Surgical Science, 2011, 2, 121-126
doi:10.4236/ss.2011.23024 Published Online May 2011 (http://www.scirp.org/journal/ss)
Relevance of Lifestyle and Attitudinal Factors to Spine
Surgery Outcomes: Empirical Results
on a Heterogeneous Sample
Carolyn E. Schwartz1,2, Brian Quaranto1,3,4, Emily Samaha3,4, Mariam Kahn-Woods 4,5, Paul Glazer6
1DeltaQuest Founda tion, Concord, MA, USA
2Departments o f Med i ci ne an d Ort h opaedic Sur gery, Tufts Universi t y Sch ool of Medi ci n e , Boston, MA, USA
3Boston College, Chestnut Hill, MA, USA
4Foundation for Orthopaedic Spine Research, Chestnut Hill, MA, USA
5University of Pennsylvania School of Nursing, Philadelphia, PA, USA
6Department of Orthopaedic Surgery, Beth Israel Deaconess Medical Center,
Harvard Medical School, Boston, MA, USA
Received January 13, 2011; revised April 4, 2011; accepted April 12, 2011
Abstract
Background Context: Patient demographic and medical indicators influence the well-being of spine surgery
patients. It may, however, be worthwhile to evaluate other lifestyle and attitudinal factors. We hypothesized
that such factors would explain at least as much variance in outcome as more commonly considered covari-
ates. Purpose: To compare explained variance in outcome of lifestyle and attitudinal factors as compared to
standard demographic and medical covariates. Study Design/Setting: Cross-sectional observational study of
patients drawn from an active clinic and internet-based support group. Patient Sample: A heterogeneous
sample of 376 patients was recruited, comprised of people with diagnoses of cervical (n = 80), lumbar (n =
228), and scoliosis (n = 68) spine disorders. Outcome Measures: Quality of Life (QOL) outcomes were
measured using the Oswestry Disability Index, Neck Disability Index, Rand-36, PROMIS Pain Impact, NRS
Back and Leg Pain, Scoliosis Research Society-22r, and Global Health. Methods: This study compared ex-
plained variance in QOL outcomes of demographic and medical versus lifestyle and attitudinal factors. De-
mographic and medical factors included age, gender, body mass index, and co-morbidities. Lifestyle factors
included exercise and commuting practice. Attitudinal factors related to social connectedness: giving and
receiving emotional support, feeling overwhelmed by others’ needs, helping orientation, and general helping
behaviors. Regression analyses estimated explained variance. Patient groups differed in most factors evalu-
ated, so the regression analyses were computed separately by group. R2 statistics were characterized as null,
small (0.02), medium (0.15), and large (0.35) effect sizes (ES), and proportions were compared for the medi-
cal/demographic versus lifestyle/attitudinal factors by group. Results: Similar proportions of variance were
explained by demographic/medical and lifestyle/attitudinal covariates across groups, with half of effect sizes
being small in magnitude and 6% being medium. Lumbar patients tended to have more small effect sizes
among lifestyle and attitudinal covariates than among medical/demographic covariates (z = –1.29, p < 0.10).
Similar patterns were found for both generic and disease-specific outcomes. Conclusions: Spine surgery
outcome research should investigate lifestyle and attitudinal factors to enhance the personal and salutogenic
relevance of the research. Time spent commuting, exercise practice, and social connectedness appear to be
relevant factors. A pre-operative evaluation of overweight and smoking status, limited social connectedness,
and long daily commutes could alert the surgeon to delay or avoid performing procedures on these patients to
avoid poor outcomes.
Keywords: Spine Surgery Outcomes, Predictors, Behaviors, Attitudes, Lumbar, Cervical, Scoliosis

C. E. SCHWARTZ ET AL. 122
1. Background Context
Medical outcome research has evolved greatly in recent
years, with increasing sophistication in estimating effects
of medical and surgical interventions to quantify the im-
portance of such effects. Measurement science has ex-
tended such work to facilitate the interpretation of
changes in outcomes in terms of their clinical signifi-
cance [1-3], and has paved the way for evidence-based
clinical treatment guidelines [4-6]. As part of this evolu-
tion, studies in spine research have documented a wide
range of factors that influence treatment outcome, in-
cluding medical factors (e.g., co-morbidities [7]), socio-
demographic factors [8] (e.g., gender, age), and behavio-
ral factors [8,9] (workers’ compensation status [10,11]).
A recent book on psychological factors related to
spine surgery noted a cluster of about ten psychosocial
and medical risk factors with sufficient empirical docu-
mentation to merit continued consideration [8]. Such
factors included psychological or personality factors (e.g.,
hostility, anxiety, depression, history of psychological
disturbance), behavioral factors (e.g., smoking, substance
abuse, worker’s compensation status, obesity), social
support, and attitudinal factors (e.g., job dissatisfyac-
tion) [8]. They note that psychosocial factors are often
found to be stronger predictors of surgical outcome than
are medical diagnostic factors, and derived an algorithm
for determining surgical prognosis on the basis of these
risk factors [8]. We believe that more research on psy-
chosocial factors in spine outcome research is warranted,
and present preliminary findings to support this recom-
mendation.
2. Purpose
The purpose of the present work was to evaluate the as-
sociation of several heretofore-unexamined lifestyle and
attitudinal factors with quality-of-life (QOL) outcomes in
a sample of patients with spinal disorders, and to com-
pare variance explained by these factors and more com-
monly considered medical and demographic factors.
3. Methods
3.1. Design
To achieve a heterogeneous sample, this cross-sectional
study recruited patients from different sources. First,
patients were recruited from an active spine surgeon’s
practice, comprised of people with diagnoses of cervical,
lumbar, and scoliosis spine disorders. Over half of the
scoliosis patient sample (53%) was additionally recruited
from other sources, including local support groups, via
an article in the Scoliosis Association of America, and
via an internet chat room for people with flatback syn-
drome. Second, this study included people representing a
broad range of time since surgery and number of spinal
surgeries. Approximately one quarter of the data were
collected within a month of a planned spinal surgery, and
three quarters of the sample had an average of 4.1 years
since surgery. Since many patients have had repeated
spinal surgeries over the course of their lifetime, com-
bining them into one analytic sample is a reasonable ap-
proach to enhancing the generalizability of the findings
as well as maximizing the sample size. Thus, it is impor-
tant to note that in the present work, “outcomes” refers to
standardized measures of physical, psychological, and
social functioning and well-being, which can pertain to
spine surgery patients at all stages of the treatment tra-
jectory.
3.2. Patient Sample
Three hundred and seventy-six people with diagnoses of
cervical (n = 80), lumbar (n = 228), and scoliosis (n = 68)
spine disorders.
3.3. Outcome Measures
Quality of Life (QOL) outcomes were measured using
the self-reported Oswestry Disability Index (ODI) [12],
Neck Disability Index (NDI) [12,13], Rand-36 [14] for
cervical and lumbar patients and the Rand-12 [15] for
scoliosis patients, PROMIS1 Pain Impact [16], Numeric
Rating Scale (NRS) items for Back and Leg Pain [17],
Scoliosis Research Society-22r [18], and a 10-point Lik-
ert scaled Global Health item. Co-morbidities were
measured by the Self-Administered Co-morbidity Ques-
tionnaire [19]. Demographic factors included age in
years, gender, dummy variables for normal- and obese-
body mass index (BMI), having a college education,
current smoker, currently on worker’s compensation, a
summative score of co-morbidities, and whether the pa-
tient endorsed having diabetes or depression. Lifestyle
measures included: 1) a three-item index of exercise
comprised of strength-building, aerobic activity, and
yoga or Pilates, with response options of rarely/never (a),
1 - 2 times per week (b), or 3 or more times per week (c);
and 2) commuting practices, as measured by daily
amount of time in hours spent commuting. Attitudinal
factors included the Schwartz Altruism Questionnaire, a
validated 18-item measure self-report measure that as-
sesses four aspects of social connectedness: Community
Connection, Community Pressure, Helping Orientation,
1Refers to measure developed by NIH Roadmap Initiative called the
Patient-Reported Outcome Measurement Information System (PRO-
MIS). This measure is a static short-form. See
www.nihpromis.org for details.

C. E. SCHWARTZ ET AL. 123
and General Helping Behavior [20].
3.4. Procedure
The study was reviewed and approved by the Beth Israel
Deaconess Medical Center Institutional Review Board,
and all patients provided written informed consent prior
to completing the questionnaires. Data were collected
online using a secure, HIPAA-compliant interface
(www.surveygizmo.com).
3.5. Statistical Analysis
This study compared explained variance in QOL out-
comes in demographic and medical factors versus life-
style and attitudinal factors. Linear regressions estimated
explained variance. R2 statistics were characterized as
null, small (0.02), medium (0.15); and large (0.35) effect
sizes (ES) [21], and proportions were compared for the
demographic/medical vs. lifestyle and attitudinal factors
by group.
4. Results
Descriptive statistics for the three patient groups are pre-
sented in Table 1. The three patient groups differed in
most factors evaluated, with the scoliosis patients being
younger, a higher proportion female, a smaller propor-
tion overweight or obese, and a larger proportion with
some college education. Scoliosis patients also reported
the longest time since surgery, with a mean of over 13
years as compared to a mean of about 2 years in the cer-
vical and lumbar patients. Scoliosis patients also had a
higher number of surgeries as compared to the cervical
and lumbar patients (mean = 1.64, 1.2, and 1.1, respec-
tively). The cervical and lumbar patients reported similar
numbers of medical co-morbidities, and substantially
fewer co-morbidities than the scoliosis patients. The
prevalence of depression and diabetes was highest
among cervical patients.
Regarding the lifestyle factors investigated, the scolio-
sis patients reported more frequent engagement in all
types of exercise, with a particularly notable difference
in the practice of yoga or Pilates compared to the other
patient groups. Similar proportions of patients were of
Caucasian race, married, currently employed, and current
smokers. The mean time spent commuting was also sim-
ilar across groups. Regarding the attitudinal factors, pa-
tient groups differed on four of the five subscales of the
Altruism scale, with scoliosis patients reporting lower
levels of giving support and helping orientations, higher
reported levels of feeling overwhelmed by others’ de-
mands, and higher reported levels of engaging in general
helping behaviors. There were no differences in reported
Table 1. Descriptive statistics of subsamples.
Cervical
(n = 80)
Lumbar
(n = 228) Scoliosis (n = 68) F or X2 Statistica
Demographic and Medical C h a r a c t er i s t i c s
Mean Age (Sd) 57.9 (13.6)56.9(14.3) 54.7 (11.9)0.55
Gender: % Female 58.4 48.0 92.6 38.7****
% Adolescent Onset
Scoliosis − − 69.1 −
Mean Body Mass
Index (Sd) 27.5 (7.2)27.8 (5.3) 24.7 (3.6)10.85***
% Underweight 10.0 6.3 0
% Normal Weight 27.1 28.3 58.6
% Overweight 37.1 40.3 34.5
% Obese 25.7 25.1 6.9
26.5****
Marital: % Married 64.5 64.0 65.1 0.03
Race: % Caucasian 94.9 92.8 95.0 4.07
Education: % Some
College or Greater 80.0 82.4 92.6 7.42
% Currently Working45.1 42.9 43.9 18.6
% Worker’S Com-
pensation 0 0.44 0 11.2*
Smoking: % Current
Smokers 8.75 7.46 − 11.9†
Katz Comorbidity
Score Mean (Sd) 3.91 (3.69)3.28 (3.50) 5.00 (3.75)11.1***
% Depression
Comorbidity 32.1 22.9 20.3 3.9
Lifestyle Characteristics
Strength-building (sd)1.67 (0.85)1.80 (0.84) 2.03 (0.83)9.84*
Aerobic (sd) 1.72 (0.91)1.79 (0.89) 2.01 (0.83)15.8**
Yoga/Pilates (sd) 1.03 (0.23)1.11 (0.73) 2.59 (0.74)233.7***
Total (sd) 4.39 (1.59)4.68 (1.63) 6.63 (1.64)34.9****
Mean Travel
hours/day (sd) 1.40 (1.96)1.31 (1.01) 1.54 (1.23)1.29
Attitudinal Characteristics
Altruism Scale
Receive Support (sd)1.87 (0.84)1.96 (0.84) 2.07 (.67)0.09
Give Support (sd) 2.09 (.80)2.01 (.91) 1.84 (0.70)0.66
Overwhelm (sd) 0.78 (0.82)0.82 (0.80) 2.42 (1.1)90.02****
Helping Orientation
(sd) 4.64 (0.71)4.31 (1.1) 1.88 (1.2)102.76****
General Helping
Behaviors (sd) 2.04 (0.81)1.91 (0.92) 2.81 (1.0)36.00****
Altruism Total Score
(sd) 35.5 (8.0)34.7 (8.9) 39.2 (7.9)10.8**
a. † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001

C. E. SCHWARTZ ET AL. 124
Table 2. Outcome scores of the subsamples.
Cervical
(n = 80) Lumbar (n = 228) Scoliosis (n = 68)
F or X2
Statistic
Mean SF-36 Physi-
cal Component
Score (sd)
40.1
(11.2)
39.7
(11.9) − 0.32
Mean SF-36 Mental
Component Score
(sd)
45.2
(14.2)
46.1
(13.1) − 1.28
Mean SF-12 Physi-
cal Component
Score (sd)
− − 40.1
(11.2) −
Mean SF-12 Mental
Component Score
(sd)
− − 49.1
(11.7) −
Mean Scoliosis
Research Soci-
ety-22r Total Score
(sd)
− − 3.5
(0.8) −
Oswestry Disability
Index (sd) − 42.3 (16.8) --- 0.41
Neck Disability
Index (sd)
53.7
(19.0) − −
NRS Leg Pain (sd) 2.2
(2.6)
3.2
(3.06) − 6.99**
NRS Back Pain (sd) 3.0
(2.93)
3.8
(2.95) − 3.84*
PROMIS Pain
Impact Short-Form
T score (sd)
58.6
(10.5)
59.4
(10.3) − 0.54
Global Health (sd) 6.5
(2.1)
6.4
(2.1)
6.8
(2.0) 1.82
levels of received support.
Table 2 presents mean outcome scores by patient
group. There were similar scores on the RAND physical
and mental component scores, the ODI/NDI, the
PROMIS Pain Impact Score, and the Global Health item.
Patient responses to the NRS leg and back pain items
differed, with lumbar patients reporting higher levels of
both leg and back pain as compared to cervical patients.
Figure 1 summarizes the findings from the univariate
regressions examining explained variance in QOL out-
come by type of covariate. We found that adjusting for
whether the data were drawn from the pre-surgical vs.
post-surgical sample did not change the effect size for
the covariates of interest. Thus, the reported regression
models did not adjust for type of sample. Similar propor-
tions of variance were explained by demographic/me-
dical and behavioral covariates across groups, with half
of effect sizes being small in magnitude and 6% being
medium. Lumbar patients tended to have more small
effect sizes among behavioral covariates (51%) than
among medical/demographic covariates (37%) (z = –
1.29, p < 0.10). Similar patterns were found for both ge-
neric and disease-specific outcomes.
Figure 2 shows more detail in explained variance in
Figure 1. A comparison of variance explained by demo-
graphic versus behavioral characteristics. Summarizes the
findings from the univariate regressions examining vari-
ance in QOL outcomes by type of covariate. Similar pro-
portions of variance were explained by demographic/
medical and behavioral (lifestyle/attitudinal) covariates
across groups.
Figure 2. Number of small effect sizes by QOL outcome,
separately by diagnostic group. Key points are that generic
and disease-specific outcomes appeared to yield similar
numbers of statistically important effect sizes, although
there were more statistically important behavioral covari-
ates predicting MCS scores than any other QOL outcome.
Additionally, cervical patients generally had more effect
sizes across the QOL outcomes than other patient groups.
Figure 3. Relative importance of behavioral covariates to
QOL outcomes. All three types of behavioral covariates are
important across patient groups and, for cervical and lum-
bar patients, have similar relative importance for the cer-
vical and lumbar patients. For scoliosis patients, however,
altruism and exercise are more important than commuting
practice for explaining spine outcomes.
QOL outcomes by groups. For the sake of simplicity, the
number of small effect sizes is plotted, since these were

C. E. SCHWARTZ ET AL. 125
the most prevalent effect sizes detected. This figure
highlights several points. First, cervical patients gener-
ally had more effect sizes across the QOL outcomes than
other patient groups. Second, there appeared to be a lar-
ger number of statistically important behavioral covari-
ates predicting MCS scores than any other QOL outcome.
Third, generic and disease-specific outcomes appeared to
yield similar numbers of statistically important effect
sizes, with the above-noted exception of MCS. The dis-
ease-specific scoliosis measure appeared to have sub-
stantially more statistically important effect sizes among
behavioral covariates, suggesting that these factors are
particularly important for this patient population.
Figure 3 shows the proportion of QOL outcome meas-
ures for which each behavioral characteristic is statisti-
cally important. These pie charts suggest that all three
types of behavioral covariates are important across pa-
tient groups. Additionally, the three types of behavioral
covariates have similar relative importance for the cervi-
cal and lumbar patients, but for scoliosis patients, altru-
ism and exercise are more important than commuting
practice for explaining spine outcomes.
5. Discussion
This study suggests that in addition to considering
known demographic and medical factors related to pa-
tient outcome, spine surgery researchers should also con-
sider including measures of lifestyle and behavioral fac-
tors. Factors such as exercise practice, average daily
commute, and social connectedness were found to have
similar value in explaining condition-specific and ge-
neric outcome measures as those demographic and
medical covariates generally considered in spine out-
come research. In our heterogeneous spine patient sam-
ple, the effect sizes were generally small for the exam-
ined covariates. Nonetheless, such factors may have a
synergistic effect on treatment outcomes, such that ad-
justing for them increases the detected effect of clinical
interventions.
This study utilized a heterogeneous sample of people
with spinal disorders expressly as a first, exploratory
endeavor to evaluate the utility of such lifestyle and atti-
tudinal factors. To build on this preliminary work, future
research might evaluate the relationship between these
factors and patient outcomes, after adjusting for the de-
mographic and medical factors. It would be useful to
know, for example, whether the examined aspects of
exercise practice, commuting burden, and social con-
nectedness have a similar association with outcomes
across patient age, gender, co-morbidity, diagnosis, and
surgery subgroups. Engaging in a balanced regimen of
exercise (i.e., integrating aerobic, strengthening, and
stretching types of exercise) may reflect other important
patient factors, including socioeconomic status, amount
of leisure time, education level, and motivation. Com-
muting burden may also reflect other factors, such as
type of occupation (i.e., more or less amenable to tele-
commuting, professional occupation rather than laborer
or service occupation), education level, and income sta-
tus (i.e., longer commutes are often related to lower
rent/housing cost further from the urban center). Social
connectedness may play a more important role later in
the recovery process, and may be more relevant for
mental health outcomes rather than disability outcomes.
In past research in adults, such altruistic social interest
behaviors were associated with higher levels of mental
health [22], and lower mortality [23], and males and fe-
males seemed to have different aspects of well-being
associated with such behaviors [20].
The limitations of the present work include the rela-
tively small numbers of cervical and scoliosis patients
that prevent subgroup analyses, and the cross-sectional
design that prevents causal inference. These limitations
are offset by the strength lent by the heterogeneous re-
cruitment strategy. This strategy enhanced the gener-
alizability and statistical power to detect small effect
sizes.
Future research using the analytical approach exem-
plified above may predict poorer outcomes in specific
patient population subsets (such as those who are over-
weight, smoke, have limited social connectedness, and
have longer commutes). A pre-operative evaluation of
these factors might then alert the surgeon to delay or
avoid performing procedures on these patients to avoid
poor outcomes.
In conclusion, this study supports the importance of
including lifestyle and attitudinal factors in an evaluation
of spine surgery outcomes. Such factors should be con-
sidered relevant as covariates for adjusting in data analy-
sis, and possibly even as stratification or matching in
clinical trials. Further, such characteristics should be
addressed clinically before and after spine surgery, since
our findings suggest that they are relevant to QOL and
well-being. One might, for example, encourage the bal-
anced integration of exercise as soon as it is safe after
surgery to improve patient outcomes, both directly and
via reduced BMI. Encouraging the patient to consider
ways to reduce daily time spent in a car may also result
in better outcomes, both by reducing back pain symp-
toms and by freeing up time in the day for activities that
enhance fitness (i.e., exercise) and mood (e.g., social
connectedness activities).
6. Acknowledgements
Funding for this work was provided in part from the

C. E. SCHWARTZ ET AL. 126
Foundation for Orthopaedic Spine Research.
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