Routineness of Social Interactions Is Associated With Higher Affective Well-Being in Older Adults.

OBJECTIVES: Some research conceptualizes routineness of daily life as an indicator of cognitive vulnerability that would lead to lower well-being in older age, whereas other research expects routineness to give rise to more meaning and stability in life and thus to higher well-being. Further research is needed to understand routineness in older adults in relation to cognitive abilities and well-being. This study examined routineness of social interactions. METHODS: We examined data from an event-contingent experience sampling study with 103 Swiss community-dwelling older adults (aged 65 to 84 years). Participants completed in-lab cognitive assessments (reasoning, episodic memory, speed, and vocabulary) and reported their well-being (positive affect, negative affect, and life satisfaction). For more than 21 days, participants reported the time and context of their social interactions (including modality, partner type, and location). Routineness of social interactions was defined as social interactions that occurred at the same time of day over the study period. It was calculated using recurrence quantification analysis. RESULTS: Linear regressions showed that higher routineness of social interaction in general, of social interaction through the same modality, and of social interaction with the same partner type were associated with higher positive affect. Higher routineness of social interaction in general was associated with lower negative affect. Routineness of social interactions was not associated with life satisfaction or cognitive abilities. DISCUSSION: A routine social life may increase older adults' affective well-being. Results are discussed in the context of activity engagement and time use in older age.

Activity Diversity and Well-Being in Daily Life: Evidence for Heterogeneity Between Older Adults.

OBJECTIVES: Although higher activity diversity is associated with higher well-being at the between-person level, it is unknown whether a day with higher activity diversity is related to higher well-being within persons. Within 24 hr per day, there are a limited number of activities on which individuals could spend their time and energy. Personal resources could influence the expenditure of energy and thus the experience with daily activities. This study examined daily associations between activity diversity and well-being and whether age and self-related health moderated the associations. METHODS: For seven times per day over 2 weeks, 129 retired older adults (Mage = 73.9 years, SDage = 5.6) reported their present activity engagement and positive and negative affect. Daily activity diversity was operationalized as the number of different activity types reported per day. Daily positive and negative affect were assessed as the average of a range of high- and low-arousal affective states. Self-rated health was assessed with an item from the 12-Item Short-Form Health Survey at baseline. RESULTS: Multilevel models showed that daily activity diversity was unrelated, on average, to daily positive or negative affect at the between- and within-person levels. Daily activity diversity was associated with lower daily positive affect in participants with lower self-rated health, but the Johnson-Neyman regions of significance were outside of the range of observed data. DISCUSSION: Divergent patterns were observed in the within-person associations between activity diversity and well-being across participants. Results are discussed in the context of time use and well-being in older age.

The Mediating Role of Affective States in Short-Term Effects of Activity Engagement on Working Memory in Older Age.

INTRODUCTION: It has been shown that activity engagement is associated with cognitive ability in older age, but mechanisms behind the associations have rarely been examined. Following a recent study which showed short-term effects of activity engagement on working memory performance appearing 6 h later, this study examined the mediating role of affective states in this process. METHODS: For 7 times per day over 2 weeks, 150 Swiss older adults (aged 65-91 years) reported their present (sociocognitive/passive leisure) activities and affective states (high-arousal positive, low-arousal positive, high-arousal negative, and low-arousal negative) and completed an ambulatory working memory task on a smartphone. RESULTS: Multilevel vector autoregression models showed that passive leisure activities were associated with worse working memory performance 6 h later. Passive leisure activities were negatively associated with concurrent high-arousal positive affect (and high-arousal negative affect); high-arousal positive affect was negatively associated with working memory performance 6 h later. A Sobel test showed a significant mediation effect of high-arousal positive affect linking the time-lagged relationship between passive leisure activities and working memory. Additionally, sociocognitive activities were associated with better working memory performance 6 h later. Sociocognitive activities were associated with concurrent higher high- and low-arousal positive affect, which, however, were not associated with working memory performance 6 h later. Thus, a mediation related to sociocognitive activities was not found. DISCUSSION: Passive leisure activities could influence working memory performance through high-arousal positive affect within a timeframe of several hours. Results are discussed in relation to an emotional, and possibly a neuroendocrine, pathway explaining the time-lagged effects of affective states on working memory performance.

Daily Affect and Daily Prospective Memory in People after Stroke and Their Partners: The Moderating Role of Resting Heart Rate.

INTRODUCTION: Experimental research suggests that affect may influence prospective memory performance, but real-life evidence on affect-prospective memory associations is limited. Moreover, most studies have examined the valence dimension of affect in understanding the influence of affect on cognitive performance in daily life, with insufficient consideration of the arousal dimension. To maximize ecological validity, the current study examined the relationships between daily affect and daily prospective memory using repeated daily assessments and the role of resting heart rate on these relationships. We examined both valence and arousal of daily affect by categorizing affect into four dimensions: high-arousal positive affect, low-arousal positive affect, high-arousal negative affect, and low-arousal negative affect. METHOD: We examined existing data collected from community-dwelling couples, of which at least one partner had a stroke history. The analytic sample included 111 adults (Mage = 67.46 years, SD = 9.64; 50% women) who provided 1,274 days of data. Among the participants, 58 were living with the effects of a stroke and 53 were partners. Participants completed daily event-based prospective memory tasks (in morning and/or evening questionnaires), reported daily affect in the evening, and wore a wrist-based Fitbit device to monitor resting heart rate over 14 consecutive days. RESULTS: Results from multilevel models show that, within persons, elevated high-arousal negative affect was associated with worse daily prospective memory performance. In addition, lower resting heart rate attenuated the inverse association between high-arousal negative affect and lowered prospective memory performance. We did not find significant associations of high- or low-arousal positive affect and low-arousal negative affect with daily prospective memory. DISCUSSION: Our findings are in line with the resource allocation model and the cue-utilization hypothesis in that high-arousal negative affect is detrimental to daily prospective memory performance. Lower resting heart rate may buffer individuals' prospective memory performance from the influence of high-arousal negative affect. These findings are consistent with the neurovisceral integration model on heart-brain connections, highlighting the possibility that cardiovascular fitness may help maintain prospective memory into older adulthood.

The short-term effects of activity engagement on working memory performance in older age.

Does a single bout of activity engagement have short-term effects on cognition in daily life? Using a smartphone-based ambulatory assessment design, this study examined the duration of the effects of three types of activities (i.e., sociocognitive, passive leisure, and physical activities) on working memory performance. For seven times per day (i.e., approximately every 2 hr) over 15 days, 150 healthy older adults (aged 65-91 years) in Switzerland reported their present activities and completed working memory assessments. In an examination of within-person concurrent associations, results from a multilevel model showed that passive leisure activities were negatively associated with working memory. Extending this to time-lagged dynamics, results from multilevel vector autoregression models showed that the negative effect of passive leisure activities and a positive effect of sociocognitive activities on working memory performance appeared 6 hr later and faded out completely by 8 hr later. Follow-up analyses showed that the time-lagged effects of activity engagement were evident among relatively younger individuals with lower levels of formal education. In sum, our findings suggest that a single bout of activity engagement has an impact on cognitive performance as quickly as 6 hr. In line with the "use it or lose it" hypothesis, our findings highlight the importance of continuous and active engagement in sociocognitive activities in older age. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Daily activity diversity and daily working memory in community-dwelling older adults.

OBJECTIVE: Cross-sectional and long-term longitudinal studies have shown that engagement in diverse activities benefits cognitive performance in older age, but it is unknown whether the beneficial effect holds within persons on a daily basis. This study examines the within-person association between activity diversity and working memory on the same day and its time-lagged directionality between days. It also examines the effects of potential moderators on the within-person association, including age, education, processing speed, and crystallized intelligence, to understand who may benefit more from daily activity diversity. METHOD: We examined smartphone-based ambulatory assessment data from 150 community-dwelling older adults (aged 65-91 years) from Switzerland. Participants reported their present activity and completed a working memory task (i.e., numerical updating) seven times per day over 15 days. Activity diversity was calculated on a daily level and scores of working memory were averaged within a day. Age, education, processing speed, and crystallized intelligence were assessed in the laboratory at baseline. RESULTS: Multilevel models showed that, within persons, higher daily activity diversity was positively associated with higher daily working memory. Moreover, the prior day's greater activity diversity led to that day's higher working memory, but not vice versa. There were no moderating effects of age, education, and crystallized intelligence, but partial evidence of a moderating effect of processing speed. CONCLUSIONS: Our results on within-person concurrent and time-lagged associations between daily activity diversity and daily working memory strengthen the existing evidence on the beneficial effect of activity diversity on older adults' cognitive performance. Results are discussed in the context of cognitive reserve theory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

GPS-Derived Daily Mobility and Daily Well-Being in Community-Dwelling Older Adults.

INTRODUCTION: Mobility as a multidimensional concept has rarely been examined as a day-to-day varying phenomenon in its within-person association with older adults' daily well-being. This study examined associations between daily mobility and daily well-being in community-dwelling older adults with a set of GPS-derived mobility indicators that were representative of older adults' daily mobility. METHODS: Participants wore a custom-built mobile GPS sensor ("uTrail") and completed smartphone-based experience sampling questionnaires on momentary affective states (7 times per day) and daily life satisfaction (in the evening). Analyses included data across 947 days from 109 Swiss older adults aged 65-89 years. RESULTS: Multilevel modeling showed that, within persons, a day with a larger life space area, more time spent in passive transport modes, and a higher number of different locations was associated with higher daily life satisfaction but not daily positive or negative affect. Follow-up analysis showed that the daily maximum distance from home was positively associated with daily life satisfaction, providing a first indication that exposure to non-habitual environments might be a possible underlying mechanism to explain the effects of mobility. CONCLUSIONS: Traveling a long distance away from home and visiting diverse locations may be a way to improve life satisfaction. Results are discussed in the context of research on healthy aging.

Alternating time spent on social interactions and solitude in healthy older adults.

Time spent on being with others (social interactions) and being alone (solitude) in day to day life might reflect older adults' agentic regulatory strategies to balance the needs to belong and to conserve energy. Motivated from a joint lifespan psychological and social relationship theoretical perspective, this study examined how time spent on social interactions and solitude alternatively unfolds within individuals in daily life, relating to individual differences in trait-level well-being and fatigue. Over 21 days, a total of 11,172 valid records of social interactions were collected from 118 older adults (aged 65-94 years) in a smartphone-based event-contingent ambulatory assessment study in Switzerland. On average, a social interaction episode lasted 39 min and a solitude episode lasted 5.03 hr. Multilevel models showed that, at the within-person level, a longer-than-usual social interaction preceded and was followed by a longer-than-usual solitude episode. Moderator analyses showed that older adults with higher trait life satisfaction and lower trait fatigue spent even more time in social interactions after longer solitude episodes, amplifying the solitude-then-interaction association. Our findings suggest that whereas social interaction is a means to improve well-being, solitude is also an integral part in older adults' daily life supporting energy recovery.

Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach.

BACKGROUND: Language use and social interactions have demonstrated a close relationship with cognitive measures. It is important to improve the understanding of language use and behavioral indicators from social context to study the early prediction of cognitive decline among healthy populations of older adults. OBJECTIVE: This study aimed at predicting an important cognitive ability, working memory, of 98 healthy older adults participating in a 4-day-long naturalistic observation study. We used linguistic measures, part-of-speech (POS) tags, and social context information extracted from 7450 real-life audio recordings of their everyday conversations. METHODS: The methods in this study comprise (1) the generation of linguistic measures, representing idea density, vocabulary richness, and grammatical complexity, as well as POS tags with natural language processing (NLP) from the transcripts of real-life conversations and (2) the training of machine learning models to predict working memory using linguistic measures, POS tags, and social context information. We measured working memory using (1) the Keep Track test, (2) the Consonant Updating test, and (3) a composite score based on the Keep Track and Consonant Updating tests. We trained machine learning models using random forest, extreme gradient boosting, and light gradient boosting machine algorithms, implementing repeated cross-validation with different numbers of folds and repeats and recursive feature elimination to avoid overfitting. RESULTS: For all three prediction routines, models comprising linguistic measures, POS tags, and social context information improved the baseline performance on the validation folds. The best model for the Keep Track prediction routine comprised linguistic measures, POS tags, and social context variables. The best models for prediction of the Consonant Updating score and the composite working memory score comprised POS tags only. CONCLUSIONS: The results suggest that machine learning and NLP may support the prediction of working memory using, in particular, linguistic measures and social context information extracted from the everyday conversations of healthy older adults. Our findings may support the design of an early warning system to be used in longitudinal studies that collects cognitive ability scores and records real-life conversations unobtrusively. This system may support the timely detection of early cognitive decline. In particular, the use of a privacy-sensitive passive monitoring technology would allow for the design of a program of interventions to enable strategies and treatments to decrease or avoid early cognitive decline.

Not "The More The Merrier": Diminishing Returns to Daily Face-To-Face Social Interaction Frequency for Well-Being in Older Age.

OBJECTIVES: While being socially active is beneficial for well-being in older age, it is unclear whether effects of social interactions on well-being indicate "the more the merrier" or if they have limits as individuals socialize more or less across different days. This study addressed diminishing returns to social interaction frequency for well-being. METHOD: We examined data from an event-contingent experience sampling study from 116 Swiss older adults (65 to 94 years old) over 21 days. Participants reported face-to-face social interactions once they occurred and daily well-being (i.e., positive and negative affect, loneliness) in the evenings. RESULTS: On average, participants had 2.09 face-to-face social interactions per day. Linear and quadratic effects from multilevel models conjointly indicated that a higher number of daily social interactions was associated with higher daily positive affect and lower daily negative affect and loneliness, but that well-being reached its peak at 2-3 times above participants' typical daily interaction frequency. Once these numbers were surpassed, the benefit of additional social interactions diminished. Additionally, participants who typically had fewer social interactions, were unmarried, lived alone, and had more health conditions showed stronger associations between daily social interaction frequency and well-being. DISCUSSION: Our findings suggest the benefits of social interactions on well-being exhibit diminishing returns. Social interactions may play a bigger role in older adults with less satiation for desire to belong and a limited future time perspective. We discuss these findings in terms of the belongingness hypothesis and the socioemotional selectivity theory.

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.

Longitudinal Within-Person Associations Between Quality of Social Relations, Structure of Social Relations, and Cognitive Functioning in Older Age.

OBJECTIVES: Individuals' social connections and interpersonal experiences can both shape and be shaped by cognitive functioning. This study examines longitudinal within-person associations between quality of social relations, structure of social relations, and cognitive functioning in older age. METHODS: We examined 16-year longitudinal data (3 waves) from 497 older adults (M = 66.07 years, SD = 0.83, range = 64-68 years) from the Interdisciplinary Longitudinal Study of Adult Development and Aging. Quality of social relations was measured by scales on perceived emotional support, instrumental support, and social integration. Structure of social relations was measured by self-reported number of leisure time partner types, indicating social network diversity. Cognitive functioning was assessed as a latent construct consisting of five cognitive tests (i.e., Information, Similarities, Letter Fluency, Picture Completion, Block Design). We used a random intercept cross-lagged panel model in the analysis. RESULTS: At the within-person level, prior quality of social relations, but not structure of social relations, was positively associated with subsequent cognitive functioning. Moreover, prior cognitive functioning was positively associated with subsequent structure of social relations, but not with quality of social relations. DISCUSSION: Quality of social relations is a protective factor of cognitive aging. Additionally, responding to prior lower cognitive functioning, social network diversity reduced, but quality of social relations did not seem to change. Overall, this study suggested that social relations and cognitive functioning mutually influence each other, but different aspects of social relations (i.e., quality, structure) might have different directional associations with cognitive functioning.

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.

Social Reminiscence in Older Adults' Everyday Conversations: Automated Detection Using Natural Language Processing and Machine Learning.

BACKGROUND: Reminiscence is the act of thinking or talking about personal experiences that occurred in the past. It is a central task of old age that is essential for healthy aging, and it serves multiple functions, such as decision-making and introspection, transmitting life lessons, and bonding with others. The study of social reminiscence behavior in everyday life can be used to generate data and detect reminiscence from general conversations. OBJECTIVE: The aims of this original paper are to (1) preprocess coded transcripts of conversations in German of older adults with natural language processing (NLP), and (2) implement and evaluate learning strategies using different NLP features and machine learning algorithms to detect reminiscence in a corpus of transcripts. METHODS: The methods in this study comprise (1) collecting and coding of transcripts of older adults' conversations in German, (2) preprocessing transcripts to generate NLP features (bag-of-words models, part-of-speech tags, pretrained German word embeddings), and (3) training machine learning models to detect reminiscence using random forests, support vector machines, and adaptive and extreme gradient boosting algorithms. The data set comprises 2214 transcripts, including 109 transcripts with reminiscence. Due to class imbalance in the data, we introduced three learning strategies: (1) class-weighted learning, (2) a meta-classifier consisting of a voting ensemble, and (3) data augmentation with the Synthetic Minority Oversampling Technique (SMOTE) algorithm. For each learning strategy, we performed cross-validation on a random sample of the training data set of transcripts. We computed the area under the curve (AUC), the average precision (AP), precision, recall, as well as F1 score and specificity measures on the test data, for all combinations of NLP features, algorithms, and learning strategies. RESULTS: Class-weighted support vector machines on bag-of-words features outperformed all other classifiers (AUC=0.91, AP=0.56, precision=0.5, recall=0.45, F1=0.48, specificity=0.98), followed by support vector machines on SMOTE-augmented data and word embeddings features (AUC=0.89, AP=0.54, precision=0.35, recall=0.59, F1=0.44, specificity=0.94). For the meta-classifier strategy, adaptive and extreme gradient boosting algorithms trained on word embeddings and bag-of-words outperformed all other classifiers and NLP features; however, the performance of the meta-classifier learning strategy was lower compared to other strategies, with highly imbalanced precision-recall trade-offs. CONCLUSIONS: This study provides evidence of the applicability of NLP and machine learning pipelines for the automated detection of reminiscence in older adults' everyday conversations in German. The methods and findings of this study could be relevant for designing unobtrusive computer systems for the real-time detection of social reminiscence in the everyday life of older adults and classifying their functions. With further improvements, these systems could be deployed in health interventions aimed at improving older adults' well-being by promoting self-reflection and suggesting coping strategies to be used in the case of dysfunctional reminiscence cases, which can undermine physical and mental health.

Linear and Nonlinear Age Trajectories of Language Use: A Laboratory Observation Study of Couples' Conflict Conversations.

OBJECTIVES: This study investigated linear and nonlinear age effects on language use with speech samples that were representative of naturally occurring conversations. METHOD: Using a corpus-based approach, we examined couples' conflict conversations in the laboratory. The conversations, from a total of 364 community-dwelling German-speaking heterosexual couples (aged 19-82), were videotaped and transcribed. We examined usage of lower-frequency words, grammatical complexity, and utterance of filled pauses (e.g., äh ["um"]). RESULTS: Multilevel models showed that age effects on the usage of lower-frequency words were nonsignificant. Grammatical complexity increased until middle age (i.e., 54) and then declined. The utterance of filled pauses increased until old age (i.e., 70) and then decreased. DISCUSSION: Results are discussed in relation to cognitive aging research.

Real-Life Language Use Across Different Interlocutors: A Naturalistic Observation Study of Adults Varying in Age.

Amid the growing interest in studying language use in real life, this study, for the first time, examined age effects on real-life language use, as well as within-person variations across different interlocutors. We examined speech samples collected via the Electronically Activated Recorder (i.e., portable audio recorder that periodically records ambient sounds) for a larger project. This existing dataset included more than 18,000 sound snippets (50-s long) from 53 American couples (breast cancer patients and their spouses; aged 24 to 94 years) in their natural environments. Sound snippets that included participant speech were coded for different interlocutors and given scores on three linguistic measures that are associated with age-related cognitive changes: usage of unique words, usage of uncommon words, and grammatical complexity. Multilevel models showed that there were no age effects on the three linguistic measures when interlocutors were not taken into account. We found that interlocutors influenced usage of unique words and grammatical complexity. More specifically, compared to talking with their spouse, participants used fewer unique words with children and friends; and used simpler grammatical structures with children, strangers, and in multiparty conversations. Next, we found that interlocutors influenced the associations between age and language use. More specifically, young adults used more unique words and more uncommon words with children than older adults. They used more uncommon words with friends and uttered more complex grammatical structures with strangers than older adults. Our results offer preliminary evidence for a new perspective to understand real-life language use: focusing not only on individual characteristics (i.e., age), but also context (i.e., interlocutors). This perspective should be useful to researchers who are interested in collecting "big data" and understanding cognitive activities in real life.

A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis.

The intuitionistic fuzzy set, as a generation of fuzzy set, can express and process uncertainty much better. Distance measures between intuitionistic fuzzy sets are used to indicate the difference degree between the information carried by intuitionistic fuzzy sets. Although some distance measures have been proposed in previous studies, they can not satisfy the axioms of distance measure, or exist counter-intuitive cases. In this paper, we give a new distance measure between intuitionistic fuzzy sets, which is based on a matrix norm and a strictly increasing (or decreasing) binary function. The new distance measure not only satisfies the axiomatic definition of distance measure, but also overcomes the counter-intuitive cases. It is proved that the new distance measure is reasonable by numerical examples. Moreover, we give the algorithms for pattern recognition and use it to solve medical diagnosis problems.

An alternative discourse of productive aging: A self-restrained approach in older Chinese people in Hong Kong.

While Western discourses regarding productive aging emphasize individuals' contributions to economic productivity, the Confucian cultural heritage of the Chinese community may provide an alternative perspective. This qualitative study explores interpretations of what constitutes productive aging, based on a series of in-depth interviews with older Chinese people in Hong Kong. It shows that some of these individuals adopted a passive and indirect interpretation of productive aging, distinct from that found in Western countries. The Confucianism-based, collectivist, normative order underpinning Hong Kong society disposed these older people to adopting a self-restrained attitude with the aim of avoiding becoming a burden to others, especially family members. Such a tendency toward self-restraint or avoidance also encompassed a compromise between ideals and reality, with the older people opting to compromise their expectations of the younger generation as a whole, their adult children in particular, in terms of respect and reciprocity.

Extreme learning machine and adaptive sparse representation for image classification.

Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks, e.g., in general, ELM is known to be less robust to noise while SRC is known to be time-consuming. Consequently, ELM and SRC complement each other in computational complexity and classification accuracy. In order to unify such mutual complementarity and thus further enhance the classification performance, we propose an efficient hybrid classifier to exploit the advantages of ELM and SRC in this paper. More precisely, the proposed classifier consists of two stages: first, an ELM network is trained by supervised learning. Second, a discriminative criterion about the reliability of the obtained ELM output is adopted to decide whether the query image can be correctly classified or not. If the output is reliable, the classification will be performed by ELM; otherwise the query image will be fed to SRC. Meanwhile, in the stage of SRC, a sub-dictionary that is adaptive to the query image instead of the entire dictionary is extracted via the ELM output. The computational burden of SRC thus can be reduced. Extensive experiments on handwritten digit classification, landmark recognition and face recognition demonstrate that the proposed hybrid classifier outperforms ELM and SRC in classification accuracy with outstanding computational efficiency.

Health Expectancies in Adults Aged 50 Years or Older in China.

OBJECTIVE: The purpose of this study is to understand the functional health of older adults in China and to assess the potential for advancing healthy and active aging. METHOD: Data of 13,739 older adults aged 50 years and older from the China Health and Retirement Longitudinal Study in 2011 were analyzed. Life expectancy in good perceived health, chronic-disease-free life expectancy, active life expectancy, and severe impairment-free life expectancy were calculated using Sullivan's method. RESULTS: At age 50 years, older adults had a life expectancy in good perceived health of 7.0 and 6.7 years in men and women, respectively. They would remain chronic-disease-free for 8.4 and 8.6 years, without activity limitation for 23.6 and 26.0 years, and severe impairment-free for 21.4 and 24.2 years. DISCUSSION: The world's largest aging population was spending a substantial proportion of remaining life years in suboptimal health and well-being, while remaining largely independent in basic self-care without severe impairments.