Individual differences in optimism versus pessimism can be measured by several devices. The measures have somewhat different focuses, but in large part they share the same underlying conception, deriving from the expectancy-value model of behavior.
Life Orientation Test
One early measure of optimism and pessimism was the Life
Orientation Test, or LOT (Scheier
& Carver, 1985).
The LOT consists of 8 coded items, plus fillers. Half the
items are framed in an optimistic manner, half in a pessimistic
manner, and respondents indicate their extent of agreement
or disagreement with each item on a multi-point scale. The
LOT has good psychometric properties, in most respects. However,
it was criticized because the optimistic and pessimistic item
sets form two factors that are not always strongly inter-related
D'Zurilla, & Maydeu-Olivares, 1994; Marshall
& Lang, 1990). Further,
it gradually became apparent that some of the items asked
about things slightly different from expectations per se.
Accordingly, the LOT was superseded by the Life Orientation
Test-Revised, or LOT-R (Scheier
et al., 1994). The LOT-R is briefer than the original
(6 coded items, 3 framed in each direction). The revision
omitted or rewrote items that did not focus explicitly on
expectancies. The LOT-R has good internal consistency (Cronbach's
alpha runs in the high .70s to low .80s) and is quite stable
over time. Because of the extensive item overlap between the
LOT and the LOT-R, correlations between the two scales are
very high (Scheier
et al., 1994). However, the positive and negative item
subsets of the LOT-R are more strongly related to each other
than were those of the LOT. Given these various considerations,
the LOT-R is preferred over the original LOT.
Both the LOT and the LOT-R provide continuous distributions of scores. Distributions tend to be skewed toward the optimistic, but not greatly so. Researchers often refer to optimists and pessimists as though they were distinct groups, but talking that way is usually just a matter of convenience. There is no specific criterion for saying a person is an optimist or a pessimist. Rather, people range from very optimistic to very pessimistic, with most falling somewhere in the middle. Most research using these instruments uses them to create continuous distributions, with optimists and pessimists being defined relative to each other.
Generalized Expectancy of Success Scale
Another measure of optimism is the Generalized Expectancy
of Success Scale, or GESS ( Fibel
& Hale, 1978). This
scale presents respondents with a series of situations, some
specific, others more general, and asks them to evaluate their
likelihood of experiencing a success in each. The stem for
each item is "In the future I expect that I will …" with response
options ranging from "highly improbable" to "highly probable."
Most of the items refer to successful outcomes, with a few
(reverse scored) relating to failures. The situations range
fairly widely. Perhaps in part for this reason, its authors
found the GESS to have 4 factors, each of which focused around
one domain (Fibel
& Hale, 1978).
The GESS underwent a minor revision in 1992 (Hale,
Fiedler, & Cochran, 1992). In the revision, some items were
rewritten, several new items were created, and the resulting
item set was distilled to 25 items. Smith,
Pope, Rhodewalt, and Poulton (1989) reported correlations of .51 and .55 between
the original GESS and the LOT in two samples. Hale
et al. (1992) reported a correlation of .40 between
the GESS-R and the LOT. These data suggest that the two measures
are assessing somewhat different qualities.
Another measure that might be used is the Optimism-Pessimism
Scale, or OPS (Dember,
Martin, Hummer, Howe, & Melton, 1989). The OPS was developed from the assumption that separate
tendencies regarding optimism and pessimism should be measured
separately. The OPS is considerably longer than the measures
just described, with 18 items reflecting optimism, 18 items
reflecting pessimism, and 20 fillers. Dember et al. reported
a separation among the subsets of items representing optimism
and pessimism, but they did not conduct a factor analysis
of the item set. Chang
et al. (1994) did so, and found multiple factors. On
statistical grounds they suggested that three factors be retained,
but found the factors not readily interpretable. After further
analysis, they concluded that the OPS is a complex, multidimensional
instrument which is difficult to interpret theoretically.
Measures of optimism focus on expectancies, but expectancies
are sometimes measured indirectly. This approach to optimism
relies on the assumption that expectancies for the future
derive from people's view of the causes for events
in the past (Seligman,
1991). If a person's explanations for bad outcomes
in the past emphasize causes that are stable, the person will
expect more bad outcomes in that domain, because the cause
is relatively permanent and thus likely to remain in force.
If attributions for past bad outcomes emphasize causes that
are unstable, the outlook for the future may be brighter,
because the cause may no longer be in force. For example,
if you attribute a failure to a lack of ability, you will
expect to continue to fail in that area of endeavor; if you
attribute it to not getting enough sleep the night before,
you won't. If explanations for bad outcomes are global (apply
across aspects of life), expectancies for the future in many
domains will be for bad outcomes, because the causal forces
are at work everywhere. If the explanations are specific,
the outlook for other areas of life may be brighter, because
the causes don't apply. For example, if you perceive that
you failed at something because you are generally inept, you
will expect to fail in all domains; if you perceive that you
simply lack talent in that one particular area, you won't.
It is often assumed that people have "explanatory
styles," which bear on the person's whole life space.
The theory behind explanatory style (Seligman,
1991) holds that optimism and pessimism are defined
by patterns of explanation for bad outcomes that are unstable
and specific versus stable and global, respectively. Explanatory
style is assessed by a questionnaire that asks people to imagine
a series of hypothetical negative events happening to them
et al., 1982). Respondents write down what they would
see as the likely cause for the event and they rate that cause
on attributional dimensions.
Another method of assessing attributional style is called
Content Analysis of Verbal Explanations,
or CAVE technique (Peterson,
Schulman, Castellon, & Seligman, 1992).
This procedure involves assembling a sample of written or
spoken material from a person-letters, diaries, interviews,
speeches, and so on-that contain statements about explanations
for negative outcomes, and analyzing the statements for their
attributional qualities. The CAVE technique is quite flexible;
it can be applied to archival data, even records pertaining
to people who are no longer alive.
The Hope scale (Snyder
et al., 1991) is a set of 4 items reflecting agency, 4
items reflecting perceptions of pathways, and 4 filler items.
As noted earlier, the pathways subscale is a little divergent
away from optimism, but the agency subscale is fairly similar
to optimism. Although the theory underlying the agency scale
emphasizes personal causal influence, that role is less salient
in the items themselves. One item expresses energetic goal
pursuit; 2 items report a history of success; the fourth item
is somewhat more ambiguous, but also seems to express a sense
of prior success. To the extent that assessment of prior success
can be taken as an index of confidence of future success,
3 of the 4 items seem to imply confidence for the future,
a content that is consistent with the optimism construct.