Feasibility Study to Quantify the Auditory and Social Environment of Older Adults Using a Digital Language Processor

Abstract

Objective To investigate the feasibility of using a digital language processor (DLP) to objectively quantify the auditory and social environment of older adults. Design Thirty-seven participants aged 64–91 residing in a retirement community were asked to wear a DLP to record their auditory and language environment during one waking day. Recordings were analyzed with specialized software to derive quantitative estimates such as the number of spoken words heard and percent of time spent around meaningful speech versus television/radio. Results Adequate DLP recordings that began before 10 A.M. and lasted for ≥ 10 hours were collected from 24 participants. The mean duration of recording was 13 hours and 13 minutes, and individuals spent a mean of 26.7% (range=4% – 58%) of their waking day near a television or other electronic sounds. The projected mean word count over a maximum of 16 hours was 33,141 with nearly a 14-fold range between the lowest and highest observed values (range=5120 – 77,882). Conclusions High-quality objective data on the auditory environment of older adults can be feasibly measured with the DLP. Findings from this study may guide future studies investigating auditory and language outcomes in older adults.

Using a Digital Language Processor to Quantify the Auditory Environment and the Effect of Hearing Aids for Adults with Hearing Loss

“…Although the methodology and specific categories of auditory environments differed between the present study, Wu and Bentler (2012), and Wagener et al (2008), the similarity of the estimates of time spent in speech environments in the three studies supports the validity of the present findings. Using the LENADLP, Li et al (2014) found that average percentage of time spent in meaningful speech and distant speech environments were 19.3%and 22.4%, respectively, which are somewhat higher than the findings of the present study. Li et al also reported that the average percentage of time spent in silence was 26.9%, which is lower than the~40%of the time spent in silence found in the present study.…”

“…Our finding that participants spent ~26% of their time in TV/electronic sound environments agrees well with previous studies, which showed that older adults spent 24% (Wu and Bentler, 2012) and 26.7% (Li et al, 2014) of their time listening to TV and other media. With regard to time spent in speech environments, Wu and Bentler (2012) reported that participants spent 61.2% of their time in speech environments, while Wagener et al (2008) found that 50.7% of recordings from participants contained speech, including speech produced by the TV and other electronic media.…”

“…Note that variation was high between individuals: AWC per hour ranged from 339 for one participant to 2,927 for another participant in the unaided condition. The mean AWC per hour found in the unaided and aided conditions of the present study was substantially lower than the mean AWC per hour found by Li et al (2014), which was 2,508words (note that because Li et al only reported AWC for the total length of participants’ recordings, average AWC per hour was calculated by dividing the mean AWC of 33,141 by the mean total recording time, 13 hr and 13 min).…”

“…More importantly, the LENA system provides access to detailed second-by-second data of sound levels and auditory environment classification, which allows for in-depth data mining. LENA was designed for and has been used extensively to study the language-learning environments of children (e.g., VanDam et al, 2012; Thiemann-Bourque et al, 2014; Gilkerson et al, 2015; Sosa, 2016), but it has also been used with adults (Li et al, 2014). Specifically, Li et al asked 37 older adults (aged 64–91 yr) residing in a retirement community to wear a LENA DLP for one day.…”

Nonstandardized Evaluation of Emergent Communication in Individuals with Severe Intellectual Disabilities: Exploring Existing Options and Proposing Innovations

“…LENA has been used by researchers and clinicians to provide assessment information regarding a variety of clinical populations, such as children with hearing loss (Suskind et al 2016) and autism spectrum disorder (Burgess et al 2013). It has also been used in a number of environments, such as homes (e.g., Burgess et al 2013), preschool classrooms (e.g., Dykstra et al 2012), the NICU (Caskey et al 2014), and even retirement communities (Li et al 2014).…”