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Discussion during treatment decision-making predicts emotional adjustment in prostate cancer patients

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Discussion during treatment decision-making predicts emotional adjustment in prostate cancer patients

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Content DISCUSSION DURING TREATMENT DECISION-MAKING PREDICTS
EMOTIONAL ADJUSTMENT IN PROSTATE CANCER PATIENTS
by
Kysa Christie
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF ARTS
(PSYCHOLOGY)
December 2006
Copyright 2006 Kysa Christie
ii
Table of Contents
List of Tables iii
Abstract iv
Chapter 1: Introduction 1
Chapter 2: Method 7
Chapter 3: Results 17
Figure 1: Participant Accrual and Retention 19
Chapter 4: Discussion 44
Bibliography 52
Appendix 57
iii
List of Tables
Table 1: Influences on Treatment Decision-Making Principal
Components Analysis 12
Table 2: Descriptive Data for Patients who Declined Study Participation 18
Table 3: Demographic and Medical Variables of Study Population 21
Table 4: Conversations and Discussion Time with Social Support Network
and Medical Team 22
Table 5: Frequencies of Influences on Treatment Decision-Making 24
Table 6: Emotional Adjustment Variables: Reliabilities, Means and
Standard Deviations 26
Table 7: Correlations between Predictor and Dependent Variables 28
Table 8: Correlations between Demographic, Medical and Key Study Variables 29
Table 9: Hierarchical Multiple Regression Results for Discussion Time
and Cancer-related Stress 31
Table 10: Hierarchical Multiple Regression Results for Discussion Time
and Positive Affect 32
Table 11: Hierarchical Multiple Regression Results for Discussion Time
and Negative Affect 33
Table 12: Hierarchical Multiple Regression Results for Conversations
and Cancer-related Stress 36
Table 13: Hierarchical Multiple Regression Results for Conversations
and Positive Affect 37
Table 14: Hierarchical Multiple Regression Results for Conversations
and Negative Affect 38
iv
Abstract
Men with prostate cancer are often encouraged to be involved in treatment
decision-making. Talking about treatment options may help men decide on a
treatment and benefit post-treatment emotional adjustment. This prospective,
longitudinal, questionnaire-based study (n=56) examines relationships among
treatment-specific discussions with physicians and social network, factors that
influence patient’s treatment decision, and post-treatment stress and affect. Patients
who engaged in more discussion of their treatment options reported significantly
lower stress, less negative affect and greater positive affect than patients who
engaged in less conversation. Additionally, discussions with social support members
significantly predicted decreases in stress and negative affect one-month following
treatment, while discussions with physicians predicted increases in positive affect.
This study suggests pre-treatment discussions may benefit emotional adjustment and
that discussions with physicians and social networks may be associated with an
overall pattern of adjustment neither achieves alone.
1
Chapter 1: Introduction
For men in the United States, prostate cancer is the most frequently
diagnosed cancer as well as the third leading cause of cancer death (American
Cancer Society [ACS], 2006). Since the late 1980s increased attention has been
given to screening, which has resulted in the detection of prostate cancer with better
prognostic risks for the patient (Cooperberg, Moul & Carroll, 2005). Early detection
is thought to have contributed to a five-year survival rate for local and regional
cancer of nearly 100%. When detected later, the cancer has often metastasized and
the five-year survival rate decreases to 33.5% (ACS, 2006).
Despite the encouraging survival rate for localized disease, cancer is still a
life-threatening illness that can elicit feelings of uncertainty and powerlessness, fears
about the cancer spreading or premature death, and apprehension about treatment
side-effects (Lintz et al., 2003; Perczek, Burke, Carver, Krongrad, & Terris, 2002;
Roesch et al., 2005). Receiving a cancer diagnosis is clearly a stressful time, even in
comparison to later points during treatment and recovery (Bisson et al., 2002; Eton &
Lepore, 2002; Perczek et al., 2002, Stanton & Snider, 1993; Steginga & Occhipinti,
2006; Steginga, Occhipinti, Gardiner, Yaxley, & Heathcote, 2004; Stone, Richards,
A'Hern, & Hardy, 2001; Thornton, Perez, & Meyerowitz, 2004).
Although several longitudinal studies report a decrease in psychological
symptoms over time (Litwin et al., 1998; Stiegelis et al., 2004; Thornton et al.,
2004), these results do not occur for everyone. Some studies fail to find significant
2
changes within six months of diagnosis (Green, Pakenham, Headley, & Gardiner,
2002; Visser et al., 2003). Additionally, a few studies with a longer follow-up period
indicate symptoms of distress may be evident up to 4 years following treatment
(Powel & Clark, 2005; Steginga et al., 2004; Steineck et al. 2002). Given the
variability in stress and mood during cancer diagnosis, treatment and recovery,
understanding factors related to beneficial changes over time would be a major
contribution.
Increasingly, prostate cancer patients are encouraged to be involved in the
treatment decision-making process (ACS, 1999). Although research suggests a
psychological benefit of being involved in treatment decisions (Deadman, Leinster,
Owens, Dewey, & Slade, 2001), making a treatment decision is still a stressful
experience (Gwede et al., 2005; Steginga et al., 2004). Depending on the stage of
the cancer, a man’s age and general health, several treatment options may be
available. For localized cancer, the most common treatments include surgery,
radiation, and close monitoring of symptoms and disease markers, often called
expectant management (ACS, 2006). For non-localized cancer, hormone therapy is
often administered alone or in combination with radiation or surgery (ACS, 2006).
The three primary treatment approaches for localized prostate cancer have
comparable survival rates (ACS, 1999; Klein & Kupelian, 2003). However all
treatments involve varying degrees of side-effects including urinary, sexual and
bowel dysfunction (Eton & Lepore, 2002; Potosky et al., 2002, 2004; Steineck et al.,
3
2002). Given the multiple methods of treatment and their associated risks and
benefits, the patient literature recommends that men gather as much information as
possible, educate themselves about each option and make a decision based on
personally relevant considerations (ACS, 1999).
During the treatment decision-making process, patients may discuss
treatment options with their doctors, family and friends. Although talking about
cancer and treatment choices may be stressful at the time, the experience may benefit
later emotional adjustment. Several mechanisms have been suggested for why
talking aids adjustment. Among these is the idea that talking about stressful events
provides an opportunity for cognitive processing (Redd et al., 2001). Within the
trauma and psychotherapy literature, cognitive processing has been defined as
examining a feared or stressful situation in order to integrate its threatening aspects
into a non-threatening, meaningful framework and to achieve emotional acceptance
of the stressor (Lepore & Helgeson, 1998). Another theory suggested by Creamer,
Burgess and Pattison (1992) posits that cognitive processing involves a cycle of
intrusive and avoidant thoughts about a stressor. While intrusive thoughts are
generally conceptualized as involuntary, the social and deliberate act of discussing
treatment options with others may activate intrusive thoughts. With cognitive
processing, intrusive thoughts are expected to decrease over time, along with reports
of distress.
4
This study applies cognitive processing theories to prostate cancer treatment
decision-making. Consistent with the finding that increased exposure to stressful
thoughts is associated with decreased stress over time, it is hypothesized that
discussions about a patient’s treatment choice may provide opportunities for
cognitive processing. Such opportunities may help patients both come to a decision
and aid emotional adjustment over time.
Previous research has retrospectively investigated social cognitive processing
among prostate cancer patients (Lepore and Helgeson, 1998). The authors examined
the relationship between intrusive thoughts and the social constraints that men
experienced while talking about their cancer. Lepore and Helgeson found that men
who had difficulty discussing their cancer with their partners were more distressed
by cancer-related thoughts than men without such difficulties. In addition, men who
felt constrained when discussing their cancer were more likely to attempt to avoid
cancer-related thoughts, compared to men who experienced fewer constraints
(Lepore & Helgeson, 1998). The possibility that men with worse mental health may
have been more likely to remember feeling constrained during conversations,
retrospectively, was raised by the study authors, and is a limitation addressed by the
current prospective study.
Conversations with others may also introduce novel perspectives and provide
information and factors to consider (Boehmer & Babayan, 2005; Clark, 1993). In
the case of treatment decision-making, an array of medical and non-medical factors
5
may influence a man’s decision. Considering multiple factors may be particularly
important given the absence of a treatment that confers a clear survival advantage.
The patient literature encourages men to be involved in their treatment choice
and recommends seeking information before making a treatment decision. Studies
from the cancer literature have also suggested that having more information benefits
psychological adjustment (Orr, 1986; Zemore & Shepel, 1987). However, what kind
of factors do patients report to be most influential? Two recent studies examined the
type of information and sources patients value while in the pre-treatment period
(Boehmer & Babayan, 2005; Capirci et al., 2005). A majority of patients in the
Capirci et al. study identified their primary concerns to be, will the treatment cure
my disease, and if my disease is not treated, will I die from it? The predominant
questions about survival are consistent with the fears of death and feelings of
uncertainty that arise in response to a cancer diagnosis. However, given that five-
year survival rates for localized cancer are nearly 100%, patient’s treatment
decisions are likely to be influenced by reasons other than maximizing the chance of
survival.
Given the options patients face and the uncertainty of treatment side-effects,
what recommendations can doctors give their patients to aid psychological
adjustment following treatment? Should patients be encouraged to consider several
different factors as they make their decision, discuss their options extensively, and
have conversations with many different people?
6
The current study aims to address these questions. In accord with cognitive
processing theories, I hypothesize that discussing treatment options with others and
considering multiple ways a treatment may influence a patient’s life will benefit
patients’ cancer-related stress, positive affect and negative affect in the months
following treatment. It bears mentioning that the Creamer et al. (1992) cognitive
processing model focuses on negative symptoms of a stressor, and does not
specifically address positive affect. In an effort to examine a broader
conceptualization of emotional adjustment, this study includes positive affect as an
outcome of interest. In the current study, patients reported whom they spoke with
from their medical team and social support system, for how long they discussed their
treatment options, and which factors influenced their treatment decision. Since
treatment-related discussions may also increase patients’ understanding of their
options, I also consider the hypothesis that patient perceived understanding of
treatment information mediates the association between treatment-related discussions
and emotional adjustment.
7
Chapter 2: Method
The current study is part of the Prostate Outcomes Project (POP), conducted
in partnership with Cedars-Sinai Medical Center. POP is a prospective, longitudinal
study examining the psychological correlates of treatment decision-making for
prostate cancer and health related quality of life.
Participants and Procedures
From April 2003 – July 2005, 162 participants were recruited by physicians
affiliated with Cedars-Sinai Medical Center and through self-referral. Physician
specialties included urology, oncology, and radiation oncology. Study eligibility
criteria included men who: 1) had a first diagnosis of prostate cancer, 2) had not started
primary treatment for prostate cancer
1
, 3) had no other active or metastatic cancer
other than non-melanoma skin cancer, 4) did not have a recurrence of prostate cancer
within six months following treatment, and 5) were able to read and write English.
During the appointment in which a participant received a prostate cancer
diagnosis, the physician also discussed POP with him. If interested in learning more
about the study, the investigator contacted the patient by telephone and requested
permission to send a consent form packet that included the study objectives and
1
Study investigators permitted the inclusion of four men who began hormone therapy within 21 days
of completing the pre-treatment questionnaire. The rationale for their inclusion was that hormone
therapy does not take effect until 2-3 months after receiving the first injection. Therefore the
questionnaire would have been completed before the effects of treatment began. Additionally, when
these four men were compared to the 11 other participants receiving hormone therapy, no significant
group differences were found for any study variables (p>.10).
8
timeline. A follow-up call was then made to review the packet and answer questions
about the consent form or project.
If a patient declined to participate upon being contacted by a study
investigator, the investigator asked permission to administer a refusal questionnaire
containing seven questions about how prostate cancer has affected his quality of life,
his role in the treatment decision-making process, and confidence in and
expectations about his treatment choice. Men who preferred not to answer these
questions were thanked for their time. Referred patients could also make a “soft
decline” by not responding to any of three phone messages left about the project.
Men who consented to participate received three questionnaire packets and
pre-paid return envelopes by mail. The first questionnaire was designed to obtain a
measure of pre-treatment behaviors and emotional functioning before the impact of
primary treatment. For men receiving neo-adjuvant hormone therapy, primary
treatment was considered to be surgery or radiation and the pre-treatment
questionnaire had to be completed before the start of surgery or radiation. To
account for delays in mail delivery, investigators allowed a ten day window between
the start of treatment and due date for questionnaires at all three time points.
The second and third questionnaire packets were designed to measure
emotional adjustment one and six months following completion of primary
treatment. Due to the variable course of hormone therapy, men receiving hormone
therapy as their primary therapy received the second and third questionnaires one
9
and six months following the start of their treatment. Men who elected expectant
management were sent the second and third questionnaires one and six months after
the receipt of their first questionnaire. For men who elected a combination treatment
approach (e.g. hormones and radiation), post-treatment questionnaire mailing dates
were based on the date of completion of the primary treatment, i.e. surgery or
radiation.
If a participant failed to return a questionnaire within 30 days, he received up
to three telephone reminders. If two consecutive questionnaires were not returned, it
was assumed he no longer wished to participate and he was removed from the study.
All questionnaires were reviewed upon receipt and participants with missing data
were contacted by telephone or mail. In situations with only a few missing items,
investigators made up to three attempts to reach a participant by phone. If less than
25% of the data for a subscale was missing and it could not be obtained from the
participant, the mean of the individual’s score on the missing subscale was
substituted for a missing item. If an entire page or more had been omitted, the page
was mailed to the participant for completion. Investigators did not employ data
substitution if more than 25% of the data was missing from a subscale or 15% from
an entire scale.
Instruments
The current study measured five types of variables: demographic and medical
characteristics, discussions about treatment options, influences on treatment
10
decision-making, patient perceived understanding of treatment information, and
emotional adjustment. Study measures are included as an Appendix.
Demographic and medical characteristics.
Participants provided information about their age, marital status, education
and income. Participants also granted access to their medical records which
provided indicators of disease severity. This study uses Gleason scores as a measure
of prognosis. Gleason scores are determined by pathologists and represent the
differentiation of the two most common patterns in a patient’s cancer cells. The
possible range of Gleason scores is 2-10, with higher scores indicating
undifferentiated cancer cells and typically poorer prognosis (ACS, 1999).
Discussion about treatment options.
The pre-treatment questionnaire contained two measures of treatment
decision-making discussions: Conversations about Treatment Options
(Conversations) and Time Discussing Treatment Options (Discussion Time).
Conversations and Discussion Time are based on actual discussions with the patient’s
medical team and social support network. Both measures were developed for POP.
To measure Conversations, participants were asked: 1) how many
conversations they had with each of several doctors (primary care, oncologist,
urologist, radiation oncologist, other) concerning their treatment decision for prostate
cancer; and 2) how many minutes they spent discussing treatment options with each
doctor. Participants also provided the same information about conversations with
11
members of their social support network (spouse or partner, other family member(s),
another prostate cancer patient, close friend, religious advisor, or other). If
participants discussed treatment options with a physician or social support member,
they indicated if they had 1, 2, 3, or 4 or more visits or conversations with them.
Given the “4 or more” response option, the data provide an estimate of conversations
rather than an exact number. These data yield two values: 1) an estimate of
Conversations with the medical team and social support network; and 2) total
Discussion Time (in minutes) spent with the medical team and social support
network.
Influences on treatment decision-making.
The Influences on Treatment Decision-Making scale (ITDM) contains a list
of 13 items that might influence the patient’s treatment decision (e.g. doctor
recommendations, length of recovery, travel plans, family opinions). The list was
developed by prostate cancer specialists at Cedars-Sinai Medical Center and prostate
cancer patients who participated in focus groups during study development.
Participants indicated the extent to which each matter played a role in deciding what
treatment was best for them. Each item is rated on a 4-point Likert-type scale,
ranging from 1 (“not influential”) to 4 (“very influential”). Responses are
dichotomized into “not considered influential” (rated 1) or “considered influential”
(rated 2-4). The possible score for items considered influential ranges from 0-13.
12
A principal components analysis with a varimax rotation was conducted on
the ITDM scale to determine if an underlying structure existed among the 13 items.
The analysis was based on the participants who returned the first questionnaire
before beginning primary treatment (n = 74). The analysis produced a four-
component solution, primarily evaluated by eigenvalues and variance. Principal
component item loadings and variance are presented in Table 1. The four
components contained only items with positive loadings. If an item loaded > .30 on
two components, it was categorized to the component on which it had the highest
loading. The principal components represent Treatment-specific Influences ( =
.81), Personal Commitments and Obligations (=.77), Influence of Medical
Professionals ( = .81), and Career and Religious Influences (=.50).
Table 1. Influences on Treatment Decision-Making Principal Components Analysis
Rotated Component Matrix
Component
% Total
Variance
Cumulative
Variance (%)
1 2 3 4 29.63 29.63
Treatment-specific Influences
Treatment side effects 0.85 0.11 0.01 -0.02
Length of recovery 0.77 0.26 -0.18 0.14
Post-treatment disability factors 0.74 -0.07 0.08 -0.03
Length of treatment 0.70 0.42 0.04 0.13
Personal Commitments and Obligations
Treatment scheduling issues 0.10 0.84 -0.01 -0.13 15.15 44.78
Travel plans 0.02 0.78 0.15 -0.06
Financial concerns 0.14 0.69 -0.14 0.25
Family responsibilities 0.36 0.66 -0.05 0.25
Influence of Medical Professionals
Physician opinions 0.05 0.03 0.93 0.02 11.98 56.77
Doctor recommendation -0.05 -0.04 0.88 -0.10
Career and Religious Influences
Religious beliefs/practices -0.04 0.15 0.28 0.84 9.97 66.74
Career concerns 0.30 0.23 -0.26 0.62
13
Patient perceived understanding of treatment information.
Three questions about Patient Perceived Understanding of treatment information
(PPU) were written for the POP study. Participants were asked: 1) how well do you
understand the information you have acquired or received, 2) how well do you
understand the possible advantages and disadvantages that prostate cancer treatments
may cause, and 3) overall, how prepared do you feel about what to expect with
regard to possible changes to your health and lifestyle after treatment? Items were
scored on a seven-point Likert-type scale, in which a higher score indicated greater
PPU. Responses to the three items were summed, yielding a possible score from 3-
21. Internal consistency for the three PPU items is acceptable ( = .76, n = 74). A
fourth item was originally included in the PPU scale but not included with the final
scale due to an internal consistency below the generally accepted standard of .70 ( =
.68, n = 74) (Lattin, Carroll & Green, 2003). The omitted item asked, How
satisfactory is this information in meeting your needs concerning your treatment for
prostate cancer? This item may reflect patient satisfaction with information, rather
than understanding, and thus it decreased the internal consistency of the four-item
scale.
Emotional adjustment.
Cancer-related stress is measured with the Impact of Events Scale – Revised
(IES-R; Weiss & Marmar, 1997). The IES-R measures participant’s reactions to
prostate cancer at each of the three study time points. The IES-R is an updated
14
version of the IES (Horowitz, Wilner, & Alvarez, 1979) and contains 22 items that
can be anchored to any specific life event. The pre-treatment IES-R uses “prostate
cancer” as the reference, and the one month and six months post-treatment IES-R
anchors responses to “prostate cancer recovery”. The items correspond with three
distinct subscales that represent the primary responses to traumatic events; intrusion,
avoidance, and hyperarousal.
For each item on the measure, participants are asked to rate how distressing
each has been for him during the past 7 days with respect to his prostate cancer.
Each item is rated on a 5-point Likert-type scale ranging from 0 (“not at all”) to 4
(“extremely”). The mean of each subscale is summed to yield the total IES-R.
Possible scores range from 0-12. The IES-R subscales and total score demonstrated
adequate reliability at each time point for participants who completed all three
questionnaires on-time, (’s >.73, n = 56).
At each time point, participant ratings of mood were obtained with the
Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988).
The PANAS is a 20-item list of words describing feelings and emotions. The
measure yields an orthogonal rating of positive affect (PA) and negative affect (NA).
NA scores have been associated with self-reported stress. PA scores have been
associated with feelings of activity, alertness and enthusiasm (Watson et al., 1988).
In the pre-treatment questionnaire, participants are asked to indicate to what
extent they have felt this way “since their prostate cancer diagnosis”. In the one
15
month and six months post-treatment questionnaires, participants are asked to what
extent they have felt this way “during the past four weeks”. Each item is rated on a
5-point Likert-type scale, ranging from 1 (“very slightly or not at all”) to 5
(“extremely”). The NA and PA subscale scores each have a possible range of 10-50.
For participants who completed all three questionnaires on-time, Cronbach’s alpha
for NA and PA was adequate at each time point (’s >.79, n = 56).
Analyses
For patients who declined participation, descriptive statistics are reported for
each item on the refusal questionnaire. Five of the seven items on the refusal
questionnaire are also asked of participants in the pre-treatment questionnaire; thus
participant and non-participant responses are compared with an independent t-test.
To compare men who completed all time points of the study with those who did not,
a retention analysis with independent t-tests on demographic and medical
characteristics, pre-treatment measures of Discussion Time, Conversations, ITDM,
patient perceived understanding of treatment information and emotional adjustment
are conducted. When comparing group differences in accrual and retention, I adopt a
conservative standard and report p-values <.10.
Correlations between all key variables are calculated to test for
multicollinearity and to identify potential confounders of the relationships between
the predictor and criterion variables. Previous studies suggest disease stage (Lintz et
al., 2003), type of treatment (van Andel et al., 2004), patient age (Lintz et al., 2003),
16
and time since diagnosis or treatment (Bisson et al., 2002; Lintz et al., 2003; Litwin,
Shpall, Dorey, & Nguyen, 1998; Stiegelis, Ranchor, & Sanderman, 2004; Thornton
et al., 2004) may be potential confounders.
Descriptive statistics for the key predictors, Discussion Time, Conversations
and ITDM, are provided. In addition, this study uses multiple regression to analyze
Discussion Time, Conversations and ITDM as a predictor of emotional adjustment
(IES-R, positive affect and negative affect) at one and six months post-treatment.
Analyses are residualized to examine the change in emotional adjustment from pre-
treatment (Time 1) to each of the two post-treatment time periods. To be specific,
Time 1 negative affect, positive affect or IES-R scores are entered in the first block.
The second block contains the potential confounders identified with the correlation
matrix. The third block contains the predictor of interest. P-values less than .05 are
considered statistically significant.
17
Chapter 3: Results
Study Recruitment
Nineteen of 162 men referred for participation were ineligible due to
beginning treatment prior to consent (n = 15), having metastatic disease (n = 2), or
having an unconfirmed diagnosis of prostate cancer (n = 2). From the remaining
group of 143 eligible patients, 69% (n = 99) consented to participate in POP. Figure
1 details participant accrual and retention. Of the 44 men who declined participation,
25 actively declined and 19 did not respond to calls from the study investigator.
Fourteen of the men who declined participation agreed to complete the refusal
questionnaire. Independent t-tests failed to find any significant group differences
between men who declined participation and study participants (see Table 2). Ten
patients provided reasons for declining participation: concerns about privacy elicited
by the HIPAA notice (n = 4), too busy (n = 3), too sick (n = 1), not interested (n = 1),
and a patient’s physician recommended against participation (n = 1). Eight of the 14
patients who declined participation had not chosen a treatment. The remaining six
patients chose surgery (n=3), hormone (n = 1), radiation (n = 1), and a combination
of hormone and radiation treatment (n = 1).
Ninety-nine participants received the pre-treatment questionnaire, of whom
74 men (75%) returned it within the required time period (Figure 1). The current
study is based on 56 participants (39% of eligible patients) who returned all three
questionnaires within the allotted time period. Three reasons account for study
18
attrition: return of questionnaires beyond the allowable time period, failure to return
questionnaires despite telephone reminders, and participant-initiated withdrawal
from the study.
An independent samples t-test of key variables compared participants who
returned the first questionnaire on-time but had an invalid second or third
questionnaire (n = 18) with participants who returned all three questionnaires on-
time (N = 56). Men who did not have a valid second or third questionnaire were
significantly older, t(72) = 3.16, p<.01 (M = 68.61 years (6.52) vs. 62.18 years
(7.79)), had a higher Gleason score, t(69) = 2.63, p = .01 (M = 7(1.00) vs. M =
6.39(.73)); and reported less negative affect, t(72) = -2.35, p = .02 (M = 15.33(6.54)
vs. M = 19.75(7.07)) than participants who returned all three questionnaires on-time.
Table 2. Descriptive Data for Patients who Declined Study Participation
Declined
Participation
Study
Participants
Refusal Questionnaire Items Mean (SD) N Mean (SD) N
Extent of patient control in deciding his
prostate cancer treatment
4.36 (0.84) 14 4.50 (0.81) 56
Confidence that treatment is the best
choice for patient
4.00 (0.58) 13 4.16 (0.81) 55
Likelihood that the treatment patient had
for prostate cancer will cure the cancer
altogether
3.46 (1.20) 13 3.45 (1.19) 56
Likelihood that the treatment will result
in additional treatments over time
2.25 (1.06) 12 2.54 (1.04) 56
Likelihood that the patient’s treatment
will result in recurrence of cancer
2.00 (1.00) 9 2.05 (0.82) 56
Prostate cancer has affected patient
quality of life
3.00 (1.08) 13 *
Overall stress of the treatment decision-
making process
2.64 (1.15) 14 *
Note. Answers were coded: 1 = not at all, 2 = a little bit, 3 = somewhat, 4 = quite a bit, 5 = very much.
Group means for each item did not significantly differ (p>.10).
* Study participants were not asked this question
19
Figure 1. Participant Accrual and Retention
Referred for
participation n=162
Met eligibility criteria
n=143
Did not meet
eligibility criteria n=19
Consented to
participate n=99
Declined participation
n=44
Returned pre-treatment
questionnaire on-time n=74
Did not return three
questionnaires on-time
n=43
Returned pre-treatment and one
month post-treatment
questionnaires on-time n=61
Returned pre-treatment, one
and six months post-treatment
questionnaires on-time n=56
20
Across the three time periods, 13 of the 99 consented participants (13%) were
dropped from the study after failing to return two consecutive questionnaires. In
addition, three participants (3%) actively withdrew themselves over the course of the
study. One participant withdrew during the one month post-treatment period citing
that the study asked too many questions. Two others withdrew during the six-month
post-treatment time period, citing too many questions (n = 1) or that the questions
did not pertain to him (n = 1).
Patient Characteristics
The 56 men who completed all three questionnaires on-time were
predominantly Caucasian (n = 50, 93%), married or partnered (n = 46, 85%) and
highly educated (77% had completed four-years of college or more). Participant’s
age ranged from 46 – 81 years (M = 62.18, SD = 7.79). Table 3 details additional
descriptive information for demographic and medical variables.
Discussion and Treatment Options Descriptive Data
Table 4 provides descriptive data for Conversations and Discussion Time
with doctors and social support network. As one would expect, all participants
reported at least one conversation with a doctor. Although more participants
reported having a single conversation with a urologist than any other specialty, over
25% of men reported two or more conversations with a primary care physician and
oncologist. Discussion Time with doctors ranged from 15 minutes to 14.83 hours (M
= 3.67 hours, SD = 2.85 hours).
21
Table 3. Demographic and Medical Variables of Study Population (N = 56)
n %* Mean (SD)
Age 56 62.18 (7.79)
Gleason score 56 6.39 (0.73)
Education
Some high school 2 4%
High school graduate 1 2%
Vocational 1 2%
Some college 7 12%
Associates degree 2 4%
Bachelor degree 8 14%
Some Graduate school 12 21%
Masters degree 11 20%
Doctoral degree 12 21%
Relationship status
+
Single 4 7%
Married 43 80%
Widowed 1 2%
Divorced/Separated 3 6%
Significant other 3 6%
Ethnicity
+
African-American 1 2%
Asian/Pacific Islander 1 2%
Non-Hispanic Caucasian 50 93%
Other 2 4%
Treatment
Hormone (H) 15 27%
Radiation (R) 7 12%
Surgery (S) 20 36%
H/R 7 12%
H/S 1 2%
R/S 2 4%
Expectant Management 4 7%
* Due to rounding, percentages may not equal 100%
+
Item data missing for two participants
22
Ninety-six percent (n = 54) of participants reported having discussions with
their social support network. The people most frequently involved were a spouse or
partner (84%), another prostate cancer patient (70%), family member(s) (57%), and
close friend(s) (54%). Of the participants who were partnered, all but one participant
involved his spouse or partner in discussions and 96% of partnered men reported
having 4 or more conversations with their partner.
Discussion Time with one’s social network ranged from zero minutes –
127.67 hours (n = 53). The open-ended format of the question resulted in a
distribution skewed to the right (mean = 888.57 minutes, SD = 1620.75, median =
300 minutes). The greatest Discussion Time was spent with a spouse or partner (M =
8.95 hours, SD = 21.74), followed by other family members (M = 2.43 hours, SD =
8.94), other prostate patients (M = 1.34 hours, SD = 2.00) and close friend(s) (M =
1.16 hours, SD = 2.19).
Table 4. Conversations and Discussion Time with Social Support Network and Medical Team
Social Support Network
Spouse/
Partner
Other
family
members
Another
prostate
patient
Close
friend
Religious
advisor Other
Freq % Freq % Freq % Freq % Freq % Freq %
Conversations
(n = 56)
0 9 16.07 24 42.86 17 30.36 26 46.43 53 94.64 48 85.71
1 0 0.00 4 7.14 6 10.71 30 53.57 3 5.36 8 14.29
2 1 1.79 2 3.57 9 16.07 0 0.00 0 0.00 0 0.00
3 1 1.79 3 5.36 3 5.36 0 0.00 0 0.00 0 0.00
>4 45 80.36 23 41.07 21 37.50 0 0.00 0 0.00 0 0.00
Minutes Minutes Minutes Minutes Minutes Minutes
Sum Social
Support
Discussion Time
n 53 55 54 54 56 56 53
Mean 537.11 145.82 80.46 69.76 2.77 43.93 888.57
SD 1304.60 536.24 119.85 131.31 14.33 243.30 1620.75
Median 120 30 30 8.5 0 0 300
Min 0 0 0 0 0 0 0
Max 7200 3600 600 600 90 1800 7660
22
Table 4: Continued
Medical Team
Primary
Care
Physician Oncologist Urologist
Radiation
oncology
physician Other
Freq % Freq % Freq % Freq % Freq %
Conversations
(n = 56)
0 18 32.14 18 32.14 5 8.93 21 37.5 42 73.21
1 23 41.07 22 39.29 51 91.07 35 62.5 15 26.79
2 7 12.50 9 16.07 0 0.00 0 0.00 0 0.00
3 4 7.14 4 7.14 0 0.00 0 0.00 0 0.00
>4 4 7.14 3 5.36 0 0.00 0 0.00 0 0.00
Minutes Minutes Minutes Minutes Minutes
Sum Doctors
Discussion Time -
n 56 55 55 56 56 55
Mean 21.02 66.73 63.89 52.14 14.64 220.02
Median 15 50 45 30 0 177.00
Min 0 0 0 0 0 15.00
Max 150 300 500 360 120 890.00
23
24
ITDM Descriptive Data
Regarding ITDM, the mean number of influential factors was 7.5 (SD =
2.78). Table 5 presents the level of influence for the 13 ITDM factors. The most
frequently endorsed items included doctor recommendations, treatment side-effects,
factors related to post-treatment disability, and physicians’ opinions.
Table 5. Frequencies of Influences on Treatment Decision-Making (n = 56)
Item Degree of Influence Freq. (%)
%, if
influential
Component 1: Treatment-specific Influences
Treatment side effects (91.07%)
Somewhat influential 14 (25%) 27.45
Moderately influential 11 (20) 21.57
Very influential 26 (46) 50.98
Factors related to post-treatment
disability (89.29%)
Somewhat influential 11 (20) 22.00
Moderately influential 13 (23) 26.00
Very influential 26 (46) 52.00
Length of recovery (73.21%)
Somewhat influential 15 (27) 36.59
Moderately influential 14 (25) 34.15
Very influential 12 (21) 29.27
Length of treatment (64.29%)
Somewhat influential 11 (20) 30.56
Moderately influential 14 (25) 38.89
Very influential 11 (20) 30.56
Component 2: Personal Commitments and Obligations
Meeting family responsibilities
(48.21%)
Somewhat influential 11 (20) 40.74
Moderately influential 11 (20) 40.74
Very influential 5 (9) 18.52
25
Table 5: Continued
Financial worries or concerns
(37.50%)
Somewhat influential 13 (23) 61.90
Moderately influential 5 (9) 23.81
Very influential 3 (5) 14.29
Treatment scheduling issues
(30.36%)
Somewhat influential 7 (13) 41.18
Moderately influential 8 (14) 47.06
Very influential 2 (4) 11.76
Travel plans (25%)
Somewhat influential 7 (13) 50.00%
Moderately influential 5 (9) 35.71%
Very influential 2 (4) 14.29%
Component 3: Influence of Medical Professionals
Doctor recommendations
(91.07%)
Somewhat influential 9 (16) 17.65%
Moderately influential 21 (38) 41.18%
Very influential 21 (38) 41.18%
Physicians’ opinions
+
(89.09%)
Somewhat influential 13 (23) 26.53%
Moderately influential 12 (21) 24.49%
Very influential 24 (43) 48.98%
Component 4: Career and Religious Influences
Career concerns or obligations
+
(32.73%)
Somewhat influential 9 (16) 50.00%
Moderately influential 6 (11) 33.33%
Very influential 3 (5) 16.67%
Religious beliefs or practices
(12.50%)
Somewhat influential 1 (2) 14.29%
Moderately influential 3 (5) 42.86%
Very influential 3 (5) 42.86%
26
Table 5: Continued
Item loaded < .30 on above Components
Family opinions (67.86%)
Somewhat influential 18 (32) 47.37%
Moderately influential 12 (21) 31.58%
Very influential 8 (14) 21.05%
+
n = 55; 1 participant did not respond to this item
Emotional Adjustment
Across the study’s three time periods, participants reported a significant
decrease in cancer-related stress, F(2,54) = 4.48, p = .02, and negative affect, F(2,54)
= 27.27, p<.01 (see Table 6). Overall, mean levels of PA and NA are comparable to
the scale’s norms, based on college students (PA: M = 32, SD = 7, NA: M = 19.5, SD
= 7) (Watson & Clark, 1988). Pre-treatment IES-R scores also represent the lower
end of the 0-12 point range (pre-treatment M = 2.25, SD = 1.84).
Table 6. Emotional Adjustment Variables: Reliabilities, Means and Standard Deviations (n = 56 )
Pre-Treatment 1 month
post-treatment
6 months
post-treatment
Possible
range Mean (SD) Mean (SD) Mean (SD)
IES-R Sum 0-12 .93 2.25
a
(1.84) .92 1.91
b
(1.70) .89 1.60
b
(1.42)
PANAS – PA 10-50 .87
+
31.48
a
(6.98) .88
++
32.63
a
(7.05) .91
++
33.57
b
(7.60)
PANAS – NA 10-50 .88 19.75
a
(7.07) .80
++
14.18
b
(5.12) .87 14.07
c
(4.53)
Note. On each line, means that do not have the same subscript differ at p<.05.
Due to missing data,
+
n = 53,
++
n = 55.
IES-R = Impact of Events Scale – Revised, PANAS = Positive and Negative Affect Schedule.
Predictors of Emotional Adjustment
As shown in Tables 7 and 8, there are no problems of multicollinearity
among the independent variables used in the regression equations (r’s < .40). With
respect to potential confounders, all significant correlations among the independent
27
variables are identified. A significant correlation occurred between the number of
days from diagnosis to start of treatment and PA at one and six months post-
treatment (r = -.27, -.35, respectively); ITDM and income (r = -.29), ITDM and
Gleason score (r = -.31), ITDM and IES-R six months post-treatment (r = .28); age
and Discussion Time with social support network (r = -.29), age and total
Discussion Time (r = -.30); and education and PPU (r = .37). These variables are
included in the appropriate regression analyses to control for their potential
confounding effects.
A primary goal of this study was to test the hypothesis that discussing
treatment options and considering influential treatment-related factors predicts
emotional adjustment following treatment. The key variables in this study include
six measures of post-treatment emotional adjustment (IES-R, PA, NA at one and
six months post-treatment) and Discussion Time, Conversations, and ITDM. For
each of the emotional adjustment variables, separate residualized multiple
regression analyses are conducted with each key predictor variable.
Table 7. Correlations between Predictor and Dependent Variables (n = 56)
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. PPU — -0.24 -0.09 -0.07 -0.18 -0.17 -0.11 -0.21 0.06 0.05 0.01 -0.02 -0.05 -0.05
2. ITDM — 0.13 0.12 0.08 0.22 0.18 0.21 0.09 0.22 0.07 0.28* 0.25 0.22
3. Discussion Time - Total — 0.99† 0.33* 0.56† 0.48† 0.50† -0.26 0.23 -0.26 -0.10 0.15 -0.20
4. Discussion Time - Social Support — 0.23 0.53† 0.45† 0.47† -0.25 0.20 -0.25 -0.10 0.14 -0.21
5. Discussion Time - Physicians — 0.50† 0.41† 0.47† -0.12 0.27* -0.12 -0.01 0.16 -0.01
6. Conversations - Total — 0.93† 0.75† -0.35† 0.35† -0.26* -0.12 0.28* -0.12
7. Conversations - Social Support — 0.44† -0.40† 0.34† -0.33† -0.16 0.23 -0.16
8. Conversations - Physicians — -0.12 0.22 -0.05 0.00 0.27* -0.01
9. IES-R, 1 month post-treatment — -0.36† 0.82† 0.63† -0.10 0.54†
10. PA, 1 month post-treatment — -0.39† -0.13 0.58† -0.25
11. NA, 1 month post-treatment — 0.56† -0.20 0.63†
12. IES-R, 6 months post-treatment — -0.17 0.60†
13. PA, 6 months post-treatment — -0.23
14. NA, 6 months post-treatment —
*p<.05, †p<.01
Note. PPU = Patient Perceived Understanding of treatment options, ITMD = Influences on Treatment Decision-Making, IES-R = Impact of Events Scale –
Revised, PA = Positive Affect, NA = Negative Affect
28
Table 8. Correlations between Demographic, Medical and Key Study Variables (n = 56)
Variables Age Income Education
Gleason
Score
Days between
Diagnosis and
Start of
Treatment
PPU 0.09 0.14 0.37** 0.00 0.02
ITDM -0.23 -0.29* -0.21 -0.31* -0.16
Discussion Time - Total -0.30* -0.17 -0.18 0.06 -0.06
Discussion Time - Social Support -0.29* -0.19 -0.20 0.05 -0.04
Discussion Time - Physicians -0.08 0.10 0.04 0.14 -0.14
Conversations - Total -0.06 -0.14 -0.10 -0.09 -0.18
Conversations - Social Support -0.07 -0.07 -0.10 -0.14 -0.21
Conversations - Physicians -0.02 -0.20 -0.06 0.02 -0.05
IES-R - Pre-treatment -0.24 -0.09 -0.07 0.04 -0.07
PA - Pre-treatment -0.06 0.06 -0.01 -0.08 -0.30*
NA - Pre-treatment -0.18 0.00 -0.21 -0.05 -0.09
IES-R - 1 month post-treatment -0.14 -0.01 -0.04 0.05 -0.07
PA - 1 month post-treatment -0.05 0.01 0.07 -0.13 -0.27*
NA - 1 month post-treatment -0.05 -0.04 -0.03 0.04 -0.02
IES-R - 6 months post-treatment 0.00 -0.09 -0.07 -0.04 0.20
PA - 6 months post-treatment -0.23 -0.01 -0.12 0.10 -0.35**
NA - 6 months post-treatment 0.03 0.02 -0.17 -0.17 0.04
*p<.05, **p<.01
Note. PPU = Patient perceived understanding of treatment information, ITDM = Influences on Treatment Decision-Making,
IES-R – Impact of Events Scale – Revised, PA = Positive Affect, NA = Negative Affect
29
30
Discussion Time as a predictor of emotional adjustment.
Beginning with Discussion Time summed across physicians and social
support members as the predictor of interest, I conducted a residualized hierarchical
linear regression analysis (Tables 9-11). The first block containing pre-treatment
IES-R, PA or NA was significant for all six criterion variables (p<.001), indicating
that pre-treatment levels of stress and mood significantly predict stress and mood one
and six-months following treatment. The second block contained three dummy-
coded variables for treatment type (hormone, radiation and surgery), and potential
confounders when necessary as identified above (age, number of days between
diagnosis and treatment, ITDM). For each of the six criterion variables, the second
block did not significantly predict additional variance, though the overall models
remained significant (p<.05). The third block contained total Discussion Time.
When all other variables were controlled, total Discussion Time significantly
explained 2.3% of the variance in IES-R one month following treatment and 5.9% of
the variance in NA one-month following treatment. The overall models for IES-R
and NA one-month following treatment were also significant, R
2
adj
= .70, F(6, 46) =
21.50, p < .001 and R
2
adj
= .38, F(6, 46) = 6.27, p < .001, respectively.
Sum Discussion Time exhibited a trend towards significance for NA at six
months following treatment, explaining an additional 4.5% of the variance (p = .07).
Sum Discussion Time did not significantly predict PA at one or six months post-
treatment, or IES-R at six months post-treatment.
Table 9. Hierarchical Multiple Regression Results for Discussion Time and Cancer-related Stress (IES-R)
1 month post-treatment IES-R 6 months post-treatment IES-R
Variable SE Beta SE Beta
Block 1: Pre-treatment measure of emotional adjustment
Pre-treatment IES-R 0.82** 0.08 0.77 0.54** 0.10 0.41
Adjusted R
2
(Block 1) = .69** Adjusted R
2
(Block 1) = .28**
Block 2: Potential confounding variables
Hormone treatment 0.03 0.34 0.12 -0.08 0.42 -0.22
Radiation treatment -0.11 0.35 -0.42 -0.23 0.44 -0.74
Surgical treatment -0.15 0.38 -0.54 -0.37* 0.48 -1.04
Age -0.06 0.02 -0.01 0.03 0.02 0.01
ITDM 0.13 0.06 0.06
R
2
change (Block 2) = .02 R
2
change (Block 2) = .11
Block 3: Discussion about treatment options
Discussion Time (total) -0.18* 0.00 0.00 -0.08 0.00 0.00
R
2
change (Block 3) = .02* R
2
change (Block 3) = .01
Overall Adjusted R
2
(overall) = .70** Adjusted R
2
(overall) = .32**
*p<.05, **p<.01
Note. Beta weights and SE values reflect results of overall model.
IES-R = Impact of Event Scale-Revised, ITDM = Influences to Treatment Decision-Making
31
Table 10. Hierarchical Multiple Regression Results for Discussion Time and Positive Affect (PA)
1 month post-treatment PA 6 months post-treatment PA
SE Beta SE Beta
Block 1: Pre-treatment measure of emotional adjustment
Pre-treatment PA 0.40** 0.14 0.41 0.41** 0.15 0.43
Adjusted R
2
(Block 1) = .23** Adjusted R
2
(Block 1) = .24**
Block 2: Potential confounding variables
Hormone treatment 0.10 2.31 1.38 -0.02 2.42 -0.32
Radiation treatment -0.14 2.53 -2.29 -0.05 2.65 -0.79
Surgical treatment 0.05 2.70 0.68 -0.02 2.83 -0.31
Age 0.02 0.13 0.02 -0.13 0.14 -0.13
Days from diagnosis to
treatment -0.16 0.00 0.00 -0.22 0.00 -0.01
R
2
change (Block 2) = .05 R
2
change (Block 2) = .07
Block 3: Discussion about treatment options
Discussion Time (total) 0.12 0.00 0.00 0.00 0.00 0.00
R
2
change (Block 3) = .01 R
2
change (Block 3) = .00
Overall Adjusted R
2
(overall) = .20** Adjusted R
2
(overall) = .19*
*p<.05, **p<.01
Note: Beta weights and SE values reflect results of overall model
32
Table 11. Hierarchical Multiple Regression Results for Discussion Time and Negative Affect (NA)
1 month post-treatment NA 6 months post-treatment NA
SE Beta SE Beta
Block 1: Pre-treatment measure of emotional adjustment
Pre-treatment NA 0.59** 0.09 0.44 0.57** 0.08 0.37
Adjusted R
2
(Block 1) = .30** Adjusted R
2
(Block 1) = .26**
Block 2: Potential confounding variables
Hormone treatment -0.11 1.47 -1.15 0.06 1.33 0.52
Radiation treatment -0.06 1.54 -0.67 -0.22 1.39 -2.28
Surgical treatment -0.39* 1.65 -4.14 -0.35* 1.49 -3.25
Age -0.07 0.08 -0.05 -0.01 0.08 0.00
R
2
change (Block 2) = .08 R
2
change (Block 2) = .10
Block 3: Discussion about treatment options
Discussion Time (total) -0.27* 0.00 0.00 -0.24 0.00 0.00
R
2
change (Block 3) = .06* R
2
change (Block 3) = .04
Overall Adjusted R
2
(overall) = .38** Adjusted R
2
(overall) = .34**
*p<.05, **p<.01
Note: Beta weights and SE values reflect results of overall model
33
34
When Discussion Time is separated into discussion with the social support
network and physicians, Discussion Time with social support significantly accounts
for 2.3% of the variance in IES-R one month post-treatment, and 5.6% of the
variance in NA one month following treatment, when all other variables are
controlled. The overall models for IES-R and NA one-month following treatment
are also significant, R
2
adj
= .70, F(6, 46) = 21.51, p < .001, and R
2
adj
= .38, F(6, 46) =
6.22, p < .001, respectively. When all other variables are controlled, Discussion
Time with physicians significantly accounts for 7.6% of the variance in PA one
month following treatment. The overall model is also significant, R
2
adj
= .30, F(6,
46) = 4.67, p = .001.
Conversation as a predictor of emotional adjustment.
The second set of analyses examined Conversations about treatment options
as a predictor of emotional adjustment following treatment. As in the previous
analyses, the first block contained the pre-treatment level of IES-R, PA or NA, the
second block contained three dummy-coded treatment variables (hormone, radiation,
surgery) and previously described potential confounders (ITDM, days between
diagnosis and treatment, entered when necessary). The third block contained total
Conversations with social support network and physicians.
As shown in Tables 12-14, total Conversations significantly predicts the three
measures of emotional adjustment one month following treatment. When all other
variables are controlled for, total Conversations significantly predicts less stress and
35
less negative affect one month following treatment, accounting for 4.8% and 6.5% of
the variance, respectively. Total Conversations also significantly predicts greater
positive affect one and six months after treatment, uniquely accounting for 9.4% and
6.3% of the variance, respectively. In addition to Conversations being a significant
predictor of IES-R, PA and NA one month following treatment, and PA six months
following treatment, the final models are also significant. For one month post-
treatment IES-R, R
2
adj
= .70, F(5, 50) = 26.19, p < .001, PA, R
2
adj
= .32, F(6, 47) =
5.18, p = .001, and NA, R
2
adj
= .40, F(5,50) = 8.17, p<.001. For six months post-
treatment PA, R
2
adj
= .28, F(6,47) = 4.51, p = .001.
When Conversations are separated into those with physicians and social
support, the full model including Conversations with physicians significantly
predicts PA one month following treatment, R
2
adj
= .28, F (6,47) = 4.40, p = .001 and
six months following treatment, R
2
adj
= .31, F (6,47) = 5.03, p<.001. When all other
variables are controlled, Conversations with physicians uniquely explains 5.6% and
8.9% of the variance in PA at one and six months following treatment. The full
model including Conversations with social support significantly predicts IES-R, R
2
adj
= .70, F (5,50) = 26.07, p<.001; PA, R
2
adj
= .30, F (6,47) = 4.82, p = .001, and NA,
R
2
adj
= .42, F (5,50) = 8.98, p<.001, one month following treatment. Conversations
with social support uniquely explains 4.7% (IES-R), 7.7% (PA), and 8.8% (NA) of
the variance in emotional adjustment one month following treatment.
Table 12. Hierarchical Multiple Regression Results for Conversations and Cancer-related Stress (IES-R)
1 month post-treatment IES-R 6 months post-treatment IES-R
Variable SE Beta SE Beta
Block 1: Pre-treatment measure of emotional adjustment
Pre-treatment IES-R 0.80** 0.07 0.73 0.47 0.09 0.36
Adjusted R
2
(Block 1) = .65** Adjusted R
2
(Block 1) = .23**
Block 2: Potential confounding variables
Hormone treatment 0.00 0.32 -0.01 -0.09 0.42 -0.26
Radiation treatment -0.08 0.33 -0.30 -0.23 0.43 -0.72
Surgical treatment -0.20 0.36 -0.68 -0.35* 0.47 -0.99
ITDM 0.18 0.06 0.09
R
2
change (Block 2) = .02 R
2
change (Block 2) = .10
Block 3: Discussion about treatment options
Conversations (total) -0.23** 0.02 -0.06 -0.13 0.03 -0.03
R
2
change (Block 3) = .05** R
2
change (Block 3) = .02
Overall Adjusted R
2
(overall) = .70** Adjusted R
2
(overall) = .29**
*p<.05, **p<.01
Note: Beta weights and SE values reflect results of overall model
36
Table 13. Hierarchical Multiple Regression Results for Conversations and Positive Affect (PA)
1 month post-treatment PA 6 months post-treatment PA
SE Beta SE Beta
Block 1: Pre-treatment measure of emotional adjustment
Pre-treatment PA 0.44** 0.12 0.44 0.45** 0.13 0.48
Adjusted R
2
(Block 1) = .23** Adjusted R
2
(Block 1) = .24**
Block 2: Potential confounding variables
Hormone treatment 0.09 2.02 1.25 -0.05 2.20 -0.70
Radiation treatment -0.10 2.20 -1.55 0.05 2.39 0.81
Surgical treatment 0.12 2.38 1.73 0.07 2.59 1.06
Days from Diagnosis to
treatment -0.07 0.00 0.00 -0.13 0.00 0.00
R
2
change (Block 2) = .06 R
2
change (Block 2) = .05
Block 3: Discussion about treatment options
Conversations (total) 0.33** 0.13 0.35 0.27* 0.14 0.31
R
2
change (Block 3) = .09** R
2
change (Block 3) = .06*
Overall Adjusted R
2
(overall) = .32** Adjusted R
2
(overall) = .28**
*p<.05, **p<.01
Note: Beta weights and SE values reflect results of overall model
37
Table 14. Hierarchical Multiple Regression Results for Conversations and Negative Affect (NA)
1 month post-treatment NA 6 months post-treatment NA
SE Beta SE Beta
Block 1: Pre-treatment measure of emotional adjustment
Pre-treatment NA 0.60** 0.08 0.44 0.58** 0.07 0.37
Adjusted R
2
(Block 1) = .30** Adjusted R
2
(Block 1) = .26**
Block 2: Potential confounding variables
Hormone treatment -0.09 1.37 -0.89 0.08 1.27 0.73
Radiation treatment -0.05 1.41 -0.53 -0.20 1.30 -2.02
Surgical treatment -0.37* 1.55 -3.83 -0.34* 1.43 -3.06
R
2
change (Block 2) = .07 R
2
change (Block 2) = .10*
Block 3: Discussion about treatment options
Conversations (total) -0.26* 0.09 -0.21 -0.16 0.08 -0.11
R
2
change (Block 3) = .07* R
2
change (Block 3) = .02
Overall Adjusted R
2
(overall) = .40** Adjusted R
2
(overall) = .34**
*p<.05, **p<.01
Note: Beta weights and SE values reflect results of overall model
38
39
ITDM as a predictor of emotional adjustment.
The final set of predictive analyses examined ITDM as a predictor of post-
treatment emotional adjustment. Again the first block contained pre-treatment IES-
R, PA or NA. This step was significant for all six criterion variables (p<.001). The
second block contained 3 dummy-coded variables for treatment type (hormone,
surgery, radiation), potential confounding variables identified above (income,
Gleason score, number of days between diagnosis and start of treatment, and sum
Conversations, entered as necessary). The third block contained ITDM. For all
criterion variables but NA at six months post-treatment, blocks two and three did not
significantly predict additional variance. For all six criterion variables, the overall
models retained significance (p<.01) but the variables entered into the second and
third blocks failed to significantly explain additional variance. In the one mentioned
exception, NA at six months post-treatment, the second block explained an
additional 14.9% of the variance,F(5,48) = 2.47, p<.001, however the addition of
ITDM was not significant.
PPU as a predictor of emotional adjustment
Originally, PPU was hypothesized to mediate the relationship between
discussion about treatment options and emotional adjustment. However, as seen in
Table 7, PPU demonstrated near-zero correlations with all post-treatment measures
of emotional adjustment. Consistent with the low correlations, in a final residualized
40
multiple regression analysis, PPU failed to significantly account for significant
variance in post-treatment emotional adjustment.
Exploratory Analyses
Analyses for non-normally distributed data.
The skewed distribution of Discussion Time, and subsequent limitations it
places on interpreting the results of the Discussion Time regression analysis,
motivated us to conduct exploratory analyses on the association between Discussion
Time and post-treatment emotional adjustment.
A common approach to non-normally distributed data is to transform the
values to their logarithm (Tabachnick & Fidel, 2001). A log transformation (lt) was
performed for Discussion Time as well as a new set of residualized multiple
regression analyses. As before, Block 1 contained the pre-treatment measure of
emotional adjustment and Block 2 contained potential confounders when necessary
(3 dummy-coded treatment variables for hormone, radiation and surgery, ITDM, and
days between diagnosis and treatment start). Discussion Time-lt was entered in
Block 3. Two differences in results occur when total Discussion-lt is entered in
Block 3 instead of total Discussion Time. First, total Discussion Time-lt becomes a
significant predictor of PA one-month following treatment, accounting for 6% of the
variance when all other variables are controlled. Second, total Discussion Time-lt
exhibits a trend towards significance when predicting IES-R one month following
41
treatment. This differs slightly from the results of the original analysis in which total
Discussion Time significantly predicts IES-R one month following treatment.
Analyses with Discussion Time-lt separated into minutes with physicians and
minutes with social support predict the same measures of emotional adjustment as
the original Discussion Time analyses. When all other variables are controlled,
Discussion Time-lt with a patient’s social network significantly explains 3.8% and
5.5% of the variance in IES-R and NA one-month following treatment, respectively.
Discussion Time-lt with physicians significantly explains 12.4% of the variance in
PA one-month following treatment, when all other variables are controlled.
In the second exploratory analysis of Discussion Time and emotional
adjustment I conducted a Yuen test. The Yuen test is a robust method for comparing
trimmed means that provides improvements over the independent t-test in power,
probability coverage and control over Type I errors (Wilcox, 2003). A trimmed
mean removes a proportion of the largest and smallest values of a variable, and then
calculates the mean of the remaining values. For the Yuen test, the default value of
trimming is 20%, which means 20% of the largest values and 20% of the smallest
values are omitted. Thus, the trimmed mean represents the mean of the remaining
60% of values.
For the Yuen test, each measure of Discussion Time (minutes with Doctors,
Social Support and total minutes) was separated into High and Low Discussion Time
groups, based on a median split. The Yuen test compared the 20% trimmed means
42
for each post-treatment measure of emotional adjustment among High and Low
Discussion Time groups. One month following treatment, the High Total Discussion
Time group reported significantly lower IES-R and NA than the Low Total
Discussion Time group (p = .01 and .006, respectively), and significantly higher PA
(p = .02). For Discussion Time with social support alone, the High Discussion Time
group reported significantly lower IES-R and NA than the Low Discussion Time
group one month-following treatment (p = .002 and .01, respectively).
Possible moderating variables.
During data analysis, the patterns of an individual’s stress and mood were
examined across the three time points. The data illustrate a few distinct response
patterns. One pattern shows a sequential decrease in stress across three points. A
second pattern resembles a V-pattern; a decrease from pre-treatment to one month
post-treatment, followed by an increase in stress between one and six months post-
treatment. A third pattern appears as a cluster of individuals who report consistently
low levels of stress across the study time periods. These diverse patterns suggest the
existence of a moderating variable.
Two individual difference variables were measured in the larger POP study,
Optimism and Need for Cognition (NFC).
2
In response to a growing body of
literature reporting mediating and moderating relationships between optimism and
stress (Chang, 1998; Chang & Sanna, 2003; Steginga & Occhipinti, 2006) I
2
POP measured optimism with the LOT-R (Scheier, Carver & Bridges, 1994), a validated measure
with a reported alpha of .78. The NFC scale was developed by Cacioppo, Petty & Kao (1984) and is
reported to have strong internal consistency ( > .90).
43
examined whether optimism moderated the relationship between Discussion
Time/Conversations and emotional adjustment. NFC, the second potential
moderator, represents a person’s tendency to engage in and enjoy effortful thinking
(Cacioppo, Petty, Feinstein & Jarvis, 1996). Perhaps a patient’s preference for
situations that require a great deal of thinking moderates their amount of discussions
about treatment options. I hypothesized that Optimism or NFC may moderate the
relationship between Discussion Time or Conversations and post-treatment
emotional adjustment.
Tests of moderation were conducted with residualized multiple regression
analyses (Aiken & West, 1991; Holmbeck, 1997). For each analysis, the first block
contained the pre-treatment measure of emotional adjustment. The second block
contained three dummy-coded variables for treatment type (hormone, surgery,
radiation), potential confounders identified with a correlations matrix (age, income,
education, ITDM, number of days between diagnosis and start of treatment). The
third block contained the centered main effect variables (Discussion Time or
Conversations, and NFC or LOT). The final block contained the cross product of
centered predictor and moderating variables (e.g. centered Discussion Time x
centered NFC). The moderation hypotheses for Optimism and NFC were not
supported, as neither Optimism nor NFC accounted for a significant interaction
between discussions about treatment decisions and levels of stress or mood following
treatment (p’s
F-change
> .05).
44
Chapter 4: Discussion
Findings from this study suggest that having discussions prior to beginning
treatment for prostate cancer significantly contributes to reductions in stress and
improvements in mood one month following treatment. Depending on with whom
patients talk, Discussion Time and Conversation generate distinct patterns of results.
Discussion Time with participant’s social support network significantly predict less
stress and less negative affect one month following treatment while Discussion Time
with physicians predict greater positive affect one month following treatment.
Similarly, Conversations with social support members significantly predict stress,
negative and positive mood one month following treatment and Conversations with
the medical team significantly predict positive affect at one and six months following
treatment. These results suggest that the type of person with whom discussion
occurs (i.e. social support versus physicians) predicts different aspects of emotional
adjustment. That is, patient involvement with both his medical team and social
network is associated with a combined pattern of adjustment that is not achieved by
either component alone.
Since stress and negative affect are conceptually related constructs that
reflect feelings of distress and fear, it is not surprising that the same variable predicts
both adjustment measures. The results are also consistent with the models of
cognitive processing (Creamer et al., 1992; Lepore, Ragan & Jones, 2000) that
predict decreases in stress from but do not discuss changes in positive affect. The
45
fact that Discussion with physicians uniquely predicts positive affect raises the
question of why talking with doctors does not predict decreases in stress but instead
contributes to an increase in positive feelings.
The results suggest that something happens during discussions with
physicians that relates to patients feeling more active and engaged one month
following treatment. Notably, pre-treatment levels of PA were not correlated with
Discussion Time or Conversations with physicians (r’s = .002, -.01, respectively)
which indicates that the association at one month following treatment is not a
residual effect of men with higher initial PA engaging their doctors in greater
discussion. Nor is it the case that greater discussion time or conversations with
doctors increases patient understanding (r’s = -.18, -.21, respectively). Perhaps
greater discussion with physicians is associated with feeling more empowered or
aligned with one’s treatment team and these feelings develop into patients reporting
greater feelings of activity and engagement in their lives.
A second interpretation is that discussions with physicians do not present
opportunities for cognitive processing in the same way as discussions with a
patient’s social support network. This could be due to differences in the content of
conversations with physicians versus conversations with one’s social network. If
cognitive processing is about integrating information, perhaps discussions with
physicians provide opportunities to obtain information rather than process it, and
46
therefore a measure of conversations is not associated with decreases in stress or
negative mood.
The results of this study raise several new questions. First, are discussions
with social support and physicians proxy measures for greater social support and
better patient-provider relations? Including a formal measure of social support and
patient-provider relations could help address this question. Second, Discussion Time
failed to predict emotional adjustment at six months following treatment, which
raises the question of how long the effects of pre-treatment discussions last. Perhaps
discussion-based processing is associated with a short-term benefit that is detectable
one month following treatment, but does not persist six months following treatment.
In order to test extended effects of pre-treatment processing, data for ongoing
discussions and processing would be necessary. Data on ongoing discussions could
clarify the association between continued prostate cancer-specific discussions and
emotional adjustment following treatment for prostate cancer.
Since this study only asked participants whom they included in the treatment
decision-making process, how often they spoke with others and for how long, data
on the content of conversations are unavailable. It would also be interesting to
examine the level of support or constraint patients felt during conversations with
their doctors and social network. Such data could inform alternate hypotheses about
conversation topic or perceived support mediating the relationship between
discussions and post-treatment emotional adjustment. Data about conversation
47
content could also help distinguish cognitive processing from ruminating, which is
typically associated with negative mood and stress (Nolen-Hoeksema, 1991, 2000).
Emotional Adjustment over Time
Descriptively, it is notable that participants did not report high mean levels of
distress following their prostate cancer diagnosis. This is similar to findings of other
studies with prostate cancer patients (Roesch et al., 2005; Thornton et al., 2004).
Further, patients and physicians may find it encouraging that stress and mood
significantly improved during the six months following treatment, although negative
and positive mood demonstrated different rates of improvement. Stress and negative
affect significantly decreased from pre-treatment to one-month after treatment while
a significant increase in positive affect occurred only between pre-treatment and six
months post-treatment.
Influential Factors during Treatment Decision-Making
Contrary to the study hypothesis, the number of factors a patient considered
to be influential during treatment decision-making did not significantly predict stress
level or mood following treatment. It was assumed that considering an influential
factor would provide an opportunity for cognitive processing by patients, but this
may not be so. The current study did not ask how much thought patients gave to
each factor, only the degree of influence it had on their decision. Thus instead of
indicating cognitive processing, a better conceptualization of the ITDM scale may be
48
as a checklist of factors. These factors may help patients decide on a treatment, but
not be associated with stress or emotional adjustment.
Despite the predictive failure of influential factors, the data add to recent
findings on factors prostate cancer patients consider during treatment decision-
making (Capirci et al., 2005; Powel & Clark, 2005). In the current study
approximately 90% of participants considered treatment side-effects and physician’s
recommendations and opinions to influence their treatment decision. The patient
literature often describes the importance of these factors, a recommendation the
current data appear to support.
The alternative hypothesis that discussions would be associated with a
patient’s perceived understanding of treatment information and post-treatment
emotional adjustment was not supported. Despite the null finding, it would be
premature to conclude that patient understanding is unrelated to post-treatment stress
and mood. In this study, patient perceived understanding and education were
significantly correlated, r(56) = .37, p = .005. Participants were highly educated and
also reported a mid- to high level of understanding treatment options. Even men
who reported the least amount of understanding still fell within the middle range of
understanding, with no one reporting poor understanding. With this highly educated
population, the range of patient understanding may have been restricted, and thus
decreased the power for patient understanding to predict emotional adjustment
following treatment.
49
Study Limitations and Suggestions
This study provides preliminary support for discussing treatment options and
emotional adjustment following treatment. However, several limitations must be
acknowledged. Despite the significant association, the study cannot conclude that
talking is responsible for the changes in emotional adjustment because of the
possibility of a third variable that accounts for both increases in pre-treatment
discussions and emotional adjustment. In future studies, it would be helpful to
measure extraversion as a possible third variable that is associated with greater
amounts of talking and greater emotional adjustment.
A second limitation is the homogeneity of participants. The sample
represents primarily white, married men with high socioeconomic status living in the
Los Angeles area. Given that African Americans have the highest incidence of
prostate cancer (ACS, 2006), it is important to consider how these findings might
generalize to a more heterogeneous population.
The Discussion Time regression analyses must be interpreted with caution
due to violations of normality and homoscedasticity. The attempt to address this
limitation by performing a log transformation of Discussion Time found the
transformed data generated similar results to the original data.
Participant recruitment and retention presented one of the most challenging
limitations. Overall, POP recruited 39% of eligible patients, and retained 57% of
consented patients across three time periods. Regarding recruitment, it is
50
encouraging that no significant differences were found between men who declined
participation and study participants, although a comparison could only be made with
the 14 men who completed the study refusal questionnaire. Challenges in
recruitment and retention generated a smaller sample size than originally planned.
Consequently, the power to detect a medium effect for the majority of multiple
regression analyses was low (1- .50) (Faul & Erdfelder, 1992).
In addition to collecting data on the content of conversations, it would be
helpful to measure Conversations with an open-ended response. In this study, the
high frequency of “4 or more” conversations with one’s spouse or partner suggests
data were lost by forcing responses into categories. It is possible that an open-ended
response to Conversations would yield a skewed distribution however, the
distribution would represent a more complete range of responses, rather than an
artificially constricted range.
Despite its limitations, this study has several strengths and contributions.
Even with a homogeneous sample, several significant associations were
demonstrated. This is a notable, as homogeneous samples may yield a restricted
range of data and thus more challenges in detecting significant associations. This
study also provides longitudinal data across three time points, capturing experiences
of men shortly after being diagnosed with prostate cancer to six months following
treatment completion. When examined together, the results of the regression
analyses and Yuen test suggest less stress and negative mood, and greater positive
51
mood one-month following treatment among participants who engaged in greater
amounts of discussion with their social network and medical team. These data may
provide useful considerations to patients and physicians about factors that influence
patient treatment decisions. Additionally, patients and physicians may be
encouraged to discuss their options with others, not only to facilitate the decision-
making process but for the emotional benefits reported by patients following
treatment.
52
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57
Appendix: Study Measures
58
General Instructions (printed on the first page of the questionnaire packet):
In this questionnaire, we are interested in your experiences as a prostate cancer patient.
Answer every question to the best of your ability. Whenever you need more room, write in
the margins or wherever you can find room. Remember, there are no right or wrong
answers, only your best answer. Please note that time frames may vary in different sections
of the questionnaire.
Demographics
1. Please check the highest level of education you have completed. (mark only one)
__ Grade school (1-8 yrs)
__ Some high school (9-11 yrs )
__ High School Graduate or GED
__ Vocational or training school after high school graduation
__ Some college
__ Associate Degree earned (AA or AD)
__ Bachelors Degree earned (BA or BS)
__ Some graduate or professional school after college graduation
__ Masters Degree earned (MA, MS, MBA, MSW, etc)
__ Doctoral Degree earned (MD, PhD, JD, etc )
2. Please check one income range that best describes your family's total income before taxes
for the previous year, including salaries, wages, tips, social security, and any other income.
__ Under $20,000 __ $100,001- $120,000
__ $20,001 -$40,000 __ $120,001 -$140,000
__ $40,001 -$60,000 __ $140,001- $160,000
__ $60,001 -$80,000 __ $160,001- $180,000
__ $80,001 -$100,000 __ Over $180,000
3. What is your height?
4. What is your weight?
5. Approximately how long did it take for you to initially contact a doctor for treatment once
you learned of your prostate cancer diagnosis?
_______Days _______Weeks
59
Refusal Questionnaire
Study Investigator says:
With respect to the quality of your life during the time since your prostate cancer
treatment…
Not at
all
A little
bit/
Slightly
Somewhat
Moderate
Quite a
bit/
Very
likely
Very
much/
Extremely
How much would you say
having prostate cancer has
affected your quality of
life?
1 2 3 4 5
To what extent did (do)
you have control in
deciding your prostate
cancer treatment?
1 2 3 4 5
How confident are you
that your prostate cancer
treatment is the best
choice for you?
1 2 3 4 5
How likely is it that the
treatment you had (will
have) for your prostate
cancer will cure your
cancer altogether?
1 2 3 4 5
How likely is it that the
treatment you had (will
have) for your prostate
cancer will result in
additional treatments over
time?
1 2 3 4 5
How likely is it that the
treatment you had (will
have) for your prostate
cancer will result in
recurrence of cancer?
1 2 3 4 5
Overall, how stressful did
(are) you find(ing) the
treatment decision making
process?
1 2 3 4 5
60
Patient Perceived Understanding of Treatment Information
The following questions are regarding your interaction with your medical team (if you have
mainly interacted with only one person (such as your doctor), please consider that person
when answering these questions). For each question, please circle the number that best
represents your current experience with prostate cancer and its treatment. You may circle
any one of the numbers (from 1 to 7) on each scale that best represents the strength of your
feelings or opinions.
1. How well do you understand the information you have acquired or received?
1 2 3 4 5 6 7
No under-
standing at
all
Some under-
standing
Complete
under-
standing
2. How well do you understand the possible advantages and disadvantages that prostate
cancer treatments may cause?
1 2 3 4 5 6 7
Don’t
understand
at all
Somewhat
understand
Completely
understand
3. Overall, how prepared do you feel about what to expect with regard to possible changes to
your health and lifestyle after treatment?
1 2 3 4 5 6 7
Not at all
prepared
Somewhat
prepared
Completely
prepared
61
Measures of Discussion Time and Conversations
1. With respect to deciding on your treatment for prostate cancer, which of the following
doctors did you include in this process? (mark all that apply)
Circle the number of visits
you had with this doctor
concerning your prostate
cancer.
Approximately how much
time did you spend
discussing your treatment
options?
__ Primary care physician 1 2 3 4 or more About ____ minutes
__ Oncologist 1 2 3 4 or more About ____ minutes
__ Urologist 1 2 3 4 or more About ____ minutes
__ Radiation oncology
physician
1 2 3 4 or more About ____ minutes
__ Other 1 2 3 4 or more About ____ minutes
2. With respect to deciding on your treatment for prostate cancer, which of the following
people did you include in this process? (mark all that apply)
Circle the number of visits
you had with this doctor
concerning your prostate
cancer.
Approximately how much
time did you spend
discussing your treatment
options?
__ Spouse or partner 1 2 3 4 or more About ____ minutes
__ Other family
member(s)
1 2 3 4 or more About ____ minutes
__ Another prostate patient 1 2 3 4 or more About ____ minutes
__ Close friend 1 2 3 4 or more About ____ minutes
__ Religious advisor 1 2 3 4 or more About ____ minutes
__ Other 1 2 3 4 or more About ____ minutes
62
Influences on Treatment Decision Making
Various factors can influence one's medical decisions. For each item below, please indicate
the extent to which each matter played a role in your deciding what treatment was best for
you. Please feel free to describe further your reasons in the space below.
Circle one number on each line
Not
influential
Somewhat
influential
Moderately
influential
Very
influential
1. Career concerns or
obligations
1 2 3 4
2. Doctor recommendations 1 2 3 4
3. Factors related to post-
treatment disability
1 2 3 4
4. Family opinions 1 2 3 4
5. Financial worries or
concerns
1 2 3 4
6. Length of recovery 1 2 3 4
7. Length of treatment 1 2 3 4
8. Meeting family
responsibilities
1 2 3 4
9. Physicians opinions 1 2 3 4
10. Religious beliefs or
practices
1 2 3 4
11. Travel plans 1 2 3 4
12. Treatment scheduling
issues
1 2 3 4
13. Treatment side effects 1 2 3 4
Additional matters or further comments:
63
Stress (IES-R)
The following is a list of difficulties people sometimes have after stressful life events. Please
read each item, and then indicate how distressing each difficulty has been for you DURING
THE PAST 7 DAYS with respect to your prostate cancer.
(circle one number on each line)
How much were you distressed
or bothered by these difficulties?
Not at
all
A little
bit
Moderate Quite
a bit
Extreme
1. Any reminder brought back
feelings about it
0 1 2 3 4
2. I had trouble staying asleep 0 1 2 3 4
3. Other things kept making me
think about it
0 1 2 3 4
4. I felt irritable and angry 0 1 2 3 4
5. I avoided letting myself get
upset when I thought about it
or was reminded of it
0 1 2 3 4
6. I thought about it when I
didn't mean to
0 1 2 3 4
7. I felt as if it hadn't happened
or wasn't real
0 1 2 3 4
8. I stayed away from
reminders of it
0 1 2 3 4
9. Pictures about it popped into
my mind
0 1 2 3 4
10. I was jumpy and easily
distracted
0 1 2 3 4
11. I tried not to think about it 0 1 2 3 4
12. I was aware that I still had a
lot of feelings about it, but I
didn't deal with them
0 1 2 3 4
13. My feelings about it were
kind of numb
0 1 2 3 4
14. I found myself acting or
feeling like I was back at that
time
0 1 2 3 4
15. I had trouble falling asleep 0 1 2 3 4
16. I had waves of strong
feelings about it
0 1 2 3 4
17. I tried to remove it from my
memory
0 1 2 3 4
18. I had trouble concentrating 0 1 2 3 4
64
19. Reminders of it caused me to
have physical reactions, such
as sweating, trouble
breathing, nausea, or a
pounding heart
0 1 2 3 4
20. I had dreams about it 0 1 2 3 4
21. I felt watchful and on guard 0 1 2 3 4
22. I tried not to think about it 0 1 2 3 4
Mood (PANAS)
This scale consists of a number of words that describe different feelings and emotions. Read
each item and then mark the appropriate answer in the space next to that word. Indicate to
what extent you have felt this way SINCE YOUR PROSTATE CANCER DIAGNOSIS.
Very
slightly or
not at all
A little Moderately Quite
a bit
Extremely
1. Interested 1 2 3 4 5
2. Distressed 1 2 3 4 5
3. Excited 1 2 3 4 5
4. Upset 1 2 3 4 5
5. Strong 1 2 3 4 5
6. Guilty 1 2 3 4 5
7. Scared 1 2 3 4 5
8. Hostile 1 2 3 4 5
9. Enthusiastic 1 2 3 4 5
10. Proud 1 2 3 4 5
11. Irritable 1 2 3 4 5
12. Alert 1 2 3 4 5
13. Ashamed 1 2 3 4 5
14. Inspired 1 2 3 4 5
15. Nervous 1 2 3 4 5
16. Determined 1 2 3 4 5
17. Attentive 1 2 3 4 5
18. Jittery 1 2 3 4 5
19. Active 1 2 3 4 5
20. Afraid 1 2 3 4 5

Abstract (if available)

Abstract Men with prostate cancer are often encouraged to be involved in treatment decision-making. Talking about treatment options may help men decide on a treatment and benefit post-treatment emotional adjustment. This prospective, longitudinal, questionnaire-based study (n=56) examines relationships among treatment-specific discussions with physicians and social network, factors that influence patient's treatment decision, and post-treatment stress and affect. Patients who engaged in more discussion of their treatment options reported significantly lower stress, less negative affect and greater positive affect than patients who engaged in less conversation. Additionally, discussions with social support members significantly predicted decreases in stress and negative affect one-month following treatment, while discussions with physicians predicted increases in positive affect. This study suggests pre-treatment discussions may benefit emotional adjustment and that discussions with physicians and social networks may be associated with an overall pattern of adjustment neither achieves alone.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Christie, Kysa (author)

Core Title Discussion during treatment decision-making predicts emotional adjustment in prostate cancer patients

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 11/30/2006

Defense Date 08/22/2006

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag OAI-PMH Harvest,prostate cancer,Quality of life,treatment decision-making

Language English

Advisor Meyerowitz, Beth E. (committee chair), Davison, Gerald C. (committee member), John, Richard S. (committee member)

Creator Email kchristi@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m204

Unique identifier UC1454779

Identifier etd-Christie-20061130 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-156705 (legacy record id),usctheses-m204 (legacy record id)

Legacy Identifier etd-Christie-20061130.pdf

Dmrecord 156705

Document Type Thesis

Rights Christie, Kysa

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu