This study explored what contributes to successful family foster care from the perspective of young people by asking them about their most positive memory of family foster care. Forty-four Dutch adolescents and young adults (aged 16–28) participated in this study and shared their most positive memory in a short interview. Their answers were qualitatively analyzed using reflexive thematic analysis, supplemented with an analysis of the structure of their memories. The thematic analysis resulted in the themes Belongingness, Receiving support, Normal family life, It is better than before, and Seeing yourself grow. The structural analysis showed that young people both shared memories related to specific events, as well as memories that portrayed how they felt for a prolonged period of time. In addition, young people were inclined to share negative memories alongside the positive memories. These results highlight that, in order to build a sense of belonging, it is important that of foster parents create a normal family environment for foster children and provide continuous support. Moreover, the negative memories shared by participants are discussed in light of a bias resulting from earlier traumatic experiences. Accepted Version. Published Version Article at Sage: https://doi.org/10.1177%2F1359104520978691
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Parents who grew up without digital monitoring have a plethora of parental monitoring opportunities at their disposal. While they can engage in surveillance practices to safeguard their children, they also have to balance freedom against control. This research is based on in-depth interviews with eleven early adolescents and eleven parents to investigate everyday negotiations of parental monitoring. Parental monitoring is presented as a form of lateral surveillance because it entails parents engaging in surveillance practices to monitor their children. The results indicate that some parents are motivated to use digital monitoring tools to safeguard and guide their children, while others refrain from surveillance practices to prioritise freedom and trust. The most common forms of surveillance are location tracking and the monitoring of digital behaviour and screen time. Moreover, we provide unique insights into the use of student tracking systems as an impactful form of control. Early adolescents negotiate these parental monitoring practices, with responses ranging from acceptance to active forms of resistance. Some children also monitor their parents, showcasing a reciprocal form of lateral surveillance. In all families, monitoring practices are negotiated in open conversations that also foster digital resilience. This study shows that the concepts of parental monitoring and lateral surveillance fall short in grasping the reciprocal character of monitoring and the power dynamics in parent-child relations. We therefore propose that monitoring practices in families can best be understood as family surveillance, providing a novel concept to understand how surveillance is embedded in contemporary media practices among interconnected family members.
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Marfan syndrome (MFS) is a multisystemic, autosomal dominant connective tissue disorder that occurs de novo in 25%. In many families, parent and child(ren) are affected, which may increase distress in parents. To assess distress, 42 mothers (29% MFS) and 25 fathers (60% MFS) of 43 affected children, completed the validated screening‐questionnaire Distress thermometer for parents of a chronically ill child, including questions on overall distress (score 0–10; ≥4 denoting “clinical distress”) and everyday problems (score 0–36). Data were compared to 1,134 control‐group‐parents of healthy children. Mothers reported significantly less overall distress (2, 1–4 vs. 3, 1–6; p = .049; r = −.07) and total everyday problems (3, 0–6 vs. 4, 1–8; p = .03; r = −.08) compared to control‐group‐mothers. Mothers without MFS reported significantly less overall distress compared to mothers with MFS, both of a child with MFS (1, 0–4 vs. 3.5, 2–5; p = .039; r = −.17). No significant differences were found between the father‐groups, nor between the group of healthy parents of an affected child living together with an affected partner compared to control‐group‐parents. No differences in percentages of clinical distress were reported between mothers and control‐group‐mothers (33 vs. 42%); fathers and control‐group‐fathers (28 vs. 32%); nor between the other groups. Distress was not associated with the children's MFS characteristics. Concluding, parents of a child with MFS did not show more clinical distress compared to parents of healthy children. However, clinical distress was reported in approximately one‐third and may increase in case of acute medical complications. We advise monitoring distress in parents of a child with MFS to provide targeted support.
Significant Others, family care, substance abuse, addiction, substance use disorder, Concerned significant others of a person with substance use disorder face psychological, social and financial problems caused by the subtance abuse of their loved one. Tradionally health care orginizations focus on the person with substance use disorder and pay less attention to their concerned significant other. In the Netherlands there is less information available about concerned significant others of persons with substance abuse. To develop a family care aproach for the significant other it's necessary to provide insight in the charasteristics of the concerned significant others of persons with substance use disorder.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
