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Journal
of
Personality
and
Social
Psychology
1986,
Vol.
50, No. 4,
832-838
Copyright
1986
by the
American
Psychological
Association,
Inc.
0022-3514/86/$00,75
Explanatory
Style
as a
Predictor
of
Productivity
and
Quitting
Among
Life
Insurance
Sales
Agents
Martin
E. P.
Seligman
and
Peter
Schulman
University
of
Pennsylvania
The
reformulated
learned
helplessness
model
claims
that
the
tendency
to
explain
bad
events
by
internal,
stable,
and
global
causes
potentiates
quitting
when
bad
events
are
encountered.
We
tested
this
prediction
in
the
work
setting
with
individuals
who
frequently
experience
bad
events.
Explanatory
style,
as
measured
by the
Attributional
Style
Questionnaire
(ASQ),
correlated
with
and
predicted
the
perfor-
mance
of
life
insurance
sales
agents.
In
a
cross-sectional
study
of 94
experienced
agents,
individuals
scoring
in the top
half
of the ASQ
sold
37%
more
insurance
in
their
first 2
years
of
service
than
those
scoring
in the
bottom
half.
In a
prospective
1-year
study
of 103
newly
hired
agents,
individuals
who
scored
in the top
half
of the ASQ
when
hired
remained
in
their
job at
twice
the
rate
and
sold
more
insurance
than
those
scoring
in the
bottom
half
of the
ASQ.
These
two
studies
support
the
claim
that
a
pessimistic
explanatory
style
leads
to
poor
productivity
and
quitting
when
bad
events
are
experienced,
and
extend
the
usefulness
of the ASQ to the
workplace.
According
to the
reformulation
of the
learned
helplessness
model, individuals with
a
"pessimistic"
explanatory style
are
more
likely
to
display helplessness
deficits
when confronted with
a bad
event than individuals
with
an
"optimistic"
explanatory
style
(Abramson,
Seligman,
&
Teasdale,
1978; Seligman,
Abramson,
Semmel,
& von
Baeyer,
1979). Individuals
who ha-
bitually
construe
the
causes
of bad
events
as
internal, stable,
and
global
("it's
my
fault,
it's going
to
last
forever,
and
it's
going
to
undermine
everything
I
do") should, when they experience
bad
events,
be
more susceptible
to
helplessness
deficits
than those
with
the
opposite
style. Peterson
and
Seligman
(1984)
reviewed
12
studies that
confirm
this model
by finding
depressive
deficits
associated
with
a
pessimistic explanatory
style
in
students,
de-
pressed patients, prisoners,
and
children.
Here
we
report
two field
studies
of
this
model, using
a
theo-
retically
relevant
population,
life
insurance
sales
agents,
and in-
vestigate
a
central helplessness
deficit—quitting.
These studies
have
two
purposes: First, they test
the
Abramson
et
al.
(1978)
model,
in
which
the
pessimistic explanatory style
predisposes
giving
up, and the
rejections inherent
in
selling
life
insurance
trigger
giving
up
when this disposition
is
present.
The
interaction
of
the
pessimistic explanatory style
and of the
rejections, though
neither
necessary
nor
sufficient
conditions,
increases
the
likeli-
hood
of
helplessness deficits. This
is a
species
of a
diathesis-
stress
model,
in
which
the
diathesis, though probably
not
con-
stitutional,
is a
pessimistic explanatory style,
and the
stress
is
The
authors
thank
Dan
Oran,
Judy
Saltzberg,
and
Jack
Riley
for
their
help
at
various
stages
of
this
study.
We
also
thank
Al
Oberlander,
Richard
Calogero,
Susan
Keppler,
Angelina
Bhatia,
Charles
Wyckoff,
and
Robert
Weber
of the
Metropolitan
Life
Insurance
Company
for
their
generous
assistance,
and
John
Creedon
and
Pierre
Maurer
of the
Metropolitan
for
getting
it all
started.
Correspondence
concerning
this
article
should
be
addressed
to
Martin
E. P.
Seligman,
Department
of
Psychology,
University
of
Pennsylvania,
3815
Walnut
Street,
Philadelphia,
Pennsylvania
19104.
repeated
failures.
Second,
we
extend
the
test
of
learned help-
lessness
and
explanatory style
to
performance
in the
workplace.
Selling
life
insurance
is a job
particularly
suitable
for the in-
vestigation
of
learned helplessness
and
explanatory style. Sales
agents repeatedly encounter
failure,
rejection,
and
indifference
from
prospective clients. Consequently,
the
turnover rate among
life
insurance agents
is
very
high
(as are the
training
costs).
Studies
by the
Life
Insurance Marketing Research Association
(LIMRA,
1983)
have
found
that
78% of the
life
insurance agents hired
in
the
United States quit within
3
years
of
service.
We
predicted
that individuals with
an
optimistic explanatory style
will
weather
such
a
challenging
job
better.
In
these studies
we
measured explanatory style with
the At-
tributional Style Questionnaire (ASQ; Peterson
et
al.,
1982;
Se-
ligman
et
al.,
1979).
Helplessness deficits were
operationalized
by
two
objective performance
measures:
survival
and
produc-
tivity.
Survived
represents whether
the
agent
is
still working
or
has
quit
after
a
specified
period
of
time.
Productivity
is the
com-
mission earned
by the
agent,
calculated
as a fixed
percentage
of
the
revenues generated
from
the
sale
of a
life
insurance policy.
The
learned helplessness model (Seligman, 1975)
predicts
that
uncontrollable
failure
will
be
followed
by
lowered response ini-
tiation.
In the job of
selling insurance, this
translates
into
fewer
sales
attempts, less
persistence,
and the
ultimate
learned help-
lessness measure, quitting.
The
reformulated learned helplessness
model (Abramson,
et
al.,
1978)
specifies
which individuals
are
more
vulnerable
and
which
are
more
resistant
to
these deficits
when
failure
is
encountered. Individuals
with
a
vulnerable
ex-
planatory style
will
tend
to
explain
the
cause
of
their
failure
as
more internal, stable,
and
global. They
will
therefore blame
themselves
and
expect
failure
to
recur over
a
longer period
of
time
and in
more
situations.
Consequently, they
will
suffer
more
self-esteem
deficits,
and
response
initiation deficits will
be
more
sustained
in
time
and
across
situations than
for
individuals with
the
opposite explanatory style.
So, we
predicted
that
individuals
who
habitually explain
failure
with internal,
stable,
and
global
832
EXPLANATORY
STYLE
833
causes
would
initiate
fewer
sales attempts,
be
less persistent, pro-
duce less,
and
quit more
frequently
than those
with
a
more
op-
timistic
explanatory
style.
Study
1:
Cross-Sectional
Method
Subjects.
Eleven hundred
Attributional
Style Questionnaires,
along
with
postpaid
return envelopes,
were
distributed
to the
entire
sales
force
of the
Pennsylvania region
of the
Metropolitan
Life
Insurance Company.
A
letter
from
the
regional manager encouraging voluntary
participation
but
assuring
sales
agents that taking
it or not
would
in no way
aifect
their
job
status, accompanied
the
questionnaire.
One
hundred sixty-nine
questionnaires were returned
completed,
and
accurate quarterly
pro-
duction
data
(in
dollar
figures)
was
available
for 94 of
these agents
up
until
that time
in
their career.
The
company keeps accurate computerized
production
records
for the
purpose
of
compensating agents.
We
analyzed
the
synchronous
correlation
of
explanatory style
with
production
for
these
94
agents.
Is
this sample
of 94
representative
of the
1,100
agents
in the
Pennsyl-
vania
region? Because
the
return rate
was so
meager,
our
main concern
was
that
there might
be
systematic production
differences
between
the
respondents
and the
nonrespondents.
The
mean quarterly production
figures
were
slightly higher
for
the
respondents (2,620),
but not
significantly
so
from
the
mean
for the
entire region (2,500;
(test
p <
.45).
Questionnaires.
The
sales agents took
the
Attributional
Style
Ques-
tionnaire (ASQ; Peterson
et
al.,
1982;
Seligman
et
al.,
1979). This
self-
report instrument yields scores
for
explanatory style
for bad
events
and
good events
using
three causal
dimensions—internal
versus external, stable
versus
unstable,
and
global versus
specific
causes.
The
format
reflects
the
fact
that
we
wanted
to
assess
how
respondents
view
themselves along
a
continuum
for
each
of the
three dimensions.
We ask
subjects
to
generate
their
own
cause
for a
series
of
hypothetical events,
and
then
to
rate
that
cause
along 7-point
scales
corresponding
to the
intemality,
stability,
and
globality
dimensions.
The ASQ
does
not
create
or
constrain
the
causal
explanations provided
by the
subject,
but at the
same time
it
allows simple
and
objective quantification
of
responses
by
asking
the
subject
to
rate
the
internality,
stability,
and
globality
of the
causes.
The
questionnaire
is
group
or
individually administered,
and the
fol-
lowing
directions
appear
on the first
page
of the
booklet:
Please
try to
vividly
imagine yourself
in the
situations that
follow.
If
such
a
situation happened
to
you,
what would
you
feel
would
have
caused
it?
While events
may
have
many causes,
we
want
you
to
pick
only
one—the
major cause
if
this happened
to
you. Please
write
this cause
in the
blank provided
after
each event. Next,
we
want
you to
answer some questions about
the
cause.
To
summarize,
we
want
you to:
1.
Read each situation
and
vividly
imagine
it
happening
to
you.
2.
Decide what
you
feel
would
be the
major
cause
of the
situation
if
it
happened
to
you.
3.
Write
one
cause
in the
blank provided.
4.
Answer three questions about
the
cause.
5.
Go on to the
next situation.
Because
we are
interested
in
style—cross-situational
explanations—we
describe
12
different
hypothetical events. Half
are
good events (e.g.,
you
meet
a
friend
who
compliments
you on
your appearance),
and
half
are
bad
events (e.g.,
you go out on a
date
and
it
goes badly).
After
each
event
are
questions about
the
cause. First,
the
subject
is
asked
to
write down
the
one
major
cause
of the
event. Then
the
subject
is
asked
to
rate
the
cause along
the
three explanatory dimensions.
The
agents' scores
on the
Aptitude Index Battery
(AIB;
LIMRA,
1982),
now
called
the
Career
Profile,
were also available.
The AIB is a
self-report
questionnaire that asks
the
applicant undisguised questions
in six
major
areas:
self-assessment
of
job
relevant
skills
and
abilities, career expecta-
tions,
motivating goals, concerns about career, satisfaction with present
job,
and
potential clients. This
selection
instrument
is
widely
used
throughout
the
insurance industry. Scores
on the AIB
match
the
profile
of
the
applicant
to the
profiles
of
successful insurance agents,
and ap-
plicants
are
hired
if
they match such actuarial
profiles
well,
or if
they
match
them marginally
but do
well
in
interviews.
Dependent
measures.
We
used
three
composite
scores
derived
from
the
ASQ:
composite negative
attributional
style (CoNeg), which
is the
composite score
for the six
negative events, summing across
internal,
stable,
and
global dimensions; composite positive attributional style
(CoPos),
the
composite score
for
the six
positive events;
and a
total
score,
composite positive minus
composite
negative
(CPCN),
the
difference
score
between
CoPos
and
CoNeg.
Past research (Peterson
&
Seligman,
1984)
indicates
that
CoNeg
and
CPCN
are the
most valid empirical predictors
of
depressive deficits.
The AIB
yields
a
single composite
score
that
rep-
resents
the
applicant's likelihood
to
succeed
as an
insurance sales agent.
Productivity
is
measured
by the
agent's
quarterly commissions,
in
dol-
lars,
for
the first
eight quarters
(2
years)
of the
agent's employment. Because
we
used
a
cross-section
of
agents,
however,
not all
agents
had 2
years
of
service
for
which
we
could obtain production data. This measure
is
directly
proportional
to and
perfectly
correlated with
the
amount
of
insurance
sold
in
that period. Commissions
for
renewals
of
previously sold policies
are
excluded
from
the
productivity
figures,
because
it is
believed
that
the
first-time
sale
of a
policy requires more motivation than
the
renewal
of
a
currently held
policy.
Procedure.
The
agents took
the AIB
before
they were hired.
We ad-
ministered
the ASQ
after
they
were
hired
and had
accumulated experience
selling
insurance
for
Metropolitan ranging
from
several months
to
several
decades. Local managers distributed
the ASQ to the
agents,
to be
taken
at
their leisure.
The
questionnaire requires about
20 rain to
take.
The
agents
returned
it
directly
to our
research group,
not to
Metropolitan,
in
individual postpaid
preaddressed
envelopes.
Results
Do
agents
with
an
optimistic explanatory
style
sell more
in-
surance
than
agents with
a
pessimistic
style?
The
answer
is
yes.
Distribution
and
reliability.
The
composite
ASQ
scores
had
the
following
means
and
standard deviations: CoNeg
M=
12.00,
SD
=
2.42;
CoPos
M
=
17.43,
SD
=
1.83; CPCN
M
=
5.42,
SD
=
2.92. These statistics resemble those
of
undergraduate stu-
dent populations.
The
reliabilities,
as
estimated
by
Cronbach's
alpha
(1951),
were
modest:
.75 for
CoNeg
and .62 for
CoPos.
There
were
no
significant
differences
in ASQ
scores
for men
versus
women
(CoNeg
(
=
.26,
ns;
men did
slightly
better),
and
no
significant
differences
by
length
of
service
(CoNeg
r =
.02,
ns),
indicating
that
experienced sales agents
did not
have
a
better
explanatory
style than
new
agents.
The
ASQ and
productivity.
CoNeg correlated
significantly
with
the first 2
years
of
production
(r -
-.18,
p <
.07),
the first
year
alone
(r=—.l9,p<
.07)
and the
second year
of
production
(r
=
-.39,
p <
.01). Agents
who
scored
in the top
half
of the
CoNeg,
using
the
median
cutoff,
sold
37%
more insurance
in
their
first 2
years
of
service than agents
who
scored
in the
bottom
half
(;
=
2.19,
p <
.02). (The
/
and p
statistics
refer
to t
test
analyses
on the
difference
in
production means.) More selective
CoNeg
cutoffs
reveal more striking results.
Agents
who
scored
in the top
decile
of
CoNeg sold
88%
more insurance
in
their
first
2
years than those
who
scored
in the
bottom decile
10%
((
=
2.17,
p <
.03). Furthermore, CoNeg discriminated
the
high
and
low
producers
even
better
in
their second
year
of
service than
in
834
MARTIN
E. P.
SELIGMAN
AND
PETER
SCHULMAN
Table
1
Cross-Sectional
Study:
Top
Half
Versus
Bottom
Half
of
the
Sales
Force
on
CoNeg
and
Their
Productivity
CoNeg
score
Production average:
First
and
second year
Good
CoNeg
<.
11.83
Bad
CoNeg
a
12.00
Production:
First year
Good
CoNeg
s
11.83
Bad
CoNeg
£
12.00
Production: Second year
Good
CoNeg
=s
11.83
Bad
CoNeg
:>
12.00
n
40
55
39
54
15
24
Quarterly
production
average
I
3,105 2.19
2,270
2,762 1.37
2,142
6,242
1.96
2,716
P
.02
.01
.03
Superiority
in
production
37%
29%
130%
Note.
CoNeg
=
Composite
negative
attributional
style.
Good
CoNeg
=
Optimistic
attributional
style
for bad
events.
Bad
CoNeg
=
Pessimistic
attributional
style
for bad
events.
All t
test
results
are
one-tailed.
their
first
year. Agents
who
scored
in the top
half
of
CoNeg sold
29%
more insurance
in
their
first
year
(t
=
2.37,
p <
.01)
and
sold
130%
more insurance
in
their second
year
((
=
1.96,
p <
.03) than agents
who
scored
in the
bottom
half.
Tables
1 and 2
present
different
CoNeg
cutoffs
and the
associated production
differences.
CPCN
did not
significantly
discriminate
productivity
at the
median
division
but did
discriminate
by
quartile
and
decile.
Agents
scoring
in the top
half were
9%
more productive
in the
first
2
years than those
in the
bottom
half
(t =
.63,
ns).
The top
quartile
was 36%
more productive
in the first 2
years than
the
bottom quartile
(t =
1.72,
p <
.05),
and the top
decile
was 67%
more
productive than
the
bottom decile
(t -
1.77,
p <
.05).
CoPos
did not
correlate
significantly
with
production.
The
AIB
and
productivity.
The
industry wide test,
the
AIB,
did not
correlate
significantly
with
the first 2
years
of
production
(/•
=
.12, ns).
It is
important
to
note that
the
distribution
of the
agents'
AIB
scores
in our
sample
was
highly
skewed,
because
most applicants
with
low AIB
scores
are not
hired
and
therefore
did not find
their
way
into
our
pool. Some agents
with
marginal
AIB
scores
are
hired because Metropolitan
allows
its
branch
managers
to
hire people with marginal scores,
if
they
look
very
promising
in
interviews.
The
distribution
of ASQ
scores
was not
skewed
(the
population
had not
been
preselected
by
ASQ),
and
ASQ
scores
did not
correlate
significantly with
AIB
scores
(CoNeg
r =
.09,
ns;
CPCN
r =
-.09, ns). Each
questionnaire,
therefore,
appears
to
measure
different
characteristics
and</