Paediatrics (RCH) - Research Publications
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ItemPsychometric Performance Comparison of the Adapted versus Original Versions of the EQ-5D-Y-3L and -Y-5L in Proxy Respondents for 2-to 4-Year-Olds(ADIS INT LTD, 2024-01-18)INTRODUCTION: Few preference-weighted instruments are available to measure health-related quality of life in young children (2-4 years of age). The EQ-5D-Y-3L and EQ-5D-Y-5L were recently modified for this purpose. OBJECTIVE: The aim of this study was to test the psychometric properties of these adapted versions for use with parent proxies of children aged 2-4 years and to compare their performance with the original versions. It was hypothesised that the adapted instrument wording would result in improved psychometric performance. METHODS: Survey data of children aged 2-4 years were obtained from the Australian Paediatric Multi-Instrument Comparison study. Distributional and psychometric properties tested included feasibility, convergence, distribution of level scores, ceiling effects, known-group validity (Cohen's D effect sizes for prespecified groups defined by the presence/absence of special healthcare needs [SHCNs]), test-retest reliability (intraclass correlation coefficients [ICCs]), and responsiveness (standardised response mean [SRM] effect sizes for changes in health). Level sum scores were used to provide summary outcomes. Supplementary analysis using utility scores (from the Swedish EQ-5D-Y-3L value set) were conducted for the adapted and original EQ-5D-Y-3L, and no value sets were available for the EQ-5D-Y-5L. RESULTS: A total of 842 parents of children aged 2-4 years completed the survey. All instruments were easy to complete. There was strong convergence between the adapted and original EQ-5D-Y-3L and EQ-5D-Y-5L. The adapted EQ-5D-Y-3L and adapted EQ-5D-Y-5L showed more responses in the severe levels of the five EQ-5D-Y dimensions, particularly in the usual activity and mobility dimensions (EQ-5D-Y-5L: mobility level 1: adapted n = 478 [83%], original n = 253 [94%]; mobility level 4/5: adapted n = 17 [2.9%], original n = 4 [1.5%)]). The difference in the distribution of responses was more evident in children with SHCNs. Assessment of known-group validity showed a greater effect size for the adapted EQ-5D-Y-3L and adapted EQ-5D-Y-5L compared with the original instruments (EQ-5D-Y-5L: adapted Cohen's D = 1.01, original Cohen's D = 0.83) between children with and without SHCNs. The adapted EQ-5D-Y-3L and adapted EQ-5D-Y-5L showed improved reliability at 4-week follow-up, with improved ICCs (EQ-5D-Y-5L: adapted ICC = 0.83, original ICC = 0.44). The responsiveness of all instruments moved in the hypothesised direction for better or worse health at follow-up. Probability of superiority analysis showed little/no differences between the adapted and original EQ-5D-Y-3L and EQ-5D-Y-5L. Supplementary psychometric analysis of the adapted and original EQ-5D-Y-3L using utilities showed comparable findings with analyses using level sum scores. CONCLUSIONS: The findings suggest improved psychometric performance of the adapted version of the EQ-5D-Y-3L and EQ-5D-Y-5L in children aged 2-4 years compared with the original versions.
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ItemComparative Psychometric Performance of Common Generic Paediatric Health-Related Quality of Life Instrument Descriptive Systems: Results from the Australian Paediatric Multi-Instrument Comparison Study(ADIS INT LTD, 2023-11-13)OBJECTIVE: The aim of this study was to compare the psychometric performance of common generic paediatric health-related quality-of-life instrument descriptive systems (PedsQL generic core 4.0, EQ-5D-Y-3L, EQ-5D-Y-5L, Child Health Utility 9D [CHU9D], Assessment of Quality of Life 6D [AQoL-6D], and Health Utilities Index Mark 3 [HUI3]) by child age, report type, and health status. METHODS: Data for children aged 5-18 years were from the Australian Paediatric Multi-Instrument Comparison study. Ceiling effects, test-retest reliability, known-group validity, convergent and divergent validity, and responsiveness were assessed in the total sample and by child age (5-12 years vs 13-18 years), report type (self- vs proxy report), and health status. Instruments were scored using an exploratory level sum score (LSS) approach. RESULTS: Survey data were available for 5945 children, with follow-up data available for 2346 children. The EQ-5D-Y-3L demonstrated ceiling effects. The PedsQL, EQ-5D-Y-3L, EQ-5D-Y-5L, and CHU9D demonstrated acceptable test-retest reliability. All instruments demonstrated known-group, convergent, and divergent validity. The EQ-5D-Y-3L, EQ-5D-Y-5L, and CHU9D demonstrated responsiveness to improvements in health and the PedsQL, EQ-5D-Y-3L, EQ-5D-Y-5L, and CHU9D to worsening health. The AQoL-6D and HUI3 had inconclusive test-retest reliability and responsiveness evidence due to small sample size. Importantly, ceiling effects, test-retest reliability and responsiveness varied by subgroup. CONCLUSION: Results reflect instrument performance using LSSs, which may differ to utility scores. In the total sample, the EQ-5D-Y-5L and CHU9D descriptive systems demonstrated evidence of good performance (i.e., meeting prespecified criteria) across all psychometric attributes tested. Performance varied by child age and report type, indicating room for considerations by population and study.
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ItemComparing the Psychometric Performance of Generic Paediatric Health-Related Quality of Life Instruments in Children and Adolescents with ADHD, Anxiety and/or Depression(Adis, 2024)Objective: The aim of this study was to examine the validity, reliability and responsiveness of common generic paediatric health-related quality of life (HRQoL) instruments in children and adolescents with mental health challenges. Methods: Participants were a subset of the Australian Paediatric Multi-Instrument Comparison (P-MIC) study and comprised 1013 children aged 4–18 years with attention-deficit/hyperactivity disorder (ADHD) (n = 533), or anxiety and/or depression (n = 480). Participants completed an online survey including a range of generic paediatric HRQoL instruments (PedsQL, EQ-5D-Y-3L, EQ-5D-Y-5L, CHU9D) and mental health symptom measures (SDQ, SWAN, RCADS-25). A subset of participants also completed the HUI3 and AQoL-6D. The psychometric performance of each HRQoL instrument was assessed regarding acceptability/feasibility; floor/ceiling effects; convergent validity; known-group validity; responsiveness and test–retest reliability. Results: The PedsQL, CHU9D, EQ-5D-Y-3L and EQ-5D-Y-5L showed similarly good performance for acceptability/feasibility, known-group validity and convergent validity. The CHU9D and PedsQL showed no floor or ceiling effects and fair–good test–retest reliability. Test–retest reliability was lower for the EQ-5D-Y-3L and EQ-5D-Y-5L. The EQ-5D-Y-3L showed the highest ceiling effects, but was the top performing instrument alongside the CHU9D on responsiveness to improvements in health status, followed by the PedsQL. The AQoL-6D and HUI3 showed good acceptability/feasibility, no floor or ceiling effects, and good convergent validity, yet poorer performance on known-group validity. Responsiveness and test–retest reliability were not able to be assessed for these two instruments. In subgroup analyses, performance was similar for all instruments for acceptability/feasibility, known-group and convergent validity, however, relative strengths and weaknesses for each instrument were noted for ceiling effects, responsiveness and test–retest reliability. In sensitivity analyses using utility scores, performance regarding known-group and convergent validity worsened slightly for the EQ-5D-Y-3L and CHU9D, though improved slightly for the HUI3 and AQoL-6D. Conclusions: While each instrument showed strong performance in some areas, careful consideration of the choice of instrument is advised, as this may differ dependent on the intended use of the instrument, and the age, gender and type of mental health condition of the population in which the instrument is being used. Trial Registration: ANZCTR—ACTRN12621000657820.
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ItemDistinct developmental trajectories of health-related quality of life for boys and girls throughout childhood and adolescence; a national level longitudinal study(BMC, 2023-08-01)BACKGROUND: To identify and describe distinct developmental trajectories of health-related quality of life (HRQoL) in a national level Australian population sample, overall and separately for boys and girls. METHODS: Data were from the Longitudinal Study of Australian Children (LSAC). Participants were children aged 4-5 years recruited in 2004 and followed through to age 16-17 years in 2016, and their caregivers. Group-based trajectory modelling was used to identify groups of children that follow qualitatively distinct developmental trajectories of HRQoL. RESULTS: Three distinct trajectories were identified for the total sample: (1) high-stable (52.2% of children); (2) middle-stable (38.0%); and (3) low-declining (9.8%). These trajectories differed for boys, who saw increasing HRQoL in the highest trajectory group; a middle-stable trajectory; and declining and rebounding HRQoL in the lowest trajectory group. In contrast, girls saw no increasing or rebounding trajectories; approximately half of girls had high-stable HRQoL and the remaining half had either steadily or rapidly declining HRQoL from age 4-5 to 16-17 years. CONCLUSIONS: Our results highlight the importance of considering the distinct trajectories for girls and boys and not relying on population mean levels of HRQoL for decision-making. The presence of developmentally distinct trajectories of HRQoL, and differences in the trajectories faced by boys and girls, should be considered when assessing the effectiveness of treatments and interventions impacting upon HRQoL throughout childhood and adolescence. Failure to account for these pre-existing trajectories may over- or under-estimate treatment effects.
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ItemNo Preview AvailableIdentifying and responding to family adversity in Australian community and primary health settings: a multi-site cross sectional study(Frontiers Media S.A., 2023-09-13)BACKGROUND: Unaddressed family adversity has potentially modifiable, negative biopsychosocial impacts across the life course. Little is known about how Australian health and social practitioners identify and respond to family adversity in community and primary health settings. OBJECTIVE: To describe, in two Australian community health services: (1) the number of adversities experienced by caregivers, (2) practitioner identification of caregivers experiencing adversity, (3) practitioner response to caregivers experiencing adversity, and (4) caregiver uptake of referrals. METHODS: Survey of caregivers of children aged 0-8 years attending community health services in Victoria and New South Wales (NSW). Analysis described frequencies of caregiver self-reported: (1) experiences of adversity, (2) practitioner identification of adversity, (3) practitioner response to adversity, and (4) referral uptake. Analyses were sub-grouped by three adversity domains and site. RESULTS: 349 caregivers (Victoria: n = 234; NSW: n = 115) completed the survey of whom 88% reported experiencing one or more family adversities. The median number of adversities was 4 (2-6). Only 43% of participants were directly asked about or discussed an adversity with a practitioner in the previous 6 months (Victoria: 30%; NSW: 68%). Among caregivers experiencing adversity, 30% received direct support (Victoria: 23%; NSW: 43%), and 14% received a referral (Victoria: 10%; NSW: 22%) for at least one adversity. Overall, 74% of caregivers accepted referrals when extended. CONCLUSION: The needs of Australian families experiencing high rates of adversity are not systematically identified nor responded to in community health services. This leaves significant scope for reform and enhancement of service responses to families experiencing adversity.
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ItemAre We Agreed? Self- Versus Proxy-Reporting of Paediatric Health-Related Quality of Life (HRQoL) Using Generic Preference-Based Measures: A Systematic Review and Meta-Analysis(ADIS INT LTD, 2022-11)OBJECTIVE: The aim of this study was to examine the level of agreement between self- and proxy-reporting of health-related quality of life (HRQoL) in children (under 18 years of age) using generic preference-based measures. METHODS: A systematic review of primary studies that reported agreement statistics for self and proxy assessments of overall and/or dimension-level paediatric HRQoL using generic preference-based measures was conducted. Where available, data on intraclass correlation coefficients (ICCs) were extracted to summarise overall agreement levels, and Cohen's kappa was used to describe agreement across domains. A meta-analysis was also performed to synthesise studies and estimate the level of agreement between self- and proxy-reported paediatric overall and domain-level HRQoL. RESULTS: Of the 30 studies included, 25 reported inter-rater agreement for overall utilities, while 17 reported domain-specific agreement. Seven generic preference-based measures were identified as having been applied: Health Utilities Index (HUI) Mark 2 and 3, EQ-5D measures, Child Health Utility 9 Dimensions (CHU9D), and the Quality of Well-Being (QWB) scale. A total of 45 dyad samples were included, with a total pooled sample of 3084 children and 3300 proxies. Most of the identified studies reported a poor inter-rater agreement for the overall HRQoL using ICCs. In contrast to more observable HRQoL domains relating to physical health and functioning, the inter-rater agreement was low for psychosocial-related domains, e.g., 'emotion' and 'cognition' attributes of both HUI2 and HUI3, and 'feeling worried, sad, or unhappy' and 'having pain or discomfort' domains of the EQ-5D. Parents demonstrated a higher level of agreement with children relative to health professionals. Child self- and proxy-reports of HRQoL showed lower agreement in cancer-related studies than in non-cancer-related studies. The overall ICC from the meta-analysis was estimated to be 0.49 (95% confidence interval 0.34-0.61) with poor inter-rater agreement. CONCLUSION: This study provides evidence from a systematic review of studies reporting dyad assessments to demonstrate the discrepancies in inter-rater agreement between child and proxy reporting of overall and domain-level paediatric HRQoL using generic preference-based measures. Further research to drive the inclusion of children in self-reporting their own HRQoL wherever possible and limiting the reliance on proxy reporting of children's HRQoL is warranted.
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ItemStrengthening Care for Children (SC4C): protocol for a stepped wedge cluster randomised controlled trial of an integrated general practitioner-paediatrician model of primary care(BMJ PUBLISHING GROUP, 2022-09)INTRODUCTION: Australia's current healthcare system for children is neither sustainable nor equitable. As children (0-4 years) comprise the largest proportion of all primary care-type emergency department presentations, general practitioners (GPs) report feeling undervalued as an integral member of a child's care, and lacking in opportunities for support and training in paediatric conditions. This Strengthening Care for Children (SC4C) randomised trial aims to evaluate a novel, integrated GP-paediatrician model of care, that, if effective, will improve GP quality of care, reduce burden to hospital services and ensure children receive the right care, at the right time, closer to home. METHODS AND ANALYSIS: SC4C is a stepped wedge cluster randomised controlled trial (RCT) of 22 general practice clinics in Victoria and New South Wales, Australia. General practice clinics will provide control period data before being exposed to the 12-month intervention which will be rolled out sequentially each month (one clinic per state) until all 22 clinics receive the intervention. The intervention comprises weekly GP-paediatrician co-consultation sessions; monthly case discussions; and phone and email paediatrician support, focusing on common paediatric conditions. The primary outcome of the trial is to assess the impact of the intervention as measured by the proportion of children's (0-<18 years) GP appointments that result in a hospital referral, compared with the control period. Secondary outcomes include GP quality of care; GP experience and confidence in providing paediatric care; family trust in and preference for GP care; and the sustainability of the intervention. An implementation evaluation will assess the model to inform acceptability, adaptability, scalability and sustainability, while a health economic evaluation will measure the cost-effectiveness of the intervention. ETHICS AND DISSEMINATION: Human research ethics committee (HREC) approval was granted by The Royal Children's Hospital Ethics Committee in August 2020 (Project ID: 65955) and site-specific HRECs. The investigators (including Primary Health Network partners) will communicate trial results to stakeholders and participating GPs and general practice clinics via presentations and publications. TRIAL REGISTRATION NUMBER: Australia New Zealand Clinical Trials Registry 12620001299998.
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ItemIntegrated Child and Family Hub models for detecting and responding to family adversity: protocol for a mixed-methods evaluation in two sites(BMJ PUBLISHING GROUP, 2022-05)INTRODUCTION: Integrated community healthcare Hubs may offer a 'one stop shop' for service users with complex health and social needs, and more efficiently use service resources. Various policy imperatives exist to implement Hub models of care, however, there is a dearth of research specifically evaluating Hubs targeted at families experiencing adversity. To contribute to building this evidence, we propose to co-design, test and evaluate integrated Hub models of care in two Australian community health services in low socioeconomic areas that serve families experiencing adversity: Wyndham Vale in Victoria and Marrickville in New South Wales. METHODS AND ANALYSIS: This multisite convergent mixed-methods study will run over three phases to (1) develop the initial Hub programme theory through formative research; (2) test and, then, (3) refine the Hub theory using empirical data. Phase 1 involves co-design of each Hub with caregivers, community members and practitioners. Phase 2 uses caregiver and Hub practitioner surveys at baseline, and 6 and 12 months after Hub implementation, and in-depth interviews at 12 months. Two stakeholder groups will be recruited: caregivers (n=100-200 per site) and Hub practitioners (n=20-30 per site). The intervention is a co-located Hub providing health, social, legal and community services with no comparator. The primary outcomes are caregiver-reported: (i) identification of, (ii) interventions received and/or (iii) referrals received for adversity from Hub practitioners. The study also assesses child, caregiver, practitioner and system outcomes including mental health, parenting, quality of life, care experience and service linkages. Primary and secondary outcomes will be assessed by examining change in proportions/means from baseline to 6 months, from 6 to 12 months and from baseline to 12 months. Service linkages will be analysed using social network analysis. Costs of Hub implementation and a health economics analysis of unmet need will be conducted. Thematic analysis will be employed to analyse qualitative data. ETHICS AND DISSEMINATION: Royal Children's Hospital and Sydney Local Health District ethics committees have approved the study (HREC/62866/RCHM-2020). Participants and stakeholders will receive results through meetings, presentations and publications. TRIAL REGISTRATION NUMBER: ISRCTN55495932.
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ItemThe relationship between physical and mental health multimorbidity and children's health-related quality of life(SPRINGER, 2022-07)PURPOSE: To examine the relationships between physical health problems, and borderline or clinical levels of mental health symptoms and children's health-related quality of life (HRQoL). METHODS: Data were from the Longitudinal Study of Australian Children (2004-2018). Parents reported on their child's HRQoL (PedsQL), physical health problems and mental health symptoms (Strengths and Difficulties Questionnaire, SDQ). A pooled cross-sectional analysis using linear regressions examined the relationships between physical health and clinical/borderline mental health symptoms, individually and when multi-morbid, and children's HRQoL, and whether these relationships vary by a range of child, family and social factors. RESULTS: The sample comprised 47,567 observations of children aged 4-17 years. Borderline and clinical levels of mental health symptoms were associated with significantly lower HRQoL, equal to more than two-times (10.5 points) and more than three-times (16.8 points) the clinically meaningful difference, respectively. This was a larger difference than that associated with physical health problems (4.4 points). We found a significant interaction effect between physical health problems and clinical mental health symptoms which was associated with even poorer HRQoL after accounting for the individual relationships of both problems. Mental health problems were associated with poorer HRQoL for older versus younger children; and the interaction effect was significant for boys but not girls. CONCLUSION: Findings highlight the importance of identifying and addressing mental health symptoms in children of all ages, even if these problems do not meet formal clinical criteria. Particular attention should be paid to the mental health and HRQoL of children with physical-mental multimorbidity, who are at risk of disproportionately poorer HRQoL.
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ItemPatient preferences using telehealth during the COVID-19 pandemic in four Victorian tertiary hospital services(WILEY, 2022-05)BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has had a major impact on healthcare services with many changes to telehealth care delivery. More information is needed about the patient perspective of telehealth in hospital services and the potential costs and benefits for patients. AIM: To measure patients' evaluation of telehealth, preferences for telehealth versus in-person appointments, and potential cost savings by patient characteristics. METHODS: A cross-sectional online survey (including patient and appointment characteristics, telehealth evaluation, preferences for care and costs) of adult patients using video telehealth in four metropolitan tertiary hospital services in Melbourne, Victoria. RESULTS: A total of 1045 patients (median age 44 years; interquartile range 29-59) participated with an overall response rate of 9.2%. For 98.7% patients, telehealth was convenient, 96.4% stated that it saved time, 95.9% found telehealth acceptable to receive care and 97.0% found that telehealth improved their access to care. Most (62.6%) preferred in-person consultations, although 86.9% agreed that telehealth was equivalent to an in-person consultation. Those in regional and rural areas were less likely to prefer in-person consultations. Patients attending for medical reasons were less likely to prefer in-person consultation compared with patients with surgical reasons. Patient preference to telehealth was independent of level of education, appointment type, self-rated health status and socio economic status. Patients saved an average of A$120.9 (standard deviation A$93.0) per appointment, with greater cost savings for patients from low and middle socio economic areas and regional or rural areas. CONCLUSION: Telehealth video consultations were largely evaluated positively with most patients considering the service to be as good as in-person. Understanding patient preference is critical to consider when implementing telehealth as mainstream across hospital health services.