Journal Information
Vol. 98. Issue 1.
Pages 48-57 (01 January 2023)
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Vol. 98. Issue 1.
Pages 48-57 (01 January 2023)
Original Article
Open Access
Psychometric properties of the Spanish version of the Pediatric Quality of Life Inventory Family Impact Module (PedsQL FIM)
Propiedades psicométricas de la versión en castellano del Cuestionario Calidad de Vida Pediátrica Módulo de Impacto Familiar (PedsQL FIM)
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Javiera Ortegaa,b,
Corresponding author
javiera_ortega@uca.edu.ar

Corresponding author.
, Natalia Vázquezb,c, Imanol Amayra Carod, Florencia Assaloneb
a Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina [CONICET], Buenos Aires, Argentina
b Centro Investigaciones de Psicología y Psicopedagogía [CIPP], Facultad de Psicología y Psicopedagogía, Pontificia Universidad Católica Argentina, Buenos Aires, Argentina
c Fundación de Psicología Aplicada a Enfermedades Huérfanas [Fupaeh], Buenos Aires, Argentina
d Departamento de Psicología, Facultad de Ciencias de la Salud, Universidad de Deusto, Bilbao, Spain
Article information
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Abstract
Introduction

This study analysed the psychometric properties of the Spanish version of the Pediatric Quality of Life Questionnaire Family Impact Module (PedsQL FIM) in the Argentinian population.

Patients and Methods

The sample included 232 caregivers, of who 108 were parents of children with chronic diseases (mean, 9.54; standard deviation [SD], 4.43) and 124 parents of children in the general population (mean, 12.37; SD, 4.6).

Results

We assessed the validity of the instrument with the known-groups method, finding significant differences between the case and control groups in the overall and subscale scores (P < .01). We also assessed test validity by means of exploratory factor analysis, which yielded an 8-factor model that explained 74.03% of the variance. We assessed reliability with the Cronbach alpha and found a high internal consistency (α=0.95).

Conclusion

The PedsQL module proved to be a valid and reliable tool to assess the impact of a chronic paediatric condition on caregiver quality of life and family functioning.

Keywords:
Family
Quality of life
Validity
Reliability
Chronic disease
Resumen
Introducción

Este trabajo analiza las propiedades psicométricas de la versión en castellano del Cuestionario de Calidad de Vida Pediátrica Módulo de Impacto Familiar (PedsQL FIM) en población argentina.

Pacientes y Métodos

Se obtuvo una muestra de 232 cuidadores, 108 de niños con enfermedades crónicas (M=9,54, DE=4,43) y 124 de niños de población general (M=12,37, DE=4,6).

Resultados

La validez del instrumento se estudió a través del método de grupos contrastados, encontrando diferencias significativas en la escala total y subdimensiones de la escala (p<0,01). A su vez, se realizó un análisis factorial exploratorio en el que se encontró un modelo de 8 factores explicando el 74,02% de la varianza total. La confiabilidad fue estudiada a través del Coeficiente Alfa de Cronbach y se encontró un valor alto de consistencia interna α=0,95.

Conclusiones

El instrumento PedsQL demostró ser una herramienta válida y confiable para estudiar el impacto que tiene una condición pediátrica crónica a nivel de la calidad de vida del cuidador y del funcionamiento familiar.

Palabras clave:
Familiar
Calidad de vida
Validez
Confiabilidad
Enfermedades crónicas
Full Text
Introduction

Chronic diseases have an impact that extends beyond the patient, affecting the entire household. In the case of paediatric chronic diseases, there is a transformation of the roles within the family, so that one member assumes the unofficial role of non-professional caregiver of the ill child. This caregiver role implies the reallocation of responsibilities within the family, shifts in supportive relationships and a reorganization of family dynamics. The parents handle care activities, support the child during hospitalizations and medical appointments and make decisions regarding treatment options.1

Due to the importance of caregivers in the care of children with chronic diseases, many studies have focused on assessing caregiver quality of life (QoL). The evidence shows that QoL decreases in parents caring for an ill child.1,2 Parents of children with chronic diseases report symptoms of anxiety, depression, stress and being overwhelmed.3–5

The Pediatric Quality of Life Inventory Family Impact Module (PedsQL-FIM) is one of the most widely used instruments for assessing the impact of chronic disease on families. It is used to assess health-related QoL in children aged 2–18 years. From this instrument, different modules have been developed to assess specific diseases or other factors related to the disease. Some of these modules have been validated for use in the Argentinean population.6,7 The PedsQL-FIM is the module that evaluates the impact of a medical condition in a child or adolescent at the family level. It explores the impact on the QoL of the primary caregiver in the family and on family functioning.8

The PedsQL-FIM has been adapted for different populations. The original version of the instrument was validated in San Diego in a sample of 23 families of children with chronic health conditions who either resided in a long-term care convalescent hospital or resided at home with their families. This initial study found a good internal consistency (Cronbach α, 0.82 and 0.97). The construct validity was assessed with the known-groups method and found that the instrument could differentiate parents of institutionalised children versus parents of children residing at home.8

We also identified 11 studies that assessed the reliability and validity of this instrument in different countries and populations. Overall, an adequate reliability was found in every population in which it was assessed, with Cronbach α values greater than 0.70 reported in all the reviewed studies.9–20

The validity of the PedsQL-FIM has been assessed chiefly through 3 methods. On one hand, construct validity was assessed by the known-groups method, the approach used originally by the authors of the instrument,8 evincing significant differences in PedsQL-FIM scores between parents of children in the general population and parents of children with chronic conditions, such as neurodevelopmental disorders,11 asthma or cardiac diseases,12 chronic gastrointestinal disorders15 and cancer.19 Other studies assessed the convergent/divergent validity of the instrument, studying its correlation with parameters such as the satisfaction with the care received,10 symptoms of autism,11 adult QoL15 and paediatric QoL, pain catastrophizing, functional impairment and emotional and behavioural problems.16 Last of all, a third group of studies used factor analysis, supporting the current 8-factor structure in every study12,13,15,17 except the one conducted in Malaysia.14 Two of the studies identified in the literature review only reported reliability results and did not assess the validity of the instrument.9,20

While the family impact module has been translated and validated for use in different countries, the nearest adaptation in the Latin American population is the Brazilian version. With the aim of obtaining an instrument that would enable the assessment of the impact of chronic conditions at the family level, we set out to assess the psychometric properties, reliability and validity of the PedsQL-FIM Spanish version, developed by the authors of this article, and thereafter evaluated by 6 raters from Spain and Argentina (Universidad de Deusto, Bilbao, Spain and Universidad Católica Argentina, Buenos Aires, Argentina).

Sample and methodsParticipants

The sample included 232 parents of children and adolescents aged 2–18 years with and without chronic diseases or conditions. Of this total, 108 were parents of children with chronic conditions (case group), and 124 parents of healthy children (control group). The chronic conditions that respondents reported on included genetic, neuromuscular and developmental disorders. Table 1 presents the characteristics of the parents and children that completed the instrument.

Table 1.

Distribution of the sample based on sociodemographic characteristics.

Sociodemographic variables  Case groupControl group
  n=108n=132
Caregiver         
Age, mean±SD  42.43±7.13    45.28±7.63   
Sex, n, %         
Male  8.30%  22  17.70% 
Female  99  91.70%  102  82.30% 
Educational attainment of respondent, n, %         
Elementary or unfinished secondary level  7.40%  1.60% 
Finished secondary level  23  21.30%  16  12.90% 
Started or finished tertiary level  25  23.10%  35  28.30% 
Started or finished university  50  46.30%  70  56.40% 
No answer  1.90%  0.80% 
Relationship to child, n, %         
Father  11  10.20%  22  17.70% 
Mother  89  82.40%  102  82.30% 
Other  7.40%  –  – 
Place of residence, n, %         
City of Buenos Aires  13  12%  27  21.80% 
Province of Buenos Aires  69  63.90%  94  75.80% 
Elsewhere in Argentina  26  24.10%  2.40% 
Child         
Age, mean±SD  9.54±4.43    12.37±4.6   
Sex, n, %         
Male  68  63%  64  51.60% 
Female  39  36.10%  60  48.40% 
Education, n, %         
Not in school  7.50%  1.60% 
Early childhood education centre  15  14.90%  16  12.90% 
Special education primary school  13  12%     
Primary school  45  41.70%  29  23.40% 
Secondary school  26  24.10%  76  61.30% 
Diagnosis, n, %         
Duchenne muscular dystrophy  25  23.10%  –  – 
Down syndrome  27  25%  –  – 
Autism spectrum disorder  13  12%  –  – 
X-linked hypophosphatemia  12  11.10%  –  – 
Other neuromuscular disease  11  10.20%  –  – 
Cystic fibrosis  8.30%  –  – 
Other chronic disease  11  10.20%  –  – 
Instrument

The PedsQL-FIM8 was designed to assess the impact of paediatric diseases on the family. This module was developed as a parent-report questionnaire. It consists of 36 items that assess the impact on the family through 8 main factors: physical functioning (6 items), emotional functioning (5 items), social functioning (4 items), cognitive functioning (4 items), communication (3 items), worry (5 items), daily activities (3 items) and family relationships (5 items). The answers are given on a 5-point Likert scale (0=it is never a problem, 4=it is almost always a problem) and are reversed scored and linearly transformed to a 0–100 scale (0=100, 1=75, 2=50, 3=25, 4=0), so that a greater score indicates better functioning. In addition to the overall family impact and subdimension scores, the instrument yields 2 summary scores: the caregiver health-related quality of life summary, which includes the physical, emotional, social and cognitive functioning dimensions, and the family summary, which includes daily activities and family relationships. In the original study, the instrument exhibited adequate reliability (α=0.82−0.97) and construct validity.

In this instance, we did not need to adapt the language of the original instrument. The research team of the Mapi Research Institute had already developed a Spanish version of the PedsQL-FIM for Argentina.21 The authors of this version had themselves suggested an evaluation of its psychometric properties.

The authors of the Spanish version8 gave their permission for us to publish the wording of the items in this article, featured in Table 2 (Spanish version), which presents the results of the factor analysis. However, it is still necessary to seek authorization from the authors to apply this instrument.

Table 2.

Distribution of items in factors.

  Physical functioning  Emotional functioning  Social functioning  Cognitive functioning  Communication  Worry  Daily activities  Family relationships 
1. I feel tired during the day  0.53               
2. I feel tired when I wake up in the morning  0.742               
3. I feel too tired to do the things I like to do  0.644               
4. I get headaches  0.762               
5. I feel physically weak  0.811               
6. I feel sick to my stomach  0.668               
7. I feel anxious    0.672             
8. I feel sad    0.712             
9. I feel angry    0.739             
10. I feel frustrated    0.713             
11. I feel helpless or hopeless    0.541             
12. I feel isolated from others      0.601           
13. I have trouble getting support from others      0.699           
14. It is hard to find time for social activities      0.682           
15. I do not have enough energy for social activities      0.641           
16. It is hard for me to keep my attention on things        0.792         
17. It is hard for me to remember what people tell me        0.79         
18. It is hard for me to remember what I just heard        0.867         
19. It is hard for me to think quickly        0.8         
20. I have trouble remembering what I was just thinking        0.865         
21. I feel that others do not understand my family’s situation          0.509       
22. it is hard for me to talk about my child’s health with others          0.68       
23. It is hard for me to tell doctors and nurses how I feel          0.715       
24. I worry about whether or not my child’s medical treatments are working            0.808     
25. I worry about the side effects of my child’s medications/medical treatments            0.708     
26. I worry about how others will react to my child’s condition          0.775       
27. I worry about how my child’s illness is affecting other family members          0.451       
28. I worry about my child’s future            0.572     
29. Family activities taking more time and effort              0.527   
30. Difficulty finding time to finish household tasks              0.861   
31. Feeling too tired to finish household tasks              0.774   
32. Lack of communication between family members                0.756 
33. Conflicts between family members                0.817 
34. Difficulty making decisions together as a family                0.761 
35. Difficulty solving family problems together                0.775 
36. Stress or tension between family members                0.759 

We collected the data by recruiting a non-probability sample. We obtained part of the sample from previous studies22,23 that sought to describe the QoL of children with neuromuscular diseases or disabilities and their families. Caregivers of children with chronic conditions were recruited through patient associations in Argentina, which disseminated the questionnaire to their members. The control group of caregivers of healthy children was recruited through chain-referral sampling using an online version of the questionnaire. Both groups were recruited at the same time. Data were anonymised and pooled, and the study adhered to the principles of research involving human subjects of the Declaration of Helsinki.24 we safeguarded the confidentiality of personal data, performing all statistical tests excluding the names of participants. We provided participants with an electronic mail address and a telephone number they could use to request any additional information or clarification as needed.

Statistical analysis

We conducted the statistical analyses with the software IBM SPSS Statistics, version 25 for Windows. To assess the psychometric properties of the instrument in the Argentinean population, we decided to use the same approach as the authors of the original instrument8 with the addition of factor analysis. To this end, we performed the Kaiser-Meyer-Olkin (KMO) and Bartlett tests to verify that the data were appropriate for factor analysis.25 Then we explored the components of the instrument using factor analysis with varimax rotation. We extracted factors with a factor loading greater than 0.40.26

Secondly, to strengthen the evidence on construct validity, we used the known-groups methods. We hypothesised that parents of children or adolescents with chronic diseases would report poorer quality of life compared to parents of children and adolescents in the general population. To determine whether the variables under study followed a normal distribution, we used the Kolmogorov-Smirnov test. Since the obtained p value was greater than 0.05, we applied the pertinent parametric statistics. To assess differences between means, we used the Student t test (significance: p < .05). We also calculated the effect size to assess the magnitude of these differences, establishing effect size categories of small (0.20) intermediate (0.50) and large (0.80). The analysis was performed with the statistical software G*Power.27

Then, we assessed the internal consistency of the instrument by calculating the Cronbach α. We considered internal consistency excellent if the value was greater than 0.90, good if it was greater than 0.80 and acceptable if it was greater than 0.70. Lastly, we used descriptive statistics (mean±standard deviation) to summarise the scores for the total instrument and its dimensions.

ResultsConstruct validity assessment

We used 2 methods to assess construct validity. First, we conducted a factor analysis of the instrument. In this analysis, we took into account the 108 cases of parents of children with chronic conditions. The result of the Bartlett sphericity test (χ2 [630]=3014.78; p<.001) was statistically significant, indicating an adequate correlation between the items. The KMO value was 0.86, which indicated the data was suitable for factor analysis. The principal component analysis with varimax rotation yielded a model with 8 factors that explained 74.02% of the total variance. Table 2 presents the item distribution and factor loading of these factors. Diverging from the composition of the original instrument, the items “I worry about how others will react to my child’s condition” and “I worry about how my child’s illness is affecting other family members” got loaded under the communication factor as opposed to the worry factor. The factor solution was orthogonal, although we found that some variables were represented in more than one factor, in which case we chose to group them in the factor in which they had the highest loading (“I feel helpless or hopeless”, “It is hard to find time for social activities”).

On the other hand, replicating the original PedsQL-FIM study, we applied the known-groups method. We analysed differences in the scores between the group of parents of children with chronic diseases and the group of parents of healthy children. We found significant differences in the total score (t [230] = –10.15; p=.00). Table 3 presents the mean, standard deviation, effect size statistics and the results of the Student t test for each dimension and subdimension of the PedsQL-FIM. The effect size was large for every dimension and subdimension with the exception of the family relationships and cognitive functioning, which had an intermediate effect.

Table 3.

Differences in total score, dimension and subdimension scores.

FIM scores  Case groupControl groupStudent t testEffect size 
  Mean  SD  Mean  SD  t (df)  p  d 
Total  59.96  21.17  108  86.31  18.38  124  −10.15 (230)  .00  1.11 
Caregiver HRQoL summary  62.16  23.43  108  86.75  18.15  124  −10.55 (230)  .00  1.01 
Family summary  61.46  25.71  108  84.53  21.55  124  −7.43 (230)  .00  0.88 
Physical functioning  59.65  28.59  108  85.15  20.52  124  −7.70 (191.12)  .00  0.92 
Emotional functioning  59.49  27.45  108  86.33  20.01  124  −8.40 (192.99)  .00  0.98 
Social functioning  61.28  30.17  108  88.51  19.91  124  −7.98 (180.95)  .00  0.95 
Cognitive functioning  55.93  23.98  108  70.60  16.61  124  −5.34 (186.75)  .00  0.67 
Communication  66.06  26.2  108  90.84  17.62  124  −8.32 (183.87)  .00  0.98 
Worry  31.09  26.21  108  80.51  29.99  124  −13.26 (230)  .00  1.32 
Daily activities  51.08  31.60  108  81.65  26.35  124  −7.94 (209.15)  .00  0.94 
Family relationships  67.69  29.07  108  86.25  21.42  124  −5.47 (194.32)  .00  0.69 
Assessment of reliability

To assess the reliability of the instrument, we analysed its internal consistency by calculating the Cronbach α. We calculated values for the total sample and for each group for the total score and the dimension scores. We found excellent levels of internal consistency in the parameters under study, with an α of 0.97 for the total score in the total sample, an α of 0.95 for the case group and of 0.97 for the control group. In addition, we verified that the α coefficient did not improve in any case by eliminating any of the elements. Table 4 presents the Cronbach α coefficients for each dimension and study group. All dimensions exhibited good internal consistency with coefficients greater than 0.70, with the exception of the worry subdimension in the case group.

Table 4.

Cronbach alpha coefficients for the dimensions of the PedsQL Family Impact Module.

Dimension  Total sample  Case group  Control group 
Total  0.97  0.95  0.98 
Caregiver HRQoL summary  0.96  0.94  0.96 
Family summary  0.93  0.89  0.94 
Physical functioning  0.91  0.89  0.90 
Emotional functioning  0.92  0.88  0.92 
Social functioning  0.88  0.84  0.87 
Cognitive functioning  0.94  0.94  0.94 
Communication  0.86  0.79  0.89 
Worry  0.89  0.69  0.89 
Daily activities  0.89  0.85  0.89 
Family relationships  0.94  0.93  0.95 
Mean and standard deviation of PedsQL-FIM scores

We calculated these statistics for the total module, dimension and subdimension scores in the total sample, the case group and the control group. The highest scores corresponded to the communication dimension in the total sample (mean=82.08; SD=23.99) and in the case and control groups. The lowest scores corresponded to the cognitive functioning score in the total sample (mean=63.77; SD=21.66) and the control group (mean=70.6; SD=16.61), and to the worry dimension in the case group (mean=31.09; SD=26.21). The mean total score in the overall sample was 74.04 (SD=23.69), compared to 59.96 in the case group (SD=21.17) and 86.31 in the control group (SD=18.31). Table 5 presents the scores for every dimension.

Table 5.

Descriptive analysis of the PedsQL-FIM dimensions in the Argentinean population.

FIM scores  Total sampleCase groupControl group
  Mean  SD  Mean  SD  Mean  SD 
Total  74.04  23.69  232  59.96  21.17  108  86.31  18.38  124 
Caregiver HRQoL summary  75.3  24.1  232  62.16  23.43  108  86.75  18.15  124 
Family summary  73.79  26.20  232  61.46  25.71  108  84.53  21.55  124 
Physical functioning  73.28  27.67  232  59.65  28.59  108  85.15  20.52  124 
Emotional functioning  73.84  27.25  232  59.49  27.45  108  86.33  20.01  124 
Social functioning  75.84  28.60  232  61.28  30.17  108  88.51  19.91  124 
Cognitive functioning  63.77  21.61  232  55.93  23.98  108  70.60  16.61  124 
Communication  79.31  25.23  232  66.06  26.2  108  90.84  17.62  124 
Worry  57.50  37.51  232  31.09  26.21  108  80.51  29.99  124 
Daily activities  67.42  32.65  232  51.08  31.60  108  81.65  26.35  124 
Family relationships  77.61  26.87  232  67.69  29.07  108  86.25  21.42  124 
Discussion

The management of children with chronic conditions must take into account the impact of these conditions at the family level. Our study contributes information about the psychometric properties of the PedsQL Family Impact Module, which can be used to assess the impact of a condition on the QoL of the caregiver and on family functioning.

Our study adds to previous works that have evaluated the psychometric properties in other countries: the United States, Malaysia, Jordan, Ethiopia, Brazil, China, Turkey and Croatia.9–20 It is also the first to assess the reliability and validity of the Spanish version of the PedsQL-FIM.

Our study applied the methodology of the original study of the PedsQL-FIM8 and went one step further with the performance of exploratory factor analysis. This analysis confirmed the 8-factor model proposed by the authors of the original instrument8 and by previous studies that have analysed its factor composition.12–14 To date, only one study has not found an 8-factor model, but a 6-factor composition.15 The difference we found in this study compared to the original instrument is that 2 items in the Spanish version, previously allocated to the worry subdimension, were reallocated to the communication subdimension because their loadings were higher in the latter. Isa et al.14 also reported issues with some of the items int eh worry subdimension, and opted to remove 2 items from this scale.

On the other hand, the module was able to discriminate between parents of children with chronic conditions and parents of healthy children, both in the total score and in the dimension scores. This results were consistent with those reported in the previous literature, which has demonstrated not only that the PedsQL-FIM can differentiate between families with chronically ill versus healthy children,15 but also differentiate between parents with chronically ill children depending on the severity of the disease.11,12,19 Both of these results indicate that this instrument is valid.

In terms of reliability, the PedsQL-FIM has exhibited an excellent internal consistency in the Argentinean population, with values that were similar to those found for the original instrument (α=0.97; α=0.96; α=0.90). Only the α of the worry subdimension was under, although near, 0.70. This was also the case of the communication subdimension in the validation of the Brazilian and Turkish versions of the instrument.13,19

The scores obtained in every dimension showed that the QoL of both the main caregiver and the family were both significantly lower in the reports of parents of children or adolescents with chronic conditions, especially in relation to worry and daily activities. This finding was related to the changes in family dynamics that result from receiving a diagnosis and the subsequent burden added to the caregiver, which may be overwhelming.1,5

We ought to mention some of the limitations of the study. First, the age group that predominated in both groups was school-age children, with children in the control group being a little older. In the future, it may be convenient to select samples that are more homogeneous in their sociodemographic characteristics, in addition to recruiting parents of preschool-age children or adolescents to be able to compare the different age groups. Furthermore, our study did not take into account the severity of the chronic conditions in the sample. A second study could compare groups of parents of children with disease of different severity, as has been done by other authors,12,19 to ascertain whether the Spanish version of the PedsQL can detect differences based on disease severity. Also, while the KMO test showed that the data were suitable for factor analysis, the case group is not ideal for it given the number of items in the instrument. We would suggest performance of exploratory and confirmatory factor analysis in a larger sample. Lastly, it would also be useful for future studies to assess the test-retest reliability of the instrument by analysing the changes in the scores.

Our study makes a relevant methodological contribution. We present evidence on the reliability and validity of the PedsQL-FIM applied to the Argentinean population, although the translation to Spanish of the items would allow using this version in other countries, such as Spain. The availability of this module will allow a family-based approach to the management of paediatric chronic diseases, taking into account the key role of parents in care delivery as they support their children with chronic conditions.

Conflicts of interest

The authors have no conflicts of interest to declare.

References
[1]
M. Garcia Rodrigues, J.D. Rodrigues, A.T. Pereira, L.F. Azevedo, P. Pereira Rodrigues, J.C. Areias, et al.
Impact in the quality of life of parents of children with chronic diseases using psychoeducational interventions - A systematic review with meta-analysis.
[2]
L. Sikorová, R. Bužgová.
Associations between the quality of life of children with chronic diseases, their parents’ quality of life and family coping strategies.
Cent Eur J Nurs Midwifery, 7 (2016), pp. 534-541
[3]
R. Stremler, S. Haddad, E. Pullenayegum, C. Parshuram.
Psychological outcomes in parents of critically ill hospitalized children.
[4]
H. Sajjadi, M. Vameghi, M. Ghazinour, M. Khodaeiardekani.
Caregivers’ quality of life and quality of services for children with cancer: a review from iran.
Glob J Health Sci., 5 (2013), pp. 173-182
[5]
F. Toledano-Toledano, D. Luna.
The psychosocial profile of family caregivers of children with chronic diseases: a cross-sectional study.
[6]
M. Roizen, S. Rodríguez, G. Bauer, G. Medin, S. Bevilacqua, J.W. Varni, V. Dussel.
Initial validation of the Argentinean Spanish version of the PedsQLí 4. 0 Generic Core Scales in children and adolescents with chronic diseases: acceptability and comprehensibility in low-income settings.
Health and Qquality of Life Outcomes, 6 (2008), pp. 1-15
[7]
J. Mozzoni, S. Gómez, M.S. Monges, M.F. de Castro Pérez, M. Méndez, P. Lemme, et al.
Validation of the Pediatric Quality of Life Inventory™, Neuromuscular Module, version 3.0 in Spanish for Argentina.
[8]
J.W. Varni, S.A. Sherman, T.M. Burwinkle, P.E. Dickinson, P. Dixon.
The PedsQL Family Impact Module: preliminary reliability and validity.
Health Qual Life Outcomes [Internet]., 2 (2004), pp. 55
[9]
A. Ab Rahman, N. Mohamad, M.K. Imran, W.P.W. Ibrahim, A. Othman, A.A. Aziz, et al.
A preliminary study on the reliability of the Malay version of PedsQLTM Family Impact Module among caregivers of children with disabilities in Kelantan, Malaysia.
[10]
E. Al-Gamal, T. Long.
Psychometric properties of the Arabic version of the PedsQL Family Impact Scale.
J Res Nurs [Internet]., 21 (2016), pp. 599-608
[11]
A. Borissov, I. Bakolis, B. Tekola, M. Kinfe, C. Ceccarelli, F. Girma, et al.
Adaptation and validation of two autism-related measures of skills and quality of life in Ethiopia.
Autism [Internet]., (2021), pp. 1-14
[12]
R. Chen, Y. Hao, L. Feng, Y. Zhang, Z. Huang.
The Chinese version of the Pediatric Quality of Life InventoryTM (PedsQLTM) Family Impact Module: cross-cultural adaptation and psychometric evaluation.
Health Qual Life Outcomes [Internet]., 9 (2011), pp. 16
[13]
K.P. Gürkan, Z. Bahar, C. Çapık, N.G. Aydoğdu, A. Beşer.
Psychometric properties of the Turkish version of the pediatric quality of life: the family impact module in parents of children with type 1 diabetes.
Child Health Care [Internet]., (2019), pp. 1-13
[14]
S.N.I. Isa, I. Ishak, A.A. Rahman, N.Z.M. Saat, N.C. Din, S.H. Lubis, et al.
A psychometric evaluation of the Malay version of PedsQLTM family impact module among caregivers of children with learning disabilities.
KnE life sci [Internet], 4 (2018), pp. 288
[15]
R. Knez, D. Stevanovic, A. Vulić-Prtorić, I. Vlašić-Cicvarić, M. Peršić.
The Croatian version of the pediatric quality of life inventory (PedsQLTM) family impact module: cross-cultural adaptation and psychometric evaluation.
J Child Fam Stud [Internet]., 24 (2015), pp. 363-371
[16]
K.E. Jastrowski Mano, K.A. Khan, R.J. Ladwig, S.J. Weisman.
The impact of pediatric chronic pain on parents’ health-related quality of life and family functioning: reliability and validity of the PedsQL 4.0 Family Impact Module.
J Pediatr Psychol [Internet], 36 (2011), pp. 517-527
[17]
G.R. Medrano, K.S. Berlin, W. Hobart Davies.
Utility of the PedsQLTM family impact module: assessing the psychometric properties in a community sample.
[18]
J.A. Panepinto, R.G. Hoffmann, N.M. Pajewski.
A psychometric evaluation of the PedsQL Family Impact Module in parents of children with sickle cell disease.
Health Qual Life Outcomes [Internet]., 7 (2009), pp. 32
[19]
A.C. Scarpelli, S.M. Paiva, I.A. Pordeus, J.W. Varni, C.M. Viegas, P.J. Allison.
The pediatric quality of life inventory (PedsQL) family impact module: reliability and validity of the Brazilian version.
Health Qual Life Outcomes [Internet]., 6 (2008), pp. 35
[20]
I. Tiberg, I. Hallstrom.
Translation and testing of a quality of life instrument: the PedsQL(TM) Family Impact Module/Oversattning och testning av ett livskvalitetinstrument: the PedsQL[TM] Family Impact Module.
Vard Nord Utveckl Forsk [Internet], 29 (2009), pp. 38-43
[21]
Pedsql.org. [citado el 1 de julio de 2022]. Disponible en: https://www.pedsql.org/translations.html.
[22]
Ortega J, Vázquez N. Calidad de vida en familias con enfermedades neuromusculares durante la pandemia por Covid-19 [Internet]. En: XIII Congreso Internacional de Investigación y Práctica Profesional en Psicología XXVIII Jornadas de Investigación XVII Encuentro de Investigadores en Psicología del MERCOSUR III Encuentro de Investigación de Terapia Ocupacional III Encuentro de Musicoterapia. Facultad de Psicología - Universidad de Buenos Aires; 2021. https://ri.conicet.gov.ar/bitstream/handle/11336/160118/CONICET_Digital_Nro.4314584f-bc3d-44fc-9ff0-77a667370063_A.pdf?sequence=2.
[23]
Vazquez V, Ruiz CA, Scavone K. Calidad de vida en familias con discapacidad durante la pandemia por COVID-19. En: XIII Congreso Internacional de Investigación y Práctica Profesional en Psicología XXVIII Jornadas de Investigación XVII Encuentro de Investigadores en Psicología del MERCOSUR III Encuentro de Investigación de Terapia Ocupacional III Encuentro de Musicoterapia. Facultad de Psicología - Universidad de Buenos Aires; 2021. https://www.aacademica.org/000-012/289.
[24]
J.L. Manzini.
Declaración DE Helsinki: principios éticos para la investigación médica sobre sujetos humanos.
[25]
H.F. Kaiser, J. Rice.
Little jiffy, Mark iv.
Educ Psychol Meas [Internet]., 34 (1974), pp. 111-117
[26]
P.J.F. Piera, C.A. Carrasco.
El análisis factorial como técnica de investigación en psicología.
[27]
J.M. Cárdenas Castro.
Potencia estadística y cálculo del tamaño del efecto en G*Power: complementos a las pruebas de significación estadística y su aplicación en psicología.
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