Small but Certain Happiness in Daily Life: Structure and Relation with Well-Being

While micro-happiness results from recurring, everyday events, infrequent life events have a considerable impact on levels of well-being. Examples of such major events include personal and family milestones such as marriage, divorce, bereavement, and childbirth (Lucas et al., 2003; Wade & Pevalin, 2004), as well as career transitions such as securing a job, receiving a promotion, experiencing unemployment, and retiring (Judge & Watanabe, 1993; McKee-Ryan et al., 2005). These life-changing events induce fluctuating patterns of well-being in the time before and after the event, creating oscillations in well-being levels (Anusic et al., 2014; Frijters et al., 2011; Luhmann & Eid, 2009; Luhmann et al., 2012; Yap et al., 2012). In a study that combined interviews and questionnaires, Kettlewell et al. found that positive events, such as getting married and gaining money, increased LS; similarly, negative events, such as separation and losing money, also decreased LS over several years of life (Kettlewell et al., 2020).

Negative events tend to increase psychological distress and negatively affect well-being. Positive events tend to increase positive emotions and life satisfaction but do not necessarily decrease psychological distress. Therefore, the two types of events (positive and negative) are treated as independent in their effects, meaning that the occurrence of positive events does not necessarily mitigate the effects of negative events and vice versa (Zautra & Reich, 1983).

Positive events often produce an immediate increase in happiness and satisfaction. However, the intensity of these positive effects may diminish over time owing to hedonic adaptation, in which individuals return to a baseline level of happiness (Brickman, 1971; Brickman et al., 1978). Negative events typically result in immediate decreases in well-being. However, the trajectory of recovery can vary, and individuals may experience substantial long-term growth after adjusting to these events. In some cases, the negative impact can also have lasting effects if not properly addressed (Lucas, 2007). That is, negative events often have a deeper initial emotional impact than positive events. The stress, grief, or anxiety caused by negative events such as bereavement or job loss can be intense and long-lasting (Baumeister et al., 2001).

Daily life events have a considerable impact on well-being. Dining, a major daily event experienced by everyone, plays a central role in daily well-being. Block et al. propose a paradigm shift in food research, suggesting that we should consider food not only as a health factor but also as a contributor to well-being (Block et al., 2011). They introduce the concept of food well-being (FWB), defined as a positive psychological, physical, emotional, and social relationship with food at both the individual and societal levels. The inability to secure a stable, satisfying diet is a critical factor that undermines not only physical health but also mental health (Runnels et al., 2011).

Specific dietary components may also influence well-being. For example, the consumption of fruits and vegetables has been associated with increased well-being, curiosity, and creativity at both inter- and intra-individual levels (Conner et al., 2015, 2017). Additionally, adherence to a Mediterranean diet positively influences life satisfaction and reduces negative emotions (Moreno-Agostino et al., 2019).

Sleep is also a critical daily event. According to a survey of 79,625 Americans, approximately 26% of adults reported experiencing frequent sleep deprivation (14 or more days in the previous 30 days) (Strine & Chapman, 2005). These individuals were significantly more likely to report “poor health,” “high psychological distress,” “high mental distress,” “activity limitations,” “depressive symptoms,” “anxiety,” and “pain” compared with those who experienced less frequent sleep deprivation.

In another study of over 750 adolescents aged 14–15 years, the diary method was used to determine that daytime stress was associated with sleep deprivation. Specifically, overnight sleep deprivation was associated with higher levels of anxiety, depressed mood, and fatigue the following day (Fuligni & Hardway, 2006). Particularly among younger individuals, increased screen time (e.g., television, computers, video games, mobile devices) and excessive use of social media negatively impact sleep quality and mental health (Hale & Guan, 2015; Woods & Scott, 2016).

Additionally, even small amounts of habitual exercise in daily life can have beneficial effects on multiple physical and mental health outcomes (Penedo & Dahn, 2005). One review reported a positive relationship between physical activity and mental health outcomes; however, this relationship is complex. It may depend on individual factors such as age, gender, fitness level, and type of exercise (Scully et al., 1998). Behavioral restrictions were imposed during the COVID-19 pandemic, emphasizing the importance of daily exercise. The data suggest that individuals who exercised almost daily during the pandemic felt better, regardless of whether they had a pre-pandemic exercise routine. Conversely, those who exercised less frequently during the pandemic reported feeling worse than those who either maintained or increased their pre-pandemic exercise frequency (Brand et al., 2020).

Based on several previous studies, we point to the importance of examining not only the relationship between major life events and well-being but also daily events. Kanner et al. developed the Uplifts Scale, which measures daily feelings of elevated mood, and the Hassles Scale, which measures daily feelings of annoyance. They showed that the Hassles Scale was a better predictor of psychological symptoms than the life event score (Kanner et al., 1981). Thus, small daily stressors have an equal or greater impact on well-being than major life events do.

Moreover, McCullough et al. used a hierarchical regression analysis method, in which they first included the number of major life events occurring as an independent variable in the model and then, subsequently, the number of daily life events. They found that the number of positive daily life events increased life satisfaction, considered as the dependent variable, even after the effects of major life events were controlled for (McCullough et al., 2000).

Several previous studies that have contrasted how big and small events, such as life and daily events, contribute to well-being have compared the impact of daily events on daily stress with that of major life events. They have consistently shown that daily events are more strongly related to psychological and physical health than life events. These daily events are also known to mediate between major negative life events and mental health status (Chamberlain & Zika, 1990; DeLongis et al., 1982; Johnson & Sherman, 1997; Ruffin, 1993).

As mentioned in the last paragraph, the daily events addressed in previous studies are stressful events that negatively affect well-being. In this study, we focus on small, daily events that have a positive impact on well-being, such as micro-happiness. McCullough et al. (2000) directly compared the impact of daily and life events on levels of well-being for both positive and negative events and confirmed the large impact of daily events on well-being levels. However, their method for assessing the impact of daily events was to have participants review and check a list of 100 large and small mixing events prepared by the authors. Additionally, the participants of the study were adolescents and thus likely to have experienced only a small fraction of major life events. In this sense, the impact of daily events on well-being might have been overestimated.

Based on previous research, this study confirms the presence or absence of experiences of major life events and then records experiences of daily events and measures their impact. This study addresses two attributes of the experiences of daily events: frequency and certainty. Life events occur only a few times in a person’s life, whereas daily events occur frequently and consistently. With daily events, we believe that a single event does not have an impact over a long period of time but rather occurs on a regular basis to produce a certain level of well-being. In this regard, frequency is an important factor that characterizes daily events.

Furthermore, certainty may be another important attribute in the concept of micro-happiness noted in Murakami’s essay. To the author’s knowledge, no study has examined the impact of certainty of daily events on well-being.

The Japanese word “certain” has two meanings: autonomy and certainty. These are thought to contribute to improving well-being from different aspects. In general, autonomy focuses on internal factors, freedom of one’s own will, and actions, while certainty focuses on external circumstances, predictability, and reliability of things.

Autonomy supports intrinsic motivation, and individuals pursue goals and activities out of genuine interest. Feeling in control of one’s choices contributes to well-being. In the self-determination theory, autonomy is considered one of the basic psychological needs and an essential element for healthy human development (Deci & Ryan, 2000, 2013). A strong correlation exists between perceptions of autonomy and overall life satisfaction (Steckermeier, 2020).

Conversely, certainty minimizes the anxiety and stress caused by ambiguity and unpredictability and contributes to improved mental health (Massazza et al., 2022). A stable environment allows people to focus on personal growth rather than worrying about survival (Shonkoff et al., 2012). Certainty builds trust in relationships and systems and reduces social and organizational tension; it is the basis for fostering positive expectations of others and institutions (Sorrentino et al., 1995).

This research consists of two studies. Study 1 includes three surveys aiming to identify the factor structure of micro-happiness and identify representative daily events that lead to each type of micro-happiness. Study 2 comparatively examines the impact of the daily events selected in Study 1 and that of the major life events examined in previous studies on well-being levels (Anusic et al., 2014; Frijters et al., 2011; Luhmann & Eid, 2009; Luhmann et al., 2012; Yap et al., 2012).

Study 1a aimed to construct a catalog of micro-happiness from open-ended responses.

Two hundred people (96 women, 104 men; M_age = 39.7 years, SD = 9.49), recruited through a crowdsourcing service, CrowdWorks, Inc., participated in this research.

Participants were given the following instructions: “In everyday life,‘ small but certain happiness’ is referred to as micro-happiness. Please identify three examples (events) of micro-happiness that apply to you. If your examples are difficult to understand, please add a brief explanation.”

The data of one participant were lost owing to a technical problem. As a result, 597 (= 3 × 199) items were collected from the 199 respondents.

From the 597 items, 14 categories were drawn, and 62 daily event items were selected to represent these categories. These 14 categories included daily events, such as dining and sleeping, that have been the subject of well-being research. This list is available in Supplementary Material 62items.

The procedure is described below. The selection was made by two coders; one was the author of this manuscript, and the other was a 32-year-old female member of the public. The latter coder had no direct conflict of interest with the author. Additionally, she was not informed of the purpose of this study and had no involvement other than the coding and creation of the questionnaire website. As she had coding experience in several other research projects, she had sufficient training in this area.

In this procedure, the KJ method was used (Scupin, 1997). The specific steps are as follows. First, the 597 items were written on small cards (about 1cm x 5cm) one by one. Items with clearly the same content were combined on one card. The cards were placed on a desk. Cards with similar content (e.g., meals with family and meals with friends) were placed close together to form a group. At this point, cards with similar meanings constructed a category.

In the first stage, each coder independently extracted the categories. The results of the first round of category extraction showed that eleven major categories were in agreement between the two coders, but some categories were not. The categorization perspectives were discussed, followed by the second round of independent category extraction. As a result, thirteen categories matched. Finally, based on the identified categories and one category that was added through the conversation, fourteen categories were established.

Of the total 597 items collected, 512 (85.8%) were included in these 14 categories. The 512 items in the 14 categories were narrowed down to 62 items by removing duplicate items. Items related to highly personal experiences or that required special explanation were removed by the two coders by consensus.

Study 1b aimed to determine the factor structure of micro-happiness using the 62 items collected in Study 1a.

The following Study 2 will examine the relationship between the frequency and certainty of daily events and levels of well-being. To do this, we selected 18 events representative of each of the six factors identified so far.

We recruited 804 participants through a crowdsourcing service, CrowdWorks, Inc. The distribution of the control variables, including representative demographic variables, is shown in Supplementary Material DVdistribution_2.

First, the frequency and certainty of daily events experienced in everyday life were recorded. The order of the frequency and certainty measures was counterbalanced.

Second, participants were asked about their cognitive and affective aspects of well-being using the SWLS and SPANE and about whether or not they had experienced the listed major life events. If they had experienced each event, they were also asked when the event occurred.

Finally, their demographic variables were collected.

First, descriptive statistics are presented as representative variables. Table 1 shows the number of participants who reported experiencing each life event. The numbers in parentheses are percentages of the 804 participants. The table also shows the number of participants who reported experiencing the event within 1 year, between 1 and 5 years, and before 5 years.

Table 2 shows the basic statistics for the frequency of experiencing daily events and the rating of the certainty of such experiences, as well as the ratings of life satisfaction (SWLS) and positive and negative emotions (SPANE) in relation to well-being. Regarding daily events, the first five are the means of the three items that constitute the factor, and the last one, drinking, is the mean of the two items.

Table 3 shows the correlations between the frequency and certainty of daily events.

We conducted hierarchical regression model analyses to examine the relationship between major life events, daily events, and well-being levels. The following is a step-by-step description of the analysis. The R scripts used in the analysis are presented in Supplementary Material models_study2.

First, in Model 1, demographic variables were entered into the model. Then, in Model 2, variables related to the presence or absence of experiencing major life events were entered into the model. All these variables are categorical, with no experience as the reference level. In Model 3, in addition to the demographic variables, ratings related to the frequency and certainty of experiencing daily events were entered into the model. All variables related to daily events were standardized. Finally, Model 4 included the presence or absence of experiencing major life events and the frequency and certainty of experiencing daily events as well as the demographic variables.

In constructing Model 2, we excluded a life event, “marriage,” because it is closely related to a demographic variable “marriage.” When assessing multicollinearity in the model that includes the two variables, we found the VIF scores for the two variables to be 17.8 and 17.7.

Table 3 indicates that the frequency and certainty of experiencing daily events are strongly correlated, with correlation coefficients exceeding .80 for contact with nature, time spent with close people, engagement with amusement media, and drinking. When all these variables were entered into the model, the VIF scores for the frequency and certainty of these events were greater than 0.4. Consequently, the certainty variables for these events were excluded from the model, which resulted in VIF scores for all variables being kept below 0.3.

We performed a post hoc analysis using G* Power (version 3.1.9.6). With a significance level of 0.01 and a sample size of 804, the power to detect the increase in R² in models 2 to 4 exceeded 0.98 for all models.

Tables 4, 5, and 6 show the results of the regressions.

First, we examine the impact of the two types of events (major and daily) on levels of well-being by comparing Model 1 as the baseline model, with Model 2, which adds whether or not major life events were experienced, and Model 3, which adds the frequency and certainty of experiencing daily events.

The base model (Model 1), which includes demographic variables, explains 28.2% of the variance in life satisfaction. Adding major life events (Model 2) increases the R² by 7.2 percentage points to 35.4%, indicating a significant relationship with these events. Including daily events (Model 3) increases the R² to 40.2%, an additional 12.0 percentage points, from the baseline model (Model 1). These results show that the relationship between both major and daily events and life satisfaction are simultaneously large, but daily events have a relatively stronger relationship.

For positive emotions, the initial model (Model 1) explains 29.1% of the variance. Adding major life events (Model 2) increases the R² by 4.2 percentage points to 33.4%. Adding daily events (Model 3) significantly increases the R² to 43.2%, with a substantial increase of 14.1 percentage points. These results suggest that daily events have a stronger relationship with positive emotions in daily life than major life events.

Conversely, the effect on negative emotions was different from that on positive emotions. The initial model (Model 1) explains 21.1% of the variance in negative emotions. Adding major life events (Model 2) increases the R² by 5.2 percentage points to 26.3%. Adding daily events (Model 3) also increases the R² by 3.5 percentage points, but only to 24.6%. The results suggest that the relationship between negative emotions and daily events may be slightly smaller than that with major life events.

Model 4, which adds daily events to Model 2, which includes major life events, better explains both life satisfaction and positive and negative emotions. However, the increase in explanatory power from Model 2 was 10.1% for life satisfaction and 14.1% for positive emotions, while it was only 3.4% for negative emotions.

The results regarding the impact of each major life event on well-being were not surprising. In Model 2, which included variables for the presence or absence of experiencing life events, three positive events, i.e., financial gains, birth of a child, and promotion, are positively related to life satisfaction, and four negative events, i.e., financial loss, unemployment, illness, and natural disaster, are negatively related to life satisfaction.

As for the affective aspects of well-being, three positive events are positively related to positive emotions and three negative events are negatively related to positive emotions, while three positive events are negatively related to negative emotions and two negative events are positively related to negative emotions (see Tables 4, 5 and 6 for details).

As for daily events, in Model 3, the frequency of experiencing daily events related to micro-happiness, such as contact with nature, time with close people, and personal relaxation, were positively related to life satisfaction and positive emotions. The frequency of drinking was also positively related to life satisfaction. Conversely, only personal relaxation showed a significant negative relationship with negative emotions.

Unexpectedly, the frequency of contact with nature is not only positively related to positive emotions but also positively related to negative emotions. Additionally, the frequency of drinking, which was positively related to life satisfaction in Model 3, becomes negatively related to positive emotions and positively related to negative emotions in Model 4, which takes into account the experience of major life events. These unexpected findings are discussed in the following Discussion section.

Finally, we note the relationship between certainty of event occurrence and well-being. In a series of analyses, we had to exclude variables related to four daily events to avoid multicollinearity. Even for the two remaining events, the certainty was not significantly related to any of the well-being indicators.

The first interest of this research is to elucidate the structure of micro-happiness. In Study 1a, the participants were asked to describe, in free form, examples of micro-happiness experienced daily. Based on the catalog of micro-happiness events collected, two exploratory factor analyses were conducted in Studies 1b to identify the underlying factor structure. Six factors were extracted as a result of the exploratory factor analysis in Study 1b and confirmed by the confirmatory factor analysis in Study 1c.

Specific events that have been central to well-being research related to everyday activities, such as dining and sleeping, were not extracted as individual factors. Instead, they were combined with other events to form a single factor. For example, sleep, exemplified by “Getting a good night’s sleep (K11),” was combined with items such as “having free and liberated time without work or housework (K57)” and “Having time alone without any demands (K58)” to form a factor called “personal relaxation.”

The fifth factor, daily chores, consists of household activities (K6 and K61) and doing strength training (K59). Exercise such as strength training is involved in a representative daily event that increases well-being, which was referred to in the introduction of this paper. Superficially, this event and daily chores seem to have nothing to do with each other. However, from the point of view of experience, they share various common features, such as exercise and movement, sense of accomplishment, establishment of routine, skill improvement, and health benefits. Based on these commonalities, this factor might have been drawn from different types of daily events.

In some cases, items that relate to a specific event, such as eating and sleeping, were separately assigned to more than one factor. Specifically, from the perspective of events, the items “eating a delicious meal (K1),” “eating alone in a relaxed atmosphere (K3), “eating with family (K4),” and “having midnight snacks (K7)” are all related to eating. Conversely, from the perspective of micro-happiness, they are classified into different factors. Specifically, enjoying a delicious meal alone while relaxing (K1 and K3) is assigned to “personal relaxation”; eating with family (K4) is assigned to “time spent with close people,” and having midnight snacks (K7) is assigned to “engagement with amusement media.” The last example is assigned to this factor because when we pick up a snack, we often snack while doing something else that is enjoyable rather than just eating it.

The micro-happiness conceptualized in this paper is closely related to daily events. At the stage of creating the initial set of micro-happiness items, participants were asked to “give examples of small but certain happiness in everyday life.” Although participants were not asked to mention events in their daily lives at this point, most of the items submitted were related to events that occur in their daily lives. On the other hand, the above discussion suggests that micro-happiness is not the event itself but is structured based on the experience created with the event. While most studies of everyday well-being have examined it based on recurring individual events, such as eating and sleeping (Block et al., 2011; Fuligni & Hardway, 2006; Runnels et al., 2011; Strine & Chapman, 2005), our results suggest the importance of taking a cross-sectional view of these events and focusing the discussion on the experiences they encompass.

The second interest of this study is to contrast the impact of daily events with the impact of major life events on well-being. We measured life satisfaction from the cognitive aspect and positive and negative emotions from the affective aspect of well-being. Controlling for demographic variables, we found that major life events explained 7.2%, 4.2%, and 5.2% of life satisfaction and positive and negative emotions, respectively (from Model 1 to Model 2), while daily events explained 12.0%, 14.1%, and 3.5%, respectively (From Model 1 to Model 3). Furthermore, after controlling for both demographic variables and the presence of major life events, we observed that daily events still explained 10.1%, 14.1%, and 3.4% of life satisfaction and positive and negative emotions, respectively (from Model 2 to Model 4). These results suggest that daily events have important implications for explaining levels of well-being.

Regarding the difference in the contribution of major life events and daily events to well-being, for life satisfaction and positive emotions, especially for positive emotions, daily events showed greater involvement than major life events. Conversely, for negative emotions, daily events showed slightly less involvement than major life events.

Psychological evidence suggests that decreasing negative emotions can be particularly challenging and often requires more structured training than increasing positive emotions (Nezlek & Kuppens, 2008).

Humans tend to pay more attention to negative information and experiences, known as the negativity bias. This bias makes it more difficult to reduce negative emotions because negative experiences can dominate attention and memory (Ito et al., 1998).

Negative emotions, such as fear, anger, and sadness, often occur automatically and can be more intense and difficult to control than positive emotions. This automatic response is thought to be evolutionarily adaptive because it helps individuals respond quickly to threats (Nesse & Ellsworth, 2009).

All daily events that produced micro-happiness in this study were associated with internal, action-related experiences, which in turn were positively associated with positive emotions. However, modifying beliefs and reinterpreting the meaning of events may be important in modifying strong negative emotions such as anger and disappointment.

Well-known methods exist for reducing negative emotions, such as cognitive behavioral therapy (Hofmann et al., 2012), expressive writing (Baikie et al., 2012), and self-compassion (Neff, 2011). These are all methods of self-reflection and modify one’s self-awareness from a meta-perspective. Combined, they can have an even greater impact on improving well-being.

We found three daily events related to micro-happiness that are positively associated with levels of well-being.

First, the most predictive factor was “time spent with close people.” These findings are consistent with those of numerous previous studies indicating that social relationships are the most important factor in well-being.

The Study of Adult Development at Harvard Medical School conducted the longest follow-up study of adults in history, following 724 men from 1938 to 1980, identifying good social relationships as a key to good health and happiness. A large body of research supports that robust social relationships are the most important factor in improving subjective well-being (Diener & Seligman, 2002; Helliwell & Putnam, 2004; Pinquart & Sörensen, 2000).

Second, “personal relaxation” was also an important factor. The relationship between mental and physical relaxation and well-being is a well-documented area in positive psychology and health sciences. Mental relaxation includes activities that calm the mind and reduce psychological stress. Practices such as mindfulness meditation (Davidson et al., 2003), deep breathing exercises (Perciavalle et al., 2017), and journaling (Smyth et al., 2018) have been extensively studied and found to be effective in promoting mental health. Physical relaxation involves activities that reduce physical tension and promote physical relaxation. Techniques such as yoga (Hendriks et al., 2017) and tai chi (Taylor-Piliae & Finley, 2020) are commonly used to achieve this.

The third factor was “contact with nature.” Numerous studies have shown that exposure to nature has a significant effect on improving affective well-being as follows. A meta-analysis of 32 studies found that exposure to natural environments resulted in a moderate increase in positive emotions and in a relatively small but consistent decrease in negative emotions compared to the comparison conditions (McMahan & Estes, 2015). These effects were also observed in everyday scenarios. Specifically, after a 50-minute walk in either a natural or urban environment, maintenance of positive emotions and a decrease in negative emotions were observed when walking in the natural environment compared to the urban environment (Bratman et al., 2015). Additionally, even brief visits to natural areas within an urban setting are effective in reducing stress (Bratman et al., 2015).

Contrary to expectations, the multiple regression analysis showed that contact with nature was positively correlated not only with positive emotions but also with negative emotions. One interpretation is that contact with nature evoked specific emotions such as nostalgia. While nostalgia is generally thought to positively contribute to well-being, nostalgic experiences often involve bittersweet memories, such as disappointments and losses, including separation and even the death of loved ones (Sedikides et al., 2008).

Nostalgia also induces negative emotions, such as the recollection of painful past experiences and the associated suffering and sadness (Layous et al., 2021).

Another interpretation is that contact with nature did not induce negative emotions but that negative emotions increased the frequency of contact with nature. Contact with nature is effective in healing and reducing stress. When the participants felt difficult emotions, they might have actively tried to contact nature to alleviate them. Mindfulness reduces daily stress and contributes to improved well-being, and evidence shows a direct relationship between contact with nature and mindfulness (Djernis et al., 2019; Lymeus et al., 2018).

Inferring a causal relationship between major life events and happiness is relatively easy. Assuming that marriage caused positive emotions is more natural than to assume that positive emotions caused marriage, whereas the relationship between daily events and levels of well-being is likely to be more interdependent. This point must be fully considered when interpreting the results of this study.

From a Japanese cultural perspective, nature is often experienced in ways that encompass both beauty and transience, creating an emotional “ bittersweetness” rather than purely positive or negative feelings. Two key concepts help explain why contact with nature might correlate with negative emotions—even as it promotes well-being:

Often translated as the “pathos of things,” mono no aware underscores a sensitivity to the fleeting nature of all phenomena (Prusinksi, 2012). While it heightens appreciation for the present moment—such as when watching cherry blossoms bloom—it also brings into focus how quickly these moments end. This awareness can evoke gentle sadness or nostalgia.

Closely related to mono no aware, wabi-sabi celebrates imperfection, impermanence, and the humble beauty found in everyday life. Contact with nature—particularly when one notices a lone, faded flower or the patina of weathered wood—can evoke a contemplative mood that includes sorrow or longing alongside awe and peace.

In sum, the positive correlation between contact with nature and negative emotions is understandable through the lens of Japanese culture: nature evokes a powerful sense of transience, imperfection, and deeper reflection (mono no aware and wabi-sabi) (Asquith et al., 1997). These concepts naturally give rise to sadness or nostalgia alongside the comfort and peace that come from immersing oneself in the natural world.

In the regression analysis of Model 3, the frequency of drinking was positively related to life satisfaction. However, in the regression of Model 4 with life events as a control variable, this relationship disappeared, and a negative relationship with positive emotions and a positive relationship with negative emotions emerged.

Moderate alcohol consumption is associated with positive psychological outcomes such as subjective health, mood improvement, stress reduction, sociability, social integration, mental health, and long-term cognitive functioning (Peele & Brodsky, 2000). Alcohol consumption can both relieve negative emotions and enhance positive emotional experiences, depending on the conditions under which it is consumed (Sayette, 2017). As indicated in these studies, moderate alcohol consumption contributes positively to levels of well-being.

Conversely, our study suggests that the effects of drinking may be confounded, to some extent, by other factors such as those related to life events. Or, at least, previous studies might have overestimated the positive contribution of alcohol consumption to well-being (Fillmore et al., 2006; Stockwell et al., 2016). That is, people who experience positive life events may have more opportunities to drink owing to economic benefits and good relationships, which in turn may be observed as an increase in well-being.

Participants were not given a specific definition of the word “certain,” whereas most of the events related to micro-happiness that the participants reported were routine events repeated in everyday life. The participants might have understood the word “certain” in relation to the concept of routine. As mentioned before, “certain” can be thought of as having two attributes, autonomy and certain, and routine is a concept that combines both. However, the results of Study 2 showed that the effect of “certain” on each well-being indicator was extremely small compared to frequency. The results of this study showed a strong correlation between the frequency of daily events and the certainty of their occurrence. In fact, when the two variables were entered simultaneously in the regression model, they exhibited strong multicollinearity, which precluded the analysis of both as independent variables in this study. Conceptually, the frequency of an event and its certainty are independent concepts. The philosopher Hume made this point in his An Enquiry Concerning Human Understanding, published in 1748. Specifically, Hume mentioned that the problem of induction challenges the idea that we can be certain about future events based on past events. He argued that just because the sun has risen every day in our experience, it does not guarantee that it will rise tomorrow; our belief that it will rise is based on habit rather than logical certainty.

From a psychological perspective, the frequency of events can influence our perception of their certainty owing to cognitive biases such as availability heuristic (Tversky & Kahneman, 1973). This heuristic suggests that individuals estimate the likelihood of an event based on how easily examples of the event come to mind. Therefore, if an event occurs frequently, it is more likely to be remembered, and people may overestimate its likelihood. In fact, imagining an event increases its subjective likelihood owing to the availability heuristic, making it easier to predict its outcome (Carroll, 1978). As predicted by the availability heuristic, recall latency for past events is negatively correlated with the perceived future probability of similar events (MacLeod & Campbell, 1992).

As mentioned in the Introduction section, in Japan, the cultural background seems to connect such micro-happiness with the small events of everyday life. This study was conducted with a Japanese population, which may limit the generalizability of the findings to other cultural or demographic contexts. Cultural differences may significantly influence how daily and major life events are perceived and their impact on well-being. Future studies could replicate the research with diverse populations in different cultural settings to increase external validity and understand cultural differences in micro-happiness and well-being.

The second limitation relates to the measurement of events. This study is based on data collected through an online questionnaire. Future research should explore these findings in greater depth using various methodologies. One methodological approach categorizes the measurement of experiences in everyday life events into three distinct types: interval-contingent, signal-contingent, and event-contingent (Wheeler & Reis, 1991). The use of digital tools and mobile applications to track daily events and well-being could provide more objective and accurate data and reduce reliance on self-report measures (Areán et al., 2016).

Third, the cross-sectional nature of the study limits the ability to make causal inferences about the relationship between micro-happiness and well-being. Longitudinal or experimental designs are needed to make more robust causal inferences.

Fourth, broadening the scope into intervention research is also necessary. Well-being studies have attempted to improve well-being through relatively simple, actionable behaviors. From a positive psychology perspective, interventions such as counting blessings, practicing kindness, setting personal goals, expressing gratitude, and using personal strengths are effective (Bolier et al., 2013). Moreover, ample evidence has shown the effectiveness of mindfulness-based (Khoury et al., 2015) and physical activity (Netz et al., 2005) interventions. Will the components of daily events related to micro-happiness identified in this study have similar intervention effects? If their effectiveness is validated, their practical importance as a method for improving well-being would be substantial.