Association between distress and knowledge among parents of autistic children
Autoři:
Afiqah Yusuf aff001; Iskra Peltekova aff002; Tal Savion-Lemieux aff003; Jennifer Frei aff003; Ruth Bruno aff003; Ridha Joober aff004; Jennifer Howe aff005; Stephen W. Scherer aff005; Mayada Elsabbagh aff002
Působiště autorů:
Department of Psychiatry, McGill University, Montreal, Quebec, Canada
aff001; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
aff002; Autism Spectrum Disorders Research Program, Research-Institute of the McGill University Health Centre, Montreal, Quebec, Canada
aff003; Research Program on Psychotic and Neurodevelopmental Disorders, Douglas Mental Health University Institute, Montreal, Quebec, Canada
aff004; The Centre for Applied Genomics, Hospital for Sick Children, Toronto, Ontario, Canada
aff005; McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
aff006; Azrieli Centre for Autism Research, Montreal Neurological Institute, Montreal, Quebec, Canada
aff007
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0223119
Souhrn
Understanding the overall utility of biological testing for autism spectrum disorder (ASD) is essential for the development and integration of biomarkers into routine care. One measure related to the overall utility of biological testing is the knowledge that a person has about the condition he/she suffers from. However, a major gap towards understanding the role of knowledge in overall utility is the absence of studies that have assessed knowledge of autism along with its predictors within a representative sample of families within the context of routine care. The objective of this study was to measure knowledge of ASD among families within the routine care pathway for biological testing in ASD by examining the association between knowledge with potential correlates of knowledge namely sociodemographic factors, parental stress and distress, and time since diagnosis among parents whose child with ASD is undergoing clinical genetic testing. Parents of a child diagnosed with ASD (n = 85, Mage = 39.0, SD = 7.7) participating in an ongoing prospective genomics study completed the ASD Quiz prior to undergoing genetic testing for clinical and research purposes. Parents also completed self-reported measures of stress and distress. Parent stress and distress was each independently correlated with knowledge of ASD, rs ≥ 0.26, ps < 0.05. Stepwise regression analysis revealed a significant model accounting for 7.8% of the variance in knowledge, F (1, 82) = 8.02, p = 0.006. The only factor significantly associated with knowledge was parental distress, β = 0.30, p = 0.006. Parental stress, time since diagnosis, and sociodemographic factors were not significant predictors in this model. We concluded that families require tailored support prior to undergoing genetic testing to address either knowledge gaps or high distress. Ongoing appraisal of the testing process among families of diverse backgrounds is essential in offering optimal care for families undergoing genetic testing.
Klíčová slova:
Human families – Schools – Biomarkers – Questionnaires – Autism spectrum disorder – Autism – Genetic testing – Genetic counseling
Zdroje
1. Mayeux R. Biomarkers: Potential Uses and Limitations. NeuroRx. 2004;1(2):182–8. doi: 10.1602/neurorx.1.2.182 15717018
2. Bosl W, Tierney A, Tager-Flusberg H, Nelson C. EEG complexity as a biomarker for autism spectrum disorder risk. BMC Med. 2011;9(1): 18. doi: 10.1186/1741-7015-9-18 21342500
3. Ecker C, Marquand A, Mourão-Miranda J, Johnston P, Daly EM, Brammer MJ, et al. Describing the brain in autism in five dimensions—magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J Neurosci. 2010;30(32): 10612–23. doi: 10.1523/JNEUROSCI.5413-09.2010 20702694
4. Pierce K, Conant D, Hazin R, Stoner R, Desmond J. Preference for geometric patterns early in life as a risk factor for autism. Arch Gen Psychiat. 2011;68(1): 101. doi: 10.1001/archgenpsychiatry.2010.113 20819977
5. Tu WJ, Yin CH, Guo YQ, Li SO, Chen H, Zhang Y, et al. Serum homocysteine concentrations in Chinese children with autism. Clin Chem Lab Med. 2013;51(2): e19–22. doi: 10.1515/cclm-2012-0196 23095201
6. Walsh P, Elsabbagh M, Bolton P, Singh I. In search of biomarkers for autism: scientific, social and ethical challenges. Nat Rev Neurosci. 2011;12(10): 603–12. doi: 10.1038/nrn3113 21931335
7. Campbell H, Hotchkiss R, Bradshaw N, Porteous M. Integrated care pathways. BMJ (Clinical research ed). 1998;316(7125): 133–7. doi: 10.1136/bmj.316.7125.133 9462322
8. Røsstad T, Garåsen H, Steinsbekk A, Sletvold O, Grimsmo A. Development of a patient-centred care pathway across healthcare providers: a qualitative study. BMC Health Serv Res. 2013;13(1): 121.
9. Johnson CP, Myers SM. Identification and Evaluation of Children With Autism Spectrum Disorders. Pediatrics. 2007;120(5): 1183–215. doi: 10.1542/peds.2007-2361 17967920
10. Anagnostou E, Zwaigenbaum L, Szatmari P, Fombonne E, Fernandez BA, Woodbury-Smith M, et al. Autism spectrum disorder: advances in evidence-based practice. Can Med Assoc J. 2014;186(7): 509–19. doi: 10.1503/cmaj.121756 24418986
11. Tammimies K, Marshall CR, Walker S, Kaur G, Thiruvahindrapuram B, Lionel AC, et al. Molecular Diagnostic Yield of Chromosomal Microarray Analysis and Whole-Exome Sequencing in Children With Autism Spectrum Disorder. JAMA. 2015;314(9): 895–903. doi: 10.1001/jama.2015.10078 26325558
12. Miller DT, Adam MP, Aradhya S, Biesecker LG, Brothman AR, Carter NP, et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet. 2010;86(5): 749–64. doi: 10.1016/j.ajhg.2010.04.006 20466091
13. Devlin B, Scherer SW. Genetic architecture in autism spectrum disorder. Curr Opin Genet Dev. 2012;22(3): 229–37. doi: 10.1016/j.gde.2012.03.002 22463983
14. Jang W, Kim Y, Han E, Park J, Chae H, Kwon A, et al. Chromosomal Microarray Analysis as a First-Tier Clinical Diagnostic Test in Patients With Developmental Delay/Intellectual Disability, Autism Spectrum Disorders, and Multiple Congenital Anomalies: A Prospective Multicenter Study in Korea. Ann Lab Med. 2019;39(3): 299–310. doi: 10.3343/alm.2019.39.3.299 30623622
15. Shen Y, Dies KA, Holm IA, Bridgemohan C, Sobeih MM, Caronna EB, et al. Clinical Genetic Testing for Patients With Autism Spectrum Disorders. Pediatrics. 2010;125(4): e727–e35. doi: 10.1542/peds.2009-1684 20231187
16. Hogart A, Wu D, LaSalle JM, Schanen NC. The Comorbidity of Autism with the Genomic Disorders of Chromosome 15q11.2-q13. Neurobiol Dis. 2010;38(2): 181–91. doi: 10.1016/j.nbd.2008.08.011 18840528
17. Weiner DJ, Wigdor EM, Ripke S, Walters RK, Kosmicki JA, Grove J, et al. Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders. Nat Genet. 2017;49(7): 978–85. doi: 10.1038/ng.3863 28504703
18. Darilek S, Ward P, Pursley A, Plunkett K, Furman P, Magoulas P, et al. Pre- and postnatal genetic testing by array-comparative genomic hybridization: genetic counseling perspectives. Genet Med. 2008;10(1): 13–8. doi: 10.1097/GIM.0b013e31815f1ddb 18197052
19. Holtzman NA, Watson MS. Promoting safe and effective genetic testing in the United States: final report of the Task Force on Genetic Testing. Baltimore: Johns Hopkins; 1999.
20. Grosse SD, Khoury MJ. What is the clinical utility of genetic testing? Genet Med. 2006;8: 448 16845278
21. Hilgart JS, Coles B, Iredale R. Cancer genetic risk assessment for individuals at risk of familial breast cancer. Cochrane Db Syst Rev. 2012;(2). doi: 10.1002/14651858.CD003721.pub3 22336791
22. Hayeems RZ, Babul-Hirji R, Hoang N, Weksberg R, Shuman C. Parents’ Experience with Pediatric Microarray: Transferrable Lessons in the Era of Genomic Counseling. J Genet Couns. 2016;25(2): 298–304. doi: 10.1007/s10897-015-9871-3 26259530
23. Jez S, Martin M, South S, Vanzo R, Rothwell E. Variants of unknown significance on chromosomal microarray analysis: parental perspectives. J Community Genet. 2015;6(4): 343–9. doi: 10.1007/s12687-015-0218-4 25666435
24. Kiedrowski LA, Owens KM, Yashar BM, Schuette JL. Parents’ Perspectives on Variants of Uncertain Significance from Chromosome Microarray Analysis. J Genet Couns. 2016;25(1): 101–11. doi: 10.1007/s10897-015-9847-3 25983052
25. Reiff M, Giarelli E, Bernhardt BA, Easley E, Spinner NB, Sankar PL, et al. Parents’ Perceptions of the Usefulness of Chromosomal Microarray Analysis for Children with Autism Spectrum Disorders. J Autism Dev Disord. 2015;45(10): 3262–75. doi: 10.1007/s10803-015-2489-3 26066358
26. McAllister M, Payne K, Macleod R, Nicholls S, Dian D, Davies L. Patient empowerment in clinical genetics services. J Health Psychol. 2008;13(7): 895–905. doi: 10.1177/1359105308095063 18809640
27. Lerman C, Lustbader E, Rimer B, Daly M, Miller S, Sands C, et al. Effects of Individualized Breast Cancer Risk Counseling: a Randomized Trial. J Natl Cancer I. 1995;87(4): 286–92. doi: 10.1093/jnci/87.4.286 7707420
28. Gazmararian JA, Williams MV, Peel J, Baker DW. Health literacy and knowledge of chronic disease. Patient Educ Couns. 2003;51(3): 267–75. 14630383
29. Jiang YH, Yuen RK, Jin X, Wang M, Chen N, Wu X, et al. Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing. Am J Hum Genet. 2013;93(2): 249–63. doi: 10.1016/j.ajhg.2013.06.012 23849776
30. Yuen RK, Thiruvahindrapuram B, Merico D, Walker S, Tammimies K, Hoang N, et al. Whole-genome sequencing of quartet families with autism spectrum disorder. Nat Med. 2015;21(2):185–91. doi: 10.1038/nm.3792 25621899
31. Yuen RK, Merico D, Cao H, Pellecchia G, Alipanahi B, Thiruvahindrapuram B, et al. Genome-wide characteristics of de novo mutations in autism. NPJ Genom Med. 2016;1: 160271–1602710. doi: 10.1038/npjgenmed.2016.27 27525107
32. Yuen R C., Merico D, Bookman M, J LH, Thiruvahindrapuram B, Patel RV, et al. Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder. Nat Neurosci. 2017;20(4):602–11. doi: 10.1038/nn.4524 28263302
33. Kuhn JC, Carter AS. Maternal self-efficacy and associated parenting cognitions among mothers of children with autism. Am J Orthopsychiatry. 2006;76(4): 564–75. doi: 10.1037/0002-9432.76.4.564 17209724
34. US Department of Health and Human Services Food and Drug Administration. Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims. US Department of Health and Human Services Food and Drug Administration. 2009 Dec [Cited 2019 May 10]. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-reported-outcome-measures-use-medical-product-development-support-labeling-claims
35. Aaronson N, Alonso J, Burnam A, Lohr KN, Patrick DL, Perrin E, et al. Assessing health status and quality-of-life instruments: attributes and review criteria. Qual Life Res. 2002;11(3): 193–205. 12074258
36. Cohen S, Williamson G. Perceived stress in a probability sample of the United States. In: Spacapan S, Oskamp S, editors. The social psychology of health: Claremont Symposium on applied social psychology. Newbury Park, CA: Sage; 1988.
37. Haverman L, van Oers HA, Limperg PF, Houtzager BA, Huisman J, Darlington A-S, et al. Development and Validation of the Distress Thermometer for Parents of a Chronically Ill Child. J Pediatr. 2013;163(4): 1140–6.e2. doi: 10.1016/j.jpeds.2013.06.011 23910979
38. Statistics Canada, Human Resources and Skills Development Canada. The National Longitudinal Survey of Children and Youth (NLSCY)—Survey Overview for the 2008/2009 Data Collection Cycle 8. Statistics Canada. 2010 Nov 10 [Cited 2019 May 10]. http://www.statcan.gc.ca/eng/statistical-programs/document/4450_D2_T9_V4-eng.pdf
39. Vogel DL, Wei M. Adult Attachment and Help-Seeking Intent: The Mediating Roles of Psychological Distress and Perceived Social Support. J Couns Psychol. 2005;52(3): 347.
40. Tomiyama S, Kikuchi M, Yoshimura Y, Hasegawa C, Ikeda T, Saito DN, et al. Changes in maternal feelings for children with autism spectrum disorder after childbirth: The impact of knowledge about the disorder. PLOS ONE. 2018;13(8): e0201862. doi: 10.1371/journal.pone.0201862 30071114
41. Pickard KE, Ingersoll BR. Quality versus quantity: The role of socioeconomic status on parent-reported service knowledge, service use, unmet service needs, and barriers to service use. Autism. 2016;20(1): 106–15. doi: 10.1177/1362361315569745 25948601
Článok vyšiel v časopise
PLOS One
2019 Číslo 9
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Je Fuchsova endotelová dystrofie rohovky neurodegenerativní onemocnění?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Graviola (Annona muricata) attenuates behavioural alterations and testicular oxidative stress induced by streptozotocin in diabetic rats
- CH(II), a cerebroprotein hydrolysate, exhibits potential neuro-protective effect on Alzheimer’s disease
- Comparison between Aptima Assays (Hologic) and the Allplex STI Essential Assay (Seegene) for the diagnosis of Sexually transmitted infections
- Assessment of glucose-6-phosphate dehydrogenase activity using CareStart G6PD rapid diagnostic test and associated genetic variants in Plasmodium vivax malaria endemic setting in Mauritania