Relationships of PedsQL 4.0 generic core scales with other validated HRQoL instruments in braced idiopathic scoliosis patients: An age and curve severity-specific analysis

Abstract

Purpose: This study aims to investigate if the addition of PedsQL 4.0 generic core scales (PedsQL) with other validated instruments in day-to-day clinical context is feasible. Methods: Patients with idiopathic scoliosis who were undergoing brace treatment and aged 8–18 were asked to fill in the PedsQL 4.0 generic core scales, SRS-22r and EQ5D questionnaires at the spine specialist outpatient clinic and were followed up at 6 months by phone consultation. Questionnaire scores at baseline and follow-up were compared. Correlation of score changes of different questionnaires were tested. Results: A total of 232 patients (58 males, 174 females) were included. PedsQL school functioning scores and total scores at follow-up were lower than at baseline (p < 0.001), with greatest reductions in school functioning domain (range: −2.8 ± 7.0 to −5.1 ± 3.6). For those aged 13–18 years, changes of PedsQL school functioning correlated with changes of SRS total score (r = 0.20; p = 0.042). For patients with baseline major Cobb angle >30°, changes in PedsQL physical functioning correlated with SRS domain score changes in function (r = 0.25; p = 0.017), pain (r = 0.24; p = 0.021) and SRS total score (r = 0.26; p = 0.016). Both changes in PedsQL school functioning (r = 0.23; p = 0.032) and total score (r = 0.22; p = 0.043) correlated with SRS total score changes. Conclusion: PedsQL was sensitive to changes of HRQoL together with SRS-22r and EQ-5D-Y-5L questionnaires. Changes in PedsQL scores were related to changes in SRS-22r scores in patients of 13–18 years with more severe curves (>30°). PedsQL is recommended to be used in conjunction with validated instruments like SRS-22r with its ability to assess changes of patient’s school functioning and overall HRQoL. The short-term nature of our study highlighted the need for future research with a larger cohort and longer duration to investigate long-term HRQoL outcomes assessed by individual questionnaires.

Keywords

braces conservative treatment EQ-5D-Y-5L health-related quality of life HRQoL idiopathic scoliosis PedsQL 4.0 generic core scales spine SRS-22r

Introduction

Globally, idiopathic scoliosis remains as the most prevalent cause of spinal deformity in paediatric population.¹ Curve magnitude and curve progression play pivotal roles in clinical decision making and are crucial indicators of treatment success.² However, while radiological outcomes are essential to clinical practice, they could not capture the full extent of functional limitation endured by scoliosis patients, as idiopathic scoliosis can significantly impact various facets of daily life.^3–6 Individual perception on the impact of disease could be obtained through patient-reported outcome measures (PROMs), providing us with a more holistic understanding on patients' health status and their corresponding health-related quality of life (HRQoL), encompassing physical, emotional and social well-being.^7,8

Generic instruments assessing HRQoL include the Paediatric Quality of Life Inventory (PedsQL) 4.0 generic core scales and the youth version of the 5-level EuroQol-5-dimension (EQ-5D-Y-5L). These tools have previously demonstrated to be effective in reflecting HRQoL for paediatric populations, both at local and global levels.^5,9–11 In particular, PedsQL was shown to excel as a multidimensional instrument capable of covering important psychosocial aspects like school life, social relationships and emotional status, which were not covered in EQ-5D-Y-5L, and was even sensitive to paediatric patients with milder impairments.⁵ Scoliosis-specific tools include the refined Scoliosis Research Society 22-item (SRS-22r) questionnaire, which has also been validated for use in adolescent idiopathic scoliosis population.¹² Compared to SRS-22r, PedsQL emphasizes more on the school performance aspect, which may be potentially significant in paediatric population. However, the precise relationships between the changes detected by these instruments in idiopathic scoliosis patients remains uncertain. In the clinical context, there is a lack of guidelines specifying which of the aforementioned frequently employed HRQoL instruments clinicians should use and whether utilising a combination of different instruments would yield optimal results.

In Hong Kong, EQ-5D-Y-5L and SRS-22r have been used commonly to assess HRQoL in idiopathic scoliosis patients.^{4,6,9,13–15} We would like to determine if the addition of PedsQL to day-to-day clinical context could result in enhanced reflection of HRQoL status in patients. This study aims to investigate the relationship in the changes of scores between PedsQL 4.0 generic core scales with SRS-22r questionnaire and EQ-5D-Y-5L. Ultimately, the ability of PedsQL to act as an effective clinical instrument in monitoring HRQoL in idiopathic scoliosis and its feasibility for widespread clinical application is assessed. We would also like to assess if a combination of different questionnaires would yield different results based on age and disease severity. This could inform clinicians in determining the ideal patient cohorts for application of these questionnaires. It should also be noted that this is the first study utilizing the traditional Chinese translated version of PedsQL to reflect changes in HRQoL in idiopathic scoliosis.

Methods

Study design and patient population

This was a prospective study involving patients attending a tertiary paediatric orthopaedic clinic in Hong Kong. Recruitment of patients was done through consecutive sampling and included both juvenile idiopathic scoliosis (JIS: aged 4–9) and adolescent idiopathic scoliosis (AIS: aged 10–18) patients.¹⁶ Only patients who could communicate in Chinese by writing and speaking, and patients undergoing brace treatment were included. Exclusion criteria included patients diagnosed with other forms of non-idiopathic scoliosis (congenital, syndromal and neuromuscular), and those who had prior surgical intervention for idiopathic scoliosis. Patients with incomplete questionnaire responses and those lost to follow-up were excluded. Informed verbal consent was obtained for all patients. All patients satisfying our inclusion criteria were asked to complete a set of questionnaires at the outpatient clinic in person during August to December 2020: PedsQL 4.0 generic core scales, EQ-5D-Y-5L and SRS-22r questionnaire. Patients were followed up by phone interviews at 6 months subsequently with the same set of questionnaires, allowing us to evaluate for any changes in self-perceived HRQoL. A study duration of 6-month was chosen as it was a reasonable timeframe effective in capturing short-term HRQoL changes. Previous studies have demonstrated that study durations of 6-month or less were sufficient to highlight the responsiveness and validity of different HRQoL instruments^9,17,18. Ethics approval was obtained from the institutional review board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (IRB Ref: UW16-288) prior to study commencement.

Questionnaires

PedsQL 4.0 generic core scales

The traditional Chinese version of PedsQL 4.0 generic core scales was previously validated for use in patients with orthopaedic paediatric conditions.^5,11 It consisted of 4 domains and a total of 23 items. Domains were physical functioning (8 items), emotional functioning (5 items), social functioning (5 items) and school functioning (5 items). Patients answered each item by rating from “0” (never) to “4” (Almost always). Calculation of scores for each item was by multiplying patients' answer by 25 (i.e. score of 2 equals 50, 4 equals 100), while domain scores were calculated by average of each item within a domain (max: 100). Total score was calculated by average of all 23 items (max: 100). Patients were asked to respond to the 8–12 years old or 13-18 years old version according to their age at recruitment.

Refined scoliosis research society 22-item (SRS-22r) questionnaire

SRS-22r questionnaire consisted of 5 domains and a total of 22 items. The 5 domains were “function”, “pain”, “self-image”, “mental health” and “satisfaction with treatment”. The first 4 domains were compulsory domains and consisted of 5 items while “satisfaction of treatment” consisted of 2 items but was not compulsory. Patients chose one out of five answers available for each question and each answer was rated by a numerical scale of “1” to “5”. Domain scores (range: 1–5) were calculated by average of individual domain questions while total SRS score was calculated by averaging all items (maximum score: 5). SRS-22r is scoliosis-specific and has been validated for use in numerous scoliosis populations.^19,20

Youth version of the 5-level EuroQol-5-dimension (EQ-5D-Y-5L)

The EQ-utility scores were generated from the corresponding 5 dimensions, namely “Mobility”, “Looking After myself”, “Doing usual activities”, “Having pain or discomfort” and “Feeling worried/ sad/ unhappy”. Each dimension consisted of 5 responses from “1” (no problems) to “5” (extreme problems, or cannot do). Health status in each dimension was described on 5 levels (Y-5L)²¹ and the utility score was calculated based on population value set. Patients also rated their own health status on a visual analogue scale from 0 to 100 as the EQ VAS score. Use of EQ-5D-Y-5L has also been validated in various AIS population.^9,14

Study outcomes

Primary outcomes were changes of questionnaire scores at follow-up compared to baseline, which reflected changes in self-perceived HRQoL. Secondary outcomes were the relationships between changes of PedsQL with changes in SRS-22r and EQ-5Q-Y-5L scores. Score changes and relationships between questionnaires were assessed according to (1) specific PedsQL version used (8–12 and 13–18 version) and (2) baseline curve severity. It would be interesting to see if a combination of different questionnaires would yield different results based on age and disease severity. A threshold of major Cobb angle of 30° was selected as the cut-off as major curves >30° are at higher risk of progression.²²

Statistical analysis

Descriptive statistics regarding patient demographics were presented. The scores of PedsQL 4.0 (for each of the versions 8–12 years and 13–18 years), SRS-22r and EQ-5D-Y-5L questionnaires at baseline and follow-up were compared according to baseline curve severity. After testing the variables for normality, non-parametric correlations were tested using the Spearman’s rho correlation (r, correlation coefficient) test. Given the exploratory nature of our correlation analysis, specific adjustments to significance levels would inherently increase Type II errors (false negative) and potential relationships between questionnaires may be missed²³. Hence, unadjusted p-value significance levels were presented. The Mann-Whitney U test was used for comparison of non-parametric variables between groups. All statistical analyses were performed using SPSS statistics (v29.0.2.0; USA). Two-tailed significance was set at p-value <0.05.

Results

Patient demographics

A total of 232 patients (58 males, 174 females included; 29 excluded due to incomplete responses) were recruited, with 56 (24.1%) and 176 (75.9%) patients distributed the 8–12 years version and 13–18 years version of PedsQL respectively, and baseline mean age were 11.1 ± 0.9 and 13.7 ± 1.3 years. Mean changes of baseline major Cobb angle were −1.3 ± 7.9°and +0.94 ± 5.2° for 8 to 12 years and 13 to 18 years group respectively (p = 0.013). There were 145 patients (62.5%) with baseline curve ≤30° and 87 (37.5%) with baseline Cobb angle >30°. All patients were braced throughout the study duration, either they initiated bracing at first interview or continued the bracing regimen previously prescribed. Further patient details were illustrated in Table 1.

Table 1.

Patient demographics and characteristics.

Parameters	Total (n = 232)
Gender, n(%)
Male	58 (25.0%)
Female	174 (75.0%)
Distribution of patients for PedsQL, n (%)
Version 8 to 12 years	56 (24.1)
Version 13 to 18 years	176 (75.9)
Age, years (mean ± SD)
8 to 12 years	11.1 ± 0.9
13 to 18 years	13.7 ± 1.3
Standing height, cm (mean ± SD)
8 to 12 years	152.9 ± 10.9
13 to 18 years	160.8 ± 10.0
Sitting height, cm (mean ± SD)
8 to 12 years	82.2 ± 5.7
13 to 18 years	86.7 ± 5.3
Body weight, kg (mean ± SD)
8 to 12 years	40.8 ± 10.89
13 to 18 years	46.3 ± 10.2
BMI, kg/m (mean ± SD)
8 to 12 years	17.2 ± 3.6
13 to 18 years	17.6 ± 3.2
Initial curve severity, Cobb angle (mean ± SD (range))
8 to 12 years	26.8 ± 10.1 (1.5 to 49)
13 to 18 years	28.0 ± 9.2 (4.9 to 59)
Change in curve magnitude, Cobb angle (mean ± SD (range))
8 to 12 years	−1.3 ± 7.9 (−27.5 to 27)
13 to 18 years	0.94 ± 5.2 (−13.7 to 18.3)
Curve type, n(%)
Thoracic (T)	140 (60.3)
Thoracolumbar/ lumbar (T/TL)	92 (39.7)

n: number, %: percentage, SD: standard deviation, PedsQL: paediatric quality of life inventory, BMI: body mass index.

Questionnaire scores at baseline and follow-up

Across all groups, PedsQL school functioning scores and total scores at follow-up were lower than baseline (p < 0.001), with greatest reductions in school functioning domain (ranging from −2.8 ± 7.0 to −5.1 ± 3.6). It should be noted that the COVID lockdown was initiated halfway into our 6-month study, which could potentially pose a more significant impact on school performance. At 6-month follow-up, SRS domain scores were significantly lower than at baseline, except for function, pain scores in 8–12 patients with curves >30° and self-image score in patients with curves >30°. EQ-utility score differences were significant in all groups, ranging from −0.040 ± 0.069 to −0.064 ± 0.067 (p < 0.001) (Table 2).

Table 2.

Comparison of questionnaire scores at baseline and 6 months follow-up.

		Baseline	Follow-up	Difference	p-value*
8 to 12 years
N = 37	Major Cobb (≤30°)
	PedsQL
	Physical functioning	99.7 ± 1.4	99.2 ± 2.4	−0.4 ± 2.9	0.255
	Emotional functioning	99.5 ± 1.8	98.8 ± 5.1	−0.8 ± 5.5	0.404
	Social functioning	100.0 ± 0.0	100.0 ± 0.0	0.0 ± 0.0	1.000
	School functioning	99.3 ± 2.1	94.1 ± 3.0	−5.1 ± 3.6	<0.001 ^†
	Total score	99.6 ± 1.1	98.2 ± 2.2	−1.4 ± 2.4	<0.001
	SRS-22r
	Function	4.95 ± 0.11	4.70 ± 0.29	−0.25 ± 0.31	0.038 ^†
	Pain	4.89 ± 0.23	4.86 ± 0.15	−0.02 ± 0.29	0.022 ^†
	Self-image	3.92 ± 0.41	3.80 ± 0.27	−0.12 ± 0.46	<0.001 ^†
	Mental health	4.61 ± 0.40	4.10 ± 0.35	−0.51 ± 0.46	<0.001 ^†
	Satisfaction with treatment	4.30 ± 0.49	3.41 ± 0.54	−1.13 ± 0.25	<0.001 ^†
	Total score	4.58 ± 0.16	4.32 ± 0.17	−0.25 ± 0.21	<0.001 ^†
	EQ-5D-Y-5L
	EQ-utility	0.986 ± 0.034	0.922 ± 0.064	−0.064 ± 0.067	<0.001 ^†
	EQ VAS	87.4 ± 10.5	78.2 ± 16.4	−9.2 ± 18.4	0.008 ^†
N = 19	Major Cobb (>30°)
	PedsQL
	Physical functioning	99.5 ± 2.2	99.7 ± 1.4	0.2 ± 0.7	1.000
	Emotional functioning	97.4 ± 10.3	98.4 ± 3.7	1.0 ± 9.9	0.624
	Social functioning	96.6 ± 14.9	100.0 ± 0.0	3.3 ± 14.5	0.795
	School functioning	98.4 ± 6.9	95.8 ± 2.5	−2.8 ± 7.0	<0.001 ^†
	Total score	98.2 ± 7.7	98.6 ± 1.3	0.4 ± 6.9	<0.001 ^†
	SRS-22r
	Function	4.80 ± 3.71	4.79 ± 0.19	−0.01 ± 0.43	0.154
	Pain	4.94 ± 0.13	4.86 ± 0.16	−0.07 ± 0.19	0.130
	Self-image	3.84 ± 0.56	3.80 ± 0.25	−0.06 ± 0.54	0.435
	Mental health	4.52 ± 0.44	4.14 ± 0.38	−0.37 ± 0.64	0.004 ^†
	Satisfaction with treatment	4.05 ± 0.69	3.80 ± 0.34	−0.25 ± 1.04	0.011 ^†
	Total score	4.51 ± 0.25	4.35 ± 0.18	−0.16 ± 0.30	0.023 ^†
	EQ-5D-Y-5L
	EQ-uility	0.979 ± 0.362	0.941 ± 0.059	−0.040 ± .069	0.03 ^†
	EQ VAS	92.5 ± 8.0	81.3 ± 15.5	−9.7 ± 17.6	0.01 ^†
13 to 18 years
N = 108	Major Cobb (≤30°)
	PedsQL
	Physical functioning	99.5 ± 2.7	99.6 ± 2.1	0.1 ± 3.5	0.992
	Emotional functioning	99.1 ± 3.9	98.6 ± 3.4	−0.6 ± 5.2	0.003 ^†
	Social functioning	99.5 ± 2.7	99.9 ± 0.7	0.4 ± 2.5	0.392
	School functioning	98.3 ± 6.5	94.4 ± 4.2	−4.0 ± 8.4	<0.001 ^†
	Total score	99.2 ± 3.1	98.3 ± 1.7	−0.9 ± 3.7	<0.001 ^†
	SRS-22r
	Function	4.90 ± 0.16	4.69 ± 0.27	−0.22 ± 0.30	<0.001 ^†
	Pain	4.86 ± 0.27	4.83 ± 0.17	−0.04 ± 0.31	<0.001 ^†
	Self-image	3.88 ± 0.43	3.74 ± 0.21	−0.14 ± 0.44	0.002 ^†
	Mental health	4.51 ± 0.48	4.05 ± 0.40	−0.46 ± 0.62	<0.001 ^†
	Satisfaction with treatment	3.93 ± 0.71	3.38 ± 0.32	−0.67 ± 0.71	<0.001 ^†
	Total score	4.51 ± 0.22	4.29 ± 0.16	−0.22 ± 0.26	<0.001 ^†
	EQ-5D-Y-5L
	EQ-utility	0.986 ± 0.042	0.932 ± 0.064	−0.054 ± 0.073	<0.001 ^†
	EQ VAS	85.2 ± 11.9	81.0 ± 15.1	−4.2 ± 19.1	0.053
N = 68	Major Cobb (>30°)
	PedsQL
	Physical functioning	99.9 ± 0.5	99.9 ± 0.8	−0.0 ± 1.0	0.988
	Emotional functioning	99.0 ± 5.2	99.0 ± 2.7	0.0 ± 6.0	0.034 ^†
	Social functioning	99.7 ± 2.4	99.9 ± 0.6	0.2 ± 2.5	0.992
	School functioning	99.3 ± 3.1	95.0 ± 3.2	−4.4 ± 5.0	<0.001 ^†
	Total score	99.5 ± 2.2	98.6 ± 1.3	−0.9 ± 2.7	<0.001 ^†
	SRS-22r
	Function	4.87 ± 0.20	4.74 ± 0.23	−0.14 ± 0.32	<0.001 ^†
	Pain	4.88 ± 0.27	4.86 ± 0.13	−0.02 ± 0.29	0.002 ^†
	Self-image	3.75 ± 0.35	3.77 ± 0.20	0.02 ± 0.37	0.732
	Mental health	4.51 ± 0.44	3.99 ± 0.42	−0.52 ± 0.60	<0.001 ^†
	Satisfaction with treatment	4.01 ± 0.51	3.21 ± 0.37	−0.73 ± 0.72	<0.001 ^†
	Total score	4.48 ± 0.20	4.30 ± 0.19	−0.18 ± 0.26	<0.001 ^†
	EQ-5D-Y-5L
	EQ-utility	0.975 ± 0.058	0.932 ± 0.067	−0.043 ± 0.095	<0.001 ^†
	EQ VAS	81.0 ± 12.9	80.4 ± 13.9	−0.6 ± 18.3	0.824

*any significant differences of mean change of scores tested by Mann-Whitney U test.

^†statistical significance (p < 0.05).

PedsQL, paediatric quality of life inventory; SRS-22r, refined scoliosis research society 22-item; EQ-5D-Y-5L, youth version of 5-level EuroQol-5-dimension; SD, standard deviation.

Relationship between questionnaires

For 8–12 years, changes in PedsQL domains scores did not significantly correlate with SRS-22r domain and EQ scores. For 13–18 years, changes in PedsQL physical functioning scores correlated with changes of SRS function (r = 0.15; p = 0.041), while changes of PedsQL school functioning correlated with changes in total SRS score (r = 0.20; p = 0.042). In contrast, changes in PedsQL social functioning showed an inverse correlation with SRS pain score change (r = −0.29; p < 0.001). EQ-VAS changes correlated with both changes in PedsQL emotional functioning (r = 0.17; p = 0.025) and total score (r = 0.17; p = 0.023) (Table 3).

Table 3.

Correlation tests between change of PedsQL scores, with SRS-22r and EQ-5D-Y-5L scores.

	Changes in SRS-22r domains and total scores						Changes in EQ-5D-Y-5L
	Function	Pain	Self-image	Mental health	Satisfaction with treatment	Total SRS score	EQ-utility	EQ-VAS
Changes in PedsQL scores
8 to 12 years
Physical functioning	−0.21	−0.02	−0.13	0.02	0.43	−0.03	−0.06	−0.04
Emotional functioning	−0.05	0.12	0.09	0.24	0.43	0.25	−0.08	−0.03
Social functioning	0.22	−0.13	0.06	0.23	0.43	0.22	−0.07	−0.22
School functioning	−0.24	−0.05	−0.09	0.05	0.43	−0.04	0.07	−0.17
Total score	−0.26	0.02	−0.03	0.12	0.43	0.07	−0.02	−0.07
13 to 18 years
Physical functioning	0.15*	0.06	0.10	−0.06	0.07	0.09	0.03	0.05
Emotional functioning	−0.05	0.04	−0.04	−0.09	−0.09	−0.04	0.09	0.17*
Social functioning	0.02	−0.29**	−0.03	0.11	/	−0.05	0.14	0.03
School functioning	0.10	0.02	0.07	0.04	0.00	0.20*	0.13	0.13
Total score	0.08	0.01	0.02	−0.07	−0.05	0.05	0.11	0.17*

Statistical significance (*p < 0.05, **p < 0.001).

PedsQL, paediatric quality of life inventory; SRS-22r, Refined Scoliosis Research Society 22-item; EQ-5D-Y-5L, youth version of 5-level EuroQol-5-dimension.

For patients with baseline major Cobb angle ≤30°, changes in PedsQL social functioning showed an inverse relationship with SRS pain domain score change (r = −0.27; p = 0.001). No significant correlations existed between changes in other PedsQL domains, SRS-22r and EQ scores. For patients with baseline major Cobb angle >30°, changes in PedsQL physical functioning correlated with SRS function (r = 0.25; p = 0.017), pain (r = 0.24; p = 0.021) and total score (r = 0.26; p = 0.016). Changes in PedsQL social functioning correlated positively with change in SRS mental health (r = 0.22; p = 0.041) but inversely correlated with SRS pain (r = −0.24; p = 0.024). Both changes in PedsQL school functioning (r = 0.23; p = 0.032) and total score (r = 0.22; p = 0.043) correlated with SRS total score change. Changes of PedsQL and EQ scores were not correlated (Table 4).

Table 4.

Correlation tests between questionnaires score changes for patients according to curve magnitude at baseline.

	Changes in SRS-22r domains and total scores						Changes in EQ-5D-Y-5L
	Function	Pain	Self-image	Mental health	Satisfaction with treatment	Total SRS score	EQ-utility	EQ-VAS score
Changes in PedsQL scores
Major Cobbs (≤30°)
Physical functioning	−0.02	−0.03	0.01	−0.09	0.06	−0.01	−0.01	0.11
Emotional functioning	−0.08	0.06	−0.11	−0.10	0.06	−0.08	−0.04	0.11
Social functioning	0.16	−0.27**	−0.08	0.09	<0.01	−0.02	0.12	−0.01
School functioning	<0.01	−0.02	−0.01	0.01	<0.01	0.05	0.11	0.05
Total score	−0.04	−0.02	−0.03	−0.1	0.03	−0.04	0.03	0.09
Major Cobbs (>30°)
Physical functioning	0.25*	0.24*	0.08	0.09	0.24	0.26*	0.17	0.15
Emotional functioning	0.01	0.08	0.12	0.14	<0.01	0.18	0.10	−0.03
Social functioning	−0.09	−0.24*	0.07	0.22*	0.24	0.03	0.14	0.04
School functioning	0.05	0.04	0.09	0.19	0.24	0.23*	0.15	0.12
Total score	0.06	0.07	0.07	0.13	<0.01	0.22*	0.13	0.02

Statistical significance (*p < 0.05, **p < 0.001).

PedsQL, paediatric quality of life inventory; SRS-22r, refined scoliosis research society 22-item; EQ-5D-Y-5L, youth version of 5-level EuroQol-5-dimension.

Discussion

PedsQL demonstrated significant differences in school functioning and total scores between baseline and follow-up, along with SRS-22r and EQ-utility scores. Changes in PedsQL were found correlated with those in other well-established, validated instruments like SRS-22r and EQ-5D-Y-5L in more severe curves and in patients aged 13 to 18 years.

Comparisons between baseline and follow-up scores revealed that PedsQL was able to detect changes in HRQoL, especially with significant differences in its school functioning and total PedsQL scores. Generally, school functioning scores at 6-month follow-up were notably lower than at baseline, despite not reaching minimal clinically important difference (MCID).²⁴ However, such MCID value was defined in pediatric diabetic patients and none were established in scoliosis population. Question items in the PedsQL school functioning domain focus on patients’ learning ability, memory and concentration in class, as well as assessment of school attendance in relation to disease. Reduced postural tolerance in scoliosis patients may contribute to back discomfort during long periods of sitting in class, negatively affecting class performance and concentration.²⁵ Given that all patients are braced during the study period, it was reported that students experienced worries and anxiety about brace wearing at school. Worries about appearance and discomfort due to bracing, such as skin irritation and back pain, could contribute to reduced school attendance.^4,6,26–30 However, we should also exhibit caution when interpreting HRQoL differences in terms of school performance. Apart from intrinsic impact of scoliosis itself, social context may play a role in affecting this aspect of HRQoL. COVID lockdown was initiated halfway into our 6-month study, with most patients forced to take lessons online. Previous studies have shown that the lack of face-to-face peer interactions and real-life learning experience during COVID lockdown could contribute to worsened HRQoL in school performance aspect.^31,32 Hence, the demonstrated changes in school performance could be a result from a combination of scoliosis itself and concurrent social limitations (COVID lockdown). However, COVID was not shown to significantly impact other aspects of HRQoL including physical function and emotional aspect³³, which indicates it might not significantly impact our evaluation of overall HRQoL changes. The observed differences of SRS scores in this study between baseline and follow-up not only reinforced the ability of SRS-22r questionnaire to detect HRQoL changes specifically for AIS patients,^12,34 the differences of SRS mental health domain and total score reaching MCID³⁵ indicated that there were indeed significant worsening of HRQoL in this study cohort. This could be explained by decreased life satisfaction and self-esteem in conservatively treated AIS patients.³⁶ In contrast, EQ VAS could only show significant differences in younger patients (8–12 years) while EQ-utility scores differences were statistically significant for both 8–12 and 13–18 years. Our patients had worsened HRQoL detected by the scoliosis-specific SRS-22r questionnaire, and these HRQoL differences were captured by PedsQL, most notably by school functioning and total scores.

Further investigation showed relationships between the changes detected by PedsQL and those changes in SRS-22r and EQ-utility scores. No significant correlations were observed between changes in PedsQL, SRS-22r and EQ-5D-Y-5L in patients of 8-12 years. It has been reported that patients with idiopathic scoliosis suffer from stress and psychological concerns more frequently with age and younger patients may not fully comprehend the true extent of the problem.³⁷ Therefore, changes in scores in younger (8–12 years) patients may not truly reflect changes of HRQoL accurately, thus explaining the lack of correlations. In contrast, for patients aged 13–18 years, PedsQL physical functioning score change was correlated to changes of SRS function domain while changes in PedsQL school functioning also correlated with SRS total score change. The SRS-22r questionnaire is the validated instrument responsive to scoliosis-related changes,¹² and the decrease in daily functioning possibly contributed by the curve or the brace treatment in this cohort could be reflected through PedsQL. Not only there are more items in PedsQL which can more comprehensively reflect school performance than SRS-22r questionnaire (5 items in PedsQL vs 2 items in SRS-22r), which lacks the assessment of in-class concentration and learning ability that are addressed in PedsQL school functioning domain. Hence, PedsQL is recommended to be used in conjunction with SRS-22r to accurately capture the school functioning aspect of HRQoL in these patients. The ability of PedsQL to elicit changes in school performance could allow clinicians to adopt a more holistic understanding on psychosocial impact of scoliosis and arrange specific measures to address issues regarding school performance. For example, braced patients that experience anxiety and distress at academic settings could be referred for psychosocial counselling. In near-mature patients with stable curves, clinicians should contemplate early/ immediate weaning to minimize the impact of prolonged bracing on school functioning aspect¹³. Furthermore, it is essential for parents not to attribute declining academic performance solely to braced individuals, considering the inherent challenges posed by the underlying disease. In terms of general health status, change of EQ-VAS correlated with PedsQL total score change (r = 0.17; p = 0.03) and emotional functioning (r = 0.17; p = 0.02). Correlation between PedsQL emotional functioning and EQ VAS emphasized the presence of emotional component in the self-perception of overall well-being.

More significant correlations were found in patients with greater (>30°) curves than in milder curves (≤30°). Most importantly, both changes in PedsQL school functioning (r = 0.23; p = 0.032) and total score (r = 0.22; p = 0.043) correlated with change in SRS total score. In contrast, there were no correlations between EQ-5D-Y-5L scores and PedsQL scores. EQ-5D-Y-5L is a generic instrument while SRS-22r is scoliosis-specific, presence of correlations between PedsQL and SRS-22r but not in EQ-5D-Y-5L highlighted the potential of PedsQL to assess scoliosis-specific aspects of HRQoL and reflected the discase-specific dimension of PedsQL, especially in patients with more severe curves. As SRS-22r questionnaire remains the extensively validated scoliosis-specific HRQoL assessment measure, our results suggested that PedsQL can be used together with SRS-22r questionnaire in patients with more severe curvature with the benefit of better monitoring HRQoL changes. PedsQL can evaluate HRQoL more extensively in the aspects relating to school performance and can aid in alerting clinicians the time at which psychosocial aspect requires attention during treatment.

Our study is the first to evaluate PedsQL and its relationships with other validated questionnaires used in idiopathic scoliosis. The evaluation of relationship between changes in HRQoL scores through time between different questionnaires is also a novel approach. However, it does have its limitations. Our study was prospective in nature and initially designed as 6-month in duration to study short term HRQoL changes detected by PedsQL. Long-term effects of disease were not accounted for with respect to our study objectives. Idiopathic scoliosis is a chronic disease and short-term HRQoL changes might not reach MCIDs of respective questionnaires.^24,35,38 Also, MCID values of PedsQL has not been previously validated for scoliosis population, which limited our assessment of HRQoL changes in our cohort. In the future, cohort studies with a longer study duration involving these questionnaires are warranted to assess the ability of these instruments to detect trends of HRQoL changes with time. In addition, patients were reviewed through telephone interviews at follow-up instead of face-to-face meetings. There could potentially be communication errors leading to inaccuracies in reported results.

Conclusion

PedsQL, especially school functioning and total scores, was sensitive to changes of HRQoL together with SRS-22r and EQ-5D-Y-5L questionnaires. Changes in PedsQL scores were more prominently related to changes in SRS-22r scores in patients of 13 to 18 years with more severe curves (>30°). Hence, the incorporation of PedsQL in assessment of HRQoL is feasible in older children and patients with more severe scoliosis. It is recommended to be used in conjunction with other validated instruments, particularly with its ability to assess changes of patient’s school functioning aspect as well as overall HRQoL. Future research with a larger cohort and longer duration is needed to validate our findings and to investigate long-term HRQoL outcomes assessed by individual questionnaires.

Footnotes

Author contributions

CHAN Kai Chun Augustine: Methodology, data curation, formal analysis, investigation, writing-original draft, writing-review and editing. CHAN Kai Him Ambrose: Data curation, investigation. WONG See Laam: Data curation, investigation. CHEUNG Jason Pui Yin: Conceptualization, methodology, resources, data curation, project administration, supervision, writing-review and editing. CHEUNG Prudence Wing Hang: Conceptualization, methodology, resources, data curation, project administration, supervision, writing-review and editing.

Declaration of conflicting interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Department Seed Fund, The University of Hong Kong (Prudence Wing Hang Cheung).

Ethical statement

ORCID iDs

Kai Chun Augustine Chan

Kai Him Ambrose Chan

Jason Pui Yin Cheung

Prudence Wing Hang Cheung

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