D Barthel1, U Ravens-Sieberer2, S Nolte3, U Thyen4, M Klein5, O Walter6, A-K Meyrose7, M Rose8, C Otto7. 1. Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Research Unit Child Public Health, Center for Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. Electronic address: d.barthel@uke.de. 2. Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Research Unit Child Public Health, Center for Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. Electronic address: ravens-sieberer@uke.de. 3. Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Department of Psychosomatic Medicine, Center of Internal Medicine and Dermatology, Charitéplatz 1, 10117 Berlin, Germany; Population Health Strategic Research Centre, School of Health and Social Development, Deakin University, Locked Bag 20001, Geelong, VIC 3220, Australia. 4. Hospital for Pediatrics and Adolescent Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany. 5. Department of Pediatrics, University Medical Center Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, House 9, 24105 Kiel, Germany. 6. Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Department of Psychosomatic Medicine, Center of Internal Medicine and Dermatology, Charitéplatz 1, 10117 Berlin, Germany. 7. Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Research Unit Child Public Health, Center for Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. 8. Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Department of Psychosomatic Medicine, Center of Internal Medicine and Dermatology, Charitéplatz 1, 10117 Berlin, Germany; Department of Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA.
Abstract
OBJECTIVE: This study aims at identifying predictors of generic health-related quality of life (HRQoL) in chronically ill children and adolescents over time. The newly developed computer-adaptive test Kids-CAT was used to assess five dimensions of HRQoL. METHODS: Longitudinal data from the Kids-CAT study on children and adolescents with asthma, diabetes and juvenile arthritis (n = 248; aged 7-17 years) were assessed at three measurement points over six months. Individual growth modeling served to investigate effects of sociodemographic, disease- and health-related as well as psychosocial factors on HRQoL dimensions Physical Well-Being (WB), Psychological WB, Parent Relations, Social Support & Peers, and School WB over time. RESULTS: Besides effects of sociodemographic variables on HRQoL dimensions Social Support & Peers as well as School WB, we found that a longer duration of the disease was associated with better Physical WB. Lower scores were found for patients with juvenile arthritis compared to those with diabetes in HRQoL dimensions Physical WB and Social Support & Peers. Disease control was positively related to Physical and Psychological WB over time. Mental health problems were negatively associated with four, and subjective health complaints with all five HRQoL dimensions over time. Parental mental health was positively related to the patients' HRQoL score in Parent Relations over time. CONCLUSIONS: HRQoL as a multidimensional construct is associated with a wide range of different factors. Pediatricians should consider potential mental health problems and subjective health complaints in their patients. Finally, parental HRQoL can affect HRQoL in chronically ill children and adolescents.
OBJECTIVE: This study aims at identifying predictors of generic health-related quality of life (HRQoL) in chronically ill children and adolescents over time. The newly developed computer-adaptive test Kids-CAT was used to assess five dimensions of HRQoL. METHODS: Longitudinal data from the Kids-CAT study on children and adolescents with asthma, diabetes and juvenile arthritis (n = 248; aged 7-17 years) were assessed at three measurement points over six months. Individual growth modeling served to investigate effects of sociodemographic, disease- and health-related as well as psychosocial factors on HRQoL dimensions Physical Well-Being (WB), Psychological WB, Parent Relations, Social Support & Peers, and School WB over time. RESULTS: Besides effects of sociodemographic variables on HRQoL dimensions Social Support & Peers as well as School WB, we found that a longer duration of the disease was associated with better Physical WB. Lower scores were found for patients with juvenile arthritis compared to those with diabetes in HRQoL dimensions Physical WB and Social Support & Peers. Disease control was positively related to Physical and Psychological WB over time. Mental health problems were negatively associated with four, and subjective health complaints with all five HRQoL dimensions over time. Parental mental health was positively related to the patients' HRQoL score in Parent Relations over time. CONCLUSIONS: HRQoL as a multidimensional construct is associated with a wide range of different factors. Pediatricians should consider potential mental health problems and subjective health complaints in their patients. Finally, parental HRQoL can affect HRQoL in chronically ill children and adolescents.
Authors: Mark A Ferro; Saad A Qureshi; Lilly Shanahan; Christiane Otto; Ulrike Ravens-Sieberer Journal: Qual Life Res Date: 2021-07-31 Impact factor: 4.147
Authors: Patricia de Gouveia Belinelo; Aleisha Nielsen; Bernadette Goddard; Lauren Platt; Carla Rebeca Da Silva Sena; Paul D Robinson; Bruce Whitehead; Jodi Hilton; Tanya Gulliver; Laurence Roddick; Kasey Pearce; Vanessa E Murphy; Peter G Gibson; Adam Collison; Joerg Mattes Journal: BMC Pulm Med Date: 2020-03-18 Impact factor: 3.317