New technology for studying the impact of regular singing and song learning on cognitive function in older adults: A feasibility study.

Abstract

As the proportion of older adults increase, there is a need to investigate ways to promote healthy cognitive aging. There is growing interest in longitudinal studies examining the impact of regular musical activity on nonmusical cognitive functions, but the financial and logistical challenges of such studies greatly limits the amount of research on this topic, especially in older adults. To surmount these challenges and stimulate the pace of research in this area we present a novel technology-based method for conducting longitudinal studies of regular singing and song learning in older adults. This method uses a tablet based app (SingFit-R) that is given to participants to take home and used for singing a specified number of songs per day. Participants choose the songs they will sing and then follow a singing schedule created by the experimenter. The app records a variety of data each time a song is sung, including song name, date and time of singing, an audio recording of the singer’s voice, and the user-set volume levels of 2 mnemonic aids that facilitate song learning: a “guide singer” and “lyric coach” (the user reduces the volumes of these aids as a song is learned). By analyzing these data researchers can verify compliance and track song learning over the course of the study. We tested the feasibility of longitudinal research with SingFit-R in a 5-week study in which older adults sang 6 songs per day for 5 days per week. We examined measures of working memory and emotion regulation in this group before and after this intervention, and compared them to control groups that listened to music or had no musical activity. Based on measures of attrition, compliance, and enjoyment among users of the app, we conclude that this method is suitable for larger-scale studies on the cognitive impact of regular singing and song learning in older adults.

Using Music Technology Creatively to Enrich Later-Life: A Literature Review

“…Significant wider benefits of singing in later life have been demonstrated (Clift et al, 2008), but there has been limited research focused on ways in which technology can be harnessed to support older people in engaging with singing. Reid et al (2017) adapted a commercially available iPad application (SingFit) and tested its efficacy as a technology-based method for conducting longitudinal studies of regular singing and song learning in older adults. Forty-eight musically inactive participants (i.e., they had not engaged actively with music-making for at least 40 years) aged 65–84 were allocated to singing, listening, or control groups.…”

“…This evidence is in accordance with research concerned with later-life musical engagement more generally, where it has been demonstrated that older learners develop compensatory strategies to mitigate physical or cognitive constraints (Gembris, 2008). Technologies that support receptive musicking (e.g., listening devices) as well as active musicking (e.g., motion sensor devices, digital musical instruments, singing apps and music composition or improvisation technologies) have been found to support access to the multiple personal, social, cognitive, and physical benefits that have been associated with musicking (e.g., Ellis, 2004; Rosseland, 2016; Reid et al, 2017; Vahia et al, 2017). Furthermore, music technologies have been shown to function as creative tools that may have the capacity to provide “restorative spaces” (Jansen, 2005) that privilege reflection and reminiscence, personal healing and problem solving (Duffey et al, 2008; Somody, 2010; Connell, 2012; Lazar et al, 2014).…”

Digital technologies in music subjects on primary teacher training degrees in Spain: Teachers’ habits and profiles

“…While these areas can be transversal, taking them as a starting point and according to classroom activities, we can categorise the use of the different technological resources as score editors (Bellini, 2008), sequencers and sound generators (Farrimond et al, 2011), audio editors (Silveira & Gavin, 2016), listening training tools (Chan et al, 2006), software for learning to play a musical instrument (Nijs & Leman, 2014; Rowe et al, 2015), developing vocal capacities (Reid et al, 2017) and even audiovisual education resources in the music classroom (Aróstegui, 2010). In these different categories, other types of elements can be transversely included, such as composition using score editors, sequencers, and sound generators and audio editors; coding music using audio editors and sound generators; and so on.…”

Functional electrical stimulation+iPad-based music therapy for upper limb recovery after stroke: Study protocol for a mixed methods randomised controlled trial

“…The purpose of the decision tree in the song learning stream (Figure 5) is to promote greater control of the specificity of movement through familiar and structured training. This stream is based upon theories regarding the reported benefits of music for leisure (Särkämö, 2017), familiar song singing (Daykin et al, 2017) and song learning in older adults (Reid, Rakhilin, Patel, Urry & Thomas, 2017). Even though the focus of this music-making stream is to encourage task-specific motor output by learning a song, the wellbeing (Daykin et al, 2017) and rehabilitative benefits of singing (Stegemöller, Radig, Hibbing, Wingate, & Sapienza, 2017) have also been considered.…”