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Counselling Psychology Quarterly
ISSN: 0951-5070 (Print) 1469-3674 (Online) Journal homepage: http://www.tandfonline.com/loi/ccpq20
Development of the Meaning in Life Measure
Clara E. Hill, Kathryn V. Kline, Matthew Miller, Ellen Marks, Kristen Pinto-
Coelho & Heidi Zetzer
To cite this article: Clara E. Hill, Kathryn V. Kline, Matthew Miller, Ellen Marks, Kristen Pinto-
Coelho & Heidi Zetzer (2018): Development of the Meaning in Life Measure, Counselling
Psychology Quarterly, DOI: 10.1080/09515070.2018.1434483
To link to this article: https://doi.org/10.1080/09515070.2018.1434483
Published online: 19 Feb 2018.
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COUNSELLING PSYCHOLOGY QUARTERLY, 2018
https://doi.org/10.1080/09515070.2018.1434483
Development of the Meaning in Life Measure
Clara E.Hilla, Kathryn V.Klineb, MatthewMillerb, EllenMarksa, KristenPinto-Coelhoa
and HeidiZetzerc
aDepartment of Psychology, University of Maryland, College Park, MD, USA; bDepartment of Counseling,
Higher Education, and Special Education, University of Maryland, College Park, MD, USA; cHosford Counseling
and Psychological Services Clinic, University of California Santa Barbara, Santa Barbara, CA, USA
ABSTRACT
To correct problems identied in existing measures of meaning in
life (MIL) (lack of inclusion of items related to felt sense, mattering,
and reectivity), a new 8-item Meaning in Life Measure (MILM) was
developed. Two subscales emerged: Experience (MILM-E, with items
related to felt sense, mattering, goals, coherence) and Reectivity
(MILM-R, with items related to valuing thinking about meaning). High
internal consistency and test–retest reliability were found for both
subscales. Concurrent validity was demonstrated by a strong positive
correlation between MILM-E and the Meaning in Life Questionnaire-
Presence (MLQ-P), and a moderate correlation between MILM-R and
the Meaning in Life Questionnaire-Search (MLQ-S). For both subscales,
small to moderate positive correlations were found with subjective
well-being, extraversion, conscientiousness, openness, agreeableness,
self-deception, and impression management; moderate negative
correlations were found with depression and emotional instability.
Participants who were older, female, of higher income, and married
with children scored slightly higher than their counterparts on MILM-E;
women scored slightly higher than men on MILM-R. We concluded
that the MILM has good psychometric properties and that MIL seems
to be composed of two factors.
The current interest in the topic of meaning in life (MIL) can be traced back to Frankl (1959),
who proered that the driving force for humankind is not sex, aggression, or power, but the
pursuit of meaning. We need to make sense out of our world, gure out our purpose and
goals, engage in life, determine what we can contribute to society, and feel that we are
signicant and matter to others and ourselves.
A considerable amount of research arms the importance of MIL. The presence of mean-
ing, as assessed through a number of dierent measures, is positively associated with some
of the hallmarks of a good life: well-being, physical and psychological health, length and
quality of life, work adjustment, and social attractiveness (Boyle, Barnes, Buchman, & Bennett,
2009; Crumbaugh & Maholick, 1964; Krause, 2007, 2009; Littman-Ovadia & Steger, 2010; Ry,
1989; Steger, Mann, Michels, & Cooper, 2009; Stillman, Lambert, Fincham, & Baumeister,
© 2018 Informa UK Limited, trading as Taylor & Francis Group
KEYWORDS
Meaning in life; felt sense;
mattering; purpose;
coherence; reflectivity
ARTICLE HISTORY
Received 14 November 2017
Accepted26 January 2018
CONTACT Clara E. Hill cehill@umd.edu
2 C. E. HILL ET AL.
2011). Likewise, the absence of meaning is associated with negative outcomes, including
psychological distress and physical and cognitive decline (Boyle, Buchman, Barnes, & Bennett,
2010; Mascaro & Rosen, 2005; Owens, Steger, Whitesell, & Herrera, 2009).
Although MIL seems to be a positive feature of human existence, dening and measuring
it have proven to be dicult (Heintzelman & King, 2014). The purpose of the present study
was thus to develop a new measure of MIL that includes components missing in previous
measures.
Measurement of Meaning in Life
The measures of meaning in life that have been developed over the decades vary widely in
terms of the denitions on which they are based. In addition, these measures suer to various
degrees from limitations such as conating meaning with purpose (Heintzelman & King,
2014; P. L. Hill, Burrow, Sumner, & Young, 2015), and having problematic and inconsistent
factor structures (Chamberlain & Zika, 1988; McGregor & Little, 1998). Furthermore, items or
entire scales have been confounded with other conceptually related but distinct constructs
such as negative aect, positive aect, and life satisfaction, which may account for the high
correlations with these other measures. For example, items in Crumbaugh and Maholick’s
(1964) Purpose in Life Test (PIL) assess positive and negative aect (Zika & Chamberlain,
1987, 1992) and life satisfaction (Chamberlain & Zika, 1988). Likewise, the PIL and Battista
and Almond’s (1973) Life Regard Index contain items that measure mood. Finally, Sammallahti,
Holi, Komulainen, and Aalberg (1996) argued persuasively that Antonovsky’s (1993) Sense
of Coherence Scale actually measures coping disposition rather than MIL.
Steger, Frazier, Oishi, and Kaler’s (2006) MLQ, with subscales of Presence and Search, is
the most widely used measure of MIL (see O’Donnell, Shim, Barenz, & Steger, 2014), and it
has the best psychometric properties of all the existing measures (see review by Brandstätter,
Baumann, Borasio, & Fegg, 2012). In their development of the MLQ, Steger et al. addressed
many of the concerns raised about other measures (e.g. poor factor structure, items con-
founded with other variables), but we have some concerns with this measure. First, the 5-item
MLQ-Presence subscale covers only two of the themes (purpose and coherence) identied
in the literature. Other relevant themes not represented in this measure include a felt sense
of meaning and mattering/signicance. Second, Steger et al. included Search as a subscale
of their MLQ, which is problematic given the nonsignicant correlation (r = −.09) between
the Presence and Search subscales. Search for meaning may be an important correlate of
MIL and is perhaps an antecedent of the presence of MIL, but we argue that it is not a com-
ponent of MIL. Looking and nding are separate but related constructs, hence the low
non-signicant correlation between the two phenomena.
Theory about Meaning in Life
Although many denitions have been asserted for the construct of MIL (e.g. Frankl, 1959;
Steger et al., 2006; Yalom, 1980), there is no commonly accepted denition. Recent reviews
(George & Park, 2016; Heintzelman & King, 2014; Martela & Steger, 2016), however, reveal a
growing consensus for a tripartite model of MIL with three dimensions: (a) mattering or
signicance, (b) purpose or goals, and (c) coherence or comprehensibility. As King, Hicks,
Krull, and Del Gaiso (2006) noted, “Lives may be experienced as meaningful when they are
COUNSELLING PSYCHOLOGY QUARTERLY 3
felt to have a signicance beyond the trivial or momentary, to have purpose, or to have a
coherence that transcends chaos” (p. 180). Martela and Steger (2016) suggested that these
three components reect evaluative, motivational, and cognitive components, respectively,
of MIL. Heintzelman and King (2014) argued that these three aspects are often treated as
synonymous with each other and with MIL, but that they are potentially distinct.
Mattering/signicance reects the need people seem to have to transcend themselves
in a way that makes them feel that they make a dierence, are signicant, or matter to others.
For example, a large survey of adolescents found that self-reported perceived mattering to
parents was positively related to global self-esteem and negatively related to variables such
as depression, anxiety, and delinquency (Rosenberg & McCullough, 1981). Similarly, in an
exploration of mattering in retirement, Schlossberg (2009) emphasized the importance of
maintaining a sense of mattering, which comprises feeling noticed, being appreciated, and
being needed or depended on by others.
Purpose/goals reect the activities that individuals use to develop meaning (Baumeister,
1991). Having goals involves developing intentions, achieving plans, creating a course for
one’s life, and implementing one’s aims in various arenas (e.g. work, family). In several studies
(e.g. Boyle et al., 2009; Matthews, Owens, Edmundowicz, Lee, & Kuller, 2006; Ry, 1989;
Scheier et al., 2006; Smith & Zautra, 2004), having highly valued purpose/goals was associated
with physical health, mental health, and well-being.
Coherence is the ability to understand one’s life, such that life “makes sense to the person
living it, it is comprehensible, and it is characterized by regularity, predictability, or reliable
connections” (Heintzelman & King, 2014, p. 562). A sense of coherence is an enduring feeling
that the environment is predictable and that things will work out reasonably well (Antonovsky,
1993). Having a sense of coherence allows one to feel that life is orderly, nonrandom, and
manageable. Frankl (1959) suggested that an ability to perceive coherence and make mean-
ing in one’s life serves as a tool for accepting suering and mitigating distress. Research from
narrative identity theory (McAdams, 2008), which views the self as composed of stories that
provide a sense of understanding, has shown that narratives weave together dierent parts
of experiences into a cohesive whole that helps individuals interpret the past and predict
future experiences.
We theorize that two components are missing from this tripartite model. The rst com-
ponent is a felt sense of meaning, which is an intuitive awareness that one’s life is meaningful.
Similar components have been included in other denitions of MIL (e.g. Reker & Wong, 1988,
2012). Whereas the other components in the tripartite model require more cognitive pro-
cessing, the felt sense is more of an immediate perception or aective impression that one
has meaning even if one cannot articulate the reasons for the sense (see also Hill, 2018).
The second component that we argue needs to be added to the tripartite model is reec-
tivity about meaning, which involves valuing and spending time pondering about MIL and
other existential concerns. Thus, reectivity is dierent from search, as assessed in the MLQ-S,
given that one can enjoy reecting about meaning whether or not it is perceived to be
present, whereas search implies looking for something that is missing or inadequate.
Reecting on one’s experience is an important step in making meaning, as has been found
in the psychotherapy training and expertise literature (Neufeldt, Karno, & Nelson, 1996;
Skovholt & Jennings, 2005). We reasoned that search, as measured by the MLQ-S, while
important as a behavioral component, misses the motivational component of valuing mean-
ing-making. We propose that a propensity to reect on MIL is as important as concluding
4 C. E. HILL ET AL.
that one has it. In fact, one would not have meaning if one did not reect on it to gain that
meaning. In addition, reectivity is a broader construct than search in that it focuses on
connecting the past, present, and future, whereas search is future-oriented. Martela and
Steger (2016) indicated that “meaning is tied up with the unique capacity of the human mind
for reective, linguistic thinking. Meaning is based in our mind’s capacity to form mental
representations about the world and develop representations between these representa-
tions” (p. 538). Martela and Steger suggested that this capability for reectivity unites the
three components of the tripartite model given that coherence, purpose, and signicance
all require the ability to reect. Although Martela and Steger did not conceptualize reectivity
as a component of MIL, we would argue that it seems like a central component if it unites
the other components.
Purposes of the present study
Our overall purpose in the present study was to investigate the components of MIL. We rst
describe the development of items to assess felt sense, mattering/signicance, purpose/
goals, coherence, and reectivity. In Study 1, we conducted an exploratory factor analysis
(EFA) of the items and assessed the test–retest reliability of the new measure, which we
called the MILM. In Study 2, we tested the replicability of the factor structure of the MILM
with a new sample using conrmatory factor analysis (CFA) and tested the MILM’s validity
and reliability. Our ultimate goal was to test theoretically plausible competing models, to
determine whether MIL can best be characterized by a tripartite model of mattering/signif-
icance, purpose/goals, and coherence/comprehensibility as proposed in the recent literature
(George & Park, 2016; Heintzelman & King, 2014; Martela & Steger, 2016); our proposed 5-way
model adding felt sense and reectivity; or some other model.
Development of the MILM
Based on reading the literature, six members of the research team (3 PhD-level counseling
psychologists and 3 doctoral students in counseling psychology) independently generated
about 100 items to reect the proposed components of felt sense, mattering/signicance,
purposes/goals, coherence/comprehensibility, and reectivity. They then discussed the items
and consensually agreed upon the ve best positively worded and ve best negatively
worded items for each of the ve constructs. Because previous studies have shown that
scores on MIL measures using 5-point scales were above average (Heintzelman & King, 2014;
King, Heintzelman, & Ward, 2016), we thought that there might have been a ceiling eect
and thus decided to use a 9-point rating scale, ranging from 1 (extremely disagree) to 9
(extremely agree), for all items.
We rst obtained IRB approval for the study, and throughout we obtained approval for
amendments. Based on the results from several pilot tests of the items with mTURK samples
(evidence has been reported for the validity and reliability of such samples; Buhrmester,
Kwang, & Gosling, 2011; Goodman, Cryder, & Cheema, 2013), we eliminated overlapping
items, randomly ordered the remaining 55 items, and asked 25 doctoral psychology students
and psychologists to indicate the best t for each item from among the ve domains. Using
a criterion that 20 of the 25 judges had to place the items in the correct conceptually derived
subscale, a list of 24 consensually agreed-upon items emerged. We had two positively worded
COUNSELLING PSYCHOLOGY QUARTERLY 5
items and two negatively worded items for each of the components of felt sense, mattering/
signicance, purpose/goals, and coherence, and four positively worded, and four negatively
worded items for the domain of reectivity (more items were retained for reectivity because
it had less backing in the previous literature). Sample items were, “I experience my life as
meaningful,” “I will be remembered,” and “Meaning in life is a topic I value.”
Study 1
The purpose of Study 1 was to conduct an EFA of the 24 retained items to develop a nal
measure. We conducted an EFA to determine the best t for the data, given that it could be
a tripartite model of mattering/signicance, purpose/goals, and coherence/comprehensi-
bility; a 5-way model adding felt sense and reectivity; or some other factor structure. We
also assessed test–retest reliability of the nal MILM measure.
Study 1: method
Participants
The undergraduate student sample was drawn from a psychology department participant
pool (N = 456), a small senior level honors class (N = 9), and research assistants in a professor’s
lab (N = 8). The total sample consisted of 473 undergraduates (349 female, 123 male, 1
unknown; 271 White, 86 Asian/Pacic Islander, 52 Black, 35 Hispanic/Latino/a, 29 multiethnic/
other/unknown; mean age = 19.64, SD = 1.49 years). A subsample of 63 undergraduates (56
female, 7 male; 31 White, 14 Asian/Pacic Islander, 4 Black, 1 Hispanic/Latino/a, 13 multieth-
nic/other/unknown; mean age = 20.51, SD = 3.05 years) was used for assessing test–retest
reliability.
Measures
Demographics measure. Participants completed a demographics questionnaire that had
questions about gender, age, race/ethnicity, highest education achieved, marital/child status,
and household income.
MILM. The 24-item MILM described above was used for the rst part of this study and
pared down to 12 items for the second part.
Procedures
Participants rst signed a consent form and then completed the MILM and a demographic
questionnaire. Students in the psychology department participant pool completed these
measures as part of an online mass testing that included other measures. The rest of the
sample completed the measures using paper and pencil. Three to four weeks later, the sub-
sample of test–retest participants again completed the MILM.
Study 1: results
Exploratory factor analyses of the MILM
To determine the appropriate number of factors to retain, we conducted a parallel analysis
of the 24 MILM items. Results suggested the retention of seven factors. Items with small
6 C. E. HILL ET AL.
primary factor loadings (λ < .50) were eliminated to increase the overall variance accounted
for in MILM items by latent factors. In addition, items with non-primary factor loadings >.30
were eliminated to increase measurement clarity. We then conducted an exploratory factor
analysis (EFA; using principal axis factoring and oblique rotation), but a number of problems
emerged with the 7-factor solution such as factors not having any highly loading items or
factors comprising only one or two items. Therefore, we explored a theoretically plausible
alternate 5-factor solution (felt sense, mattering/signicance, purpose/goals, coherence/
comprehensibility, and reectivity), but this 5-factor model also exhibited the same serious
aws. We reasoned that the problems were likely due to wording eects (having half posi-
tively and half negatively worded items), given that the measurement costs associated with
the use of negatively worded items often outweigh the benet of their inclusion (cf. Dalal
& Carter, 2015), and so we decided to drop all the negativelyworded items. We then con-
ducted an EFA on the 12-item MILM, which included 2 items for each of 4 factors (felt sense,
mattering/signicance, purpose/goals, coherence/comprehensibility), and 4 items for
reectivity.
A Kaiser–Meyer–Olkin (KMO) value of .875 suggested that the data for the 12 positively
worded items were factorable. For the EFA (using principal axis factoring extraction and
direct oblimin rotation) of the 12-item MILM, a parallel analysis identied four factors to be
retained. In order to rule out rival hypotheses regarding the MILM factor structure, we exam-
ined 1, 2, 3, and 4-factor solutions. We rejected the 4-factor solution because two of the
factors failed to meet the commonly accepted minimum requirement of three items loading
on each factor (Tabachnick & Fidell, 2007). For the three factor solution, all but one item
loaded >.50 and none of the non-primary loadings were >.30, but 2 factors (one composed
of felt sense and mattering items and the other composed of purpose and coherence items)
were highly correlated (.68), which was cause for concern. We rejected the one-factor solution
because 2 items did not have primary factor loadings >.50. Ultimately, the 2-factor solution,
accounting for approximately 63% of the variance in MILM items seemed the best t given
that all primary factor loadings were >.50, non-primary factor loadings were all <.30, the
two factors were moderately (r = .45) correlated, and the two factors could be interpreted
easily.
Finally, we wanted to develop a measure with the smallest number of items to reduce
participant burden while maintaining the breadth of the MIL construct. Therefore, we
selected the item with the highest loading for each of the four aspects of MIL (felt sense,
mattering/signicance, purpose/goals, coherence/comprehensibility) for the rst factor,
which we labeled the Experience subscale (MILM-E). We retained all four items for the second
scale, which we labeled the Reectivity subscale (MILM-R). The nal MILM was thus 8 items,
with 4 items for MILM-E and 4 items for MILM-R (see Table 1 for factor loadings; see Appendix
1 for nal measure).
Internal consistency reliability was .85 for the total scale (MILM-Total or MILM-T), .82 for
MILM-E, and .86 for MILM-R. Three-week (M = 22.06, SD = 3.50 days) test–retest reliability
was .87 for the MILM-T, .85 for MILM-E, and .82 for MILM-R. See Table 2 for means and standard
deviations of the total scale and two subscales of the MILM.
COUNSELLING PSYCHOLOGY QUARTERLY 7
Study 2
Given that we now had a viable measure, the overall purpose of Study 2 was to investigate
further the psychometric properties of this measure in a new sample. We chose to use an
MTurk sample to reect a wider range of the population than was possible with the university
sample used in Study 1.
The rst purpose of Study 2 was thus to use CFA to determine if we could replicate the
factor structure of the 8-item MILM developed through EFA in Study 1. A second purpose
was to do additional tests of validity by correlating the MILM with the MLQ, the most fre-
quently used measure of MIL.
A third purpose was to relate the MILM to other measures of related constructs. Given
that the presence or experience of MIL has been positively related to positive aect and
well-being and negatively related to measures of negative aect and psychopathology (see
Halusic & King, 2013; Steger et al., 2006), we included measures of these constructs in our
study. Importantly, as these constructs have been too highly related and perhaps conated
with measures of MIL in past studies, we wanted the constructs to be moderately rather than
highly related.
Table 1.Factor loadings for MILM in Study 1 and 2.
Note: Study 1, N=473, used an exploratory factor analysis. Study 2, N=401, used a confirmatory factor analysis.
Study 1 Study 2
MILM-E MILM-R MILM-E MILM-R
Experience items
I experience my life as meaningful .88 .03 .89 –
I will be remembered .76 .01 .8 –
I have something I want to accomplish in my life .65 −.08 .76 –
I can make connections between events in my past and present .72 .01 .75 –
Reflectivity items
I think about what gives me meaning −.14 −.92 – .82
Meaning in life is a topic I value −.03 −.74 – .76
There are times in my life when I think about what it all means. .17 −.72 – .87
I often reflect about issues related to meaning in life .21 −.66 – .86
Table 2.Means and standard deviations and internal consistency reliability for the MILM in Studies 1
and 2.
MILM-Total MILM-Experience MILM-Reectivity
M SD α M SD α M SD α
Study 1 (N = 473) 6.98 1.23 .85 7.45 1.34 .82 6.52 1.55 .86
Study 2 (N = 401) 6.94 1.39 .87 7.13 1.51 .84 6.74 1.71 .86
Male (N = 152) 6.61 1.36 .86 6.74 1.54 .85 6.48 1.67 .87
Female
(N = 243)
7.14 1.37 .86 7.39 1.43 .81 6.90 1.73 .86
Single/no
children
6.71 1.48 .87 6.77 1.68 .84 6.65 1.74 .85
Single/children 6.92 1.45 .87 7.35 1.37 .81 6.49 1.97 .89
Married/no
children
6.83 1.28 .83 7.07 1.48 .85 6.58 1.56 .80
Married/
children
7.27 1.27 .87 7.51 1.27 .80 7.03 1.64 .89
8 C. E. HILL ET AL.
In addition, we wondered how the MILM scales would be related to personality variables.
Studying the relationship between MIL and personality is a common strategy for generating
hypotheses about how people use features of their personality to cultivate MIL (Lavigne,
Hofman, Ring, Ryder, & Woodward, 2013). McAdams (2012) noted that high levels of extra-
version, conscientiousness, emotional stability, and openness to experience tend to be asso-
ciated with the overall feeling that life has purpose and value, that one is meaningfully
connected to others, and that obstacles in life can be overcome. McAdams suggested that
these dispositional traits provide psychological resources that people can draw on in their
quest for meaning.
A fourth purpose was to relate the MILM with a measure a social desirability. We included
both the Self-Deception (SDE) and Impression Management (IM) Scales of the Brief Inventory
of Desirable Responding and Impression Management (BIDR; Paulhus, 1984) to explore how
the MILM-E and MILM-R were related to social desirability. Unlike Scheier et al. (2006), we
chose not to use the Marlowe-Crowne Social Desirability Scale (MCSD; Crowne & Marlowe,
1960) because the MCSD conates self-deception and impression management, which have
been shown to be separate dimensions of socially desirable responding (Paulhus, 1991;
Tracey, 2016).
A fth purpose was to examine the MILM in relation to demographic variables (age,
income, gender, race/ethnicity, and marital status/children). In their undergraduate student
sample, Steger et al. (2006) found no relationship between the MLQ-P and MLQ-S subscales
and participants’ gender or race, although they found a small positive correlation between
MLQ-P and age. In a German sample of people of all ages and educational levels, Schnell
(2009) reported small positive correlations between meaningfulness and both age and edu-
cation (using the Sources of Meaning and Meaning in life Questionnaire, SoMe, Schnell &
Becker, 2006). Regarding marital status/children, Baumeister (1991) noted that parents with
children living at home usually score low on happiness indicators, but once the children
have left home, the parents report being glad that they had children because of the meaning
provided.
Finally, we wanted to determine if the MILM could explain variance above and beyond
the MLQ in predicting subjective well-being (SWB) and depression. In other words, even
though we expected that the MILM and MLQ would be highly related, we wondered if the
MILM would have predictive power above and beyond the MLQ.
Study 2: method
Participants
The sample consisted of 401 U.S. MTurk participants (248 female, 152 male, 1 other; 302
White, 23 Asian/Pacic Islander, 29 Black, 25 Hispanic/Latino/a, 22 multiethnic/other/
unknown; mean age = 35.54, SD = 12.14 years). In terms of education level, 91 had completed
high school, 56 were currently in college/had completed some college, 149 had a bachelor’s
degree, 15 were currently in graduate school, 57 had a master’s degree, 5 had a doctoral
degree, and 28 were other/unknown. In terms of household income, 60 earned less than
$20,000, 99 earned $20,000 to $39,999, 94 earned $40,000 to $59,999, 53 earned $60,000 to
$79,999, 49 earned $80,000 to $99,999, 37 earned $100,000 to $150,000, and 9 earned more
than $150,000. In terms of marital status, 152 were single/divorced/widowed with no
COUNSELLING PSYCHOLOGY QUARTERLY 9
children, 48 were single/divorced/widowed with children, 72 were married/in committed
relationship with no children, and 129 were married/in committed relationship with
children.
Measures
The demographics measure and the 8-item MILM (See Study 1) were used in Study 2.
Meaning in Life Questionnaire (MLQ; Steger et al., 2006) is a 10-item self-report measure
assessing an individual’s MIL. The MLQ comprises two subscales developed through factor
analyses: Presence of Meaning (MLQ-P; e.g. “I have a good sense of what makes my life
meaningful”) and Search for Meaning (MLQ-S; e.g. “I am seeking a purpose or mission for
my life”). Items are rated on a 7-point scale ranging from 1 (absolutely untrue) to 7 (absolutely
true). High scores reect high levels of MIL. Steger et al. reported positive correlations
between MLQ-P and measures of well-being and religiosity, and negative correlations
between the MLQ-S and measures of negative aect, neuroticism, and depression, which
supports validity for the subscales. For both Presence and Search subscales, Steger et al.
reported adequate internal consistency reliability (.84 and .81, respectively), and test–retest
reliability over a one-month period (.73 and .70, respectively). Internal consistency reliability
in the present sample was .94 for Presence and .93 for Search.
Positive Aect Negative Aect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) is a
20-item measure of positive and negative emotions using a 5-point Likert scale ranging from
1 (very slightly or not at all) to 5 (extremely). High scores reect high levels of aect. In previous
studies, the relationship between Positive Aect (PA) and Negative Aect (NA) was negative
and low, ranging from -.12 to -.23 (Tellegen, 1985; Watson & Clark, 1984). PA was negatively
correlated and NA was positively correlated with measures of depression, anxiety, and dis-
tress, providing evidence of validity (Watson et al., 1988). Internal consistency reliability
ranged from .86 to .90 for PA and .84 to .87 for NA; 8-week test–retest reliability ranged from
.39 to .71 (Costa & McCrae, 1980; Watson & Clark, 1984). Although various intervals of time
have been used in the past, we asked participants in our study to report on the extent to
which they felt a particular emotion during the past week. For the present study, internal
consistency reliability was .91 for PA and .87 for NA.
Satisfaction with Life (SWL; Diener, Emmons, Larsen, & Grin, 1985) is a 5-item self-report
measure assessing individuals’ judgment of global life satisfaction. Items (e.g. “I am satised
with my life”) are rated on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree).
High scores reect high levels of satisfaction. The SWL is moderately correlated with self-re-
port measures of well-being as well as with interviewer and peer ratings of well-being.
Coecient alpha was reported to be .87; 8-week test–retest reliability was .82. For the current
study, internal consistency reliability was .92.
Subjective Well-Being (SWB; Diener, 1994) is a sum of the standard scores of the 10-item
PA from the PANAS and the 5-item SWL measure minus the 10-item NA from the PANAS.
High scores reect high levels of subjective well-being. This widely used approach is collo-
quially known as an index of happiness (Diener, 2000). Factor analyses have shown that SWB
forms a single factor that has predictive validity (Diener, 1994; Elliot & Sheldon, 1996; Sheldon
& Elliot, 1999; Sheldon & Kasser, 1995; Sheldon & Lyubomirsky, 2006). The validity and relia-
bility of the SWB have been demonstrated through numerous studies and the SWB was
sensitive to positive changes in participants’ activity levels and circumstances (Elliot &
Sheldon, 1996; Sheldon & Elliot, 1999; Sheldon & Kasser, 1995).
10 C. E. HILL ET AL.
Patient Health Questionnaire-9 (PHQ-9; Kroenke, Spitzer, & Williams, 2001; Kroenke et al.,
2009) is a 9-item self-administered measure of depression, developed from the Primary Care
Evaluation of Mental Disorders Patient Health Questionnaire (PRIME-MD PHQ; Spitzer et al.,
2000), which is based on the DSM-IV diagnostic criteria for depression. High scores reect
high levels of depression. Individuals respond to the prompt, “Over the last 2 weeks, how
often have you been bothered by any of the following problems?” (e.g. “Little interest or
pleasure in doing things”) using a Likert scale of frequency from 0 (not at all) to 3 (nearly
every day). Higher scores on the PHQ-9 were associated with lower functioning as measured
by the Medical Outcomes Study-Short Form General Health Survey (SF-20) (Stewart, Hays,
& Ware, 1988). Criterion-based validity was established by comparing PHQ-9 scores with the
outcome of diagnostic clinical interviews and other indicators of functionality (e.g. sick days),
such that cut scores of 5, 10, 15, and 20 were consistent with diagnoses of mild, moderate,
moderately severe, and severe depression, respectively (Kroenke et al., 2009). The PHQ-9
appears to be valid for use with culturally diverse populations and people with a wide range
of medical conditions (Kroenke et al., 2009). Kroenke et al. (2001) reported internal consist-
ency reliability for the PHQ-9 ranging from .89 to .96, and 2-day test–retest reliability of .84.
For the current study, internal consistency reliability was .91.
40-Item Mini-Markers Set is a list of 40 adjectives representing the “Big Five” scales
(Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Openness)
(Goldberg, 1992; Saucier, 1994). Participants rate themselves in the present time (not how
they wish to be in the future) according to a 9-point Likert scale of accuracy ranging from 1
(extremely inaccurate) to 9 (extremely accurate). High scores reect high levels of each con-
struct. The 40 adjectives were extracted from Goldberg’s (1992) initial list of 100 descriptors
using factor analysis. Internal consistency reliability for two samples, each over 300 people,
ranged from .76 to .86 (Saucier, 1994). Internal consistency reliability for the present study
ranged from .65 to .88.
Balanced Inventory of Desirable Responding-6 (BIDR-6; Paulhus, 1984) is a 40-item measure
assessing Self-Deception (SDE) and Impression Management (IM). SDE is designed to meas-
ure defensiveness towards psychological threats and positively biased self-perceptions. IM
is designed to measure responding that is guided by a desire to create a favorable impression
on others. Items are rated on a 7-point scale from 1 (not true) to 7 (very true). High scores
reect high levels of SDE or IM. Moderate correlations were reported between SDE and
measures of defensiveness (Paulhus, 1988; Paulhus & Reid, 1991). Paulhus (1991) reported
positive relationships between IM and measures of agreeableness, conscientiousness, lying,
and role-playing. Internal consistency reliability ranged from .68 to .80 for SDE and .75 to .86
for IM. Five-week test–retest reliability was .69 for SDE and .65 for IM. Internal consistency
reliability for the present study was .83 for SDE and .78 for IM.
Procedures
Participants signed a consent form and then took the measures in the following order: MILM,
MLQ, PANAS, SWL, PHQ-9, BIDR-IM, Mini-Markers, and BIDR-SDE. Each participant earned 50
cents for completing the measures.
COUNSELLING PSYCHOLOGY QUARTERLY 11
Study 2: results
CFA for the MILM
To cross-validate the 8-item 2-factor model of the MILM, we conducted a CFA of covariance
and asymptotic covariance matrices in LISREL 8.54, and used the Satorra–Bentler (1994)
scaled chi-square (SB x2) to address the violation of multivariate normality. The Root Mean
Square Error of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR),
and Comparative Fit Index (CFI) were selected a priori to assess model t. Using a single
index strategy (cf. Hu & Bentler, 1999), an SRMR value less than or equal to .09, RMSEA values
less than .08, and CFI values greater than or equal to .90 are individually indicative of ade-
quate model t (Hu & Bentler, 1999).
The 8-item 2-factor model of the MILM exhibited an adequate to good model t, SB
x2 = 54.64, p < .05, df = 19; RMSEA = .069 (.048; .090); SRMR = .049; CFI = .97. The variance
accounted for was 63% and 69% of the variance in MILM-E and MILM-R subscale scores,
respectively. All of the model parameters (N = 17) were signicant and the standardized
factor loadings ranged from .74 to .88 (see Table 1).
The one-factor model exhibited a poor t to the data, SB x2 = 386.24, p < .05, df = 20;
RMSEA = .214 (.196; .233); SRMR = .125; CFI = .84. The one-factor model was thus ruled out
as a plausible representation of the data.
Internal consistency reliability was .87 for the MILM-T .84 for MILM-E, and .86 for MILM-R.
The correlation between MILM-E and MILM-R was .49. See Table 2 for means and standard
deviations.
Correlations with other measures
Table 3 shows the correlations between the MILM-T, MILM-E, and MILM-R and all other var-
iables. Correlations >.10 were signicant at the p < .05 level, >.13 at the p < .01 level, >.16 at
the p < .001 level. A correlation of .10 is a small eect size, .30 a medium eect size, and .50
a large eect size (Cohen, 1988).
Concurrent validity of the MILM. The MILM-E was strongly correlated with the MLQ-P
(r = .79), suggesting that the two scales measure the same construct. The MILM-E was
not signicantly related to the MLQ-S (r= -.07), indicating that these measures reect
independent constructs. The MILM-R was moderately signicantly related to the MLQ-P
(r=.42) and the MLQ-S (r=.37), indicating that Reectivity is a separate but related construct
to both Presence and Search.
The MILM-E related strongly positively to SWB (r = .67), whereas the MILM-R related mod-
erately positively to SWB (r = .32). Thus, participants who reported that they experienced
and reected about meaning also reported higher levels of subjective well-being.
The MILM-E and MILM-R related negatively but moderately to PHQ-9 (r = −.48 and −.17,
respectively) and the Mini-Markers Emotional Stability Scale (r = −.39 and −.14, respectively).
Thus, participants who rated themselves as experiencing and reecting about meaning also
rated themselves as having less depression and emotional instability.
In terms of the other Mini-Markers scales, the MILM-E and MILM-R related positively but
moderately to extraversion (r = .30 and .15, respectively), agreeableness (r = .45 and .29,
respectively), conscientiousness (r = .39 and .22, respectively), and openness (r = .27 and .35,
respectively). Thus, participants who rated themselves as experiencing and reecting about
12 C. E. HILL ET AL.
Table 3.Correlations among all variables for the MILM in Study 2.
Notes: N=401. MILM-T=Meaning in Life Measure-Total; MILM-E=Meaning in Life Measure-Experience, MILM-R=Meaning in Life Measure-Reflectivity, MLQ-P=Meaning in life Questionnaire-Pres-
ence, MLQ-S=Meaning in life Questionnaire-Search, SWB=Subjective Well Being (Positive Affect+Satisfaction in Life – Negative Affect), PHQ-9=Patient Health Questionnaire-9, Extraver=Ex-
traversion Scale of the Mini-Markers, Agreeable=Agreeableness Scale of the Mini-Markers, Consciens= Conscientiousness Scale of the Mini-Markers, Em Sta=Emotional Stability Scale of the
Mini-Markers, Openness=Openness Scales of the Mini-Markers, SDE=Self-Deception Scale of the Balanced Inventory of Desirable Responding-6, IM=Impression Management of the Balanced
Inventory of Desirable Responding-6, Age=years of age, Education= highest level of education, Income= amount of annual income. Correlations of at least .10 are significant at p<.05, cor-
relations of at least .13 are significant at p<.01, correlations of at least .16 are significant at p<.001. A correlation of .10 is a small effect size, .30 a medium effect size, and .50 a large effect size.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1. MILM-T –
2. MILM-E .84 –
3. MILM-R .88 .49 –
4. MLQ-P .69 .79 .42 –
5. MLQ-S .20 −.07 .37 −.21 –
6. SWB .56 .67 .32 .72 −.17 –
7. PHQ-9 −.36 −.48 −.17 −.54 .22 −.67 –
8. Extraver .26 .30 .15 .30 −.04 .40 −.27
9. Agreeable .42 .45 .29 .47 .01 .47 −.33 .18
10. Consciens .35 .39 .22 .34 −.09 .47 −.38 .22 .52
11. Em Stab −.30 −.39 −.14 −.47 .21 −.60 .57 −.28 −.46 −.45
12. Openness .36 .27 .35 .18 .20 .19 −.13 .19 .34 .25 −.18
13. SDE .41 .47 .25 .44 −.13 .51 −.36 .37 .38 .49 −.52 .26
14. IM .25 .26 .19 .27 −.06 .30 −.29 .14 .48 .44 −.43 .17 .52
15. Age .08 .10 .04 .11 −.16 .17 −.21 .03 .22 .25 −.24 .13 .13 .25
16. Education .03 .07 −.01 .07 .01 .06 −.07 .03 .02 .01 −.03 .07 .05 .04 .09
17. Income .09 .12 .04 .15 −.02 .26 −.23 .09 .04 .12 −.11 −.06 .03 .01 .07 .19
COUNSELLING PSYCHOLOGY QUARTERLY 13
meaning also evaluated themselves as being extraverted, agreeable, conscientious, and
open.
In terms of social desirability, the MILM-E and MILM-R related positively but moderately
to SDE (r = .41 and .47, respectively) and IM (r = .25 and .26, respectively). Thus, participants
who rated themselves as experiencing and reecting about meaning reported some ten-
dency toward self-deception and impression management. Tracey (2016) warned that it is
unwise “to implicitly assume that SDR is harmful bias” (p. 229) and recommended that rather
than routinely eliminating the eects of social desirability on a measure, it is best to consider
whether its features might actually be part of the construct of interest. Indeed, we argue
that MILM items such as “I experience my life as meaningful” could elicit self-consciousness
and a desire to look good to self and others.
Demographic variables. Table 3 shows that the MILM-E subscale had small positive
correlations with age (r=.10) and income (r=.12), although the correlation with educational
level was not signicant (r=.07). In contrast, MILM-R was not signicantly correlated with age
(r=.04), income (r=.04), or educational level (r=−.01). The results of t-tests indicated that
women scored higher than did men on both the MILM-E, t(398)=−4.23, p=.000, and the
MILM-R, t(398)=−2.39, p=.017. Analyses of variance (ANOVAs) for race/ethnicity indicated no
signicant dierences among ve groups (302 White, 29 Black, 25 Hispanic/Latino/a, 23 Asian/
Pacic Islander, 16 multiethnic) on MILM-E, F(4,390)=.52, p=.72, partial η
2
=.01, or MILM-R,
F(4,390)=.58, p=.68, par tial η2=.01. An ANOVA for marital/child status indicated signicant
dierences among four groups (married/partnered with children, married/partnered without
children, single with children, single without children) for MILM-E, F(3,397)=6.32, p<.001,
partial η
2
=.05, with post hoc comparisons revealing that single participants with no children
scored lower than married/partnered participants with children. No dierences for marital
status/children were found for the MILM-R, F(3,397)=1.95, p=.12, partial η2=.02. Thus,
MILM-E was slightly higher for older than younger people, people with higher rather than
lower income, women than men, and married/partnered with children than single without
children, but did not dier based on educational level. MILM-R, in contrast, was slightly
higher for women than men but did not dier based on age, income, educational level, or
marital status/children.
Predicting SWB and PHQ-9 from MLQ and MILM
In the prediction of SWB, we entered MLQ-P and MLQ-S in the rst step, and MILM-E and
MILM-R in the second step of a hierarchical regression analysis. The two MLQ scales in Step
1 predicted a signicant amount of the variance of SWB, R2 = .515, adjusted R2 = .513,
F(2, 400) = 211.28, p = .000. Adding the two MILM scales in Step 2 contributed additional
variance, R2 change = .028, F(4, 400) = 117.78, p = .000. The subscales that contributed sig-
nicantly to the variance at Step 2 were the MLQ-P, unstandardized β = 6.84, t = 8.31, p = .000,
and MILM-E, unstandardized β = 3.71, t = 4.86, p = .000.
Similarly, in the prediction of the PHQ-9, we entered MLQ-P and MLQ-S in the rst step,
and MILM-E and MILM-R in the second step of a hierarchical regression analysis. The two
MLQ scales in Step 1 predicted a signicant amount of the variance of PHQ-9, R2 = .299,
adjusted R2 = .296, F(2, 400) = 84.92, p = .000. Adding the two MILM scales in Step 2 contrib-
uted additional variance, R2 change = .014, F(4, 400) = 45.04, p = .000. The subscales that
contributed signicantly to the variance at Step 2 were MLQ-P, unstandardized β = −1.63,
14 C. E. HILL ET AL.
t = −5.24, p = .000, MLQ-S, unstandardized β = .46, t = 2.20, p = .028, and the MILM-E, unstand-
ardized β = −.80, t = −2.78, p = .006.
Overall discussion
Although recent theorists (George & Park, 2016; Heintzelman & King, 2014; Martela & Steger,
2016) have proposed a tripartite model of MIL composed of coherence, mattering, and
purpose, our EFA and CFA results suggested that these three components could not be
distinguished from each other or from felt sense, suggesting that all four are aspects of the
same underlying dimension of MIL. Furthermore, our ndings extend the MIL literature by
highlighting reectivity as a unique but related dimension of MIL. Thus, our EFA results
indicated a two-factor structure of MIL, with one 4-item Experience subscale (with items
indicative of felt sense, mattering/signicance, purpose/goals, and coherence/comprehen-
sibility), and a second 4-item Reectivity subscale.
Two sets of ndings led to the conclusion that MIL is not composed of ve easily-distin-
guishable components. First, when we asked 25 psychologists and psychologists-in-training
to identify which factor was the best t for each of 55 items, less than half of the carefully
constructed items were placed in the theoretically correct factor by at least 20 of the people
(a relatively lenient criterion). Second, the EFA and CFA did not support a ve-factor structure,
but rather yielded two related factors.
These ndings challenge Steger et al.’s (2006) two-factor (Presence and Search) model
for MIL. In fact, Presence and Search were non-signicantly related in Steger et al.’s (2006)
investigation of the MLQ, suggesting that they are not part of the same construct. In contrast,
the Experience and Reectivity scales of the MILM t together in the factor analyses and
were moderately correlated, suggesting that they are part of the same construct. Furthermore,
the analyses predicting subjective well-being and depression indicated that the MILM-E
Scale added variance above and beyond the MLQ-P Scale, suggesting the benet of adding
items reecting felt sense and mattering (the MLQ-P Scale items reect only purpose and
coherence).
In addition, we believe that the MILM-R scale reects an advancement in the eld, espe-
cially as compared with the MLQ-S scale. First, the MILM-E and MILM-R were moderately
related, whereas the MLQ-P and MLQ-S were not signicantly related to each other, indicating
that the two MILM scales were measuring something more related. Fur thermore, the MILM-E
and MILM-R were both positively related to measures of personality functioning (although
correlations were stronger for MILM-E than for MILM-R), whereas correlations with MLQ-P
and MLQ-S were in the opposite direction (MLQ-P was positively related to measures of
psychological functioning whereas MLQ-S was negatively related). Third, MILM-R was more
related to the measure of openness whereas MILM-E was more related to other psychological
functioning variables. Thus, MILM-E seems to assess having meaning, whereas MILM-R seems
to assess valuing thinking about meaning.
These current ndings advance the eld then in suggesting a more parsimonious but
comprehensive bipartite model of MIL. One component involves the experience of felt sense,
mattering/signicance, purpose/goals, and coherence/comprehensibility, and the second
component involves reecting about MIL.
COUNSELLING PSYCHOLOGY QUARTERLY 15
Psychometric properties of the MILM
Construct validity
For the MILM, we found evidence for two factors (Experience and Reectivity) in an EFA and
replicated these in a CFA. The two scales were moderately related (r = .45 and .49); internal
consistency reliability and test–retest reliability were high for both the MILM-E and MILM-R.
Thus, the construct validity of the MILM was good.
One important aspect of construct validity of a measure is whether it is highly related to
other measures of the same construct (convergent evidence). We demonstrated convergent
evidence for the MILM-E in that it was correlated highly with the MLQ-P, which assesses the
presence of MIL. Furthermore, we showed that the MILM-R was only moderately related to
the MLQ-S, indicating that the MILM-R and MLQ-S are related but dierent constructs. The
MILM-R also was distinct but related to the MILM-E and MLQ-P. Thus, reectivity assesses a
process that is related to but dierent from experience/presence, one that we think plays
an important role in having a sense of meaning. People who think about meaning tend to
report having more meaning perhaps because they work to construct their meaning.
Despite the similarities between the MLQ and the MILM (e.g. both have a subscale of
experiencing meaning and a subscale of thinking about meaning, we argue that the MILM
is an improvement over the MLQ. First, as mentioned above, it adds felt sense and mattering/
signicance to the assessment of experience/presence and yet has about the same number
of items (four vs. ve). Second, reectivity seems to us to be more justied in the assessment
of MIL because it is a broader construct in terms of focus (integrating past, present, and
future rather than just future) and applicability (people can always reect on meaning
whereas search implies that one looks for it when it is absent).
Concurrent validity
The MILM scales were positively related to subjective well-being and negatively related to
depression and emotional instability. These results are consistent with ndings that other
measures of MIL have been positively related to positive aect and well-being and negatively
related to negative aect and psychopathology (Halusic & King, 2013; Steger et al., 2006).
Additional tests of the nomological net of MIL involved comparing the MILM scales with
personality variables. In these analyses, the MILM scales were positively and moderately
related to extraversion, agreeableness, conscientiousness, and openness. Thus, participants
who rated themselves as experiencing more meaning and reecting about meaning also
evaluated themselves as being higher on all four of the positive personality dimensions of
the Big Five. These ndings are similar to those of McAdams (2012), who noted that high
levels of extraversion, conscientiousness, and openness to experience tend to be associated
with the overall feeling that life has purpose and value, that one is meaningfully connected
to others, and that obstacles in life can be overcome. However, our ndings were discrepant
from those of McAdams for agreeableness, which we found to be related to meaning but
he did not.
Social desirability
The MILM scales were positively related to self-deception (moderate eect sizes) and impres-
sion management (small eect sizes). Given that higher scores on the Self-Deception Scale
indicate defensiveness against perceived psychological threats and positive self-bias, it
16 C. E. HILL ET AL.
makes sense that items on the MILM would elicit threats of meaninglessness and raise
respondents’ defenses. Some degree of self-deception is natural and might even serve as a
protective factor against depression, an interpretation that is supported by the moderate
negative correlation between SDE and PHQ-9. In addition, the lower correlations between
the MILM scales and the Impression Management Scale is not surprising because impression
management has more to do with creating a favorable impression among others than guard-
ing against internal threats. In contrast to our small to moderate relationships with social
desirability, Steger et al. (2006) found no relationship of the MLQ-P with social desirability,
perhaps because they used the Marlowe-Crowne Social Desirability Scale which has been
criticized in the literature for conating self-deception and impression management.
Demographics and the MILM
MILM-E was slightly higher for older than younger adults, which is not surprising given that
older people usually have more established identities. Similarly, Schnell (2009) and Steger
et al. (2006) found small positive correlations with age. Interestingly, MILM-R was not signif-
icantly correlated with age, indicating that adults of all age levels have an equal likelihood
of valuing thinking about meaning.
In addition, MILM-E was slightly higher for those with more income, which makes
sense given that income provides more opportunities for people to pursue their dreams.
Similarly, several studies have found that people with more financial resources rated
themselves as having more meaning than did people with fewer such resources (King
et al., 2016; Kobau, Sniezek, Zack, Lucas, & Burns, 2010; Pinquart, 2002; Ward & King,
2016). Interestingly, once again, MILM-R was not significantly correlated with income,
indicating that people of all income levels have an equal likelihood of valuing thinking
about meaning.
In addition, women scored slightly higher on both the MILM-E and MILM-R. Given that
Schnell (2009) and Steger et al. (2006) did not nd gender dierences, these results suggest
that either the MILM is measuring something slightly dierent than previous measures or
that the samples were dierent in some way. Perhaps these ndings reect gender role
dierences such that it is more acceptable for women than men to experience and think
about meaning, to be concerned about mattering, and to admit to being reective (Gilligan,
1982; Noddings, 1984).
We also found dierences on MILM-E for marital status and children. Those people who
reported having the most meaning were married/partnered people with children, which
supports Baumeister, Vohs, Aaker, and Garbinsky’s ndings (2013) that people who looked
back on having children reported having more meaning. Unfortunately, we did not inquire
about the age of the children so we could not compare our ndings with Baumeister et al.
to determine if parents whose children had left home had more or less meaning.
Scores on the MILM
Scores were above the average of 5 on the 9-point scale, indicating that in general participants
perceived that they had meaning in their lives. Similarly, Heintzelman and King (2014) and King
et al. (2016), in noting that participants scored well above the numerical mean on measures of
MIL, suggested that people are pretty satised in general with their levels of meaning.
COUNSELLING PSYCHOLOGY QUARTERLY 17
Scores on MILM-E were higher than scores on MILM-R, indicating that participants
were more likely to endorse experiencing meaning than to endorse reflecting about
meaning. Likewise, although the correlations were mostly in the same direction, the
MILM-E was more strongly correlated than the MILM-R with other related constructs
(SWB, PHQ-9, Emotional Stability, Extraversion, Agreeableness, and Conscientiousness.
The exception was that the MILM-R was more strongly correlated with Openness than
was MILM-E. In terms of social desirability, the MILM-R was slightly more highly related
to SDE than was the MILM-E, and the two MILM scales were about the same on the IM.
In terms of demographic variables, MILM-E was more strongly related to age, income,
gender, educational level, and marital status/children than was the MILM-R. Thus, the
MILM-E seems to be more related to subjective well-being, lack of depression, emotional
stability, extraversion, agreeable, and conscientiousness (all positive quality of life and
personality traits), whereas the MILM-R seems to be more related to openness (more of
a cognitive trait).
For researchers interested in assessing the global construct of meaning, we recommend
using the total score of the MILM. For researchers more interested in separating the experi-
ence of having meaning from reecting about meaning, we recommend using the separate
scales of MILM-E and MILM-R.
Limitations
In terms of limitations, all the data were collected in the U.S. and thus ndings cannot be
generalized to participants in other countries. Furthermore, although we had large samples,
these data cannot be construed as providing a representative sample of the population of
the U.S. (e.g. older people were probably underrepresented, children were not assessed).
Additional testing needs to be done with other populations.
Another limitation is that the MILM is a self-report measure, with all the inherent problems
associated with this type of measurement for this type of construct (e.g. people have diculty
assessing themselves on such a vague construct). It should be noted, however, that since
MIL is an internal construct, self-report is probably the best indicator of it.
Implications for future research
Given the good psychometric properties found in our samples, the MILM appears to be ready
to be used by other researchers. It would be interesting to use the MILM in various cultures
within the U.S. (e.g. African Americans, Asian Americans) as well as in other countries (e.g.
South Africa, China) to determine how the experience of MIL diers based on culture.
Researchers could also examine relationships of MIL with additional measures, especially
ones related to anxiety. Researchers could also relate MIL with other positive psychology
constructs (e.g. gratitude, forgiveness).
Finally, researchers could use these measures to learn more about working with MIL in
psychotherapy. Using the MLQ with participants engaged in ongoing psychotherapy not
focused on meaning, C. E. Hill, Kline, Aaron, King, and Kivlighan (in press) found that those
starting high in MLQ-Presence decreased in Presence during the middle of therapy and then
increased back to initial levels at the end of therapy, whereas as those initially low in Presence
increased during the middle of therapy and then decreased back to initial levels at the end
18 C. E. HILL ET AL.
of therapy. Those who started high in Search decreased to a moderate level, and those who
started low in Search increased to a moderate level at the end of therapy. These ndings
could be replicated with the MILM.
Within naturally occurring psychotherapy, we could also examine cases in which there
were large changes on the MILM, identifying specic instances where MIL was discussed to
learn more about how therapists work with MIL in therapy. Researchers could also test the
eects of working with MIL with specic populations (e.g. clients undergoing transitions,
clients with terminal illnesses, clients with career concerns) to determine how components
of MIL change as a result of psychotherapy.
Disclosure statement
No potential conict of interest was reported by the authors.
Notes on contributors
Clara E. Hill is a professor of psychology. The author’s research interests include psychotherapy process
and outcome, psychotherapy training and supervision, helping skills, meaning in life, dreams, and
qualitative research.
Kathryn V. Kline is a doctoral student in counseling psychology. The author’s research interests include
psychotherapy process, therapist training, and therapeutic relationship.
Matthew Miller is an associate professor. The author’s research interests include multicultural psychol-
ogy, career psychology, and assessment.
Ellen Marks is a postdoctroal felllow. The author’s research interests include concealment and disclosure
of secrets in psychotherapy, psychotherapy process and outcome, and meaning in life.
Kristen Pinto-Coelho is a aliate faculty. The author’s research interests include psychotherapy process
and outcome, supervision, and therapist training.
Heidi Zetzer is a lecturer. The author’s research interests include multicultural supervision and white
privilege.
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Appendix 1. Meaning in Life Measure (MILM)
Instructions: Please take a moment to think about what makes your life feel important to you. Please
respond to the following statements as truthfully and accurately as you can. Remember that these
are very subjective questions and there are no right or wrong answers. Circle the number that best
ts how you feel about each item,
Strongly
Disagree Neutral
Strongly
Agree
1. I will be remembered 1 2 3 4 5 6 7 8 9
2. I can make connections between events in my past and present 1 2 3 4 5 6 7 8 9
3. I have something I want to accomplish in my life 1 2 3 4 5 6 7 8 9
4. I experience my life as meaningful 1 2 3 4 5 6 7 8 9
5. I think about what gives me meaning 1 2 3 4 5 6 7 8 9
6. Meaning in life is a topic I value 1 2 3 4 5 6 7 8 9
7. There are times in my life when I think about what it all means 1 2 3 4 5 6 7 8 9
8. I often reflect about issues related to meaning in life 1 2 3 4 5 6 7 8 9
Notes: Items 1, 2, 3, and 4 t on MILM-Experience; items 5, 6, 7, and 8 t on MILM-Reectivity. Scale
scores can be calculated by averaging the scores across the items for the scale (i.e. dividing the sum
by the total number of items).
