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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Background: Adverse Childhood Experiences (ACEs) are an overlooked risk factor for behavioural, mental and physical health disparities in children with intellectual disabilities (ID) and borderline intellectual functioning (BIF). Aims: To gain insight into the presence of the 10 original Wave II ACEs and family context risk variables in a convenience sample of children with ID and BIF in Dutch residential care. Methods and procedures: 134 case-files of children with ID (n = 82) and BIF (n = 52) were analysed quantitatively. Outcomes and results: 81.7 % of the children with ID experienced at least 1 ACE, as did 92.3 % of the children with BIF. The average number of ACEs in children with ID was 2.02 (range 0???? 8) and in children with BIF 2.88 (range 0???? 7). About 20 % of the children with moderate and mild ID experienced 4 ACEs or more. Many of their families faced multiple and complex problems (ID: 69.5 %; BIF 86.5 %). Multiple regression analysis indicated an association between family context risk variables and the number of ACEs in children. Conclusions and implications: The prevalence of ACEs in children with ID and BIF appears to be considerably high. ACEs awareness in clinical practice is vital to help mitigate negative outcomes.
Background: The outbreak of the COVID-19 pandemic influenced family-centred care dramatically due to restricting visiting policies. In this new situation, nurses were challenged to develop new approaches to involve family members in patient care. A better understanding of these changes and the experiences of nurses is essential to make an adaptation of procedures, and to secure a family-centred approach in care as much as possible. Objectives: The aim of this study was to investigate how family involvement had taken place, and to explore the experiences of nurses with family involvement during the COVID-19 outbreak. In addition, we aimed to formulate recommendations for the involvement of family. Methods: We conducted a qualitative study using patient record review and focus-group interviews between April and July 2020. We reviewed records of patients with confirmed COVID-19, who were admitted to the COVID-19 wards at two affiliated university hospitals in the Netherlands. All records were searched for notations referring to family involvement. In two focus-groups, nurses who worked at the COVID-19 wards were invited to share their experiences. The Rigorous and Accelerated Data Reduction (RADaR) method was used to collect, reduce and analyse the data. Results: In total, 189 patient records were reviewed and nine nurses participated in the focus-group meetings. Patient records revealed infrequent and often unstructured communication with focus on physical condition. Nurses confirmed that communication with family was far less than before and that the physical condition of the patient was predominant. The involvement of family in care was limited to practicalities, although more involvement was described in end-of-life situations. Nurses experienced moral distress due to the visiting restrictions, though some acknowledged that they had experienced the direct patient care so intense and burdensome, that family contact simply felt too much. Conclusion: The communication with and involvement of family in hospital care changed enormously during the COVID-19 outbreak. Based on the identified themes, we formulated recommendations that may be helpful for family-centered care in hospitals during periods of restricted visiting policy.
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).
