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Ecological Analysis of a Hospital
Location Dependencies in the
Behavior of
taff
and Patients]
by
William
F
LeCompte and Edwin
P
Willems
University of Houston Baylor College of Medicine
Abstract
This is a report of an ongoing analysis and
evaluation
of
the Texas Institute for Rehabilitation
and Research in Houston, Texas, which provides com-
prehensive
rehabilitation
to persons with spinal cord
injuries. The major investigative purpose has been
to use methods that would yield
quantitative docu
mentation of a) the nature of the hospital as an
environmental system, and
b)
the nature of the
interface of the hospital's del ivery system with pa
tient
behavior and
experience.
The first
is
provided
by a behavior setting survey of the hospital
as de
veloped by Roger
G.
Barker) and the second by first-
hand observations
of patients.
Against
the
framework
of the
behavior
setting analysis, the observational
data
provide a
fine-grained, quantitative
picture of
patient
behavior, hospital
delivery,
and the loca
tional
dependencies
in
behavior and del
ivery.
This
research can be seen as a prototype or model for
other investigations of environmental dependencies
in human
behavior.
Introduction
Our talk today will describe what we have
discovered
about
the
treatment
environment
of pa
tients with injuries to the spinal
cord,
through the
convergent appl ication of two methods. The methods
to be described
are
different in level of analysis and
in
their data base,
but the two
can
be used to focus
on
a
critical aspect
of any environment designed for
people; namely, the actions
of
individuals within a
defined location. The
relevance
of this work for
environmental design seems
clear;
the field, at pres
ent, consists of a host of untested behavioral assump-
tions embedded in a structural context. The present
methodology is proposed as one way to
articulate and
generate data on these assumptions.
Method]: The Behavior
Setting
Survey
(William
F.
LeCompte)
As defined by Roger Barker (2), and as used
in previous
research,
the behavior
setting
unit
repre
sents a
stable
combination
of one
or more extra
individual patterns
of behavior
surrounded by a
non
psychological
milieu.
Slide] presents
three defin
ing characteristics of any behavior setting. The
following slides
illustrate
these points visually in a
number of locations around the
hospital.
Slide 2: Here is one of the most typical
hos
pital settings;
namely,
a one-man
office.
Slide 3: This
area, called the prevocational
skills area, is interesting because it provides an illus-
tration of
the need for
one
of the defining
character
istics; to the
left
of the
picture
is a fragile white
screen
that
marks the boundary
of
this
setting.
Its
function
is
to inform
one that
he is
entering
a
differ
ent
place.
As a boundary, its function is more sym
bolic than
real.
That
is,
it
does not
filter out
auditory stimuli, and it is too low
to effectively
stop
all
visual cues.
But
the inhabitants of the pre
vocational skills area need it to define
their
territory.
Slide 4: This setting has been labeled as
trafficways in view of its dominant action pattern
of
locomotion . It is
included to illustrate the variety
one finds
in
situations.
Slide 5: Here is a typical laboratory at the
hospital. Note
the high degree
of
individual
atten
tion to projects and the lack of social interaction.
The two people
at
the far
end of
the
lab
are convers
ing in low tones
about
a project, but there
is
little
disruption of the
others.
Slide 6: This is a typical ward
ofthehospital;
one sees occasional signs of boundary maintenance as
in this slide, but generally wards function as a
rich,
open behavior setting.
Slide
7: Let' s turn
to
the
classic areas of
the
t r e ~ n v i r o n m e n t
in a rehabilitation
facil
ity. Here is the general physical
therapy
area.
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Note the vast amount of
specialized
equipment in
this room. The area in the
center
has been affec
tionately designated as the fishbowl and is
speci
a i z e d for the administrative and
clerical
tasks
that
physical therapists
do.
However, the boundaries
here
are
transparent to
allow
the
staff
to observe
their patients.
Slide
8: In this
close-up of
the fishbowl
area, w ~
some of the ways in which the
exclusiveness of this
area
is
maintained, despite
the
visual access to outsiders.
Note
the narrow entrances
and the impossibility of defining the
area as
a
traffic
way.
Intruders sense
that
they must not
enter
and
wait, passively,
to be
noticed.
Slide
9:
This slide depicts quite a different
organization. t is the occupational therapy (OT)
department taken with a wide-angle lens. To your
right
is
the
recreational
therapy and to your
left
is
the general OT
area.
The doors
lead
to
other OT
settings such as a
kitchen,
a woodshop,
and
a driver
simulation room. Contrary
to
physical therapists,
the occupational therapists
apparently
prefer
closed
in areas for
specialized activities.
In
general,
there
are more than twice as many settings in OT than in
PT.
Slide 10:
Finally,
here
is
a view of a weekly
meeting of the rehabilitation team. Note that pa
tients
are
not present
here.
The Behavior
Setting
Survey:
With this much as
introduction,
then,
let me
describe the
behavior setting
survey
of
the treatment
environment.
To begin
with,
the slides
illustrate
one
facet
of this approach
that
is basic to an understand
ing of the method: the units of analysis here
are
not
created
by an investigator, but rather
are
discovered
by him in his survey.
In other words, they exist within the defined
phenomena, in the same way as do cells for a
biolo
gist or planets for
an
astronomer. The task of the
scientific investigator is to achieve a more precise
and
quantitative
description
of
these
naturally
occur
ring
phenomena.
In
the
behavior setting
survey of the
treatment
environment,
122 of these units were reliably
discrim
inated
at a level of interdependence corresponding
to the everyday
experience
of
their inhabitants.
Hence,
the total treatment environment within the
hospital consists of 122
equivalent
units which can be
systematically described in countless ways, depend
ing on the interest of an investigator. For our
pur
poses, let me mention some general findings regardirg
different parts of the treatment environment.
Perhaps the most general question
to
be con
sidered is: To what extent is the treatment
environ
ment devoted to
direct patient-care activities?
The
next slide has been prepared to provide a visual
answer to that
question--it
is based on the Occu
pancy
time
index,
defined as
the product
of i1ietotal
number
of people
in
the setting
times
their average
duration or stay within the
setting.
The
cumulative
result is then multiplied by the number of times the
setting happens within the survey
year.
Slide :
The occupancy time for
each set
ting has been represented in this figure as a circle,
the
area
of which increases proportionately
to
the
total
person-hours-per-year
occupancy of
that
setting.
The total treatment environment of the hospit
al is represented
here.
The 76 settings above the
horizontal
line
are
the
patient
sector
of
the
treatment
environment while the
46
settings below
the line
con
stitute that
part
of
the treatment environment in
which patients
are
not found. The
latter
constitute
the backstage in Goffman's 3) sense, where
im
portant decisions
are
made by professional staff
regarding the fate of the patients. Some
representa
tive backstage settings include: Weekly
chart
rounds
where a doctor reviews his case load; departmental
staff meet i ngs; offices of heads of departments.
To
the left of the
vertical
line bisecting the patient
sector of
the treatment environment
are the classic
treatment
areas.
They
constitute
somewhat more than
25 per
cent
of all
settings.
The remaining settings in
the
patient sector,
to the right
of
the
vertical line,
include a
cafeteria,
walking rounds, and
all other
non treatment settings in which patients
are
found.
In
general,
the total
occupancy
time of the
patient sector is nearly five times as large as
the non
patient
sector of the treatment environment. Hence,
one would expect to find approximately a
f i v ~ t o o n e
difference in occupancy time of professional
person
nel on the
average.
Table 1 presents the
actual percentage of
occupancy
times
in
back-
and frontstage
settings.
The first
column, territorial range,
contains the
per
centage
of the 122 settings in which
each
type
of
personnel is found.
Physicians have the highest territorial range,
entering
over half of the settings in the treatment
en
vironment, while vocational counselors have the
narrowest range,
entering
less than one-quarter of the
122
settings.
Despite this
evidence of
an
extremely
broad
territorial range,
Table 1 shows
that
far
from
maintaining a
five-to-one ratio of
occupancy time
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Table 1
Overall Territorial Range and Percentage
of
Occupancy
Times for Hospital Personnel
in
Frontstage and Backstage Settings
Occupational
Group
Physicians
Aides and
Orderlies
Nurses
Administrative Personnel
Physical Therapists
Occupational Therapists
Social Workers
Vocational Counselors
Other
Occupations
Totals
Contribution to
Occupancy
Times
( of
Total)
Overall Patient
Territorial Sector
Range (N=76)
55%
32
43
49
29
25
39
24
4.9%
34.4
20.2
13.2
2.8
4.9
6.0
2.5
11.1
100.0
Nonpatient
Sector
(N=46)
17.5%
7.3
6.2
47.6
3.7
4.2
3.1
3.3
7.0
100.0
between patient
and
nonpatient sectors
of
the
treat
ment environment, physic ians
actually
reverse the
expected proportions. That
is,
they occupy
non
patient
settings
nearly
four times more than patient
settings. Only
administrative personnel are as remote
from patients. Aides,
orderlies, and nurses
constitute
frontline groups, while
other
professions seem to
dis
tribute
their
time more
evenly.
Turning now to a consideration
of
the
treat
ment environment as a whole, the behavior setting
data are capable
of
generating quantitative,
precise
inter-
as
well as intra-environmental comparisons.
Many writers have described aspects
of
institutions
which
care
for a target population 24 hours a
day
(e.g.,
Goffman,
4).
Such descriptions are
typically
rich in qualitative
detail
and correspondingly poor
in
quantitative
analysis.
Before presenting some
compar
ative data,
let
me
digress for a moment to describe
another
useful unit.
One
of the most important classifications
of
the inhabitants
of
behavior settings relates the amount
of
control a person has over
the activity
in the setting.
Leaders
and active
functionaries within settings
are
called
performers, while customers,
audience,
and
onlookers
are
referred to as member s. We have
found
that
a classification
of
settings on the basis
of
their
performers
is
an important taxonomic step in
studying the treatment environment. Such a
classifi
cation
has been
labeled
a
genotype.
Genotypes:
I n
brief,
two settings are judged to be in the
same
genotype
i at least 75 per cent
of
the timespent
by performers
in
them
is
spent by
people
with
equiva
lent
backgrounds (Barker,
2,
Pp. 80-89).
For
ex
ample, 12 of
the 122
behavior
settings were found to
have physicians in single leadership positions. These
constitute
a single genotype,
and it
can be compared
with
another
genotype in which physicians and nurses
share leadership positions. I n
general, the
122 set
tings
form
a total
of
52
genotypes, each controlled
by
a different combi nation
of
performers. If the number
of
settings in an environment provides a measure
of
the
size
or extent
of
the place, then the number
of
genotypes can be consi dered a measure of the vari
ety
one finds in
that place.
t answers
the question,
How many different kinds
of
things
are there here?
Cqnsider the following
analogy.
A farmer
may tell
that
he has 100
acres
under
cultivation,
with four different kinds
of crops.
Number
of
settings
can
be considered equivalent to
acres
in the
analogy,
and number
of
genotypes to the four types
of crops.
Just
as the
25-to-one
ratio
of acreage
to crops is
meaningful,
the setting-tcrgenotype ratio can tell
us
the
relation of
extent to variety within
the
treatment
environment.
Hospital-Town Comparisons:
Barker
(2)
has provided a number of structural
indices
from
a small midwest town, surveyed during
1963 and
1964.
Table 2 summarizes the
data
from
both hospital and town environments on both extent
and variety measures. These data
bear
on the
ques
tion of the similarity between community types.
Table 2
Ecological Comparisons between
TIRR
and Midwest,
Kansas
Item
T1RR
Midwest
No.
of
Behavior
Settings 122 884
No.
of
Genotypes
52
198
Genotype/Setti ng
.430 .225
Ratio
Total
Occupancy
1,316,185 1,822,004
Time hrs.
hrs.
Time/Setting
Ratio
10,800
2,129
TIRRJ
MWX 100
14%
26%
191%
65%
197%
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The data in Table 2
tell
an interesting story;
the hospital is far less
extensive
than the community,
and t provides only about o n e q u a r t ~ r of the variety
one encounters in the small town. However, one
finds nearly twice the amount of variety per unit set
ting in
TIRR
than in
Midwest.
The hospital records
only about two-thirds
the occupancy
time
of
the town,
yet
here
again
one finds almost
twice
as much
occu
pancy per unit setting in the hospital than in
the
town.
The town
data
in Table 2
include
only com
muni ty behavi or settings;
obviously, the addition Qf
family settings would give rise
to
much greater figVres.
However, the hospital
data
obviously do not i n l u ~ e
the homes
of
the working personnel. I n that respect,
then, it seems quite legitimate
to
compare the two
envi ronments.
Let
me
summarize this
part
of
my
talk
to
pro
vide a
contextual
framework for
Dr.
Willems' descrip
tion of the patient observation methodology. After
his
presentation,
I shall return to discuss some more
specific findings regarding the settings
actually in
habited
by the patients in his observation
sample.
We have found the treatment environment to be
struc
tured into a backstage and a frontstage with
the vari-
0us types
of
hospital personnel positioned accordingly.
The physician seems to operate as a kind
of
back
stage controller, receiving inputs about patients in
directly and sending decisions back through the net
work to frontline personnel. Further, the entire
treatment environment seems, in comparison to
the
small community, to be a more specialized but more
densely populated
place,
with
greater
diversity per
un
it
setting.
Method 2: Direct Observation
(Edwin P. Willems)
Against
the
framework
of
the overall environ
mental survey
of
the hospital presented by Dr. Le
Compte,
we were in the position to study the interface
between the treatment environment and the behavior
and experience
of
its primary target population: the
patients.
What do patients do? What does their behavior
look
like in terms
of events, structure, pace, and dy
namics?
In
what ways,
predicted
or not, do the
behavioral repertoires and
activities of
patients
charge
as they progress through
the
hospital's program
of
treatment? From
the standpoint
of patient behavior,
what happens
in
the various subparts--the behavior
settings--of
the hospital; how can
the
various
behavior
settings be characterized in behavioral terms? How
does the
behavior
and experience
of
patients
change,
and how does the impact of the hospital change as pa
tients
move
from
one subpart
of
the hospital to
another? These questions and others I ke them point
to several notable issues. (a) They poin t to the
crux,
the
payoff point,
of
hospital functioning--they point
to the direct
interface
between the hospital system
and the
behavior
and
experience of patients. b)
Fur
thermore,
such questions
point to the
kinds
of
data
for which students of design and behavior
have
been
pleading.
As is true in so many other areas
of
human
behavior,
these questions
are
u ually answered
through a combination
of crude,
hit-or-miss
observa
tion,
retrospective summaries, interviews,
anecdotes;
and
a host
of
beliefs, assumptions,
and
pet
ideas. In
order to
generate
a more
systematic,
quantitative pool
of data to answer such
questions--and
taking out
pro
cedural cues primari
Iy
from
the
work
of
Herbert F.
Wright and Roger
G.
Barker
(5)--we
began a program
of
direct observation
of patients;
patients
actually
in
the hospital at the time of the behavior setting survey
that
Dr. LeCompte has
described.
Twelve adult patients with high spinal cord in
juries and involved
in
comprehensive
rehabilitation
programs
at
the Texas Institute for Rehabilitation
and
Research made
up the
observational
target group,
including
eight males,
four females, a mixture
of
races and
ages,
and patients who varied
from
early
in
treatment to
predischarge.
For
each
patient, a con
tinuous descriptive protocol was
generated,
based
upon continuous firsthand observation of his
behavior
and situation for one day, beginning at 5:00 a.m.
and ending at 11 :00 p.m.
To
obtain the protocols, a
team
of
three
observers was assigned to
each
of the
patients. On a patient's appointed day, the team
assigned to
him
rotated
in
two-hour observation shifts.
A minimum
of
stri ctures was placed on the
observa
tional
process--observations were recorded in the
everyday
language
of
the obseryers. All observations
were dictated into
small,
battery-operated tape re
corders and in
general,
each passing minute
of clock
time was
noted.
A series
of
systematic
editorial
and
clerical
steps then yielded what we were after: twelve
18-hour protocols, totaling 216 hours
of
patient time,
representing
on-the-spot
descriptions
of
what-the pa
tients did and
including
enough
of
the context
of
their
behavior
to make it
intell
igible.
Our
first
analysis,
keyed
to
answering some
of
the questions mentioned
earlier,
has been based upon
a distinction between molar
and
molecular events
in
the behavior
streams
of
the
patients, or
between what
we call chunks and bits. The analysis assumes
that
a
protocol captures
anddescribes the
ongoing experience
behavior
stream
of
a patient and
that
the
events
in the
behavior stream include things the patient does, things
that are done to him or with him, and segments in
which the patient is idle or
passive.
For our purposes,
our major coding
unit,
a
chunk, is
a molar
event
in
the
behavior
stream of a
patient
which
a) can
be
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readily characterized
by a
single principal
activity,
b) begins at a
clearly described starting
pClint, (c)
occurs
over
time
in
a
characteristic, regular
manner
with
all
its essential
accompaniments, and
d)
ends at
a
clearly described
stopping
point. One
necessary
condition for marking a chunk is that the patient him
self
be
directly involved
in
it.
Thus, if
the
patient
is
clearly described
as
having been involved
in
two
distinct,
molar, principal
activities
at
the
same
time,
two chunks
are demarcated
as
occurring simultane
ously. Chunks
are
marked off with major
brackets.
To
each
chunk marked on
the protocol, the
following
items of information
are attached:
(a) a
descriptive
label for
the chunk; b)
how long
the chunk lasted;
(c)
who, out of
31
categories of other
persons, was
directly involved
in
the principal
activity
of
the
chunk, and
how many such persons
were involved;
d) who instigated the chunk; e)
the degree
of in
volvement by the target patient in
the principal
ac
tivity, on a
scale
from active participation through
passive participation,
to resistive participation; f) the
number
of other
persons in
the
immediate
situation,
but
not
directly involved
in the
principal
activity of the
chunk; g) the beginning clock
time of the
chunk; and
h)
the specific behavior setting
in which
the
chunk
occurred.
The protocols
describe
more
than the
molar
behavi
or
events, or
chunks.
We
have
focused on two
kinds
of
short, fleeting
social
encounters
( bits )-
fleeting
intrusions by others
in
the patients'
behavior
streams. The bits of the first type are directed toward
the patient's care, safety,
comfort,
or treatment. The
second
type
includes
greetings,
fleeting
small talk,
and
other
short, but purely
sociable, encounters.
Each
is accompanied
by a code for who was involved
in
it. Finally,
transfers (from
bed
to
wheelchair,
etc.)
and
transports to formally
scheduled events are coded
as
chunks.
Other
changes of location
or position
are
indicated
by a
separate code.
For our
analysis,
one person
coded
an
entire
protocol, after
which a second person
coded
a portion
of
it
independently.
Across
seven
independent
checks,
involving a total of
730
minutes of protocol time and
four independent coders, pairs of coders agreed on 84
per cent of
their
accounting for protocol time
in
terms
of
chunks (6). A
second
coder
then
studied
each pro
tocol
in
its
entirety and
he
and
the
original
coder
re
solved
any
questions
and
disagreements
that
arose (7).
In order
simply to
illustrate
some
general
characteristics of
the
data
we are
retrieving
from these
observations,
I shall summarize
several aspects of
the
behavior
and experience of
four of the
twelve patients.
All four
were
males,
but,
by
date of
admission
and
progress through
the
hospital's
program
of comprehen
sive
rehabilitation,
two were early
in
treatment and
two
were advanced,
or
predischarge, at the
time
the
observations
were made.
The first two
examples illustrate descriptions
of topographical or structural
aspects
of behavior.
Table 3 shows the total number of separate major
be
havior
stream
events,
or
chunks, that occurred
in the
days of the
early and advanced patients,
as
well
as
the
number
of
different
kinds
of
chunks
that occurred.
Table
3
Summary
of
Numbers
of
Chunks
No. of
different
Total
kinds of
number
chunks
of (out of
chunks
4 kinds)
Early
patients
139.SO
21.0
Advanced patients 193.5
27.5
Advanced/Early
1.39
1.31
aEntries
are averages
for two
patients.
Here
is
a
behavioral documentation of what we com
monly
assume, or at least hope:
as
the patient pro
gresses in
treatment,
his
behavioral
day
becomes
fuller,
more eventful, and more differentiated. The
first two lines show this progress
in
terms of
absolute
numbers
and
the last
line
shows it in terms of ratios
of
advanced
patients over
early
patients.
Table 4 shows
structural aspects in
terms
of
behavioral overlapping.
The first column summarizes
the
average total
number of
observational
minutes
Table 4
Summary of Overlapping, by Instances and Time
Instances
Observational of
Minutes
Overlap
Early
patients
1020.0
23.5
Advanced
patients
1080.0
51.5
Advanced/
Early
2.19
Overlapping
of
Total
Minutes
(Col.
1)
77.75
7.6
180.00
16.7
2.32
2.20
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ava i1able as a basel ine; the second column records the
number of times
that
behavioral chunks occurr ed
simul
taneously, or
in
overlapping fashion, for
each set of
patients; and the third column shows the average num
ber of observational minutes that involved
overlap.
The last column summarizes the proportion
of overlap
ping minutes to
total
observational minutes. The table
summarizes the
extent
to which
the
behavior streams
of
the
patients
proceeded
in
multiple file as against
sim
pie,
single
file.
The ratios in the last line
indicate
that
the behavior streams
of
the
advanced patients
marched along in
complex,
multiple patterns more
than twice as
often,
more than twice as
long, and in
more than twice as high a proportion
of
total time as
the behavior streams
of
the early patients.-fnSUnimary,
the
data in
Tables 3 and
4,
which
exploit
only the
number
of
chunks, the chunk labels, and the length
code,
illustrate that
the
behavior
of
early and ad
vanced patients differs
in
overall richness,
differenti
ation, and complexity.
There
are
many dimensions on which
the
over
all diversity and variation in the
experience
of
pa
tients can be documented
from
these observational
data.
The
data
in Table 5
exploit
the chunk codes
for transfer and transport and the
other change-of
location codes to provide one
picture of
environmental
diversity and change to which the patients were
ex
posed.
From
left to right, the columns summarize
a)
location changes within one room,
b)
movements
across the boundary
of
one room, (c) movements across
the boundaries
of
more than one room,
d)
totals
of
these three kinds
of
changes
of
location, (e)
the num
ber
of
separate behavior
settings
entered, and
f)
the
number
of
times they
entered behavior settings.
First,
whereas
advanced
patients also ranged
in
and
out of
immediate rooms (second column), prob::lbly
reflect
ing the
fact
that they were
in
wheelchairs
and
could
move themselves.
I have focused on the distinctions between two
early and two advanced patients and the normaliz
ing of
behavior
streams with progress
in
rehabilitation
to provide a
relatively
straightforward illustration
of
the
validity
and
usability of
the kinds
of data
we have
obtained
with the procedures we have
described.
We
are
finding such
data
indispensable
in
the
documentation
of
many aspects
of
the system for de
livering
care, treatment,
and service to
patients.
Dr. LeCompte will now present some general
charac
teristics
of
the 19 behavior settings that were
actually
entered by
the 12
patients we observed, after which
we shall demonstrate some
of
the ways we
are
using
the
observational data to study environmental depen
dencies in patient behavior.
Home Range
Characteristics
of
the
12
Patients
(William
F.
LeCompte)
David
Stea's 8)
term, Home
Range, is
an
ecological concept
that can be useful to key in to the
results
of
the present
study.
We have defined the
home range
of
this sample
of
patients as the
total
num
ber of behavior settings penetrated by them during the
day in which they were
observed.
Table 6 contains a
listof the 19settings
in
the
home range
of
these
patients.
Perhaps the first item
to
be considered
regard
ing these
data relates
to
their validity;
to what
extent
Table 5
Changes
of
Location
and
Behavior Setting Entries
Movements
No.
of
Different
No. of
Across
One
Within
Room
Boundary
Room Only
Only
Early Patients
13.0
0.0
Advanced Patients
35.0
7.0
Advanced/Early
2.69
as the
entries in
the last
line indicate, the advanced
patients were involved in much higher numbers
of
lo
cation
changes
of
all
types than were
early patients.
Second, early
patients were
either
involved in
move
ments within rooms (transfers, etc. , first column) or
major transports about
the
hospital (third column),
Past More
Behavior Behavior
Than
One
Settings
Setting
Room
Total Entered
Entries
7.5
20.5
5.5
16.5
29.5 71.5 11.5 56.0
3.93 3.49 2.09
3.39
does the sample
of
12 observation days
reflect
the
general occupancy
time
of patients
at
TIRR? In
order
to generate
data on
this
question,
estimates
of
patient
occupancy
time were
calculated separately from
the
protocol records and from the behavior setting survey
for each
setting.
The last two columns in Table 6
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Table 6
Home Range
of
the 12 Patients in the Observation Sample
Behavior Setting
Total Occupancy Time
Patient
Occupancy Time Estimates
(Person -Hours/Year)
From Behavior
From
No.
Name
Setting Survey) Sample)
l
Nursing Wards
317,828 hrs. 21.00
hrs.
12.22 hrs.
2.
Sel f-care Ward
117,192
hrs.
19.00hrs.
13.30
hrs.
7.
Dental CI inic
4,860
hrs.
1.00hrs.
.59
hrs.
10.
Physical Therapy Area
26,475hrs.
.68
hrs.
2.97hrs.
12.
Electrical Stimulation 261 hrs. .52
hrs.
.14
hrs.
13.
Occupational Therapy Area
22,430
hrs.
.08
hrs.
1.14
hrs.
16.
Recreational Therapy Area
5,935 hrs.
1.00
hrs.
1.37hrs.
20.
Job Clinic
360 hrs. 1.50 hrs.
.11 hrs.
22.
Men's
Lounge
1,150hrs.
-0-
hrs. .10 hrs.
24.
Hallways
207,750
hrs.
.
01
hrs.
.12 hrs
26.
Korner Store
2,667hrs.
.
01
hrs.
.03 hrs
27.
Food Machines
73,444
hrs.
.25
hrs. .63 hrs 0
28.
Waiting Area
30,021
hrs. . 25
hrs.
.33hrs
29.
Cafeteria
24,732 hrs.
1.00hrs.
1.62 hrs.
35.
X -Ray Laboratory
2,781
hrs.
25 hrs. .41 hrs
40.
Photography Studi
4,453
hrs.
12
hrs.
.02 hrs .
49.
Doctor's
Office
4,740 hrs.
-0-
hrs.
.15
hrs.
111. Schoolroom
4,720
hrs.
1.50hrs.
.79 hrs.
112. Evening Recreation 3,750 hrs. 1.50
hrs.
1.13 hrs.
Total
855,549 hrs.
49.67
hrs.
37.17hrs.
provide estimates from the
behavior
setting survey and
from the protocol records, respectively.
In
both cases,
the figures represent average
occupancy
times for a
single patient during one
occurrence of
the
setting.
The patient
occupancy
estimates
from
these two
sources are remarkably close, as is apparent in Table6.
The total times
are
within
12 .5hours of each other.
More impressively, the product-moment
correlation
between the two estimates across the 19 settings
is
+.98.
It seems
clear that
the set
of 12
observation
days furnishes an extremely accurate sample of
patient
occupancy within the home
range.
Turning to the home range
itself,
perhaps the
first item
of
interest is its smallness. This list
of
19
behavior settings constitutes only 15 per cent
of
the
total number of settings in the treatment environment
and with regard to
genotypes,
only 37 per
cent
are
included.
Thus, the
patients'
days
occur
within quite
narrowly define d boundaries, even within the rather
narrow confi nes
of
the treafment envi ronment.
Although the home range
is,
thus, restricted
in
number of settings and
in
genotypes, it
is interest
ing
that
the total
occupancy
time in the patient home
range accounts for more than 75 per
cent of
the total
time in the patient sector.
In other
words, these 12
patients are
located
where the
action
is in the treat
ment environment.
Physical Structure of the Patient Habitat:
As
might be
expected
from the enormous
occu
pancy time
of
the
patient
home
range,
the physical
size
of
these settings tends on the
average
to be
quite
large.
We have measured this with an index
called
the longest
look.
It
is
simply the number
of
feet
in the diagonal from one
corner of
the setting
to
the
opposite corner, representing the longest possible
view withi n the
setting.
Longest look data for the
patient home range provide a mean value
of
nearly
55 feet, compared to 35 feet for all settings entered
by patients, and 27 feet for backstage settings.
Interpersonal Structu re
of
the Patient Habitat:
The
variety of
members
of
the
rehabilitation
team in the patient home range
is
also impressively
large.
Taking the
eight occupational
groups
dis
played in Table 1 and adding another seven groups
that were not displayed we constructed a people
variety index by tallying
the
number
of
times in
each
setting that at least one member
of
a group
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appeared
as a regular inhabitant. The mean people
variety for the patient home range was 6.58,
signifi
c a n t y larger than the mean
of 4.45
for all settings
entered
by patients or the mean
of 4.09
for backstage
settings.
Despite this
evidence
of
greater variety
in
;:>ersonnel,
however,
the
behavior
setting survey
data
show that patients had an unequal probability
of en
countering various types
of
personnel. Ranking
the
15 groups in the
rehabilitation
team on the basis
of
their contribution to
yearly occupancy
time in the
home range provides an index
of
differential
expo
sure to patients. Far in excess
of
any
other
group are
aides and orderlies with a figure above 150,000 hours.
Next in frequency are nurses, with nearly
80,000
hours
of
exposure. Secretaries, custodians, and
occu
pational therapists appear
next
most frequently wi th
approximately
20,000
hours
of
exposure
each. Vol
unteers
occur in
the next category with about
16,500
hours. Three members
of
the
rehabilitation
team
ap
pear next,
with
about 11,500
hours, namely,
physi
cal therapists, physicians, and social workers.
Only
dietitians, vocational counselors, and bracemakers
have fewer hours
of
exposure
in
the
patient
home
range than physicians.
One
very
clear
implication
of
these data on performances is
that
the "front
ine
groups tend to involve poorly trained, low power oc
cupations,
while the appearance
of
physicians is
pro
porti onate Iy few and far between.
Finally,
I would like to
characterizesomeas
pects
of
the "social
weather of
the
patient
home
range.
To what
extent are
the
people
in these
be
havior settings involved in
certain characteristic ac
tivities?
The data show that the most prevalent action
patterns
are
those involving social interaction, cleri
cal
activities, and
nutrition, while treatment and
rec
reation
occur
in about 50 per cent of the
settings.
Somewhat less present are actions such as physical
evaluation,
mai
ntenance,
and activities devoted to
improving personal
appearance. Nearly completely
absent are research and religious activities.
In closing, let me try to summarize some of the
main features of these contextual
data on
the structure
of the
patients' habitats.
We have found the
patient
home range to be larger both
in
physical
size
and in
population than typical behavior settings in the
treat
ment environment, to possess,
on
the
average,
a
greater variety of
occupational types, and to include
a vastly
greater
exposure time
of
low level performers
than skilled
rehabilitation
personnel.
Noticeable
by
their lack
of
exposure in the patient home range
are
such groups as physicians, social workers,
and
physi
cal therapists. Almost completely ab sent from patient
home range are
dietitians,
vocational counselors and
bracemakers. Characteristic
activities
in the patient
home range include social interaction, nutrition,
clerical
jobs, with some recreation and
treatment,
while
physical
evaluation,
personal
appearance,
re
ligion, and research seem to be underrepresented.
With this much
ofa chart
to help
us
survey
the
ecological terrain over the
patients'
habitat,
let us
turn to Dr.
Wi
IIems observational
data
to discover how
individual behavioral indices fit into this
picture.
Behavioral Landscapes: Location Dependencies
in the Home Range of Twelve Patients
(Edwin
P.
Willems)
Dr. LeCompte has presented the actual home
range
of
the 12
patients
who were observed so inten
sively, and he has described that home
range.
In
the parlance of the ecologist, he
has,
first of all,
presented the overall ecological survey of a particu
lar
habitat--the
hospital. Then,
using the
actual
occu
pancy and
behavior ofa subpopulation--the
patients-
as
the
criterion,
he has demarcated a special subpart
of
the
habitat
as the home range of the patients, and
he has described
that
home range by some of its
gen
eral soc
ial, environmental, and
behavioral
charac
teristics. We come now to the final questions
of
this
presentation: Considering the
day-long
observations
of
the 12 patients, how did
their
behavior distribute
itself over the behavior settings that constituted their
home range? And, what were some of the critical
dependencies
on location that occurred in their be
havior?
Across the
12
patient
protocols, our coding
system
yielded
a total
of
1815 chunks and the
addi
tion
of
lengths
of
these chunks
yielded
a
total of
14227 chunk minutes . Table 7 displays the way
in
which these behaviors were distributed across several
behavior settings, in
terms of per cents of chunk
Table 7
Distribution
of
Chunk Minutes by Behavior
Setting
in Which They
Occurred
Stations
1-3
2 Station 4
1 Genera
I
PT
Area
13 General
OT Area
16 Recreationa l Therapy
24 Hallways
29 Cafeteria
Other
Total
No.
of
Minutes %
of
Total
5082
4709
1704
749
403
395
48
837
14227
35.7
33.1
12.0
5.3
2.8
2.8
2.4
5.9
100.0
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minutes that occurred in each. Several things stand
out: (a) Ninety-four per cent of the patients chunk
minutes occurred in the 7 settings displayed.
b) That
means
that 94 per
cent of
the patients behavior time
was captured by fewer than six per
cent of the
hospit
al s
122 behav ior sett ings . (c)
In fact,
about 69 per
cent of
the patients behavior time was spent in only
two
settings--the
two wards or primary living
areas.
Table
8
characterizes three of these settings in
more detail, in terms of the distributions of patient
behaviors that occurred within each. These data in
dicate that in addition to capturing a high proportion
Table 8
Characterizations of Three Settings By
Patient Behaviors
Occurring
in Them
2) Station 4 (4709 Chunk Minutes)
Idle
Nursing Care & Hygiene
Conversing
Sleeping
Eating Scheduled Meal
Passive Recreational
Transferri ng
Telephoning
Exercise & Performance Training
Other
N
1149
1045
828
666
217
151
129
126
123
275
(10) General PT Area (1704 Chunk Minutes)
Exercise & Performance Training
Conversing
Idle
Transferring
Other
29) Cafeteria (348 Chunk Minutes)
Eating Scheduled Meal
Conversing
Other
N
1025
317
161
110
91
N
213
131
4
24.4
22.2
17.6
14.1
4.6
3.2
2.7
2.7
2.6
5.8
60.2
18.6
9.4
6.5
5.3
61.2
37.6
1.1
of
patient
behavior, the wards were also quite diverse
and complex in terms of
patient
behavior. The cafe
teria,
on the other hand, was a much more specia l ized
setting for patients, being devoted to eating and con
versing.
We turn now to a more dynamic,
inferential,
and program-oriented aspect
of
patient behavior.
From
our codes, it is possible to retrieve a) the total
number of waking and non-idle chunk minutes for the
patients, b)
the number
of
chunk minutes in which
the patients acted
alone,
and (c) the number of chunk
minutes instigated by the patients themselves--all
differentiated by behavior settings. With total wak
ing and non-idle minutes as the baseline, averaging
the two per cents for acting alone and patient instiga
tion gives us an index
of
the extent to which the
be
havior streams of the patients were under their own
control, or,
if you
will,
an index of
patient indepen
dence.
Table
9
displays indices of independence for
the seven behavior settings that contained the largest
amounts of
patient behavior.
The highest rates of
behavioral independence by patients were associated
with the
cafeteria
and hallways, two settings which
Table 9
Indices of
Patient
Independence for
Seven Behavior Settings
29)
Cafeteria
24) Hallways
1) Stations 1-3
2)
Station 4
13) General OT Area
10) General PT Area
16) Recreational Therapy
Total
Chunk
Minutes
a
346
387
3003
2894
697
1543
388
Index
of
Independence
64.3
48.1
29.7
23.9
15.1
7.5
.2
aExcludes Idle and Sleeping time.
are only tangential to the formal program of rehabili
tation. By contrast, three settings
that
lie at the
heart
of
the formally defined program
of
rehabilita
tion--physical
therapy,
occupational
therapy,
and
recreational therapy--produced the lowest
rates.
Another way to summarize these data is to say that
when the patients moved from
cafeteria
and hallways
--two
settings that
are
complex and demanding, but
peripheral to the formal
rehabilitative
process--to
the more formal treatment settings, the message some
how got through that they were to be much more de
pendent and doci Ie.
t is possible that these differences in rates of
independence were produced by different patients
who entered the settings at varying rates. To test
this alternative hypothesis, we calculated combined
indices
of
independence for (a)
cafeteria, hallways,
and
wards;
b) occupational therapy,
physical
ther
apy,
and recreational therapy; and c)
each
of the
12
patients.
In the case of each
patient,
the results
corroborated the pattern found above; for all
12
pa
tients,
the index of independence dropped
dramatic
ally as they moved
from
cafeteria-hallways-wards to
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occupational therapy-physical therapy-recrea tional
therapy.
Data such as these not only point to powerful
location dependencies in the dynamics of
behavior,
but they should be useful to those who wish to evalu
ate how their programs
are
being
carried
out. The
use of
patient
instigation and
acting alone
to measure
variations in independence among settings is only one
example of what the observational data
enable us
to
do.
We have analyzed associations between
inde
pendence and types of behavior and differences among
patients. We have studied differences among patients,
settings, types of behavior, and involvements by vari-
0us persons with the patients for their effects upon be
havioral zest, as measured by
patient
initiative and
degree of involvement. We
are
planning analyses
which exploit--singly and in various combinations-
dimensions of behavior such as numbers of chunks per
hour, rate
of overlapping,
and degree of involvement
to make inferences about behavioral pace.
* * * * *
We have presented only a few sparse illustra
tions of our approach to the study of human environ
ments: overal l environmental analys is with conver
gence
down to the way in which the moment-by
moment behavior of inhabitants distributes itself
within that environment. The general investigation
of environment and behavior can
benefit from
the
application
of strategies similar to these because de
facto environmental dependencies should be our point
of
departure.
f
this be
so,
then there
is
no substitute
for being present to observe and measure behavior
when and where it
occurs.
Notes and References
I . The research reported here and the preparati on of
this paper were supported by Research and Train
ing Center No.4 (RT-4), Baylor
College
of
Medicine, funded by Social and Rehabilitation
Services, USDHEW.
2.
Barker, R. G. Ecological psychology. Stanford,
Cali fornia: Stanford University Press, 1968.
3.
Goffman , E. The presenta tion of self in
every
day life. Garden City, New York: Anchor
Book5,l959.
4. Goffman , E. Asylums. New York: Doubleday,
1961.
5. Wright, H. F. Recording and analyzing chi Id
behavior.
New York: Harper Row, 1967.
6. In order to check agreement on the ratings
attached to the chunks, we selected 43 chunks
on whose demarcation two coders had agreed
exactly. Out of these 43 chunks, pairs of
rat
ers
agreed
on the following number and per
cents: T code--39 (90.7 ); 0 code--41 9 5 . 3 ~ ;
I code--40 (93.0 );
01
code--38 (88.4 ); RP
code--33 (76.7 ).
7. Detai Is of the
entire
observational and coding
process are presented in: Wil lems,
E P., &
Vineberg,
S.
E. Procedural supports for the
direct observation
of
behavior in naturciT
settings.
Houston, Texas: Texas Institutefor Rehabilita
tion and Research, 1970.
8. The writers are indebted
to
David Stea for a copy
of an unpublished manuscript which contains the
text of his paper presented
at
a symposium
at
the
University
of
Michigan in 1968.
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