Pain and Suffering Have Distinct Effects on Distress and Wellbeing: Evidence From a Longitudinal Multi-Country Analysis

Pain and Suffering Have Distinct Effects on Distress and Wellbeing: Evidence From a Longitudinal Multi-Country Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pain and Suffering Have Distinct Effects on Distress and Wellbeing: Evidence From a Longitudinal Multi-Country Analysis Lucia Macchia, Tyler VanderWeele, Richard Cowden This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7933890/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Pain and suffering often co-occur, but sometimes they occur relatively independently. Little is known about whether experiencing pain without suffering might have unique implications for individual functioning compared to experiencing suffering without pain. Leveraging longitudinal data from a diverse and international sample of individuals across 22 countries and one territory (N = 20,944), we explored potential differences between these concatenations of pain and suffering on 20 subsequent distress and wellbeing outcomes. Adjusting for demographic characteristics, baseline values of the respective outcome, and country fixed effects, regression analyses provided evidence suggesting that those with ‘no pain and a lot of suffering’ had worse subsequent outcomes on two composite measures of wellbeing, several specific indicators of wellbeing, and loneliness than those with ‘a lot of pain and no suffering’. This study highlights the importance of differentiating pain from suffering, with implications for research on these distinct forms of distress and for interventions aimed at promoting wellbeing. Health sciences/Signs and symptoms/Pain/Chronic pain Health sciences/Health care/Public health Figures Figure 1 Introduction Pain and suffering are two of the most common human experiences. For instance, 31% of people worldwide report having experienced pain 1 , and around 28 million adults in the United Kingdom live with chronic pain 2 . Recent data from Wave 1 of the Global Flourishing Study (GFS) indicate that across 22 countries there was an average of 44% of people in each country who reported experiencing ‘some/a lot’ of suffering 9 , suggesting a relatively high prevalence of suffering in the general population. In addition to their prevalence, the importance of pain and suffering relies on their potential consequences. For instance, in the United States, pain has been a key underlying factor of the opioid epidemic and the so-called ‘deaths of despair’ phenomenon 3 , 4 . Pain can have detrimental consequences for people’s life satisfaction 5 , 6 and productivity 7 , as well as a nation’s economic system 8 . At the same time, suffering has been found to be associated with worse health and wellbeing outcomes, including depressive mood, pain-related limitations, sleepless days, life satisfaction, happiness, and physical and mental health 10 . Suffering can also have other important consequences like frustration, withdrawal, helplessness, ໿strained relationships, and a reduced ໿sense of purpose 11 , 12 . Pain and suffering are often highly intertwined, and individuals may use these terms interchangeably. However, they are distinct experiences with different meanings and potential consequences. In this study, we explore the wellbeing consequences of experiencing pain without suffering and suffering without pain across 20 distress and wellbeing outcomes using a diverse, global longitudinal dataset. Theoretically, pain is often understood as a primarily biological and sensory signal, yet, the Biopsychosocial Model of Pain suggests that pain may also be shaped by psychological and social processes 13 . On the other hand, suffering is an interpretive and meaning-laden experiential state that reflects a person’s judgment about what they are encountering, which may occur in the presence or absence of physical pain 14 . From a practical perspective, experiencing suffering without pain may signal deeper disruptions in meaning, belonging, or purpose that can erode wellbeing. Conversely, individuals who live with pain but do not experience suffering may be supported by coping strategies, resilience, or positive meaning-making that buffer against negative outcomes. This suggests that suffering, even in the absence of pain, can sometimes be more corrosive to wellbeing than pain alone. These ideas suggest that interventions that extend beyond biological mechanisms are needed to address important psychological and social dimensions of different forms of distress. While policies and interventions that target only the biological side of pain may overlook some of the potential downstream consequences of suffering, it is equally problematic if the meaning or contextual considerations that may be primary in suffering are emphasized to the point where pain is minimized or ignored. By disentangling the two, research and policy can inform more precise healthcare and wellbeing strategies, ensuring that both pain and suffering are appropriately addressed when they arise. The present study is the first global empirical test in that direction. Pain is commonly defined as ໿“an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage” 15,p.2 . Suffering ໿can be understood as “the undesired experience, of considerable intensity or duration, of a negative physical or affective state” 16 . On these definitions, pain and suffering will often co-occur, but not all pain will be accompanied by suffering. For example, sometimes with athletic training, or in masochism (when pain is desired and sought for pleasure), pain is less likely to be experienced as suffering 14 . Conversely, suffering from loneliness may be present without an experience of physical pain. Providing some support for a distinction between pain and suffering, country-level distributions of pain and suffering using data from the GFS showed meaningful differences in the percentage of people who endorsed ‘some/a lot’ of pain versus ‘some/a lot’ of suffering in a number of countries, including an 8% difference in endorsement in Germany, Indonesia, and Poland, a 10% difference in Egypt, and a 16% difference in the Philippines 9 , 17 . Although recent conceptual and empirical work points to the potential importance of differentiating these two experiences for theory, research, and practice, little empirical attention has been dedicated to this idea until more recently. Much of the existing empirical research that has explored pain and suffering together has mostly relied on clinical populations. For example, using a sample of 125 patients who visited the emergency room in the United Kingdom, one study showed that pain and suffering can co-occur: 61.6% of patients reported suffering, 72% reported pain, and 29.6% reported both 18 . A review paper has documented that suffering was present in patients with different conditions that might be associated with pain 19 . In related work, some researchers have recognised the possibility that people’s physical injury and the subsequent pain can act as the visual evidence of their suffering (Chen et al., 2008; Williams & Zadro, 2001). Others have used these terms interchangeably. For example, one study that explored the link between pain in the body and spirituality talked about the suffering of the pain or people suffering physical wounds or discomforts 22 . Another study explored how the context influenced the price people would pay for pain relief and referred to it as ‘relieving suffering’ 23 p.309 . Despite these insights, there is a lack of robust multinational empirical research exploring the distinct effects of pain and suffering in the general population. Developing a more precise understanding of how suffering and physical pain can uniquely predict individual functioning may have important implications for measurement and intervention. Here, we take a step toward addressing this gap by exploring whether experiencing pain without suffering or experiencing suffering without pain is more strongly associated with a set of 20 subsequent distress and wellbeing outcomes in a large diverse and international sample. Methods All materials for this article are publicly available. The data that support the findings of this article are openly available on the Open Science Framework. The specific dataset used was wave 1 and 2 non-sensitive Global data https://www.cos.io/gfs . Code for analyses can be found in the OSF at https://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf . All analyses were preregistered with the OSF at https://osf.io/r5ehx/?view_only=c697c231e5ed4b1fa6d4cf93beb54038 . Data We used data from the Global Flourishing Study (GFS), a multinational longitudinal study with nationally representative samples from 207,919 participants across 22 countries and one territory: Argentina, Australia, Brazil, China, Egypt, Germany, Hong Kong (Special Administrative Region of China), India, Indonesia, Israel, Japan, Kenya, Mexico, Nigeria, the Philippines, Poland, South Africa, Spain, Sweden, Tanzania, Turkey, the United Kingdom, and the United States. To date, the GFS provides two waves of data. Extensive details about the GFS methodology and sample can be found in the GFS Questionnaire Development Report 24 , the GFS Methodology 25 , the GFS Codebook, and the GFS Translations documents 26 . Sample characteristics for the full sample of wave 1 can be found in the GFS study profile (VanderWeele et al., 2025), while characteristics for the sample used in this study can be found in Table 1 below. Table 1 Descriptive statistics for variables involved in the analyses, n = 20,944. Wave 1 Wave 2 Variable Mean Std. Dev. Mean Std. Dev. Min Max Flourishing Index 7.685 1.876 7.528 1.862 0 10 Secure flourishing Index 7.47 1.883 7.338 1.875 0 10 Happiness 7.308 2.702 7.135 2.638 0 10 Life satisfaction 7.215 2.894 7.033 2.839 0 10 Mental Health 8.144 2.596 7.958 2.561 0 10 Physical Health 7.491 2.825 7.282 2.736 0 10 Meaning 7.615 2.677 7.463 2.631 0 10 Purpose 7.867 2.629 7.747 2.613 0 10 Relationship contentment 7.956 2.541 7.797 2.568 0 10 Relationship satisfaction 7.666 2.693 7.483 2.675 0 10 Orientation to promote good 8.247 2.108 8.075 2.192 0 10 Delayed gratification 7.337 2.748 7.306 2.627 0 10 Financial security 6.273 3.642 6.267 3.539 0 10 Material security 6.517 3.653 6.507 3.541 0 10 Threat life 1.822 1.117 1.951 1.102 1 4 Depression symptoms 1.66 1.036 1.704 1.005 1 4 Anxiety symptoms 1.714 1.038 1.759 1.013 1 4 Loneliness 2.804 3.338 2.927 3.258 0 10 Perceived discrimination 1.728 .943 1.781 .925 1 4 Health problems Yes .202 .402 .223 .417 0 1 Pain-suffering No pain – no suffering .696 .46 0 1 A lot of pain – no suffering .038 .191 0 1 No pain – A lot of suffering .039 .194 0 1 A lot of pain – A lot of suffering .227 .419 0 1 Age 45.44 17.161 18 99 Gender Male .5 .5 0 1 Female .498 .5 0 1 Other .001 .034 0 1 Marital status Married .598 .49 0 1 Separated .021 .145 0 1 Divorced .054 .225 0 1 Widowed .042 .201 0 1 Never .23 .421 0 1 Domestic Partner .055 .228 0 1 Employment status Employed for an employer .357 .479 0 1 Self-employed .178 .382 0 1 Retired .161 .367 0 1 Student .052 .223 0 1 Homemaker .124 .33 0 1 Unemployed and looking .082 .274 0 1 None of these/other .045 .208 0 1 Level of education up to 8 years .196 .397 0 1 9–15 years .535 .499 0 1 16 + years .268 .443 0 1 Number of children 1.083 1.829 0 97 Measures Exposure. To create the main exposure for this analysis, we concatenated the individual pain and suffering variables from wave 1 of the GFS. Pain was assessed with: “How much bodily pain have you had during the past 4 weeks?” and could answer ‘a lot’, ‘some’, ‘not very much’, or ‘none at all’. Suffering was assessed with: “To what extent are you suffering? This can be any type of physical or mental suffering” Both measures were rated using a four-point response scale: ‘a lot’, ‘some’, ‘not very much’, or ‘none at all’. We produced a pain-suffering variable with 16 categories (see Fig. 1 ). Since we were interested in the extremes of the pain and suffering distributions, we selected the following four categories: 1) No pain and no suffering, 2) A lot of pain and no suffering (reference category), 3) No pain and a lot of suffering, and 4) A lot of pain and a lot of suffering. This four-category variable was used in the regression analyses shown in Table 2 (N = 20,944, M age =45.44 ± 17.46 years, Female = 49.8%). Table 2 Coefficients of the exposure ‘No pain – A lot of suffering’ (Ref.: ‘A lot of pain – No suffering’) in the Global Flourishing Study (N = 20,944). Outcome in Wave 2 Controlling only for the relevant outcome in Wave 1 (1) Controlling for additional outcomes in Wave 1 (2) Estimate SE Estimate SE Flourishing Index (0–10) -0.245 ** (0.071) -0.187 * (0.071) Secure flourishing Index (0–10) -0.201 ** (0.069) -0.171 * (0.062) Happiness (0–10) -0.455 * (0.186) -0.275 (0.134) Life satisfaction (0–10) -0.507 ** (0.163) -0.402 ** (0.106) Mental Health -0.479 *** (0.122) -0.385 ** (0.109) Physical Health -0.030 (0.110) 0.368 *** (0.095) Meaning -0.448 * (0.185) -0.263 (0.143) Purpose -0.551 *** (0.114) -0.293 * (0.111) Relationship contentment -0.471 * (0.196) -0.315 * (0.134) Relationship satisfaction -0.564 ** (0.165) -0.346 * (0.134) Orientation to promote good -0.202 (0.115) -0.019 (0.084) Delayed gratification -0.147 (0.165) 0.057 (0.138) Financial security -0.138 (0.197) 0.034 (0.214) Material security -0.369 * (0.176) -0.206 (0.208) Threat life 0.087 (0.080) -0.001 (0.082) Depression symptoms 0.121 (0.069) 0.086 (0.065) Anxiety symptoms 0.146 (0.075) 0.075 (0.046) Loneliness 0.601 ** (0.178) 0.315 * (0.128) Perceived discrimination 0.037 (0.040) 0.013 (0.043) Health problems -0.022 (0.029) -0.028 (0.028) Note : * p < 0.05, ** p < 0.01, *** p < 0.001. Table shows unstandardized coefficients from Ordinary Least Squares Regressions with standard errors clustered at the country level in parentheses. All models include demographic variables including age, gender (female, male, other), marital status (married, separated, divorced, widowed, single, domestic partner), employment status (employed for an employer, self-employed, retired, student, homemaker, unemployed and looking for a job, none of these/other), level of education (primary, secondary, tertiary), number of children, and country fixed effects. Full models can be found in Tables S.1 and S.2 in the SM. Models in column 2 also controlled for Secure Flourishing Index values, threat life, depression symptoms, anxiety symptoms, loneliness, perceived discrimination, and health problems in wave 1. These full models can be found in Tables S.3 and S.4 in the SM. Each cell corresponds to a different regression . For example, the first coefficient − 0.245 is the coefficient of Flourishing as a function of the pain-suffering category ‘No pain – A lot of suffering’ (Ref.: ‘A lot of pain – No suffering’). Scale of outcomes : Flourishing (0 = Low-10 = High), happiness (0 = Extremely unhappy-10 = Extremely happy), life satisfaction (0 = Not at all satisfied-10 = Completely satisfied), physical and mental health (0 = Poor-10 = Excellent), meaning (0 = Not at all-10 = Completely), orientation to promote good and delayed gratification (0 = Not true-10 = Completely true), purpose, relationship contentment and relationship satisfaction (0 = Strongly disagree-10 = Strongly agree), financial security and material security (0 = Low-10 = High). Threat life (1 = Not at all-4 = A lot)), depression symptoms and anxiety symptoms (1 = Not at all 4 = Nearly every day), loneliness and perceived discrimination (0 = Never to 10 = Always), health problems (0 = No, 1 = Yes). Outcomes. We analysed a total of 20 outcomes, including the Flourishing and Secure Flourishing Indexes (2), their components (12), and distress-related variables (6). Wave 2 values of these variables were used as dependent variables, and their baseline values from wave 1 were used as covariates. The exact wording for the measures used in this study can be found at https://www.cos.io/gfs-wave-data . Following previous work (VanderWeele, 2017), we created a Flourishing Index and a Secure Flourishing Index. The Flourishing Index included five domains with two components each: (i) happiness and life satisfaction, (ii) physical and mental health, (iii) meaning and purpose in life, (iv) character and virtue, and (v) close social relationships. Responses to wave 2 items for the components within each domain were first averaged, and the five domains were averaged for a Flourishing Index score (α = 0.86). The Secure Flourishing Index comprises the five Flourishing Index domains plus a sixth domain of financial and material security. Scores for the six domains were averaged to obtain a Secure Flourishing Index score (໿α = 0.83). The same procedure was used to create the Flourishing Index (α = 0.85) and Secure Flourishing Index (α = 0.80) in wave 1 (VanderWeele et al., 2025). Following prior work e.g., 12 , the 12 individual items were also analysed separately as specific indicators. The six distress-related wave 2 variables included: (i) threat life (how much the respondent was bothered by the most serious threat to life they have witnessed or experienced), (ii) frequency of depression symptoms, (iii) frequency of anxiety symptoms, (iv) frequency of loneliness, (v) frequency of perceived discrimination, and (vi) health problems. Statistical analyses We conducted 20 Ordinary Least Squares regressions, one for each wave 2 outcome. Models regressed each individual outcome on the pain-suffering exposure, the respective outcome in wave 1, and all demographic variables in wave 1. All models included country fixed effects to account for common factors in each country and clustered the standard errors at the country level to account for the correlation of responses from people living in the same country. As a sensitivity analysis, we repeated these 20 models with additional wave 1 covariate adjustment for Secure Flourishing Index values, threat life, depression symptoms, anxiety symptoms, loneliness, perceived discrimination, and health problems. We conducted complete-case analyses since attrition from wave 1 to wave 2 in the two pain-suffering categories of interest was relatively low: ‘no pain-a lot of suffering’ (4.84% of the total sample) and ‘a lot of pain-no suffering’ (4.68% of the total sample). See additional comments below. Results Figure 1 shows the percentage of individuals across the 16 categories of the wave 1 pain-suffering variable (N = 206,882). The co-occurrence of pain-suffering at the same level is quite common, with categories representing some of both (16.4%) and a little of both (16.9%) showing comparatively higher percentages. The four categories of the pain-suffering concatenation that formed the focal predictor in our main analysis have varied representation: (i) No pain and no suffering (12.8%), (ii) A lot of pain and no suffering (0.78%, N = 1,628), (iii) No pain and a lot of suffering (0.8%, N = 1,686), and (iv) A lot of pain and suffering (4.6%). To conduct the main inferential analyses, we restricted the sample to these four pain-suffering categories, resulting in a sample of 20,944 individuals. With this restriction, proportions in each category were as follows. The proportion of people who reported a lot of one and none of the other was relatively similar: ‘a lot of pain and no suffering’ (3.8%), and ‘no pain and a lot of suffering’ (3.9%). While the majority of people in this sample reported no pain and no suffering (69.6%), a smaller proportion reported a lot of pain and a lot of suffering (22.7%). Roughly half (49.8%) of participants were female (Std. Dev.= 0.5), and the mean age was 45.44 years (Std. Dev.= 17.26). In this sample, average responses to the wellbeing and distress variables were similar across wave 1 and wave 2. Descriptive statistics for all variables are shown in Table 1 . Column 1 in Table 2 shows that after controlling for wave 1 demographic characteristics and the prior value of the respective outcome, those who experienced ‘no pain and a lot of suffering’ (compared to those who experienced ‘a lot of pain and no suffering’) reported a greater decline in scores on the Flourishing Index ( b = -0.245, β = -0.025, p = .002, 95%CI[-0.393, -0.096]) and the Secure Flourishing Index ( b = -0.201, β = -0.021, p = .008, 95%CI[-0.343, -0.057]), happiness ( b = -0.455, β = -0.033, p = .023, 95%CI[-0.841, -0.068], life satisfaction ( b = -0.507, β = − .035, p = .005, 95%CI[-0.845, -0.168]), mental health ( b = -0.479, β = -0.036, p = .001, 95%CI[-0.731, -0.225]), meaning ( b = -0.448, β = -0.033, p = .024, 95%CI[-0.831, -0.065]), purpose ( b =-0.551, β = -0.040, p < . 001, 95%CI[-0.787, -0.314]), relationship contentment ( b = -0.471, β = -0.035, p = .025, 95%CI[-0.876, -0.064]), relationship satisfaction ( b = -0.564, β = -0.041, p = .003, 95%CI[-0.906, -0.221]), material security ( b = -0.369, β = -0.020, p = .047, 95%CI[-0.733, -0.005]), and a greater increase in loneliness ( b = 0.601, β = 0.035, p = .003, 95%CI[0.232, 0.969]) in wave 2. Full models can be found in Tables S.1 and S.2 in the Supplemental Materials. After simultaneously adjusting for prior values of the full set of wave 1 outcomes (column 2, Table 2 ), the strength of associations for several outcomes generally attenuated but in many cases remained substantial: Flourishing Index ( b = -0.187, β = -0.019, p = .015, 95%CI[-0.334, -0.040]), Secure Flourishing Index ( b = -0.171, β = -0.017, p = .012, 95%CI[-0.299, -0.042]), life satisfaction ( b = -0.402, β = -0.027, p = .001, 95%CI[-0.622, -0.181]), mental health ( b = -0.385, β = -0.029, p = .002, 95%CI[-0.611, -0.160]), purpose ( b = -0.293, β = -0.021, p = .015, 95%CI[-0.522, 0.063]), relationship contentment ( b = -0.315, β = -0.023, p = .028, 95%CI[-0.593, -0.037]), relationship satisfaction ( b = -0.346, β =, p = .017, 95%CI[-0.624, -0.067]), loneliness ( b = 0.315, β = 0.018, p = .023, 95%CI[0.048, 0.581]). The association with physical health became statistically significant and positive ( b = 0.368, β = 0.026, p = .001, 95%CI[0.171, 0.565]). Full models can be found in Tables S.3 and S.4 in the Supplemental Materials. To shed some light on cross-country variations, we estimated the distribution of our pain-suffering variable in each country. This is shown in Table S.5. While in most countries the ‘no pain-no suffering’ category had the highest percentage of respondents, in some countries like Philippines and Turkey the ‘a lot of pain-a lot of suffering’ category had the highest percentage of respondents. Regarding the other categories, some countries like Brazil, Egypt, Indonesia, and South Africa had the highest percentage of respondents in the ‘a lot of pain – no suffering’ category whereas some other countries like Argentina, Germany, India, Philippines, and Turkey had the highest percentage of respondents in the ‘no pain – a lot of suffering’ category. Discussion This is, to the best of our knowledge, the first study to use longitudinal data from general population samples across geographically and culturally diverse countries to document potential effects of experiencing pain without suffering versus suffering without pain on wellbeing and distress. Our findings shed new light on both the co-occurrence and dissociation of pain and suffering and help to address an important gap in our understanding of whether experiencing pain without suffering differs in its implications for individual functioning relative to experiencing suffering without pain. First, we document that experiences of pain and suffering do not always co-occur. In our sample, some individuals reported pain without suffering and others reported suffering without pain. Second, our regression analyses showed that those who reported ‘no pain and a lot of suffering’ had worse subsequent wellbeing (and to a lesser extent worse distress) on a range of outcomes compared to those who reported ‘a lot of pain and no suffering’. Those who experienced ‘no pain and a lot of suffering’ reported comparative lower subsequent flourishing, secure flourishing, happiness, life satisfaction, mental health, relationship contentment, relationship satisfaction, and material security than those who experienced ‘a lot of pain and no suffering’. These findings suggest that experiencing only suffering may lead to a greater decline in some aspects of wellbeing compared to experiencing only pain. Third, we show that for the six distress-related outcomes, people who experienced suffering without pain (versus pain without suffering) reported greater subsequent loneliness. For the other outcomes—such as anxiety and depression—little evidence of a difference was observed. This suggests that when it comes to psychological distress, suffering and pain may have more similar effects, possibly related to the shared negative affective components embedded in both experiences 29 – 31 . This potential pain-suffering-distress overlap might also be seen as being in line with prior work that showed that ໿acetaminophen (widely known as paracetamol) can reduce the pain that arises from social rejection by reducing the neural responses in regions of the brain that have been associated with distress 32 . The bidirectional link between pain and negative emotions 33 , along with the biopsychosocial model of pain that suggests that biological and psychosocial aspects underlie the experience of pain, also supports these ideas 13 . In contrast to the clearer distinctions observed in positive wellbeing outcomes, the overlap in negative emotional content might explain why these two states appear less differentiated in their association with various forms of subsequent distress. After adjusting for the full set of wave 1 outcomes simultaneously, a notable shift emerged pointing to a possible suppression effect: physical health became significantly more positive among those who reported only suffering compared to those who reported only pain. This suggests that pain may be more directly tied to physical health, while suffering may be more strongly linked to mental, social, and emotional domains. This finding raises important questions about the way pain is assessed in both research and practice. Specifically, it prompts consideration of whether pain measures should distinguish between physical and other categories of pain (e.g., psychological, social)—as their implications for wellbeing might differ meaningfully. Current tools often conflate these dimensions, which could obscure critical distinctions in how individuals experience and report pain and suffering. More research in this area is needed. One of the limitations of this study is the potential impact of differential attrition between wave 1 and wave 2, with those who had better wellbeing on some wave 1 indicators showing a higher likelihood of dropping out of the ‘no pain-a lot of suffering’ group than the ‘a lot of pain-no suffering’ group (see Tables S.6 and S.7 in the SM). Although such attrition will not bias analyses if it is non-differential conditional on covariates, differential dropout may nonetheless influence the generalizability of the findings by reducing the representativeness of the ‘no pain-a lot of suffering’ group at wave 2. Another limitation is that, while we employed a longitudinal design with staggered measurement of key variables at two time points assessed with a lag of about one year, we cannot make definitive claims about causal relationships. Also, although we used data from 22 countries, our results may not be generalizable to other regions and cultures 34 . Future research should explore whether these findings hold in other countries and cultural contexts. Finally, our measures of pain and suffering used a 4-point scale, which did not allow us to conduct a more detailed exploration of levels of pain and suffering. However, the data used here is the only one currently available that measured these two concepts with the exact same scale, allowing us to explore the co-occurrence (or not) of pain and suffering while minimizing the noise that different scales might bring. By showing that pain-suffering experiences are differently linked to subsequent wellbeing and distress outcomes, this study highlights the importance of distinguishing these two concepts. This work lays the groundwork for future research on the conceptual and semantic differences between pain and suffering. In practice, understanding the difference between experiences and implications of pain versus suffering is important for employing appropriate measures and intervention strategies to support the wellbeing of those affected by these distinct forms of distress. Declarations Conflicts of interest: Tyler VanderWeele reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy. Funding: No. Artificial intelligence: No. Ethics: Secondary data was used, thus, institutional ethical approval was not required. Preregistration: All analyses were preregistered with the Open Science Framework (OSF) at https://osf.io/r5ehx/?view_only=c697c231e5ed4b1fa6d4cf93beb54038. Materials: All study materials are publicly available (https://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf). Data: The data that support the findings of this article are openly available on the Open Science Framework. The specific dataset used was wave 1 and 2 non-sensitive Global data https://www.cos.io/gfs available February 2024 - March 2026 via preregistration and publicly from then onwards. Researchers interested in working with these data before March 2026, need to preregister their analysis. No specific additional registration is needed to access the data. Analysis scripts: Code for analyses can be found in Open Science Framework (OSF) at https://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf Author Contributions : RC and LM designed the analyses, LM conducted the analyses, LM wrote the first draft of the paper, RC and TVV provided revisions. References Macchia, L. Pain trends and pain growth disparities, 2009–2021. Economics and Human Biology 47, 101200 (2022). Fayaz, A., Croft, P., Langford, R. M., Donaldson, L. J. & Jones, G. T. Prevalence of chronic pain in the UK: A systematic review and meta-analysis of population studies. BMJ Open 6, (2016). Case, A., Deaton, A. & Stone, A. A. Decoding the mystery of American pain reveals a warning for the future. Proceedings of the National Academy of Sciences of the United States of America 117, 24785–24789 (2020). Garland, E. L., Froeliger, B., Zeidan, F., Partin, K. & Howard, M. O. 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Available at SSRN : https://ssrn.com/abstract=5078503 or http://dx.doi.org/10.2139/ssrn.5078503 (2025). Raja, S. et al. The revised IASP definition of pain: concepts, challenges, and compromises. Pain 161, 1976–1982 (2020). VanderWeele, T. J. Suffering and response: Directions in empirical research. Social Science and Medicine 224, 58–66 (2019). Macchia, L. et al. Demographic variation in pain across 22 countries. Communications Medicine 5, 1–8 (2025). Body, R., Kaide, E., Kendal, S. & Foex, B. Not all suffering is pain: Sources of patients’ suffering in the emergency department call for improvements in communication from practitioners. Emergency Medicine Journal 32, 15–20 (2015). Fishbain, D. A. Review The Pain — Suffering Association, A Review. 1057–1072 (2015). Chen, Z., Williams, K. D., Fitness, J. & Newton, N. C. When hurt will not heal: Exploring the capacity to relive social and physical pain. Psychological Science 19, 789–795 (2008). Williams, K.D., Zadro, L. Ostracism: On being ignored, excluded and rejected. in Interpersonal rejection (ed. Leary, M. R.) 21–53 (New York: Oxford University Press., 2001). Cova, V. & Cova, B. Pain, suffering and the consumption of spirituality: a toe story. Journal of Marketing Management 35, 565–585 (2019). Vlaev, I., Seymour, B., Dolan, R. J. & Chater, N. The price of pain and the value of suffering. Psychological Science 20, 309–317 (2009). Crabtree, S., English, C., Johnson, B. R., Ritter, Z. & VanderWeele, T. J. Global Flourishing Study: Questionnaire Development. Gallup Inc. , [Retrieved on 2025-05-21 from https://osf.io/y3t6m (2021). Available at: https://osf.io/y3t6m . Ritter, Z. et al. Global Flourishing Study Methodology. Gallup Inc. (2024). Available at: https://osf.io/k2s7u . Johnson, B. R. et al. The Global Flourishing Study. (2024). Available at: https://doi.org/10.17605/OSF.IO/3JTZ8 . VanderWeele, T. J. et al. The Global Flourishing Study: Study profile and initial results on flourishing. Nature Mental Health 3, 636–653 (2025). VanderWeele, T. J. On the promotion of human flourishing. Proceedings of the National Academy of Sciences of the United States of America 114, 8148–8156 (2017). Price, D. D. Psychological and neural mechanisms of the affective dimension of pain. Science 288, 1769–1772 (2000). Franklin, J. C., Lee, K. M., Hanna, E. K. & Prinstein, M. J. Feeling worse to feel better: Pain-offset relief simultaneously stimulates positive affect and reduces negative affect. Psychological Science 24, 521–529 (2013). Koopmann-Holm, B., Bartel, K., Bin Meshar, M. & Yang, H. E. Seeing the whole picture? Avoided negative affect and processing of others’ suffering. Personality and Social Psychology Bulletin 46, 1363–1377 (2020). DeWall, C. N. et al. Acetaminophen reduces social pain: Behavioral and neural evidence. Psychological Science 21, 931–937 (2010). Macchia, L. Understanding despair: The role of physical pain. American Journal of Health Promotion 1–3 (2023). doi: 10.1177/08901171231177849 Simons, D. J., Shoda, Y. & Lindsay, D. S. Constraints on Generality (COG): A proposed addition to all empirical papers. Perspectives on Psychological Science 12, 1123–1128 (2017). Additional Declarations Yes there is potential Competing Interest. Tyler VanderWeele reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy. Supplementary Files 2SupplementalMaterials.docx Supplemental materials Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7933890","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":539993729,"identity":"9a26432d-e085-4944-96d8-0b1a757ea340","order_by":0,"name":"Lucia Macchia","email":"data:image/png;base64,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","orcid":"","institution":"City St Georges, University of London","correspondingAuthor":true,"prefix":"","firstName":"Lucia","middleName":"","lastName":"Macchia","suffix":""},{"id":539993730,"identity":"277d0747-63fa-4e94-878a-2ef744edb6f5","order_by":1,"name":"Tyler VanderWeele","email":"","orcid":"https://orcid.org/0000-0002-6112-0239","institution":"Harvard 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07:17:19","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":113383,"visible":true,"origin":"","legend":"","description":"","filename":"COMMSMED2526360structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7933890/v1/9bf6705158b49959d7c3c83e.xml"},{"id":95916206,"identity":"da15fba3-1247-490f-a6b1-4abf36067e1a","added_by":"auto","created_at":"2025-11-14 11:48:40","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":121792,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7933890/v1/482e711708977d7f5ee4260c.html"},{"id":95916199,"identity":"87f7d3c7-a4cb-4f89-a8da-2d793b592243","added_by":"auto","created_at":"2025-11-14 11:48:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":180131,"visible":true,"origin":"","legend":"\u003cp\u003ePain-suffering combined categories in year 1. The Global Flourishing Study (N = 206,882). Bars represent error bars. Blue bars represent a lot of pain with different suffering combinations. Beige bars represent some pain with different suffering combinations. Orange bars represent not very much pain with different suffering combinations. Green bars represent no pain with different suffering combinations.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7933890/v1/a6e2dae8a2a4c39d8042eb7f.png"},{"id":104401563,"identity":"ece65957-aad8-4fa0-970b-eaad2989a90e","added_by":"auto","created_at":"2026-03-11 12:12:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1066301,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7933890/v1/d2bfeecc-b109-4c72-8901-4f724c866572.pdf"},{"id":95916198,"identity":"ac2333c6-9b45-47a3-bb39-cbcb75761878","added_by":"auto","created_at":"2025-11-14 11:48:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":128953,"visible":true,"origin":"","legend":"Supplemental materials","description":"","filename":"2SupplementalMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7933890/v1/81fd193a95415c4defd657f9.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nTyler VanderWeele reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy.","formattedTitle":"Pain and Suffering Have Distinct Effects on Distress and Wellbeing:\r\nEvidence From a Longitudinal Multi-Country Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePain and suffering are two of the most common human experiences. For instance, 31% of people worldwide report having experienced pain \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, and around 28\u0026nbsp;million adults in the United Kingdom live with chronic pain \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Recent data from Wave 1 of the Global Flourishing Study (GFS) indicate that across 22 countries there was an average of 44% of people in each country who reported experiencing \u0026lsquo;some/a lot\u0026rsquo; of suffering \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, suggesting a relatively high prevalence of suffering in the general population.\u003c/p\u003e\u003cp\u003eIn addition to their prevalence, the importance of pain and suffering relies on their potential consequences. For instance, in the United States, pain has been a key underlying factor of the opioid epidemic and the so-called \u0026lsquo;deaths of despair\u0026rsquo; phenomenon \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Pain can have detrimental consequences for people\u0026rsquo;s life satisfaction \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and productivity \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, as well as a nation\u0026rsquo;s economic system \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. At the same time, suffering has been found to be associated with worse health and wellbeing outcomes, including depressive mood, pain-related limitations, sleepless days, life satisfaction, happiness, and physical and mental health \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Suffering can also have other important consequences like frustration, withdrawal, helplessness, ໿strained relationships, and a reduced ໿sense of purpose \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePain and suffering are often highly intertwined, and individuals may use these terms interchangeably. However, they are distinct experiences with different meanings and potential consequences. In this study, we explore the wellbeing consequences of experiencing pain without suffering and suffering without pain across 20 distress and wellbeing outcomes using a diverse, global longitudinal dataset.\u003c/p\u003e\u003cp\u003eTheoretically, pain is often understood as a primarily biological and sensory signal, yet, the Biopsychosocial Model of Pain suggests that pain may also be shaped by psychological and social processes \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. On the other hand, suffering is an interpretive and meaning-laden experiential state that reflects a person\u0026rsquo;s judgment about what they are encountering, which may occur in the presence or absence of physical pain \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFrom a practical perspective, experiencing suffering without pain may signal deeper disruptions in meaning, belonging, or purpose that can erode wellbeing. Conversely, individuals who live with pain but do not experience suffering may be supported by coping strategies, resilience, or positive meaning-making that buffer against negative outcomes. This suggests that suffering, even in the absence of pain, can sometimes be more corrosive to wellbeing than pain alone.\u003c/p\u003e\u003cp\u003eThese ideas suggest that interventions that extend beyond biological mechanisms are needed to address important psychological and social dimensions of different forms of distress. While policies and interventions that target only the biological side of pain may overlook some of the potential downstream consequences of suffering, it is equally problematic if the meaning or contextual considerations that may be primary in suffering are emphasized to the point where pain is minimized or ignored. By disentangling the two, research and policy can inform more precise healthcare and wellbeing strategies, ensuring that both pain and suffering are appropriately addressed when they arise. The present study is the first global empirical test in that direction.\u003c/p\u003e\u003cp\u003ePain is commonly defined as ໿\u0026ldquo;an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage\u0026rdquo; \u003csup\u003e15,p.2\u003c/sup\u003e. Suffering ໿can be understood as \u0026ldquo;the undesired experience, of considerable intensity or duration, of a negative physical or affective state\u0026rdquo; \u003csup\u003e16\u003c/sup\u003e. On these definitions, pain and suffering will often co-occur, but not all pain will be accompanied by suffering. For example, sometimes with athletic training, or in masochism (when pain is desired and sought for pleasure), pain is less likely to be experienced as suffering \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Conversely, suffering from loneliness may be present without an experience of physical pain. Providing some support for a distinction between pain and suffering, country-level distributions of pain and suffering using data from the GFS showed meaningful differences in the percentage of people who endorsed \u0026lsquo;some/a lot\u0026rsquo; of pain versus \u0026lsquo;some/a lot\u0026rsquo; of suffering in a number of countries, including an 8% difference in endorsement in Germany, Indonesia, and Poland, a 10% difference in Egypt, and a 16% difference in the Philippines \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough recent conceptual and empirical work points to the potential importance of differentiating these two experiences for theory, research, and practice, little empirical attention has been dedicated to this idea until more recently.\u003c/p\u003e\u003cp\u003eMuch of the existing empirical research that has explored pain and suffering together has mostly relied on clinical populations. For example, using a sample of 125 patients who visited the emergency room in the United Kingdom, one study showed that pain and suffering can co-occur: 61.6% of patients reported suffering, 72% reported pain, and 29.6% reported both \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. A review paper has documented that suffering was present in patients with different conditions that might be associated with pain \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In related work, some researchers have recognised the possibility that people\u0026rsquo;s physical injury and the subsequent pain can act as the visual evidence of their suffering (Chen et al., 2008; Williams \u0026amp; Zadro, 2001). Others have used these terms interchangeably. For example, one study that explored the link between pain in the body and spirituality talked about the suffering of the pain or people suffering physical wounds or discomforts \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Another study explored how the context influenced the price people would pay for pain relief and referred to it as \u0026lsquo;relieving suffering\u0026rsquo; \u003csup\u003e23 p.309\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite these insights, there is a lack of robust multinational empirical research exploring the distinct effects of pain and suffering in the general population. Developing a more precise understanding of how suffering and physical pain can uniquely predict individual functioning may have important implications for measurement and intervention. Here, we take a step toward addressing this gap by exploring whether experiencing pain without suffering or experiencing suffering without pain is more strongly associated with a set of 20 subsequent distress and wellbeing outcomes in a large diverse and international sample.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAll materials for this article are publicly available. The data that support the findings of this article are openly available on the Open Science Framework. The specific dataset used was wave 1 and 2 non-sensitive Global data \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cos.io/gfs\u003c/span\u003e\u003cspan address=\"https://www.cos.io/gfs\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Code for analyses can be found in the OSF at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf\u003c/span\u003e\u003cspan address=\"https://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. All analyses were preregistered with the OSF at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/r5ehx/?view_only=c697c231e5ed4b1fa6d4cf93beb54038\u003c/span\u003e\u003cspan address=\"https://osf.io/r5ehx/?view_only=c697c231e5ed4b1fa6d4cf93beb54038\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData\u003c/h2\u003e\u003cp\u003eWe used data from the Global Flourishing Study (GFS), a multinational longitudinal study with nationally representative samples from 207,919 participants across 22 countries and one territory: Argentina, Australia, Brazil, China, Egypt, Germany, Hong Kong (Special Administrative Region of China), India, Indonesia, Israel, Japan, Kenya, Mexico, Nigeria, the Philippines, Poland, South Africa, Spain, Sweden, Tanzania, Turkey, the United Kingdom, and the United States. To date, the GFS provides two waves of data. Extensive details about the GFS methodology and sample can be found in the GFS Questionnaire Development Report \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, the GFS Methodology \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, the GFS Codebook, and the GFS Translations documents \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Sample characteristics for the full sample of wave 1 can be found in the GFS study profile (VanderWeele et al., 2025), while characteristics for the sample used in this study can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics for variables involved in the analyses, n\u0026thinsp;=\u0026thinsp;20,944.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eWave 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eWave 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Dev.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStd. Dev.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlourishing Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.685\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.528\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecure flourishing Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHappiness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.638\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.839\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMental Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.958\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.561\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.491\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.825\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.736\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeaning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.677\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.463\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.631\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePurpose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship contentment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.797\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.568\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelationship satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.666\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.483\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrientation to promote good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDelayed gratification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.748\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.306\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.627\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinancial security\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaterial security\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.507\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThreat life\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.951\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.704\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.759\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoneliness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived discrimination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.728\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.943\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.925\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHealth problems\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.402\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePain-suffering\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo pain \u0026ndash; no suffering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA lot of pain \u0026ndash; no suffering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo pain \u0026ndash; A lot of suffering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA lot of pain \u0026ndash; A lot of suffering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeparated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomestic Partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployed for an employer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.357\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHomemaker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnemployed and looking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone of these/other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eup to 8 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026ndash;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.535\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.443\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of children\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.829\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eExposure.\u003c/b\u003e To create the main exposure for this analysis, we concatenated the individual pain and suffering variables from wave 1 of the GFS.\u003c/p\u003e\u003cp\u003ePain was assessed with: \u0026ldquo;How much bodily pain have you had during the past 4 weeks?\u0026rdquo; and could answer \u0026lsquo;a lot\u0026rsquo;, \u0026lsquo;some\u0026rsquo;, \u0026lsquo;not very much\u0026rsquo;, or \u0026lsquo;none at all\u0026rsquo;. Suffering was assessed with: \u0026ldquo;To what extent are you suffering? This can be any type of physical or mental suffering\u0026rdquo; Both measures were rated using a four-point response scale: \u0026lsquo;a lot\u0026rsquo;, \u0026lsquo;some\u0026rsquo;, \u0026lsquo;not very much\u0026rsquo;, or \u0026lsquo;none at all\u0026rsquo;.\u003c/p\u003e\u003cp\u003eWe produced a pain-suffering variable with 16 categories (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Since we were interested in the extremes of the pain and suffering distributions, we selected the following four categories: 1) No pain and no suffering, 2) A lot of pain and no suffering (reference category), 3) No pain and a lot of suffering, and 4) A lot of pain and a lot of suffering. This four-category variable was used in the regression analyses shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (N\u0026thinsp;=\u0026thinsp;20,944, M\u003csub\u003eage\u003c/sub\u003e=45.44\u0026thinsp;\u0026plusmn;\u0026thinsp;17.46 years, Female\u0026thinsp;=\u0026thinsp;49.8%).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCoefficients of the exposure \u0026lsquo;No pain \u0026ndash; A lot of suffering\u0026rsquo; (Ref.: \u0026lsquo;A lot of pain \u0026ndash; No suffering\u0026rsquo;) in the Global Flourishing Study (N\u0026thinsp;=\u0026thinsp;20,944).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eOutcome in Wave 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eControlling only for the relevant outcome in Wave 1\u003c/p\u003e\u003cp\u003e(1)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eControlling for additional outcomes in Wave 1\u003c/p\u003e\u003cp\u003e(2)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFlourishing Index (0\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.245\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.071)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.187\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.071)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSecure flourishing Index (0\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.201\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.069)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.171\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.062)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eHappiness (0\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.455\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.186)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.134)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLife satisfaction (0\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.507\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.163)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.402\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.106)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMental Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.479\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.122)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.385\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.109)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePhysical Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.110)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.368\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.095)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMeaning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.448\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.185)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.143)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePurpose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.551\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.114)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.293\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.111)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRelationship contentment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.471\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.196)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.315\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.134)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRelationship satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.564\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.165)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.346\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.134)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOrientation to promote good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.115)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.084)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDelayed gratification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.165)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.138)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFinancial security\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.197)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.214)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMaterial security\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.369\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.176)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.208)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eThreat life\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.080)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.082)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDepression symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.069)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.065)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAnxiety symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.075)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.046)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLoneliness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.601\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.178)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.315\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.128)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePerceived discrimination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.040)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.043)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eHealth problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0.029)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(0.028)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Table shows unstandardized coefficients from Ordinary Least Squares Regressions with standard errors clustered at the country level in parentheses. All models include demographic variables including age, gender (female, male, other), marital status (married, separated, divorced, widowed, single, domestic partner), employment status (employed for an employer, self-employed, retired, student, homemaker, unemployed and looking for a job, none of these/other), level of education (primary, secondary, tertiary), number of children, and country fixed effects. Full models can be found in Tables S.1 and S.2 in the SM. Models in column 2 also controlled for Secure Flourishing Index values, threat life, depression symptoms, anxiety symptoms, loneliness, perceived discrimination, and health problems in wave 1. These full models can be found in Tables S.3 and S.4 in the SM.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEach cell corresponds to a different regression\u003c/b\u003e. For example, the first coefficient \u0026minus;\u0026thinsp;0.245 is the coefficient of Flourishing as a function of the pain-suffering category \u0026lsquo;No pain \u0026ndash; A lot of suffering\u0026rsquo; (Ref.: \u0026lsquo;A lot of pain \u0026ndash; No suffering\u0026rsquo;).\u003c/p\u003e\u003cp\u003e\u003cb\u003eScale of outcomes\u003c/b\u003e: Flourishing (0\u0026thinsp;=\u0026thinsp;Low-10\u0026thinsp;=\u0026thinsp;High), happiness (0\u0026thinsp;=\u0026thinsp;Extremely unhappy-10\u0026thinsp;=\u0026thinsp;Extremely happy), life satisfaction (0\u0026thinsp;=\u0026thinsp;Not at all satisfied-10\u0026thinsp;=\u0026thinsp;Completely satisfied), physical and mental health (0\u0026thinsp;=\u0026thinsp;Poor-10\u0026thinsp;=\u0026thinsp;Excellent), meaning (0\u0026thinsp;=\u0026thinsp;Not at all-10\u0026thinsp;=\u0026thinsp;Completely), orientation to promote good and delayed gratification (0\u0026thinsp;=\u0026thinsp;Not true-10\u0026thinsp;=\u0026thinsp;Completely true), purpose, relationship contentment and relationship satisfaction (0\u0026thinsp;=\u0026thinsp;Strongly disagree-10\u0026thinsp;=\u0026thinsp;Strongly agree), financial security and material security (0\u0026thinsp;=\u0026thinsp;Low-10\u0026thinsp;=\u0026thinsp;High). Threat life (1\u0026thinsp;=\u0026thinsp;Not at all-4\u0026thinsp;=\u0026thinsp;A lot)), depression symptoms and anxiety symptoms (1\u0026thinsp;=\u0026thinsp;Not at all 4\u0026thinsp;=\u0026thinsp;Nearly every day), loneliness and perceived discrimination (0\u0026thinsp;=\u0026thinsp;Never to 10\u0026thinsp;=\u0026thinsp;Always), health problems (0\u0026thinsp;=\u0026thinsp;No, 1\u0026thinsp;=\u0026thinsp;Yes).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutcomes.\u003c/b\u003e We analysed a total of 20 outcomes, including the Flourishing and Secure Flourishing Indexes (2), their components (12), and distress-related variables (6). Wave 2 values of these variables were used as dependent variables, and their baseline values from wave 1 were used as covariates. The exact wording for the measures used in this study can be found at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cos.io/gfs-wave-data\u003c/span\u003e\u003cspan address=\"https://www.cos.io/gfs-wave-data\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eFollowing previous work (VanderWeele, 2017), we created a Flourishing Index and a Secure Flourishing Index. The Flourishing Index included five domains with two components each: (i) happiness and life satisfaction, (ii) physical and mental health, (iii) meaning and purpose in life, (iv) character and virtue, and (v) close social relationships. Responses to wave 2 items for the components within each domain were first averaged, and the five domains were averaged for a Flourishing Index score (α\u0026thinsp;=\u0026thinsp;0.86). The Secure Flourishing Index comprises the five Flourishing Index domains plus a sixth domain of financial and material security. Scores for the six domains were averaged to obtain a Secure Flourishing Index score (໿α\u0026thinsp;=\u0026thinsp;0.83). The same procedure was used to create the Flourishing Index (α\u0026thinsp;=\u0026thinsp;0.85) and Secure Flourishing Index (α\u0026thinsp;=\u0026thinsp;0.80) in wave 1 (VanderWeele et al., 2025). Following prior work \u003csup\u003ee.g., 12\u003c/sup\u003e, the 12 individual items were also analysed separately as specific indicators.\u003c/p\u003e\u003cp\u003eThe six distress-related wave 2 variables included: (i) threat life (how much the respondent was bothered by the most serious threat to life they have witnessed or experienced), (ii) frequency of depression symptoms, (iii) frequency of anxiety symptoms, (iv) frequency of loneliness, (v) frequency of perceived discrimination, and (vi) health problems.\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eWe conducted 20 Ordinary Least Squares regressions, one for each wave 2 outcome. Models regressed each individual outcome on the pain-suffering exposure, the respective outcome in wave 1, and all demographic variables in wave 1. All models included country fixed effects to account for common factors in each country and clustered the standard errors at the country level to account for the correlation of responses from people living in the same country.\u003c/p\u003e\u003cp\u003eAs a sensitivity analysis, we repeated these 20 models with additional wave 1 covariate adjustment for Secure Flourishing Index values, threat life, depression symptoms, anxiety symptoms, loneliness, perceived discrimination, and health problems.\u003c/p\u003e\u003cp\u003eWe conducted complete-case analyses since attrition from wave 1 to wave 2 in the two pain-suffering categories of interest was relatively low: \u0026lsquo;no pain-a lot of suffering\u0026rsquo; (4.84% of the total sample) and \u0026lsquo;a lot of pain-no suffering\u0026rsquo; (4.68% of the total sample). See additional comments below.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the percentage of individuals across the 16 categories of the wave 1 pain-suffering variable (N\u0026thinsp;=\u0026thinsp;206,882). The co-occurrence of pain-suffering at the same level is quite common, with categories representing some of both (16.4%) and a little of both (16.9%) showing comparatively higher percentages. The four categories of the pain-suffering concatenation that formed the focal predictor in our main analysis have varied representation: (i) No pain and no suffering (12.8%), (ii) A lot of pain and no suffering (0.78%, N\u0026thinsp;=\u0026thinsp;1,628), (iii) No pain and a lot of suffering (0.8%, N\u0026thinsp;=\u0026thinsp;1,686), and (iv) A lot of pain and suffering (4.6%).\u003c/p\u003e\u003cp\u003eTo conduct the main inferential analyses, we restricted the sample to these four pain-suffering categories, resulting in a sample of 20,944 individuals. With this restriction, proportions in each category were as follows. The proportion of people who reported a lot of one and none of the other was relatively similar: \u0026lsquo;a lot of pain and no suffering\u0026rsquo; (3.8%), and \u0026lsquo;no pain and a lot of suffering\u0026rsquo; (3.9%). While the majority of people in this sample reported no pain and no suffering (69.6%), a smaller proportion reported a lot of pain and a lot of suffering (22.7%). Roughly half (49.8%) of participants were female (Std. Dev.= 0.5), and the mean age was 45.44 years (Std. Dev.= 17.26). In this sample, average responses to the wellbeing and distress variables were similar across wave 1 and wave 2. Descriptive statistics for all variables are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eColumn 1 in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that after controlling for wave 1 demographic characteristics and the prior value of the respective outcome, those who experienced \u0026lsquo;no pain and a lot of suffering\u0026rsquo; (compared to those who experienced \u0026lsquo;a lot of pain and no suffering\u0026rsquo;) reported a greater decline in scores on the Flourishing Index (\u003cem\u003eb\u003c/em\u003e= -0.245, \u003cem\u003eβ\u003c/em\u003e= -0.025, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.002, 95%CI[-0.393, -0.096]) and the Secure Flourishing Index (\u003cem\u003eb\u003c/em\u003e= -0.201, \u003cem\u003eβ\u003c/em\u003e= -0.021, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.008, 95%CI[-0.343, -0.057]), happiness (\u003cem\u003eb\u003c/em\u003e= -0.455, \u003cem\u003eβ\u003c/em\u003e= -0.033, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.023, 95%CI[-0.841, -0.068], life satisfaction (\u003cem\u003eb\u003c/em\u003e= -0.507, \u003cem\u003eβ\u003c/em\u003e= \u0026minus;\u0026thinsp;.035, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.005, 95%CI[-0.845, -0.168]), mental health (\u003cem\u003eb\u003c/em\u003e= -0.479, \u003cem\u003eβ\u003c/em\u003e= -0.036, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.001, 95%CI[-0.731, -0.225]), meaning (\u003cem\u003eb\u003c/em\u003e= -0.448, \u003cem\u003eβ\u003c/em\u003e= -0.033, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.024, 95%CI[-0.831, -0.065]), purpose (\u003cem\u003eb\u003c/em\u003e=-0.551, \u003cem\u003eβ\u003c/em\u003e= -0.040, \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.\u003c/em\u003e001, 95%CI[-0.787, -0.314]), relationship contentment (\u003cem\u003eb\u003c/em\u003e= -0.471, \u003cem\u003eβ\u003c/em\u003e= -0.035, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.025, 95%CI[-0.876, -0.064]), relationship satisfaction (\u003cem\u003eb\u003c/em\u003e= -0.564, \u003cem\u003eβ\u003c/em\u003e= -0.041, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.003, 95%CI[-0.906, -0.221]), material security (\u003cem\u003eb\u003c/em\u003e= -0.369, \u003cem\u003eβ\u003c/em\u003e= -0.020, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.047, 95%CI[-0.733, -0.005]), and a greater increase in loneliness (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.601, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.003, 95%CI[0.232, 0.969]) in wave 2. Full models can be found in Tables S.1 and S.2 in the Supplemental Materials.\u003c/p\u003e\u003cp\u003eAfter simultaneously adjusting for prior values of the full set of wave 1 outcomes (column 2, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), the strength of associations for several outcomes generally attenuated but in many cases remained substantial: Flourishing Index (\u003cem\u003eb\u003c/em\u003e= -0.187, \u003cem\u003eβ\u003c/em\u003e= -0.019, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.015, 95%CI[-0.334, -0.040]), Secure Flourishing Index (\u003cem\u003eb\u003c/em\u003e= -0.171, \u003cem\u003eβ\u003c/em\u003e= -0.017, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.012, 95%CI[-0.299, -0.042]), life satisfaction (\u003cem\u003eb\u003c/em\u003e= -0.402, \u003cem\u003eβ\u003c/em\u003e= -0.027, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.001, 95%CI[-0.622, -0.181]), mental health (\u003cem\u003eb\u003c/em\u003e= -0.385, \u003cem\u003eβ\u003c/em\u003e= -0.029, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.002, 95%CI[-0.611, -0.160]), purpose (\u003cem\u003eb\u003c/em\u003e= -0.293, \u003cem\u003eβ\u003c/em\u003e= -0.021, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.015, 95%CI[-0.522, 0.063]), relationship contentment (\u003cem\u003eb\u003c/em\u003e= -0.315, \u003cem\u003eβ\u003c/em\u003e= -0.023, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.028, 95%CI[-0.593, -0.037]), relationship satisfaction (\u003cem\u003eb\u003c/em\u003e= -0.346, \u003cem\u003eβ\u003c/em\u003e=, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.017, 95%CI[-0.624, -0.067]), loneliness (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.315, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.023, 95%CI[0.048, 0.581]). The association with physical health became statistically significant and positive (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.368, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.001, 95%CI[0.171, 0.565]). Full models can be found in Tables S.3 and S.4 in the Supplemental Materials.\u003c/p\u003e\u003cp\u003eTo shed some light on cross-country variations, we estimated the distribution of our pain-suffering variable in each country. This is shown in Table S.5. While in most countries the \u0026lsquo;no pain-no suffering\u0026rsquo; category had the highest percentage of respondents, in some countries like Philippines and Turkey the \u0026lsquo;a lot of pain-a lot of suffering\u0026rsquo; category had the highest percentage of respondents. Regarding the other categories, some countries like Brazil, Egypt, Indonesia, and South Africa had the highest percentage of respondents in the \u0026lsquo;a lot of pain \u0026ndash; no suffering\u0026rsquo; category whereas some other countries like Argentina, Germany, India, Philippines, and Turkey had the highest percentage of respondents in the \u0026lsquo;no pain \u0026ndash; a lot of suffering\u0026rsquo; category.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is, to the best of our knowledge, the first study to use longitudinal data from general population samples across geographically and culturally diverse countries to document potential effects of experiencing pain without suffering versus suffering without pain on wellbeing and distress. Our findings shed new light on both the co-occurrence and dissociation of pain and suffering and help to address an important gap in our understanding of whether experiencing pain without suffering differs in its implications for individual functioning relative to experiencing suffering without pain.\u003c/p\u003e\u003cp\u003eFirst, we document that experiences of pain and suffering do not always co-occur. In our sample, some individuals reported pain without suffering and others reported suffering without pain. Second, our regression analyses showed that those who reported \u0026lsquo;no pain and a lot of suffering\u0026rsquo; had worse subsequent wellbeing (and to a lesser extent worse distress) on a range of outcomes compared to those who reported \u0026lsquo;a lot of pain and no suffering\u0026rsquo;. Those who experienced \u0026lsquo;no pain and a lot of suffering\u0026rsquo; reported comparative lower subsequent flourishing, secure flourishing, happiness, life satisfaction, mental health, relationship contentment, relationship satisfaction, and material security than those who experienced \u0026lsquo;a lot of pain and no suffering\u0026rsquo;. These findings suggest that experiencing only suffering may lead to a greater decline in some aspects of wellbeing compared to experiencing only pain.\u003c/p\u003e\u003cp\u003eThird, we show that for the six distress-related outcomes, people who experienced suffering without pain (versus pain without suffering) reported greater subsequent loneliness. For the other outcomes\u0026mdash;such as anxiety and depression\u0026mdash;little evidence of a difference was observed. This suggests that when it comes to psychological distress, suffering and pain may have more similar effects, possibly related to the shared negative affective components embedded in both experiences \u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. This potential pain-suffering-distress overlap might also be seen as being in line with prior work that showed that ໿acetaminophen (widely known as paracetamol) can reduce the pain that arises from social rejection by reducing the neural responses in regions of the brain that have been associated with distress \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The bidirectional link between pain and negative emotions \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, along with the biopsychosocial model of pain that suggests that biological and psychosocial aspects underlie the experience of pain, also supports these ideas \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In contrast to the clearer distinctions observed in positive wellbeing outcomes, the overlap in negative emotional content might explain why these two states appear less differentiated in their association with various forms of subsequent distress.\u003c/p\u003e\u003cp\u003eAfter adjusting for the full set of wave 1 outcomes simultaneously, a notable shift emerged pointing to a possible suppression effect: physical health became significantly more positive among those who reported only suffering compared to those who reported only pain. This suggests that pain may be more directly tied to physical health, while suffering may be more strongly linked to mental, social, and emotional domains. This finding raises important questions about the way pain is assessed in both research and practice. Specifically, it prompts consideration of whether pain measures should distinguish between physical and other categories of pain (e.g., psychological, social)\u0026mdash;as their implications for wellbeing might differ meaningfully. Current tools often conflate these dimensions, which could obscure critical distinctions in how individuals experience and report pain and suffering. More research in this area is needed.\u003c/p\u003e\u003cp\u003eOne of the limitations of this study is the potential impact of differential attrition between wave 1 and wave 2, with those who had better wellbeing on some wave 1 indicators showing a higher likelihood of dropping out of the \u0026lsquo;no pain-a lot of suffering\u0026rsquo; group than the \u0026lsquo;a lot of pain-no suffering\u0026rsquo; group (see Tables S.6 and S.7 in the SM). Although such attrition will not bias analyses if it is non-differential conditional on covariates, differential dropout may nonetheless influence the generalizability of the findings by reducing the representativeness of the \u0026lsquo;no pain-a lot of suffering\u0026rsquo; group at wave 2. Another limitation is that, while we employed a longitudinal design with staggered measurement of key variables at two time points assessed with a lag of about one year, we cannot make definitive claims about causal relationships.\u003c/p\u003e\u003cp\u003eAlso, although we used data from 22 countries, our results may not be generalizable to other regions and cultures \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Future research should explore whether these findings hold in other countries and cultural contexts. Finally, our measures of pain and suffering used a 4-point scale, which did not allow us to conduct a more detailed exploration of levels of pain and suffering. However, the data used here is the only one currently available that measured these two concepts with the exact same scale, allowing us to explore the co-occurrence (or not) of pain and suffering while minimizing the noise that different scales might bring.\u003c/p\u003e\u003cp\u003eBy showing that pain-suffering experiences are differently linked to subsequent wellbeing and distress outcomes, this study highlights the importance of distinguishing these two concepts. This work lays the groundwork for future research on the conceptual and semantic differences between pain and suffering. In practice, understanding the difference between experiences and implications of pain versus suffering is important for employing appropriate measures and intervention strategies to support the wellbeing of those affected by these distinct forms of distress.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u003c/strong\u003e Tyler VanderWeele reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArtificial intelligence:\u0026nbsp;\u003c/strong\u003eNo.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics:\u003c/strong\u003e Secondary data was used, thus, institutional ethical approval was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreregistration:\u003c/strong\u003e All analyses were preregistered with the Open Science Framework (OSF) at https://osf.io/r5ehx/?view_only=c697c231e5ed4b1fa6d4cf93beb54038.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials:\u003c/strong\u003e All study materials are publicly available (https://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData:\u003c/strong\u003e The data that support the findings of this article are openly available on the Open Science Framework. The specific dataset used was wave 1 and 2 non-sensitive Global data https://www.cos.io/gfs available February 2024 - March 2026 via preregistration and publicly from then onwards. Researchers interested in working with these data before March 2026, need to preregister their analysis. No specific additional registration is needed to access the data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis scripts:\u003c/strong\u003e Code for analyses can be found in Open Science Framework (OSF) at https://osf.io/84kcb/?view_only=85b9b9cab46c4553942d19f2abec36bf\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: RC and LM designed the analyses, LM conducted the analyses, LM wrote the first draft of the paper, RC and TVV provided revisions.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMacchia, L. 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Constraints on Generality (COG): A proposed addition to all empirical papers. \u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e 12, 1123\u0026ndash;1128 (2017).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7933890/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7933890/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePain and suffering often co-occur, but sometimes they occur relatively independently. Little is known about whether experiencing pain without suffering might have unique implications for individual functioning compared to experiencing suffering without pain. Leveraging longitudinal data from a diverse and international sample of individuals across 22 countries and one territory (N\u0026thinsp;=\u0026thinsp;20,944), we explored potential differences between these concatenations of pain and suffering on 20 subsequent distress and wellbeing outcomes. Adjusting for demographic characteristics, baseline values of the respective outcome, and country fixed effects, regression analyses provided evidence suggesting that those with \u0026lsquo;no pain and a lot of suffering\u0026rsquo; had worse subsequent outcomes on two composite measures of wellbeing, several specific indicators of wellbeing, and loneliness than those with \u0026lsquo;a lot of pain and no suffering\u0026rsquo;. This study highlights the importance of differentiating pain from suffering, with implications for research on these distinct forms of distress and for interventions aimed at promoting wellbeing.\u003c/p\u003e","manuscriptTitle":"Pain and Suffering Have Distinct Effects on Distress and Wellbeing:\nEvidence From a Longitudinal Multi-Country Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 11:48:35","doi":"10.21203/rs.3.rs-7933890/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ba483ada-2107-4ba2-a49e-a3ee30aad874","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57440250,"name":"Health sciences/Signs and symptoms/Pain/Chronic pain"},{"id":57440251,"name":"Health sciences/Health care/Public health"}],"tags":[],"updatedAt":"2026-03-03T21:30:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 11:48:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7933890","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7933890","identity":"rs-7933890","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}