The assessment and diagnosis of intellectual disability when development is atypical. A Norwegian population study of individuals with CHARGE syndrome

Figures & data

Table 1. Summary of studies addressing cognitive and behavioral functioning of individuals with CHARGE adapted from the review by Thomas et al. [10].

Studies addressing cognitive and/or behavioral functioning	Evaluation of the assessment methodology		Incidence intellectual disability
	Measures of cognition	Measures of adaptive behavior	% (n/N)	Quality indicators
Hittner et al. [11]	2	NA^a	100% (7/7)	1-Poor	Non-standardized reports or review of clinical information
Davenport et al. [12]	2	NA	100% (7/7)
Oley et al. [13]	3	NA	60% (12/20)
Asher et al. [14]	1	NA	100% (14/14)	2-Adequate	Standardised informant reports
Blake et al. [15]	1	NA	–
Harvey et al. [16]	2	NA	29% (2/7)	3-Good	Standardised behavioral or observational assessment
Blake and Brown [17]	1	NA	63% (19/30)
Tellier et al. [18]	1	NA	–
Roger et al. [19]	1	NA	–	4-Excellent	Consensus in evaluation drawn from multiple measures and at least one involve standardized behavioral or observational assessment
Raqbi et al. [20]	1	NA	–
Hartshorne and Cypher [21]	NA	1	–
Salem-Hartshorne and Jacob [22]	2	NA	46% (46/100)
Bernstein and Denno [23]	1	2	90% (26/29)
Blake et al. [24]	1	1	–
Issekutz et al. [25]	NA	1	–
Smith et al. [26]	1	1	100% (11/11)
Souriau et al. [27]	NA	1	–
Strömland et al. [28]	2	3	–
Thelin and Fussner [29]	NA	1	–
Johansson et al. [30]	2	3	79% (22/28)
Jongmans et al. [31]	1	NA	74% (23/31)
Dobbeltsteyn et al. [32]	1	NA	–
Reda and Hartshorne [33]	NA	2	–
Wincent et al. [34]	1	NA	–
Hartshorne et al. [35]	1	1	–
Wulffaert et al. [36]	2	NA	75% (15/20)
Wessels et al. [37]	1	NA	–
Dammeyer [38]	3	NA	18% (3/17)
Deuce et al. [39]	1	1	–
Hartshorne et al. [40]	NA	2	–
Husu et al. [41]	1	NA	–
Lasserre et al. [42]	3	NA	63% (5/8)
Hsu et al. [43]	1	NA	–
Shoji et al. [44]	1	NA	100% (25/25)
Sohn et al. [45]	3	NA	94% (17/18)
Hale et al. [46]	1	NA	–
Deuce [47]	1	NA	40% (21/52)
Legendre et al. [48]	1	NA	66% (63/96)
Shiohama et al. [49]	1	NA	–
Abadie et al. [50]	2	NA	70% (45/65)
Cheng et al. [51]	1	1	90% (9/10)

^aNA: Not Applicaple.

Thomas and colleagues [10] reviewed studies between 1979, the time when CHARGE was first recognized, and 2021. One focus was to evaluate the methodology employed to assess the cognition and behavioral functioning of individuals with CHARGE by using four different quality indicators: 1-Poor; 2-Adequate; 3-Good; and 4-Excellent. Their review also included how many of the studies’ participants demonstrated challenges corresponding to an intellectual disability. No study reached the quality of excellence (indicator 4). However, four studies involving cognitive assessment, and two involving behavioral assessment qualified to an indicator of 3 (good). Notable, while most of the studies were given a quality indicator of 1 (poor), or a 2 (adequate) on either the cognitive assessment or the behavioral assessment, many reported an estimate of intellectual disability, which overall appeared high.

Table 2. Selected demographic, sensory, and developmental information of the participants (N = 35).

		n	M	SD
Age intervals	Pre-schoolers (ages 2.0–6:11)	5
	Children (ages 7.0–12.11)	7
	Adolescents (ages 13.0–16.11)	6
	Young adults (ages 17.0–21.11)	5
	Adults (ages 22.0–65)	12
Gender ratio	Males	20
	Females	15
Participants without deafblindness		17
Participants with deafblindness		18
Hearing status	No impairment (0–20 dB)	1
	Mild (21–40 dB)	4
	Moderate (41–60 dB)	13
	Severe (61–80 dB)	7
	Profound/deafness (> 80 dB)	10
Vision deficits	No impairment	13
	Mild (acuity worse than 6/12–6/18)	10
	Moderate (acuity worse than 6/18–6/60)	8
	Severe (acuity between 6/60–3/60)	3
	Blindness (acuity worse than 3/60)	2
Functional vision Rasch calibrated scores^a			54.9	37.2
Age for onset of independent walking			3:7^b	1:6
	Within 1 year of life	2
	Between age 1:1 and 2:0	2
	Between age 2:1 and 3:0	9
	Between age 3:1 and 4:0	4
	Between age 4:1 and 5:0	8
	After age 5:1	4
	Never walked without support	3
	Not attained ability at time of assessment	2
Age of receiving hearing aids	Within the first two years of life	19
	Between age 2:1 and 3:0	7
	Between age 3:1 and 4:0	2
	After age 4:1	5
	No hearing aid	1
Age start talking or signing			3:3	2:2
	Within 1 year of life	4
	Between age 1:1 and 2:0	5
	Between age 2:1 and 3:0	11
	Between age 3:1 and 4:0	8
	Between age 4:1 and 5:0	3
	After age 5:1	3
Language and communication	Norwegian speech with or without sign support	17
	Norwegian Sign Language	9
	AAC^c including visual and tactile signs	5
	Communication mode undecided at the time of the assessment	4

Age intervals followed those employed in the different age versions of the performance-based measures [5–7]. Also included was the number of young adults, which corresponded to the upper age limit of Vineland (Norwegian version), which is 21:11 [4]. Few medical and educational data were available for the oldest participant since the parents were dead, medical records obsolete, and the older sibling had fragmentary memory of birth and early development. Classification of the participants with hearing impairment followed the World Health Organization grading of hearing impairment with the corresponding audiometric International Organization for Standardization value [65]. The main visual parameter in this study was visual acuity, which followed the World Health Organization classific ation system (https://www.who.int/publications-detail-redirect/9789241516570).

^aRasch calibrated scores: Functional vision was calculated using the first part of the pediatric eye questionnaire, which uses Rasch calibrated scores between 0 to 100, where values at the high end reflect small interference in daily life due to functional vision [66]

^bEstimates were based on the participants that had attained independent walking at the time of the assessment (n = 29)

^cAAC: Augmentative and Alternative Communication [67].

Table 3. Categories of accommodations according to the review by Sireci and O’Riordan [68] transferred to the present study to evaluate the comparability of scores obtained from test-items before and after any accommodations.

Categories of accommodations	Accommodations in the present study	Comparability between standardized and accommodated test-items
Presentation The manner in which the test is presented (e.g. large-print formats, Braille, interpreter/ translations, signs, items/questions read aloud).	Administration on sign language and sign supported speech. Translation supported by personnel with specific knowledge of the participants’ background communication skills	Studies in large part related to reading aloud, which indicate little interference of the test-items’ validity. Accommodations involving sign language raised validity concerns^a
Response The manner in which the student responds (e.g. interpreter/translations, signs, separate answer sheet, transcription by administrator/marking answers, word processor, computer).	Responding by sign language. Translation of responses by personnel with specific knowledge of the participants’ background and communication skills.	Few studies have been conducted, indicating low probability of accommodations related to manner of response interfere with tests’ validity. Accommodations involving sign language raised validity concerns^a
Setting The setting in which the test is administered (e.g. one-on-one, hospital, home, other location)	Setting was chosen according to the participants’ or parents’ wishes, either at school, home, work, office.	Few studies have been conducted, indicating low probability of accommodations related to test setting interfere with tests’ validity. In the present study accommodation of setting was restricted to finding a working area that allowed some control of external factors. Accordingly, the likelihood of affecting test validity was considered low.
Timing The timing of the test (e.g. extended time, additional scheduled breaks, changed test schedule)	Awaiting testing until the participants had become acquainted with the test administrator/neuropsychologist. Diving the Wechsler scale in separate test sessions across several days due to health issues. Test-items administrated according to the participants needs, not following the predefined sequence.	Studies focus on the effect of extended time during problem solving, which is in general related to enhanced performance of individuals with disabilities indicating low probability of test validity interference. Because the accommodations connected to timing were less intrusive in the present study than those referred to in research, the likelihood of affecting test validity was considered low.
Equipment and devices (e.g. color chooser, magnification device, amplification device, color overlay)	Hearing aids and voice transmitter. Visual and tactile framing on the desk to define the working area.	Studies focus on the effect of calculators and resource guides, which overall appear more beneficial for individuals without disabilities. Accommodations in the present study targeted accessibility more specifically by counteracting the effects of auditory and visual impairment. The likelihood of affecting test validity was considered low.

^aSpecific validity concerns are related to test administration involving sign language. Test validity depend not only on the clinician’s understanding of participants’ bicultural and bilingual background [73]. Correct interpretation and evaluation of responses also requires theoretical and clinical knowledge of specific characteristics of the cognitive processing of individuals born with auditory impairment [74,75]. In the present study measures were taken to address these factors. For example, all assessment involving sign language was conducted with the participant’s usual communication partner present. These professionals knew the participants background and thereby their characteristic communication patterns and objects of reference. Furthermore, the testing was completed by the same neuropsychologist, who had experience within the field of combined sensory impairment, deafblindness, and CHARGE.

Figure 1. Distribution of the participants’ performance-based assessment after excluding the 5 who needed modified test conditions (n = 30). Despite skewing to the right, the distribution was considered normal according to the tests of normality. The distribution indicated a bimodality, marked by the blue arrow above.

Figure 2. Distribution of the parental reports on Vineland adaptive ability Scale of the participants’ overall adaptive behavior abilities (GAI). The distribution was based on 22 reports. Twelve participants were eliminated because of their age, and 5 participants were already excluded to avoid compromising the validity of the data set. According to the tests of normality the data set appeared normally distributed.

Figure 3. Distribution of the preschoolers’ CQ scores after their performances on either WPPSI (n = 4) or Bayley-III (n = 1). Four preschoolers out of 5 was assessed with WPPSI-IV. One child was assessed with Bayley-III because of the young age. Bayley-III is not an intelligence scale, like the Wechsler scales, but gives information about whether a child’s developmental trajectory is proceeding as expected, relative to same-age peers. This may be part of the reason for the differences in performances, as illustrated by the two blue bars.

Figure 4. Distribution of the participants’ CQ scores after excluding the preschoolers’ performances due to the indicated bimodality. Tests of normality appeared satisfactory also after the exclusion (n = 25).

Table 4. Explorative bifactor analysis of the participants’ performances on WISC-V.

	Factor loadings		Reliability statistics
Test items	Factor 1	Factor 2	Factor 1	Factor 2
Blocks	0.94	−0.17	α = 0.87	α = 0.84
Matrices	0.91	0.25	5 items	3 items
Coding	0.84
Picture memory	0.83	0.15
Figure weights	0.83
Symbol search	0.78	0.39
Visual puzzles	0.71	0.32
Letter-number sequence	0.68	0.43
Digit-span	0.65	0.61
Verbal reasoning	0.11	0.89
Information	0.12	0.88
Receptive vocabulary		0.81
Similarities	0.32	0.75
Arithmetic	0.38	0.60

Extraction method principal component analysis. Rotation method Varimax with Kaiser normalization.

Table 5. Factor analysis of the performances on WISC-V with 5 fixed factors.

	Factor loadings
Test items	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5
Coding	0.91	0.12		0.18
Symbol search	0.81	0.16	0.18	0.41	0.12
Matrices	0.79	0.48	0.28		0.10
Blocks	0.79	0.45		−0.36	0.20
Picture memory	0.79	0.18	−0.15	0.22	0.51
Visual puzzles	0.67	0.27	0.47	−0.11	0.18
Letter-number sequence	0.28	0.88		0.26	0.26
Figure weights	0.62	0.69			−0.28
Digit-span	0.37	0.47	0.40	0.22	0.32
Verbal reasoning		0.22	0.88	0.36
Information		0.83	0.31	0.36
Receptive vocabulary			0.30	0.91	0.13
Similarities	0.18	0.45	0.31	0.75
Arithmetic	0.23	0.22	0.43		0.79

Extraction method principal component analysis. Rotation method Varimax with Kaiser normalization.

Table 6. Explorative bifactor analysis of the performances on WAIS-IV.

	Factor loadings
Test items	Factor 1	Factor 2
Symbol search	0.96
Arithmatic	0.91	0.29
Matrices	0.83	0.18
Figure weights	0.81	0.55
Visual puzzles	0.80	0.39
Coding	0.78	0.57
Letter-number sequence	0.74	0.56
Receptive vocabulary	0.30	0.92
Information	0.45	0.88
Blocks		0.83
Verbal reasoning	0.20	0.82
Digit-span	0.60	0.76
Similarities	0.65	0.73

Extraction method principal component analysis. Rotation method Oblimin with Kaiser normalization.

Table 7. Factor analysis of the performances on WAIS-IV with 4 fixed factors.

	Factor loadings
Test items	Factor 1	Factor 2	Factor 3	Factor 4
Symbol search	8.7		0.48	−0.12
Letter-number sequence	0.80	0.34	0.28	0.39
Figure weights	0.68	0.36	0.50	0.38
Digit-span	0.63	0.62	0.23	0.41
Verbal reasoning	0.11	0.96	0.12	0.17
Information	0.27	0.68	0.39	0.57
Receptive vocabulary	0.29	0.67	0.16	0.62
Coding	0.61	0.63	0.46	0.14
Similarities	0.43	0.60	0.50	0.41
Matrices	0.26	0.13	0.91	0.13
Arithmtic	0.58	0.14	0.74	0.27
Visual puzzles	0.39	0.45	0.72
Blocks		0.22	0.11	0.96

Extraction method principal component analysis. Rotation method Oblimin with Kaiser normalization.

Thomas AT, Waite J, Williams CA, et al. Phenotypic characteristics and variability in CHARGE syndrome: a PRISMA compliant systematic review and meta-analysis. J Neurodev Disord. 2022;14(1):49. doi: 10.1186/s11689-022-09459-5.

 PubMed Web of Science ®Google Scholar

Hittner HM, Hirsch NJ, Kreh GM, et al. Colobomatous microphthalmia, heart disease, hearing loss, and mental retardation-a syndrome. J Pediatr Ophthalmol Strabismus. 1979;16(2):122–128. doi: 10.3928/0191-3913-19790301-10.

 PubMed Web of Science ®Google Scholar

Davenport SL, Hefner MA, Mitchell JA. The spectrum of clinical features in CHARGE syndrome. Clin Genet. 1986;29(4):298–310. doi: 10.1111/j.1399-0004.1986.tb01258.x.

 PubMed Web of Science ®Google Scholar

Oley CA, Baraitser M, Grant DB. A reappraisal of the CHARGE association. Journal of Medical Genetics. 1988;25(3):147–156. (1)., (), –. doi: 10.1136/jmg.25.3.147.

 PubMed Web of Science ®Google Scholar

Asher BF, McGill TJ, Kaplan L, et al. Airway complications in CHARGE association. Archives of Otolaryngology–Head & Neck Surgery. 1990;116(1):15.

 Google Scholar

Blake KD, Russell-Eggitt IM, Morgan DW, et al. Who’s in CHARGE? Multidisciplinary management of patients with CHARGE association. Arch Dis Child. 1990;65(2):217–223. doi: 10.1136/adc.65.2.217.

 PubMed Web of Science ®Google Scholar

Harvey AS, Leaper PM, Bankier A. CHARGE association: clinical manifestations and developmental outcome. Am J Med Genet. 1991;39(1):48–55. doi: 10.1002/ajmg.1320390112.

 PubMed Web of Science ®Google Scholar

Blake KD, Brown D. CHARGE association looking at the future, the voice of a family support group. Child Care Health Dev. 1993;19(6):395–409. doi: 10.1111/j.1365-2214.1993.tb00744.x.

 PubMed Web of Science ®Google Scholar

Tellier AL, Cormier-Daire V, Abadie V, et al. CHARGE syndrome: report of 47 cases and review. Am J Med Genet. 1998;76(5):402–409. doi: 10.1002/(SICI)1096-8628(19980413)76:5<402::AID-AJMG7>3.0.CO;2-O.

 PubMed Web of Science ®Google Scholar

Roger G, Morisseau-Durand MP, Van Den Abbeele T, et al. The CHARGE association: the role of tracheotomy. Arch Otolaryngol Head Neck Surg. 1999;125(1):33–38. doi: 10.1001/archotol.125.1.33.

 PubMedGoogle Scholar

Raqbi F, Le Bihan C, Morisseau-Durand MP, et al. Early prognostic factors for intellectual outcome in CHARGE syndrome. Dev Med Child Neurol. 2003;45(7):483–488. doi: 10.1111/j.1469-8749.2003.tb00944.x.

 PubMed Web of Science ®Google Scholar

Hartshorne TS, Cypher AD. Challenging behavior in CHARGE syndrome. MHDD. 2004;7(2):41–52.

 Google Scholar

Salem-Hartshorne N, Jacob S. Characteristics and development of children with CHARGE association/syndrome. J Early Interv. 2004;26(4):292–301. doi: 10.1177/105381510402600405.

 Web of Science ®Google Scholar

Bernstein V, Denno LS. Repetitive behaviors in CHARGE syndrome: differential diagnosis and treatment options. Am J Med Genet A. 2005;133A(3):232–239. doi: 10.1002/ajmg.a.30542.

 PubMed Web of Science ®Google Scholar

Blake KD, Salem-Hartshorne N, Daoud MA, et al. Adolescent and adult issues in CHARGE syndrome. Clin Pediatr. 2005;44(2):151–159. doi: 10.1177/000992280504400207.

 PubMed Web of Science ®Google Scholar

Issekutz KA, Graham JM, Prasad C, et al. An epidemiological analysis of CHARGE syndrome: preliminary results from a Canadian study. Am J Med Genet. 2005;133A(3):309–317. doi: 10.1002/ajmg.a.30560.

 PubMed Web of Science ®Google Scholar

Smith IM, Nichols SL, Issekutz K, et al. Behavioral profiles and symptoms of autism in CHARGE syndrome: preliminary Canadian epidemiological data. Am J Med Genet A. 2005;133A(3):248–256. doi: 10.1002/ajmg.a.30544.

 PubMed Web of Science ®Google Scholar

Souriau J, Gimenes M, Blouin C, et al. CHARGE syndrome: developmental and behavioral data. Am J Med Genet A. 2005;133A(3):278–281. doi: 10.1002/ajmg.a.30549.

 PubMed Web of Science ®Google Scholar

Strömland K, Sjögreen L, Johansson M, et al. CHARGE association in Sweden: malformations and functional deficits. Am J Med Genet A. 2005;133A(3):331–339. doi: 10.1002/ajmg.a.30563.

 PubMed Web of Science ®Google Scholar

Thelin JW, Fussner JC. Factors related to the development of communication in CHARGE syndrome. Am J Med Genet A. 2005;133A(3):282–290. doi: 10.1002/ajmg.a.30550.

 PubMed Web of Science ®Google Scholar

Johansson M, Råstam M, Billstedt E, et al. Autism spectrum disorders and underlying brain pathology in CHARGE association. Dev Med Child Neurol. 2006;48(1):40–50. doi: 10.1017/S0012162206000090.

 PubMed Web of Science ®Google Scholar

Jongmans MCJ, Admiraal RJ, Van Der Donk KP, et al. CHARGE syndrome: the phenotypic spectrum of mutations in the CHD7 gene. J Med Genet. 2006;43(4):306–314. doi: 10.1136/jmg.2005.036061.

 PubMed Web of Science ®Google Scholar

Dobbelsteyn C, Peacocke SD, Blake K, et al. Feeding difficulties in children with CHARGE syndrome: prevalence, risk factors, and prognosis. Dysphagia. 2008;23(2):127–135. doi: 10.1007/s00455-007-9111-6.

 PubMed Web of Science ®Google Scholar

Reda NM, Hartshorne TS. Attachment, bonding, and parental stress in CHARGE syndrome. MHDD. 2008;11(2008):1.

 PubMedGoogle Scholar

Wincent J, Holmberg E, Strömland K, et al. CHD7 mutation spectrum in 28 swedish patients diagnosed with CHARGE syndrome. Clin Genet. 2008;74(1):31–38. doi: 10.1111/j.1399-0004.2008.01014.x.

 PubMed Web of Science ®Google Scholar

Hartshorne TS, Heussler HS, Dailor AN, et al. Sleep disturbances in CHARGE syndrome: types and relationships with behavior and caregiver well-being. Dev Med Child Neurol. 2009;51(2):143–150. doi: 10.1111/j.1469-8749.2008.03146.x.

 PubMed Web of Science ®Google Scholar

Wulffaert J, Scholte EM, Dijkxhoorn YM, et al. Parenting stress in CHARGE syndrome and the relationship with child characteristics. J Dev Phys Disabil. 2009;21(4):301–313. doi: 10.1007/s10882-009-9143-y.

 PubMed Web of Science ®Google Scholar

Wessels K, Bohnhorst B, Luhmer I, et al. Novel CHD7 mutations contributing to the mutation spectrum in patients with CHARGE syndrome. Eur J Med Genet. 2010;53(5):280–285. doi: 10.1016/j.ejmg.2010.07.002.

 PubMed Web of Science ®Google Scholar

Dammeyer J. Development and characteristics of children with usher syndrome and CHARGE syndrome. Int J Pediatr Otorhinolaryngol. 2012;76(9):1292–1296. doi: 10.1016/j.ijporl.2012.05.021.

 PubMed Web of Science ®Google Scholar

Deuce G, Howard S, Rose S, et al. A study of CHARGE syndrome in the UK. Br J Vis Impair. 2012;30(2):91–100. doi: 10.1177/0264619612443883.

 Google Scholar

Hartshorne N, Hudson A, MacCuspie J, et al. Quality of life in adolescents and adults with CHARGE syndrome. Am J Med Genet A. 2016;170(8):2012–2021. doi: 10.1002/ajmg.a.37769.

 PubMed Web of Science ®Google Scholar

Husu E, Hove HD, Farholt S, et al. Phenotype in 18 Danish subjects with genetically verified CHARGE syndrome. Clin Genet. 2013;83(2):125–134. doi: 10.1111/j.1399-0004.2012.01884.x.

 PubMed Web of Science ®Google Scholar

Lasserre E, Vaivre-Douret L, Abadie V. Psychomotor and cognitive impairments of children with CHARGE syndrome: common and variable features. Child Neuropsychol. 2013;19(5):449–465. doi: 10.1080/09297049.2012.690372.

 PubMed Web of Science ®Google Scholar

Hsu P, Ma A, Wilson M, et al. CHARGE syndrome: a review. J Paediatr Child Health. 2014;50(7):504–511. doi: 10.1111/jpc.12497.

 PubMed Web of Science ®Google Scholar

Shoji Y, Ida S, Etani Y, et al. Endocrinological characteristics of 25 Japanese patients with CHARGE syndrome. Clin Pediatr Endocrinol. 2014;23(2):45–51. doi: 10.1297/cpe.23.45.

 PubMedGoogle Scholar

Sohn YB, Ko JM, Shin CH, et al. Cerebellar vermis hypoplasia in CHARGE syndrome: clinical and molecular characterization of 18 unrelated Korean patients. J Hum Genet. 2016;61(3):235–239. doi: 10.1038/jhg.2015.135.

 PubMed Web of Science ®Google Scholar

Hale CL, Niederriter AN, Green GE, et al. A typical phenotypes associated with pathogenic CHD7 variants and a proposal for broadening CHARGE syndrome clinical diagnostic criteria. Am J Med Genet A. 2016;170A(2):344–354. doi: 10.1002/ajmg.a.37435.

 PubMedGoogle Scholar

Deuce G. The education of learners with CHARGE syndrome. British Journal of Special Education. 2017;44(4):376–393. doi: 10.1111/1467-8578.12183.

 Google Scholar

Legendre M, Abadie V, Attié-Bitach T, et al. Phenotype and genotype analysis of a French cohort of 119 patients with CHARGE syndrome. Am J Med Genet C Semin Med Genet. 2017;175(4):417–430. doi: 10.1002/ajmg.c.31591.

 PubMed Web of Science ®Google Scholar

Shiohama T, McDavid J, Levman J, et al. Quantitative brain morphological analysis in CHARGE syndrome. Neuroimage Clin. 2019;23(2019):101866. Article 101866. doi: 10.1016/j.nicl.2019.101866.

 PubMedGoogle Scholar

Abadie V, Hamiaux P, Ragot S, et al. Should autism spectrum disorder be considered part of CHARGE syndrome? A cross-sectional study of 46 patients. Orphanet J Rare Dis. 2020;15(1):136–136. doi: 10.1186/s13023-020-01421-9.

 PubMed Web of Science ®Google Scholar

Cheng SS, Luk HM, Chan DK, et al. CHARGE syndrome in nine patients from China. Am J Med Genet A. 2020;182(1):15–19. doi: 10.1002/ajmg.a.61398.

 PubMed Web of Science ®Google Scholar

Sparrow SS, Cicchetti DV, Balla DA. Vineland adaptive behavior scales: Norwegian version. (2nd ed.). Stockholm: NCS Pearson; 2011.

 Google Scholar

Olusanya BO, Davis AC, Hoffman HJ. Hearing loss grades and the international classification of functioning, disability and health. Bull World Health Organ. 2019;97(10):725–728. doi: 10.2471/BLT.19.230367.

 PubMed Web of Science ®Google Scholar

Hatt SR, Leske DA, Castañeda YS, et al. Development of pediatric eye questionnaires for children with eye conditions. Am J Ophthalmol. 2019;200(2019):201–217. doi: 10.1016/j.ajo.2019.01.001.

 PubMedGoogle Scholar

von Tetzchner, S., Martinsen, H, editors. Introduction to augmentative and alternative communication: sign teaching and the use of communication aids for children, adolescents and adults with developmental disorders. (2nd ed.). London: Whurr Publisher; 2000.

 Google Scholar

Sireci S, O’Riordan M. Comparability when assessing individuals with disabilities. In: Berman AI, Haertel EH, Pellegrino JW, editors. Comparability of large-scale educational assessments. Issues and recommendations. Washington DC: National Academy of Education; 2020. p. 177–204.

 Google Scholar

Chatzidamianos G, Burns D, Andriopoulou P, et al. The challenges and facilitators to successful translation and adaptation of written self-report psychological measures into sign languages: a systematic review. Psychol Assess. 2021;33(11):1100–1124. doi: 10.1037/pas0001061.

 PubMed Web of Science ®Google Scholar

Marschark M, Knoors H. Educating deaf children: language, cognition, and learning. Deaf Educ Int. 2012;14(3):136–160. doi: 10.1179/1557069X12Y.0000000010.

 Google Scholar

Marschark, M., & Knoors, H. (Eds.) 2020. The oxford handbook of deaf studies in learning and cognition. Oxford: Oxford University Press.

 Google Scholar