2019 |
Jaafar, N H; Othman, A; Majid, N A; Harith, S; Zabidi-Hussin, Z Parent-report instruments for assessing feeding difficulties in children with neurological impairments: a systematic review Journal Article Developmental Medicine and Child Neurology, 61 (2), pp. 135-144, 2019, ISSN: 00121622, (cited By 1). Abstract | Links | BibTeX | Tags: Assessment of Humans, Autism, Behavioural Paediatric Feeding Assessment Scale, Caloric Intake, Child Behaviour, Child Parent Relation, Childhood Disease, Children, Children's Eating Behaviour Inventory, Complication, Construct Validity, Content Validity, Criterion Related Validity, Cystic Fibrosis, Eating Disorder, Enalapril Maleate, Eosinophilic Gastrointestinal Disorder, Esophagus Atresia, Feeding, Feeding and Eating Disorders, Feeding Behavior, Feeding Difficulty, Food Intake, Human, Nervous System Diseases, Neurologic Disease, Nutritional Assessment, Parents, Pediatric Assessment Scale for Severe Feeding Problem, Pediatric Eating Assessment Tool, Predictive Value, Preschool, Preschool Child, Priority Journal, Procedures, Psychology, Psychometrics, Psychometry, Quality of Life, Receiver Operating Characteristic, Review, Scoring System, Self Disclosure, Sensitivity and Specificity, Syndrome CHARGE, Systematic Review, Test Retest Reliability @article{Jaafar2019135, title = {Parent-report instruments for assessing feeding difficulties in children with neurological impairments: a systematic review}, author = {N H Jaafar and A Othman and N A Majid and S Harith and Z Zabidi-Hussin}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052789833&doi=10.1111%2fdmcn.13986&partnerID=40&md5=d02a2bfcd15a25988b9c23855cd87444}, doi = {10.1111/dmcn.13986}, issn = {00121622}, year = {2019}, date = {2019-01-01}, journal = {Developmental Medicine and Child Neurology}, volume = {61}, number = {2}, pages = {135-144}, publisher = {Blackwell Publishing Ltd}, abstract = {Aim: This study aimed to review the psychometric properties and clinical application of parent-report instruments that assess feeding difficulties in children with neurological impairments. Method: Papers were identified through five electronic databases based on 15 keywords and were included if they met the following criteria: published in English, described the implementation of parent-report instruments, and included children with neurological impairments (either in the report or a related study population). Results: In total, 1220 relevant abstracts were screened and 22 full-text articles were evaluated. The following six parent-report instruments met the inclusion criteria: (1) Screening Tool of Feeding Problems applied to children, (2) Paediatric Eating Assessment Tool, (3) Paediatric Assessment Scale for Severe Feeding Problems, (4) Montreal Children's Hospital Feeding Scale, (5) Children's Eating Behaviour Inventory, and (6) Behavioural Paediatric Feeding Assessment Scale (BPFAS). Based on comprehensive psychometric testing and consistently good results, the BPFAS was considered the most valid and reliable instrument. The BPFAS also showed good clinical applicability because it was readily available, required a short administration time, and used a simple scoring system. Interpretation: We reviewed the available parent-report instruments for assessing feeding difficulties in children with neurological impairments. The BPFAS had the best psychometric properties and clinical applicability. What this paper adds: Six parent-report instruments were suitable for assessing feeding in children with neurological impairments. The Behavioural Paediatric Feeding Assessment Scale (BPFAS) has the strongest psychometric properties. The BPFAS also has good clinical applicability. © 2018 Mac Keith Press}, note = {cited By 1}, keywords = {Assessment of Humans, Autism, Behavioural Paediatric Feeding Assessment Scale, Caloric Intake, Child Behaviour, Child Parent Relation, Childhood Disease, Children, Children's Eating Behaviour Inventory, Complication, Construct Validity, Content Validity, Criterion Related Validity, Cystic Fibrosis, Eating Disorder, Enalapril Maleate, Eosinophilic Gastrointestinal Disorder, Esophagus Atresia, Feeding, Feeding and Eating Disorders, Feeding Behavior, Feeding Difficulty, Food Intake, Human, Nervous System Diseases, Neurologic Disease, Nutritional Assessment, Parents, Pediatric Assessment Scale for Severe Feeding Problem, Pediatric Eating Assessment Tool, Predictive Value, Preschool, Preschool Child, Priority Journal, Procedures, Psychology, Psychometrics, Psychometry, Quality of Life, Receiver Operating Characteristic, Review, Scoring System, Self Disclosure, Sensitivity and Specificity, Syndrome CHARGE, Systematic Review, Test Retest Reliability}, pubstate = {published}, tppubtype = {article} } Aim: This study aimed to review the psychometric properties and clinical application of parent-report instruments that assess feeding difficulties in children with neurological impairments. Method: Papers were identified through five electronic databases based on 15 keywords and were included if they met the following criteria: published in English, described the implementation of parent-report instruments, and included children with neurological impairments (either in the report or a related study population). Results: In total, 1220 relevant abstracts were screened and 22 full-text articles were evaluated. The following six parent-report instruments met the inclusion criteria: (1) Screening Tool of Feeding Problems applied to children, (2) Paediatric Eating Assessment Tool, (3) Paediatric Assessment Scale for Severe Feeding Problems, (4) Montreal Children's Hospital Feeding Scale, (5) Children's Eating Behaviour Inventory, and (6) Behavioural Paediatric Feeding Assessment Scale (BPFAS). Based on comprehensive psychometric testing and consistently good results, the BPFAS was considered the most valid and reliable instrument. The BPFAS also showed good clinical applicability because it was readily available, required a short administration time, and used a simple scoring system. Interpretation: We reviewed the available parent-report instruments for assessing feeding difficulties in children with neurological impairments. The BPFAS had the best psychometric properties and clinical applicability. What this paper adds: Six parent-report instruments were suitable for assessing feeding in children with neurological impairments. The Behavioural Paediatric Feeding Assessment Scale (BPFAS) has the strongest psychometric properties. The BPFAS also has good clinical applicability. © 2018 Mac Keith Press |
2018 |
Toh, T -H; Tan, V W -Y; Lau, P S -T; Kiyu, A Accuracy of Modified Checklist for Autism in Toddlers (M-CHAT) in Detecting Autism and Other Developmental Disorders in Community Clinics Journal Article Journal of Autism and Developmental Disorders, 48 (1), pp. 28-35, 2018, ISSN: 01623257, (cited By 9). Abstract | Links | BibTeX | Tags: Article, Autism, Autism Assessment, Autism Spectrum Disorders, Checklist, Children, Cohort Analysis, Cohort Studies, Community Health Centers, Developmental Disorders, Diagnostic Accuracy, Female, Health Center, Human, Infant, Major Clinical Study, Malaysia, Male, Mass Screening, Modified Checklist for Autism in Toddlers, Pediatric Hospital, Predictive Value, Preschool, Preschool Child, Priority Journal, Procedures, Psychology, Retrospective Studies, Retrospective Study, Sensitivity and Specificity, Standards, Toddler @article{Toh201828, title = {Accuracy of Modified Checklist for Autism in Toddlers (M-CHAT) in Detecting Autism and Other Developmental Disorders in Community Clinics}, author = {T -H Toh and V W -Y Tan and P S -T Lau and A Kiyu}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028764085&doi=10.1007%2fs10803-017-3287-x&partnerID=40&md5=21bce2407197b8b1e43b4420d274861b}, doi = {10.1007/s10803-017-3287-x}, issn = {01623257}, year = {2018}, date = {2018-01-01}, journal = {Journal of Autism and Developmental Disorders}, volume = {48}, number = {1}, pages = {28-35}, publisher = {Springer New York LLC}, abstract = {This study determined the accuracy of Modified Checklist for Autism in Toddlers (M-CHAT) in detecting toddlers with autism spectrum disorder (ASD) and other developmental disorders (DD) in community mother and child health clinics. We analysed 19,297 eligible toddlers (15–36 months) who had M-CHAT performed in 2006–2011. Overall sensitivities for detecting ASD and all DD were poor but better in the 21 to <27 months and 27–36-month age cohorts (54.5–64.3%). Although positive predictive value (PPV) was poor for ASD, especially the younger cohort, positive M-CHAT helped in detecting all DD (PPV = 81.6%). This suggested M-CHAT for screening ASD was accurate for older cohorts (>21 months) and a useful screening tool for all DD. © 2017, Springer Science+Business Media, LLC.}, note = {cited By 9}, keywords = {Article, Autism, Autism Assessment, Autism Spectrum Disorders, Checklist, Children, Cohort Analysis, Cohort Studies, Community Health Centers, Developmental Disorders, Diagnostic Accuracy, Female, Health Center, Human, Infant, Major Clinical Study, Malaysia, Male, Mass Screening, Modified Checklist for Autism in Toddlers, Pediatric Hospital, Predictive Value, Preschool, Preschool Child, Priority Journal, Procedures, Psychology, Retrospective Studies, Retrospective Study, Sensitivity and Specificity, Standards, Toddler}, pubstate = {published}, tppubtype = {article} } This study determined the accuracy of Modified Checklist for Autism in Toddlers (M-CHAT) in detecting toddlers with autism spectrum disorder (ASD) and other developmental disorders (DD) in community mother and child health clinics. We analysed 19,297 eligible toddlers (15–36 months) who had M-CHAT performed in 2006–2011. Overall sensitivities for detecting ASD and all DD were poor but better in the 21 to <27 months and 27–36-month age cohorts (54.5–64.3%). Although positive predictive value (PPV) was poor for ASD, especially the younger cohort, positive M-CHAT helped in detecting all DD (PPV = 81.6%). This suggested M-CHAT for screening ASD was accurate for older cohorts (>21 months) and a useful screening tool for all DD. © 2017, Springer Science+Business Media, LLC. |
2016 |
Ilias, S; Tahir, N M; Jailani, R; Hasan, C Z C Classification of autism children gait patterns using Neural Network and Support Vector Machine Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509015436, (cited By 5). Abstract | Links | BibTeX | Tags: Accuracy Rate, Autism, Classification (of information), Diseases, Gait Analysis, Gait Parameters, Gait Pattern, Industrial Electronics, Kinematics, Neural Networks, NN Classifiers, Sensitivity and Specificity, Support Vector Machines, Three Categories @conference{Ilias201652, title = {Classification of autism children gait patterns using Neural Network and Support Vector Machine}, author = {S Ilias and N M Tahir and R Jailani and C Z C Hasan}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992135613&doi=10.1109%2fISCAIE.2016.7575036&partnerID=40&md5=55c6d166768ed5fa3b504a2bd3441829}, doi = {10.1109/ISCAIE.2016.7575036}, isbn = {9781509015436}, year = {2016}, date = {2016-01-01}, journal = {ISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics}, pages = {52-56}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {In this study, we deemed further to evaluate the performance of Neural Network (NN) and Support Vector Machine (SVM) in classifying the gait patterns between autism and normal children. Firstly, temporal spatial, kinetic and kinematic gait parameters of forty four subjects namely thirty two normal subjects and twelve autism children are acquired. Next, these three category gait parameters acted as inputs to both classifiers. Results showed that fusion of temporal spatial and kinematic contributed the highest accuracy rate for NN classifier specifically 95% whilst SVM with polynomial as kernel, 95% accuracy rate is contributed by fusion of all gait parameters as inputs to the classifier. In addition, the classifiers performance is validated by computing both value of sensitivity and specificity. With SVM using polynomial as kernel, sensitivity attained is 100% indicated that the classifier's ability to perfectly discriminate normal subjects from autism subjects whilst 85% specificity showed that SVM is able to identify autism subjects as autism based on their gait patterns at 85% rate. © 2016 IEEE.}, note = {cited By 5}, keywords = {Accuracy Rate, Autism, Classification (of information), Diseases, Gait Analysis, Gait Parameters, Gait Pattern, Industrial Electronics, Kinematics, Neural Networks, NN Classifiers, Sensitivity and Specificity, Support Vector Machines, Three Categories}, pubstate = {published}, tppubtype = {conference} } In this study, we deemed further to evaluate the performance of Neural Network (NN) and Support Vector Machine (SVM) in classifying the gait patterns between autism and normal children. Firstly, temporal spatial, kinetic and kinematic gait parameters of forty four subjects namely thirty two normal subjects and twelve autism children are acquired. Next, these three category gait parameters acted as inputs to both classifiers. Results showed that fusion of temporal spatial and kinematic contributed the highest accuracy rate for NN classifier specifically 95% whilst SVM with polynomial as kernel, 95% accuracy rate is contributed by fusion of all gait parameters as inputs to the classifier. In addition, the classifiers performance is validated by computing both value of sensitivity and specificity. With SVM using polynomial as kernel, sensitivity attained is 100% indicated that the classifier's ability to perfectly discriminate normal subjects from autism subjects whilst 85% specificity showed that SVM is able to identify autism subjects as autism based on their gait patterns at 85% rate. © 2016 IEEE. |
2008 |
Amar, H S S Meeting the needs of children with disability in Malaysia Journal Article Medical Journal of Malaysia, 63 (1), pp. 1-3, 2008, ISSN: 03005283, (cited By 20). Links | BibTeX | Tags: Autism, Behaviour Modification, Child Development, Child Health Care, Children, Clinical Assessment, Clinical Decision Making, Developmental Disorders, Developmental Screening, Disabled Children, Editorial, Health Care, Health Care Delivery, Health Practitioner, Health Program, Health Survey, Human, Intellectual Impairment, Learning Disorder, Malaysia, Pediatric Physiotherapy, Pediatric Rehabilitation, Physical Disability, Preschool, Public Health Service, Register, Sensitivity and Specificity, Sensory Dysfunction, Social Adaptation, Social Welfare, Speech Therapy, Support Group, United Kingdom, United States @article{Amar20081, title = {Meeting the needs of children with disability in Malaysia}, author = {H S S Amar}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-49749107033&partnerID=40&md5=968c527b940374a37322a599d3ccc812}, issn = {03005283}, year = {2008}, date = {2008-01-01}, journal = {Medical Journal of Malaysia}, volume = {63}, number = {1}, pages = {1-3}, note = {cited By 20}, keywords = {Autism, Behaviour Modification, Child Development, Child Health Care, Children, Clinical Assessment, Clinical Decision Making, Developmental Disorders, Developmental Screening, Disabled Children, Editorial, Health Care, Health Care Delivery, Health Practitioner, Health Program, Health Survey, Human, Intellectual Impairment, Learning Disorder, Malaysia, Pediatric Physiotherapy, Pediatric Rehabilitation, Physical Disability, Preschool, Public Health Service, Register, Sensitivity and Specificity, Sensory Dysfunction, Social Adaptation, Social Welfare, Speech Therapy, Support Group, United Kingdom, United States}, pubstate = {published}, tppubtype = {article} } |
2019 |
Parent-report instruments for assessing feeding difficulties in children with neurological impairments: a systematic review Journal Article Developmental Medicine and Child Neurology, 61 (2), pp. 135-144, 2019, ISSN: 00121622, (cited By 1). |
2018 |
Accuracy of Modified Checklist for Autism in Toddlers (M-CHAT) in Detecting Autism and Other Developmental Disorders in Community Clinics Journal Article Journal of Autism and Developmental Disorders, 48 (1), pp. 28-35, 2018, ISSN: 01623257, (cited By 9). |
2016 |
Classification of autism children gait patterns using Neural Network and Support Vector Machine Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509015436, (cited By 5). |
2008 |
Meeting the needs of children with disability in Malaysia Journal Article Medical Journal of Malaysia, 63 (1), pp. 1-3, 2008, ISSN: 03005283, (cited By 20). |