Poor mental health is a state of psychological distress that is influenced by lifestyle factors such as sleep, diet, and physical activity. Compulsivity is a transdiagnostic phenotype cutting across a range of mental illnesses including obsessive–compulsive disorder, substance-related and addictive disorders, and is also influenced by lifestyle. Yet, how lifestyle relates to compulsivity is presently unknown, but important to understand to gain insights into individual differences in mental health. We assessed (a) the relationships between compulsivity and diet quality, sleep quality, and physical activity, and (b) whether psychological distress statistically contributes to these relationships.

We collected harmonized data on compulsivity, psychological distress, and lifestyle from two independent samples (Australian n = 880 and US n = 829). We used mediation analyses to investigate bidirectional relationships between compulsivity and lifestyle factors, and the role of psychological distress.

Higher compulsivity was significantly related to poorer diet and sleep. Psychological distress statistically mediated the relationship between poorer sleep quality and higher compulsivity, and partially statistically mediated the relationship between poorer diet and higher compulsivity.

Lifestyle interventions in compulsivity may target psychological distress in the first instance, followed by sleep and diet quality. As psychological distress links aspects of lifestyle and compulsivity, focusing on mitigating and managing distress may offer a useful therapeutic approach to improve physical and mental health. Future research may focus on the specific sleep and diet patterns which may alter compulsivity over time to inform lifestyle targets for prevention and treatment of functionally impairing compulsive behaviors.

Wisdom is a personality trait comprising seven components: self-reflection, pro-social behaviors, emotional regulation, acceptance of diverse perspectives, decisiveness, social advising, and spirituality. Wisdom, a potentially modifiable trait, is strongly associated with well-being. We have published a validated 28-item San Diego Wisdom Scale, the SD-WISE-28. Brief scales are necessary for use in large population-based studies and in clinical practice. The present study aimed to create an abbreviated 7-item version of the SD-WISE.

Participants included 2093 people, aged 20-82 years, recruited and surveyed through the online crowdsourcing platform Amazon Mechanical Turk. The participants’ mean age was 46 years, with 55% women. Participants completed the SD-WISE-28 as well as validation scales for various positive and negative constructs. Psychometric analyses (factor analysis and item response theory) were used to select one item from each of the seven SD-WISE-28 subscales.

We selected a combination of items that produced acceptable unidimensional model fit and good reliability (ω = 0.74). Item statistics suggested that all seven items were strong indicators of wisdom, although the association was weakest for spirituality. Analyses indicated that the 28-item and 7-item SD-WISE are both very highly correlated (r = 0.92) and produce a nearly identical pattern of correlations with demographic and validity variables.

The SD-WISE-7, and its derived Jeste-Thomas Wisdom Index (JTWI) score, balances reliability and brevity for research applications.

The ultimate goal of artificial intelligence (AI) is to develop technologies that are best able to serve humanity. This will require advancements that go beyond the basic components of general intelligence. The term “intelligence” does not best represent the technological needs of advancing society, because it is “wisdom”, rather than intelligence, that is associated with greater well-being, happiness, health, and perhaps even longevity of the individual and the society. Thus, the future need in technology is for artificial wisdom (AW).

We examine the constructs of human intelligence and human wisdom in terms of their basic components, neurobiology, and relationship to aging, based on published empirical literature. We review the development of AI as inspired and driven by the model of human intelligence, and consider possible governing principles for AW that would enable humans to develop computers which can operationally utilize wise principles and result in wise acts. We review relevant examples of current efforts to develop such wise technologies.

AW systems will be based on developmental models of the neurobiology of human wisdom. These AW systems need to be able to a) learn from experience and self-correct; b) exhibit compassionate, unbiased, and ethical behaviors; and c) discern human emotions and help the human users to regulate their emotions and make wise decisions.

A close collaboration among computer scientists, neuroscientists, mental health experts, and ethicists is necessary for developing AW technologies, which will emulate the qualities of wise humans and thus serve the greatest benefit to humanity. Just as human intelligence and AI have helped further the understanding and usefulness of each other, human wisdom and AW can aid in promoting each other’s growth

Aging is associated with numerous stressors that negatively impact older adults’ well-being. Resilience improves ability to cope with stressors and can be enhanced in older adults. Senior housing communities are promising settings to deliver positive psychiatry interventions due to rising resident populations and potential impact of delivering interventions directly in the community. However, few intervention studies have been conducted in these communities. We present a pragmatic stepped-wedge trial of a novel psychological group intervention intended to improve resilience among older adults in senior housing communities.

A pragmatic modified stepped-wedge trial design.

Five senior housing communities in three states in the US.

Eighty-nine adults over age 60 years residing in independent living sector of senior housing communities.

Raise Your Resilience, a manualized 1-month group intervention that incorporated savoring, gratitude, and engagement in value-based activities, administered by unlicensed residential staff trained by researchers. There was a 1-month control period and a 3-month post-intervention follow-up.

Validated self-report measures of resilience, perceived stress, well-being, and wisdom collected at months 0 (baseline), 1 (pre-intervention), 2 (post-intervention), and 5 (follow-up).

Treatment adherence and satisfaction were high. Compared to the control period, perceived stress and wisdom improved from pre-intervention to post-intervention, while resilience improved from pre-intervention to follow-up. Effect sizes were small in this sample, which had relatively high baseline resilience. Physical and mental well-being did not improve significantly, and no significant moderators of change in resilience were identified.

This study demonstrates feasibility of conducting pragmatic intervention trials in senior housing communities. The intervention resulted in significant improvement in several measures despite ceiling effects. The study included several features that suggest high potential for its implementation and dissemination across similar communities nationally. Future studies are warranted, particularly in samples with lower baseline resilience or in assisted living facilities.

This study of loneliness across adult lifespan examined its associations with sociodemographics, mental health (positive and negative psychological states and traits), subjective cognitive complaints, and physical functioning.

Analysis of cross-sectional data

340 community-dwelling adults in San Diego, California, mean age 62 (SD = 18) years, range 27–101 years, who participated in three community-based studies.

Loneliness measures included UCLA Loneliness Scale Version 3 (UCLA-3), 4-item Patient-Reported Outcomes Measurement Information System (PROMIS) Social Isolation Scale, and a single-item measure from the Center for Epidemiologic Studies Depression (CESD) scale. Other measures included the San Diego Wisdom Scale (SD-WISE) and Medical Outcomes Survey- Short form 36.

Seventy-six percent of subjects had moderate-high levels of loneliness on UCLA-3, using standardized cut-points. Loneliness was correlated with worse mental health and inversely with positive psychological states/traits. Even moderate severity of loneliness was associated with worse mental and physical functioning. Loneliness severity and age had a complex relationship, with increased loneliness in the late-20s, mid-50s, and late-80s. There were no sex differences in loneliness prevalence, severity, and age relationships. The best-fit multiple regression model accounted for 45% of the variance in UCLA-3 scores, and three factors emerged with small-medium effect sizes: wisdom, living alone and mental well-being.

The alarmingly high prevalence of loneliness and its association with worse health-related measures underscore major challenges for society. The non-linear age-loneliness severity relationship deserves further study. The strong negative association of wisdom with loneliness highlights the potentially critical role of wisdom as a target for psychosocial/behavioral interventions to reduce loneliness. Building a wiser society may help us develop a more connected, less lonely, and happier society.