Building on burgeoning research in the field of arts and health, this article explores the role that learning musical instruments can play in enhancing wellbeing in older adulthood. Despite an increasing focus on the role of learning in supporting mental wellbeing, there is strikingly little research that examines this in relation to music, or that explores wellbeing as a subjective phenomenon captured through mixed-methods enquiry. This research addresses this gap through two inter-related studies. Study 1 adopts questionnaire measures of wellbeing with 98 music-learning and comparison participants, concluding that learning in older adulthood offers significant wellbeing benefits, with music particularly enhancing some health-promoting behaviours. To explore in more detail what learning music means to older adults, Study 2 adopts qualitative methods with a sub-group of 21 music-learning participants, concluding that learning music can enhance subjective wellbeing through six mechanisms: (1) subjective experiences of pleasure; (2) enhanced social interactions; (3) musically-nuanced engagement in day-to-day life; (4) fulfilment of musical ambition; (5) ability to make music; and (6) self-satisfaction through musical progress. Drawing the two studies together, the article concludes by arguing for further research to contribute to the growing body of evidence placing music learning at the centre of healthy ageing agendas.
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Online support communities are gaining attention among child-attracted persons (CAPs). Though research has largely focused on the negative consequences these environments create for potential offending, they may also provide a beneficial alternative to more formal treatment settings. To assess the utility for clinical and therapeutic purposes, this analysis focused on subcultural dynamics to examine self-reported wellbeing outcomes of participation in a Dutch forum for CAPs. A total of 15 semi-structured interviews were conducted with moderators, members and mental health professionals involved in the community. Thematic analyses demonstrated that by means of informal social control, bonds of trust and social relational education, the network aims to regulate the behavior and enhance the wellbeing of its marginalized participants. Key outcomes include a decreased sense of loneliness and better coping with stigma, to the point that participants experience less suicidal thoughts. Association with prosocial peers also helps to set moral boundaries regarding behavior towards children, although we cannot fully rule out potential adverse influences. Online support networks offer a stepping stone to professional care that fits individual needs of CAPs, while also providing an informal environment that overcomes limitations of physical therapy and that extents principles of existing prevention and desistance approaches. Gepubliceerd door uitgever Sage: Bekkers, L. M. J., Leukfeldt, E. R., & Holt, T. J. (2024). Online Communities for Child-Attracted Persons as Informal Mental Health Care: Exploring Self-Reported Wellbeing Outcomes. Sexual Abuse, 36(2), 158-184. https://doi.org/10.1177/10790632231154882
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Non-professional runners make extensive use of consumer-available wearable devices and smartphone apps to monitor training sessions, health, and physical performance. Despite the popularity of these products, they usually neglect subjective factors, such as psychosocial stress, unexpected daily physical (in)activity, sleep quality perception, and/or previous injuries. Consequently, the implementation of these products may lead to underperformance, reduced motivation, and running-related injuries. This paper investigates how the integration of subjective training, off-training, and contextual factors from a 24/7 perspective might lead to better individual screening and health protection methods for recreational runners. Using an online-based Ecological Momentary Assessment survey, a seven-day cohort study was conducted. Twenty participants answered daily surveys three times a day regarding subjective off-training and contextual data; e.g., health, sleep, stress, training, environment, physiology, and lifestyle factors. The results show that daily habits of people are unstructured, unlikely predictable, and influenced by factors, such as the demands of work, social life, leisure time, or sleep. By merging these factors with sensor-based data, running-related systems would be able to better assess the individual workload of recreational runners and support them to reduce their risk of suffering from running-related injuries
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