No money be happy

no money be happy

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Data collection took place in coastal communities in the Solomon Islands and Bangladesh. In each country, we worked on two sites, one rural and one urban. The sites were selected to exemplify different societal models, cultural values, and to provide substantial variation in the degree of monetization.

Both the Solomon Islands and Bangladesh are listed as Least Developed Countries by the UN and strongly rely on small-scale fisheries for their food security and livelihoods. By focusing on small-scale fishing communities, we ensured that all sites have the possibility to have some level of subsistence without money. The selected sites contrast in their level of market integration, i. Depending on their number of households, between two and six communities were sampled within each site to cover the sample size targets.

Communities within each site were selected for logistical reasons e. The Solomon Islands are one of the largest Pacific Island states. In the Roviana region we surveyed the small-scale fishing communities of Bulelavata, Baraulu, Hapai and Olive, in which the land is customary-owned and the sea is governed by customary sea tenure.

Fishers sell their catch in the daily Gizo fish market, a small regional market for the Western Province and use the money to buy some processed foods or to pay school tuition fees, but their basic needs are in the most part covered through subsistence activities.

Bangladesh is one of the most densely populated countries in the world, The sites in Bangladesh were Nijhum Dwip and Chittagong. Nijhum Dwip, the rural site, is a relatively recent remote island created by a sand alluvium accumulation and colonized by fishermen in the early s. Most fishermen work for a patron, who provides a loan and the boat and fishing gear. Communities depend on money for certain goods and services, particularly food provision, and typically at least one household member engaged in some form of paid work, but household members were involved in subsistence activities.

Chittagong, the urban site, is the largest port in Bangladesh and the second largest city in the country. We sampled two communities in the metropolitan area, North Salimpur and Sagorika. Sagorika, being closer to the city center was more hectic and received a diverse and changing group of buyers. It is also a scenic location within Chittagong commonly visited by weekenders.

The data collection took place between April and August Every question in the surveys was designed to be as unambiguous and transferable across languages as possible, trying to reduce the possible biases and heuristics that may occur among different cultural settings [ 30 ]. A pilot study was conducted in the Solomon Islands to test the questionnaires suitability and length, and necessary adjustments in the phrasing of questions were made.

Each of the three methods had a different sampling strategy and data analysis, which are detailed below. All the statistical analyses and graphs were performed using R, version 3. Since the logistic limitations associated with the remote sites made conducting a pilot study to estimate variation in answers unfeasible, the minimum sample size per site was established at [ 31 ].

Participants were selected by random sampling from a household list of residents obtained from community leaders in the Solomon Islands, and by convenience sampling in Bangladesh due to the larger village sizes and lack of complete household registries. To reduce sampling error, communities in Bangladesh were spatially divided in a grid and convenience sampling was performed by enumerators in randomly selected areas within the grid. Mean age of participants was This gender asymmetry was due to difficulty in finding female participants, especially in Bangladesh where the proportion of female participants was only 8.

Despite our efforts to overcome the inherent logistic hurdles, the external validity of our findings is likely lower for the study sites in Bangladesh. The structured interviews lasted between 30 and 45 minutes and were designed to collect data about participants' fishing practices, sociodemographic factors, and connectedness with the global market.

Participants were asked to rate their life satisfaction which was asked as the first question of the survey to avoid biasing the participants , and respond to affect questions about the previous day, i. Of the standard life evaluation questions, SWL was employed because it uses the simplest and most straight-forward wording [ 30 , 33 ]. Another life evaluation method, used by the Gallup World Poll, is the Cantril ladder question.

After pilot testing in the Solomon Islands, it was determined that the SWL question was easier to understand to participants. SWL data were used as reported by participants. Prior studies have shown that affect balance shares variance with both life satisfaction and disaggregated measures of emotional experience at particular times [ 34 ].

Affect balance was calculated as the average of three positive and three negative emotions: sadness, anger, and worry were subtracted to happiness, enjoyment, and smiling or laughing, producing an index ranging from -1 completely negative affect balance to 1 completely positive affect balance. The mean value of each range was then converted to USD, divided by the number of household members estimated using the marital status and number of children in the household , and scaled to a yearly income per capita.

Interviews included two questions to estimate the degree of monetization, as defined in the manuscript. We asked participants to estimate: 1 the percentage of catch the main livelihood activity typically sold outside their community and 2 the percentage of food typically purchased from a store as opposed to food produced by themselves. We then calculated the mean between these percentages for each participant and represented them in a boxplot Fig 2D.

Our index is a simplification of the complex process of societal monetization and may omit important aspects of this transition. Therefore, the index is merely used to illustrate the range of cash dependency of our sites. Two-sided Kruskal-Wallis tests were used to assess the differences in SWL, affect balance and monetization index between the sites. These data can be found in the S1 Data. This method provides direct assessments by querying research subjects at random times throughout the day.

By prompting participants to answer questions about their current mood and activities, this measure avoids potential recall bias, and identifies subjective experiences that complement the emotions captured by the affect balance measure. They were called twice a day during two weeks in separate months July and August A summary of the ESM sample is shown in S2 Table ; because of the intensive sampling technique and to adhere to anonymity ethical requirements, only the gender and age of respondents was recorded.

Participants were called once in the morning and once in the evening, at random times and responded to a quick phone interview including questions about what they were doing at the moment and what emotions they were feeling. The lack of infrastructure e. Conversely, the study could be reproduced twice in consecutive months in Bangladesh. This list was prepared and then tested and refined in a pilot study in Roviana Solomon Islands.

The original data can be downloaded from the S2 Data. The percentage of positive and negative responses was calculated for each site and are reported in Fig 2C and S3 Table. Cultures with low numeracy have been reported to simplify the available scale and limit their responses to central and extreme options [ 37 ].

To test whether this effect could have modified our results, SWL answers were aggregated in a 3-point scale containing answers 0—3, 4—7, 8—10 and the same summary statistics were applied to check for consistency in the results. For the affect balance robustness test, we reproduced the Kruskal-Wallis tests with the average of the affect balance with the full set of questions that were originally asked about yesterday, a total of 7 pertaining to positive affect, and 4 pertaining to negative affective states.

To assess qualitative differences in the perceived drivers of subjective well-being, a total of participants between 66 and in each study site were selected by convenience sampling and prompted to list the three main things that make them happy. Their responses were then categorized based on similarity of concepts by peer coding [ 38 ], in which two researchers classified all responses independently and then compared their results until consensus was reached. Some responses could have been classified in more than one category, and consensus was reached during the peer coding exercise as to how to prioritize the classification of conflicting answers.

Fishing appeared frequently as it permeates many aspects of daily life in small-scale fishing communities. In the communities studied here, people engage in fishing both as subsistence and income generating activity, which could not be distinguished from their responses. Thus, if fishing was clearly referred to as an economic means e. The original responses given by participants items 1—3 and our peer coding classification codes 1—3 can be found in S3 Data.

The percentage of total responses was calculated and represented in Fig 3 of the manuscript. The distribution of all answers is shown for each site, as classified among inductive categories determined by peer coding. S5 Table shows representative examples of responses classified in each category. Three distinct clusters were obtained, and their frequency of appearance in each study site was calculated and is shown in Fig 4. The radar plot A displays the three clusters based on the grouping of the responses shown in Fig 3.

B shows the cluster distribution by site as the percentage of respondents that fall within each cluster. Despite the complex nature of SWB, the three measures showed a decreasing trend with increasing monetization Fig 2. Mean SWL in Roviana and Gizo, the less monetized sites, was not significantly different but very high 8. Affect balance showed high dispersion but was also higher in the Solomon Islands 0.

Nijhum Dwip had the lowest overall affect balance, the only discrepant measure in the study. Since affect tends to show higher sensitivity to short-term circumstances, we attribute this discrepancy to the frequent hurdles reported by participants in Nijhum Dwip, including exposure to extreme weather events, lack of hospital infrastructure, and frequent harassment by pirates [ 40 ]. Momentary affect was remarkably similar between sites in the same country. Thus, despite the inherent variability in primary data, all three measures show the highest levels of SWB at the least monetized sites.

Fig 1 illustrates the degree to which our results diverge from the expectation that happiness requires high incomes, focusing on SWL, the SWB metric that has been most strongly associated with national GDP per capita. These values do not differ substantially from that of Finland, which had the highest reported national average during our study year at 7.

For Bangladesh, SWL at our study sites was higher than the reported national average for the same year i. This possibility would be consistent with our finding that SWL in rural Nijhum Dwip was significantly higher than in the more urbanized Chittagong sites, while the latter are closer to the expected GDP-life satisfaction curve Fig 1. A potential confounding variable that is often associated with market integration is access to technology and communication networks.

Access to information from faraway cultures with different lifestyles may change the standards people have for a good life and raise the standard against which they compare their living conditions, all of which may be reflected in their SWB [ 14 ]. However, our SWB measures do not appear to show a strong bias with access to technology.

For instance, SWB at the urban site in the Solomon Islands, which is better connected, was not significantly different from the rural and more remote site, and affect balance in Nijhum Dwip was lower than Chittagong, which is greatly globalized in terms of communication. Despite the complication of within-country variation, the pattern between the study sites holds and is consistent across the three independent SWB measures: SWB decreases with the degree of monetization in our study sites.

Thus, not only may income be insufficient to measure what matters for well-being [ 1 , 3 ], but the relationship can be reversed when applied to lesser-monetized societies. To further investigate the observed discrepancy with a priori expectations, we analyzed the factors identified by respondents to be important for their happiness in each of the study sites. As with the SWB measures, the most frequently reported factors showed consistent differences between study sites Fig 3.

Pleasant activities such as listening to music, relaxing, or going for a walk by the seaside were frequently cited at the less-monetized sites, and the frequency of these factors decreased with monetization. Family factors, such as seeing parents happy or spending time with relatives, were common at all sites, but their frequency increased markedly with increasing monetization, as did the frequency of answers related to economic aspects, such as having a high income or selling their fishing catch.

Fishing and subsistence activities were more important in the rural sites, while social factors, like playing games with friends or going to parties, were more common at urban sites. To more clearly identify changes along the monetization gradient, we carried out a clustering analysis of the co-occurring happiness factors mentioned by participants, which revealed three main clusters Fig 4A. Cluster A is dominated by answers related to family and social activities.

Cluster C is dominated by answers related to economic activities or outcomes, such as having a high income. The cluster analysis indicates a consistent trend in the perceived drivers of SWB along the gradient of increasing monetization. More than half of the answers at the least monetized site were contained in Cluster B, reflecting simple pleasures and contact with nature, but the frequency of this cluster decreased steadily with monetization Fig 4B. In contrast, the more monetized sites were dominated by answers belonging to Cluster A and Cluster C, reflecting social and economic factors.

This shift could reflect cultural differences between the less monetized Solomon Islands and more monetized Bangladesh, but the observed trend is consistent with the monetization gradient. Although monetization itself is unlikely to be the only driver of this trend, we hypothesize that it may reflect a tendency for how perceptions of happiness change when societies transition from subsistence to monetized economies.

At subsistence sites, people live in close contact with nature in their everyday lives, often embedded within biodiverse ecosystems. Recent work has suggested a universal human tendency to obtain well-being benefits by spending time in natural environments [ 42 — 44 ], with a stronger effect in pristine and biodiverse environments [ 45 ], and by engaging in physical activity in nature [ 46 ].

The prevalence of Cluster B at the subsistence sites is therefore aligned with the provision of well-being benefits from the natural environment. Having a supportive and cohesive social network, or high social capital, is also widely recognized as a universal driver of SWB [ 16 ].

It might therefore appear curious that the frequency of social factors was low at subsistence sites, almost doubling across our gradient of monetization. However, because our question asked for perceived drivers of happiness, respondents were unlikely to report factors for which they had not experienced a large variation.

Thus, if respondents rarely felt a significant lack of social support, they would be less likely to list social factors as important sources of happiness. Consistent with this, traditional subsistence practices have been shown to increase kin and kith solidarity as the entire community contributes to these activities, and connect contemporary communities to cultural traditions and their elders [ 47 ].

In contrast, with increased monetization people often spend more time working, away from their close relatives, and engage in uncertain social interactions with strangers rather than in their small, close-knit subsistence communities [ 48 , 49 ]. In the same way, economic factors may barely appear in the lesser-monetized site because people do not depend on money to fulfil their basic needs, and money does not play a central role in determining self-worth.

The identified happiness drivers are therefore likely to reflect both fulfillment of perceived deficiencies and enriching experiences, dependent on learned expectations. Our findings from minimally monetized societies challenge the prevailing view that economic growth is a reliable pathway to increase subjective well-being.

While the data presented here were collected only in two countries, and must therefore be extrapolated with caution, this is the first study to our knowledge that systematically compares standardized SWB measures in minimally-monetized, very low-income societies. Culture plays a major role on how happiness is perceived and conceptualized [ 15 , 23 ], and likely has complex influences on our measures of SWB. Nevertheless, among the populations studied here, our findings are highly consistent across the three independent SWB metrics, which are unlikely to share the same cultural effects or measurement problems.

The highest SWL occurred with the least degree of monetization and was comparable to the SWL reported from high income countries. The results provide an unusually clear substantiation of the often-discussed importance of non-material and non-market determinants of SWB and raises reasonable doubts to the income-happiness debate as a whole, suggesting that this debate could be missing a part of the picture when it comes to subjective well-being.

Economic growth and development are often perceived as an essential step for improving human welfare in developing societies [ 50 ], but our findings suggest that high subjective well-being, an important component of this equation, can also be achieved by focusing directly on the drivers of SWB, such as provision of basic needs, access to healthy natural environments, and social cohesion.

Our findings also overturn the view, based on the income-happiness association, that sustainability is incompatible with high levels of happiness [ 51 ], since they prove that very high SWB can be achieved in self-sufficient societies with low material impact.

By providing a perspective far removed from the industrialized world, minimally-monetized societies may hold essential insights on the fundamental drivers of human happiness. The Kruskall-Wallis tests were run including all the study sites.

The tests included all sites. The robustness test for SWL, consisting on simplifying the scale by aggregating the responses to a central value, yielded the same patterns with sites as the full scale SWL value. For affect balance, results were slightly lower than the standard affect balance, but the same pattern was consistent across sites. This file contains the raw data collected for SWL and for the calculation of affect balance, local income, and index of monetization, along with the date, location and site for each respondent.

This file contains the raw data from phone interviews, along with participant ID, date and time of the call, and location of respondents. The authors would like to thank the local enumerators that helped collect the data in the Solomon Islands and Bangladesh, as well as the communities in the study sites for access, hospitality and patient collaboration. We are grateful for the statistics support received from A.

Heneghan for assistance with the visualization code, and to I. Savin for useful comments on the manuscript. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Economic growth is often assumed to improve happiness for people in low income countries, although the association between monetary income and subjective well-being has been a subject of debate.

Introduction While human well-being is a universal goal of public policy, most metrics used for assessing social progress rely on economic performance [ 1 ]. Download: PPT. Fig 1. Fig 2. Subjective well-being and index of monetization at the study sites.

Study sites Data collection took place in coastal communities in the Solomon Islands and Bangladesh. Data collection and analysis The data collection took place between April and August Satisfaction with Life SWL , affect balance, local income and monetization index.

Momentary affect. Robustness of SWB results. Differences in perceived drivers of happiness among sites. Results and discussion High subjective well-being with minimal monetization Despite the complex nature of SWB, the three measures showed a decreasing trend with increasing monetization Fig 2. Sources of happiness To further investigate the observed discrepancy with a priori expectations, we analyzed the factors identified by respondents to be important for their happiness in each of the study sites.

Conclusions Our findings from minimally monetized societies challenge the prevailing view that economic growth is a reliable pathway to increase subjective well-being. Supporting information. S1 Table. Summary statistics of monetization index and results from significance tests between the study sites.

S2 Table. ESM participants characteristics by site. S3 Table. Summary statistics of subjective well-being measures stratified by site. S4 Table. Summary statistics of the robustness tests for subjective well-being measures stratified by site. S5 Table. Categories used in the analysis of differences in happiness definitions. S6 Table. S1 Data. S2 Data.

Happiness is an intentional internal feeling that is an effect of chemical reactions in our body. In a study done by Michigan State University , they asked customer service workers to think of positive thoughts. Everyone just lit up like a light bulb and smiled! I think we already know that would happen! If you do not feel like smiling right now, think of a happy thought and force those muscles.

The secret here is to fake it until you make it. Take control of your thoughts. If you notice it straying to the past or future, consciously bring it back to the present — the now. Let go of all the anger and regrets you have of yesterday or your worries for tomorrow. Instead, find joy in the present. Put your focus and attention on what you are doing. Spend your time on something that you find meaningful.

Use your time to add value to yourself. Fall into the habit of being thankful for the big things, the little things and the things in between. When you have a grateful heart you become a magnet of blessings. Nobody wants to be with people who are pessimistic. Whining will not help you win! To help you with this exercise, start a gratitude journal. I encourage you to get up and exercise right in your own home or in a park!

This releases feel-good hormones and burns out stress chemicals. You get an all-natural high that is way better than Prozac! It also gives a feeling of accomplishment. Exercise outside or even take your lunch out in the open just to soak in that free vitamin D from Mr. An added bonus would be a nice tan that will give you that healthy glow. Stop complaining about the lack of provision.

Change your perspective. Happiness depends on the way you look at life and the people around you. Everything is temporary so do not let your today define your tomorrow. Stop scrolling through your Facebook or Instagram account so you would not have a constant reminder of what you are missing out. Do not compare yourself with what others have accomplished. With little money, you will be forced to live with fewer material possessions. Accept that reality and start caring less about owning more.

Owning more will only make you happy for a few moments because we will always want more. If you need to buy something, do it consciously and deliberately. Speak nicely and always find an opportunity to help. Do not be afraid to be altruistic.

Helping others adds more meaning and purpose to our lives. It has also been found out to help the release of endorphins so we feel good after doing good to others. It helps our body recover and repair so when you wake up you will be more focused and more productive. Sleep deprivation affects the hippocampus, a part of the brain where positive memories are processed. It also affects our sensitivity to negative emotions like stress, anxiety, anger, and fear.

Find time to connect with yourself through different activities like reading, meditating, praying, and journaling. This allows you to unload your daily burdens as well as plan out your next steps. A few minutes of silence per day helps your hippocampus store memories.

It can also be considered a skill. Identifying what makes you happy on. The key lesson here is to use your current financial status to discover how you can become a better version of yourself. When you look back on this period of your life you will understand that what you once thought was a stumbling block was actually a stepping stone.

It s pretty hard to maintain happiness if you hate your job. Don t waste the best years of your life in a joyless job, even if it s paying the bills.

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