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To explore associations between autism traits and family functioning over time, we studied longitudinal data of a mixed group of 168 clinically referred autistic and non-autistic children. Cross-lagged models showed a significant association between fewer autism traits at the diagnostic assessment and better family functioning 1 year later for the whole group, independently of children's internalizing or externalizing behavior. When splitting the group into autistic children (58%) and non-autistic children (42%) based on an autism diagnosis, this association was only significant in the subgroup of non-autistic children with autism traits. We hypothesized that the needs of families experiencing difficulty understanding and adjusting to their children with autism traits, but no clinical autism diagnosis, might be unmet without the training or support facilities offered to families with autistic children. Although further research is needed to explore this association, clinicians may also consider supporting families of non-autistic children with autism traits to prevent family functioning problems. Because high autism trait levels in non-autistic children may be of a different origin than autism, for example, other neurodevelopmental or mental health problems, family training or support should be tailored to the child's underlying difficulties.

This study investigated the association of child, caregiver, and caregiving measurements with the quality of life (QoL) in 81 caregivers (mostly parents) of clinically referred children with autism spectrum disorder (ASD). We used the EuroQol five-dimensional (EQ-5D) questionnaire and the care-related QoL questionnaire (CarerQol) to respectively assess health-related QoL and care-related QoL. Health-related QoL was associated with the caregiver's internalizing problems and adaptive coping, explaining 38% of the variance. Parenting stress and adaptive coping were associated with the care-related QoL and explained 60% of the variance. Child variables were not associated with the caregiver's health- and care-related QoL if caregiver and caregiving variables were taken into account. Findings indicate the importance of the caregiver's mental health, coping, and parenting stress in caring for children with ASD.

This study investigated the association of child, caregiver, and caregiving measurements with the quality of life (QoL) in 81 caregivers (mostly parents) of clinically referred children with autism spectrum disorder (ASD). We used the EuroQol five-dimensional (EQ-5D) questionnaire and the care-related QoL questionnaire (CarerQol) to respectively assess health-related QoL and care-related QoL. Health-related QoL was associated with the caregiver's internalizing problems and adaptive coping, explaining 38% of the variance. Parenting stress and adaptive coping were associated with the care-related QoL and explained 60% of the variance. Child variables were not associated with the caregiver's health- and care-related QoL if caregiver and caregiving variables were taken into account. Findings indicate the importance of the caregiver's mental health, coping, and parenting stress in caring for children with ASD., Author(s): Leontine W. ten Hoopen [sup.1] [sup.2] , Pieter F. A. de Nijs [sup.1] , Jorieke Duvekot [sup.1] , Kirstin Greaves-Lord [sup.1] [sup.3] [sup.4] , Manon H. J. Hillegers [sup.1] [...]

Background: Health economic evaluations using common health-related quality of life measures may fall short in adequately measuring and valuing the benefits of mental health care interventions. The Mental Health Quality of Life questionnaire (MHQoL) is a standardized, self-administered mental health–related quality of life instrument covering 7 dimensions known to be relevant across and valued highly by people with mental health problems. The aim of this study was to derive a Dutch value set for the MHQoL to facilitate its use in cost-utility analyses. Methods: The value set was estimated using a discrete choice experiment (DCE) with duration that accommodated nonlinear time preferences. The DCE was embedded in a web-based self-complete survey and administered to a representative sample (N = 1,308) of the Dutch adult population. The matched pairwise choice tasks were created using a Bayesian heterogeneous D-efficient design. The overall DCE design comprised 10 different subdesigns, with each subdesign containing 15 matched pairwise choice tasks. Each participant was asked to complete 1 of the subdesigns to which they were randomly assigned. Results: The obtained coefficients indicated that "physical health,""mood," and "relationships" were the most important dimensions. All coefficients were in the expected direction and reflected the monotonic structure of the MHQoL, except for level 2 of the dimension "future." The predicted values for the MHQoL ranged from −0.741 for the worst state to 1 for the best state. Conclusions: This study derived a Dutch value set for the recently introduced MHQoL. This value set allows for the generation of an index value for all MHQoL states on a QALY scale and may hence be used in Dutch cost-utility analyses of mental healthcare interventions. Highlights: A discrete choice experiment was used to derive a Dutch value set for the MHQoL. This allows the use of the MHQoL in Dutch cost-utility analyses. The dimensions physical health, mood, and relationships were the most important. The utility values range from −0.741 for the worst state to 1 for the best state. [ABSTRACT FROM AUTHOR]

To explore associations between autism traits and family functioning over time, we studied longitudinal data of a mixed group of 168 clinically referred autistic and non-autistic children. Cross-lagged models showed a significant association between fewer autism traits at the diagnostic assessment and better family functioning 1 year later for the whole group, independently of children's internalizing or externalizing behavior. When splitting the group into autistic children (58%) and non-autistic children (42%) based on an autism diagnosis, this association was only significant in the subgroup of non-autistic children with autism traits. We hypothesized that the needs of families experiencing difficulty understanding and adjusting to their children with autism traits, but no clinical autism diagnosis, might be unmet without the training or support facilities offered to families with autistic children. Although further research is needed to explore this association, clinicians may also consider supporting families of non-autistic children with autism traits to prevent family functioning problems. Because high autism trait levels in non-autistic children may be of a different origin than autism, for example, other neurodevelopmental or mental health problems, family training or support should be tailored to the child's underlying difficulties. Little is known about family functioning over time when raising a child with autism traits, with or without a clinical autism diagnosis. Therefore, we asked caregivers—mostly parents—of a group of 168 children about the family functioning and the child's emotional and behavioral characteristics, as well as autistic traits, twice with about 1 year in between. For numerous reasons, the children were referred to youth mental health care centers, including child and adolescent psychiatric services. Care as usual was offered after the diagnostic assessment if a clinical diagnosis was the assessment outcome. Caregivers reported less problematic family functioning in children with fewer autism traits over time. The child's additional emotional or behavioral characteristics did not seem to influence this relation. Furthermore, we split the whole group into autistic children with a clinical autism diagnosis (58%) and non-autistic children with autism traits but without a clinical diagnosis (42%) to see whether we would find the same results in both groups. Surprisingly, the relation between family functioning and the level of a child's autism traits only held for the subgroup of non-autistic children with autism traits. Thus, raising children with autism traits without a clinical diagnosis may affect family functioning over time. We think that families might have difficulty understanding and adjusting to the autism traits of their children but are lacking the support that is exclusively offered to families of children with a clinical autism diagnosis. We must be cautious because we do not know whether there is a causal relation. Although further research is needed to explore and learn to understand this result, clinicians might consider offering support to families of children with subthreshold autism to prevent problems in family functioning. Because high autism trait levels in non-autistic children may be of a different origin than autism, for example, other neurodevelopmental or mental health problems, family training or support should be tailored to the child's underlying difficulties. [ABSTRACT FROM AUTHOR]

AbstractBackgroundObjectiveMethodsResultsConclusionsWork-related mental health problems impose significant economic and personal burdens. eHealth interventions may offer low-cost, practical solutions, but guidance on their cost-effectiveness in workplace mental health is limited.The objective of this study was to systematically review economic evaluations of workplace eHealth interventions for mental health, offering insights into methodologies and cost-effectiveness outcomes.Adhering to PRISMA guidelines, searches were conducted in Embase, MEDLINE, Web of Science, Google Scholar, Cochrane library, PsycInfo and EconLit databases in May 2022, selecting peer-reviewed papers that performed economic evaluations on workplace eHealth interventions for adult mental health. Quality was assessed using the Drummond checklist.From 3213 references, eight met the inclusion criteria. These studies varied in economic perspective, types of economic analysis type, primary outcome measures, intervention focus (e.g. stress, alcohol, insomnia & return-to-work) and direct non-medical costs. Five eHealth interventions were found to be cost-effective and/or have a positive return on investment, with seven studies rated as high quality according to the Drummond checklist.The study outcomes unveiled the potential cost-effectiveness of eHealth interventions targeting mental health issues, particularly these focusing on workplace stress. However, generalization is challenging due to variations in the methodologies across studies. [ABSTRACT FROM AUTHOR]

This study assessed the quality of life of informal caregivers for individuals with mental health problems in the Netherlands. An online survey was administered to a panel of informal caregivers in June 2020 ( n = 261). Informal caregivers of persons with mental problems were found to have an exceptionally low quality of life. A high subjective burden ( p < .001), lower perseverance time ( p = .016), low caregiver overall health status ( p = .004) and psychological wellbeing ( p = .008), younger caregiver age ( p = .011), child caregiving responsibilities ( p = .025), and no social support network ( p = .038) were associated with worse quality of life scores. These findings shed light on the significant challenges faced by informal caregivers of persons with mental health problem. This raises concerns about the long-term sustainability of informal care and mental healthcare reform., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Background: Occupational e-mental health (OeMH) interventions significantly reduce the burden of mental health conditions. The successful implementation of OeMH interventions is influenced by many implementation strategies, barriers, and facilitators across contexts, which, however, are not systematically tracked. One of the reasons is that international consensus on documenting and reporting the implementation of OeMH interventions is lacking. There is a need for practical guidance on the key factors influencing the implementation of interventions that organizations should consider. Stakeholder consultations secure a valuable source of information about these key strategies, barriers, and facilitators that are relevant to successful implementation of OeMH interventions., Objective: The objective of this study was to develop a brief checklist to guide the implementation of OeMH interventions., Methods: Based on the results of a recently published systematic review, we drafted a comprehensive checklist with a wide set of strategies, barriers, and facilitators that were identified as relevant for the implementation of OeMH interventions. We then used a 2-stage stakeholder consultation process to refine the draft checklist to a brief and practical checklist comprising key implementation factors. In the first stage, stakeholders evaluated the relevance and feasibility of items on the draft checklist using a web-based survey. The list of items comprised 12 facilitators presented as statements addressing "elements that positively affect implementation" and 17 barriers presented as statements addressing "concerns toward implementation." If a strategy was deemed relevant, respondents were asked to rate it using a 4-point Likert scale ranging from "very difficult to implement" to "very easy to implement." In the second stage, stakeholders were interviewed to elaborate on the most relevant barriers and facilitators shortlisted from the first stage. The interview mostly focused on the relevance and priority of strategies and factors affecting OeMH intervention implementation. In the interview, the stakeholders' responses to the open survey's questions were further explored. The final checklist included strategies ranked as relevant and feasible and the most relevant facilitators and barriers, which were endorsed during either the survey or the interviews., Results: In total, 26 stakeholders completed the web-based survey (response rate=24.8%) and 4 stakeholders participated in individual interviews. The OeMH intervention implementation checklist comprised 28 items, including 9 (32.1%) strategies, 8 (28.6%) barriers, and 11 (39.3%) facilitators. There was widespread agreement between findings from the survey and interviews, the most outstanding exception being the idea of proposing OeMH interventions as benefits for employees., Conclusions: Through our 2-stage stakeholder consultation, we developed a brief checklist that provides organizations with a guide for the implementation of OeMH interventions. Future research should empirically validate the effectiveness and usefulness of the checklist., (©Alberto Raggi, Renaldo M Bernard, Claudia Toppo, Carla Sabariego, Luis Salvador Carulla, Sue Lukersmith, Leona Hakkaart-van Roijen, Dorota Merecz-Kot, Beatriz Olaya, Rodrigo Antunes Lima, Desirée Gutiérrez-Marín, Ellen Vorstenbosch, Chiara Curatoli, Martina Cacciatore. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.03.2024.)

Lay Abstract: Little is known about family functioning over time when raising a child with autism traits, with or without a clinical autism diagnosis. Therefore, we asked caregivers-mostly parents-of a group of 168 children about the family functioning and the child's emotional and behavioral characteristics, as well as autistic traits, twice with about 1 year in between. For numerous reasons, the children were referred to youth mental health care centers, including child and adolescent psychiatric services. Care as usual was offered after the diagnostic assessment if a clinical diagnosis was the assessment outcome. Caregivers reported less problematic family functioning in children with fewer autism traits over time. The child's additional emotional or behavioral characteristics did not seem to influence this relation. Furthermore, we split the whole group into autistic children with a clinical autism diagnosis (58%) and non-autistic children with autism traits but without a clinical diagnosis (42%) to see whether we would find the same results in both groups. Surprisingly, the relation between family functioning and the level of a child's autism traits only held for the subgroup of non-autistic children with autism traits. Thus, raising children with autism traits without a clinical diagnosis may affect family functioning over time. We think that families might have difficulty understanding and adjusting to the autism traits of their children but are lacking the support that is exclusively offered to families of children with a clinical autism diagnosis. We must be cautious because we do not know whether there is a causal relation. Although further research is needed to explore and learn to understand this result, clinicians might consider offering support to families of children with subthreshold autism to prevent problems in family functioning. Because high autism trait levels in non-autistic children may be of a different origin than autism, for example, other neurodevelopmental or mental health problems, family training or support should be tailored to the child's underlying difficulties.