Loneliness and social isolation are not associated with executive functioning in a cross-sectional study of cognitively healthy older adults

The literature on the relationship between social interaction and executive functions (EF) in older age is mixed, perhaps stemming from differences in EF measures and the conceptualization/measurement of social interaction. We investigated the relationship between social interaction and EF in 102 cognitively unimpaired older adults (ages 65-90). Participants received an EF battery to measure working memory, inhibition, shifting, and global EF. We measured loneliness subjectively through survey and social isolation objectively through naturalistic observation. Loneliness was not significantly related to any EF measure (p-values = .13-.65), nor was social isolation (p-values = .11-.69). Bayes factors indicated moderate to extremely strong evidence (BF01 = 8.70 to BF01 = 119.49) in support of no relationship..   Overall, these findings suggest that, among cognitively healthy older adults, there may not be a robust cross-sectional relationship between EF and subjective loneliness or objective social isolation.

How ready is speech-to-text for psychological language research? Evaluating the validity of AI-generated English transcripts for analyzing free-spoken responses in younger and older adults

For the longest time, the gold standard in preparing spoken language corpora for text analysis in psychology was using human transcription. However, such standard comes at extensive cost, and creates barriers to quantitative spoken language analysis that recent advances in speech-to-text technology could address. The current study quantifies the accuracy of AI-generated transcripts compared to human-corrected transcripts across younger (n = 100) and older (n = 92) adults and two spoken language tasks. Further, it evaluates the validity of Linguistic Inquiry and Word Count (LIWC)-features extracted from these two kinds of transcripts, as well as transcripts specifically prepared for LIWC analyses via tagging. We find that overall, AI-generated transcripts are highly accurate with a word error rate of 2.50% to 3.36%, albeit being slightly less accurate for younger compared to older adults. LIWC features extracted from either transcripts are highly correlated, while the tagging procedure significantly alters filler word categories. Based on these results, automatic speech-to-text appears to be ready for psychological language research when using spoken language tasks in relatively quiet environments, unless filler words are of interest to researchers.

Age-related differences in the interplay of fluency and complexity in Chinese-speaking seniors' oral narratives

BACKGROUND

Previous studies on language production in normal ageing have primarily focused on distinct dimensions of older adults' spoken language performance, such as fluency and complexity. However, little attention has been paid to the complex, interconnected relations between these dimensions. Additionally, older adults have been treated as a homogeneous group, with little consideration for the differential characteristics of language performance across different stages of ageing.

AIMS

This study aims to investigate how increasing age impacts Chinese seniors' oral language performance, focusing on fluency (articulation rate and dysfluency rate), complexity (lexical and syntactic) and the potential interactions between these dimensions.

METHODS & PROCEDURES

Spontaneous oral narratives were collected from 60 normally ageing individuals, who were categorised into three groups: young-old (60-69 years old), middle-old (70-79 years old) and old-old (≥80 years old). Four measures for assessing language performance, namely, articulation rate, dysfluency rate, lexical complexity and syntactic complexity, were derived from the oral narratives. Dynamic systems techniques, including moving correlations, locally estimated scatterplot smoothing and Monte Carlo simulations, were employed for data analysis.

OUTCOMES & RESULTS

This study revealed two major findings. First, across different age groups, the seniors' oral narratives significantly differed in the aspect of articulation rate and syntactic complexity. Specifically, both the young-old and the middle-old groups exhibited significantly higher articulation rates than the old-old group; the middle-old group also demonstrated significantly higher syntactic complexity compared to the old-old group. Second, the distinct subsystems (i.e., articulation rate, dysfluency rate, lexical and syntactic complexity) of seniors' oral narratives demonstrated varying interactions across different stages of ageing. While these subsystems tended to coordinate with each other in young-old individuals, they exhibited a greater tendency to compete in middle-old and old-old individuals.

CONCLUSIONS & IMPLICATIONS

The findings reveal that subsystems of older adults' oral narratives display varying interactions with the increase of age, indicating that focusing solely on one dimension of language performance may result in inaccurate or misleading conclusions. Therefore, a multi-index comprehensive assessment should be employed for the enhancement of clinical evaluations of language performance in older adults. Additionally, it is vital to consider the interactional patterns (i.e., support or competition) between language subsystems when assessing language performance in normal ageing.

WHAT THIS PAPER ADDS

What is already known on the subject Previous research on language production in normal ageing has primarily focused on distinct dimensions of older adults' spoken language performance, such as fluency, vocabulary richness and grammatical complexity, overlooking the intricate interconnections between these dimensions. However, investigating these connections is significant for a thorough and in-depth understanding of language production in late adulthood, which operates as a system comprising interconnected components. Furthermore, existing studies have predominantly treated older adults as a homogeneous group, comparing their language use to that of young people. This approach lacks justification, given the substantial variations in language use among seniors at different stages of ageing. What this paper adds to existing knowledge The present findings illuminate the dynamic nature of language production in normal ageing. Not only do the distinct dimensions or subsystems of older adults' oral narratives (e.g., articulation rate, dysfluency rate, syntactic complexity) change with age, but more important, the ways in which these subsystems interact with each other also evolve with age, resulting in changing states of spoken language production in the ageing process. More specifically, our study provides evidence that the interactions among subsystems of older adults' oral narratives predominately transition from supportive relationships in earlier stages to competitive ones at later stages of ageing. What are the potential or actual clinical implications of this work? The present study suggests the use of multiple linguistic indices related to various aspects of language performance to assess the spoken language production of older adults. This is highlighted by the observation that various dimensions of older adults' oral narratives continuously interact with one another across different stages of ageing, and hence focusing solely on one dimension of language performance tends to lead to inaccurate or misleading results. Additionally, the patterns of interaction (i.e., support or competition) between different dimensions of language performance may reflect older adults' capacity to coordinate and control attentional resources and therefore should be taken into consideration in clinical evaluations of language performance in older adults.

The paucity of morality in everyday talk

Given its centrality in scholarly and popular discourse, morality should be expected to figure prominently in everyday talk. We test this expectation by examining the frequency of moral content in three contexts, using three methods: (a) Participants' subjective frequency estimates (N = 581); (b) Human content analysis of unobtrusively recorded in-person interactions (N = 542 participants; n = 50,961 observations); and (c) Computational content analysis of Facebook posts (N = 3822 participants; n = 111,886 observations). In their self-reports, participants estimated that 21.5% of their interactions touched on morality (Study 1), but objectively, only 4.7% of recorded conversational samples (Study 2) and 2.2% of Facebook posts (Study 3) contained moral content. Collectively, these findings suggest that morality may be far less prominent in everyday life than scholarly and popular discourse, and laypeople, presume.

Charting everyday activities in later life: Study protocol of the mobility, activity, and social interactions study (MOASIS)

Prominent theories of aging emphasize the importance of resource allocation processes as a means to maintain functional ability, well-being and quality of life. Little is known about which activities and what activity patterns actually characterize the daily lives of healthy older adults in key domains of functioning, including the spatial, physical, social, and cognitive domains. This study aims to gain a comprehensive understanding of daily activities of community-dwelling older adults over an extended period of time and across a diverse range of activity domains, and to examine associations between daily activities, health and well-being at the within- and between-person levels. It also aims to examine contextual correlates of the relations between daily activities, health, and well-being. At its core, this ambulatory assessment (AA) study with a sample of 150 community-dwelling older adults aged 65 to 91 years measured spatial, physical, social, and cognitive activities across 30 days using a custom-built mobile sensor ("uTrail"), including GPS, accelerometer, and audio recording. In addition, during the first 15 days, self-reports of daily activities, psychological correlates, contexts, and cognitive performance in an ambulatory working memory task were assessed 7 times per day using smartphones. Surrounding the ambulatory assessment period, participants completed an initial baseline assessment including a telephone survey, web-based questionnaires, and a laboratory-based cognitive and physical testing session. They also participated in an intermediate laboratory session in the laboratory at half-time of the 30-day ambulatory assessment period, and finally returned to the laboratory for a posttest assessment. In sum, this is the first study which combines multi-domain activity sensing and self-report ambulatory assessment methods to observe daily life activities as indicators of functional ability in healthy older adults unfolding over an extended period (i.e., 1 month). It offers a unique opportunity to describe and understand the diverse individual real-life functional ability profiles characterizing later life.

Differentiating dreaming and waking reports with automatic text analysis and Support Vector Machines

We analyzed similarities and differences between dream and waking reports in a collection by Kahan and Sullivan (2012). We compared word frequencies in the reports using the automatic text analysis software, Linguistic Inquiry and Word Count (LIWC). Social words were more frequent in dream than waking reports, support for Social Simulation Theory. Positive emotion words were less frequent in dream than waking reports, support for Threat Simulation theory. Amount of cognition was the same in dream and waking reports, i. e., the number of words in the summary category "Cognitive Processes" was not significantly different. But specific categories of cognitive words differed in frequency. We also applied a machine learning technique to dream research and built a support vector machine to achieve binary characteristics detection (here, whether a report is about waking or dream) based on LIWC word counts. Performance metrics for the support vector machine were high.

The Sounds of Memory: Extending the Age-Prospective Memory Paradox to Everyday Behavior and Conversations

OBJECTIVES

Around the turn of the millennium, the "age-prospective memory (PM) paradox" challenged the classical assumption that older adults necessarily evidence a marked decline in PM functioning. As previous investigations highlighted ecological validity to be a potential explanation, the present study sought to extend established approaches by using novel real-world assessment technologies to examine PM unobtrusively in everyday-life conversations.

METHOD

Next to laboratory PM tasks, real-life PM performance of 53 younger adults (19-32 years) and 38 older adults (60-81 years) was assessed from three sources: Over nine days, participants completed an experimenter-given naturalistic task, a diary-based approach assessing self-assigned intentions, as well as an ambulatory assessment with the Electronically Activated Recorder (EAR), a device that unobtrusively samples ambient sounds to detect spontaneous speech production related to (lapses in) everyday PM.

RESULTS

Older adults showed lower performance in laboratory PM only for the time-based task, and performed either equally well as or even better than younger adults in everyday PM. With regard to PM performance as captured in real-life ambient audio data, younger adults talked more frequently about PM than older adults, but no significant difference between younger and older adults was found for speech related to PM errors.

DISCUSSION

Findings confirmed older adults' preserved PM performance in everyday life across different indicators with increasing ecological validity. Furthermore, as a novel method to assess conversational PM in everyday life, the EAR opens new insights about the awareness of PM lapses and the communication of intentions in real life.

With a little help from familiar interlocutors: real-world language use in young and older adults

OBJECTIVES

Functional psychologists are concerned with the performance of cognitive activities in the real world in relation to cognitive changes in older age. Conversational contexts may mitigate the influence of cognitive aging on the cognitive activity of language production. This study examined effects of familiarity with interlocutors, as a context, on language production in the real world.

METHOD

We collected speech samples using iPhones, where an audio recording app (i.e. Electronically Activated Recorder [EAR]) was installed. Over 31,300 brief audio files (30-second long) were randomly collected across four days from 61 young and 48 healthy older adults in Switzerland. We transcribed the audio files that included participants' speech and manually coded for familiar interlocutors (i.e. significant other, friends, family members) and strangers. We computed scores of vocabulary richness and grammatical complexity from the transcripts using computational linguistics techniques.

RESULTS

Bayesian multilevel analyses showed that participants used richer vocabulary and more complex grammar when talking with familiar interlocutors than with strangers. Young adults used more diverse vocabulary than older adults and the age effects remained stable across contexts. Furthermore, older adults produced equally complex grammar as young adults did with the significant other, but simpler grammar than young adults with friends and family members.

CONCLUSION

Familiarity with interlocutors is a promising contextual factor for research on aging and language complexity in the real world. Results were discussed in the context of cognitive aging.

Older Adult's Marital Status, Conversation Frequency, and Well-being in Everyday Life

OBJECTIVES

Marital status contributes to differences in social experiences and well-being in late life. Yet, we know little about the role of conversation in these processes. Drawing on a functionalist perspective and hierarchical compensatory model, this study aimed to understand (a) whether older adults' marital status is associated with conversation frequency throughout the day, (b) whether contacts with non-spousal ties elicit more conversations among unmarried older adults, and (c) whether conversations exert a stronger effect on mood for unmarried older adults than married older adults.

METHODS

Adults aged 65+ (N = 272) provided information about their background characteristics and social partners. Across 5-6 days, they completed ecological momentary assessments (EMA) reporting their social encounters and mood every 3 hours. Concurrently, electronically activated recorders (EAR) captured 30-seconds of sound every 7 minutes. We compared older adults who were: married, widowed, and divorced.

RESULTS

Multilevel models revealed that married older adults engaged in more conversations than divorced older adults throughout the day. Contact with friends elicited more conversations for divorced older adults than married older adults. Furthermore, conversations enhanced mood throughout the day, but this effect was more salient for widowed than married older adults.

DISCUSSION

Findings highlight the role of marital status in older adults' daily conversational experiences and compensatory processes that may occur. Widowed and divorced older adults differed from married older adults in distinct ways. Divorced older adults may compensate for lack of spouse with friends, whereas widowed older adults may benefit emotionally from engaging in conversations.

Deep multiple instance learning for foreground speech localization in ambient audio from wearable devices

Over the recent years, machine learning techniques have been employed to produce state-of-the-art results in several audio related tasks. The success of these approaches has been largely due to access to large amounts of open-source datasets and enhancement of computational resources. However, a shortcoming of these methods is that they often fail to generalize well to tasks from real life scenarios, due to domain mismatch. One such task is foreground speech detection from wearable audio devices. Several interfering factors such as dynamically varying environmental conditions, including background speakers, TV, or radio audio, render foreground speech detection to be a challenging task. Moreover, obtaining precise moment-to-moment annotations of audio streams for analysis and model training is also time-consuming and costly. In this work, we use multiple instance learning (MIL) to facilitate development of such models using annotations available at a lower time-resolution (coarsely labeled). We show how MIL can be applied to localize foreground speech in coarsely labeled audio and show both bag-level and instance-level results. We also study different pooling methods and how they can be adapted to densely distributed events as observed in our application. Finally, we show improvements using speech activity detection embeddings as features for foreground detection.

Eavesdropping on Autobiographical Memory: A Naturalistic Observation Study of Older Adults' Memory Sharing in Daily Conversations

The retrieval of autobiographical memories is an integral part of everyday social interactions. Prior laboratory research has revealed that older age is associated with a reduction in the retrieval of autobiographical episodic memories, and the ability to elaborate these memories with episodic details. However, how age-related reductions in episodic specificity unfold in everyday social contexts remains largely unknown. Also, constraints of the laboratory-based approach have limited our understanding of how autobiographical semantic memory is linked to older age. To address these gaps in knowledge, we used a smartphone application known as the Electronically Activated Recorder, or “EAR,” to unobtrusively capture real-world conversations over 4 days. In a sample of 102 cognitively normal older adults, we extracted instances where memories and future thoughts were shared by the participants, and we scored the shared episodic memories and future thoughts for their make-up of episodic and semantic detail. We found that older age was associated with a reduction in real-world sharing of autobiographical episodic and semantic memories. We also found that older age was linked to less episodically and semantically detailed descriptions of autobiographical episodic memories. Frequency and level of detail of shared future thoughts yielded weaker relationships with age, which may be related to the low frequency of future thoughts in general. Similar to laboratory research, there was no correlation between autobiographical episodic detail sharing and a standard episodic memory test. However, in contrast to laboratory studies, episodic detail production while sharing autobiographical episodic memories was weakly related to episodic detail production while describing future events, unrelated to working memory, and not different between men and women. Overall, our findings provide novel evidence of how older age relates to episodic specificity when autobiographical memories are assessed unobtrusively and objectively “in the wild.”