research studies on psychological well being

Increasing evidence suggests that psychological well-being (PWB) is associated with lower disease and mortality risk, and may be enhanced with relatively low-cost interventions. Yet, dissemination of these interventions remains limited, in part because insufficient attention has been paid to distinct PWB dimensions, which may impact physical health outcomes differently.

This essay first reviews the empirical evidence regarding differential relationships between all-cause mortality and multiple dimensions of PWB (e.g., life purpose, mastery, positive affect, life satisfaction, optimism). Then, individual-level positive psychology interventions aimed at increasing PWB and tested in randomized-controlled trials are reviewed as these allow for easy implementation and potentially broad outreach to improve population well-being, in concert with efforts targeting other established social determinants of health.

Several PWB dimensions relate to mortality, with varying strength of evidence. Many of positive psychology trials indicate small-to-moderate improvements in PWB; rigorous institution-level interventions are comparatively few, but preliminary results suggest benefits as well. Examples of existing health policies geared towards the improvement of population well-being are also presented. Future avenues of well-being epidemiological and intervention research, as well as policy implications, are discussed.

Conclusions

Although research in the fields of behavioral and psychosomatic medicine, as well as health psychology have substantially contributed to the science of PWB, this body of work has been somewhat overlooked by the public health community. Yet, the growing interest in documenting well-being, in addition to examining its determinants and consequences at a population level may provoke a shift in perspective. To cultivate optimal well-being—mental, physical, social, and spiritual—consideration of a broader set of well-being measures, rigorous studies, and interventions that can be disseminated is critically needed.

Peer Review reports

Over the past decades, evidence for the mental and physical health benefits of enhanced psychological well-being (PWB) has expanded dramatically [ 1 , 2 , 3 ]. Notably, research in the fields of behavioral and psychosomatic medicine, as well as health psychology have substantially contributed to this body of work [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Yet, such work is still overlooked by a considerable proportion of the public health community, despite accumulating compelling reasons for a paradigm shift [ 8 ]. Associations of PWB levels with subsequent physical health outcomes have been well-documented [ 1 , 2 ]. Easy-to-implement well-being interventions have been developed and evaluated in randomized-controlled trials (RCT), with many showing positive results [ 9 , 10 ]. The potential for developing scalable interventions to be broadly disseminated is substantial and, in many cases, could require only limited or no professional training resources [ 9 , 10 ]. Such interventions would improve not only PWB, but may have the potential to promote and maintain physical health as well [ 11 ]. This could be done in concert with efforts targeting other established social determinants of physical health/mortality (e.g., poverty, education, discrimination, social capital) [ 12 , 13 ]. Existing skepticism among scientists may be due to insufficient attention paid to distinct dimensions of PWB (e.g., positive affect, optimism), which could differentially impact physical health and explain certain conflicting findings [ 2 ]. If PWB’s importance is to be embraced by the public health community and incorporated into policies, these distinctions need to be made clear. In this debate article, we argue that PWB dimensions, including life purpose, personal growth, mastery, autonomy, ikigai, life satisfaction, positive affect, sense of coherence, and optimism, may relate differently to all-cause mortality, based on existing empirical evidence. We also discuss some available interventions promoting PWB and how these might be used and disseminated more broadly.

PWB is important not only because of its potential effects on physical health but also as its own end. The World Health Organization (WHO) defines health as a “state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.” Importantly, PWB reflects more than the mere absence of psychological distress, such as anxiety or depressive symptoms. Although there is an inverse correlation between self-reported positive and negative psychological states, most coefficients vary from small-to-moderate, but are generally not strong in magnitude [ 14 , 15 , 16 ]. Psychological distress and well-being also have distinct biological correlates, further supporting the idea that they are separate rather than mirrored constructs [ 15 , 17 , 18 , 19 ]. Accordingly, a successful psychotherapeutic or pharmacological treatment of anxiety symptoms will decrease symptoms of psychological distress but will not necessarily translate into a greater sense of purpose in life, autonomy, or optimism.

If we are to take seriously the WHO’s integrative conceptualization of health, PWB should be embraced as a fundamental public health goal [ 8 ]. The adoption of policies and programs supporting PWB in individuals and groups requires an understanding of the potential community benefits of such efforts. Through our assessment of the research investigating the relationship between PWB and all-cause mortality, interventions to change PWB, and policy implications of well-being research, we aim to contribute to this understanding.

Defining well-being

Well-being is a complex and multifactorial construct. Measures of well-being are sometimes divided into objective measures, which mostly refer to “standard of living,” and subjective measures, which capture psychological, social, and spiritual aspects and are based on cognitive and affective judgements individuals make about their lives [ 20 ]. When these measures concern psychological aspects (e.g., happiness), they are often referred to as measures of psychological well-being (PWB). While certain PWB dimensions such as life satisfaction are often imbedded in “quality of life” measures, this latter multidimensional construct is much broader and includes other aspects related to mental and physical health like perceived stress, functioning/disability status, and physical symptoms [ 21 , 22 ]. PWB on its own has been a central area of research in psychology for decades [ 7 ]. It is also important to epidemiology, to understand its contribution to health outcomes [ 8 ], and more broadly to public health, notably to implement country-level monitoring and policies promoting overall health [ 7 ].

Distinct theoretical dimensions have been proposed to characterize PWB research thus far (see [ 1 ] for details) including: hedonic well-being (e.g., feeling happy), evaluative well-being (e.g. being satisfied with life), eudaimonic well-being (e.g., finding purpose in life, having a sense of mastery and autonomy in one’s own decisions), and other constructs that contribute to feeling whole or well (e.g., optimism). In the following section, we describe these PWB dimensions and illustrate their potential effects on physical health by examining the evidence on how each is associated with all-cause mortality. Even though composite PWB measures exist, some authors have shown that it remains difficult to measure PWB across a continuum (unidimensionally) [ 23 ] and others have insisted on understanding PWB as a multidimensional, rather than unidimensional, construct [ 24 ]. Moreover, research has documented statistically significant associations among PWB dimensions themselves, with magnitude of estimates varying from small to moderate when evaluated among adults from various countries [ 14 , 25 , 26 , 27 , 28 ]. Overall, these findings suggest that although PWB dimensions may share a latent factor, they do represent distinct constructs.

Psychological well-being and mortality

A growing body of evidence suggests that various PWB dimensions are associated with subsequent chronic diseases and mortality, and potential mechanisms explaining associations, including stress-buffering effects [ 1 , 2 ] and healthier behaviors [ 1 , 2 , 5 , 29 ]. For instance, prior epidemiological research has shown that individuals experiencing higher levels of optimism were more likely to subsequently engage in favorable habits (e.g., physical activity), reduce/cease detrimental ones (e.g., smoking), leading to an overall healthy lifestyle [ 30 , 31 , 32 , 33 ]; in turn, the adoption of such healthy habits may lower one’s risk of chronic diseases and mortality [ 1 , 2 ]. However, it is not always clear whether these longitudinal relationships remain after rigorous confounder control, whereby a third factor, such as socioeconomic status (e.g., education, personal income), influences both PWB and health. Likewise, whether these longitudinal associations do not simply capture reverse causation, whereby health status drives PWB levels, is sometimes uncertain. However, considering premature mortality risk, an objective endpoint, offers some methodological strengths such as virtually no misclassification and research based on longitudinal design by nature of the outcome. Recent meta-analyses have suggested that life satisfaction, positive affect, meaning/purpose in life, and optimism are protective against premature mortality [ 34 , 35 , 36 ], though the quality of statistical adjustment for potential confounders in these studies was variable. Here, we briefly discuss evidence as to whether and how various PWB dimensions are prospectively associated with premature all-cause mortality, specifically. Searches of literature written in English or French within PubMed and PsycInfo databases targeted individual prospective and longitudinal studies evaluating the role of at least one PWB dimension with mortality risk. Additional studies were obtained through bibliographies of eligible articles. Rigorous individual studies included in this narrative review all adjusted for baseline sociodemographics (e.g., age, sex, education), medical status (e.g., blood pressure, body mass index, chronic conditions), and health behaviors (e.g., smoking, physical activity). Some studies further adjusted for psychological distress, to determine PWB’s role on mortality beyond anxiety and depression symptoms, and for self-rated health.

Purpose in life

Experiencing a sense of purpose and direction in one’s life has been consistently associated with reduced mortality. For instance, among 1236 older U.S. adults (mean age = 78 years), every standard deviation (SD) increase in life purpose was associated with 40% decreased hazard of 5-year mortality (hazard ratio, HR = 0.60; 95% confidence interval, CI = 0.42–0.87) [ 37 ]. In the Women’s Health Initiative cohort, after additional statistical control for psychological distress in multivariable models, greater life purpose was associated with lower likelihood of death over a 2-year period in 7675 older U.S. women [ 38 ]. Meta-analyses suggested similar effects (higher versus lower purpose in life; rate ratio, RR = 0.83, CI = 0.75–0.91) [ 35 ]. Some research has examined the role of meaning in life but the results are less convincing than those assessing purpose. A study of 1361 older U.S. adults (mean age = 79 years) over 5 years found no relationship of meaning in life with overall mortality (OR = 0.97; CI = 0.93–1.01) in multivariable models further adjusting for self-rated health [ 39 ]. These results raise the question of whether “meaning” and “purpose,” often used interchangeably, might capture distinct constructs that relate differently to mortality [ 40 ].

Personal growth

To our knowledge, personal growth –that is whether individuals seek to realize their full potential and recognize that the self is constantly developing– has been explored in relation to mortality in only a handful of studies. Notably, in the Women’s Health Initiative investigation described above, personal growth levels were associated with lower 2-year mortality rates, both continuously (per 1-unit increase: HR = 0.95; CI = 0.93–0.98) and categorically (lower versus higher [reference group] quartile: OR = 2.10, CI = 1.42–3.08) [ 38 ]. This study also evaluated life purpose, with contrasting multivariable-adjusted estimates suggesting stronger associations with life purpose than personal growth (ORs = 3.55 versus 2.10) on mortality.

Mastery –whether individuals effectively manage their environments or perceive life as being under their control– has also been well-studied in relation to mortality. An investigation following 2829 Dutch adults (ages 55–85) for up to 3 years found that a 1-unit rise was associated with lower mortality odds (OR = 0.94, CI = 0.89–0.99), even after extensive adjustment of covariates including self-rated health, social support, self-efficacy, and self-esteem [ 41 ]. Likewise, among English adults from the EPIC-Norfolk Study ( N = 20,495; ages 41–80), every 1-SD increase in mastery was associated with a lower rate of death (RR = 0.82, CI = 0.76–0.89) over 5 years, further controlling for psychological distress [ 42 ]. Similar results were obtained in U.S. samples too [ 43 ].

Although research is sparse, available evidence suggests mortality risk is not strongly associated with autonomy, characterized as the extent to which individuals act independently without concern for external pressures. In a study of 9420 midlife British adults (mean age = 58 years) over a 5-year period, autonomy scores were unrelated to the hazard of death in multivariable models also controlling for self-rated health and psychological distress (per 1-unit increase: HR = 1.02; CI = 0.96–1.09) [ 44 ].

This Japanese term translates into the happiness, worth, and benefit of being alive. It captures not only eudaimonic well-being (e.g., life purpose) but also hedonic well-being (e.g., pleasure), though usually assessed with only one item. Using data from the nationwide Japan Collaborative Cohort Study for Evaluation of Cancer Risk ( N = 73,272; ages 40–79), adults with higher (versus lower) levels of ikigai had a reduced hazard of mortality over 5 years (HR men = 0.80; CI = 0.72–0.89; HR women = 0.80; CI = 0.69–0.92) [ 45 ]. In another Japanese cohort ( N = 43,391; ages 40–79), lower and moderate ikigai levels (versus higher) were related to an increased 7-year hazard of death (HR moderate = 1.1; CI = 1.0–1.2; HR lower = 1.5; CI = 1.3–1.7), with further adjustment for self-rated health not altering these results [ 46 ].

Positive affect

Feeling happy, joyful, cheerful, excited and proud are often included in the construct of positive affect. Data from the German Aging Survey ( N = 3124; ages 40–85) showed that every unit increase in positive affect was associated with a lower 14-year mortality risk, after adjusting for sociodemographics, medical status, psychological distress, and also life satisfaction (HR = 0.81, CI = 0.70–0.93), though further controlling for self-rated health and physical activity attenuated the association (HR = 0.88, CI = 0.76–1.02) [ 47 ]. Even if happiness is a pleasurable feeling that is sometimes included in positive affect, it has also been studied on its own in prior PWB-mortality research. In a subset of the Million Women Study ( N = 719,617; ages 53–72), English women who said they were “unhappy” or “usually happy” on a 1-item measure did not differ in mortality risk in 10-year follow-up compared to those who said they were “happy most of the time” (RR = 0.98, CI = 0.94–1.01; RR = 0.99, CI = 0.96–1.01, respectively) [ 48 ]. While this study has drawn media attention because of its large sample size and control for multiple covariates, its conclusions based on the use of a single happiness item have also has generated some controversy. Likewise, another study of older adults found no association between happiness assessed with 2 items and mortality [ 49 ]. These results may suggest that the comprehensive experience of various types of positive affect, rather than the sole experience of feeling happy as captured by single items, is what matters in terms of longevity.

Life satisfaction

Life satisfaction can be measured either globally, capturing the extent to which individuals judge their life as a whole to be satisfactory, or specifically by life domains (e.g., work, family). A Canadian population-based study ( N = 73,904; ages 18 to > 80) revealed that “very dissatisfied” (versus “very satisfied or satisfied”) individuals had an increased mortality risk (HR = 1.70, CI = 1.16–2.51), after controlling for numerous relevant covariates [ 50 ]. In the German Aging Survey described above, mortality risk was reduced for each unit increase in life satisfaction after adjusting for sociodemographics, medical status, psychological distress and also positive affect (HR = 0.89, CI = 0.79–1.00), but became unrelated after additional controlling for self-rated health and physical activity [ 47 ]. Although the estimate appears stronger with positive affect than life satisfaction in this study, even after including both in statistical models, these dimensions were assessed with distinct scales and scores were not standardized, which precludes formal comparison.

Sense of coherence

One of the most rigorous early studies evaluating sense of coherence’s role in mortality risk has been conducted in the EPIC-Norfolk Study data ( N = 16,668; ages 41–80) [ 51 ]. Sense of coherence was captured by the sum of 3 items measuring, respectively, the level of manageability, comprehensibility, and meaningfulness in one’s life. Adults with higher (versus lower) sense of coherence had a reduced risk of 6-year mortality (RR = 0.76, CI = 0.64–0.90), after statistical control for multiple covariates including psychological distress. These results have been replicated in a recent study of 585 men who were followed for 22 years and completed a more comprehensive assessment of the three constructs above [ 52 ]. Yet, it remains unclear whether any protective effects on mortality risk should instead be attributed to other PWB constructs captured by this scale. Notably, the meaningfulness item (“ Do you usually feel that your daily life is a source of personal satisfaction ?”) might relate to lower mortality risk because it captures, in fact, life satisfaction.

Multiple investigations indicate that dispositional optimism—a person’s general expectation that the future will turn out well or that good things will happen in the future—is associated with lower mortality rates. The Women’s Health Initiative ( N = 97,253; ages 50–79) showed that higher versus lower quartiles of optimism were related to a reduced hazard of mortality over 8 years (HR = 0.86, CI = 0.79–0.93), after adding psychological distress to multivariable models [ 53 ]. Analyses conducted in another cohort of midlife U.S. women, the Nurses’ Health Study, replicated these results using the same research design [ 54 ]. Additionally, a Netherlands-based study among men and women ages 65–85 ( N = 941) found a similar pattern over a 9-year period (HR higher versus lower quartiles = 0.71; CI = 0.52–0.97), although results were not adjusted for psychological distress [ 55 ]. Altogether, these estimates are comparable to those reported by a recent meta-analysis (higher versus lower optimism; RR = 0.86; 95% CI, 0.80–0.92) [ 36 ].

Overall psychological well-being

Other authors have considered global measures of psychological well-being. For instance, in a subset of the Midlife in the United States Study ( N = 3032; ages 25–74), scores on items assessing positive affect, life satisfaction, eudaimonic well-being and social well-being were combined to capture positive mental health—also labeled flourishing by the authors [ 56 ]. Multivariable findings indicated that lower versus higher flourishing levels were related to greater odds of 10-year mortality (OR = 1.62; CI = 1.00–2.62). While combining various components of PWB may form a stronger predictor of subsequent health [ 57 ], these composite scores also somewhat limit our understanding of the specific dimensions that matter and the recommendations for future interventions.

Overall, existing literature indicates that several PWB dimensions are associated with a reduced risk of premature all-cause mortality among the general population, with small to medium effects. These relationships were observed in studies with large sample sizes and over short to long follow-up periods. Associations were robust to adjustment for numerous covariates, including potential mechanisms that could explain associations (e.g., health behaviors); for some dimensions, associations were obtained despite the use of distinct PWB measures (e.g., optimism, sense of coherence). Among the dimensions reviewed, purpose in life, optimism, and ikigai , had the strongest evidence, followed by life satisfaction, positive affect, mastery, and sense of coherence. Available results with happiness, personal growth, and autonomy suggested no effect or were too limited to draw firm conclusions. Other PWB dimensions, including self-acceptance and emotional vitality, may have been investigated with all-cause mortality risk using prospective research designs, but studies using rigorous control for traditional medical and behavioral risk factors are scarce.

All studies reported above carefully controlled for sociodemographics, medical status, and health behaviors, and even after further adjustment for psychological distress, associations were generally evident, which further supports PWB as distinct from the absence of psychological distress. When more than one PWB dimension was investigated, however, very few authors evaluated their independent roles by including dimensions simultaneously in the models [ 47 ]. Thus, while these PWB factors appear conceptually distinct, it remains uncertain whether they independently reduce all-cause mortality and if so, the relative magnitude of their effects. When adjusting for self-rated health, some of the studies of certain domains, though not all, indicated null estimates. Self-rated health usually assesses, via one item, whether individuals perceive their health as excellent, very good, good, fair or poor, and is one of the strongest predictors of future morbidity and mortality risk [ 58 ]. However, controlling for self-rated health may sometimes be an overadjustment, because this rating is both defined and influenced by functional health, physical conditions, and most importantly, psychological distress and well-being [ 58 ]. Nevertheless, those PWB dimensions that are associated with lower mortality even after adjustment for self-rated health arguably manifest even stronger evidence for a causal relationship.

Psychological well-being and other outcomes

Although our narrative review focused on mortality, it is worth briefly noting that PWB may have important effects on numerous other outcomes. Observational and experimental research indicates that greater PWB levels are related to lower risk of cardiometabolic diseases, infectious illness and physical decline, though results with cancer are less clear [ 1 , 2 , 54 ]; PWB has also been related to more favorable health behaviors and healthier biological processes, which could act as mechanistic pathways relating PWB to chronic disease and mortality risk [ 1 , 2 , 29 , 33 ]. Observational and experimental research also suggests PWB relates to higher future levels of employment, income, and work retention, as well as greater social support later on [ 59 ]. Likewise, prospective observational studies show that low PWB levels, including dimensions like self-acceptance, autonomy, life purpose, positive relationships, and mastery, are associated with greater likelihood of clinical depression 10 years later, after controlling for baseline traditional risk factors and psychological distress [ 60 ]. PWB was predictive of post-treatment symptom severity and remission status, independent of initial symptoms of depression and anxiety, in a recent clinical trial evaluating the effectiveness of cognitive-behavioral therapy for anxiety disorders [ 61 ]. PWB is not simply the absence of mental illness, and, in fact, contributes to subsequently preventing its onset and relapse. Moreover, PWB is desired not primarily because of its effects on mental and physical health, but as an end itself [ 57 ]. Most people want to be happy, satisfied with their life, and pursue a life that has meaning. PWB is thus important in its own right.

Interventions

Albeit approximately 30% of one’s PWB is explained by heritable/dispositional factors, it is clear that external life events and environmental influences can account for a large proportion of an individual’s PWB. For instance, it has been well documented that greater levels of PWB are associated with higher levels of education, income, occupational status, and social capital [ 3 , 7 , 62 , 63 ]. Intentional choices and behaviors, such as self-regulation and lifestyle habits, are also important determinants of PWB [ 5 , 63 ]. Positive psychology (PP) thus appears as a compelling intervention strategy, as it aims to improve the frequency and intensity of positive emotional experiences, including optimism, gratitude, purpose/satisfaction in life, and positive affect, through intentional actions in the form of targeted, structured activities [ 9 , 64 , 65 ]. While these interventions aim to improve PWB within individuals, individuals are not the sole responsible agent of such changes; in fact, leveraging community and institutional resources is also increasingly encouraged to promote all individuals’ PWB by making strategies accessible to diverse groups of the population. In this regard, various PP interventions have been evaluated and have shown to improve mood and well-being among different populations [ 7 , 9 , 10 , 65 ].

At the individual level, PP interventions are typically assigned, either separately or in combination, on a short-term regular basis (e.g., weekly) for participants to complete on their own, and then, in some cases, reviewed with a clinical or research professional to further elicit PWB [ 66 ]. Individual, group, and self-help interventions, including acts of kindness, counting blessings, and mindfulness, were first evaluated in non-clinical samples (e.g., community, students; examples in Table 1 with complete references in the Additional file 1 ) [ 9 , 63 , 64 ].

In an early meta-analysis of 49 randomized or quasi-experimental studies ( N = 4235), such PP interventions improved well-being, with a small but clinically meaningful mean effect size ( r = 0.29, CI = 0.21–0.37) [ 64 ]. A more recent meta-analysis of 39 RCTs ( N = 6139) [ 9 ] showed a similar effect of PP interventions on PWB (Cohen’s d = 0.20, CI = 0.09–0.30), with strongest effects for strategies targeting optimism, gratitude, and kindness [ 67 ], and with gains persisting for up to 6 months post-intervention ( d = 0.16, CI = 0.02–0.30). Comparable effects are observed among clinical populations. A meta-analysis of 30 studies ( N = 1864) in participants with either a psychiatric disorder (e.g., depression, anxiety) or a somatic condition (e.g., cardiometabolic disease, cancer) indicated that PP interventions had a small but meaningful effect on PWB (Hedges’ g = 0.24, CI = 0.13–0.35) [ 65 ]. Yet, it is still unclear whether longer-term health outcomes, including disease incidence and premature mortality, may be altered by improving PWB through these brief PP interventions, or if longer, more intensive interventions would be required [ 2 ].

Considering PP interventions at the institutional level is also critical. Because even changes of small magnitude at the individual level may translate into large changes at the population level, the potential benefits of such interventions on mental and physical health, including mortality risk, may be substantial. For instance, recent research has estimated a 5% decreased risk of stroke for individuals endorsing higher vs. lower levels of optimism, via optimism’ role on healthy lifestyle [ 33 ]. Such reduction in risk would indeed have major repercussions on a population’s health and economy .

In 2018, a public health summit of experts in mental and occupational health urged for building scientific evidence in the workplace that supports specific interventions aiming to improve and maintain employees’ health, including PWB [ 68 ]. Practices supporting, for instance, work-life balance and a physically/psychologically safe environment contributed to job satisfaction, independently of wages [ 20 , 68 ]. Because employees’ general sense of well-being, beyond job satisfaction, could contribute to productivity and profitability [ 20 , 68 ], broadly defined well-being interventions are increasingly evaluated in organizational settings. While the number of workplace-related RCTs is comparatively fewer, preliminary results are encouraging. A recent systematic review of RCTs and quasi-experimental studies indicated that PP interventions in the workplace were the only brief interventions to have a meaningful, albeit small, impact on employees’ mental health and well-being, whereas no evidence was found for strategies like relaxation and massage [ 69 ]. A subsequent RCT tested a 5-week online PP intervention adapted for the workplace among U.K. government employees (Table 2 ) [ 10 ]. Participants receiving the intervention ( n = 170; vs. wait-list control group, n = 160) reported enhanced levels of positive affect and flourishing ( p < .05), but not life satisfaction, post-intervention [ 10 ], reinforcing further empirical attention to PWB facets separately.

Besides the workplace, institution-based RCTs have also been conducted in schools (examples in Table 2 with complete references in the Additional file 1 ). While most studies have evaluated multicomponent interventions, making it difficult to disentangle the contribution of specific strategies, beneficial effects on PWB and other psychosocial outcomes were often observed. Other interventions relying on cognitive-behavioral strategies, like the Penn Resiliency Program, have been successful in improving psychosocial outcomes, including PWB, in schools and other settings (e.g., U.S. Army, see details in [ 11 ]).

Policy implications

Over the past decade, governments from a dozen countries have also initiated regular well-being surveys as a component of public health data collection. Some countries evaluate hedonic PWB through a four-to-six domain questionnaire. Notably, in Bhutan, PWB is evaluated every few years with items like “ All things considered, how satisfied are you with your life as a whole these days? ”, along with other complimentary domains including social support, negative emotional experience, and spirituality. Likewise, the U.K. national survey includes a similar life satisfaction question, as well as items probing meaningful activities and positive/negative affect. Other national surveys use broader, culturally-relevant indices or objective well-being measures that capture infrastructure and services, environment and landscape factors, social relationships and even trust in government (e.g., Italy, Israel, Canada). International well-being surveys sometimes issue an annual “happiest country on Earth.” This judgment pleases not only the popular press, but also national governments that increasingly recognize that well-being measures can be a crude but reliable indicator of overall citizen satisfaction. Results from these surveys, after being reported to national assemblies, may also subsequently spur policy interventions. For example, the U.K. initiated the 24-h, free and confidential helpline, “Silver Line”, in 2013 in response to survey feedback of decreasing social connectedness among the aged [ 70 ]. Over 5 years, 2 million calls were received and over 70% reported that the helpline not only enhanced their social lives but also their happiness [ 70 ]; the U.K.’s first Minister of Loneliness was subsequently appointed in 2018.

Besides the importance of systematic monitoring of well-being indicators at the population level, implementing effective well-being policies is key to having a broader outreach in addition to individually tailored interventions. Notably, the Health-in-All-Policies (HiAP) approach, originating in South Australia, Europe, and Canada, has introduced a strategic way to better tackle social determinants of health, as documented in the 2010 Adelaide Statement [ 71 ]. This administrative process, more recently adapted by U.S. state and local governments, integrates health as a central outcome of all departments regardless of their functional oversight. Consequently, all sectors (e.g., employment, parks and recreation, housing administrations) become responsible for health-related interventions (e.g., facilitating access to greenness), rather than relying solely on public health policies [ 72 ]. For instance, better transport opportunities (e.g., cycling and walking paths) and reducing environmental degradation (e.g., pollution) may be ensured by leveraging a collaborative workforce as well as cross-cutting information and evaluation systems [ 71 ]. Such collaborative approaches can in turn enhance a population’s physical health more efficiently, via downstream consequences on common risk factors (e.g., obesity) and chronic conditions (e.g., cardiovascular diseases). HiAP could be improved by further integrating well-being science, including brief and relatively low-cost empirically-based PP interventions, into such municipal- and state-led strategies. Even though effects observed in individual-level RCTs are small in magnitude, such improvements in PWB could translate into notable changes at the population-level.

In parallel, policy strategies should address “the causes of the cause,” namely upstream social determinants that may drive PWB per se. As briefly mentioned previously, higher levels of education, income, occupational status, and social capital [ 3 , 7 , 62 , 63 ], to name a few, have been associated with enhanced levels of PWB. Coordinated government actions, notably via the HiAP approach, tackle such social determinants. For example, working towards educational attainment and employment stability across various sociodemographic groups would not only create engaged citizens and promote better physical health, but also potentially increase their PWB [ 71 ]. Additionally, anti-discrimination policies, including the Equal Employment Opportunity Act, have historically helped to minimize group-based disparities in the social determinants of mental and physical health [ 73 ]. Therefore, stronger enforcement of anti-discrimination policies might be another way to alter downstream PWB. Efforts to support families and opportunities for community participation could likely increase levels of PWB as well [ 8 , 57 ]. Lastly, because economic motives may act as a barrier to seeking mental health support, adequate reimbursement of psychotherapy services could also be implemented to enhance PWB [ 74 ].

Existing community initiatives might be disseminated across the country as well. Among others, the Office of Civic Wellbeing located in and supported by the city of Santa Monica, California, has launched the Wellbeing Project in 2013 [ 75 ]. This groundbreaking model for city governments uses the science of well-being to document community’s strengths and needs, along with the multiple determinants involved, to improve collective well-being. Moving from data to action, the Office has now various ongoing projects dealing with social determinants of PWB. One of them, in partnership with the Los Angeles County Department of Public Social Services, enrolls eligible Santa Monica residents for “CalFresh,” a public benefit program that supports individuals to meet their nutritional needs and improve healthy eating [ 75 ].

Limitations and future avenues

PWB has promising potential to improve mental and physical health, derived from epidemiological studies and clinical trials described above. Although the current review was comprehensive but non-systematic by nature, some limitations were evident and should guide future research and practice. Firstly, PWB-mortality associations have been rarely investigated across sociodemographic groups (i.e., by explicitly evaluating effect modification, beyond statistical adjustment), and many interventions have been restricted to clinical or convenience samples, mostly in high-income countries, which may not be generalizable to other populations. Yet, preliminary observational findings from these studies hint at effect modification by sex [ 34 , 45 ], race/ethnicity [ 53 ], educational attainment [ 43 ], as well as specific causes of death (e.g., cardiovascular versus cancer) [ 42 , 45 , 53 ]. As for age, insight about the role of PWB, as experienced during childhood or adolescence, in health would be informative from a lifecourse perspective. However, most epidemiological cohorts have not queried PWB indicators in early life, and studies in younger individuals do not have the required follow-up to evaluate PWB’s role in mortality.

With regard to lower-middle-income countries, a handful of studies have examined the interplay between mental and physical health. However, to our knowledge they either have not collected data on PWB indicators specifically to date (e.g., the Kenyan Grandparents Study) or did not yet investigate PWB’s role in mortality, most likely because they were initiated recently (e.g., the Brazilian Longitudinal Study of Aging, Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa). Besides country-level income, the role of other indicators of socioeconomic status (SES) in the PWB-mortality relationship specifically is less known. In fact, although most rigorous studies cited above have controlled for education level, fewer investigations have adjusted for individual/family income [ 38 , 44 , 53 ], occupation status/types [ 42 , 45 , 46 , 51 , 53 , 55 ], or area deprivation [ 48 ], and did not formally assess effect modification. Hence, it remains unclear as of now whether findings obtained from studies assessing the PWB-mortality association in high-income countries and adjusting for certain SES indicators may generalize to those of lower-middle-income countries and other socioeconomic groups.

Furthermore, rigorous methodologies should be favored (e.g., lagged analyses to address potential for reverse causation, repeated PWB measurements to capture changes, comprehensive set of covariates to account for confounding, simultaneous adjustment for multiple dimensions of PWB). In addition to improving methodological rigor, systematically incorporating well-being scales in large national cohort studies will help solidify the evidence of PWB’s causal role in health outcomes [ 8 ].

Of course, PWB measure selection depends on the context. For instance, for a multi-purpose epidemiological cohort study, with limited space on the questionnaires, or for studies in which PWB is investigated only as an outcome, a composite PWB measure might be sufficient. However, to advance science and be more precise, and consistent with the argument that PWB is a multidimensional rather than unidimensional construct detailed above, dimension-specific measures should be favored. To date, numerous large-scale studies have administered at least one PWB measure to their participants (e.g., Women’s Health Initiative cohort, Nurses’ Health Study, Midlife in the United States Study, Health and Retirement Study, Longitudinal Aging Study Amsterdam, EPIC-Norfolk Study, Japan Collaborative Cohort Study). Including additional PWB measures in these studies, to permit comparison across constructs, and expanding PWB assessments to other large national cohorts is warranted. Consequently, such evidence will guide the development of more targeted and efficient intervention, as well as primary/primordial prevention strategies. For instance, PP interventions implemented earlier in the lifecourse may have the potential to reduce adverse behaviors and detrimental biological processes over time, possibly lowering likelihood of chronic illness later in life.

Lastly, additional research exploring whether and how well-being strategies and policies can be implemented in communities will be needed to achieve a population-level impact. Notably, health professionals should assess the barriers and benefits of integrating PWB into standard clinical practices focused on deficits and disorders. Leveraging input from local agents who grasp the needs and characteristics of certain subgroups would facilitate the crafting and delivery of empirically-based PP interventions (e.g., teachers in targeted schools of low-SES neighborhoods). Eventually, public health policy-makers will have to evaluate the cost-effectiveness of implementing PP interventions in these distinct environments (e.g., medical settings, schools, neighborhoods) [ 76 ].

Existing research to date suggests that many, though not all, dimensions of psychological well-being (PWB) are associated with all-cause mortality. Building from the evidence of associations between PWB and mortality, this essay then discusses interventions to promote PWB. Many randomized-controlled trials evaluating positive psychology interventions at the individual level indicate small-to-moderate improvements in various PWB dimensions; rigorous institution-level interventions are comparatively few, but preliminary results suggest benefits as well. These interventions have the potential to be easily implemented and, in turn, have a broad outreach to improve population well-being. Existing health policies geared towards the improvement of population well-being could also leverage the science of PWB.

While this body of work has been overlooked by part of the public health community [ 8 , 11 ], the growing interest in documenting well-being, in addition to examining its determinants and consequences at a population level may provoke a shift in perspective. Over the past decade, numerous countries have initiated well-being assessment via national surveys, which have led to the implementation of some institutional policies geared towards PWB’s enhancement. However, there is at present no attempt at national measurement in the U.S.; it is perhaps time that this be changed. To cultivate optimal well-being—mental, physical, social, and spiritual—consideration of a broader set of well-being measures, rigorous studies, as well as public and private interventions is critically needed.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

Confidence interval

Health-in-All-Policies

Hazard ratio

Positive psychology

Psychological well-being

Randomized-controlled trial

Relative risk

Standard deviation

United Kingdom

United States

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Acknowledgements

We thank Dr. Laura D. Kubzansky for prior discussions on this topic.

Funding: This work was supported by salary and training support from the Canadian Institute of Health Research and the Fonds de Recherche du Québec – Santé (postdoctoral fellowships) to CTF, the National Institutes of Health to RAM, CVH, and LPT (NHLBI grant K23 HL135277, NCI grant 3R25CA057711, and T32-ES007069, respectively), as well as the John Templeton Foundation (grant 61075) to TJV. These funding bodies were not involved in the design of the current study, nor the collection, analysis, or interpretation of data and in writing the current manuscript.

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CTF and TJV conceived the manuscript idea; CTF conducted a first review of the literature in 2015–2016; CTF, TJV, RAM, CVH, CJH, LPT and GRW updated the literature review in 2018; CTF and TJV wrote the manuscript; CTF, TJV, RAM, CVH, CJH, LPT and GRW provided critical feedback on the manuscript and approved the final version.

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Trudel-Fitzgerald, C., Millstein, R.A., von Hippel, C. et al. Psychological well-being as part of the public health debate? Insight into dimensions, interventions, and policy. BMC Public Health 19 , 1712 (2019). https://doi.org/10.1186/s12889-019-8029-x

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The Relationship between Psychological Well-Being and Psychosocial Factors in University Students

Francisco manuel morales-rodríguez.

1 Department of Educational and Developmental Psychology, Faculty of Psychology, Campus Universitario de Cartuja, University of Granada, 18071 Granada, Spain; [email protected]

Isabel Espigares-López

2 Department of Legal Medicine, Toxicology and Psychiatry, Faculty of Medicine, Avda. de la Investigación, 11, 18016 Granada, Spain; [email protected]

3 Department of Occupational Therapy, Faculty of Medicine, Nursing and Health Sciences, Monash University—Peninsula Campus, Frankston, VIC 3199, Australia; [email protected]

José Manuel Pérez-Mármol

4 Department of Physiotherapy, Faculty of Health Sciences, University of Granada, Avda. de la Ilustración, 60, 18016 Granada, Spain

5 Instituto de Investigación Biosanitaria de Granada (ibs.Granada), 18016 Granada, Spain

Determining what factors influence the psychological well-being of undergraduate university students may provide valuable information to inform the development of intervention programs and targeted learning activities. The objective of this study was to investigate the correlation between psychological well-being in university students and their self-reported learning styles and methodologies, social skills, emotional intelligence, anxiety, empathy and self-concept. The final sample consisted of 149 Spanish university students, with an average age of 21.59 years ( SD = 4.64). Psychological well-being dimensions, along with learning style and methodology preferences, social skills, level of social responsibility, emotional intelligence, state and trait anxiety, empathy and levels of self-concept were measured using a series of validated self-report scales. The results indicate that the total variance explained by the university students’ psychological well-being factors were as follows: i) self-acceptance dimension (R 2 = 0.586, F (6,99) = 23.335, p < 0.001); ii) positive relationships dimension (R 2 = 0.520, F (6,99) = 17.874, p < 0.001); iii) autonomy dimension (R 2 = 0.313, F (4,101) = 11.525, p < 0.001); iv) environmental mastery dimension (R 2 = 0.489, F (4,101) = 24.139, p < 0.001); v) personal growth dimension (R 2 = 0.354, F (4,101) = 13.838, p < 0.001); and vi) purpose-in-life dimension (R 2 = 0.439, F (4,101) = 19.786, p < 0.001). The study findings may be used to inform new educational policies and interventions aimed at improving the psychological well-being of university students in the international context.

1. Introduction

1.1. psychological well-being.

Psychological well-being has been defined within the eudaimonic perspective as the development of one’s true potential. This is in contrast to the subjective well-being view [ 1 , 2 ]. Psychological well-being is viewed as the result of a life well-lived and is an important factor in students successfully adapting to college/university life. For this reason, this construct usually includes dimensions such as self-acceptance, positive relationships, autonomy, environmental mastery, personal growth and purpose-in-life [ 3 ]. Students attending university have to adjust to a new learning context and are under increased academic pressure [ 4 , 5 ]. This stage is considered to be one of the highest anxiety and lowest psychological well-being phases in the life cycle, with high levels of psychological distress compared with the general population [ 4 , 6 ]. Several studies have reported lower levels of psychological well-being in students attending university [ 3 , 7 , 8 ]. In a recent study by Sandoval et al. [ 8 ], a high percentage of university students exhibited a medium degree of psychological well-being, indicating that it is an indicator of their degree of adjustment adaptation.

1.2. Psychosocial Factors

Several models support the possible psychosocial factors related to psychological well-being. From a general perspective, the psycho-educational approach is an integral framework for the development and evaluation of psychological and educational constructs such as social skills, empathy, self-concept, anxiety and emotional intelligence, among others [ 9 , 10 , 11 ]. More specific frameworks, such as EuroPsy for the development of standards for high-quality professional education in psychology, include the following higher education competencies: adequate levels of empathy or anxiety, socially responsible attitudes, emotional management, problem solving and learning style preferences [ 11 ]. Other frameworks, such as the European Higher Education Area [ 10 ] and the Organization for Economic Cooperation and Development [ 9 ], highlight the importance of developing systemic competencies that include inter- and intra-personal psychological resources such as emotional intelligence, self-esteem, social skills, social responsibility and empathy [ 9 , 10 ]. From a psychological perspective, emotions are key constructs related to psychological well-being and satisfaction with life, according to classical theoretical models such as that of Goleman [ 12 ], Mayer et al. [ 13 ] and Bar-On [ 14 ]. Other more contemporary models include those by Bisquerra and Pérez-Escoda [ 12 , 15 , 16 , 17 , 18 ]. These models propose that emotional/psychological skills may be divided into two poles inside a continuum. The positive side includes elements such as self-esteem, social skills and empathic attitudes, and the negative side includes symptoms such as anxiety [ 5 , 19 , 20 , 21 , 22 ]. Both sides seem to have a relationship with psychological well-being, according to the existing empirical literature [ 5 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ].

From an educational perspective, learning style preferences are understood as the various ways of overcoming, planning and resolving the demands of learning. There are four learning styles based on the preferences of the individual: the activist style based on direct experience, the reflector style based on observation and data collection, the theorist style based on abstract conceptualization and conclusion formation and the pragmatist style based on active experimentation and a search for practical applications [ 26 ]. In relation to learning methodologies, two types are usually differentiated, traditional learning, usually more common in education, whose methodology is expository, individualistic and competitive, and cooperative learning, which is characteristically more autonomous, social and dialectical. García-Ruiz and González Fernández [ 27 ] noted that the cooperative learning methodology was more positive for students than the traditional approach, since their learning was greater and of better quality. Cooperative learning methodologies usually influence the degree of academic satisfaction [ 5 , 28 ]. In turn, the greater the satisfaction with the academic environment in general (contents of university subjects, types of assessments used, methodologies applied to learning, teaching / learning styles, etc.), the larger the psychological well-being perceived by university students [ 22 ].

Under the umbrella of educational resources, social skills are the ability to adequately manage interpersonal relationships with the environment and to correctly understand, control and adjust interpersonal strategies. Social skills are measured by the overall social competence of the individual and by the inter- and intra-personal strategies used [ 29 ]. These skills appear to be related to academic performance in the university environment [ 30 ]. Positive social relationships have been shown to be associated with psychological well-being [ 31 ]. In addition, university social responsibility has been studied from the perspective of the organization, understanding that it should meet the expectations of stakeholders such as current and/or future students [ 32 ]. However, the importance of the individual perspective of the students’ values should be emphasized [ 33 ].

On the positive side of the psychological continuum, emotional intelligence interconnects emotions with reason, or in other words, emotions influence our thoughts, just as our cognitive processes influence our emotional states [ 34 ]. The concept of emotional intelligence is defined as the cognitive abilities that can be measured through tasks involving the processing of emotional information. This has been developed at a theoretical and empirical level, to demonstrate its predictive ability in different areas of daily life [ 35 , 36 ]. The latest research on emotional intelligence highlights its role in the ability of individuals to adapt to daily life environments and is linked to well-being [ 36 , 37 , 38 , 39 ]. In the tertiary context, the implication of high emotional intelligence in relation to academic performance in university students has been studied, emphasizing the role of emotional skills [ 24 ]. Some authors have highlighted the importance of emotional intelligence as a type of psychosocial adaptation in the university educational environment [ 38 ], it being a possible predictor of psychological well-being [ 23 ]. Several studies involving university students have examined the impact of proficient emotional intelligence skills in relation to academic performance, highlighting the key role of emotional skills [ 24 ]. This indicates the key role of emotional intelligence and its related dimensions (such as empathy) in university teaching and learning environments with students.

Empathy is the skill that allows us to know how other people are feeling, what they are thinking, understand their intentions, predict their behavior and understand their emotions [ 39 ]. Some studies on empathy have focused on analyzing it in young people, as it contributes to the enhancement of social skills and prosocial behavior [ 40 , 41 ]. The psychological well-being perceived by students appears to be strongly associated with empathy. Gustems Carnicer and Calderón [ 42 ] conducted a study with a group of university students where they found that students at high risk of psychological distress had higher scores for empathic stress and avoidance coping strategies. On the one hand, they obtained a direct correlation between psychological distress and emotional discharge, cognitive avoidance, the search for alternative rewards and resignation [ 42 ]. Recent studies have reported relationships between the emotional ability known as empathy and subjective well-being in university students [ 5 , 43 , 44 ]. Self-concept is considered a complex term because of the difficulty of differentiating it from similar terms that have even been used as synonyms, such as self-esteem [ 45 ]. Several authors refer to this as the labels that people give themselves, generally related to their physique, behavior and emotions [ 46 ]. Behavioral, affective and social functioning are explained by the perception of an individual’s experiences; therefore, one’s self-concept could be a predictor of one’s psychological well-being [ 45 , 47 ]. In a study conducted with university students in the area of self-concept within a cooperative learning structure, there was an improvement in self-concept [ 48 ]. Other studies [ 49 ] have reported positive relationships between psychological well-being and physical self-concept and self-esteem [ 22 , 49 , 50 , 51 ]. Therefore, self-concept could be included in studies as a probable factor related to university students’ psychological profiles.

On the negative side of the psychological continuum, anxiety has been erroneously considered synonymous with other concepts such as stress, fear or distress. Spielberger et al. [ 52 ] defined anxiety as an emotional reaction that is externalized through tension, apprehension, nervousness and worry, in addition to activation of the autonomous nervous system. Spielberger, Gorsuch and Lushene [ 53 ] establish two types of anxiety based on lengths of time: state and trait anxiety. For Spielberger [ 54 ], state anxiety refers to an immediate emotional state, modifiable over time, while trait anxiety is a relatively stable disposition, tendency or personality trait. Different concepts of anxiety (state and trait) need to be studied. According to Sandín and Chorot [ 55 ], anxiety implies at least three response systems (cognitive, physiological and behavioral), with their activation creating a fight or flight response, which in turn can have an effect at the psychological level [ 55 ]. The vast majority of the scientific literature suggests that approximately 50% of university students have experienced significant levels of anxiety [ 56 , 57 ]. Research focused on the university population concludes that the effects of anxiety are closely related to certain variables such as academic performance, abandoning the course and psychological and emotional well-being [ 58 , 59 ]. However, it has not been studied in conjunction with other explanatory variables of psychological well-being.

The study of the potential predictive relationship between the psychosocial factors previously described and psychological well-being in a university student sample provides a more holistic view for prospective educators, researchers and health care practitioners. Findings from this study may inform the development of new educational policies and intervention programs aimed at directly improving the psychological well-being of university students in the international context. Likewise, studies of this type could strengthen lines of research oriented towards the application of intervention programs aimed at the well-being of students and their academic performance. Conducting studies with sample groups of first-year undergraduate students from social and health areas allows a suite of baseline educational and psychosocial data measures to be collected on which intervention programs can be founded. This is beneficial in two key ways. Firstly, the objective data can be used to determine what psychosocial and educational factors need urgent attention and remediation activities put in place in courses such as social education, pedagogy or speech therapy. Secondly, follow-up data can be then collected after program planning, implementation and completion to determine its efficacy in those disciplines. The information about the possible potential relationship between psychological well-being and psychosocial factors provides a landscape overview about potential strategic changes that are needed in this higher education context over the duration of enrolment of first-year students up until they finish their degree. This evaluation is useful to improve the process of adjustment, socio-emotional adaptation to the university context and the quality of life of first-year students to better equip them with the foundation skills needed to be successful upon graduation and during the first few years of their work life. In sum, collecting baseline data from first-year students can have both short- and long-term benefits for the designer of intervention programs and for the students themselves.

1.3. Research Hypothesis

The research hypothesis of this study is as follows: psychological well-being dimensions are significantly related to a multifactorial construct composed of psycho-educational dimensions, such as educational aspects (learning style and methodology, social skills and level of social responsibility) and psychological or cognitive-affective skills (emotional intelligence, anxiety, empathy and levels of self-concept).

To investigate the possible association between psychological well-being and psychological factors among undergraduate university students.

2. Materials and Methods

2.1. design.

A cross-sectional approach using standardized self-report scales.

2.2. Participants

The initial sample consisted of 164 participants, of whom 32.3% were men and 67.7% women. The sample was taken from the first year of the undergraduate degree courses in Social Education, Pedagogy and Speech Therapy at the University of Granada, Spain. After applying the selection criteria for the present study, the final sample was 149 university students (15 students were excluded). The inclusion criteria were: a) being a full-time university student enrolled in the first year of his/her course; and b) providing informed consent to take part in the study. The exclusion criteria included: a) not completing each and every one of the questionnaires provided; b) not being a full-time student, having a recognized part-time student status and/or having requested a single assessment; and c) being a student with special educational needs. The present study protocol was approved by the Ethics Committee of the University of Granada (Granada, Spain), with the registration number: 328/CEIH/2017. The participants completed an individual informed consent form to participate in the study.

2.3. Instruments

Demographic data were collected through a self-report questionnaire. It included items asking questions about the following information: age, sex, academic program, year and semester of course. There was an evaluation of psychological well-being, learning styles, learning methodologies, social skills, social responsibility, emotional intelligence, anxiety, empathy and levels of self-concept. All the instruments used in the study were validated in Spanish language versions: they were available and were completed in Spanish.

2.3.1. Psychological Well-Being

The starting point was Ryff’s Psychological Well-Being Scale [ 1 , 22 ]. The Spanish adaptation was provided by Díaz et al. [ 3 ], who assessed six dimensions of psychological well-being: self-acceptance: as the individual’s attempt to feel good about themselves; positive relationships: understood as the capacity to love, where social relationships are stable and trustworthy; autonomy: described as self-determination, independence and personal authority; environmental mastery: involving managing the demands and opportunities of the environment to satisfy one’s own needs and capacities; personal growth: where there is an effort to develop one’s capabilities and maximize them; and purpose in life: it consists of the need to set goals and define objectives to give life meaning. The scale consists of 39 items that use a Likert-type response format, ranging from one (total disagreement) to six (total agreement). A higher score means that the person shows higher levels of well-being. The Spanish version of the instrument has adequate reliability and validity properties for the six dimensions (RMSEA = 0.07). Internal consistency coefficients for the subscales of the Spanish version for the sample of this study were as follows: self-acceptance, 0.88; positive relationships with others, 0.72; autonomy, 0.90; environmental mastery, 0.89; purpose-in-life, 0.88; and personal growth, 0.94.

2.3.2. Learning Styles and Methodologies

The Honey-Alonso Learning Styles Questionnaire [ 26 ] evaluates the psychological, affective and physiological characteristics expressed by a person when faced with a learning situation. Learning styles are divided into four dimensions: 1) active style, based on direct experience, 2) reflexive style, based on observation and data collection, 3) theoretic style, based on abstract conceptualization and conclusion formation and 4) pragmatic style, based on active experimentation and the search for practical applications. The questionnaire is composed of 80 items that use a dichotomous response format. The maximum score is 20 points for each style. The Spanish version of the instrument exhibited adequate validity properties for the 4 dimensions after factorial analysis. The active style explained 41% of total variance, the theoretic style 39.5%, the pragmatic style 40.2% and reflexive style 42.7% [ 26 ]. The reliability results obtained for the sample of this study for the styles were a Cronbach alpha of: 0.88 (active), 0.90 (reflexive), 0.88 (theoretic) and 0.76 (pragmatic). Further, also used was the questionnaire on cooperative learning and traditional learning methods [ 41 ]. This questionnaire assesses the respondent’s skill acquisition level, based on the respondents’ preference for the two learning approaches. This instrument has adequate psychometric properties of reliability and validity. The questionnaire consists of 34 items. Internal consistency coefficients of Cronbach’s alpha of 0.92 for traditional learning, and 0.89 for cooperative learning have been reported.

2.3.3. Social Skills

The social skills scale consists of 20 items, each item representing one inter- or intra-personal social skill, using a Likert scale of five response options, ranging from one (never) to five (always) [ 29 ]. This instrument has adequate psychometric properties of reliability and validity. The study of the validity of this instrument yields satisfactory results. The reliability analysis for the present study showed a Cronbach alpha coefficient of 0.93. The social responsibility questionnaire [ 60 ] evaluates the self-attribution of socially responsible behavior. The questionnaire is divided into 40 items that use a Likert scale scoring format from one (never) to five (always). The higher the score, the more frequently an individual engages in socially responsible behavior. This instrument has adequate psychometric properties of reliability and validity. The validity was verified by the inter-judge agreement method and was satisfactory [ 60 ]. A Cronbach alpha of 0.96 was obtained for this questionnaire.

2.3.4. Emotional Intelligence

The Trait Meta-Mood Scale-24 (TMMS-24) [ 61 , 62 ] emotional intelligence questionnaire was used. This questionnaire evaluates perceived emotional intelligence, understood as the ability to control feelings and emotions, to discriminate between them, and to use that ability to direct one’s own thoughts and actions. The instrument has three dimensions: emotional attention, understood as the capacity to feel and adequately express feelings; clarity, interpreted as an optimal understanding of one’s own emotional states; and repair, which alludes to the capacity for optimal control of emotional states. The questionnaire consists of 24 items rated on a Likert scale from one to five points. In terms of validity, all three factors were correlated appropriately and in the expected direction with classical criteria variables such as depression, anxiety, rumination and life satisfaction [ 61 ]. The instrument has shown a high reliability in its three dimensions: Cronbach alpha of 0.87 for emotional attention, 0.78 for clarity and 0.57 for repair.

2.3.5. Anxiety

The State-Trait Anxiety Inventory [ 63 ] was used. This inventory has been designed to evaluate two aspects of anxiety: anxiety as a state, understood as a transient emotional condition; and anxiety as a trait, attributed to a relatively stable propensity for anxiety. The questionnaire consists of 40 items that are rated using a four-point Likert response scale which depends on intensity, ranging from zero (almost never/nothing) to three (almost always/much) [ 63 ]. The Spanish version of the instrument has adequate psychometric properties of reliability and validity. The Cronbach’s alpha coefficient for the state anxiety subscale was 0.93, while for the trait anxiety subscale it was 0.88.

2.3.6. Empathy

The Test of Cognitive and Affective Empathy—TECA [ 39 ] was used. This test evaluates cognitive-affective skills related to the level of empathy. The test consists of four dimensions. Within the cognitive area are the dimensions of perspective taking (capacity for tolerance, communication and personal relationships) and emotional understanding (ability to recognize and understand emotional states, intentions and impressions of others). The affective area includes empathic stress (connection with other people’s negative emotional states) and empathic happiness (ability to share other people’s positive emotions) [ 39 ]. The test consists of 33 items that are rated on a Likert scale from one (totally disagree) to five (totally agree). High scores in each dimension indicate a higher level of empathy. The Spanish version of the instrument has adequate psychometric properties of reliability and validity [ 39 ]. Cronbach’s alpha resulted in 0.87 for the global TECA and the higher value for the four dimensions was a Cronbach alpha of 0.63.

2.3.7. Self-Concept

The AF5 Multidimensional Self-Concept Scale [ 64 ] was used. This scale is based on a model that views self-concept as a multidimensional construct organized hierarchically from a general dimension. This questionnaire evaluates five dimensions: academic/professional, social, emotional, family and physical. This instrument consists of 30 items, scored on a scale from 1 to 99 points, where 1 corresponds to total disagreement and 99 to total agreement. The higher the score, the better the self-concept. The Spanish version of the instrument has adequate psychometric properties of reliability and validity. The factor analysis satisfactorily confirmed the five theoretical dimensions, explaining 51% of the total variance [ 64 ]. The reliability of the total scale in this study using Cronbach’s alpha test was 0.86 and this was 0.90 for academic/professional, 0.50 for social, 0.82 for emotional, 0.53 for family and 0.83 for physical.

2.4. Procedure

Regarding recruitment of the sample, participation was voluntary, i.e., the consecutive recruitment of participants was performed. The questionnaires were completed by the student participants at the end of a scheduled morning class during the second semester, under the supervision of a research assistant. Once the general procedures and objectives of the study had been explained, instructions were given to complete the questionnaires in hard copy version. The students provided written consent and the confidentiality of the data obtained was assured. The questionnaires were field-tested beforehand. The average time it took participants to complete the questionnaire was two hours, split between two sessions. In each session, the participants took at least one voluntary five-minute break. The anonymity of the participants was guaranteed since the hard copy included only a number, and their personal data were preserved in a different document linking this number and their personal data. Power relationships from an ethical perspective were not present. The data were manually entered into a database.

2.5. Data Analysis

The SPSS software (version 22.0, IBM Corp, Armonk, NY, USA) was used for the statistical analysis. A descriptive analysis was performed and the normal distribution of the variables was confirmed. Student t-test and univariate analysis of variance (ANOVA) were completed to investigate the relationship between psychological well-being and sex and level of course, respectively. Pearson’s correlation coefficient was used to determine the association between psychosocial variables and each of the psychological well-being dimensions. We used multiple linear regression analysis to investigate the predictive relationship between emotional well-being as the dependent variable, and age and the psychosocial variables (learning style and methodology preferences, social skills, level of social responsibility, emotional intelligence, anxiety, empathy and levels of self-concept) as the independent variables. The regression analysis was also executed in an independent manner when differences between academic disciplines were found for any of the psychological well-being dimensions. Normality of residuals, homogeneity of variance for residuals and linearity of data were examined before completing the regression model. The data met all the assumptions required to carry out the multiple linear regression analyses. Multi-collinearity was avoided by selecting a stepwise method in the regression model. A p < 0.05 was used as the significance level in the study.

2.6. Sample Size

In a previous study completed by Atienza [ 22 ], a significant bivariate correlation of 0.298 between psychological well-being (self-acceptance dimension) and emotional intelligence (repair dimension), measured with the Ryff scale (assessing well-being) and the TMMS-24 scale (evaluating repair), was used to calculate the sample size required to detect this size effect in the sample. This was carried out using the G*power software (version 3.1, Institut für Experimentelle Psychologie, Düsseldorf, Germany). This calculation demonstrated that a sample size of 140 university students was needed to provide a confidence interval of 95%, with a power of 95%, assuming a bilateral significance level (α) of 0.05. To be able to handle possible missing data, any participants dropping out or badly completed instruments, the recruited sample should be increased by around 5%. As a result, the final sample should include at least 147 participants.

3.1. Description of the Sample

The total sample consisted of 149 students enrolled on the Social Education ( n = 52), Pedagogy ( n = 56) and Speech Therapy ( n = 41) courses at the University of Granada, of whom 67.7% were women and 32.3% men, with an average age of 21.59 ( SD = 4.64) years. One hundred percent of the sample was recruited from the first year of the three courses. The descriptive statistics of the independent and independent variables of the sample are reported in Table 1 .

Descriptive results (range, mean, SD and quartile scores) of psychological well-being, learning style and methodology, social skills, social responsibility, emotional intelligence, anxiety, empathy and levels of self-concept in university students.

SD = standard deviation; Q = quartile scores.

3.2. Confounding Variables for Psychological Well-Being

No statistically significant differences between sexes in relation to psychological well-being were found since there were no differences between male and female participants in terms of self-acceptance ( t = 0.285, p = 0.776), positive relations with others ( t = -0.971, p = 0.333), autonomy ( t = 0.929, p = 0.354), environmental mastery ( t = 0.067, p = 0.947), purpose-in-life ( t = −1.344, p = 0.181) and personal growth ( t = −0.955, p = 0.343). Among the three student course groups, statistically significant differences in the scores for the psychological well-being dimensions of environmental mastery (F(2,101) = 3.682, p = 0.028) and purpose-in-life (F(2,101) = 4.631, p = 0.011) (ANOVA) were found.

Specifically, the post-hoc analysis showed differences between the student participants enrolled on the Pedagogy and Speech Therapy academic courses for environmental mastery ( p = 0.037; Pedagogy M ± SD = 12.90 ± 0.62; Speech Therapy M ± SD = 10.56 ± 0.68) and purpose-in-life ( p = 0.011; Pedagogy M ± SD = 21.19 ± 4.33; Speech Therapy M ± SD = 18.17 ± 5.69).

3.3. The Correlation between the Psychological Well-Being Dimensions and Psychosocial Factors

Bivariate correlation analyses have shown direct and inverse relationships between the psychological well-being dimensions and the cooperative learning methodology, the empathy dimension of emotional understanding, social skills and all dimensions of the levels of self-concept, emotional intelligence and levels of anxiety in university students. These results are shown in Table 2 .

Correlations between psychological well-being and age, sex, learning style and methodology, level of social responsibility, empathy, anxiety, social skills, level of self-concept and emotional intelligence in university students.

* p < 0.05; ** p < 0.001.

The dependent variables (each dimension on the Ryff’s Psychological Well-Being Scale) exhibited a normal distribution. After testing the normality of the residuals in the regressions, it was confirmed that the observed residuals were normally distributed. The independence of data for all regressions performed for each dimension of well-being was confirmed. There was a linear relationship between the independent variables and the dependent variables. Homogeneity of the residuals’ variance was not violated and the data met the assumption of homoscedasticity.

3.4. Influence of Psychosocial Factors on Psychological Well-Being in University Students

Multivariate regression analysis showed that the cooperative learning methodology, the clarity dimension of emotional intelligence, state anxiety, the emotional understanding dimension of empathy and physical and family self-concept were significantly related to the dependent variable, predicting 58.6% of the total variance (R 2 = 0.586, F(6,99) = 23.335, p < 0.001) of levels of self-acceptance in university students. The active learning style, emotional understanding and empathic stress, academic/professional self-concept, social self-concept and family self-concept were significantly related to the dependent variable, predicting 52% of the total variance (R 2 = 0.520, F(6,99) = 17.874, p < 0.001) of levels of positive relationships in this sample. Social skills, the emotional attention and clarity dimensions of emotional intelligence and emotional self-concept were significantly related to the dependent variable, predicting 31% of the total variance (R 2 = 0.313, F(4,101) = 11.525, p < 0.001) of levels of autonomy. Global emotional intelligence, state anxiety, emotional understanding and family self-concept were significantly related to the dependent variable, predicting 48.9% of the total variance (R 2 = 0.489, F(4,101) = 24.139, p < 0.001) of levels of environmental mastery. The emotional attention dimension of emotional intelligence, state anxiety, the emotional understanding dimension of empathy and academic/professional self-concept were significantly related to the dependent variable, predicting 35.4% of the total variance (R 2 = 0.354, F(4,101) = 13.838, p < 0.001) of levels of personal growth. Global emotional intelligence, state anxiety, empathic happiness and family self-concept were significantly related to the dependent variable, predicting 43.9% of the total variance (R 2 = 0.439, F(4,101) = 19.786, p < 0.001) of levels of purpose-in-life. There was no collinearity between the variables included in the regression model.

Figure 1 depicts the relationship between the psychological well-being dimensions and psychosocial factors. Table 3 shows the final multiple regression models of the psychological well-being dimensions after the selection of independent variables.

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Directed acyclic graph of the relationship between the psychological well-being dimensions and psychosocial factors. Source: created with DAGitty.

Influence of psychosocial factors on psychological well-being in university students.

R 2 , regression coefficient of determination; B, regression coefficient; CI , confidence interval; β , adjusted coefficient from multiple linear regression analysis; SE coefficient standard error.

The multivariate linear regression analysis involving the students on the Pedagogy program indicated that state anxiety, family self-concept, traditional learning methodologies and empathy (emotional understanding) were significantly related to environmental mastery, predicting 54% of its total variance (R 2 = 0.540, F = 9.990, p < 0.001). For students on the Speech Therapy program, state anxiety and emotional intelligence (emotional attention) were significant predictors of the psychological well-being dimension (R 2 = 0.593, F = 21.110, p < 0.001), accounting for 59.3% of its total variance. For student participants enrolled on the Pedagogy course, the results demonstrated that state anxiety, social responsibility and theoretic learning style were significantly related to purpose-in-life, predicting 49% of its total variance (R 2 = 0.492, F = 11.306, p < 0.001). In the Speech Therapy program, the perspective taking, empathic stress and empathic happiness empathy dimensions predicted 57.3% of the total variance of this dimension (R 2 = 0.573, F = 12.528, p < 0.001). In Table 4 , the independent multiple regression models for the psychological well-being dimensions of environmental mastery and purpose-in-life among the students of the Pedagogy and Speech Therapy courses are shown.

Influence of psychosocial factors on psychological well-being in university students according to the academic program—Pedagogy or Speech Therapy.

4. Discussion

This study investigated the possible association between self-reported levels of psychological well-being and educational aspects (learning style and methodology, social skills and level of social responsibility) and psychological or cognitive-affective skills (emotional intelligence, anxiety, empathy and levels of self-concept). The final regression models indicated that the psychological well-being dimension of self-acceptance appears to be related to the cooperative learning methodology, the clarity dimension of emotional intelligence, state anxiety, the emotional understanding dimension of empathy and physical and family self-concept. The positive relationships dimension appeared to be related to the active learning style, the emotional understanding and empathic stress dimensions of empathy, academic/professional self-concept, social self-concept and family self-concept. Autonomy was associated with the emotional attention and clarity dimensions of emotional intelligence, emotional self-concept and social skills. Environmental mastery was related to global emotional intelligence, state anxiety, the emotional understanding dimension of empathy and family self-concept. Personal growth was associated with the emotional attention dimension of emotional intelligence, state anxiety, the emotional understanding dimension of empathy and academic/professional self-concept. Finally, purpose-in-life was related to global emotional intelligence, state anxiety, the empathic happiness dimension of empathy and family self-concept.

4.1. Learning Styles

Consistent with the emotional skills model [ 5 , 23 , 34 ], the results of this study demonstrate the importance of educational and socio-emotional constructs on psychological well-being. Nevertheless, the current study focuses on a particular group of university students (Social Education, Pedagogy and Speech Therapy) that could be more sensitized than others to the study variables due to the nature of these disciplines in themselves. These disciplines usually give help and service to people with disabilities. Specifically, the present study demonstrates that Pedagogy and Speech Therapy students exhibited differences for the two psychological well-being dimensions of environmental mastery and purpose-in-life. Pedagogy students demonstrated that state anxiety, family self-concept, traditional learning methodologies and empathy (emotional understanding) were significantly related to environmental mastery, and that state anxiety, social responsibility and theoretic learning style predicted purpose-in-life. For students enrolled in the Speech Therapy program, state anxiety and emotional intelligence (emotional attention) predicted the environmental mastery dimension, and the empathy dimensions of perspective taking, empathic stress and empathic happiness predicted purpose-in-life.

Within the two learning methodology options evaluated, a direct and significant relationship has been found between the cooperative learning methodology and the psychological well-being dimensions of self-acceptance, environmental mastery, personal growth and purpose-in-life. This indicates that a more cooperative learning methodology is more positive for students than the traditional one, since their learning could be greater and improved in quality [ 65 , 66 ]. Therefore, students who prefer this methodology will have a higher probability of showing higher psychological well-being. However, the results have shown that there is no significant relationship between learning style and psychological well-being in the population studied. Generally, while there is previous scientific literature including this educational variable, as far as we know, no conclusive results have been obtained about student preferences for one style or another, since this preference seems to vary with time and experience [ 67 , 68 ]. Another study found that the most effective active methodologies according to students were work and group dynamics [ 69 ]. Online, the higher the level of satisfaction and emotional well-being, the better the academic performance of students seems to be [ 70 ].

4.2. Social Skills

Regarding social skills, a significant direct relationship with all psychological well-being dimensions has also been observed. Therefore, the higher the level of social skills in these students, the higher the level of general psychological well-being. These results are consistent with those reported by Recabarren [ 71 ], Vasilenko et al. [ 31 ], Souri and Hasanirad [ 72 ] and Freire et al. [ 73 ]. These authors concluded that a larger number of positive relationships in one’s own environment or context led to better coping strategies and more resilience or capacity to adapt. This strengthening of strategies is likely to produce higher levels of psychological well-being for students because they achieve a higher level of support and optimism. In relation to social responsibility, no significant association with psychological well-being has been found [ 72 , 73 ]. The reason for this could be that while social responsibility is based on positive values such as altruism, more individualistic and selfish behaviors may prevail in the current world. This construct could be affecting the psychological well-being of university students in Spain [ 33 ]. In some recent studies [ 74 ], social responsibility has been shown to be correlated directly with life satisfaction for students during university years. The higher the social skills, the higher the level of emotional intelligence [ 13 , 15 ], which is associated with better psychological well-being [ 23 ].

4.3. Emotional Intelligence

4.4. Anxiety

If anxiety levels are considered, both of these (state and trait) showed a significant but inverse relationship with the psychological well-being dimensions. State anxiety shows a relationship with all the well-being dimensions, although the highest significant association was observed with the environmental mastery dimension. This can be interpreted as meaning that the greater the state of anxiety that students feel at the present moment, the lower their levels of general psychological well-being in all its dimensions. In contrast, trait anxiety, characterized by a more stable construct over time, was only inversely related to the positive relationships dimension. It follows that students who have the personality trait of anxiety will have greater difficulties in establishing positive relationships with their environment. It can be concluded that, in keeping with the studies of Cooke et al. [ 4 ], Recabarren [ 71 ] and Stallman [ 6 ], higher levels of anxiety occur in the university stage and psychological well-being declines worryingly. Zuñiga [ 51 ] pointed out that state anxiety and trait anxiety seem to be correlated with all psychological well-being dimensions, except the personal growth dimension, applying the same instruments to assess anxiety and well-being in university students.

4.5. Empathy

Within the empathy dimensions, the emotional understanding dimension has been shown to be directly related to all psychological well-being dimensions, although the highest significant correlation has been obtained with the personal growth dimension. Therefore, students who are most able to understand their emotions and the emotions of others seem to show higher levels of overall psychological well-being. These results are also similar to those found by Cicognani et al. [ 78 ], where they show the importance of a sense of community, participation and social understanding for psychological well-being. In line with this, Gustems Carnicer and Calderón [ 42 ] found that students at high risk of psychological distress were more likely to show empathic stress and avoidance coping strategies. As in our study, other authors such as Serrano and Andreu [ 43 ] and Cañero et al. [ 5 ] showed, in the Spanish university context, that empathy was a predictor of subjective well-being in university students. Likewise, Malhotra and Kaur [ 44 ] also found a relationship between emotional empathy and perceived well-being. Sánchez-López et al. [ 79 ] found no significant correlation between psychological well-being and empathy in a study they reported.

4.6. Self-Concept

4.7. Limitations

Participants took part in the study on a voluntary basis and were not randomly selected. This research only used self-reported measures (i.e., self-rating scales) to evaluate psychological well-being and the set of constructs from the psycho-educational approach which may have been subject to recall bias. As a result, respondent bias may have been present due to social desirability. Additionally, participants may have answered items on the social responsibility questionnaire and the TECA in a socially desirable manner. Hence, objective evaluations would be more appropriate to evaluate the constructs examined in this study. Students were recruited from a single geographical location, so the generalizability of the results may be limited. The nature of the courses taken by the students in the study sample (Degree in Social Education, Pedagogy and Speech Therapy) may have sensitized them (had an influence) to the study variables response, therefore impacting on the results. Likewise, all of the student participants were recruited from the first year of the three courses which may have impacted their answers on the self-report questionnaire. For this reason, the interpretation of the findings for other similar populations of university students should be approached with caution.

4.8. Future Research

Future studies should evaluate the impact of educational initiatives taking into account the psychological well-being of university students and their learning styles, social skills, emotional intelligence, anxiety, empathy and self-concept and the emotional dimension, whether positive (emotional intelligence) or negative (anxiety), in university students as a group. However, since the study was conducted at one university site, future research in this topic should be made multi-center by including student data from several educational institutions. Additionally, multi-level analysis could be performed by taking into consideration specific needs and demands by geographical location or sociodemographic characteristic. In future research, it is important to test the role of possible moderators other than age, sex or academic discipline. A longitudinal study should be designed to evaluate the change in the variables investigated in this research as participants get older.

4.9. Implications for Education

Some possible educational implications arise from the current findings which may help to improve the learning process and its quality for students. The results can be used to design initiatives that increase the general perception of psychological well-being, prevent stress in the educational setting and lead to better academic performance.

The data could be used to implement academic development and an effective approach to the educational process and provide counselling and support services with strategies that will enhance students’ management of emotions and their ability to cope with certain conflict situations.

5. Conclusions

Among the psychological and cognitive dimensions selected, emotional intelligence, empathy, social skills and self-concept were positively correlated with all psychological well-being dimensions, whereas for learning methodologies, only the cooperative one was positively correlated with most of the psychological well-being dimensions. In contrast, anxiety was inversely correlated with the perception of well-being in university students, negatively influencing it. Therefore, it is necessary to look at this issue in more depth, providing more comments and observations on these results.

Acknowledgments

The authors would like to thank the students who participated in this study, as well as the university authorities for their help in recruiting the sample.

Author Contributions

F.M.R. conceived and designed the study, recruited the participants, and contributed to the manuscript writing and data analysis. I.E.L. and T.B. contributed to the bibliographic review and the manuscript writing. J.P.M. conceived and designed the study, contributed to the bibliographic review, manuscript writing and data analysis. All authors revised the manuscript critically and approved the final version of the manuscript.

This research received no external funding.

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Psychological well-being, characterized by feelings, cognitions, and strategies that are associated with positive functioning (including hedonic and eudaimonic well-being), has been linked with better physical health and greater longevity. Importantly, psychological well-being can be strengthened with interventions, providing a strategy for improving population health. But are the effects of well-being interventions meaningful, durable, and scalable enough to improve health at a population-level? To assess this possibility, a cross-disciplinary group of scholars convened to review current knowledge and develop a research agenda. Here we summarize and build on the key insights from this convening, which were: (1) existing interventions should continue to be adapted to achieve a large-enough effect to result in downstream improvements in psychological functioning and health, (2) research should determine the durability of interventions needed to drive population-level and lasting changes, (3) a shift from individual-level care and treatment to a public-health model of population-level prevention is needed and will require new infrastructure that can deliver interventions at scale, (4) interventions should be accessible and effective in racially, ethnically, and geographically diverse samples. A discussion examining the key future research questions follows.

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Numerous studies have documented a rise in deaths of despair, deaths arising from suicide, drug overdose, and alcoholism (Case & Deaton, 2015 ). Despite the recognition of the critical interplay between mental and physical health, much research has focused on risk factors and deficits. Recent work, however, suggests the enormous value of examining positive health assets as well (Kubzansky et al., 2018 ; VanderWeele et al., 2020 ). Psychological well-being, characterized by feelings, cognitions, and strategies that are associated with positive functioning (including hedonic and eudaimonic well-being), is important in its own right, but accumulating evidence suggests it also uniquely contributes to better physical health and longer lives (Kubzansky et al., 2018 ; Levine et al., 2021 ; Ryff, 2014 ; Seligman, 2008 ; Steptoe, 2019 ; VanderWeele, 2017 ). Footnote 1 For example, a 2017 meta-analysis of 76 prospective studies found higher levels of optimism, sense of purpose in life, positive affect, and life satisfaction are consistently associated with reduced mortality risk (Martín-María et al., 2017 ). An emerging literature has identified potential underlying mechanisms including reductions in harmful health behaviors (e.g., cigarette smoking, physical inactivity, poor diet) and biological processes (e.g., elevated inflammation) through which psychological well-being leads to health benefits (J. K. Boehm et al., 2018 ; Feig et al., 2022 ; Kim et al., 2019 ; Kubzansky et al., 2018 ; Ryff, 2014 ; Seligman, 2008 ; VanderWeele, 2017 ).

Because various dimensions of psychological well-being can be modified (Carr et al., 2021 ), investigators have proposed interventions targeting psychological well-being as one strategy for improving physical health in both the general population and individuals with medical conditions (van Agteren et al., 2021 ). However, such proposals rely on the assumption that these factors are not only modifiable, but also meaningful, durable, and scalable. To explore the exciting possibility that psychological well-being interventions can also contribute to improving population health, the Lee Kum Sheung Center for Health and Happiness at the Harvard T.H. Chan School of Public Health hosted a 2-day cross-disciplinary workshop, “Interventions to Modify Psychological Well-Being: What Works, What Doesn’t Work, and an Agenda for Future Research.”

This workshop builds on prior work in the Science of Behavior Change (SOBC). Starting in 2009, researchers in the SOBC network developed an understanding of how to create and sustain effective change in adaptive health behaviors such as diet, exercise, and medication adherence (Nielsen et al., 2018 ). The SOBC approach follows four steps: (1) identify the hypothesized mechanism underlying behavior change, (2) measure it accurately and precisely, (3) influence or intervene to impact the mechanism, and (4) evaluate if the intervention-induced changes in the mechanism translates into behavior change. Our workshop focused on psychological well-being as one mechanism that may be harnessed to drive behavior change, as well as to trigger other biobehavioral changes that lead to improved physical health. In addition, we noted that the SOBC principles outlined for changing behaviors can be applied to changing psychological well-being itself. Our overarching aim was to create a research agenda for developing and evaluating scalable psychological well-being interventions that are sufficiently powerful to improve physical health at the population level.

The workshop began with a recognition that subjective interpretations of well-being have generally been considered in the context of hedonic (i.e., involving pleasure and happiness) or eudaimonic (i.e., involving optimal psychological functioning and self-realization) well-being (Keyes et al., 2002 ). Workshop attendees noted that psychological well-being is separate from states of psychological distress and related disorders (e.g., absence of anxiety does not necessarily equate to high levels of joy and meaning). Thus, interventions designed to enhance psychological well-being need to go beyond simply reducing symptoms of psychological distress, and evaluation of these interventions should reflect this understanding; additionally, researchers should separate boosts in psychological well-being from decreases in distress by including and measuring both outcomes carefully. Attendees presented examples of interventions with documented success in modifying psychological well-being and then considered a set of related issues, including the magnitude of effect sizes from well-being interventions and whether these reflect changes in psychological well-being that are large enough to influence downstream health behaviors and processes, the scaling of interventions, barriers to developing durable and scalable interventions, and strategies that might overcome these barriers. Below, we summarize insights from the convening.

Summary of the Workshop

The workshop included presentations around select interventions with demonstrated effects on psychological well-being. For example, Eric Loucks presented his work on mindfulness-based interventions, oriented toward the question of what allows people to make shifts in life to promote psychological and physical well-being (Loucks et al., 2019 , 2022 ). Specifically, he described mindfulness-based stress reduction (MBSR) techniques tested in clinical trials, which showed that MBSR leads to improved psychological well-being (de Vibe et al., 2017 ) and physical health as demonstrated in more recent studies among medical populations (Loucks et al., 2019 ). Richard Davidson described findings demonstrating that mindfulness-based interventions can affect neuroplasticity and epigenetics and suggested these biological alterations can elucidate whether and how MBSR leads to improved physical health (Chaix et al., 2020 ; Davidson & McEwen, 2012 ). Further, based on epigenetic findings, he raised the intriguing possibility of intergenerational transmission of well-being, which could be viewed as a particularly durable intervention effect.

Jeff Huffman, Judy Moskowitz, and Sonja Lyubomirsky each discussed their research on positive psychological interventions (PPIs)—interventions that explicitly target psychological well-being (Fritz & Lyubomirsky, 2018 ; Lyubomirsky & Layous, 2013 ). Meta-analyses of PPIs demonstrate these interventions have consistent, albeit relatively modest, effects on psychological well-being (Carr et al., 2021 ; Koydemir et al., 2021 ; van Agteren et al., 2021 ). However, evidence that PPIs may ultimately influence physical health outcomes is more limited, likely due to time and budget constraints that restrict studies to relatively brief follow-up time and smaller sample sizes which can make it more difficult to detect effects on many more distal physical health outcomes.

Katey Warran discussed research on the role of arts-based interventions in improving health and well-being. Drawing on the 2019 WHO Health Evidence Network synthesis report, Warran defined arts activities as including performing arts activities, visual arts participation, literature engagement, digital arts activities, and cultural engagement (e.g., going to museums and galleries). She characterized the evidence regarding the benefits of the arts as substantial and described numerous observational studies that have demonstrated an arts-health association. To illustrate, she described a study that showed engaging in arts activities was associated with reduced depression (Bone et al., 2022 ). She further noted that arts activities are considered complex interventions because they combine multiple components to initiate non-linear mechanisms of action that influence mental and physical health outcomes (Fancourt et al., 2021 ; Warran et al., 2022 ).

Tyler VanderWeele provided an overview of forgiveness interventions (Wade & Tittler, 2019 ). VanderWeele modified existing interventions for large-scale application (i.e., distilling established protocols into a 2–3-h workbook that can be administered on-line or in-person) and to global audiences (e.g., Indonesia or South Africa). Current research suggests these interventions lead to increased forgiveness and hope, as well as reduced depression and anxiety (VanderWeele, 2018 ; Wade & Tittler, 2019 ). VanderWeele further noted that forgiveness interventions may also lead to higher community levels of forgiveness, which could contribute to healing community and political divides. However, research has not yet established whether these interventions are sufficiently potent to induce subsequent changes in physical health. Given the potential ease of disseminating forgiveness workbooks, such interventions may have an important role in promoting population health (VanderWeele, 2018 ).

Noting that numerous effective interventions already exist, Stephen Schueller expressed concern that translation into widespread dissemination has been slow. He suggested progress will require moving beyond repeated pilot and efficacy trials toward greater investment in implementation. Such efforts should include identifying facilitators and barriers to successful implementation across contexts and then using this information to inform the design and evaluation of effective implementation strategies (Bauer & Kirchner, 2020 ). The research agenda for PPIs should consider stage of evidence to determine unanswered questions in implementation (Lane-Fall et al., 2019 ) and use appropriate study designs to explore these questions (Wolfenden et al., 2021 ). Schueller further noted that mode of delivery is important when implementing scaled-up versions of interventions. Promising approaches include digital delivery, single-session interventions, and micro-interventions (i.e., highly focused low-burden brief interventions delivered in the context of a person’s daily life; Baumel et al., 2020 ; Hirshberg et al., 2022 ).

Based on the workshop discussions, we see several exciting directions for research to provide greater insight into whether and how we might create scalable interventions to modify psychological well-being in ways sufficiently powerful to influence downstream health outcomes. In the following section, we highlight four key topics, then discuss additional substantive issues that emerged, and conclude with thoughts on the future.

1) What Are Meaningful Effect Sizes?

Many existing interventions rely on either “light-touch” brief activities (e.g., writing a gratitude journal) or more intensive delivery methods (e.g., positive psychotherapy, meditation training; J. Boehm et al., 2012 ). Whereas “light-touch” interventions are more scalable, it remains unclear if they have sufficiently durable or potent effects to catalyze meaningful improvements in downstream health endpoints. A recent systematic review and meta-analysis of interventions designed to improve psychological well-being considered not only PPIs developed within the field of positive psychology but also non-PPIs such as mindfulness meditation and more traditional therapeutic approaches (van Agteren et al., 2021 ). The review found psychological well-being can be enhanced across varied interventions and effects differed according to target population (e.g., general population versus physically ill patients) and, most notably, intervention intensity (e.g., multi-component versus single element interventions). Less well studied is how large an increase in psychological well-being is needed to observe meaningful downstream effects on physical health, and this likely depends on which physical health outcomes are considered. Moreover, attendees suggested large samples may be needed to detect effects in randomized trials, particularly if intervention effects on psychological well-being and subsequent effects on physical health are both modest.

Important to note is that whereas meta-analyses show promising average effect sizes, effects are also highly heterogeneous. Understanding the heterogeneity of effects (e.g., where and with whom each intervention works) is critical for assessing whether any given effect appears small because interventions were incorrectly targeted to some subgroups or did not fully account for the context in which they occur. Without understanding this heterogeneity, it is difficult to appropriately power studies.

Ultimately, workshop attendees noted that even if changes in psychological well-being lead only to small changes in downstream behaviors and physical health, such effects are still valuable—especially if the interventions are easy to deploy, scale, and adopt at the population level. Given most health outcomes are multiply determined, any one variable likely contributes only modestly. For example, associations between aspirin and prevention of heart attacks ( r = 0.03) or cardiac patient education and exercise ( r = 0.09) appear small (Götz et al., 2022 ). However, these interventions are important because small effect sizes translate into meaningful changes at the population level under particular circumstances (e.g., if many small effects act in concert to create larger substantive composite effects) or as they accumulate across the lifespan (Götz et al., 2022 ).

The impact of PPIs also differs depending on context. Investigators must carefully consider the population under study and the social environment in which interventions are implemented (Bryan et al., 2021 ). A new “moderation as mediation” framework illustrates how contextual factors can act like a switch that turns mechanistic pathways on or off. For example, one study examined effects of a growth mindset intervention (i.e., bolstering beliefs that abilities are learnable and can be improved through effort) delivered to students on their math performance. Investigators first evaluated teachers’ mindsets. If a teacher believed that abilities are inherently stable and unchangeable, then the effect of growth mindset interventions on students’ math GPAs was minimal. However, when teachers themselves had a growth mindset, then the intervention successfully enhanced students’ performance (Yeager et al., 2022 ).

2) How Durable Are Effects of Psychological Well-Being Interventions?

If psychological well-being influences physical health, it is likely because relevant psychological states are enduring and thereby lead to recurring effects on health-relevant habits and biological processes. Interventions seeking to change psychological well-being sufficiently to impact downstream biobehavioral processes related to physical health will need to produce sustained effects. However, durability of effects is less well-understood (Miller et al., 2017 ). In one of the largest meta-analyses of PPIs, most studies tracked outcomes for < 6 months and none for > 12 months (Carr et al., 2021 ). Thus, it remains unclear if effects of PPIs are sustained over periods long enough to lead to changes in physical health. Moreover, studies including longer follow-up time will need to consider carefully how to capture the durability of intervention effects, including deciding how and at what intervals investigators should measure changes in psychological well-being, as well as how to retain study participants over longer periods.

Several substantive issues are also relevant. First, investigators should evaluate whether interventions create a habit (e.g., teach skills that become habitual to repeatedly boost effects over time) or crystallize a new way of thinking (e.g., “wise interventions” that target psychological processes contributing to core underlying thought processes and recursive dynamics that compound over time; Cohen et al., 2017 ; Miller et al., 2017 ; Walton & Wilson, 2018 ).

Second, developmental theory suggests there are points in the life course when exposures to certain risk factors are particularly harmful (i.e., sensitive periods like before a major life transition), and also when health interventions may be most effective (Bailey et al., 2020 ; Berkman, 2009 ; Meyer et al., 2012 ). Scholars should seek to identify these optimal points or “signature moments.” Of note, optimal timing for delivering interventions may also depend on which facet of psychological well-being is targeted. For example, purpose in life interventions might be particularly helpful during identity development, “midlife crises,” and retirement—destabilizing periods due to the many substantial changes in life patterns; at such times, developing or re-discovering a sense of purpose may mitigate potential derailment.

Third, if psychological well-being interventions need repeated administration for durable effects, it will be important to embed these interventions into systems and social practices. For example, clear evidence that psychological well-being interventions enhance health and reduce healthcare costs motivate healthcare systems to adopt and maintain these interventions. To facilitate development of sustainable financing models we might encourage creating healthcare system classification codes that facilitate tracking and reimbursement of evidence-based interventions.

3) Delivery and Scalability of Psychological Well-Being Interventions

Psychological well-being interventions that demonstrate the strongest effects are often complex (involving multiple components), time-intensive to deliver, and require in-person attendance. Moreover, following a biomedical model, many psychological well-being interventions target individuals who are either high-risk or already have disease. A key activity for future work following a public health model of prevention is to determine if existing labor-intensive interventions developed in medically high-risk populations can be adapted for use in the general population and delivered at a manageable cost. Investigators will also want to consider whether existing “light-touch” interventions, which are easier to deliver on a larger scale but often demonstrate smaller (and perhaps less durable) effects on psychological well-being, can be modified to enhance both size and durability of effects. Some work suggests rigorously optimized simpler interventions can have more durable effects, including findings from studies of single session interventions (Schleider & Weisz, 2016 ). Attendees also noted that “light-touch” interventions targeting domains like a sense of belonging and academic performance have shown large and durable effects (e.g., lasting 6–11 years; Brady et al., 2020 ; Goyer et al., 2017 ). Important next steps include linking these interventions to physical health.

One possible concern with shifting intervention work to the general population is that healthy individuals may be less likely to participate as they are not motivated by a specific illness or problem that needs attention. By anticipating this potential concern ahead of time, those who deliver the intervention should carefully consider how to present these interventions to the public. Further, when conducting interventions in healthy populations, the metric of health would not be survival or improvement in disease status, but rather delayed onset of disease, a more difficult outcome to capture, especially in the short term.

These concerns notwithstanding, workshop attendees noted the COVID-19 pandemic spurred development of innovative methods of synchronous and asynchronous intervention delivery that can now be leveraged to advance the field. Discussions around scalability often focus on the role of technology (e.g., smart watches, app-based delivery), and the COVID-19 pandemic drove wider adoption of these methods. Examples from behavioral health can inform thinking on how to scale PPIs. For example, a successful treatment for individuals with substance use disorders relied on administering cognitive behavioral therapy. While effective, delivering the intervention widely was not feasible due to high cost. A computerized version of the intervention was developed, and subsequent evaluations found it was equally as effective as in-person delivery (Carroll et al., 2009 , 2014 ). Other exciting possibilities for digital interventions were also identified. For example, workshop attendees noted micro-interventions that sprinkle 30–90 s doses of intervention content throughout the day via mobile devices should be further evaluated.

Our discussion also highlighted potential pitfalls of these intervention dissemination methods. Barriers to quitting digitally delivered interventions are lower, resulting in higher drop-out. A recent review of mental health app usage by people in the real world observed that across 93 mental health apps, median retention rate at 15 days was 3.9% (Baumel et al., 2019 ). Newer methods of enhancing retention have somewhat improved these numbers. For example, one study of a game implementing mental health therapy in real-world conditions (7,782 users) reported 10% retention at 15 days which was a doubling of the previously reported retention rates. Despite this improvement, it is still the case that 90% of those who started therapy were not retained (Ferguson et al., 2021 ). Moreover, participants who drop out are often those who are most in need of the intervention or who are the least motivated, so failure to retain them can produce a biased understanding of efficacy. Digital formats may also render it more difficult to deploy features demonstrated to promote continued engagement in interventions, such as developing relationships with participants. Finally, some interventions may not translate easily to digital formats resulting in a loss of their potency.

Workshop attendees reiterated the value of creating a “science of engagement” to help identify not only different profiles of intervention participants (digital or otherwise) but also an accounting of active ingredients and optimal dosages that work best for different individuals. Investigators should consider when and how interventions can incorporate elements of fun to promote retention and continued engagement. For all modes of intervention, interpersonal connection or “human touch” is likely critical for promoting and maintaining engagement. Investigators should consider how they might embed interventions into the existing infrastructure of relationships individuals already have. For example, studies could capitalize on existing social relationships to enhance social support, collaboration, or competition (e.g., Patel et al., 2021 ). Additionally, in the realm of healthcare, researchers might work with general practitioners, nurses, or social workers who could then provide their clients with strategies to improve psychological well-being (see Kubzansky et al., 2018 ). This type of engagement could lower participation barriers for people who are less digitally connected.

4) Do Psychological Well-Being Interventions Work in Diverse Populations and Settings?

Tailoring and contextualizing interventions for minoritized and underserved populations are critical. The same intervention may work differently depending on gender, race, ethnicity, and other characteristics of the population. Interventions are less often tested in disadvantaged individuals including those with severe financial constraints, limited access to technology, or extreme time scarcity. Interventions developed for individuals who are already ill may need substantial adaptation (or simply not apply) for use with healthy individuals for whom the ultimate goal is to prevent illness. Interventions can backfire when administered in settings and populations for which assigned activities have poor “fit.” For example, gratitude interventions can be problematic when delivered to members of cultures where gratitude is experienced as indebtedness or guilt, or to severely depressed individuals, for whom expressions of gratitude can increase feelings of being a burden on others (Fritz & Lyubomirsky, 2018 ).

Prior to implementing any intervention on a large scale, investigators should gain as much insight as possible into the populations targeted for intervention. One strategy for doing this might be to conduct pre-implementation focus groups with members of the community and other key stakeholders; these can provide critical information regarding fit of a planned intervention with the target population. Administrative data (i.e., zipcode, neighborhood characteristics) and more detailed individual-level data may also be needed to design interventions that are appropriate and relevant. Efforts to obtain this kind of information are particularly important when developing interventions for traditionally minoritized or underserved groups for whom fewer interventions have been developed, and whose needs are less well understood by most investigators. To ensure interventions are both effective and sustainable, investigators will need to work directly with these groups through an iterative process to create protocols and principles that most directly serve the group’s needs (Hernandez et al., 2016 , 2018 ; Lau, 2006 ).

Investigators will also need to move away from convenience samples and use varied strategies to increase the likelihood that individuals in specific populations participate. A key approach will be to develop novel ways to integrate interventions into everyday contexts and develop partnerships with institutions like schools, workplaces, or healthcare settings. Other possibilities include implementing interventions through partnerships with health insurance companies or other organizations (e.g., older adult advocacy groups like AARP). Such partnerships may increase the sustainability of interventions for continued implementation in the real world. Several workshop attendees provided examples of successful partnerships. For example, effective interventions developed and tested in the Army (e.g., Army Wellness Centers) have had broad reach across soldiers, their family members, retirees, and others. However, non-academic partners may have the sense that researchers are less interested in taking the time to gain the expertise and competence needed to work with specific groups or on questions that are of direct interest to the community. For academics, it can be difficult to ensure sufficient rigor and transparency in the research, advance scientific knowledge in non-proprietary ways, and align timelines with their non-academic partners.

Additional Research Issues

Several cross-cutting research issues were also identified. A key debate is the conceptualization and measurement of psychological well-being, as well as the content and contours of psychological well-being relative to other factors (see EWB article this issue). It will be important to seek consistency in outcome assessment across studies (Moskowitz et al., 2021 ). Second, researchers might consider identifying a core set of well-being questions that can be applied consistently across studies. This would make it easier to compare results for different interventions conducted in different populations and settings. Another way to enhance comparability across studies is to harness the “megastudy” experimental paradigm, in a massive field experiment where many different treatments are tested synchronously in one large sample using a common, objectively measured outcome. For example, a consortium of 30 scientists from 15 different universities worked in small independent teams to design and test a total of 54 unique digital interventions aimed at promoting gym attendance among 61,293 members of an American fitness chain (Milkman et al., 2021 ). This experimental paradigm has several advantages including: (1) the ability to compare diverse interventions in an “apples-to-apples” manner by reducing the inherent heterogeneity that arises when studies are conducted independently, (2) enabling economies of scale, and (3) accelerating the pace of science (e.g., enhancing the ability to publish null results).

Third, creating optimal control groups presents significant challenges (Freedland et al., 2011 ). It is often difficult to create an activity for the control group that permits isolating the active ingredient of an intervention. For example, a study aiming to demonstrate that engaging in prosocial acts leads to improved psychological well-being would need to assess if prosociality per se is the active ingredient, versus simply engaging in a social activity (Regan et al., In Press ). An appropriate control activity would have participants perform acts that are social but not prosocial; however, identifying clear boundaries between similar activities can be difficult.

Fourth, managing expectations in control groups is critical, as is measuring participant beliefs and expectations to understand how intervention and control procedures are received (Haeck et al., 2016 ). To make these more nuanced comparisons, larger samples are often needed, but this raises additional dilemmas regarding resource allocation. It may not be clear if comparing an intervention to a sham intervention or active control is better than running competing interventions against each other to establish which is more effective (Hameiri & Moore-Berg, 2022 ). For example, one study compared effects of a PPI (i.e., writing about three things that went well each day, for seven days) with a positive placebo (i.e., writing about a positive memory for seven days) and found no difference in depression between the intervention and placebo, although some differences in happiness were evident (Mongrain & Anselmo-Matthews, 2012 ). One challenge with this comparison is that writing about a positive memory may also be considered a PPI. More broadly, this work suggests the importance of carefully considering the content of control conditions that allow for differentiating between positive interventions and positive expectancies.

A fifth issue relates to whether and which specific dimensions of psychological well-being should be targeted when aiming to enhance physical health. A recent narrative review evaluated articles examining various facets of well-being in relation to mortality, including only those that featured large sample sizes with robust adjustment for covariates; purpose in life, optimism, and life satisfaction were most consistently associated with reduced mortality risk, independent of covariates, followed by ikigai, positive affect, mastery, and sense of coherence (Trudel-Fitzgerald et al., 2021 ). The review found inconsistent relationships of mortality with happiness, personal growth, and autonomy, or there was too little research to draw firm conclusions. Ideally, future research will be able to include these facets within the same study and then compare effect estimates of each dimension of psychological well-being on the health outcome of interest to determine if some dimensions should be prioritized for intervention. Future research might also consider whether dimensions of psychological well-being that have not yet been considered in relation to physical health (e.g., self-acceptance, joy, awe) are promising (Trudel-Fitzgerald et al., 2021 ). In fact, with regard to interventions seeking to modify psychological well-being, many studies have targeted overall well-being non-specifically (e.g., via cash transfers; Dwyer & Dunn, 2022 ; Kushlev et al., 2020 ; McGuire et al., 2022 ). Whether gains achieved by improving a specific facet of psychological well-being in relation to physical health are greater than simply aiming to improve overall well-being (or any single facet) has not yet been determined. However, some research suggests that targeted approaches may be more effective (Trudel-Fitzgerald et al., 2021 ).

Sixth, it is also critical to evaluate mechanisms by which interventions lead to improved psychological well-being. Studies may want to consider repeated assessments of psychological states over time as well as measures of potential mediators or explanatory factors to facilitate tests of mediation. Recent work suggests the value of considering dynamic processes as mechanisms or pathways. For example, a recent paper identified a set of dynamic psychosocial processes through which PPIs may enhance psychological well-being, including: (1) attention and awareness, (2) comprehension and coping, (3) emotions, (4) goals and habits, and (5) virtues and relationships (Rusk & Waters, 2015 ). Such work can guide for future work seeking to examine and test mechanisms of PPIs more explicitly. Similar work can be done to identify mechanisms by which emotional well-being improves physical health, another critical issue for the field.

Several additional activities will further enhance progress. Investigators should explicitly evaluate whether some features of interventions make them more robust to inevitable differences in how they are implemented in real-world settings. Administering combinations of single interventions may be more effective than administering any one singly. Exploring methodological innovations may also help address limitations in existing studies. For example, integrative data analysis is a recently developed method by which studies using similar approaches can be combined (Graham et al., 2022 ). Applying these methods will allow for greater power to detect small effects.

What Does the Future Hold

After an intensive and rich exchange of ideas, workshop attendees identified several important lessons that inform next steps. They noted the need for sustained funding to support this research. While the NIH SOBC initiative has been an important source of funding, investigators also need to develop other partnerships. Foundations may have more appetite for piloting interventions that have “good enough” evidence to accelerate what is currently a long timeline for taking interventions from development to demonstrations of efficacy and implementation. Elevating the importance of the issues identified in the workshop regarding effect sizes, durability, and scalability will also be useful.

Diverse and transdisciplinary teams are needed for this work to succeed. Ideally, teams would possess diverse lived experiences and viewpoints, gather experts in basic science, intervention research, implementation science, and complexity science and incorporate input from key stakeholders to inform development of the most effective interventions. Such teams may be easier to find and build with the shareable resources and the creation of networks. Further discussion revolved around increasing political will to invest in psychological well-being. One way would be to survey public opinion and attitudes on psychological well-being and its importance in health and leverage the findings to engage and build partnerships with policy-makers and economists. Several other countries have developed high level positions aimed at fostering greater policy engagement with research in this domain, including the United Arabic Emirates and the UK, and U.S. Surgeon General Vivek Murthy is advocating this approach (Murthy, 2022 ).

Another strategy may be to link psychological well-being to other endpoints of significant concern to policy makers and funders. For example, recent work has identified the economic value of targeting and delaying aging (Scott et al., 2021 ). Additionally, the psychopathology literature has estimated the economic costs of several psychological illnesses and the potential cost savings by implementing interventions that aim to decrease these ailments (Knapp & Wong, 2020 ). More generally, research in this area might adopt methods developed in other domains using cost-effectiveness analysis to prioritize intervention strategies based not only on cost and effectiveness, but also on feasibility and projected population impact. For example, research on physical activity promotion and obesity prevention in childhood has taken this economic evaluation approach, first using a systematic review to identify key interventions with evidence of effectiveness and then using microsimulation models of the U.S. population to project effects of nationally implementing each intervention on physical activity and childhood obesity, drawing on current population health and health care cost data (Cradock et al., 2017 ). Similar methods might be effectively applied to evaluating interventions to modify psychological well-being. Knowing how psychological well-being might impact trajectories of aging and costs would generate interest in investment and sustainable funding for interventions to increase population-levels of psychological well-being. More generally, attendees agreed that given current trends in population health and particularly mental health, it is more important than ever to think creatively about ways to improve psychological well-being at the population level. We hope that sharing this discussion and the creativity, energy, and passion in the meeting will inspire continued work in this area and draw new investigators at all levels to the endeavor.

We note ongoing discussion about terminology; the workshop was convened using the term “psychological well-being.” However, since the convening, investigators have proposed using the term “emotional well-being” when discussing a similar construct. For the current article, we continue using the term “psychological well-being” as this is the term used in the convening, but refer readers to the article Park et al., 2023 , describing the use of the term “emotional well-being.”.

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Acknowledgements

We are deeply grateful to the following individuals, as they helped organize and take notes at our conference: Melia Dunbar, Harvard T.H. Chan School of Public Health Deepa Manjanatha, San Diego State University/University of California San Diego Jaime Mchunu, Harvard T.H. Chan School of Public Health Caitlyn Wilson, University of Colorado Denver

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Laura D. Kubzansky

Department of Psychology, University of British Columbia, Vancouver, Canada

Eric S. Kim

Department of Psychology, Chapman University, One University Drive, Orange, CA, USA

Julia K. Boehm

Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA

Richard J. Davidson

Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA

Jeffrey C. Huffman

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Department of Epidemiology, Mindfulness Center, Brown University School of Public Health, Providence, RI, USA

Eric B. Loucks

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Sonja Lyubomirsky

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ESK was supported by the Canadian Institutes of Health Research and the Michael Smith Foundation for Health Research; RP was supported by National Institutes of Health (R01MH118274); CTF is the Junior Research Chair on Social Disparities, Stress-Related Coping, and Health at Université du Québec à Trois-Rivières.

Laura D. Kubzansky and Eric S. Kim were both co-1 st authors, Judith Moskowitz is senior author and all other authors are listed alphabetically by last name.

Workshop Participants.

Julia Boehm, Chapman University.

Ruijia Chen, University of California, San Francisco.

Richard Davidson, University of Wisconsin-Madison.

Jeffrey Huffman, Massachusetts General Hospital.

Eric Kim, University of British Columbia.

Laura Kubzansky, Harvard T.H. Chan School of Public Health.

Eric Loucks, Brown University.

Sonja Lyubomirsky, University of California, Riverside.

Wendy Mendes, University of California, San Francisco.

Judy Moskowitz, Northwestern University Fienberg School of Medicine.

Lis Nielsen, National Institute on Aging.

Lisa Onken, National Institute on Aging.

Rosalind Picard, MIT Media Lab.

Alonzo Plough, Robert Wood Johnson Foundation.

Theresa Santo, U.S. Army Public Health Center.

Stephen Schueller, University of California, Irvine.

Claudia Trudel-Fitzgerald, Université du Québec à Trois-Rivières and Research Center of Institut Universitaire en Santé Mentale de Montréal.

Tyler VanderWeele, Harvard T.H. Chan School of Public Health.

Vish Viswanath, Harvard T.H. Chan School of Public Health.

Katey Warran, University College London.

David Yeager, University of Texas, Austin.

Charlotte Yeh, AARP.

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Kubzansky, L.D., Kim, E.S., Boehm, J.K. et al. Interventions to Modify Psychological Well-Being: Progress, Promises, and an Agenda for Future Research. Affec Sci 4 , 174–184 (2023). https://doi.org/10.1007/s42761-022-00167-w

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Overall, research (based primarily on the MIDUS study) suggests that subjective well-being improves between the ages of 25 and 74. Overall, positive affect
chapter three literature review psychological well-being
The second study was to compare psychological well-being amongst different types of sport and exercise (Edwards et al., 2004) confirming previous research