical therapy	New	19	12.3
	Continuing	93	60
	New	62	40

Descriptive analysis

Table 1 presents the descriptive analysis of each ESPAFT item, with the highest score observed for Item 5 (M = 4.13, SD = 0.72) and the lowest for Item 6 (M = 3.72, SD = 0.74). Additionally, a higher prevalence of the highest response options (happy and very happy) was noted across all items, without evidence of a ceiling effect. Finally, the item–test correlations ranged from 0.40 to 0.75, indicating adequate homogeneity (r_i−t < 0.20) and ruling out multicollinearity (r_i−t < 0.95).¹⁵

Evidence of validity based on internal structure

To demonstrate evidence of validity based on the internal structure of the ESPAFT, CFA with a WLSMV estimator was used, given the ordinal nature of the items.²⁰ The original model, consisting of nine items under a unidimensional framework, did not show entirely satisfactory fit indices (χ²/df = 13.96, CFI = 0.963, NNFI = 0.951, RMSEA = 0.290 [0.265, 0.316], and SRMR = 0.178). For this reason, the modification indices were reviewed, revealing high values between Items 7 and 6 (MI = 335.151). Consequently, a second model was tested with the re-specification of these items, resulting in acceptable fit indices (χ²/df = 1.60, CFI = 0.998, NNFI = 0.998, RMSEA = 0.062 [0.021, 0.096], and SRMR = 0.057) (see Table 2).

Table 2.

Descriptive analysis of the items.

Items	M	SD	Min.	Max.	Percentage of responses					r _i−t
Items	M	SD	Min.	Max.	1	2	3	4	5	r _i−t
p1	4.1	0.76	1	5	0.6	1.9	14.8	52.3	30.3	0.71
p2	3.83	0.89	1	5	0.6	8.4	20.0	49.0	21.9	0.72
p3	3.96	0.81	2	5	0	5.2	19.4	50.3	25.2	0.69
p4	3.94	0.9	1	5	1.9	5.8	14.2	52.3	25.8	0.75
p5	4.13	0.72	1	5	0.6	2.6	8.4	60.0	28.4	0.74
p6	3.72	0.74	1	5	0.6	6.5	21.9	62.6	8.4	0.54
p7	3.74	0.75	1	5	0.6	6.5	20.6	62.6	9.7	0.57
p8	4.05	0.76	1	5	0.6	3.9	11.0	59.4	25.2	0.4
p9	4.01	0.86	1	5	0.6	5.2	16.8	47.7	29.7	0.71

M: mean; SD: standard deviation; Min: minimum response score; Max: maximum response score; 1: very dissatisfied; 2: dissatisfied; 3: neutral; 4: satisfied; 5: very satisfied; r_i−t: item–test correlation.

Table 3 shows that the nine items of the ESPAFT had factor loadings ranging from 0.506 to 0.877, which are considered acceptable as they exceed the 0.30¹⁵ threshold and are statistically significant (p < 0.05). Additionally, the instrument demonstrated considerable internal consistency, as the omega coefficient exceeded 0.70.¹⁶ In terms of variance explained, the single-factor model of the ESPAFT accounted for 57.4% of the total variance.

Table 3.

Fit indices of the proposed models.

Models	χ ²	df	χ²/df	CFI	NNFI	RMSEA (95% CI)	SRMR
M1	376.99	27	13.96	0.963	0.951	0.290 (0.265, 0.316)	0.178
M2	41.61	26	1.60	0.998	0.998	0.062 (0.021, 0.096)	0.057

M1: general model; M2: general model re-specified in Items 6 and 7. χ²: chi-square; df: degrees of freedom; χ²/df: chi-square divided by degrees of freedom; CFI: comparative fit index; NNFI: non-normed fit index; RMSEA: root mean square error of approximation with 95% confidence interval in brackets; SRMR: standardized root mean square residual.

Psychometric network analysis

The EBICglasso estimator was used to conduct the network analysis of each item. The analysis revealed direct relationships between the items, with the strongest connections observed between p7-p6 (r = 0.82), followed by p5-p4 (r = 0.35) and p1-p3 (r = 0.32). In terms of centrality strength, p7 showed the highest score (0.854), followed by p1 (0.605) and p5 (0.516), confirming their strong interconnection with other items in the network.

Discussion

The advancement of technology and the impact of the COVID-19 pandemic have enhanced the accessibility of health services, reducing transportation costs, optimizing time, facilitating physiotherapy care for remote populations, and increasing the involvement of patients and caregivers in their treatment.^21,22

To better assess the perception of patient care quality, it is essential to use tools that evaluate these experiences. These tools may include qualitative methods, such as interviews, focus groups, and follow-up surveys, or quantitative methods, such as questionnaires and scales that are quick to administer.²³ Having validated instruments in the healthcare field is essential to ensure the quality and effectiveness of care.²² Validation involves rigorous processes to ensure that a tool provides accurate, consistent, and reliable measurements, guaranteeing that the results can be replicated across different studies or programs to improve the quality standards of healthcare in TR.²⁴ Additionally, the use of this instrument can help detect potential issues in the implementation of TR treatments, assess the impact of technology in healthcare, and highlight the need to ensure the effectiveness of remote interventions.^25,26

In recent years, there has been a rise in surveys evaluating satisfaction with TR; however, few of these measures are specifically targeted to the field of physical therapy.^27,28 Given the practicality and efficiency of questionnaires, it is essential that they are straightforward and include a carefully selected set of questions. These questions should identify the strengths and weaknesses of the care provided by the physical therapist, as well as its impact on the patient's improvement and well-being.²⁹ Furthermore, it is important that the questionnaire reflects the user's perception of the professional's technical competence.²³ For this reason, the present study aimed to determine the psychometric properties of a scale measuring satisfaction with physiotherapy care delivered via TR in caregivers of pediatric patients during the COVID-19 pandemic.

First, the content validity of the ESPAFT was assessed using expert judgment, which confirmed the clarity and representativeness of each item as adapted from the medical to the physiotherapeutic field. These findings support the theoretical acceptance of each item, allowing the application of this instrument in future research on TR in physiotherapy. Although there is limited research specifically validating the UW Patient Satisfaction Survey, some studies have utilized it in various contexts.^10,12,13 On the other hand, there are proposals aimed at designing specific instruments to measure satisfaction with TR in the physiotherapeutic setting. An example is the Telerehabilitation Satisfaction Questionnaire (TrSQ), a brief 11-item instrument designed for neurological patients with stroke.³⁰ This questionnaire demonstrated adequate content validity, as evaluated by five physical therapists with experience in TR.³⁰ Another brief instrument for measuring satisfaction with physical therapy care is the Basic Physical Therapy Satisfaction Questionnaire, designed for adult patients with pain. It consists of five items developed by clinical experts.³¹ However, this instrument has not undergone validation by expert judges and requires adaptation for use in a virtual context.

The instrument's structure ESPAFT was analyzed using CFA to provide evidence of validity based on the internal structure. The results indicated that the unidimensional model with nine items did not fit satisfactorily across all fit indices, particularly in the error measures (RMSEA and SRMR). For this reason, a second unidimensional model with re-specified items (Items 6 and 7) was considered, which presented satisfactory fit indices. This suggests that revising and modifying items may be necessary to improve the internal validity of an instrument, highlighting the importance of detailed analysis in the validation process of measurement tools.³² The factor loadings of the ESPAFT exceeded 0.50 for all items, demonstrating an adequate item structure. This indicates that each item has a strong correlation with the factor it measures, thereby validating its contribution to the assessed construct.^20,30 Similarly, the TrSQ demonstrates adequate evidence of internal structure, with factor loadings above 0.40 for all items.

In terms of reliability, an omega coefficient of 0.888 was deemed acceptable, indicating that the results obtained by ESPAFT are consistent across participants in the study. This also ensures that there is no significant variation influenced by random factors or procedural inconsistencies.¹⁶ Consequently, it can be concluded that ESPAFT can establish standard procedures for evaluating the satisfaction of caregivers in physical therapy. Another study found that the original version of the instrument demonstrated adequate reliability, as evidenced by Cronbach's alpha, excluding Item 6. This was observed in a sample of Chilean patients of all ages (children, adults, and older adults) who received physical therapy via videoconference (Table 4).¹²

Table 4.

Factor loadings and reliability of the ESPAFT.

Items	β	95% CI		p
Items	β	Lower	Upper	p
1. How well did the physical therapist explain your child's treatment plan?	0.877	0.827	0.926	<0.001
2. How well did this service meet your child's physical therapy care needs?	0.839	0.776	0.902	<0.001
3. Overall quality of care your child received.	0.832	0.775	0.888	<0.001
4. How easy was it to communicate with the physical therapist through this medium?	0.866	0.814	0.917	<0.001
5. How well did you understand the guidance provided by the physical therapist?	0.875	0.828	0.921	<0.001
6. How clearly could you see the image on the screen?	0.521	0.415	0.627	<0.001
7. How clearly could you hear what the physical therapist was saying?	0.566	0.468	0.663	<0.001
8. How courteous and attentive were the clinic's providers?	0.506	0.384	0.627	<0.001
9. Your overall impression of communicating with the physical therapist in this way.	0.798	0.736	0.86	<0.001
Omega coefficient = 0.888.
Analysis of variance explained = 0.574

Finally, the network analysis revealed that Item 7 had the highest strength centrality, indicating a stronger relationship within the network. The strongest relationship was observed between Items 7 and 6, suggesting that effective physiotherapy care via TR largely depends on adequate audio and image quality, as supported by studies.^33,34 These aspects enable the assessment of movement, posture, exercise performance, the delivery of clear and precise instructions, demonstrations, emotional support, and motivation for the patient, as well as multisensory interaction that can enhance learning and adherence to treatment. Consequently, any issues with these technical aspects will directly impact treatment efficacy and overall satisfaction with TR.^12,35

Limitations

As limitations, we identified the lack of previous studies on the review and adaptation of the instrument's psychometric properties at the national level. Additionally, only one instrument was used to assess the psychometric properties, which limited our ability to demonstrate evidence of concurrent validity or validity based on the relationship with other variables. On the other hand, this study was conducted exclusively with a pediatric population diagnosed with neurological and orthopedic pathologies. Therefore, it is recommended that future research includes more homogeneous populations in terms of diagnostic criteria to enhance the generalizability and representativeness of the results. Additionally, it is recommended to consider the following aspects: the use or adaptability of available resources during virtual therapy sessions, the feasibility of using the platform, and the visual technical support, such as camera focus, for effective monitoring by the physiotherapist.

Conclusion

This study contributes to the evaluation of physiotherapy satisfaction via TR through a simple, valid, and reliable instrument (ESPAFT) in Spanish, which can also be administered online. Furthermore, the use of the validated ESPAFT in TR will not only guarantee the quality of care provided to patients but also ensure that the practices adopted are grounded in robust scientific evidence. This is especially important in a field where face-to-face interaction with pediatric caregivers is limited, and the accuracy of assessments and treatments heavily depends on the reliability of the tools used.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251315299 - Supplemental material for Psychometric properties of a physiotherapy care satisfaction scale using telerehabilitation in caregivers of pediatric patients during the COVID-19 pandemic

Supplemental material, sj-docx-1-dhj-10.1177_20552076251315299 for Psychometric properties of a physiotherapy care satisfaction scale using telerehabilitation in caregivers of pediatric patients during the COVID-19 pandemic by Jessica Liz Gonzalez Ccosi, Deysi Pedraza Ricra, Miguel Basauri-Delgado and Jacksaint Saintila in DIGITAL HEALTH

Footnotes

Acknowledgements

The authors extend their gratitude to all the caregivers who voluntarily participated in this study. We also thank the clinic management for permitting us to conduct the research.

Contributorship

JLGC and DPR designed the study. JLGC and DPR performed literature searches and provided summaries of previous research studies. MB-D performed the statistical analysis and interpretation of the data. JLGC, DPR, and JS wrote the first draft of the article. All read and approved the final manuscript.

Data availability

Data supporting the conclusions of this research will be made available in coordination with the corresponding author.

Dewrests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

The research was reviewed and approved by the Institutional Research Ethics Committee of Universidad Nacional Mayor de San Marcos (Resolution No. 000071-20210000011).

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Guarantor

Informed consent

Additionally, written informed consent was obtained from each participant, in full compliance with the principles outlined in the Declaration of Helsinki.

ORCID iD

Jacksaint Saintila

Supplemental material

Supplemental material for this article is available online.

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