Mental and social well-being are integral components of health, as their association with physical health is reciprocal. Wisdom has emerged as one of the domains of mental well-being as its core lies in the quintessential aspects of human life (Wang, Reference Wang2022). Due to its potential contribution to better overall physical health, mental well-being, and positive psychological experiences, enhancing wisdom shall be one of the healthy aging promoting strategies from a public health angle. To understand the role of wisdom in older adults’ well-being at a societal level and to develop and test wisdom-enhancing interventions, researchers have been called on to expand empirical research on wisdom (Jeste and Lee, Reference Jeste and Lee2019). However, wisdom research among older adults remains limited in the fast-growing literature. Little understanding of the measurements of wisdom may be one of the significant obstacles to the research community on old-age mental health.
Historically, the concept of wisdom has been explored in religion and philosophy. Throughout the way from the introduction of modern psychology, wisdom has been gradually embraced as a scientific construct (Grossmann et al., Reference Grossmann2020). Per se, wisdom is complicated to define its nature of unique humanness. In the past half-century, investigators have recognized that wisdom is driven by personal experience and demonstrated in behavior (Jeste et al., Reference Jeste, Ardelt, Blazer, Kraemer, Vaillant and Meeks2010). For example, a person who could find practical and emotionally satisfying solutions to a tensive situation may be considered a wise man. Nowadays, investigators have agreed that wisdom is a multidimensional trait consisting of specific domains. Most recently, Jeste and colleagues proposed that wisdom is relevant to seven domains: self-reflection, prosocial behaviors, emotional regulation, acceptance of diverse perspectives, decisiveness, social advising, and spirituality (Jeste et al., Reference Jeste2021). Following the multidimensional definition of wisdom, investigators have developed various measurements of wisdom that are requisite for empirical studies.
Among the existing literature, most assessment instruments on wisdom are self-rated scales (Bangen, et al., Reference Bangen, Meeks and Jeste2013). However, in a literature review, Meeks and Jeste proposed that certain neurocircuitry of normal brains may serve the neural substrates of wisdom components. For example, the amygdala, nucleus accumbens, striatum, and medial prefrontal cortex may formulate the circuit of social cooperation, which contributes to an individual’s prosocial attitudes and behaviors (Meeks and Jeste, Reference Meeks and Jeste2009). Therefore, building upon the neurobiological model, Thomas and colleagues developed the San Diego Wisdom Scale (SD-WISE) (Thomas et al., Reference Thomas2019). Compared with the Three-Dimensional Wisdom Scale (3D-WS), Self-Assessed Wisdom Scale (SAWS), and the Wise Thinking and Acting Questionnaire (WITHAQ), the SD-WISE is relatively more comprehensive in tapping into the core features of wisdom (Thomas et al., Reference Thomas2019). In addition, the recently developed 28-item SD-WISE (SD-WISE-28) expanded the original scope to a broader one, relating wisdom to cognitive and affective circuits and having spirituality neuroscience involved (Jeste et al., Reference Jeste2021).
Maintaining health and functioning for older adults is a critical public health priority. Many countries have funded healthy aging cohort studies, aiming to depict health outcomes trajectories and identify potential preventive strategies for reducing health problems and related disabilities (Minicuci et al., Reference Minicuci, Naidoo, Corso, Rocco, Chatterji and Kowal2019; Wu et al., Reference Wu2020; Zeng et al., Reference Zeng, Feng, Hesketh, Christensen and Vaupel2017). However, mental health primarily focuses on mood, cognition, and social participation across the large cohorts, while wisdom is rarely included and studied. On the one hand, the development of wisdom measurements is far behind the commencement of the nationwide or globally harmonized healthy aging cohorts. On the other hand, most wisdom scales are lengthy and may add time costs to the existing large-scale cohorts. Therefore, wisdom scientists have seen great promise in creating shorter measures of wisdom.
In the current issue of the International Psychogeriatrics, Thomas and colleagues (Reference Thomas2022) published an abbreviated SD-WISE consisting of seven items, one corresponding to one of seven components included in the original version. The authors used the SD-WISE-28 and collected valid data from 1,786 people aged 20–82. Following the procedures of fitting the data with the item response theory (IRT) graded response models, extracting the discrimination parameters, fitting the confirmatory factor model to the possible 7-item combination, and examining the psychometric properties with the IRT model, Thomas et al. proposed a 7-item SD-WISE as a brief and reliable scale to measure wisdom. It is interesting to find out that Leeman and colleagues recently did similar work, shortening the 40-item SAWS to 15 items based on a survey among Australian participants (Leeman et al., Reference Leeman, Knight, Fein, Winterbotham and Webster2022). However, different methodologies were applied in these two studies. Leeman et al. combined confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) in extracting five factors (Leeman et al., Reference Leeman, Knight, Fein, Winterbotham and Webster2022). Thomas et al., however, applied the IRT to select one item from each of the seven SD-WISE-28 subscales and formulated an abbreviated version (Thomas et al., Reference Thomas2022). The essential discrepancy between the two brief tools may lie in the grounded concept of wisdom in the original scales: SAWS includes five components – reminiscence/reflection, humor, emotional regulation, critical life experiences, and openness (Dean Webster, Reference Dean Webster2007; Leeman et al., Reference Leeman, Knight, Fein, Winterbotham and Webster2022); SD-WISE-27 consists of seven subscales (Jeste et al., Reference Jeste2021). Although, as Ardelt commented, “the SAWS might be considered a combination of predictors and consequences of wisdom rather than a measure of wisdom per se,” it is necessary for investigators to compare the qualities of the instruments and choose an optimal tool for their research purpose (Ardelt, Reference Ardelt2011).
As discussed earlier, wisdom would contribute more if viewed as an ecological mental health domain, especially when it integrates with emotional, psychological, and social well-being (Wang, Reference Wang2022). In their paper, Thomas et al. also computed the total score of the 7-item SD-WISE as the wisdom index to represent the overall wisdom. Furthermore, the index was correlated with mental health outcomes, such as depression, loneliness, resilience, happiness, and mental well-being (Thomas et al., Reference Thomas2022). Therefore, the global wisdom index drawn from the abbreviated version may be feasible for the cohort studies, taking advantage of simplicity and usefulness.
The authors’ observation of a modest positive association between overall wisdom and age may coincide with the assumption that people become happier when they get older (Jeste, et al., Reference Jeste, Wolkowitz and Palmer2011). However, in Thomas et al.’s study, the span of participants’ age was huge (Thomas et al., Reference Thomas2022). According to Sternberg’s perspective, “there is no one trajectory of wisdom with age” (Sternberg, Reference Sternberg2005). Wisdom development may have a plateau across the life course. Also, the genetic and socio-environmental factors may moderate the phenotype of wise behaviors. The age effect and its interaction with genetic susceptibility or lifestyle on the wisdom index were not examined thoroughly in Thomas et al.’s study. It remains unclear whether each component of wisdom shares a similar trajectory from 20 to 82 years. For example, a personal experience usually accumulates with age. Nevertheless, social participation may drop after a person retires. Less social interaction may not gain as much experience as it did prior to the retirement. In another situation, old persons with physical functional limitations may feel challenged to rate the reverse-scored item “I avoid situations where I know my help will be needed.” Therefore, measuring individuals’ wisdom needs to be adapted to their real-life situations.
Besides, the conception of wisdom in Thomas et al. study can be viewed as a person-based definition. In contrast, the demonstration of wise behavior may be better observed during the interaction between an individual and the situation faced by the individual, which could be considered an endeavor-based definition (Yang, et al., Reference Yang, Kuo and Lin2022). Yang et al. argued that “no prescribed set of internal qualities can consistently lead a person to display wisdom across all situations.” The SD-WISE-7 evaluates solely a person’s internal qualities and character strength rather than the real-life endeavors. Ideally, integrating person- and endeavor-based measurements could provide a comprehensive understanding of an individual’s wisdom. However, Yang et al. used 220 wisdom incidents to rate the three wisdom components, that is, cognitive integration, embodying actions, and positive effects (Yang et al., Reference Yang, Kuo and Lin2022). The long-standing process may compromise its feasibility in large-scale cohort studies. There might be some alternatives to consider. As discussed earlier, attaining wisdom resembles the formulation of cognitive reserve, where life experiences, such as acculturalization, social adaptation, lifetime learning, education, and leadership, may interplay (Wang, Reference Wang2020, Reference Wang2022). To my knowledge, most healthy aging cohorts measure individual development and social factors, such as life experiences, lifestyle, previous and present occupation, education, and social connectedness (Minicuci et al., Reference Minicuci, Naidoo, Corso, Rocco, Chatterji and Kowal2019; Wu et al., Reference Wu2020; Zeng et al., Reference Zeng, Feng, Hesketh, Christensen and Vaupel2017). These data, to some extent, may depict an individual’s social environment, subserving the foundation of wisdom development. It might be interesting to integrate the person-based measurement, if the SD-WISE-7 is applied, with social contextual factors, when exploring the health outcomes in old age.
From the positive aging perspective, measuring wisdom is not the end. Instead, it is a new beginning for developing mental well-being promoting interventions. With a more profound understanding of its constructive framework, mental healthcare providers are keen to bolster older adults’ wisdom and utilize their wisdom in the real-life process. In recent years, social prescribing has been introduced to some countries, aiming to improve health and well-being through addressing individuals’ social needs and connecting them to non-clinical services and supports (Morse et al., Reference Morse2022). Implementing social prescribing may depend on the synergy between the personal and societal levels, such as empowering individuals to build up their motivation and confidence and facilitating multi-sectoral collaboration to promote service integration. Previous local pilot projects have found that wise residents, sometimes called community volunteers, play pivotal roles in strengthening the efforts of link workers and social care workers and facilitating social prescribing in their neighborhoods (Morse et al., Reference Morse2022). Applying the brief tool of wisdom assessment in social prescribing may have a dual effect: First, it will boost the empirical wisdom research in aging cohorts; second, it may aid the recruitment of wise community volunteers, facilitating the implementation of social prescribing and consolidating their social engagement. Ultimately, both will enrich the understanding and utilization of wisdom among older adults.
You have
Access
Mental and social well-being are integral components of health, as their association with physical health is reciprocal. Wisdom has emerged as one of the domains of mental well-being as its core lies in the quintessential aspects of human life (Wang, Reference Wang2022). Due to its potential contribution to better overall physical health, mental well-being, and positive psychological experiences, enhancing wisdom shall be one of the healthy aging promoting strategies from a public health angle. To understand the role of wisdom in older adults’ well-being at a societal level and to develop and test wisdom-enhancing interventions, researchers have been called on to expand empirical research on wisdom (Jeste and Lee, Reference Jeste and Lee2019). However, wisdom research among older adults remains limited in the fast-growing literature. Little understanding of the measurements of wisdom may be one of the significant obstacles to the research community on old-age mental health.
Historically, the concept of wisdom has been explored in religion and philosophy. Throughout the way from the introduction of modern psychology, wisdom has been gradually embraced as a scientific construct (Grossmann et al., Reference Grossmann2020). Per se, wisdom is complicated to define its nature of unique humanness. In the past half-century, investigators have recognized that wisdom is driven by personal experience and demonstrated in behavior (Jeste et al., Reference Jeste, Ardelt, Blazer, Kraemer, Vaillant and Meeks2010). For example, a person who could find practical and emotionally satisfying solutions to a tensive situation may be considered a wise man. Nowadays, investigators have agreed that wisdom is a multidimensional trait consisting of specific domains. Most recently, Jeste and colleagues proposed that wisdom is relevant to seven domains: self-reflection, prosocial behaviors, emotional regulation, acceptance of diverse perspectives, decisiveness, social advising, and spirituality (Jeste et al., Reference Jeste2021). Following the multidimensional definition of wisdom, investigators have developed various measurements of wisdom that are requisite for empirical studies.
Among the existing literature, most assessment instruments on wisdom are self-rated scales (Bangen, et al., Reference Bangen, Meeks and Jeste2013). However, in a literature review, Meeks and Jeste proposed that certain neurocircuitry of normal brains may serve the neural substrates of wisdom components. For example, the amygdala, nucleus accumbens, striatum, and medial prefrontal cortex may formulate the circuit of social cooperation, which contributes to an individual’s prosocial attitudes and behaviors (Meeks and Jeste, Reference Meeks and Jeste2009). Therefore, building upon the neurobiological model, Thomas and colleagues developed the San Diego Wisdom Scale (SD-WISE) (Thomas et al., Reference Thomas2019). Compared with the Three-Dimensional Wisdom Scale (3D-WS), Self-Assessed Wisdom Scale (SAWS), and the Wise Thinking and Acting Questionnaire (WITHAQ), the SD-WISE is relatively more comprehensive in tapping into the core features of wisdom (Thomas et al., Reference Thomas2019). In addition, the recently developed 28-item SD-WISE (SD-WISE-28) expanded the original scope to a broader one, relating wisdom to cognitive and affective circuits and having spirituality neuroscience involved (Jeste et al., Reference Jeste2021).
Maintaining health and functioning for older adults is a critical public health priority. Many countries have funded healthy aging cohort studies, aiming to depict health outcomes trajectories and identify potential preventive strategies for reducing health problems and related disabilities (Minicuci et al., Reference Minicuci, Naidoo, Corso, Rocco, Chatterji and Kowal2019; Wu et al., Reference Wu2020; Zeng et al., Reference Zeng, Feng, Hesketh, Christensen and Vaupel2017). However, mental health primarily focuses on mood, cognition, and social participation across the large cohorts, while wisdom is rarely included and studied. On the one hand, the development of wisdom measurements is far behind the commencement of the nationwide or globally harmonized healthy aging cohorts. On the other hand, most wisdom scales are lengthy and may add time costs to the existing large-scale cohorts. Therefore, wisdom scientists have seen great promise in creating shorter measures of wisdom.
In the current issue of the International Psychogeriatrics, Thomas and colleagues (Reference Thomas2022) published an abbreviated SD-WISE consisting of seven items, one corresponding to one of seven components included in the original version. The authors used the SD-WISE-28 and collected valid data from 1,786 people aged 20–82. Following the procedures of fitting the data with the item response theory (IRT) graded response models, extracting the discrimination parameters, fitting the confirmatory factor model to the possible 7-item combination, and examining the psychometric properties with the IRT model, Thomas et al. proposed a 7-item SD-WISE as a brief and reliable scale to measure wisdom. It is interesting to find out that Leeman and colleagues recently did similar work, shortening the 40-item SAWS to 15 items based on a survey among Australian participants (Leeman et al., Reference Leeman, Knight, Fein, Winterbotham and Webster2022). However, different methodologies were applied in these two studies. Leeman et al. combined confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) in extracting five factors (Leeman et al., Reference Leeman, Knight, Fein, Winterbotham and Webster2022). Thomas et al., however, applied the IRT to select one item from each of the seven SD-WISE-28 subscales and formulated an abbreviated version (Thomas et al., Reference Thomas2022). The essential discrepancy between the two brief tools may lie in the grounded concept of wisdom in the original scales: SAWS includes five components – reminiscence/reflection, humor, emotional regulation, critical life experiences, and openness (Dean Webster, Reference Dean Webster2007; Leeman et al., Reference Leeman, Knight, Fein, Winterbotham and Webster2022); SD-WISE-27 consists of seven subscales (Jeste et al., Reference Jeste2021). Although, as Ardelt commented, “the SAWS might be considered a combination of predictors and consequences of wisdom rather than a measure of wisdom per se,” it is necessary for investigators to compare the qualities of the instruments and choose an optimal tool for their research purpose (Ardelt, Reference Ardelt2011).
As discussed earlier, wisdom would contribute more if viewed as an ecological mental health domain, especially when it integrates with emotional, psychological, and social well-being (Wang, Reference Wang2022). In their paper, Thomas et al. also computed the total score of the 7-item SD-WISE as the wisdom index to represent the overall wisdom. Furthermore, the index was correlated with mental health outcomes, such as depression, loneliness, resilience, happiness, and mental well-being (Thomas et al., Reference Thomas2022). Therefore, the global wisdom index drawn from the abbreviated version may be feasible for the cohort studies, taking advantage of simplicity and usefulness.
The authors’ observation of a modest positive association between overall wisdom and age may coincide with the assumption that people become happier when they get older (Jeste, et al., Reference Jeste, Wolkowitz and Palmer2011). However, in Thomas et al.’s study, the span of participants’ age was huge (Thomas et al., Reference Thomas2022). According to Sternberg’s perspective, “there is no one trajectory of wisdom with age” (Sternberg, Reference Sternberg2005). Wisdom development may have a plateau across the life course. Also, the genetic and socio-environmental factors may moderate the phenotype of wise behaviors. The age effect and its interaction with genetic susceptibility or lifestyle on the wisdom index were not examined thoroughly in Thomas et al.’s study. It remains unclear whether each component of wisdom shares a similar trajectory from 20 to 82 years. For example, a personal experience usually accumulates with age. Nevertheless, social participation may drop after a person retires. Less social interaction may not gain as much experience as it did prior to the retirement. In another situation, old persons with physical functional limitations may feel challenged to rate the reverse-scored item “I avoid situations where I know my help will be needed.” Therefore, measuring individuals’ wisdom needs to be adapted to their real-life situations.
Besides, the conception of wisdom in Thomas et al. study can be viewed as a person-based definition. In contrast, the demonstration of wise behavior may be better observed during the interaction between an individual and the situation faced by the individual, which could be considered an endeavor-based definition (Yang, et al., Reference Yang, Kuo and Lin2022). Yang et al. argued that “no prescribed set of internal qualities can consistently lead a person to display wisdom across all situations.” The SD-WISE-7 evaluates solely a person’s internal qualities and character strength rather than the real-life endeavors. Ideally, integrating person- and endeavor-based measurements could provide a comprehensive understanding of an individual’s wisdom. However, Yang et al. used 220 wisdom incidents to rate the three wisdom components, that is, cognitive integration, embodying actions, and positive effects (Yang et al., Reference Yang, Kuo and Lin2022). The long-standing process may compromise its feasibility in large-scale cohort studies. There might be some alternatives to consider. As discussed earlier, attaining wisdom resembles the formulation of cognitive reserve, where life experiences, such as acculturalization, social adaptation, lifetime learning, education, and leadership, may interplay (Wang, Reference Wang2020, Reference Wang2022). To my knowledge, most healthy aging cohorts measure individual development and social factors, such as life experiences, lifestyle, previous and present occupation, education, and social connectedness (Minicuci et al., Reference Minicuci, Naidoo, Corso, Rocco, Chatterji and Kowal2019; Wu et al., Reference Wu2020; Zeng et al., Reference Zeng, Feng, Hesketh, Christensen and Vaupel2017). These data, to some extent, may depict an individual’s social environment, subserving the foundation of wisdom development. It might be interesting to integrate the person-based measurement, if the SD-WISE-7 is applied, with social contextual factors, when exploring the health outcomes in old age.
From the positive aging perspective, measuring wisdom is not the end. Instead, it is a new beginning for developing mental well-being promoting interventions. With a more profound understanding of its constructive framework, mental healthcare providers are keen to bolster older adults’ wisdom and utilize their wisdom in the real-life process. In recent years, social prescribing has been introduced to some countries, aiming to improve health and well-being through addressing individuals’ social needs and connecting them to non-clinical services and supports (Morse et al., Reference Morse2022). Implementing social prescribing may depend on the synergy between the personal and societal levels, such as empowering individuals to build up their motivation and confidence and facilitating multi-sectoral collaboration to promote service integration. Previous local pilot projects have found that wise residents, sometimes called community volunteers, play pivotal roles in strengthening the efforts of link workers and social care workers and facilitating social prescribing in their neighborhoods (Morse et al., Reference Morse2022). Applying the brief tool of wisdom assessment in social prescribing may have a dual effect: First, it will boost the empirical wisdom research in aging cohorts; second, it may aid the recruitment of wise community volunteers, facilitating the implementation of social prescribing and consolidating their social engagement. Ultimately, both will enrich the understanding and utilization of wisdom among older adults.
Acknowledgements
This work was supported by grants from the Science and Technology Innovation 2030 – Major Project, Ministry of Science and Technology of China (2021ZD0201805).
Conflict of interest
The author has no conflict of interest to report.