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Predictors of change in unmet
supportive care needs in cancer
Author
McDowell, Michelle, Occhipinti, Stefano, Ferguson, M., Dunn, J., Chambers, Suzanne
Published
2010
Journal Title
Psycho-Oncology
DOI
https://doi.org/10.1002/pon.1604
Copyright Statement
Copyright 2010 John Wiley & Sons, Ltd. This is the pre-peer reviewed version of the following article:
Predictors of change in unmet supportive care needs in cancer, Psycho-Oncology, 19(5):508-516,
which has been published in final form at http://dx.doi.org/10.1002/pon.1604
Downloaded from
http://hdl.handle.net/10072/35274
1
SHORT TITLE: Predictors of change in unmet supportive care needs
Predictors of Change in Unmet Supportive Care Needs in Cancer.
McDowell, M. E., Occhipinti, S., Ferguson, M., Dunn, J., & Chambers, S. K.
Michelle McDowell, BPsych (Hons), School of Psychology, Griffith University, Brisbane
Stefano Occhipinti, PhD, School of Psychology, Griffith University, Brisbane
Megan Ferguson, BSc (Hons, Psych), Viertel Centre for Research in Cancer Control, Cancer
Council Queensland
Jeff Dunn, PhD, Chief Executive Officer, Cancer Council Queensland; School of Social
Science, University of Queensland; School of Public Health, Tropical Medicine and
Rehabilitation Sciences, James Cook University
Suzanne K. Chambers, PhD, General Manager Programs and Research, Viertel Centre for
Research in Cancer Control, Cancer Council Queensland; School of Psychology, Griffith
University.
Keywords: Cancer, Oncology, Supportive Care Needs
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Abstract
Objective: Patient Reported Outcome (PRO) assessments can assist health professionals to
tailor their health practices to the individual needs of patients and improve patient care over
time. The present study assessed prospective predictors of unmet supportive care needs in
cancer patients over a six month period.
Methods: Participants were recruited from a regional cancer treatment centre in Australia and
completed the Supportive Care Needs Survey (SCNS) at recruitment (n = 439; 61.4%
response rate) and six months follow-up (n = 396). Hierarchical logistic regression was used
to identify predictors of change unmet needs across each supportive care domain. Predictor
variables were socio-demographic, treatment and psychosocial factors including depression,
anxiety, social support, and patient satisfaction.
Results: Unmet needs were reported by approximately two thirds of patients at baseline and
half of patients at six months follow-up. Having unmet needs at baseline was the strongest
predictor of unmet needs at six months. Longer time since diagnosis was a consistent
predictor of greater unmet needs, associated with change in physical/daily living,
psychological and health system and information unmet needs over time. By contrast, a
complex relationship was found in that patient satisfaction, psychosocial and treatment
characteristics predicted higher needs in some domains and lower needs in others.
Conclusions: Unmet supportive care needs persist over time and psychological needs may
emerge later in the illness continuum. Interventions to meet the needs of longer term cancer
survivors are needed and should closely articulate with reported supportive care needs.
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Predictors of Change in Unmet Supportive Care Needs in Cancer
Patient Reported Outcome (PRO) assessments are being used increasingly to assess
areas of care where patients feel that they continue to need support following their cancer [1,
2]. For example, the Supportive Care Needs Survey [3], the Cancer Survivors Unmet Needs
measure [4], and the Cancer Patient Needs Questionnaire [5] are PRO assessments designed
for patients to report the extent to which they have unmet supportive care needs across
physical, psychological and informational domains. Patient report measures have received
considerable attention for their potential to improve healthcare practice, particularly given the
low congruence between healthcare needs identified as important by health professionals
compared to patients [2, 6]. For example, Snyder et al. [2] found that patients identify
information about treatment and care coordination as the most important aspects of their
healthcare whereas health professionals nominate symptom-related issues (e.g., pain). Thus,
it is proposed that PRO assessments may help health professionals to tailor their professional
practices more effectively to the individual needs of patients.
As well, identifying the characteristics of patients who are more likely to report unmet
needs may allow better targeting of services. To date, younger age [7-11], living in rural
areas [8, 12], later stage disease [7, 12, 13], type of cancer treatment [8, 9, 12], time since
diagnosis [11, 14] and physical or mental quality of life [13, 15] have been associated with
greater unmet needs. However, while these predictors provide some insight into the patients
at risk of higher unmet supportive care needs, many of these factors are not amenable to
change and so cannot be targeted by support interventions. There is some evidence that
depression, anxiety and psychological distress are associated with patients reporting greater
unmet needs [13, 16]. However, it is not clear how these factors relate to different needs
domains. For example, although Snyder et al. [15] reported that better emotional functioning
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was associated with fewer psychological, patient care and support, and health system and
information needs, Bredart et al. [17] found that lower emotional functioning was related to
higher satisfaction with provision of information, organisation of care, and the technical and
interpersonal skills of doctors. Thus, while psychological distress may increase patient need
for information and support it may also act as a motivator for patients to mobilise support.
Specifically, Lepore, Glaser and Roberts [18] found that for women with breast
cancer, early negative affect predicted subsequent received support suggesting that cancer
patients who are more distressed receive and utilise greater social support. Accordingly,
patients who perceive emotional, instrumental or informational support from health
professionals, family members and friends report better adjustment and health-related quality
of life [19-21]. However, despite considerable research suggesting that social support is
related to positive adjustment to cancer, Beesley et al. [12] found that social support was not
associated with unmet needs. As this is the only study examining the association between
social support and unmet needs further exploration of this relationship is needed.
Further, if patients are not satisfied with their medical care they may be more likely to
report unmet patient care, health system and information needs. An aspect of medical care
that patients want most improvement from health professionals is the provision of information
[17] and patients who report barriers to information access experience lower emotional,
functional and social well-being [22]. The change in care and support following treatment
completion suggests that patient satisfaction and social support may be important predictors
of unmet supportive care needs over time. At the conclusion of treatment, medical care and
support may decrease owing to the belief that the worst is over and that the patient does not
require ongoing assistance [23]. Patients indicate some discomfort requesting information
from medical providers as time since diagnosis increases and instead seek information from
popular media [24]. Breast cancer patients report a significant decrease in the helpfulness of
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emotional, informational and decision-making support from family, friends and health
providers within the first year of diagnosis [19] and patient satisfaction with healthcare
decreases over time [25]. As well, there is some evidence that perceptions of higher
continuity of care are associated with lower supportive care needs [26]. The potential for
social support and patient satisfaction to predict unmet supportive care needs over time has
yet to be explored.
The present study examined the prevalence and prospective predictors of unmet
supportive care needs in cancer patients over a six month time period. In addition to patient,
cancer and treatment characteristics, the present study explored the contribution of
psychosocial predictors that are amenable to change and can be targeted by healthcare
interventions. It was predicted that after controlling for socio-demographic, cancer and
treatment characteristics and quality-of life factors, psychological (anxiety, depression and
distress), patient satisfaction and social support factors would predict unmet supportive care
needs prospectively.
Method
Participants
Participant demographics and study protocols have been reported in detail elsewhere
[27]. Patients were eligible if they were over the age of 20 years; had been diagnosed with a
solid tumour or haematological cancer; presented for diagnosis or treatment to a regional
cancer treatment centre in Queensland, Australia, between January 2004 and June 2006; and
had presented to the cancer centre within the six months prior to the commencement of the
study. Patients with prostate cancer were excluded from the present study owing to a preexisting study.
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Of the 439 respondents (61% response rate) who consented to participate in the study
at time 1, 59% were female and the majority were born in Australia (83.8%). The age of
participants ranged between 22 and 89 years (M = 59.23, SD = 12.00). The average time
since diagnosis was 87.48 weeks (ranging from 1-1057 weeks) at the time of recruitment.
The majority of patients (78.6%) had completed treatment at the time of the interview; 76.7%
had surgery, 64.1% chemotherapy, 74.4% radiation and 21% hormone therapy. The average
time since treatment completion was 49.11 weeks (ranging from 0-223.43 weeks). Over 90%
of participants (n = 396) who participated in the first assessment completed the six month
assessment. However, 43 of these had commenced additional treatment and these patients
were excluded from later longitudinal analyses only. There were no differences between the
demographic characteristics of participants who completed both assessment points and those
who completed only the first assessment.
Procedure
A brief computer-assisted telephone interview (CATI) was used to assess sociodemographic and medical characteristics at baseline and at six months follow-up including
information about cancer diagnoses and treatment and health care utilisation. Following each
CATI, patients completed a self-report questionnaire assessing psychosocial factors including
supportive care needs, anxiety and depression, patient satisfaction, quality of life and social
support. The self-report questionnaire was mailed to participants following the CATI.
Measures
Predictor Variables
Socio-demographic and medical variables. Age, gender, time since diagnosis,
whether the patient had finished treatment, type of treatment received (chemotherapy,
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radiation, surgery or hormone therapy) and driving distance from hospital were assessed in
the interview.
Health-Related Quality of Life. The Medical Outcomes Study Health Survey ShortForm [SF-36v2;28] is a well-validated, reliable generic measure of health-related quality of
life assessing eight domains of physical and mental quality of life including: physical
functioning, role-physical, bodily pain, general health, vitality, social functioning, roleemotional, and mental health. The present study utilised the Physical and Mental Component
Scale scores to examine physical and mental health dimensions [29]. Higher scale scores
indicate better health (ranging from 0 worst health to 100 best health).
Depression and Anxiety. The Hospital Anxiety and Depression Scale [HADS;30]
assesses depression (7 items) and anxiety (7 items) using 4-point Likert scales measuring the
frequency with which a respondent has experienced different feelings within the past week
(e.g., I feel tense or ‘wound up’). The anxiety and depression scales range from 0 (no
distress) to 21 (high distress) with scores greater than 7 indicative of a case at risk of
psychological distress.
General Distress. The Distress Thermometer (DT) is a brief screening tool assessing
psychological distress in cancer patients [31, 32]. The DT is a single-item 11-point scale
ranging from 0 (no distress) to 10 (extreme distress) and respondents are instructed to circle
the number that best describes how much distress they have been experiencing within the past
week. A cut-off score of > 4 is indicative of psychological distress and has been shown to be
comparable with the HADS as a measure for identifying distressed cancer patients and is
sensitive to respondents who do not meet anxiety or depression caseness [31].
Social Support. The ENRICHD Social Support Instrument [33] was used to measure
patient social support. Five items assess functional and emotional support utilising a fivepoint scale ranging from 1 (none of the time) to 5 (all of the time) with higher scores
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indicating greater availability of social support (e.g., is there someone available to you whom
you can count on to listen to you when you need to talk). The scale has been used as a
prospective predictor of healthcare experience in previous research [34] and demonstrates
good internal consistency in the present study (α = .93 at time 1 and α = .92 at time 2).
Patient Satisfaction. A modified version of the Patient Satisfaction Questionnaire
Short Form [PSQ-18;35] was used to assess patient satisfaction with healthcare. A principal
components analysis of the PSQ-18 revealed a single factor with an eigenvalue greater than
one accounting for more than 84% of the variance. The four items that loaded above .70 on
this factor were incorporated into a patient satisfaction scale, representing a general
summation of patient satisfaction items (e.g., the medical care I have been receiving is just
about perfect; when I go for medical care, they are careful to check everything when treating
and examining me; those who provide my medical care sometimes hurry too much when they
treat me; I have some doubts abut the ability of the doctors who treat me). Items were rated
on a scale ranging from 1 (strongly agree) to 5 (strongly disagree) with relevant items
reversed scored so that higher scores indicated greater patient satisfaction with healthcare.
The modified patient satisfaction scale showed good reliability (α = .82 at time 1 and α = .75
at time 2).
Outcome Variable (baseline and six month follow-up)
Supportive Care Needs. The Supportive Care Needs Survey Short Form (SCNSSF34) assessed supportive care needs across five domains: physical/daily living (5 items),
psychological (5 items), patient care and support (10 items), sexuality (3 items) and health
system and information needs (11 items). The SCNS-SF34 is a validated assessment of
supportive care needs and has been used extensively to assess supportive care needs in cancer
populations [3] and has been shown to be psychometrically sound [1, 8]. In the present study,
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Cronbach’s alpha demonstrated good internal consistency for all five domains ranging from α
= .87 to α = .96. Patients are asked to indicate their level of need for help for each item over
the past month. Needs are measured on a five-point scale ranging from no need-not
applicable, no need-satisfied, low need, moderate need or high need. Individual needs items
are dichotomised into no-to-low need and moderate-to-high need to assess the proportion of
patients reporting individual unmet needs [9, 12] and summated scale scores are standardised
to rank the prevalence of each need domain (ranging from 0-100).
Statistical Analysis
To examine predictors of unmet supportive care needs patients were categorised as
having some need if they reported having at least one low-to-high need in a domain, and no
need if they did not report any need to all items in a domain [3]. Hierarchical logistic
regression was used to identify predictors of change in unmet need across each supportive
care domain, separately. After controlling for time 1 supportive care needs, patient and
medical characteristics were entered as predictors prior to psychosocial predictors. As
treatment completion was a predictor in the current study, patients who reported starting a
new treatment at time 2 were excluded from logistic regression analyses. As patient
satisfaction and social support have not been examined in prior research, they were added in a
final step to explore whether they explained any additional variance in unmet needs. Thus,
predictors were entered in the following steps: (1) time 1 supportive care needs; (2) age, time
since diagnosis, finished treatment, gender, driving distance from hospital, treatment received,
physical and mental quality of life; (3) anxiety, depression and distress; (4) patient satisfaction
and social support.
Results
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Prevalence of unmet needs at time 1 and time 2
Consistent with Beesley et al. [12] and Sanson-Fisher et al. [9], dichotomised no-tolow and moderate-to-high individual needs item were used to assess the prevalence of unmet
supportive care needs. Almost two thirds of patients (57.8%) reported having at least one
moderate to high unmet need at baseline and just under half (47.4%) reported at least one
moderate to high unmet need at six month follow-up. The top 10 moderate to high unmet
needs were in the physical/daily living and psychological domains and the majority of these
unmet needs remained in the top 10 needs reported at 6 months (see Table 1).
Standardised Likert summated scores were used to rank the prevalence of needs
domains. At time 1, health system/information (median = 25) and physical/daily living
(median = 25) needs were ranked most prevalent followed by psychological (median = 22.5),
patient care/support (median = 20) and sexuality needs (median = 8.33). Ratings were similar
for these domains at time 2: health system/information (median = 20.45), physical/daily living
(median = 20), psychological (median = 20), patient care/support (median = 15) and sexuality
needs (median = 0).
Predictors of Unmet Supportive Care Needs
Descriptive statistics for all variables used in the analyses are presented in Table 2.
Logistic regression results for prospective predictors of unmet supportive care needs are
reported in Table 3. Participants who reported having unmet needs at time 1 were between
2.92-7.03 times more likely to report having unmet needs at time 2 and baseline unmet needs
were highly significant prospective predictors across all needs domains (see Table 3).
Physical/daily living needs. Time 1 physical/daily living needs, older age, being
female, longer time since diagnosis, lower physical quality of life, greater depression, and
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greater distress were associated with being more likely to have unmet physical/daily living
needs at time 2.
Psychological needs. Once accounting for time 1 psychological unmet needs, only
increasing time since diagnosis was associated with a greater likelihood of time 2 unmet
psychological needs.
Patient care/support needs. Being female was the only predictor associated with
change in unmet patient care and support needs at time 2 after accounting for time 1 patient
care needs.
Sexuality needs. Time 1 sexuality needs, lower mental quality of life, greater patient
satisfaction with healthcare and less social support was associated with a greater likelihood of
time 2 unmet sexuality needs.
Health system/information needs. Health system/information needs at time 1, longer
time since diagnosis, not having had hormone therapy and lower patient satisfaction with
healthcare was associated with being more likely to report time 2 unmet health system and
information needs.
Discussion
Consistent with previous research, the highest ranked unmet supportive care needs
were in the physical/daily living and psychological needs domains [7, 9, 12] and a large
proportion of respondents experienced at least one mod-to-high unmet need at baseline and
six month follow-up. The proportion of respondents reporting unmet needs at time 1 was
reduced at time 2 across all domains.
Predictors of change in unmet supportive care needs varied across each needs domain
demonstrating how patient, medical and psychosocial characteristics may differentially
12
predict areas of unmet supportive care needs. For instance, psychological factors such as
depression, anxiety and distress have been linked previously to patients reporting unmet needs
[13, 16] and the present study extends these findings by identifying which needs domains are
predicted by psychological factors. Specifically, greater depression and greater distress at
time 1 was associated with patients reporting unmet needs in the physical/daily living domain
at six months follow-up. The prediction of change in physical unmet needs by psychological
factors is consistent with the results of Ronis et al. [36] who found that depression predicted
change in 6 of 12 health-related quality of life domains over a one year period from pre- to
post-treatment.
Paradoxically, although over time patients experience less distress over time, unmet
physical/daily living, psychological, and health system/information needs increased with
longer time since diagnosis. Patients experience a significant disruption in their global
functioning and supportive care needs immediately following diagnosis however they
continue to require assistance adapting to and coping with their cancer throughout the cancer
trajectory [23, 37]. Stanton et al. [23] suggests that the realisation one has cancer may only
become apparent over time, for example when active coping strategies (e.g., treatment) are
removed. As well, family and medical support decreases once cancer treatment is completed
leaving patients with fewer resources, and less communication and support during their
recovery. Psychological adjustment to the reality of cancer, and treatment outcomes and sideeffects may change during the cancer experience supporting the idea that patients’ long-term
physical, psychological and informational needs increase with such an awareness.
These results support research focusing on cancer survivorship. Despite being
satisfied with information and medical care during treatment, cancer survivors report less
satisfaction with the physical, emotional and lifestyle support they receive with regards to the
changes they may experience over time [38-41]. Research on unmet needs in cancer
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survivors has focused almost exclusively on breast cancer patients, and the present study
generalises these findings to patients who may have a variety of cancer and treatment
experiences.
As predicted, lower patient satisfaction with healthcare was associated with reporting
change in health system and information needs. This result is consistent with the idea that
patients make judgements about their healthcare based on the quality of physician-patient
communication and the provision of adequate information about cancer [42]. Dissatisfaction
with initial information about cancer may increase the need for information over time.
Although lower patient satisfaction related to change in health system/information needs,
greater patient satisfaction was associated with unmet sexuality needs. A possible
explanation for this finding concerns the complexity of patient and physician expectations
about the role of sexuality issues in medical care. For example, some patients hold the view
that health professionals are medical experts and feel that if sexuality issues were of concern
they would have been mentioned by their health professional whereas physicians have
reported avoiding sexuality issues and feeling uncertain or uncomfortable about discussing
these with patients [43, 44]. Patients may be neglecting issues of sexuality in assessments of
their medical care and report sexuality needs independently of patient satisfaction. By
excluding sexuality issues from assessments of satisfaction with medical care, patients with
great satisfaction initially may then become aware of unmet sexuality needs over time.
Alternatively, as patients are satisfied with their medical care and as medical issues become
less of a focus over time, patients may be more aware of alternative aspects of their life where
their needs are unmet, for example, assessing and addressing their sexual relationships and
sexuality needs.
This second explanation is consistent with the finding that lower social support was
associated with a higher likelihood of reporting unmet sexuality needs. Addressing sexuality
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needs may be more difficult for patients who perceive that they have limited social support to
encourage disclosure of such a sensitive issue. Patients who perceive emotional and
informational support from family, friends and health providers demonstrate better adjustment
[19-21] and sexuality needs may be a persistent area of concern for patients who perceive
inadequate support.
Conclusions and Future Directions
Cancer patients continue to report unmet supportive care needs years after their cancer
diagnosis. The complex relationships between patient care, health system and information
needs and psychological factors highlight the role of medical professionals in ensuring cancer
patients are satisfied with their treatment and cancer care and are adjusting to their cancer
over time. These findings extend across a general cancer sample and patients who have
experienced a range of treatment and healthcare experiences suggesting that these predictors
can be generalised to a variety of healthcare settings. Further, these results support
recommendations deriving from a recent report into the medical and psychosocial issues faced
by cancer survivors proposing that cancer patients be provided with a survivorship care plan
that addresses information related to their long-term care and identifies psychological and
social support services available to them over time [45].
The present study has provided valuable insight into the socio-demographic, cancer
and psychosocial characteristics that are associated with the changing needs of cancer patients
over time. Extending previous research on supportive care needs by incorporating
psychosocial factors including psychological distress, social support and patient satisfaction
predictors will help health professionals to identify patients who may be at risk of greater
unmet needs over time. As well, unlike many of the socio-demographic, cancer and treatment
factors explored in prior research on supportive care needs, psychosocial predictors are
15
amenable to change and can be targeted by healthcare interventions. For example,
interventions that reduce psychological distress and depression in cancer patients may
increase patients’ feelings of being able to cope with their physical needs over time.
Although the present study explores direct relationships between psychosocial factors and
unmet supportive care needs, additional research examining moderational or mediational
relationships is needed. For example, although lower patient satisfaction has been linked to
greater health system/information needs, there is some evidence that the quality of physicianpatient communication [42] and the quality of physician empathic responses can influence
patient satisfaction and psychosocial health outcomes [46]. Further, physician empathy can
indirectly affect depression and socio-emotional-cognitive quality of life through a desire for
more information from physicians about treatment options and health promotion [47].
Additional research into possible indirect relationships between psychosocial, cancer and
socio-demographic predictors may further identify those patients with healthcare experiences
that are more likely to lead to poor psychosocial and physical adjustment.
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Acknowledgements
This project was funded by the Cancer Council Queensland. We gratefully acknowledge the
support of The Townsville Hospital and Ms Alison Beeden in the undertaking of this
research.
17
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20
Table 1. Top 10 unmet supportive care needs listed as moderate to high at time 1 and time 2.
Item
Time 1
Time 2
Domain
(%)
(%)
Lack of energy/tiredness
26.5
21.4
Physical
Not being able to do the things you used to do
26.5
20.9
Physical
Fears about the cancer spreading
24.9
19.8
Psychological
Concerns about the worries of those close to you
21.8
20.1
Psychological
Uncertainty about the future
20.6
16.7
Psychological
Work around the home
19.2
14.6
Physical
Worry that the results of treatment are beyond your control
19.1
13.3
Psychological
Feeling down or depressed
18.9
16.9
Psychological
Anxiety
18.2
14.1
Psychological
Feelings of sadness
15.6
11.5
Psychological
Pain
14.7
13.0
Physical
21
Table 2. Descriptive statistics for predictors and supportive care needs at Time 1 and Time 2.
Predictors
Time 1
Time 2
M (SD)
M (SD)
PCS
43.30 (11.64)
45.26 (10.98)
MCS
48.92 (10.65)
49.54 (10.97)
Depression
4.26 (3.51)
4.03 (3.42)
Anxiety
6.14 (4.00)
5.99 (4.11)
Distress
2.98 (2.72)
2.93 (2.82)
Patient satisfaction
4.01 (.72)
3.97 (.66)
20.82 (4.76)
20.66 (4.65)
Time 1
Time 2
Social support
Outcome
(% reporting unmet need)
60.82
53.79
Psychological
65.71
55.99
Patient care/support
30.79
24.87
Sexuality
30.70
26.89
Health system/information
47.12
37.17
Physical/daily living
Note: higher scores indicate more of the construct.
22
Table 3. Final Logistic Regression Models Predicting Change in Supportive Care Needs
Physical/daily living
Psychological
Patient care & support
Sexuality
Health system &
information
OR (CI)
OR (CI)
OR (CI)
OR (CI)
OR (CI)
SCNS domain need (time1)
3.02 (1.56-5.83)**
Age (in years)
1.04 (1.01-1.08)**
.99 (.97-1.02)
1.00 (.97-1.03)
.99 (.96-1.02)
1.02 (.99-1.05)
2.72 (1.32-5.61)**
1.41 (.73-2.73)
2.71 (1.23-5.97)*
.81 (.37-1.75)
1.45 (.77-2.75)
.60 (.33-1.10)
.92 (.52-1.63)
.76 (.40-1.45)
.53 (.28-1.01)
.80 (.45-1.39)
1.01 (1.00-1.01)*
1.01 (1.00-1.01)*
1.00 (.99-1.01)
1.00 (.99-1.01)
1.00 (1.00-1.01)*
.43 (.17-1.07)
.86 (.37-1.99)
.82 (.34-1.99)
1.02 (.41-2.51)
.55 (.25-1.23)
.77 (.34-1.75)
1.16 (.53-2.53)
1.06 (.43-2.61)
1.01 (.42-2.43)
2.07 (.95-4.53)
1.12 (.53-2.40)
.84 (.42-1.68)
.98 (.45-2.14)
1.51 (.69-3.31)
.65 (.33-1.27)
1.20 (.62-2.30)
.96 (.51-1.79)
.86 (.42-1.75)
1.25 (.60-2.60)
1.06 (.56-1.98)
.68 (.31-1.50)
1.03 (.48-2.20)
.80 (.35-1.80)
.67 (.28-1.63)
.45 (.21-.96)*
PCS (time1)
.96 (.93-.99)*
1.00 (.97-1.03)
1.00 (.96-1.03)
.99 (.96-1.03)
.98 (.95-1.01)
MCS (time1)
.98 (.93-1.03)
.98 (.94-1.03)
.98 (.93-1.03)
.96 (.91-1.00)*
.99 (.95-1.03)
1.31 (1.12-1.53)**
1.15 (.99-1.33)
1.01 (.88-1.17)
.92 (.80-1.07)
1.07 (.94-1.21)
.90 (.79-1.02)
1.08 (.97-1.21)
.98 (.88-1.10)
1.01 (.89-1.13)
1.00 (.90-1.12)
1.26 (1.06-1.49)**
1.15 (.99-1.34)
.99 (.84-1.17)
1.13 (.96-1.33)
1.02 (.88-1.19)
Patient satisfaction (time1)
1.49 (.94-2.38)
1.08 (.70-1.67)
.76 (.48-1.19)
2.49(1.46-4.26)**
.61 (.40-.93)*
Social support (time1)
1.04 (.95-1.11)
1.03 (.97-1.12)
.98 (.91-1.06)
.91 (.85-.98)*
.95 (.89-1.02)
Female
†
Lives within driving distance
†
Time since diagnosis (weeks)
Finished treatment
Had surgery
†
†
Had radiation
†
Had chemotherapy
†
Had hormone treatment
†
HADS depression (time1)
HADS anxiety (time1)
Distress (time1)
Total Model
2
4.26 (2.22-8.17)***
2
7.03 (3.48-14.19)***
2
7.03 (3.428-14.47)***
2
2.92 (1.58-5.39)**
2
x = 145.99
x = 121.30
x = 74.54
x = 90.57
x = 84.16
p = .000
p = .000
p = .000
p = .000
p = .000
*p <.05 **p <.01 ***p<.001
OR = odds ratio, CI = confidence interval
Note. † = predictor is a dummy variable.