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The dynamics of well-being in daily life: a multilevel perspective

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Content 1

The Dynamics of Well-Being in Daily Life: A Multilevel Perspective

David B. Newman
Department of Psychology
Social Psychology
Doctor of Philosophy
University of Southern California
Faculty of the USC Graduate School
August 15, 2019

2
Table of Contents

Acknowledgements………………………………………………………………………… 3
Introduction………………………………………………………………………………… 4
Chapter I: Nostalgia and Well-Being in Daily Life: An Ecological Validity Perspective… 10
Transition…………………………………………………………………………………... 68
Chapter II: Global Reports of Well-Being Overestimate Aggregated Daily States………...69
General Discussion………………………………………………………………………… 87
References………………………………………………………………………………….. 89
Appendix…………………………………………………………………………………… 105
Tables………………………………………………………………………………………. 106
3
Acknowledgements

I would like to thank my co-advisors, Norbert Schwarz and Arthur Stone, for their guidance and
mentorship throughout my studies as a doctoral student. I have learned a great deal from each of
them through our conversations, our coauthored papers, and through lab meeting discussions. I
am very grateful for the influence they have had on my academic career thus far. I would also
like to thank Daphna Oyserman, Donna Spruijt-Metz, and Cheryl Wakslak for serving on my
dissertation committee and for their helpful comments and edits on an earlier draft of my paper
on nostalgia.
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Introduction
Social and personality psychologists rely heavily on experiments in controlled settings to
understand thoughts, feelings, and behaviors in daily life. Although informative in providing
insight into causal mechanisms, carefully controlled experiments leave open how well the results
bear on phenomena as they occur in daily life. The use of methods that describe phenomena in
the real world can provide useful and important information and appeals for greater use of these
methods have certainly been warranted (Rozin, 2009). Purely descriptive information is limited
though in the extent to which phenomena can be explained. An alternative to emphasizing a
single method is to use a variety of techniques to understand thoughts, feelings, and behaviors in
daily life.
One class of methods that is well-suited to study daily life processes is known as
ecological momentary assessment (EMA; Stone & Shiffman, 1994). In these studies, participants
are asked about their behaviors, thoughts, and feelings in real time. They involve a selection of
time points that attempt to either capture a representative sample of time points or a strategic
sample of instances of a particular behavior or experience. Participants complete multiple reports
over time which helps depict the ebb and flow of experiences in a dynamic manner.
The use of EMA and daily diary techniques can considerably extend the research in
social and personality psychology in several ways (Newman & Stone, 2019). First, EMA
methods enable researchers to examine within-person processes, a level of analysis that is
distinct from between-person analyses, the level at which many, if not most, theories are tested.
Second, EMA methods ask participants to reflect on the current moment or to recall a short
amount of time (e.g., the last few hours). This limits recall biases and heuristics that are present
in single-assessment global reports. Distinguishing the present moment from longer recall
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periods can yield novel insights about phenomena as they occur in daily life. Third, EMA
methods typically select a random (and somewhat representative) sample of time points from the
larger population of time points of people’s current lives, which increases the ecological validity
of these findings. This can often lead to novel conclusions that contrast with findings from
experimental paradigms that study specific contexts. I expand on each of these three
characteristics of EMA methods, followed by on overview of the two chapters that include
studies that utilize these techniques to examine well-being in daily life.
Distinguishing between- and within-person relationships
Between-person analyses primarily focus on relationships between variables measured as
individual differences. Within-person analyses, in contrast, primarily focus on relationships
between repeated measures of situations, feelings, states, and behaviors. These levels of analysis
are mathematically independent (Nezlek, 2001) and can represent distinct psychological
processes (Affleck, Zautra, Tennen, & Armeli, 1999). Failing to disentangle these levels of
analysis can lead to misleading conclusions. For example, consider the relationship between
typing speed and typing mistakes. A between-person analysis would reveal that people who type
quickly make fewer mistakes than those who type more slowly (a negative relationship).
Presumably, those who type quickly have had lots of practice over the years and have acquired a
level of expertise, whereas those who type slowly are likely novices who might make frequent
mistakes. In contrast, a within-person analysis would reveal that for any particular person, the
number of typing mistakes will increase as typing speed increases (a positive relationship;
Hamaker, 2012). Making a general conclusion about potential effects of typing speed on typing
mistakes from a between-person level of analysis would lead to an erroneous conclusion, namely
6
that typing speed decreases typos. This type of error is known as an ecological fallacy
(Robinson, 1950).
Several other examples of contrasting relationships at between- and within-person levels
of analysis have been documented in health and clinical psychology. For example, between-
persons, those who exercise regularly have a lower risk of having a heart attack (a negative
relationship). In contrast, within-persons, the average person is at a higher risk of having a heart
attack when they exercise compared to times when they are not exercising (a positive
relationship; Curran & Bauer, 2011).
A couple of interesting between- vs. within-person distinctions have been made recently
in the fields of social and personality psychology. At a between-person level of analysis, those
who report higher levels of searching for meaning in life report lower levels of presence of
meaning in life (Steger, Frazier, Oishi, & Kaler, 2006; Steger, Kashdan, Sullivan, & Lorentz,
2008). In contrast, within-individuals, people report greater levels of presence of meaning in
daily life on days when they search for meaning in their lives (Newman, Nezlek, & Thrash,
2018a). Asking people at one time to think about how much they search for meaning in their
lives likely prompts thoughts about what the overarching meaning is to their lives, which can be
a difficult task. Searching for meaning in daily life, however, is much more manageable and can
lead to the feeling that life is quite meaningful on that particular day and on the following day.
As another example, Newman and colleagues found that people who report engaging in prayers
of supplication, thanksgiving, confession, and adoration all report greater well-being than those
who do not pray as frequently (Newman, Nezlek, & Thrash, 2018b, in preparation). This pattern
replicates a more general finding that religious people report greater well-being than non-
religious people (Diener, Tay, & Myers, 2011; Steger & Frazier, 2005). Moving beyond
7
between-person analyses, Newman et al. showed that, within-persons, people reported greater
well-being on days when they engaged in prayers of thanksgiving and adoration but lower well-
being on days when they engaged in prayers of supplication and confession. These within-person
relationships demonstrate how the daily events of the day can dictate the types of prayer people
engage in and how they feel on those days, a process that differs substantially from the between-
person relationships. These studies illustrate the dangers of generalizing a pattern of findings
from one level of analysis to another.
Global evaluations vs. daily reports
In addition to providing information about within-person relationships, EMA methods
restrict the reflection period to a short amount of time, such as the present moment or past couple
of hours. This differs considerably from global evaluations in which participants reflect on their
lives, which is a prominent method of self-report in cross-sectional studies that attempt to assess
personality traits or individual differences. When people are asked to think about their lives in
general, they obviously cannot replay their entire lives and sum up or create an average level of
the construct. Instead, they try to remember and confirm instances of the variable of interest in
their lives. This results in a biased reconstruction of their life that overemphasizes peak and
recent experiences (Robinson & Clore, 2002; Schwarz, 2012).
Global evaluations also differ from concurrent, momentary reports in terms of their
psychological distance. Global evaluations require the participant to reflect on a long period of
time, whereas momentary reports require a much shorter reflection. As temporal distance
increases, judgments become less concrete and more abstract (Trope & Liberman, 2010). This
has important implications for particular well-being judgments that are more abstract in nature,
such as meaning in life. People tend to find more meaning in life as psychological distance
8
increases (e.g., as people think about their life in the future as opposed to the present; Waytz,
Hershfield, & Tamir, 2015).
Daily life vs. experiments
In addition to providing a contrast to global evaluations, EMA methods can also offer a
unique perspective that differs from results from experimental methods. It is important to
remember, as Joe McGrath noted, that all methods are seriously flawed (McGrath, 1982). That
is, they each have their own strengths and weaknesses. Experiments excel at demonstrating
causality by ruling out third variable confounds through random assignment. They also offer
precision in understanding exact processes and mechanisms that underlie various effects. One
limitation of experiments though, is that they often lack ecological validity. That is, it is often
difficult to determine whether the variable manipulated in the lab is the same of the variable that
occurs in the real world. In some cases, manipulating the variable alters the very construct that
experimenters intended to study. For example, lack of control has been shown to increase an
illusory pattern perception (Whitson & Galinsky, 2008). In these experiments, participants in the
lack-of-control condition receive random feedback after clicking on dots on a computer screen.
In the real world, however, lack of control takes a different form (e.g., “will my boss fire me?”
“Will the military require my family to move?”). This type of lack of control looks quite
different from the uncertainty that undergraduate participants face in the lab.
EMA methods attenuate this issue by sampling random and representative moments from
one’s life. The sampling design allows researchers to more easily generalize findings to the real
world. It also depicts a more accurate representation of people’s thoughts, feelings, and
behaviors, which is often more mundane and less extreme than the situations created in the lab.
Measuring states as they occur in daily life can sometimes lead to conclusions that differ from
9
conclusions drawn from experiments. Of course, EMA methods have their own set of limitations
that differ from the limitations of experiments. Because the primary goal of EMA methods is to
measure variables as they occur naturally, these variables cannot be easily manipulated in real
time. Therefore, EMA methods are limited in the extent to which they can address causal
processes. The best approach, therefore, is to use a variety of methods to offset limitations of
each individual method (McGrath, 1982). In some cases, findings across methods converge,
whereas in other cases, they lead to opposing conclusions.
Overview of dissertation
The dissertation is composed of two chapters that include sets of studies that utilize EMA
and daily diary methods to understand well-being in daily life. The first chapter examines what
nostalgia looks like in daily life and how it relates to well-being. The chapter addresses between-
and within-person relationships between nostalgia and well-being. The finding that nostalgia is
negatively related to well-being in daily life contrasts with many experiments that find that
nostalgia increases well-being. This illustrates the importance of relying on several different
methodologies to obtain a more complete and accurate depiction of nostalgia’s effect on well-
being. The studies in the second chapter compare aggregated daily states of well-being with
global evaluations of well-being. Global evaluations of well-being were consistently higher than
aggregated daily states. These findings demonstrate how well-being judgments may differ
depending on the reflection period, and this has important implications for well-being research.

10
Chapter I: Nostalgia and Well-Being in Daily Life: An Ecological Validity Perspective
Newman, D. B., Sachs, M. E., Stone, A. A., & Schwarz, N. (in press). Nostalgia and well-being
in daily life: An ecological validity perspective. Journal of Personality and Social Psychology,
http://dx.doi.org/10.1037/pspp0000236
Abstract
Nostalgia is a mixed emotion. Recent empirical research, however, has highlighted positive
effects of nostalgia, suggesting it is a predominantly positive emotion. When measured as an
individual difference, nostalgia-prone individuals report greater meaning in life and approach
temperament. When manipulated in an experimental paradigm, nostalgia increases meaning in
life, self-esteem, optimism, and positive affect. These positive effects may result from the
specific experimental procedures used and little is known about daily experiences that covary
with nostalgia. To address this gap, we aimed to measure nostalgia in ecologically valid contexts.
We created and validated the Personal Inventory of Nostalgic Experiences (PINE) scale (Studies
1a - 1d) to assess both trait and state-based nostalgic experiences. When measured as an
individual difference, the nomological net was generally negative (Study 2). When measured in
daily life (Studies 3 – 4), nostalgia as a state variable was negatively related to well-being.
Lagged analyses showed that state nostalgia had mixed effects on well-being at a later moment
that day and negative effects on well-being on the following day. To reconcile the discrepancies
between these studies and the positive effects of nostalgia from previous research, we showed
that experimentally induced nostalgic recollections were rated more positively and less
negatively than daily experiences of nostalgia (Study 5). These studies show that nostalgia is a
mixed emotion; although it may be predominantly positive when nostalgic memories are
generated on request, it seems predominantly negative when nostalgia is experienced in the
course of everyday life.
11
Keywords: nostalgia, well-being, ecological validity, ecological momentary assessment,
diary study
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Nostalgia is often classified as a mixed emotion because it is composed of positive and
negative aspects. The Oxford English dictionary defines nostalgia as “A sentimental longing or
wistful affection for a period in the past.” Similar to other emotions, nostalgia presumably varies
within individuals. Someone may feel nostalgic at a particular moment in time but not the next.
The intensity of nostalgic feelings may also vary considerably from moment to moment or from
day to day. Moreover, these fluctuating states of nostalgia likely occur concurrently with a
variety of situations, contexts, and internal states. Currently very little is known about the daily
experiences that occur in real time when people feel nostalgic. The goal of the present set of
studies was to examine the daily experiences, feelings, thoughts, and states of well-being that
accompany feelings of nostalgia.
Review of Empirical Findings on Nostalgia
Recent empirical findings from psychology suggest that nostalgia is associated with
numerous psychological benefits. For example, nostalgia-prone individuals (those who report
higher levels of intensity and frequency of nostalgia) report greater meaning in life (Cheung et
al., 2013; Routledge et al., 2011) and approach motivation (Stephan et al., 2014), a dimension of
personality that, in contrast to avoidance motivation, is associated with positive emotionality
(Elliot & Thrash, 2010). In experimental settings, nostalgia increases meaning in life, optimism,
self-esteem, social connectedness, and positive affect (Cheung et al., 2013; Routledge et al.,
2011; Wildschut, Sedikides, Arndt, & Routledge, 2006). In a recent review of the literature,
Sedikides and colleagues concluded that “...nostalgia is considered an emotion, and a
predominantly positive one at that” (Sedikides et al., 2015, p. 6).
Recent theories hold that feelings of nostalgia are associated with positive outcomes
because of two different mechanisms. One mechanism is a regulatory, restorative, or palliative
13
function in which nostalgia buffers certain negative effects. When negative events occur, they
can influence an individual in a negative manner by decreasing well-being. Negative events can
also trigger feelings of nostalgia, and these nostalgic experiences attenuate the associated
negative effects. For example, the negative effects of experimentally induced self-threat (Vess,
Arndt, Routledge, Sedikides, & Wildschut, 2012) and perceived meaninglessness (Routledge et
al., 2011) have been attenuated by recalling nostalgic experiences. In correlational studies, the
negative effects of loneliness have been buffered by nostalgia (Zhou, Sedikides, Wildschut, &
Gao, 2008). Presumably, recalling nostalgic experiences increases one’s sense of social
connectedness, which is assumed to restore one’s well-being following a negative experience.
A second mechanism of nostalgia is one in which nostalgia serves self-oriented,
existential, and social functions, which subsequently lead directly to positive outcomes. In terms
of its self-orienting function, participants in one study reported higher self-esteem after listening
to a nostalgic song (Cheung et al., 2013). People also reported higher optimism about their future
after smelling scents that made them feel nostalgic (Cheung et al., 2013). Regarding the
existential function, after pondering a past nostalgic event, people reported lower levels of
searching for meaning in life (Routledge et al., 2011). Finally, several studies support a social
function of nostalgia. For example, after participants were instructed to think about the most
nostalgic experience in their own lives, they reported lower attachment anxiety and avoidance
(Wildschut et al., 2006 study 6), a higher degree of social support (Zhou et al., 2008), and an
increased level of trust towards an outgroup member (Turner, Wildschut, & Sedikides, 2012).
Recalling a nostalgic memory has even increased prosocial behavior, such as helping a stranger
pick up dropped pencils (Stephan et al., 2014) and donating to charity (Zhou, Wildschut,
14
Sedikides, Shi, & Feng, 2012). In sum, various mechanisms suggest that nostalgic recollections
can lead to positive outcomes (for a review, see Sedikides et al., 2015).
Ecological Validity Considerations
Although such experimental studies are informative in providing information about
psychological processes involved in nostalgia and its outcomes, they tell us little about the
emergence and consequences of nostalgia in everyday life (Brunswik, 1956; Shiffman & Stone,
1998). In the absence of such information, one cannot even determine to what extent the
experimental settings created by researchers mimic circumstances that elicit feelings of nostalgia
in natural contexts. It also remains unknown what types of situations, feelings, and states of well-
being are likely to co-occur with nostalgia in daily life. To our knowledge, only one study has
captured nostalgia as it has occurred in daily life (Zhou, Wildschut, Sedikides, Chen, &
Vingerhoets, 2012, Study 1). In this study, 19 Chinese participants recorded how nostalgic they
felt each evening over the course of 30 days. Participants were more likely to feel nostalgic on
cold days than on warm days. No other situational factors or internal feelings were assessed in
this study, however. Clearly, there is a dearth of information about the daily experiences that
could covary with daily states of nostalgia.
Our aim was to bridge this gap in the literature by examining and measuring nostalgia in
daily life through the use of daily diary (Bolger, Davis, & Rafaeli, 2003) and ecological
momentary assessment (EMA) techniques (Stone & Shiffman, 1994). Diary and EMA studies
are designed to capture behavior, thoughts, and feelings as they occur in real time in daily life
(Shiffman, Stone, & Hufford, 2008). One advantage of this methodology is that recall biases are
limited; daily or momentary reports are much more accurate in capturing affective experience
than global recalls (National Research Council, 2013, pp. 29–30; Robinson & Clore, 2002;
15
Schwarz, 2012). Such techniques allow the researcher to measure “life as it is lived” (Bolger et
al., 2003), suggesting that EMA techniques can greatly enhance our understanding of nostalgia in
real-world settings.
Another advantage of daily diary and EMA techniques is that they can capture ordinary
feelings and experiences, whereas experimental manipulations often privilege unusual
experiences in the interest of strong manipulations. Indeed, the most common experimental
manipulation of nostalgia is the Event Reflection Task, which asks participants to “...think of a
past event that makes you feel most nostalgic” (italics added for emphasis). Such instructions
explicitly ask for an event that is likely to differ from one’s most common nostalgia experiences,
which are not the “most” nostalgic ones. In other studies (Iyer & Jetten, 2011, Study 3;
Wildschut et al., 2006, Study 6), participants were asked to recall a nostalgic event that had
personal meaning (e.g., “please think of a nostalgic event in your life—a nostalgic event that has
personal meaning for you”). Asking for a “meaningful” event increases the odds that the recalled
event affects well-being related measures, which may or may not be the case for other episodes
of nostalgia. In short, commonly used experimental instructions in nostalgia research compound
the concerns usually associated with recall-based reports (for reviews, see Schwarz, 2012;
Schwarz, Kahneman, & Xu, 2009), including the higher memorability of extreme and personally
meaningful events and the disproportionate impact of peaks and ends (Fredrickson & Kahneman,
1993; Morewedge, Gilbert, & Wilson, 2005). Moreover, negative affect associated with past
events has often been found to fade quicker than positive affect (e.g., Ritchie et al., 2006;
Walker, Vogl, & Thompson, 1997), adding a risk of differential affect reconstruction when
people report on distant episodes. People also remember central aspects of nostalgia (e.g., fond
memories, personal meaning, happiness), which tend to be relatively positive, more easily than
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peripheral aspects of nostalgia (e.g., mixed feelings, regret, loneliness, pain/anxiety), which tend
to be relatively negative (Hepper et al., 2012), again enhancing the risk of biased reconstruction.
All of these concerns should be attenuated when participants report how nostalgic they
feel in real time. Concurrent or temporally close reports can provide a more representative
sample of nostalgic experiences, including experiences of lower intensity. They also bypass the
difficulties associated with selecting and reconstructing a past experience. In addition, any
negative affect that may be associated with nostalgia is less likely to be missed in real-time
reporting. By the same token, however, real-time assessments of nostalgia are unlikely to capture
rare episodes of particularly intense nostalgia, unless the sample of persons and/or time points is
very large. Hence, real-time studies may miss benefits that are uniquely associated with peak
nostalgia experiences.
Based on these considerations we hypothesized that the relationship between nostalgia
and well-being captured in everyday experiences would not be as positive as suggested by much
of the experimental work (Sedikides & Wildschut, 2018). We further predicted that the
nomological net of nostalgia would be mixed, i.e., nostalgia would relate to some positive and
some negative attributes. This pattern of findings would be consistent with common definitions
of nostalgia that contain positive and negative aspects. The Greek origin of the word nostalgia
even contains positive and negative aspects (nostos = “return home”, algos = “pain”).
Measurement of Nostalgia
In order to test this hypothesis and evaluate the experience of nostalgia in daily life, we
needed to create a measure that could capture nostalgia in ecologically valid settings. Some
existing scales measure nostalgia in very specific settings, such as in the context of marketing
(Pascal, Sprott, & Muehling, 2002), and in response to advertisements (Marchegiani & Phau,
17
2013). The Nostalgia Inventory (Batcho, 1995) lists specific aspects of one’s past that one
misses, such as family, places, toys, and music. This restricts the concept of nostalgia to aspects
of one’s past that one misses and excludes other aspects, such as the extent to which one yearns
for and desires to return to or relive a past experience or situation.
The most widely used measure of nostalgia, the Southampton Nostalgia Scale (SNS;
Barrett et al., 2010; Routledge, Arndt, Sedikides, & Wildschut, 2008), is also not ideal for our
purposes. The most recent version of the scale contains seven items designed to assess nostalgia
proneness as an individual difference (Barrett et al., 2010). Each item contains the word
“nostalgia” which creates a narrow construct. As McCrae (2015) noted, trait variance becomes
confounded with specific item variance when an instrument is dominated by almost identical
questions, a technique that Cattell (1973) once called a “bloated specific”. Additionally, one item
of the SNS asks participants to recall how often they bring to mind nostalgic experiences with
responses ranging from “At least once a day” to “Once or twice a year.” This question assumes
that nostalgia is a dichotomous variable (e.g., one either feels nostalgic or not) rather than a
continuous variable (e.g., one can feel nostalgic to varying degrees). Finally, two of the SNS
items ask participants how valuable and significant nostalgic feelings are to them, which
selectively directs attention to positive aspects of nostalgia. In sum, published scales assessing
nostalgia have either measured the construct in highly specific contexts, have asked participants
questions that rely on extensive recall, and have included aspects that do not pertain to the
experience per se.
Overview of present studies
As a first step, we created and validated a brief trait nostalgia scale (Studies 1a – 1d).
Next, we examined the between-person relationships between nostalgia, personality, and well-
18
being measured as traits or individual differences to assess the nomological net of nostalgia
(Study 2). To ascertain the usefulness of this new scale, we additionally compared the strengths
of the relationships between our new scale and other constructs with the relationships between
the SNS scale and other constructs.
Following scale construction, we conducted a daily diary study (Study 3) to address our
primary research aim of understanding how nostalgia relates to other daily experiences, feelings,
and thoughts in a naturalistic setting. The intensive repeated measures nature of a diary study
also allowed us to examine within-person relationships, a level of analysis that is statistically
orthogonal to between-person relationships (Nezlek, 2001). Separating within-person and
between-person variance in nostalgia considerably extends the research agenda, given that
theories concerning the relationship between nostalgia and well-being have been tested almost
exclusively with between-person designs. In Study 4, we conducted an EMA study in which
participants reported their momentary nostalgic feelings and well-being at randomly selected
time points throughout the day, thus eliminating the need to recall any past experiences. The
findings from these naturalistic studies diverged from experimental findings by showing that
nostalgia is a mixed emotion, although more strongly associated with negative feelings than
positive feelings. Study 5 addressed this divergence between experimental and real-time findings
by comparing recalled nostalgic experiences with daily nostalgic experiences. This comparison
allowed us to determine whether experimentally induced nostalgic recollections are more
positive than everyday nostalgic experiences, a difference that may drive the associations
observed in Studies 3 and 4.

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Studies 1a – 1d: Scale Construction
The purpose of the first set of studies was to develop a short nostalgia scale. Although
our primary goal was to create a scale that could assess nostalgia at the daily level, we
additionally aimed to test the psychometric properties of the scale as an individual difference
measure. We initially asked participants to think of their life in general to assess a trait-like
individual difference measure of nostalgia. The creation of a trait measure of nostalgia would
serve as a foundation for developing daily items to be administered in daily diary studies.
Study 1a
Method
The cognitive interview portion of Study 1a was approved by the Institutional Review
Board at the University of Southern California under the ID UP-15-00625. The latter part of
Study 1a, Study 1b, Study 1c, Study 2, and Study 3 were approved by the Institutional Review
Board at the University of Southern California under the ID UP-15-00479.
To generate items for a measure of nostalgia, we initially drew from four primary
sources. First, we considered words written by students about a recent nostalgic experience
(Wildschut et al., 2006). Second, we read definitions from several dictionaries, such as Oxford,
Merriam-Webster, and Collins English. Third, we considered the items from scales that have
been used to measure nostalgia in specific contexts, such as the personal nostalgic response to
advertisements (Marchegiani & Phau, 2013), the Evoked Nostalgia Scale to assess nostalgia in
marketing contexts (Pascal et al., 2002), and the Batcho Nostalgia Scale (Batcho, 1995) designed
specifically to assess the extent to which people miss aspects of their past. Fourth, to assess
nostalgia in an ecologically valid context, we called 33 undergraduate students (Mage = 20.09, SD
= 1.4; 51.52% female) in the evening between 9:00pm – 11:30pm and asked them to recount the
20
events of their day. After reconstructing their day, we asked participants how nostalgic they felt
today on a 10-point scale (1 = not at all, 10 = very much). After the participants provided a
numeric rating, we asked them what words came to mind when they heard the word ‘nostalgia’
or what they thought of when they thought of the word ‘nostalgia’. The answers to these
questions are listed in Supplemental Table 1.
From these sources, we created a list of 15 items with the goal of capturing a wide variety
of language used to define nostalgia. We placed a particular emphasis on the responses recorded
by participants at the end of their day because these descriptions were recorded in an
ecologically valid setting (see Supplemental Table 2). We then administered the 15-items to 470
undergraduate students from a large private university in the US. Participants were asked,
“Please indicate the extent to which each of the following statements describe you in general.”
Responses were recorded on a 7-point scale (1 = Not at all, 7 = Very much). As recommended by
Meade and Craig (2012), we included an instructed response item to capture insufficient effort
responses: “Please select the choice ‘Very much’ for this question.” Twenty-six participants
failed to answer this question correctly and their data were removed; final analyses included data
from 444 participants (Mage = 20.21, SD = 2.82; 77.5% female).
Results
We factor analyzed responses to the 15 items with the R package semTools and the
function factanal. First, we examined the eigenvalues (7.62, 1.28, .93, .69, .60...). A single factor
solution seemed most reasonable, but we also examined a two-factor model using a maximum
likelihood estimation with direct oblimin rotation (as recommended by Costello & Osbourne,
2005). The items did not load onto the two respective factors in a meaningful manner, so we
21
opted for a single factor model. The factor loadings are presented next to items in Supplemental
Table 2.
Study 1b
Method
Some of the 15 items were redundant. Because our goal was to create a brief scale, we
kept the first 6 items because they had high factor loadings and still contained varied descriptions
of nostalgia. We distributed the shortened scale to 298 undergraduate students from the same
university as Study 1a (Mage = 19.48, SD = 1.69, 71.5% female) in a similar manner.
Results
We ran a confirmatory factor analysis (CFA) using the lavaan package (Rosseel, 2012) in
R. All 6 items were treated as indicators of a latent construct of nostalgia. The variance of the
latent construct was fixed at 1 so that we could estimate each factor loading. The data were not
multivariate normal as indicated by Mardia’s tests of skewness, γˆ1,p = 3.82, p < 0.001, and
kurtosis, γˆ2,p = 65.12, p < 0.001, so we used a maximum likelihood estimator with robust
standard errors (Yuan & Bentler, 2000). The standardized loadings of each indicator were as
follows: .74, .81, .70, .81, .76, .83. The model fit was not optimal, χ
2
(9) = 89.58, p < .001;
RMSEA = .228, 90% CI [.186, .272]); CFI = .874; SRMR = .065. Therefore, we tested
alternative models by dropping items that we felt were redundant with the others. After dropping
items 2 and 4, we found good model fit with items 1, 3, 5, and 6 as indicators of a latent
construct. Standardized factor loadings were .83, .81, .83, .65 and the model fit was considerably
better, χ
2
(2) = .85, p = .66; RMSEA = .000, 90% CI [.000, .121]; CFI = 1.00, SRMR = .008.
These four items were as follows: “How nostalgic do you feel?”, “To what extent do you feel
22
sentimental for the past?”, “How much do you feel a wistful affection for the past?”, and “To
what extent do you feel a longing to return to a former time in your life?”
Study 1c
Method
Although the 4-item model showed good model fit, we may have capitalized on chance
given that the shortened 4-item model was generated after we tested model fit with the initial 6-
items. To rule out this possibility, we administered the shortened 4-item scale to 440
undergraduate students (Mage = 20.13, SD = 1.93; 69.8% female) during the next semester in a
similar manner as before.
Results
We ran a CFA with the four items as indicators of a single latent construct as described
previously. The data were not multivariate normal as indicated by Mardia’s tests of skewness,
γˆ1,p = 1.62, p < 0.001, and kurtosis, γˆ2,p = 32.61, p < 0.001. Therefore, we used a maximum
likelihood estimator with robust standard errors (Yuan & Bentler, 2000). The standardized factor
loadings were all above .70: .82, .84, .85, and .72. Model fit indicators were good: χ
2
(2) = .57, p
= .75, RMSEA = .000, 90% CI [.000, .092], CFI = 1.000, SRMR = .005. Revelle’s omega
coefficient to test reliability was also sufficiently high (.89) as was Cronbach’s alpha (.87). We
note that Cronbach’s alpha has several documented limitations (Bentler, 2017; McNeish, 2017),
but we report it throughout nevertheless due to its widespread use. In sum, the four-item measure
of nostalgia demonstrated excellent psychometric properties. The four items are highlighted with
an asterisk in Supplemental Table 2 and can additionally be found in the Appendix.

23
Study 1d
Method
Study 1d was approved by the Institutional Review Board at the University of Southern
California under the ID UP-16-00003. Next, we tested the reliability of the trait measure by
assessing nostalgia as an individual difference at two time points separated by 10 weeks. This
enabled us to examine measurement invariance and the correlation between latent constructs at
two time points.
198 undergraduate students signed up for the study and completed the first measure of
nostalgia in exchange for research credit for a course. The first questionnaire was distributed at
the beginning of the semester and the follow-up questionnaire was distributed 10 weeks later.
Twelve participants did not complete the second questionnaire. Final analyses included 186
participants (Mage = 20.28; SD = 2.57; 77.4% female). Participants who completed both
questionnaires did not differ significantly from participants who only completed the first
questionnaire in terms of their age, t(16.79) = 1.76, p = .31, ratio of males to females (odds ratio
= 1.14, p = .74), or mean levels of nostalgia, t(12.13) = 1.65, p = .13.
Similar to the previous studies, participants were asked to think about their life in general
as they completed the four-item nostalgia scale.
Results
Means, standard deviations, skewness, kurtosis, and inter-item correlations for the trait
version of the scale are presented in Supplemental Table 3. Revelle’s omega measure of
reliability was .91 (alpha = .88) at Time 1 and .89 (alpha = .88) at Time 2.
We tested measurement invariance across time points using a confirmatory factor
analysis approach as outlined by Vandenberg and Lance (2000). The four nostalgia items
24
distributed at Time 1 were treated as indicators of a latent construct at Time 1, and the four
nostalgia items at Time 2 were similarly treated as indicators of a latent construct at Time 2.
Errors terms of each nostalgia item at Time 1 were allowed to freely covary with each respective
nostalgia item at Time 2 (e.g., item1 at Time1 with item1 at Time2). Variances of each latent
construct were fixed to 1 and the latent constructs were allowed to freely covary.
First, we found that the data were not multivariate normal as indicated by Mardia’s tests
of skewness, γˆ1,p = 6.80, p < 0.001, and kurtosis, γˆ2,p = 90.77, p < 0.001, so we used a
maximum likelihood estimator with robust standard errors (Yuan & Bentler, 2000). The model
fit was good: χ
2
(2) = 18.62, p = .23; RMSEA = .040, 90% CI [.000, .091]; CFI = .995; SRMR =
.025. The standardized factor loadings at time 1 were .85, .87, .82, and .70; at Time 2, the
standardized factor loadings were .84, .84, .85, and .69. The standardized covariation between
the latent nostalgia constructs at Time 1 and Time 2 was .64, z = 11.26, p < .001. Although this
correlation was not as high as some correlations in test-retest reliability studies involving
individual differences, it is similar to studies that have assessed positive and negative affect at
multiple time points just four weeks apart (e.g., Lucas, Diener, & Suh, 1996).
More importantly, we tested measurement invariance to determine whether the latent
constructs of nostalgia at both time points were represented by the four nostalgia items in similar
manners. The four tests of measurement invariance increase in the extent to which they restrict
the models to be similar to both time points. Configural or pattern invariance tests whether the
number and pattern of factor loadings remains constant. Weak or metric invariance restricts the
respective factor loadings at each time to be equal and tests whether the factor variances and
covariances are equal across time points. Strong or scalar invariance restricts the intercepts to be
equal at each time point and tests whether the means of each item are consistent. Finally, strict or
25
error invariance restricts the uniquenesses or error terms of each indicator to be equal. Typically,
the former two tests of measurement invariance are considered adequate and the latter two tests
are considered too strict (Little, 2013). As presented in Supplemental Table 4, we found
measurement invariance at each level of restriction. That is, not only were the factor patterns and
factor loadings similar at each time point, but the factor means and error structures were also
consistent over time. This suggests that the four items reliably measure the underlying construct
in a similar manner over time.
Discussion
Thus far we have established that the four-item measure of nostalgia concisely
summarizes aspects of nostalgia using a variety of terms. The items show good internal
consistency, and they hang together in a similar manner over time. We now name this scale the
Personal Inventory of Nostalgic Experiences (PINE; see Appendix for the list of items).
Study 2: Individual Differences in Nostalgia
In this study, we examined the nomological net of nostalgia at a trait level of analysis.
We relied on two of the major theories of personality, namely approach and avoidance
temperament (Elliot & Thrash, 2002) and the Big Five personality traits (McCrae & Costa,
1987). Because nostalgia entails thinking about the past, we considered individual differences in
time perspectives captured with the Time Perspective Inventory (Zimbardo & Boyd, 1999). We
also included several well-being measures, such as satisfaction with life, meaning in life, affect,
self-esteem, and depression because one of our primary aims was to understand the relationship
between nostalgia and well-being. Finally, we examined the relationships between nostalgia and
various other measures that often predict or relate to well-being, such as optimism, searching for
meaning in life, regret, empathy, and inspiration. These variables have been measured in
26
previous research on nostalgia, often as a dependent variable. Our goal was to examine these
relationships at a trait level.
We also expected the PINE Scale to be positively related to the Southampton Nostalgia
Scale while not being redundant as to suggest the items measure the same latent construct. Given
that the Southampton Nostalgia Scale was correlated with various measures of well-being, a
further goal of this study was to compare the strengths of the relationships between well-being
and the PINE scale with those of the Southampton Nostalgia Scale.
Method
Participants and procedure. Undergraduate students completed online questionnaires in
exchange for course research credit. Participants were instructed to reflect on their life in general
as they responded to the questions. Seven samples of participants completed questionnaires
online via the survey provider Qualtrics. Some of the measures were asked in multiple
questionnaires, and we aggregated the samples to increase power in our calculations. Moreover,
some participants completed multiple questionnaires. For these participants, we included their
first questionnaire and excluded any additional questionnaires that contained a duplicate
measure. The total aggregated sample included 596 (Mage = 20.06, SD = 2.2; 72.80% female)
unique participants.
Materials.
Nostalgia. Nostalgia was assessed in each sample with the 4-item PINE measure with a
7-point response scale (1 = Not at all, 7 = Very much). In three of the samples, participants also
completed the Southampton Nostalgia Scale, which contains 7 items. For example, “How
valuable is nostalgia for you?” (1 = Not at all, 7 = Very much). When participants completed
both scales in the same questionnaire, the order in which they completed scales was randomized
27
and a few scales were included in between the separate nostalgia scales to distribute any
potential context effects.
Personality traits and individual differences. Approach/avoidance temperament and the
Big Five were used to assess personality. We used a 12-item scale to measure approach and
avoidance temperament (Elliot & Thrash, 2010). Responses were recorded on a 7-point scale (1
= Strongly Disagree, 4 = Neither Agree nor Disagree, 7 = Strongly Agree). In two samples (N =
171), we used a 44-item scale to assess the Big Five (John & Srivastava, 1999), and in one
sample (N = 108) we used the newer 60-item Big Five 2 scale (Soto & John, 2017). Correlations
between nostalgia and the five personality traits did not differ meaningfully between the two
measures of the Big Five, so we combined the samples together for the analyses.
The Time Perspective Inventory (TPI; Zimbardo & Boyd, 1999) includes five factors to
describe individual differences in how participants think about time: past positive (e.g., “It gives
me great pleasure to think about my past”), past negative (e.g., “I think about the bad things that
have happened to me in the past”), present fatalistic (e.g., “Since whatever will be will be, it
doesn’t really matter what I do”), present hedonic (e.g., “I believe that getting together with
one’s friends to party is one of life’s important pleasures”), and future (e.g., “I believe that a
person’s day should be planned ahead each morning”). Responses were recorded on a 5-point
scale (1 = Very uncharacteristic, 5 = Very characteristic).
Well-being and related constructs. Given the focus of the paper, we included several
well-being indicators and other constructs relevant to well-being (inspiration, empathy, searching
for meaning in life, regret, and depression). Satisfaction with life was assessed with the 5-item
Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985) with responses on a 7-
point scale (1 = Strongly disagree, 7 = Strongly agree).
28
Affect was measured using a circumplex model that distinguishes valence (positive and
negative) and arousal (activated and deactivated) (e.g., Feldman Barrett & Russell, 1998). Items
were taken from a list of adjectives that have been used reliably in daily diary research (e.g.,
Brandstätter, 2007; Nezlek, 2005) and were worded to reflect one’s life in general. Positive
activated affect (PA) was assessed with the words enthusiastic, delighted, happy, glad, and
excited; positive deactivated affect (PD) with the words calm, peaceful, relaxed, contented, and
at ease; negative activated affect (NA) with stressed, angry, annoyed, tense, and nervous;
negative deactivated affect (ND) with depressed, disappointed, miserable, gloomy, and sad.
Responses were recorded on a 7-point scale (1 = do not feel this way at all, 4 = feel this way
moderately, 7 = feel this way very strongly).
The two dimensions of meaning in life (presence and search) were assessed with the
Meaning in Life Questionnaire (Steger, Frazier, Oishi, & Kaler, 2006). Example items include
“My life has a clear sense of purpose” and “I am searching for meaning in my life” for presence
and search, respectively. Responses were recorded on a 7-point scale (1 = Absolutely Untrue, 7 =
Absolutely True).
Self-esteem was assessed with the 10-item Rosenberg scale (Rosenberg, 1965) with
responses recorded on a 4-point scale (1 = Strongly Disagree, 4 = Strongly Agree).
Regret was measured with a 5-item scale that has been used in the context of decision
making (Schwartz et al., 2002). An example item is “When I think about how I’m doing in life, I
often assess opportunities I have passed up,” and responses were recorded on a 7-point scale (1 =
Completely disagree, 7 = Completely agree).
Empathy was assessed with the Interpersonal Reactivity Index (Davis, 1983). The scale is
composed of four subscales: perspective taking, fantasy, empathic concern, and personal distress.
29
Given our interest in the broad concept, we created an aggregate score across all subscales.
Participants responded on a 5-point scale (1= Does not describe me well, 5 = Describes me very
well).
Depression was measured using the Center for Epidemiologic Studies Depression Scale
(Radloff, 1977), which instructs participants to recall how often they have felt a particular way
during the past week. The scale contains 20-items (e.g., “I thought my life had been a failure”).
Responses were recorded on a 4-point scale (0 = Rarely or none of the time (less than 1 day)…, 3
= Most or all of the time (5-7 days)).
Inspiration was measured with four items (e.g., “I feel inspired”). After each item,
frequency and intensity were recorded with the questions “How often does this happen?” and
“How deeply or strongly (in general)?” on 7-point response scales (1 = Never, 7 = Very often; 1
= Not at all, 7 = Very deeply or strongly, respectively) (Thrash & Elliot, 2003). As recommended
by Thrash and Elliot (2003), we aggregated these items for a total score of inspiration and
present correlations with nostalgia and all three inspiration scores (frequency, intensity,
aggregate).
Means for each construct were calculated and used for the correlations with the exception
of depression in which the sum was used. Reliabilities were calculated using Revelle’s omega.
The number of participants who completed each measure, the means or sums, and standard
deviations for each measure are included in Table 1.
Results and Discussion
First, we examined the Pearson’s correlations between nostalgia and personality traits,
individual differences, and well-being measures. The results and descriptive statistics of the
measures are presented in Table 1. Individuals who reported high levels of nostalgia reported
30
high avoidance temperament but there was no significant relationship with approach
temperament. In terms of the Big 5, nostalgia was only significantly (positively) related to
neuroticism.
In terms of the time perspective inventory, nostalgia was positively related to past
positive, past negative, present fatalistic, and present hedonic, but was not related to future. This
suggests that individuals who are prone to nostalgia think about the past in both positive and
negative ways, which is consistent with the notion that nostalgia is a mixed emotion. In a
multiple regression model, we included both past positive and past negative as standardized
predictors simultaneously and found that nostalgia was still significantly related to past positive,
β = .43, t = 9.97, p < .001, and past negative, β = .43, t = 9.95, p < .001.
Regarding well-being and related constructs, nostalgia was negatively (marginally)
related to satisfaction with life, meaning in life (presence), and self-esteem; nostalgia was
positively related to negative activated affect, negative deactivated affect, meaning in life
(search), empathy, inspiration intensity (although not frequency), regret, and depression; and
nostalgia was not significantly related to positive activated or positive deactivated affect. In sum,
individuals who were prone to nostalgia reported low levels of well-being, but they also reported
higher levels of empathy and inspiration intensity.
Next, we wanted to contrast these correlations with the relationships between nostalgia
measured with the Southampton Nostalgia Scale and other variables. A subsample of participants
completed the PINE and SNS measures. Before examining these comparisons, we first
conducted separate confirmatory factor analyses to examine model fit of the PINE and SNS
measures. The data were not multivariate normal for either scale as indicated by Mardia’s tests of
skewness (PINE: γˆ1,p = .69, p < 0.001; SNS: γˆ1,p = 7.71, p < 0.001) and kurtosis (PINE: γˆ2,p =
31
30.22, p < 0.001; SNS: γˆ2,p = 82.75, p < 0.001), so we used a maximum likelihood estimator
with robust standard errors (Yuan & Bentler, 2000). Fit indices for the PINE scale showed
excellent model fit, χ
2
(2) = 2.47, p = .29; RMSEA = .026, 90% CI [.000, .112]; CFI = 1.000;
SRMR = .007. In contrast, the SNS showed unacceptable model fit, χ
2
(14) = 107.60, p < .001;
RMSEA = .212, 90% CI [.175, .250]; CFI = .898; SRMR = .061.
Finally, we compared the strengths of the relationships between these two nostalgia
scales and a subset of the available individual difference measures. The correlations were
compared using William’s test because the pairs of dependent correlations shared one variable
(Steiger, 1980; Williams, 1959). The PINE and SNS measures were positively related, r(228) =
.66, p < .001. As can be seen in Table 2, there were a few differences between the correlations
involving the PINE scale and the correlations involving the SNS. For example, approach
temperament was not significantly related the PINE scale but it was significantly related to SNS,
and these correlations were significantly different. In terms of the Big 5, the pattern of relations
was similar for agreeableness, conscientiousness, and neuroticism. However, extraversion was
slightly positively related to SNS but was slightly negatively related to the PINE scale. Although
neither correlation was significant, the difference between these correlations was significant.
Similarly, openness to experience was positively related to SNS but was not related to the PINE
scale.
Individuals who reported high levels of SNS also reported higher levels of inspiration,
satisfaction with life, meaning in life (both presence and search), and lower levels of depression
in comparison to individuals who reported high levels of nostalgia on the PINE scale. In an
attempt to understand why the SNS was more positively related to well-being than the PINE, we
considered the approach-oriented wording of several of the SNS items (e.g., “How important is it
32
for you to bring to mind nostalgic experiences?”, “Generally speaking, how often do you bring to
mind nostalgic experiences?”). Pursuing and seeking nostalgic experiences is different from
simply feeling nostalgic, which could explain why the SNS was positively related to approach
motivation and the PINE was not. After controlling for approach motivation in multiple
regression analyses with standardized coefficients, we found that the relationships between SNS
and satisfaction with life, β = .06, t = .91, p = .37, presence of meaning in life, β = .00, t = .07, p
= .95, and depression, β = .27, t = 2.86, p < .01, were more similar to the relationships between
PINE and those respective well-being measures, β = .01, t = .11, p = .92; β = -.06, t = .91, p =
.37; β = .31, t = 3.53, p < .001, respectively.
In sum, these findings show that, between-individuals, the nomological net of nostalgia
as measured with the PINE scale is more negative than previously suggested by the results from
trait correlations involving the SNS (Routledge et al., 2011; Stephan et al., 2014).
Study 3: Daily States of Nostalgia
After establishing good psychometric properties of the PINE scale and after examining
the between-person nomological net of nostalgia, we sought to measure nostalgia as it occurred
in daily life in an ecologically valid context. To do so, participants completed end-of-the-day
reports about their daily experiences, state of well-being, thoughts, and how nostalgic they felt
that day. This type of study can advance our understanding of nostalgia by showing what types
of events and experiences are likely to occur on days when one feels nostalgic. It also allows for
the examination of within-person relationships between nostalgia, well-being, and daily events.
This level of analysis is mathematically independent from the between-person relationships
examined in Study 2 and from between-subject experiments involving nostalgia. Within-person
33
relationships also address processes that are psychologically distinct from between-person
relationships (Affleck, Zautra, Tennen, & Armeli, 1999).
Method
Participants and procedure. A subset of the participants from Study 2 (232
undergraduate students; Mage = 19.94, SD = 1.68, 82.3% female) signed up for the study in
exchange for research credit. Prior to completing daily reports, they either watched an
instructional video online or participated in an online video call with one of the coauthors to
learn about the procedure. They were instructed to complete a daily questionnaire administered
via email with a Qualtrics link just before going to bed in the evening. Over the course of 14
days, an email was sent at 9:00pm each evening and a reminder email was sent to participants at
7:00am the following morning if they forgot to complete the questionnaire the night before.
Emails completed as late as 10:00am were accepted, consistent with previous diary studies (e.g.,
Oishi, Diener, Choi, Kim-Prieto, & Choi, 2007).
The diary studies were conducted in three separate semesters with different participants.
Because the procedures were nearly identical and because the measures used in each sample
were very similar, we aggregated participants across all three samples. Doing so minimizes the
potential of capitalizing on sampling variability. Separate analyses were also calculated and
differences across samples were not meaningful, so we present the aggregated analyses.
We collected 3,011 daily reports and excluded 287 entries that were either duplicate
entries, completed after 10:00am the following day, or completed in less than 2 or 3 minutes
(depending on the sample and number of questions asked). We additionally excluded data from
participants who failed to correctly answer an instructed response item, (e.g., “Please select ‘A
moderate amount’ for this question”) as recommended by Meade and Craig (2012), or whose
34
total number of valid completed entries was less than 5. This resulted in 2,724 entries (90.47%)
for analysis, a percentage consistent with many diary studies (Nezlek, 2012, pp. 45–49).
Participants completed an average of 11.74 of the 14 possible daily questionnaires (SD = 2.14)
and the minimum number of completed reports was 5.
Measures
Daily events. Participants first answered 26 questions about events and experiences that
are common in everyday life among undergraduate students. The list of events is a compilation
from the Daily Event Schedule (Butler, Hokanson, & Flynn, 1994), the Objective/Subjective
Event Checklist (Seidlitz & Diener, 1993), and other items from a diary study by Gable, Reis,
and Elliot (2000). Events were grouped into categories of positive social (e.g., “Had especially
good interactions with friend(s) or acquaintances”), positive achievement (e.g., “Completed work
on an interesting project or assignment”), negative social (e.g., “Was excluded or left out by my
group of friends”), and negative achievement (e.g., “Fell behind in coursework or duties”).
Additionally, we created five items concerning events that would likely covary with nostalgic
experiences: “Met up with a friend or acquaintance you hadn’t seen in a long time,” “Sent email,
text, facebook message, or communicated in some way with an old friend or acquaintance,”
“Heard a song that I had not heard in a long time,” “Watched a movie or part of a movie (e.g.,
youtube clip) that reminded me of my past,” and “Saw an old photo of myself or friends (on
instagram, facebook, text, etc.)”. These five nostalgic events were administered in the third
sample only. The first two items were included in the first and second samples. For each daily
event, participants responded on a 5-point scale (0 = did not occur, 1 = occurred and not
important, 2 = occurred and somewhat important, 3 = occurred and pretty important, 4 =
35
occurred and extremely important). The average score was calculated which provides a measure
that captures whether an event occurred and how important the event was to the participant.
Helping behavior was measured with 10 items that assessed the extent to which they
helped strangers with everyday activities (e.g., “Today, I gave directions to a stranger or
acquaintance”). These items were originally adapted from the Self-Report Altruism Scale
(Philippe Rushton, Chrisjohn, & Cynthia Fekken, 1981) and later consolidated and reworded for
a daily diary study (Morelli, Rameson, & Lieberman, 2014). Responses were recorded on the
same response scale as the daily events (0 = did not occur…, 4 = occurred and extremely
important).
To measure the extent to which participants engaged in social media, we created several
items that were adapted from previous daily diary studies (Walters & Horton, 2015; Wenninger,
Krasnova, & Buxmann, 2014). These items were meant to assess active (e.g., sending messages
to a friend) and passive (e.g., viewing images of friends) participation. In the first two samples,
items were worded specifically for Facebook use, whereas the items in the third sample were
edited to more broadly include many forms of social media, such as Instagram. Edited items
occur after the backslash. Participants were asked, “Of the time you spent on Facebook/social
media today, to what extent did you engage in the following activities?” The items were:
“Passively scrolling through my news feed/Passively scrolling through the feed,” “Commenting
on friends’ posts, status updates, pictures, etc./Commenting on posts or photos,” “Messaging
friends/Direct messaging friends,” “Updating my status/Updating my status/profile,” “Uploading
pictures or videos/Publishing posts or photos,” “Searching through specific people’s profiles or
pictures/Looking at specific people’s accounts,” and “Playing games.” Responses were recorded
36
on a 7-point scale (1 = Not at all, 7 = A great deal). The results across the studies did not differ
meaningfully, so we combined the items for a composite score.
Nostalgia. To measure daily states of nostalgia, we asked participants to indicate the
extent to which the PINE statements described them today. Items were worded in the past tense
(“How nostalgic did you feel today?”, “To what extent did you feel sentimental for the past?”,
“How much did you feel a wistful affection for the past?”, “To what extent did you feel a
longing to return to a former time in your life?”). Responses were recorded on a 7-point scale (1
= Not at all, 7 = Very much).
Temporal thoughts. To assess convergent and discriminant validity at the daily level, we
included three items to assess the extent to which participants thought about the past, present,
and future each day: “Today, how often did you think about things that had occurred in the
past?”, “How often were you focused today on what was happening in the moment?”, and
“Today, how often did you think about things that are to come in your future?” These single
items have been adapted from a longer trait version (Shipp, Edwards, & Lambert, 2009) and
have been used reliably at the daily level (Rush & Grouzet, 2012). Responses were recorded on a
9-point scale (1 = Never, 9 = Constantly).
Well-being. Similar to affect in Study 2, daily affective states were measured using a
circumplex model. Participants were asked to indicate how strongly they felt each adjective
today on a 7-point scale (1 = did not feel this way at all, 4 = felt this way moderately, 7 = felt this
way very strongly). The same adjectives from Study 2 were used in the diary studies. In addition
to the 20 adjectives used to measure the affect circumplex, loneliness was assessed with the
items alone and lonely, similar to the methods and items used to assess daily states of loneliness
in previous research (e.g., Doane & Adam, 2010; Jonason, Webster, & Lindsey, 2008).
37
Daily states of satisfaction with life were assessed with a single item: “How satisfied
were you with your life today?” Responses were recorded on a 7-point scale (1 = not at all, 7 =
very much).
Daily states of meaning in life were distinguished by the extent to which one found
meaning in life (presence) and the extent to which one searched for meaning in life (search) on
that day. Presence was assessed with the items, “How meaningful did you feel your life was
today?” and “How much did you feel your life had purpose today?”; search was assessed with
the items, “How much were you searching for meaning in your life today?” and “How much
were you looking to find your life’s purpose today?”, similar to previous diary studies that have
assessed these constructs (e.g., Newman, Nezlek, & Thrash, 2018; Steger & Kashdan, 2013).
Responses were recorded on a 7-point scale (1 = not at all, 7 = very much).
Daily states of inspiration were measured with three items that have been adapted from a
trait measure to be administered at the daily level (Thrash & Elliot, 2003; Thrash, Elliot,
Maruskin, & Cassidy, 2010). These items were, “Something I encountered or experienced
inspired me today,” “Today I felt inspired,” and “Today I was inspired to do something”.
Responses were recorded on a 7-point scale (1 = Not at all, 7 = Very strongly).
Regret was captured with three items that were adapted from a trait measure (Schwartz et
al., 2002). Similar to Newman, Schug, Yuki, Yamada, and Nezlek (2018), the items were
reworded at the daily level: “Whenever I made a choice today, I was curious about what would
have happened if I had chosen differently,” “Today, when I thought about how I’m doing in life,
I often thought about the opportunities I had passed up,” and “Whenever I made a choice today, I
tried to get information about how the other alternatives would have turned out.” Responses were
38
recorded on a 7-point scale (1 = Strongly disagree, 4 = Neither agree nor disagree, 7 = Strongly
agree).
Daily states of self-esteem were measured with four items that were adapted from
Rosenberg’s (1965) 10-item trait measure to reflect the daily state (Nezlek, 2005). These items
were “Today, I felt like a failure,” “Today, I felt that I had many good qualities,” “Today, I
thought I was no good at all,” and “Today, on the whole, I was satisfied with myself.” Responses
were recorded on a 7-point scale (1 = very uncharacteristic of me today, 7 = very characteristic
of me today).
Rumination and reflection were assessed with three items for each construct that were
adapted from the trait measures developed by Trapnell and Campbell (1999). The rumination
items were “How much today did you ruminate or dwell on things that happened to you?”, “How
much today did you play back over in my mind how you acted in a past situation?”, and “How
much today did you spend time rethinking things that are over and done with?”; the reflection
items were “How much today did you think about your attitudes and feelings?”, “How much
today did you think about the nature and meaning of things?”, and “How much today did you
think introspectively or self-reflectively, i.e., about yourself and what you are like?”. Because the
reliability for reflection was not as high as we had hoped (.46), we removed the second item
following the advice of Nezlek (2012) and practice of Newman and Nezlek (2019).
Optimism was measured with three items that were adapted and reworded from the Life
Orientation Test-Revised (Scheier, Carver, & Bridges, 1994). These items were “I usually
expected the best today”, “Today, I was optimistic about my future”, and “Overall, I expected
more good things to happen to me today than bad.” Responses were recorded on a 7-point scale
(1 = very uncharacteristic of me today, 7 = very characteristic of me today).
39
Results
Overview. These data were multilevel in nature such that i days were nested within j
persons. Because of this nested structure, we could not assume independence among
observations, so we used multilevel modeling to differentiate between- and within-person
variation. We used the program HLM 7.01 (Raudenbush, Bryk, & Congdon, 2011) for all
analyses and reported unstandardized coefficients. We began by presenting descriptive statistics
of each variable by providing estimates of the means, the amount of variance between- and
within-individuals, and the reliability of each variable. Next, we analyzed the within-person
relationships between nostalgia and daily events to understand when people were likely to feel
nostalgic. We also provided convergent and discriminant validity by examining the extent to
which nostalgia covaries with daily thoughts about the past, present, and future. After these
models, we examined within-person relationships between nostalgia and well-being and
variables relevant to well-being, such as regret, inspiration, and rumination. We built models
with and without controls for negative events. Finally, we examined lagged analyses as one
potential method of testing causal pathways involving nostalgia.
Descriptive statistics. To provide estimates of the means and variances, we created
unconditional or null models, which means that each variable was entered as the outcome or
dependent variable in separate models without any predictors. The intercept was allowed to vary
randomly and the coefficient value takes into account the number of observations provided by
each participant. The unconditional model also provides estimates of within- and between-person
variation. These results are presented in Table 3. Nostalgia’s mean was 2.69 on a 1-7 scale, and a
closer examination of the distribution suggested the variable was positively skewed. On 30.6%
of the days, participants reported feeling not nostalgic at all. Roughly half of the variance of
40
nostalgia occurred within-individuals, similar to measures of affect and loneliness. The means of
all of the constructs were sufficiently far away from the endpoints of the scales so ceiling effects
were not an issue.
To calculate the reliability of each variable, we followed recommendations by Nezlek
(2017). Three level models were created in which items were nested within days, and days were
nested within persons. The intercepts of these null models provide ratios of true variance over
total variance without confounding within- and between-person variation. These statistics are
presented in Table 3. Notably, the reliability of the four items measuring daily states of nostalgia
was reasonably high (.90).
To offer additional support of the construct validity of the trait PINE scale, we examined
the correlation between the daily average nostalgia score and the trait nostalgia score. The
correlation was calculated by taking the square root of the percent the between-person variance
from the nostalgia null model was reduced when the PINE scale was entered as a predictor at
level 2. This percentage of reduced variance is conceptually equivalent to r
2
. The square root, r,
was .72, indicating reasonable validity.
Relationships between daily events/temporal thoughts and nostalgia. To understand
when people were likely to experience nostalgia, we created two-level models in which days
were nested within persons. Nostalgia was the outcome measure and daily events were entered
group-mean centered (i.e., centered around each individual’s mean) at Level 1 to control for any
individual differences in these measures (Enders & Tofighi, 2007). Error terms were trimmed if
the random effects were not significant, defined loosely as p = .15 (as recommended by Nezlek,
2012, pp. 65–68). We also added a time variable, which was group-mean centered at level 1, to
41
account for a possible linear trend in the data. Doing so controls for such trends without formally
modeling autocorrelated error (Nezlek, 2012, pg. 114-117)
1
. The model was as follows:

Day level: yij (nostalgia) = β0j + β1j (positive social events) + β2j (negative social
events) + β3j (positive achievement events) + β4j (negative achievement
events) + β5j (time) + rij
Person level: β0j = γ00 + u0j
β1j = γ10 + u1j
β2j = γ20 + u2j
β3j = γ30 + u3j
β4j = γ40 + u4j
β5j = γ50 + u5j
Daily states of nostalgia were positively related to negative social events, γ20 = .30, t =
3.58, p < .001, and negative achievement events, γ40 = .21, t = 3.79, p < .001, and were not
significantly related to positive social events, γ10 = .05, t = 1.13, p = .26, or positive achievement
events, γ30 = -.00, t <1, p = .93. To interpret these unstandardized coefficients, as negative social
events increase by 1 point on the raw scale (0 = did not occur, 4 = occurred and extremely
important) for the average individual, nostalgia increases by .30 on the raw scale (1 = Not at all,
7 = Very much) holding all other daily events constant. That is, participants on average were
likely to feel nostalgic when negative events occurred. The strengths of the relationships between

1
Time coefficients indicated a slight negative autocorrelation (ranging from b = -.00, t = .10, p =
.92, to b = -.03, t = 4.91, p < .001), but inclusion of the time coefficient did not meaningfully
change the fixed effects of primary interest (the largest change of a fixed effect was from b = .53,
t = 7.16, p < .001, to b = .57, t = 7.96, p < .001).
42
nostalgia and social and achievement events were not significantly different, positive: χ
2
(1) =
.62, p > .5; negative: χ
2
(1) = .62, p > .5, so we aggregated across social and achievement events
to create composite positive and negative event scores. We additionally constrained the
coefficients to be equal with a chi-squared based test of fixed effects. Consistent with the notion
that the “bad is stronger than the good” (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001),
the relationship between nostalgia and negative events, γ20 = .53, t = 7.16, p < .001, was stronger
than the relationship between nostalgia and positive events, γ10 = .08, t = 1.25, p = .21; χ
2
(1) =
18.57, p < .001.
Next, we entered the nostalgic events variable as a sole predictor group-mean centered
and found a positive relationship with nostalgia, γ10 = .29, t = 7.27, p < .001. Likewise, we found
significant positive relationships between nostalgia and helping behavior, γ10 = .27, t = 3.01, p <
.01, between nostalgia and active social media use, γ10 = .21, t = 4.30, p < .001, and between
nostalgia and passive social media use, γ10 = .15, t = 5.00, p < .001. This means that people were
likely to feel nostalgic when they met friends/acquaintances they hadn’t seen in a long time,
heard a song they hadn’t heard in a while, helped others, and engaged in social media either
actively or passively.
Finally, to examine convergent and discriminant validity, we assumed participants would
be more likely to think about the past than the present or future when they felt nostalgic. To test
this, we created a model in which nostalgia was the outcome measure and past (“Today, how
often did you think about things that had occurred in the past?”), present (“How often were you
focused today on what was happening in the moment?”), and future (“Today, how often did you
think about things that are to come in your future?”) were entered simultaneously group-mean
centered at Level 1:
43

Day level: yij (nostalgia) = β0j + β1j (past) + β2j (present) + β3j (future) + β4j (time) +
rij
Person level: β0j = γ00 + u0j
β1j = γ10 + u1j
β2j = γ20 + u2j
β3j = γ30 + u3j
β4j = γ40 + u4j
As predicted, people were likely to feel nostalgic when thinking about the past, γ10 = .41, t =
24.90, p < .001, rather than the present, γ20 = .01, t < 1, p = .38, or future, γ30 = .01, t < 1, p = .38.
Relationships between nostalgia and well-being and related constructs. In the next set
of models, we examined the relationships between daily states of nostalgia and various well-
being measures and other relevant measures that have been linked to nostalgia in previous
studies. Nostalgia was entered as a group-mean centered predictor at level 1 and each well-being
variable was entered as the outcome measure in separate analyses.

Day level: yij (well-being) = β0j + β1j (nostalgia) + β2j (time) + rij
Person level: β0j = γ00 + u0j
β1j = γ10 + u1j
β2j = γ20 + u2j
As can be seen in Table 4, on days when people felt nostalgic, they also reported greater negative
affect (both activated and deactivated), loneliness, regret, rumination, reflection, searching for
meaning, and inspiration. On these days, they also reported less satisfaction with life and self-
44
esteem. Nostalgia was not significantly related to positive activated affect, positive deactivated
affect, presence of meaning in life, or optimism.
Given that people felt nostalgic when negative events occurred, it is possible that the
negative relationships between nostalgia and well-being could be caused by negative events
which would presumably lower well-being. To test this possibility, we created models in which
we statistically adjusted for negative events by adding this measure as a predictor along with
nostalgia at level 1. The results of these analyses remained largely the same although the
relationships between nostalgia and well-being were slightly attenuated (See Table 4). These
analyses showed that the negative relationships between nostalgia and well-being cannot simply
be attributed to the negative effects associated with negative events.
Lagged analyses. To provide some insight into the direction of the effects between
nostalgia, daily events, and well-being, we examined one-day lagged relationships between these
measures (for a discussion of the logic of such analyses, see Nezlek, 2012, pg. 111-114). We
used temporal precedence as a proxy for causality (West & Hepworth, 1991) while still
acknowledging the caveat that third variables could potentially explain the relationships. To test
the lagged effect to nostalgia, yesterday’s nostalgia and yesterday’s daily events/well-being were
used to predict today’s nostalgia. To test the lagged effect from nostalgia, today’s daily
events/well-being were the outcome measure:

Lag to nostalgia: yij (nostalgia day n) = β0j + β1j (nostalgia day n -1) + β2j (daily event/well-being
day n -1) + rij
Lag from nostalgia: yij (daily event/well-being day n) = β0j + β1j (nostalgia day n -1) + β2j (daily
event/well-being day n -1) + rij
45
In the first set of models, yesterday’s loneliness, γ20 = .05, t = 2.00, p < .05, was positively
related to today’s nostalgia, and yesterday’s active social media use, γ20 = -.11, t = 2.15, p < .05,
was negatively related to today’s nostalgia. Reverse lagged effects involving these variables
were not significant (all ts < 1.13, ps > .25). This suggests that loneliness leads people to feel
more nostalgic on the following day, and active social media use leads people to feel less
nostalgic the following day. In the second set of models, yesterday’s nostalgia was positively
related to today’s negative events, γ10 = .02, t = 2.34, p = .02; γ10 = .02, t = 2.60, p = .01 (both
social and achievement, respectively), thinking about the past, γ10 = .14, t = 2.67, p < .01, and
rumination, γ10 = .17, t = 2.46, p < .05, and was negatively related to PD, γ10 = -.05, t = 2.02, p <
.05. Reverse lagged effects were not significant (all ts < 1.46, all ps > .14)
2
. This suggests that
nostalgia could lead people to experience negative events, to think about the past more, to
ruminate, and to feel less peaceful and calm on the following day. Finally, there were significant
positive lagged relationships from ND to nostalgia, γ20 = .06, t = 2.07, p < .05, and from
nostalgia to ND, γ10 = .05, t = 2.20, p = .03. This means that yesterday’s nostalgia is likely to
make one feel sad and depressed on the following day, and yesterday’s sadness and depression
are likely to lead one to feel more nostalgic on the following day. All other lagged relationships
were not significant (all ts < 1.55, ps > .12). In sum, nostalgia tends to have mostly negative
effects on one’s well-being the following day.

2
Because loneliness was positively related to tomorrow’s nostalgia, we controlled for loneliness
in the other lagged analyses. Substantive conclusions remained the same, namely that nostalgia
was still significantly related to tomorrow’s negative social and achievement events, thinking
about the past, rumination, and PD.
46
Discussion
These results show that nostalgic feelings varied considerably from day to day. People
were more likely to feel nostalgic when negative events occurred than when positive events
occurred. They were also likely to feel nostalgic on days when they helped others, were
reminded of old friendships or music, felt inspired, and engaged in social media use. Despite a
few positive or mixed effects, the predominant finding was that people reported lower levels of
well-being on days when they felt nostalgic, and these effects remained even after statistically
adjusting for negative events. Lagged relationships also indicated that experiencing nostalgia on
one day was negatively related to one’s well-being on the following day.
Study 4: Momentary States of Nostalgia
Study 3 showed that everyday nostalgia relates negatively to well-being, in contrast to the
positive effects of nostalgia observed in experimental laboratory studies. This observed
discrepancy could be due to differences in the measurement of nostalgia and/or differences in the
extent to which nostalgia has been measured or manipulated in ecologically valid contexts.
Alternatively, this discrepancy could be due to differences in the questionnaire reporting period.
In the experimental studies, nostalgia was manipulated and the dependent variable was measured
either immediately or within a few minutes of the manipulation. In contrast, participants in Study
3 were asked to reflect on their entire day. It is possible that nostalgia has immediate positive
benefits but that these effects dissipate relatively quickly. If so, the benefits of nostalgia may not
be captured by end-of-day diaries because they may dissipate before participants complete their
diaries.
To address the latter possibility, we conducted an ecological momentary assessment
study in which participants completed reports of how nostalgic they felt at randomly selected
47
moments during the day, thus shrinking the temporal distance between experience and report.
Random selection of time points throughout the day aims to capture a representative sample of
the larger population of time points in participants’ current lives (Shiffman et al., 2008). If
nostalgia has an immediate positive effect, people should report high levels of well-being at
moments when they feel nostalgic. Alternatively, if the positive effects of nostalgia are limited to
extreme and memorable episodes, positive within-person relationships between momentary
nostalgia and momentary well-being should not be observed in EMA data, which privilege the
more modest experiences of daily life.
Method
Study 4 was approved by the Institutional Review Board at the University of Southern
California under the ID UP-17-00143.
Participants and procedure. 79 undergraduate students signed up for the study in
exchange for research credits. Participants initially completed a questionnaire containing a few
brief personality measures (nostalgia, meaning in life questionnaire, neuroticism) and some
demographics. The questionnaire also contained instructions about the procedure of the study
and how to download the Personal Analytics Companion (PACO) app on their mobile phone
(Evans, 2016).
Notifications were sent to the participant via the PACO app at 8 random times during the
day from 9:00am until 10:00pm. Each notification occurred at least 45 minutes after the previous
notification. After receiving the notification, participants could open their app and complete a
short questionnaire. Consistent with the practice of a recent EMA study (Hofmann, Wisneski,
Brandt, & Skitka, 2014), the notifications were accepted up until two hours after the notification
48
was sent. Participants received notifications each day for 7 days so that both weekday and
weekend days could be represented.
Seven participants decided to drop out of the study after signing up or after completing
just a few responses due to scheduling issues or for unknown reasons. Two other participants
completed less than 40% of the notifications. Data were analyzed from 70 participants (Mage =
20.53, SD = 1.63, 75.71% female) who completed 2,922 momentary reports. On average,
participants completed 41.74 (75.3%) responses (SD = 7.79, minimum percentage was 44.64%).
Measures. At each notification, participants answered three questions about where they
were, what they were doing and who they were with. Next, they completed 8 items about their
emotional states, and individual items about how nostalgic they felt, how meaningful they found
their lives at the moment, and how optimistic they felt about their life at the moment.
The goal in asking the three questions about the activity of the participant was to capture
a broad sense of what activities covary with momentary states of nostalgia. Given that this was
the first study to assess nostalgia in the moment, we thought such questions would be
informative. We realize that these questions are not comprehensive in capturing all possible
situations, as is the goal of questionnaires such as the DIAMONDS (Rauthmann et al., 2014),
Riverside Situational Q-Sort (e.g., Sherman, Nave, & Funder, 2010), or CAPTION (Parrigon,
Woo, Tay, & Wang, 2017). Because such questionnaires require many items, we opted instead
for a brief set of three items to capture the activity of the participant.
The first question asked, “Where are you right now?” with the following options:
Home/dorm/apartment, At a friend’s place, School, Traveling, and Other. The second question
asked, “What are you doing right now?” with the options: Working/studying, Eating, Exercising,
Traveling, and Other leisure. The third question asked, “Who are you with?” with the following
49
options: Friends, Coworkers/classmates, Family, Strangers, and Alone. For each question, the
response options were not mutually exclusive; that is, participants were allowed to select
multiple options.
Following the questions about the participants’ activity, questions regarding well-being
were included to capture some of the corresponding well-being related measures that have been
used in laboratory settings, such as positive affect (Wildschut et al., 2006), meaning in life
(Routledge et al., 2011), and optimism (Cheung et al., 2013). Therefore, we included single
items to measure meaning in life (“How meaningful do you find your life right now?”) and
optimism (“How optimistic do you feel about your life right now?”). In terms of emotions, rather
than focusing exclusively on positive affect, we additionally included negative affect items.
Similar to the daily diary studies, we relied on an affective circumplex model and used two items
for each quadrant by selecting items that had high factor loadings from the previous studies.
Positive activated affect was assessed with excited and enthusiastic; positive deactivated affect
was assessed with calm and relaxed; negative activated affect was assessed with tense and
stressed; negative deactivated affect was assessed with depressed and sad. Participants were
asked, “How [emotion adjective] do you feel right now?” The single item for nostalgia was,
“How nostalgic do you feel right now?” Participants answered each item by responding on a 7-
point scale (1 = not at all, 7 = very much).
Results
Overview. To account for the nested data structure, we used multilevel modeling. In
most of the models, we nested moments within days, and days were nested within persons to
account for between-person variation, within-person between-day variation, and within-person
within-day variation. In the preliminary models, we examined the reliabilities of the affect items.
50
We also ran basic descriptive statistics and unconditional models to understand how much
variation of each construct occurred at each level of analysis. In the first primary set of models,
we examined the relationships between nostalgia and momentary activities in an exploratory
manner to understand which types of activities were most likely to covary with momentary states
of nostalgia. In the second primary set of analyses, we examined the within-person relationships
between momentary states of nostalgia and momentary states of affect, meaning in life, and
optimism. Finally, we examined lagged analyses to determine what type of short-term effects
nostalgia had on affect, meaning in life, and optimism.
Descriptive statistics. Reliability analyses for the affect measures were conducted by
nesting items within moments, and moments within persons. A response variable at the item
level was the dependent variable in unconditional models. Similar to the reliability analyses from
the diary studies, the reliability estimate of the intercept provides an estimate of the true variance
over total variance, a classic definition of reliability. This method of calculating reliability does
not confound between- and within-person variation as Cronbach’s alpha would (Nezlek, 2017).
The reliabilities of the affect measures were .75 or higher. All other measures were assessed with
a single item and their reliability estimate could not be calculated.
To provide estimates of how much variation of each construct occurred at each level of
analysis, unconditional models were run in which moments were nested within days, and days
were nested within individuals. See Table 5 for the descriptive statistics. More than half of the
variation for nostalgia, meaning in life, and optimism occurred between individuals. Of the
within-person variation, more than half occurred within-day as opposed to between-day. For PA,
PD, and NA, more variation occurred within-individuals within-day than either within-
individuals between-day or between-individuals. About half of the variation for ND occurred
51
between-individuals and about a third of the variation occurred within-individuals within-day.
These results suggest that sufficient within-individual within-day variation occurred to examine
within-person relationships between momentary states of nostalgia and well-being related
constructs.
The distribution of nostalgia was positively skewed. Participants reported feeling not at
all nostalgic 51.67% of the total moments.
Relationships between nostalgia and momentary events. To understand when
participants felt nostalgic, we created models involving the type of activity, the location of the
participant, and the type of people the participant was with. Because these variables were not
mutually exclusive, we created dummy codes for each answer to specify whether the person was
or was not engaged in a particular activity. Each dummy code was entered uncentered into the
model at level 1, and the level 1 intercept was dropped. This meant that the coefficient for each
dummy code represented the mean levels of nostalgia for each activity. These coefficients were
then constrained with a chi-squared based test of fixed effects to determine whether these
coefficients differed significantly. A variable representing the occasion of measurement was
entered group-mean centered to control for mean level changes in the outcome within each day
3
.

Momentary level: yijk (nostalgia)= π1jk (activity present dummy code) + π2jk (activity absent
dummy code) + π3jk (time) + eijk
Day level: activity present: π1jk = β10k + r1jk

3
Time occasion coefficients included positive and negative values (ranging from b = -.0004, t =
4.35, p < .001, to b = .0006, t = 4.40, p < .001), but inclusion of the time occasion coefficient did
not meaningfully change the fixed effects of primary interest (the largest change of a fixed effect
was from χ
2
(1) = 17.33, p < .001, to χ
2
(1) = 21.15, p < .001).
52
activity absent: π2jk = β20k + r2jk
time: π3jk = β30k + r3jk
Person-level: activity present: β10k = γ100 + u10k
activity absent: β20k = γ200 + u20k
time: β30k = γ300 + u30k

Participants were more likely to feel nostalgic when they were eating (γ = 2.35), with
friends (γ = 2.30), and with family (γ = 2.64) than when they were not eating (γ = 2.23), not with
friends (γ = 2.22), and not with family (γ = 2.21), χ
2
(1) = 4.50, p < .05; χ
2
(1) = 2.89, p = .08;
χ
2
(1) = 7.94, p < .01, respectively. They were less likely to feel nostalgic when they were at
school (γ = 2.13), working/studying (γ = 2.16), or with coworkers/classmates (γ = 2.04) than
when they were not at school (γ = 2.28), not working/studying (γ = 2.29), and not with
coworkers/classmates (γ = 2.29), χ
2
(1) = 14.75, p < .001, χ
2
(1) = 6.78, p < .01; χ
2
(1) = 21.15, p <
.001, respectively. All other contrasts were not significant (ps > .25).
Relationships between momentary nostalgia and well-being. Next, we examined the
within-person relationships between momentary states of nostalgia and meaning in life,
optimism, and affect. Nostalgia was entered group-mean centered as a level 1 predictor to
account for any individual differences in nostalgia, and each of the other variables were entered
separately as outcome measures. A time variable representing the occasion of measurement was
also entered group-mean centered to control for mean level changes in the outcome within each
day.

53
Momentary level: yijk (well-being) = π0jk + π1jk (nostalgia) + π2jk (time) + eijk
Day level: intercept: π0jk = β00k + r0jk
nostalgia: π1jk = β10k + r1jk
time: π2jk = β20k + r2jk
Person-level: intercept: β00k = γ000 + u00k
nostalgia: β10k = γ100 + u10k
time: β20k = γ200 + u20k
As can be seen in Table 5, nostalgia was positively related to ND but was not significantly
related to any of the other affect variables, meaning in life, or optimism. That is, when
participants felt nostalgic, they were also likely to feel depressed and sad.
Although non-significant results do not mean that no effect exists, it is possible to
compare the strengths of the relationships between 1) nostalgia and ND and 2) nostalgia and
other well-being variables. Doing so would provide more conclusive evidence that the main
relationship worth paying attention to is the relationship between nostalgia and ND. Stated in
other words, a demonstration that certain relationships are significant while others are not
significant provides some useful information. Demonstrating that the significant relationship
with ND is significantly stronger than the relationships with other variables strengthens the
argument that nostalgia is more likely to covary with momentary negative states than positive
ones.
To compare the strengths of these relationships, we “stacked the data” by creating an
item level file in which a response variable alternated between ND and one of the other well-
being variables. A similar technique was described by Bauer, Preacher, and Gil (2006) to
compare direct and indirect effects simultaneously in multilevel mediation analyses. In our
54
models, items were nested within moments, moments were nested within days, and days were
nested within persons in a four-level model. Dummy codes at level 1 for ND and the other
respective well-being variable were entered uncentered, and the level 1 intercept was dropped.
Nostalgia was entered group-mean centered at level 2, and the coefficient between nostalgia and
ND was constrained to the coefficient between nostalgia and the other well-being construct. The
strength of the relationship between nostalgia and ND was stronger than the relationships
between nostalgia and meaning in life, χ
2
(1) = 7.44, p < .01; optimism, χ
2
(1) = 5.43, p < .05; PA,
χ
2
(1) = 8.77, p < .01; and PD, χ
2
(1) = 13.69, p < .001. In sum, the positive relationships between
nostalgia and meaning in life, optimism, and PA were not only small and nonsignificant, they
were significantly weaker than the relationship between nostalgia and ND.
Lagged analyses. Finally, to examine any short-term effects that nostalgia may have on
well-being, we ran lagged analyses. In such models, the amount of time between measurements
are assumed to be roughly equal, an assumption that is easily met in daily diary studies but not in
EMA studies that intentionally schedule notifications at random times. Therefore, we created
subsets of the data that included responses recorded within certain similar amounts of time.
These subsets included responses within 90 minutes, 120 minutes, and 180 minutes of a previous
response, as well as responses between 0-59 minutes, between 60-119, and between 120-179
minutes of a previous response. Doing so obviously lowered the number of observations which
lowers statistical power and representativeness of the time points. Therefore, following the
recommendations of Bolger, Stadler, and Laurenceau (2012), we conducted power analyses
using MPlus V8 (Muthén & Muthén, 2017) by running simulations based on the parameters
obtained from the same-moment within-person relationships presented above. Assuming an
estimated within-person correlation of r = .30 (a medium effect size by standard conventions),
55
only the time windows of 0-120 and 0-180 following a previous response yielded power
estimates close to or above the recommended value of .80 (.77 and .81, respectively). Hence,
these time frames were used in the analyses.
The lagged analysis models were created similarly to the ones in Study 3. In the models
with responses that occurred within 120 minutes of the previous response (n = 1,467), there were
no significant relationships between nostalgia and meaning in life, optimism, or any affect
measure (all ts < 1.47, ps > .14). In the models with responses that occurred within 180 minutes
of the previous response (n = 1,965), nostalgia at time n - 1 was positively related to PA at time
n, γ = .10, t = 2.58, p = .01, and was negatively related (marginally) to PD at time n, γ = -.08, t =
1.85, p = .065. All other lagged relationships were not significant (all ts < 1.43, ps > .15).
Potential third variable critiques aside, this suggests that nostalgia could increase feelings of
excitement and enthusiasm up until roughly three hours later, but it also decreases feelings of
calm and relaxation during this same time window.
Discussion
Nostalgia varied considerably from moment to moment during the course of the day.
People reported feeling nostalgic when they were eating, with friends, and with family, and they
reported feeling less nostalgic when they were at school, working/studying, or with
coworkers/classmates. Critical to our main hypothesis, people were likely to feel depressed and
sad when they felt nostalgic. Momentary nostalgia did not covary significantly with positive
affect, meaning in life, or optimism. Lagged relationships were mostly non-significant with the
exception that people were likely to feel greater PA and lower PD up to three hours later. In
contrast to experimental studies that showed momentary positive effects of recall-induced
56
nostalgia on well-being, nostalgia was negatively related to concurrent well-being when
measured in ecologically valid contexts during the course of the day.
Study 5: Comparing Recalled and Daily Nostalgic Events
The results from our diary and ecological momentary assessment studies showed that
nostalgia was negatively related to well-being, whereas many experimental studies showed that
nostalgia has a positive effect on well-being. To address this discrepancy, we ran a study in
which participants wrote about their most nostalgic experience (similar to the Event Reflection
Task) and their everyday experiences that made them feel nostalgic in daily life. As discussed in
the introduction, people are likely to view their most nostalgic experiences more positively than
everyday experiences of nostalgia. By definition, the “most” nostalgic experiences are likely to
be more extreme, more meaningful, and more memorable. They are also more distant in time and
their representation is therefore likely to be more stylized and stripped of tangential details than
representations of very recent events (Trope & Liberman, 2010). Moreover, negative affect
associated with past events fades faster than positive affect (Ritchie et al., 2006; Walker, Vogl, &
Thompson, 1997), increasing the likelihood that any mixed feelings that may have been
experienced concurrently are lost in later reconstructions. Each of these differences predicts that
studies based on recalling one’s most nostalgic experience should arrive at a more positive
picture of nostalgia’s relationship with well-being than studies based on more recent and
mundane experiences of nostalgia in everyday life.
To test this hypothesis, we asked the same participants to complete the Event Reflection
Task of Sedikides and colleagues (Sedikides et al., 2015; Wildschut et al., 2006) and a one-week
daily diary study, in counterbalanced order. This allows us to assess how ratings of positivity,
negativity, meaning in life, and self-esteem differ between the “most” nostalgic experience that
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participants’ recall when asked to do so and the ordinary experiences of nostalgia that they
record in a daily diary. In addition to analyses of participants’ own ratings, we conducted content
analyses to determine whether the topics described in the texts differed across recalled
experiences and daily experiences.
Method
Participants and procedure. This study was approved by the Institutional Review Board
at the University of Southern California under the ID UP-18-00183 and preregistered at
aspredicted.org under ID #9565 (https://aspredicted.org/4ic4c.pdf). Participants were 81 (Mage =
20.31, SD = 1.73; 81.5% female; 43.2%) undergraduate students from the same university as the
preceding studies and received course research credit. All participants completed the Event
Reflection Task (Sedikides et al., 2015; Wildschut et al., 2006) and a one-week daily diary study.
They were randomly assigned to complete either the Event Reflection Task first (n = 43) or the
diary study first (n = 38). Two days before the first daily questionnaire was administered, all
participants received an email with a Qualtrics link that included either the Event Reflection
Task and a few demographic questions or demographic questions only. The one-week diary
study procedure was identical to the procedure in Study 3. Two days after the final diary
questionnaire was distributed, all participants received another email with a link to a
questionnaire that contained either the Event Reflection Task and a few demographic questions
or the demographic questions only. All participants completed the Event Reflection Task only
once.
Data cleaning was conducted in a similar manner as Study 3. Responses that were
completed after 10:00am, duplicate responses, and responses that failed to correctly answer an
instructed response item were eliminated from final analyses. Participants who completed less
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than three valid daily questionnaires were also eliminated. Of the initial 535 daily questionnaires,
484 were retained for final analyses (90.47%); 81 of the initial 90 (90.0%) participants remained
as well. They completed an average of 5.98 of the 7 possible daily questionnaires (SD = 1.11,
median = 6, minimum = 3).
Measures. The Event Reflection Task materials were copied from Sedikides et al. (2015;
initially created by Wildschut et al., 2006). Participants were shown a definition of nostalgia and
were then asked to think of a past event that makes them feel most nostalgic. They were asked to
write four keywords relevant to this nostalgic event and were then asked to describe the
experience and how it made them feel in a text box. On the following screen, they were asked,
“How positive was this experience for you?” and “How negative was this experience for you?”
on 7-point scales (1 = Not at all positive, 7 = Very positive; 1 = Not at all negative, 7 = Very
negative, respectively). Next, meaning in life, self-esteem, and nostalgia were measured as states
with items that were slightly reworded from the daily items from Study 3. For example, meaning
in life items were, “How meaningful do you feel your life is right now?” and “How much do you
feel your life has purpose right now?” A few demographic questions followed.
The daily questionnaires included questions about daily events, affect, nostalgia, meaning
in life, self-esteem, satisfaction with life, and the past, present, and future that were same as
Study 3. Participants who reported some level of nostalgia (by endorsing a value greater than
“not at all” for any of the four items) were asked to think about the experience that made them
feel nostalgic today. They were asked to write down four keywords relevant to this nostalgic
event, and on the next page they were asked to describe the experience and how it made them
feel today. These instructions were the same as those from the Event Reflection Task but
reworded to make sense for the daily nature of the questionnaire. If the participant reported
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feeling not at all nostalgic for all four items, they were asked to think about an ordinary
experience today. Similarly, they were asked to write down four keywords relevant to the
ordinary event, and on the next page they were asked to describe the experience and how it made
them feel today. Similar to the Event Reflection Task questionnaire, participants were asked how
positive and negative this experience was to them with the exact same wording and response
scale.
Results
Event reflection task and diary comparisons. Of interest is whether the same person
reports differential subjective experiences after thinking about a past event that made them feel
“most nostalgic” (the wording of the ERT instructions) than after describing a recent everyday
event for which they indicated nostalgic feelings. To address this issue, we first compared the
mean ratings, within-individuals, of nostalgia, positivity, negativity, meaning in life, and self-
esteem between the Event Reflection Task and daily reports. Because daily reports were nested
within individuals, we used multilevel modeling. Each daily score was subtracted from that
specific individual’s respective ERT score to create a new difference score variable. This
difference score variable was entered as the outcome variable in an unconditional model (i.e., no
predictors at levels 1 or 2). The intercept coefficient provides an estimate of the difference
between the ERT score and the average daily scores while taking the nested data structure into
account.
Average ERT and daily scores aggregated across conditions (completing the ERT portion
before vs. after completing the diary portion) are presented on the left side of Table 6 and
statistical comparisons of the means obtained from the intercept coefficients are presented on the
right side of Table 6. Average daily reports come from unconditional models. Interaction effects
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were tested by adding a dummy-coded predictor uncentered at level 2 to determine whether the
condition (order of completing ERT and diaries) influenced the difference between ERT and
daily scores. Interaction coefficients were not significant with the exception of the effect for
nostalgia between ERT and daily nostalgia, b = .94, t = 2.81, p < .01, and marginally for self-
esteem between ERT nostalgia and ordinary reports, b = -.52, t = 1.81, p = .08. Main effects
within each group were significant and in the same direction, so we collapsed across conditions.
Consistent with our hypothesis, participants reported higher nostalgia, positivity, and
meaning in life and lower negativity during the ERT than during daily nostalgic reports. Self-
esteem levels did not differ significantly, however. Daily positivity, negativity, meaning in life,
and self-esteem scores were not significantly different between daily nostalgia and daily ordinary
experiences. In short, daily nostalgic experiences were no more or less positive than ordinary
daily experiences but were less positive and more negative than recalled nostalgic experiences
under ERT instructions.
Content coding. To shed more light on these differences, research assistants who were
blind to the purpose of the study provided content coding of each written text. Drawing on a
previous content analysis by Hepper and colleagues (Hepper et al., 2012; 2014), we used 35
categories of nostalgia that represent associations people have with nostalgia. Two research
assistants reported whether each of the 35 categories was present in the text (1 = present, 0 =
absent). To simplify the analyses, we organized the 35 categories into 3 groups according to
factor analyses performed by Hepper et al. (2014): longing for the past (e.g., longing/yearning,
fond memories), positive affect (e.g., happiness, comfort/warmth), and negative affect (e.g.,
sadness/depressed, pain/anxiety). A score of .40, for example, indicates that 40% of the
categories in that particular group were present in those written texts. ICCs of coders’ ERT
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ratings were reasonably high (.71, .45, and .72, for longing for the past, positive affect, and
negative affect, respectively), as were the reliabilities of the coders’ daily ratings (.64, .51, and
.66 for longing for the past, positive affect, and negative affect, respectively), so we aggregated
across coders’ ratings.
Consistent with the subjective reports, participants’ descriptions of ERT nostalgic
experiences contained higher percentages of material categorized as longing for the past and
positive affect than their descriptions of daily nostalgic experiences (see bottom of Table 6).
There were no significant differences in negative affect.
Discussion
Given the discrepancies between the findings of previous experimental studies and our
diary (Study 3) and EMA (Study 4) studies, Study 5 assessed how the event that people recall
when asked to describe the “most” nostalgic experience they can remember compares to the,
presumably more ordinary, events people recall in daily diaries. Not surprisingly, the daily
nostalgic events differed from the most nostalgic experiences people could remember: what the
same participants recorded in their daily diaries was less positive and more negative than what
they recalled about the most nostalgic experience they could remember. This suggests that the
positive effects of nostalgia on well-being observed in experiments (Sedikides et al., 2015) can
be attributed in part to the highly positive nature of the recalled nostalgic experiences. In daily
life, nostalgia seems more mundane, less intense, and less beneficial.
General Discussion
The purpose of these five studies was to measure nostalgia in ecologically valid contexts
to understand how nostalgia relates to daily experiences, feelings, and thoughts. To accomplish
this, we first created and validated a trait-version of the Personal Inventory of Nostalgic
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Experiences scale. When assessed as a trait measure (i.e., between-persons), nostalgia-prone
people generally reported lower well-being than people who were less nostalgia-prone. We
found that nostalgia was positively related to negative affect, regret, and depression; nostalgia
was negatively related to satisfaction with life, presence of meaning in life, and self-esteem.
Nostalgia-prone individuals also reported relatively high levels of avoidance motivation,
neuroticism, thinking about the past in a negative manner, and thinking about the present in a
fatalistic manner. Not all relationships were negative, however; nostalgia was positively related
to thinking of the past in positive ways, thinking of the present in hedonic ways, and empathy.
Thus, although most associations involving nostalgia and well-being were negative, we found
some support for the notion that nostalgia is a mixed emotion as suggested by previous findings
(e.g., Sedikides et al., 2015).
When assessed repeatedly in daily life, there was considerable within-person variation in
nostalgic states, similar to other measures of affect. At a within-person level of analysis, people
were more likely to feel nostalgic on days that included negative social and achievement events
than on days that included positive social and achievement events. Nostalgia was also negatively
related to daily and momentary states of well-being, and these relationships were not explained
by the occurrence of daily negative events. Lagged analyses also showed that nostalgia was
either negatively related, not significantly related, or both positively and negatively related to
well-being at a later moment in time or on the following day.
Although most within-person analyses showed that nostalgia was negatively related to
well-being and daily events, it is important to note a few positive or neutral relationships. People
were more likely to feel nostalgic on days when they helped others, felt inspired, were engaged
in social media, heard songs they had not heard in a long time or communicated in some manner
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with an old friend/acquaintance, and searched for meaning in life. At a momentary level, people
were more likely to feel nostalgic when they were eating and with friends and family. In
combination, the results from between- and within-person levels of analysis indicate that
nostalgia is a mixed emotion, albeit one that is more strongly and consistently associated with
negative than with positive affect.
This conclusion, based on assessments of everyday nostalgic experiences in ecologically
valid contexts, is opposite to the conclusions drawn from experimental studies that induced
nostalgia through recall tasks (Sedikides et al., 2015; Sedikides & Wildschut, 2018). One likely
reason for this discrepancy is that the experimental studies encouraged the recall of extreme
nostalgic experiences, which are more positive and less negative than the ordinary experiences of
nostalgia in everyday life, as indicated by the within-person comparisons of Study 5. Similarly,
studies that used preselected stimuli to induce nostalgia have relied mostly on positive stimuli
(e.g., Barrett et al., 2010; Routledge et al., 2011), which may highlight the positive aspects of
nostalgia. Hence, the conclusion that nostalgia is predominantly positive, and related to positive
well-being outcomes (Sedikides et al., 2015), may be limited to positive instances of nostalgia,
which these procedures selectively privilege. The observation does not hold up with more
representative samples of everyday nostalgic experiences captured with EMA (Study 4) or daily
diaries (Studies 3 and 5): daily experiences that trigger nostalgic feelings are less positive than
the experimental literature suggests and relate negatively (or less positively) to well-being.
In combination, this suggests that the affect and well-being outcomes associated with
nostalgia may depend on the nostalgia eliciting event: positively colored nostalgic experiences
are beneficial, but many, if not most, moments of nostalgia in everyday life have a more negative
flavor. If so, deliberately engaging in the recollection of extremely nostalgic moments may be
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beneficial, paralleling the results of experiments that prompt such deliberative recollections (e.g.,
Routledge et al., 2011; Wildschut et al., 2006). Reliving nostalgic moments may enhance well-
being and buffer against adverse effects of negative experiences as suggested by experimental
findings (e.g., Zhou et al., 2008). On the other hand, involuntarily experiencing nostalgia that is
elicited by situational cues may be predominantly negative, as indicated by the EMA (Study 4)
and diary (Studies 3 and 5) findings.
The proposed distinction between the deliberate and involuntary experience of nostalgia
also received some support when nostalgia was measured as an individual difference (Study 2).
The SNS contains several items that reflect an active, nostalgia seeking experience (e.g.,
“Generally speaking, how often do you bring to mind nostalgic experiences?”), whereas the
PINE does not. Paralleling the differences between experimental studies and EMA and diary
studies, the SNS is positively associated with well-being, whereas the PINE is negatively
associated with well-being. In addition, the SNS was also positively associated with approach
motivation, whereas the PINE was not significantly related to approach motivation. These
observations are consistent with the notion that actively pursuing nostalgia may have positive
effects on well-being, whereas involuntarily experiencing nostalgia due to contextual influences
may have negative effects on well-being. Future research may fruitfully test these conjectures.
Taking a step back, it is worth remembering Joe McGrath’s (1982, p. 70) admonition that
“all research strategies and methods are seriously flawed.” Reliance on multiple methodologies
can attenuate the problem by providing multiple complementary perspectives. Experiments excel
at addressing what can occur (e.g., “Can nostalgia increase meaning in life?”) and at testing a
hypothesized underlying process. In contrast, diary and EMA techniques excel at addressing
what typically does occur in real life (e.g., “Do people believe their lives are meaningful when
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they feel nostalgic?”), but provide limited insight into causality. Both types of questions are
important and diverging observations enrich our understanding of a phenomenon, raising new
questions for further testing.
Limitations and Future Directions
No set of studies comes without limitations. As is usually the case in nostalgia research,
participants were undergraduate students in the United States, which limits generalizations across
age groups but facilitates comparison with the large bulk of studies conducted with
undergraduate students in the United States and the United Kingdom.
Nevertheless, in future research on nostalgia, several age-related topics would be worth
considering. Do older adults feel nostalgic as often and as intensely as younger adults? Is the
relationship between nostalgia and well-being consistent across age groups or does it vary? What
types of daily experiences elicit feelings of nostalgia among people of various ages? Recent
findings indicate that older adults are more likely to experience mixed emotions more broadly
(Schneider & Stone, 2015), which might suggest that older adults would also feel nostalgic more
often than younger adults. Furthermore, older adults tend to experience and recall positive
emotions and experiences more than negative emotions and experiences (Mather & Carstensen,
2005). This suggests that when older adults feel nostalgic, their recollections might be more
positive than typical nostalgic recollections. Future research is needed to test such possibilities.
Relatedly, the time points that we randomly sampled were presumably representative of
this particular period of our participants’ lives, namely during the college years in young
adulthood. One could envision a sampling design in which time periods (e.g., young adulthood,
early parenthood, retirement, etc.) were randomly sampled from the larger population of time
periods of people’s lives. Although practically challenging, such a longitudinal design would
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allow researchers to learn more about which periods of life people might be likely to experience
nostalgia, such as the transition from high school to college or from the end of a career to
retirement.
A similar limitation is that participants were only sampled from the US which restrains
generalizability across cultures. Although people in many countries conceptualize nostalgia in
similar ways (Hepper et al., 2014), the types of daily experiences associated with daily states of
nostalgia may vary across cultures. The implementation of EMA studies on nostalgia in different
countries or cultures could shed light on this topic.
The same-day (Study 3) and same-moment (Study 4) within-person relationships between
nostalgia and daily events and well-being cannot provide causal evidence for the direction of the
effects. For example, negative social events, such as being made fun of by others, might lead
people to feel depressed, which could lead them to seek nostalgic memories or feelings.
Although we ran one-day lagged analyses in the diary study, some effects of nostalgia might not
last until the following day. Alternatively, certain daily experiences or even repeated experiences
might only affect well-being and/or nostalgia several days or weeks later. Longitudinal studies or
other EMA techniques with different reporting schedules would be needed to test such
possibilities.
An additional avenue for future research concerns the relationship between nostalgia and
daily events that have not been considered in previous research, such as negative achievement-
oriented events, such as failing an exam. Several studies have examined the positive social
connectedness aspect of nostalgia (Hepper, Ritchie, Sedikides, & Wildschut, 2012; Reid, Green,
Wildschut, & Sedikides, 2015; Wildschut et al., 2006), but have not considered how nostalgia
may be related to other (and predominantly negative) aspects of daily life. These negative daily
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experiences could be used in experimental manipulations to determine the consequences of
nostalgic feelings that are elicited from negative stimuli.
Conclusion
In sum, we find that nostalgia is a mixed emotion that varies both between and within
individuals. Nostalgia-prone individuals tend to report lower well-being and are characterized by
several negative traits, such as neuroticism and avoidance motivation, although they also report
greater empathy. In daily life, people are more likely to feel nostalgic on days when negative
social and achievement events occur than when positive events occur, although they are also
more likely to help others and feel inspired when they feel nostalgic. Daily and momentary
nostalgic states are consistently related to increased negative affect and are not related to
concurrent positive affect. Taken together, these findings diverge from experiments in which
participants are asked to recall their “most” nostalgic experience, which typically increases well-
being. Daily states of nostalgia are more negative, less positive and intense, and less beneficial
for well-being than recalled extreme nostalgic experiences. Our findings indicate that nostalgia
should be considered a mixed emotion that is more likely to covary with negative states than
positive ones.

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Transition
These studies have shown that the measurement of nostalgia in daily life can lead to
conclusions that differ from the conclusions drawn from experimental methods. In particular, the
Event Reflection Task requires participants to think of their most nostalgic experience, which is
not representative of the range of typical stimuli in daily life that elicit feelings of nostalgia.
The next chapter examines a similar comparison between daily life methods and other
methods that rely on extensive recall, which carries the risk of recall biases. In many studies,
participants are asked at one time to reflect on their life in general and to report on their
personality, attitudes, behaviors, or well-being. These types of judgments rely on various
heuristics and can be influenced by numerous factors. The following studies attempt to compare
how global evaluations of well-being compare to reports of well-being measured in daily life in
ecologically valid contexts.

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Chapter II: Global Reports of Well-Being Overestimate Aggregated Daily States

Newman, D. B., Schwarz, N., & Stone, A. A. (in preparation). Global reports of well-being
overestimate aggregated daily states

Abstract
When evaluating their lives, people can either reflect broadly on their life at one time or they can
provide repeated assessments during their daily lives. Global evaluations are reconstructions that
are influenced by peak, recent, and frequently occurring states, whereas daily reports reflect
naturally occurring variations in daily life. The present research compared the averages of
individual global evaluations and corresponding aggregated daily states from an ordinary two-
week period and used a range of well-being measures (life satisfaction, meaning in life, and
affect) and other relevant constructs (searching for meaning in life and nostalgia). Across all
measures, global reports were significantly higher than aggregated daily states. That is, when
people evaluate their lives at one time, they conclude that life is more extreme; life is more
satisfying and more meaningful, and positive and negative emotions are more intensely
experienced compared to their own reports in daily life.
Keywords: well-being, daily diary, ecological validity, global evaluations

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What offers a better depiction of a person’s life: a global evaluation or their day-to-day
experience? Global evaluations require people to bring to mind relevant aspects of their lives and
privilege memorable experiences, such as a wedding or an exotic vacation. Single assessments or
recollections of life in general necessarily omit ordinary and mundane experiences, such as
sitting in front of the computer. Assessments in daily life likely capture a more realistic picture
of how someone’s life is going but may miss some of the peak memorable experiences.
Understanding the distinction between global evaluations of one’s life and contextualized reports
of states has been an important topic in social and personality psychology. More specifically,
well-being can be assessed in similar manners, and the latter has been advocated by the
philosopher Jeremy Benthem and more recently by Kahneman (1999), who referred to the sum
of all momentary states of positive and negative feelings as objective happiness.
These distinct methods of assessing well-being have various strengths and weaknesses.
The goal of the present research was to compare the averages of specific global reports with their
corresponding aggregated daily states of well-being. Doing so provides insight into the cognitive
processes involved in each form of judgment and yields provocative implications for well-
being/social and personality psychology, namely that these different methods do not capture the
same construct.
Processes involved in global reports and aggregated states
Global reports of well-being, often assessed with either single-item measures (e.g., “All
things considered, how satisfied are you with your life as a whole these days?”; World Values
Survey) or multiple-item scales (e.g., Satisfaction with Life Scale), allow people to consider
longer periods of time that might include peak experiences or major life events, such as marriage
or career accomplishments. Clearly people are not able to replay their entire life as they make
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these judgments. Rather, people are influenced by chronically accessible information and
temporarily accessible information (Schimmack, Diener, & Oishi, 2002; Schwarz & Strack,
1999). Chronically accessible information refers to any type of information that is brought to
mind repeatedly over time. Temporarily accessible information can take the form of one’s
present mood (Schwarz & Clore, 1983), thoughts about your current romantic situation
(Schwarz, Strack, & Mai, 1991), or thoughts about the current state of the country (Deaton &
Stone, 2016). These sources of information can have profound effects on subsequent judgments
of global well-being reports.
This means that global evaluations reflect a process in which people perform a
confirmatory search for instances of the target judgment. The longer the reflection period, the
more extreme instances people will be able to find. This essentially produces a peak effect.
Additionally, the currently accessible information, such as how one’s life if currently going right
now, will influence this judgment. The net effect results in a judgment that is highly influenced
by the peak experiences that come to mind, tempered by the current situation, which is rarely as
extreme as the peak experience.
Studies that have asked people to recall a recent past experience support this process
model. For example, in one study, participants completed momentary reports of their satisfaction
and positive and negative affect at randomly selected times during a spring break vacation
(Wirtz, Kruger, Napa Scollon, & Diener, 2003). Recalled reports of each specific measure of
well-being was higher than the corresponding momentary average. Similarly, global reports of
how one typically feels while driving luxury cars are typically higher and not strongly related to
episodic reports of a recent driving experience (Schwarz & Xu, 2011). In other studies,
participants have been asked to recall their well-being, pain, fatigue or other health relevant
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variables from the preceding few days or weeks (Stone et al., 1998; Stone, Broderick, &
Schwartz, 2010). When the momentary average is compared with the recall, the recall is
typically higher than the momentary average (Broderick et al., 2008; Stone et al., 2010; Stone,
Broderick, Shiffman, & Schwartz, 2004). For example, participants completed momentary
reports of pain and fatigue at randomly selected times during the day, and they also completed
end-of-day reports of their pain and fatigue. End-of-day reports were significantly higher than
the average of momentary reports, although these effects were somewhat small (Stone et al.,
2010).
In addition to using global reports to characterize individuals, researchers can measure
individual differences by aggregating daily or momentary states. This method has been
advocated among researchers in various areas, including social interactions, romantic intimacy,
personality, and health behaviors (e.g., Affleck, Zautra, Tennen, & Armeli, 1999; Bolger, Davis,
& Rafaeli, 2003; Fleeson, 2001, Tennen, Suls, & Affleck, 1991) and could theoretically be
applied to individual differences in well-being. Doing so would eliminate or drastically reduce
any recall bias inherent in global reports. It would also incorporate the situation more
appropriately than global evaluations. Assuming the sample of time points constitutes a fairly
representative sample for this period of the individual’s life, an aggregation of these states may
provide a more “accurate” characterization of the individual.
Although perhaps more “accurate” in describing the attributes of an individual,
momentary or daily reports likely capture more mundane and less memorable experiences than
global reports. Hence, they may not accurately represent the way people think about themselves
and they may not predict future intentions as well as global reports (e.g., Wirtz et al., 2003).

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The present research
Previous research in this area has addressed different questions than the questions posed
by the current study. Much of the prior work has focused on the correlation of aggregated daily
or momentary states and global evaluations or recalls. Although momentary states measured
throughout the course of the day are different from end-of-day daily reports of states, researchers
have attempted to characterize individuals based on the aggregation of both types of
measurement. For example, Hudson, Anusic, Lucas, and Donnellan (2017) and Anusic, Lucas,
and Donnellan (2016) reported relatively weak correlations (rs ranged from .33 to .54) between
global reports of affect and affect assessed with the Day Reconstruction Method (DRM).
Correlations between global reports of affect and daily averages of affect in other studies have
been a bit higher though (rs ranged from .59 to .65; Newman, Nezlek, & Thrash, 2018). In other
health domains, the correlation between the recall and momentary average of pain and fatigue
has ranged from .81 to .90 (Stone et al., 2010).
The present research extends prior findings in several important ways. First, whereas
previous research has compared aggregated daily or momentary states with recall of that
experience, the present study compares aggregated daily states with global ratings. Second, the
present research expands the range of measures that has typically been considered among studies
that measure well-being. Well-being can be reasonably conceptualized as containing three
aspects: evaluative (e.g., how satisfied people are with their lives), experiential (e.g., how people
feel when living their lives), and eudaimonic (e.g., how meaningful or purposeful their lives
seem; see Kahneman, 1999; Schwarz & Strack, 1999; Steptoe, Deaton, & Stone, 2015, for a
discussion). In addition to measuring evaluative and experiential well-being (measures that have
dominated the well-being literature), we measured a sense of meaning and purpose in life.
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Moreover, we sought to examine two relevant constructs that have less normal distributions in
daily life, nostalgia and searching for meaning in life. The measurement of these additional
constructs allowed us to generalize our findings more broadly. Third, the present study
counterbalanced the order in which participants completed the global reports and the daily
reports, which allows for the possible examination of any order effect and provides insight into
how global judgments are formed. Given that people are influenced by peak experiences, recent
episodes, and frequently occurring events and states, global reports should be more highly
correlated with peak, recent, and average states among participants who complete the daily diary
reports before the global evaluations. When daily states are brought to mind through repeated
administration, they should influence a subsequent judgment (e.g., Schwarz et al., 1991). The
present study allowed for this examination.
Method
Participants and procedure. We conducted an initial study and replicated the findings
with a larger sample. The two studies had very similar procedures and measures across two
semesters. Because the results were nearly identical across semesters and for the sake of brevity,
we describe the method and results together.
Participants were undergraduate students who received course research credit. They were
instructed to think about their life as a whole as they completed a questionnaire at one time. They
also received daily questionnaires for two weeks and were instructed to think about their day as
they completed the daily questionnaires. Daily questionnaires were emailed to students at
9:00pm each evening. Reminder emails were distributed the following morning at 7:00am to
those who did not complete the questionnaire in the evening. Responses were accepted until
10:00am. Daily questionnaires were eliminated if they were completed after 10:00am, if they
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were duplicate entries, if the participant failed to correctly answer an instructed response item as
recommended by (Meade & Craig, 2012), or if the participant completed less than five valid
entries
4
. Of the initial 3,153 daily questionnaires, we used 2,984 (5.36% eliminated) daily
questionnaires in our final analyses, which included 244 participants (Mage = 20.21; SD = 2.09;
74.2% female). On average, participants completed 12.23 daily reports (SD = 2.12; minimum =
5, median = 13). The participants were also randomly assigned to either complete the global
evaluations before or after the two-week diary portion of the study. The global evaluations
questionnaire was administered two days before or two days after the two-week daily diary
period.
Measures. Global ratings of satisfaction with life were measured with the 5-item
Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985) with responses recorded
on a 7-point scale (1 = Strongly disagree, 7 = Strongly agree). Global ratings of presence and
search for meaning in life were assessed with an adapted version of the 10-item Meaning in Life
Questionnaire (Steger, Frazier, Oishi, & Kaler, 2006). The first item was changed from “I
understand my life’s meaning” to “My life is full of meaning,” and the second item was changed
from “I am looking for something that makes my life feel meaningful” to “I am searching for
something that makes my life feel meaningful.” These items were altered so that the
corresponding reworded items administered in the daily questionnaires would make more sense.
Responses were recorded on a 7-point scale (1 = Absolutely untrue, 7 = Absolutely true). Global
ratings of positive and negative affect were measured with items that have been used in
circumplex models that distinguish valence and arousal (e.g., Brandstaetter, 2007; Feldman-
Barrett & Russell, 1998; Nezlek, 2005). Positive activated (PA) affect items were enthusiastic,

4
Because daily questionnaires in the second study were longer than the daily questionnaires in the first study, daily
questionnaires from the second study completed in less than two minutes were also eliminated from final analyses.
76
delighted, happy, glad, and excited; positive deactivated (PD) items were calm, peaceful,
relaxed, contented, and at ease. Negative activated (NA) affect items were stressed, angry,
annoyed, tense, and nervous; negative deactivated (ND) affect items were depressed,
disappointed, miserable, gloomy, and sad. Responses were recorded on a 7-point scale (1 = do
not feel this way at all, 4 = feel this way moderately, 7 = feel this way very strongly). Global
ratings of nostalgia were assessed with the 4-item PINE scale (e.g., “How nostalgic do you
feel?”, “To what extent do you feel sentimental for the past?”; Newman, Sachs, Stone, &
Schwarz, in press). Responses were recorded on a 7-point scale (1 = Not at all, 7 = Very much).
Daily well-being measures were assessed by rewording several of the corresponding trait
items as is common practice in diary studies (Nezlek, 2012, pg. 32-33). Participants answered
questions about their daily affect using the same items that were used in the trait questionnaire,
and responses were again recorded on a 7-point scale that reflected the daily nature of the
questions (1 = did not feel this way at all, 4 = felt this way moderately, 7 = felt this way very
strongly). Daily nostalgia was measured with the PINE scale, but questions were reworded to be
appropriate for daily reports, e.g., “How nostalgic did you feel today?” Responses were recorded
on a 7-point scale (1 = Not at all, 7 =Very much). Daily satisfaction with life was measured with
two items that were adapted from the Satisfaction with Life Questionnaire (“I was satisfied with
my life today” and “The conditions of my life today were excellent”). Responses were recorded
on a 7-point scale (1 = Strongly disagree, 7 = Strongly agree). Presence and search for meaning
in life were also measured with two items each that were adapted from the Meaning in Life
Questionnaire (presence: “My life today was full of meaning” and “My life had a clear sense of
purpose today”; search: “Today, I was searching for something that makes my life feel
meaningful” and “I was looking to find purpose in my life today”) (Steger et al., 2006).
77
Responses were also recorded on a 7-point scale (1 = Absolutely untrue, 7 = Absolutely true).
Response scales for the daily measures were the same as the response scales for the
corresponding trait scores so that the averages could be compared.
Because the daily questions about meaning in life and satisfaction with life contained the
word “life,” we tested for any ambiguities in interpretation by randomly assigning half of the
participants in the second sample to answer the same questions reworded with the word “day”
instead of “life.” For example, the first item measuring presence of meaning in life was “My life
(day) today was full of meaning.” The wording of these items had no substantive effect on the
averages, so the analyses presented below reflect the aggregated scores across conditions.
It is also important to note that given the added burden of repeated daily questionnaires
on participants, we could not administer all of the daily items for satisfaction and meaning that
we administered for the global reports. To facilitate an appropriate comparison of the daily
reports and the global reports, we selected the two items from the global reports that mirrored the
daily report questions as reasonable indicators of the construct. Analyses that follow reflect the
two-item global reports of satisfaction with life, presence of meaning in life, and search for
meaning in life.
Results
Preliminary analyses. Descriptive statistics and reliability estimates from Cronbach’s
alpha for all global reports are reported in Table 7. To calculate descriptive statistics for the daily
reports, we used multilevel modeling to account for between- and within-person variation and
used the program HLM 7.01 (Raudenbush, Bryk, & Congdon, 2011). To examine reliabilities of
the daily measures, we first created an item level file that contained the scores of the individual
items. Items were nested within days, and days were nested within persons. The item variable for
78
each measure was entered as the outcome measure in separate unconditional models. The
reliability of the intercept provides a ratio of true variance over total variance, a common
definition of reliability (Nezlek, 2017). All daily measures had reasonably high reliabilities (See
Table 7).
Next, we ran two-level (days nested within people) unconditional models to examine the
amount of within- and between-person variation (See Table 7). These analyses showed that a
considerable amount of variation occurred at both levels. Next, the corresponding global measure
was entered at level 2 to examine the correlation between the global score and the average of the
corresponding daily measure. The correlation is sometimes referred to as a measure of validity.
The decrease in level 2 variation was divided by the total level 2 variation from the unconditional
model. The square root of this is analogous to a Pearson’s correlation. The correlation between
the trait measure and corresponding daily averages were all reasonably high with the exception
of searching for meaning in life.
Primary analyses. Finally, critical to the main purpose of the study, we compared the
means of the global reports with the corresponding aggregated means of the daily reports (See
Table 8). To do so, we subtracted each daily score from that person’s corresponding global
evaluation score. We then built unconditional models in which this new difference score variable
was entered as the outcome measure. The intercept was allowed to vary randomly, and no
predictors were entered into the model. Error terms with random effect p-values greater than .15
were trimmed from the models as recommended by Nezlek (2012, pp. 65-68). The intercept of
this model provides an estimated difference between the global reports and the aggregated daily
scores while maintaining the nested data structure. There were significant main effects for all
variables such that global reports were higher than daily averages.
79
Although all global measures were higher than aggregated daily states, some differences
were stronger than others. The satisfaction with life global-state difference was the smallest
(.30), followed by PD (.41) and the presence of meaning in life (.55). To compare these
differences statistically, we “stacked the data” by creating an outcome variable that alternated
between two difference scores (see Bauer, Preacher, & Gil, 2006, for a discussion of a similar
procedure). A dummy coded variable representing one of the difference scores was entered
uncentered at level 1 and the level 1 intercept was kept. The coefficient of the dummy-coded
variable represents the difference between the respective difference scores. These models
indicated that the satisfaction with life global-state difference was not significantly different from
the PD global-state difference, γ10 = -.12, 95% CI [-.27, .03], t = 1.59, p = .112, r = .43
5
, but it
was significantly different from the presence of meaning in life global-state difference, γ10 = -
.25, 95% CI [-.41, -.10], t = 3.23, p = .001, r = .45, and from all other measures (all γ10 < -.30, ps
< .003, rs > .44). These results show that the discrepancy between global reports of satisfaction
with life and aggregated daily states of satisfaction is not as large as the other respective well-
being discrepancies.
Finally, we examined the interaction of order (global reports completed before vs. after)
by measure (global vs. daily), which was significant for most measures (see Table 8). The
difference between global reports and aggregated daily states was larger among people who
completed the global reports before the daily diaries. The one exception to this pattern was

5
An effect size estimate, r, was calculated by taking the square root of the percent the within-
person variance from the null model was reduced when the dummy-coded variable was entered
as a predictor at Level 1.

80
satisfaction with life. The discrepancy between global satisfaction and aggregated daily
satisfaction was larger among those who completed the global reports after the daily diaries.
In addition to examining differences in means, we compared the correlations between 1)
peaks (maximum values), recent states (last three daily reports), and averages of daily states and
2) global reports across conditions. As expected, many of the correlations were stronger among
those who completed the global reports after the daily diary reports (see Table 9). These
differences were most pronounced in the correlations involving peak states and were more
evident in measures of satisfaction with life, meaning in life, and nostalgia than they were in
affective states. These findings reiterate the difference between the aggregation of daily states,
which are influenced by the present day, and global evaluations, which are influenced by peak
states, recent states, and frequently occurring states.
Discussion
The present study investigated two different methods of depicting how people’s lives are
going. Global evaluations of satisfaction with life, affect, presence of and search for meaning in
life, and nostalgia were consistently higher than their corresponding daily aggregates. This
confirms that people are not able to accurately replay their entire lives and create an average
report of how their lives have been (Bradburn, Rips, & Shevell, 1987). Rather, they appear to
reflect on key aspects of their lives, such as peak experiences and recent memories. The
memorable aspects of people’s lives are more extreme than daily life. Stated in other words,
daily life is more mundane and less intense than our biased reconstructions of our lives.
The discrepancy between global evaluations and daily states is consistent with and builds
upon previous research but also extends the research in important ways. Much of the previous
research has compared recollections of specific experiences, such as spring break vacations
81
(Wirtz et al., 2003), menstrual cycles (McFarland, Ross, & DeCourville, 1989), or EMA
reporting periods (Stone et al., 1998), with aggregated states during the experience. Other studies
have compared global reports of specific aspects of their lives (e.g., math anxiety) with online
experiences of the specific event (e.g., taking a math test; Goetz, Bieg, Lüdtke, Pekrun, & Hall,
2013). The general pattern that has emerged in these studies is that as psychological distance
increases, reports tend to increase, presumably because the level of abstraction has also
increased. Additionally, recalls tend to converge with lay beliefs about how their experiences
typically are or should be.
The present study has extended the current research by comparing global evaluations
with aggregated states, as opposed to recalls of specific periods. It has also increased the range of
well-being measures to include meaning in life. This has yielded several implications not only in
the field of well-being research, but more broadly in the areas of social and personality
psychology.
For example, is it better to measure personality traits by asking people to reflect on their
life at one time or should researchers measure momentary or daily states of personality in daily
life and examine the distribution of these states? The latter method, referred to as Whole Trait
theory has been advocated recently as a method of measuring individual differences in
personality traits while still capturing within-person variation (Fleeson & Jayawickreme, 2015).
Although beneficial in many regards, aggregating daily or momentary states may miss the peak
experiences that rarely happen but nevertheless influence people’s perceptions of themselves.
The aggregation of daily states may not capture individual differences in important life events
that do not occur on a daily basis.
82
Relatedly, the correlation between aggregated daily or momentary states and the global
report of that particular variable has been a common metric of scale validation in personality
psychology. Correlations in the range of .60 to .70 have typically been considered a reasonable
standard for convergent validity. The present results showed that although the correlations
between aggregated daily states of well-being and global reports of well-being were reasonably
high, the means were consistently higher in the global reports than the daily states. That is,
people who report high levels of global life satisfaction tend to report high levels of daily life
satisfaction, but the two measures are not capturing the same construct. Global evaluations
involve the reflection of peak experiences of their lives, whereas daily reports do not (Schwarz,
2012). Moreover, the correlation between aggregated daily states and global reports, often
labeled as a measure of validity, is influenced by the order in which these measures are
completed. When global reports are completed after repeated daily reports, the correlation
between the two are much stronger. Thus, the “validity” statistics should consider the order in
which these measured are completed.
The results also have several important implications more specifically for well-being
research. For example, according to a thorough review of published reports of global reports of
meaning in life, Heintzelman and King (2014) showed that the average is higher than the
midpoint of the scale and concluded that life is actually pretty meaningful. The present study
qualifies this conclusion by noting that life is pretty meaningful when people consider their life
as a whole, but it is less meaningful when people consider their daily experiences. This
discrepancy between global meaning in life and daily meaning in life is consistent with some
recent experimental findings that have shown that life is more meaningful as psychological
distance is increased, for example by imagining themselves in a distant location or by thinking
83
about themselves in the future or the past (Waytz, Hershfield, & Tamir, 2015). Our results
suggest that meaning can be found at higher levels when thinking about your life more broadly,
which allows for the recollection of specific experiences that may imbue life with meaning but
may not provide much daily meaning. For example, the recollection of saving someone’s life
five years ago may provide someone with lots of meaning when asked to reflect on life more
generally, but it may not provide much meaning every day, particularly if the saved person is not
involved in this person’s daily life.
The present research also contributes to a growing body of research comparing meaning
in life with satisfaction with life (e.g., Newman, Schwarz, Graham, & Stone, 2019; Tov & Lee,
2016). The discrepancy between global reports and daily aggregates was smaller for satisfaction
with life than it was for meaning in life or several of the affect measures. In thinking about this
discrepancy between global reports and daily aggregates, it is useful to think about affect first.
The gold standard for measuring affect in daily life is through EMA or daily diary methods. How
happy or sad someone is in daily life is best measured by asking that person how happy or sad
they are during randomly selected moments in daily life. Any discrepancy between a global
report or recall of affect and the online experience is considered an error, misremembering, or a
biased recall. It is noteworthy that this discrepancy is not as pronounced for satisfaction as it is
for affect. People’s global evaluation of how satisfied they are with their life is more consistent
with their daily experience than a global rating of affect is with their daily affective experience.
It is possible that daily satisfaction reports reflect not only daily experiences but also an
integration of how their life is currently going with how their day was.
The discrepancy between global and daily meaning was more similar to the affect
discrepancy than the satisfaction discrepancy. Whereas previous research has shown that daily
84
affect is more highly related to daily satisfaction than daily meaning in life (Tov & Lee, 2016),
our findings show that the affect discrepancy is more highly similar to the meaning in life
discrepancy than the satisfaction discrepancy. However, the meaning in life discrepancy needs to
be interpreted differently. There is no gold standard for meaning in life as there is for affect. That
is, how meaningful someone’s life is at the present (e.g., while writing a dissertation) may
depend on future life circumstances (e.g., whether that person becomes a productive and
successful professor).
It is also worth noting that the discrepancy between global reports and aggregated daily
states was considerably larger for searching for meaning in life and nostalgia than the other
variables. This could be due to the non-normal distributions of each variable in daily life.
Moreover, the correlation between aggregated daily states and global reports of searching for
meaning in life was considerably lower than other validity measures. This suggests that people
think about different aspects of their lives when they search for meaning in their lives in general
as opposed to searching for meaning in their daily lives, consistent with the results from
Newman et al. (2018).
Another interesting implication concerns the distinction between positively- and
negatively-valenced well-being measures. When reflecting on life in general, life seems more
meaningful, more satisfying, and more intensely full of positive emotions. This may lead some to
conclude that when evaluating your life, it is best to think of the big picture. However, doing so
would also lead to the conclusion that life is more stressful, sad, and depressing than it truly is.
This is consistent with much of the mindfulness research that shows that people can reduce stress
by focusing on the present (Fjorback, Arendt, Ørnbøl, Fink, & Walach, 2011). Focusing on life
85
in general instead of focusing on the present day or situation may have different effects on well-
being depending on the exact measure of well-being.
Finally, it is important to note that the discrepancy between global and daily aggregated
states was strongest among those who completed the global reports before the daily diary with
the exception of satisfaction with life. This pattern of results could be explained from a
consistency motivation account (Ross, 1989). Among those who completed the diary reports
first, those particular days provide a more accessible input than the distant days, which would
only be accessible if they were extreme. The daily reporting attenuates the advantage of
memorable episodes at the expense of more recent episodes. The stronger correlations between
peak, recent, and average daily states and global reports among those who completed the daily
reports before the global reports attests to this account. Accessible information influences a
subsequent judgment (e.g., Schwarz et al., 1991).
Limitations and future directions. There are a couple of limitations worth mentioning.
The first is that the two-week daily diary period may not be long enough to capture a truly
random and representative sample of days of the year. The goal of the study was to capture
typical days of the year. If we had included non-normal days, such as the final exam period or a
spring break vacation, average levels of well-being may have differed, which would alter the
discrepancy between daily aggregates and global reports. Comparing global reports with daily
averages over longer periods of time that include unique experiences remains a fruitful avenue
for future research.
Another limitation of the study was that participants’ affective reports were assessed at
the end of the day rather than in the moment. This daily recall introduces a certain amount of
86
bias (Shiffman, Stone, & Hufford, 2008). In future studies, aggregated affective states could be
measured with the use of EMA techniques.
Conclusion. There are different ways of assessing people’s well-being. Thinking about
and reflecting on how your life is going at one time involves a cognitive process that differs
considerably from how your life is going in real time. Global reports were consistently higher
than aggregated daily states. This has several important implications for the interpretation of
results that rely on these different methods. In sum, life is considered more satisfying, more
meaningful, and is characterized to a greater extent by more intense positive and negative
emotions when reflecting on life in general than it is when reflecting on daily life in real time.

87
General Discussion
The studies in each chapter have utilized daily diary and ecological momentary
assessment techniques to measure well-being in daily life and have challenged some conclusions
drawn from studies that have relied on different methods. For example, is nostalgia beneficial for
your well-being? The answer depends on the type of nostalgic experience brought to mind.
When asked to reflect on their most nostalgic experience, people believe their lives seems more
meaningful and they feel more optimistic about the future. In daily life, in contrast, people often
feel nostalgic when negative events occur, and they do not feel particularly happy during those
moments. Similarly, is life pretty meaningful? It depends on whether you reflect on your life
generally or on your day-to-day life. A general life reflection allows people to bring to mind the
peak experiences that imbue life with meaning, whereas much of daily life is routine, mundane,
and less meaningful.
Clearly, daily diary and ecological momentary assessment techniques offer a unique
perspective, particularly in fields that have traditionally relied on one type of method.
Experiments excel at testing causal processes and can precisely determine which specific
mechanisms are involved in particular processes. They often lack ecological validity though, as
the manipulation may simulate a situation that does not often occur in the real world and that
does not adequately reflect real-world psychological processes. EMA methods can address this
limitation quite well because the random selection of time points should capture moments that
are typical in daily life. Although EMA methods can address these types of concerns quite well,
they typically do not provide as much support for causal relationships as experiments do because
of potential third variable issues. As noted by Joe McGrath (1982), all methods are seriously
flawed. The best strategy, therefore, is to try to combine methods to offset the limitations of each
88
particular method. When research in a particular field or area relies too heavily on one type of
method, new insights can often be gained through the use of a different method. The present set
of studies builds on the research that attempts to integrate and compare results across different
methods.

89
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Appendix
Personal Inventory of Nostalgic Experiences (PINE) scale.
Item Number Statement
1 How nostalgic do you feel?
2 To what extent do you feel sentimental for the past?
3 How much do you feel a wistful affection for the past?
4 To what extent do you feel a longing to return to a former time in your life?

106
Table 1. Descriptive statistics and trait correlations between nostalgia and predictors.

Variable N Mean SD
Omega
(alpha) r
Nostalgia 596 4.23 1.49 .92 (.91)
Personality/Individual differences

Approach 525 5.31 0.98 0.89 (.84) 0.00
Avoidance 525 4.46 1.28 0.88 (.83) 0.22***
Agreeableness 279 3.71 0.61 0.81 (.72) 0.05
Conscientiousness 279 3.41 0.66 0.87 (.83) -0.08
Extraversion 279 3.27 0.77 0.89 (.84) -0.07

Neuroticism 279 3.13 0.77 0.89 (.86) 0.21***
Openness 279 3.69 0.71 0.89 (.86) 0.05
Past positive 356 3.55 0.67 0.84 (.77) 0.40***
Past negative 356 3.02 0.77 0.87 (.84) 0.40***
Future 356 3.47 0.59 0.83 (.79) -0.02
Present fatalistic 356 2.58 0.65 0.81 (.76) 0.32***
Present hedonic 356 3.42 0.61 0.88 (.85) 0.20***
Well-being/Relevant measures
Satisfaction with life 526 4.73 1.32 0.89 (.88) -0.08
a

Positive activated affect 283 4.54 1.21 0.92 (.90) -0.02
Positive deactivated affect 283 4.34 1.24 0.92 (.90) -0.07
Negative activated affect 283 3.72 1.18 0.88 (.80) 0.34***
Negative deactivated affect 283 2.89 1.37 0.79 (.91) 0.34***
Meaning in life (presence) 525 4.56 1.29 0.89 (.87) -0.11*
Meaning in life (search) 525 4.98 1.3 0.93 (.91) 0.19***
Self-esteem 299 3.28 0.89 0.95 (.90) -0.12*
Regret 526 4.52 1.12 0.80 (.75) 0.30***
Depression 220 21.09 12.12 0.93 (.91) 0.35***
Inspiration Frequency 452 4.95 1.28 0.93 (.91) -0.02
Inspiration Intensity 452 4.58 1.26 0.94 (.91) 0.11*
Inspiration Aggregate 452 4.77 1.17 0.96 (.93) 0.05
Empathy 108 3.44 0.45 0.89 (.82) 0.23*
Note:
a
p <.10. *p <.05. **p <.01. ***p <.001.

107
Table 2. Correlation comparisons between the PINE scale and the SNS scale.

Correlation
with PINE
Correlation
with SNS
Correlation
comparison
Variable N r r t
Approach 231 0.03 0.23** -3.72***
Avoidance 231 0.22** 0.25*** -0.70
Agreeableness 174 0.10 0.16* -1.06
Conscientiousness 174 -0.07 0.06 -1.99*
Extraversion 174 -0.10 0.11 -3.43**
Neuroticism 174 0.23** 0.21** 0.20
Openness 174 0.02 0.24** -3.72***
Satisfaction with life 232 0.02 0.13
a
-2.06*
Meaning in life (presence) 231 -0.04 0.09 -2.43*
Meaning in life (search) 231 0.23** 0.34*** -2.20*
Regret 232 0.29*** 0.26*** 0.67
Depression 113 0.29** 0.14 2.03*
Inspiration Frequency 232 0.12
a
0.28*** -3.19**
Inspiration Intensity 232 0.14* 0.31*** -3.24**
Inspiration Aggregate 232 0.14* 0.32*** -3.46**
Note:
a
p <.10. *p <.05. **p <.01. ***p <.001.

108
Table 3. Descriptive statistics for all daily measures for Study 3.
Daily Measure # Daily reports Intercept Variance Reliability
Within Between
Nostalgia 2723 2.69 1.47 1.45 .90
Daily events
Positive social events 2724 .88 .38 .22
Negative social events 2723 .31 .14 .08
Positive achievement events 2724 .73 .29 .15
Negative achievement events 2724 .62 .24 .14
Nostalgia events 2721 .63 .49 .17
Social media active 2703 1.77 .36 .41
Social media passive 2702 3.52 .92 1.54
Helping 2028 .25 .09 .07
Temporal Thoughts
Past 2722 3.86 3.51 1.96
Present 2722 5.93 3.06 2.05
Future 2721 5.86 3.72 2.00
Well-being and relevant measures
Positive activated affect 2722 3.72 1.33 1.11 .84
Positive deactivated affect 2722 3.66 1.13 1.01 .85
Negative activated affect 2722 3.04 1.21 .75 .67
Negative deactivated affect 2724 2.31 1.05 .86 .79
Loneliness 2721 2.31 1.23 1.26 .81
Satisfaction with life 2016 4.58 1.42 .99
Meaning (presence) 2723 3.76 1.46 1.53 .86
Meaning (search) 2723 2.67 1.28 1.38 .88
Self-esteem 1321 4.98 .93 .99 .52
Inspiration 2721 3.19 2.00 1.17 .90
Optimism 1321 4.30 1.24 1.45 .82
Regret 1321 3.19 1.14 .99 .64
Rumination 695 3.02 1.46 .93 .79
Reflection 695 3.59 1.43 1.25 .63
Note: Reliability statistics were not calculated for single item measures or for daily events as we
did not expect them to be internally consistent as suggested by Stone, Kessler, and
Haythomthwatte (1991).

109
Table 4. Relationships between nostalgia and well-being/well-being related variables with and
without controlling for negative events.

Without control With control
Nostalgia Nostalgia Negative events
Variable # Daily reports Coeff. t-ratio Coeff. t-ratio Coeff. t-ratio
Positive activated affect 2721 .00 <1 .03 1.08 -.68 7.76***
Positive deactivated affect 2721 -.04 1.69
a
-.01 <1 -.73 9.50***
Negative activated affect 2721 .13 5.55*** .08 4.00*** 1.25 15.10***
Negative deactivated affect 2723 .20 8.13*** .16 6.98*** 1.06 14.12***
Loneliness 2720 .17 6.53*** .15 5.92*** .55 6.73***
Satisfaction with life 2016 -.12 3.92*** -.09 2.85** -1.06 9.64***
Meaning (presence) 2722 -.01 <1 .01 <1 -.55 5.41***
Meaning (search) 2722 .11 4.45*** .11 4.61*** -.06 <1
Self-esteem 1321 -.12 4.14*** -.08 3.12** -.85 8.78***
Inspiration 2721 .11 3.69*** .13 4.41*** -.48 5.04***
Optimism 1321 -.02 <1 -.00 <1 -.54 5.01***
Regret 1321 .18 6.32*** .17 5.70*** .38 4.76***
Rumination 695 .49 9.84*** .48 9.98*** .75 5.13***
Reflection 695 .36 7.17*** .34 6.99*** .48 3.27**
Note:
a
p <.10. *p <.05. **p <.01. ***p <.001.

110
Table 5. Descriptive statistics of variables in Study 4 and within-person relationships between
momentary nostalgia and momentary well-being after adjusting for a linear time trend.

Variation

Between-person Within-person
Within-person
relationships

Reliability
Unconditional
model
intercept
Between-
day
Within-
day Coeff t-ratio
Nostalgia 2.25 1.73 .19 .79
Meaning in life 4.09 1.24 .19 .57 .04 1.50
Optimism 4.34 1.14 .22 .64 .04 1.49
Positive activated
affect
.79 3.41 .73 .37 1.16 .05 1.32
Positive
deactivated affect
.80 4.02 .63 .37 1.11 .01 <1
Negative activated
affect
.75 2.78 .69 .57 .97 .01 <1
Negative
deactivated affect
.78 1.91 .78 .29 .50 .16 5.44***
Note:
a
p <.10. *p <.05. **p <.01. ***p <.001

111
Table 6. Averages of Event Reflection Task and diary ratings, and comparisons of the averages in Study 5.
Averages ERT vs. nostalgic
days
ERT vs. ordinary
days
Nostalgic days vs.
ordinary days
ERT
(n = 81)
Nostalgic
days
(n = 278)
Ordinary
days
(n = 206) b t b t b t
Nostalgia 4.61 3.14 1.00 1.57 9.11***
Positivity 5.95 5.02 4.81 .92 4.53*** 1.21 5.18*** .23 1.26
Negativity 1.99 2.47 2.49 -.42 2.21* -.63 3.34** -.06 <1
Meaning in life 5.40 4.79 4.62 .61 4.66*** .87 6.28*** .16 1.44
Self-esteem 5.44 5.25 5.32 .11 <1 .22 1.51 -.07 <1
RA longing for the past .34 .27 .09 .07 3.84*** .25 16.96*** .18 16.51***
RA positive affect .27 .22 .14 .06 2.98** .13 7.38*** .08 7.03***
RA negative affect .08 .07 .08 .01 <1 -.00 <1 -.01 1.36
Note: ERT = Event Reflection Task. RA = research assistant coding. Nostalgic days refer to days when participants reported a daily
nostalgic score greater than 1. Ordinary days refer to days when they reported nostalgic scores of 1 (not at all). Nostalgia scores on
ordinary days had no variance so those models did not converge, nor were they necessary.
a
p <.10. *p <.05. **p <.01. ***p <.001

112
Table 7. Descriptive statistics of daily and global reports.

Daily Reports Global Reports
Variation
Variable Intercept within between reliability validity M SD Reliability
Positive activated affect 3.76 1.27 1.32 .84 .72 4.46 1.29 .91
Positive deactivated affect 3.54 1.06 .98 .82 .71 3.96 1.14 .86
Negative activated affect 3.06 1.18 .72 .61 .60 3.66 1.16 .79
Negative deactivated affect 2.27 1.07 .82 .79 .68 2.86 1.26 .87
Satisfaction with life 4.57 1.54 .92 .79 .71 4.87 1.41 .78
Meaning in life – presence 4.20 1.20 1.17 .78 .67 4.75 1.36 .82
Meaning in life – search 3.45 1.22 1.22 .84 .33 4.98 1.35 .91
Nostalgia 2.76 1.54 1.54 .89 .62 3.88 1.58 .91

113
Table 8. Comparisons of global reports and aggregated daily state reports.

Daily report
averages Global reports Main effect Interaction
Variable
Global
report
first group
Diary
first
group
Global
report
first group
Diary
first
group b [95% CI] t p d b [95% CI] t p d
Positive
activated
affect
3.71 3.81 4.47 4.46 .71 [.58, .83] 11.31 < .001 .72 .11 [-.13, .36] .90 .369 .11
Positive
deactivated
affect
3.45 3.64 3.99 3.93 .41 [.31, .52] 7.46 < .001 .48 .25 [.04, .47] 2.29 .023 .29
Negative
activated
affect
3.00 3.13 3.81 3.51 .60 [.47, .72] 9.44 < .001 .60 .43 [.19, .67] 3.46 .001 .44
Negative
deactivated
affect
2.17 2.38 3.01 2.71 .58 [.46, .71] 9.46 < .001 .60 .50 [.26, .73] 4.14 < .001 .54
Satisfaction
with life
4.61 4.53 4.76 4.99 .30 [.16, .43] 4.36 < .001 .28 -.32 [-.58, -.06] 2.38 .018 .30
Meaning in
life –
presence
4.17 4.23 4.78 4.72 .55 [.41, .68] 8.03 < .001 .52 .10 [-.16, .37] .76 .446 .09
Meaning in
life – search
3.29 3.62 5.15 4.78 1.51 [1.32, 1.70] 15.59 < .001 1.00 .71 [.34, 1.08] 3.77 < .001 .48
Nostalgia 2.67 2.85 4.31 3.44 1.12 [.95, 1.28] 13.28 < .001 .85 1.04 [.74, 1.35] 6.77 < .001 .87
Note: The main effect refers to the difference between trait reports and aggregated daily states collapsed across condition. Because
reliable effect sizes could not be calculated for the specific multilevel models that used difference scores, we calculated Cohen’s d
effect sizes from repeated measures ANOVA models.

114
Table 9. Correlations between global reports and 1) peak states, 2) last three daily reports, and 3) daily averages across conditions.
Correlation between peak
(maximum) and global report
Correlation between last three days
and global report
Correlation between daily average
and global report
Variable Global
first
Diary
first
z p q Global
first
Diary
first
z p q Global
first
Diary
first
z p q
Positive activated
affect
.53 .69 1.98 .048 .257 .63 .61 .25 .802 .033 .68 .70 .25 .806 .032
Positive
deactivated affect
.45 .58 1.31 .189 .170 .55 .62 .78 .434 .101 .66 .73 1.05 .293 .136
Negative activated
affect
.56 .40 1.61 .107 .209 .45 .49 .44 .662 .057 .60 .56 .43 .671 .055
Negative
deactivated affect
.63 .48 1.72 .086 .222 .52 .57 .59 .559 .076 .63 .70 1.00 .315 .130
Satisfaction with
life
.34 .63 2.98 .003 .386 .47 .63 1.75 .079 .227 .57 .76 2.64 .008 .342
Meaning in life –
presence
.44 .62 1.98 .048 .256 .52 .59 .68 .494 .089 .64 .66 .30 .765 .039
Meaning in life –
search
.22 .46 2.10 .036 .272 .09 .45 3.06 .002 .396 .20 .49 2.57 .010 .333
Nostalgia .49 .61 1.32 .187 .171 .44 .61 1.86 .063 .241 .52 .76 3.28 .001 .425
Note: Comparisons of correlations were conducted with a Fisher’s r to z transformation and Cohen’s q is provided as an effect size estimate.

Abstract (if available)

Abstract The dissertation is composed of two chapters that include sets of studies that utilize EMA and daily diary methods to understand well-being in daily life. The first chapter examines what nostalgia looks like in daily life and how it relates to well-being. The chapter addresses between- and within-person relationships between nostalgia and well-being. The finding that nostalgia is negatively related to well-being in daily life contrasts with many experiments that find that nostalgia increases well-being. This illustrates the importance of relying on several different methodologies to obtain a more complete and accurate depiction of nostalgia’s effect on well-being. The studies in the second chapter compare aggregated daily states of well-being with global evaluations of well-being. Global evaluations of well-being were consistently higher than aggregated daily states. These findings demonstrate how well-being judgments may differ depending on the reflection period, and this has important implications for well-being research.

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Asset Metadata

Creator Newman, David Benjamin (author)

Core Title The dynamics of well-being in daily life: a multilevel perspective

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Psychology

Publication Date 07/19/2019

Defense Date 04/04/2019

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag daily diary,ecological validity,OAI-PMH Harvest,well-being

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Schwarz, Norbert (committee chair)

Creator Email davidnew@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-184353

Unique identifier UC11660742

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Legacy Identifier etd-NewmanDavi-7565.pdf

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Document Type Dissertation

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Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

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