Auto-gestão e qualidade de vida em mulheres com endometriose

Prévia do material em texto

Self-management factors associated
with quality of life among women with
endometriosis: a cross-sectional
Australian survey
Rebecca O’Hara1,2,*, Heather Rowe1, and Jane Fisher1
1Public Health and Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia 2Robinson Research Institute, University
of Adelaide, North Adelaide, South Australia 5006, Australia
*Correspondence address. Robinson Research Institute, Ground Floor, 55 King William Rd, North Adelaide, South Australia, 5006,
Australia. E-mail: research@beckohara.com.au
Submitted on May 13, 2019; resubmitted on September 22, 2020; editorial decision on November 3, 2020
STUDY QUESTION: What self-management factors are associated with quality of life among women with endometriosis?
SUMMARY ANSWER: Greater self-efficacy was associated with improved physical and mental quality of life.
WHAT IS KNOWN ALREADY: Women with endometriosis have an impaired quality of life compared to the general female
population. However, most studies have investigated quality of life in a hospital or clinic setting rather than a community setting and the
association between self-management factors and quality of life have not, to date, been investigated.
STUDY DESIGN, SIZE, DURATION: A cross-sectional, population-based online survey was performed, which was advertised through
women’s, community and endometriosis-specific groups.
PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 620 women completed the survey for this study. Mental and
physical quality of life was assessed using the standardized SF36v2 questionnaire. Self-management factors included self-efficacy, partners in
health (active involvement in managing the condition) and performance of self-care activities. Treatment approaches included the use of hor-
monal treatment, pain medications and complementary therapies and whether the participant had a chronic disease management plan.
Hierarchical regression analyses were used to examine whether self-management and treatment factors were associated with quality of life.
MAIN RESULTS AND THE ROLE OF CHANCE: Both physical and mental quality of life were significantly lower among women with
endometriosis compared to the mean scores of the general Australian female population (P< 0.001). Physical quality of life was positively
associated with income sufficiency (P< 0.001) and greater self-efficacy (P< 0.001), but negatively associated with age (P< 0.001), pain
severity (P< 0.001), use of prescription medications (P< 0.001), having a chronic disease management plan (P< 0.05) and number of
self-care activities (P< 0.05). Mental quality of life was positively associated with being older (P< 0.001), partnered (P< 0.001), having a
university education (P< 0.05), increasing self-efficacy (P< 0.001) and higher partners in health scores (P< 0.001).
LIMITATIONS, REASONS FOR CAUTION: Results are derived from a cross-sectional study and can only be interpreted as associa-
tions not as causal relationships. The sample was more educated, more likely to speak English and be born in Australia than the general
Australian female population of the same age, which may influence the generalizability of these results.
WIDER IMPLICATIONS OF THE FINDINGS: This study investigated a knowledge gap by investigating quality of life of women with
endometriosis in a large community sample. Self-efficacy was significantly associated with both physical and mental quality of life.
Supporting women with endometriosis to improve self-efficacy through a structured chronic disease management programme may lead to
improvements in this aspect of wellbeing.
STUDY FUNDING/COMPETING INTEREST(S): R.O. undertook this research as part of her PhD at Monash University, which was
supported by an Australian Government Research Training Program Stipend. J.F. is the Finkel Professor of Global Public Health, which was
supported by the Finkel Family Foundation. There are no conflicts of interest to declare.
TRIAL REGISTRATION NUMBER: NA.
Key words: quality of life / psychology / self-management / women’s health / health outcomes / endometriosis / chronic disease
VC The Author(s) 2020. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved.
For permissions, please email: journals.permissions@oup.com
Human Reproduction, Vol.36, No.3, pp. 647–655, 2021
Advance Access Publication on December 30, 2020 doi:10.1093/humrep/deaa330
ORIGINAL ARTICLE Gynaecology
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Introduction
Endometriosis is a common, inflammatory condition, which is diag-
nosed surgically and does not have a cure (Leyland et al., 2010;
Zondervan et al., 2018). It is characterized by tissue similar to the lin-
ing of the uterus growing outside of the uterus, often on the pelvic
organs and tissues (Zondervan et al., 2018). The condition can result
in pain and can contribute to infertility. Endometriosis is a chronic con-
dition (O’Hara et al., 2018) that can require long-term management
through surgery, pain medications and hormonal treatments
(Dunselman et al., 2014; Zondervan et al., 2018).
Previous studies have suggested that people with endometriosis
have an impaired health-related quality of life when compared with
those without endometriosis (Gao et al., 2006; Nnoaham et al., 2011;
De Graaff et al., 2013; Marinho et al., 2018). These impairments are
related to pain and symptoms (Marinho et al., 2018), social and psy-
chological functioning (Gao et al., 2006) and physical quality of life
(Marinho et al., 2018). De Graaff’s et al. (2013) study highlighted that
physical quality of life was protected by income, whilst the number of
comorbidities, number of physicians consulted, effect on job, number
of laparotomies and symptoms (chronic pain and dyspareunia) were
associated with reduced physical quality of life (De Graaff et al., 2013).
Mental quality of life was protected by being partnered and reduced
by the presence of symptoms (dyspareunia and chronic pain), number
of comorbidities and having a high BMI (De Graaff et al., 2013). Gao
et al. (2006) reported that hormonal treatments and surgical interven-
tion were associated with improvements in physical and psychological
functioning, pain, vitality and general health.
De Graaff et al. (2015) have suggested that quality of life studies in-
volving women recruited through health centres and patient associa-
tions may not be representative of the total population of women
with endometriosis. They conclude that quality of life studies should
recruit women who live in a specific geographic area rather than
recruiting from a particular hospital or patient association (De Graaff
et al., 2015). However, there are few investigations of quality of life
among women with endometriosis recruited in a community setting
rather than a patient association or clinic setting.
The World Health Organization (WHO) has recognized the impor-
tance of people with a chronic disease being active participants in their
own care, and the need for supportive health practice environments
that promote self-management of chronic diseases (WHO, 2002).
Self-management is a multifaceted construct for which there is no
agreed definition in the literature (Barlow et al. 2002). It is generally
conceptualized as the active participation of the person in planning,
decision-making and undertaking tasks to manage the symptoms, treat-
ment and the physical and psychosocial changes involved in living with
a chronic disease (Clark et al. 1991; Barlow et al. 2002).
Self-management extends beyond self-care,which entails tasks that
an individual performs at home to manage the symptoms of the condi-
tion (Clark et al. 1991). Effective self-management requires partnership
and collaboration between the patient and healthcare provider (Clark
et al. 1991; Holman and Lorig, 2004). The patient with a chronic illness
is responsible for making informed management decisions based on
knowledge of the condition and available treatment options, undertak-
ing behavioural change, making emotional and social adjustments,
monitoring symptoms and taking action based on monitoring and com-
municating trends or issues with the condition to health practitioners
(Clark et al. 1991; Holman and Lorig, 2004; Creer and Holroyd,
2006). Lorig and Holman (2003) have proposed that there are five
core self-management skills: problem-solving, decision-making, identify-
ing and utilizing resources, forming a patient–healthcare provider part-
nership and taking action. There is evidence from investigations of
other chronic diseases that, when compared with usual care, interven-
tions to improve self-management skills are effective in improving
knowledge, self-efficacy, performance of self-management tasks and
some aspects of health status (Barlow et al., 2002).
To the best of our knowledge, quality of life studies among women
with endometriosis have not investigated the influence of self-
management approaches on quality of life outcomes. The aim was to
address these knowledge gaps and assess the self-management factors
associated with quality of life among a community-sample of women
with endometriosis in Australia.
Materials and methods
The Endometriosis Management in Australia Study was a population-
based, cross-sectional survey.
Setting
Australia has a national healthcare scheme (Medicare) which provides
access to free health services in a public hospital. Residents in
Australia can elect to pay for private health insurance (45.7% of the
Australian population as of December 2017; Australian Prudential
Regulation Authority, 2018), which provides access to private hospitals
and practitioners of choice (Duckett, 2005). When purchasing private
health insurance, consumers have the option to purchase hospital
cover only, ‘extras’ or combined hospital and ‘extras’ cover. The
‘extras’ insurance covers services not covered by Medicare (e.g. dental
or allied health services).
Gynaecologists typically lead the care for endometriosis in Australia,
and the condition is monitored by general practitioners (GPs) (Young
et al., 2016), however, this varies depending on access to gynaecology
services, particularly in regional or remote areas of the country. Some
gynaecologists and GPs charge no out of pocket fees above the
Medicare rebate, however, most will levy a fee.
Chronic disease management is supported by Medicare items for
chronic disease management, which allow GPs to prepare and imple-
ment a Chronic Disease Management—GP Management Plan (CDM
Plan) and Team Care Arrangements (TCAs) for people with chronic
diseases (Australian Government Department of Health, 2016a).
These items are available for preparing, co-ordinating, reviewing or
contributing to CDM Plans (Australian Government Department of
Health, 2016a). The eligibility criteria for the development of a CDM
Plan are that the individual has a medical condition(s) that has been
present for 6 months or longer that the GP believes would benefit
from a structured approach or multidisciplinary care. There is no list
of eligible conditions; rather, the clinical judgement of the GP deter-
mines the person’s eligibility. Individuals with a CDM Plan may also ob-
tain a TCA, which entitles them to access five subsidized allied health
services per calendar year through referral by their GP (Australian
Government Department of Health, 2016a).
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Each general practice will have its own template for preparing a
CDM Plan and TCA, but they typically involve assessment of the pa-
tient, identification and documentation of the patient’s goals, the treat-
ments or services required and actions to be taken by the patient and
GP (Australian Government Department of Health, 2016a; Newland
and Zwar, 2006). Medicare items cover a regular review of the plan
(e.g. every 3 months) and preparation of a new plan (e.g. every
12 months). These dates are documented in the plan.
Participants and recruitment
Inclusion criteria were to be a woman with self-reported, surgically
diagnosed endometriosis, living in Australia and able to communicate
in English. Exclusion criteria were to be aged less than 18 years and to
have suspected, but not surgically diagnosed endometriosis.
In order to enlarge the sampling frame as much as possible, the
survey was advertised by 163 health, endometriosis-specific and com-
munity organizations through social media, newsletter and hardcopy
flyers in public spaces (e.g. community noticeboards). Some regional
newspapers also advertised the study on their own initiative. The on-
line survey was hosted on the Qualtrics survey platform (Qualtrics,
2018) and open from 14 November 2017 to 8 January 2018. At the
time of the study, 86.1% of women in Australia reported using the in-
ternet 2016–2017 (Australian Bureau of Statistics, 2018). In a
consumer survey, all but 1% of the females surveyed (n¼ 400) had
some form of internet-enabled device (i.e. computer, smartphone,
tablet) and 69% had used online social networking sites (Sensis, 2016).
However, potential participants were offered the options of com-
pleting a paper-based survey or undergoing a telephone interview with
the researcher, in case they lacked access to the internet or preferred
these other formats of participation.
Ethical approval
Ethical approval was obtained from the Monash University Human
Research Ethics Committee (2017-1166).
Measurement
The self-report survey instrument was developed through a review of
available endometriosis measures, expert panel review and pilot tested
with women with endometriosis. The instrument consisted of 58
fixed-response, standardized and study-specific questions measuring
health-related quality of life, medical history, symptoms, treatment,
self-management and demographics.
Quality of life
The SF36v2 Health Survey, validated for use in Australia, was used to
measure health-related quality of life (HRQol), (reference period ¼
prior 4 weeks). The survey measures eight domains of HRQol
including physical functioning, general health, vitality, social functioning,
mental health, bodily pain, role limitations associated with mental
health (role-emotional) and physical health (role-physical; Maruish,
2011). These domains contribute to the development of two summary
component scores: physical health score (PCS) and mental health
score (MCS), which were the main outcome measures for this study
(Maruish, 2011). Responses to the SF36v2 items were imported into
Quality Metric’s proprietary scoring software (v5.1) in order to
produce the two summary component measures (PCS and MCS).
Missing data were not imputed except for items pertaining to the
SF36v2: missing data for these items were imputed based on Quality
Metric’s ‘maximum data recovery method’ in the software (Quality
Metric Incorporated, 2017). Further information on Quality Metric’s
proprietary scoring software can be found in the user manual
(Maruish, 2011). Higher scores indicate better quality of life. The sum-
mary measures have excellent internal consistency (Cronbach alpha
0.96 PCS and 0.93 MCS; Maruish, 2011).
Pain severity
Respondents were asked to ratehow severe their pelvic pain was on
average in the last 3 months using a scale from ‘no pain’ (0)—‘worst
possible pain’ (10). This question was adapted from the Global Study
of Women’s Health (GSWH) survey (Nnoaham et al., 2011) and sim-
plified to measure pelvic pain in general rather than assess each type
of pain (e.g. period pain, pain with intercourse, pain at other times).
Treatment approaches
Questions measuring the use of hormonal treatments and prescription
pain medications in the last 3 months were adapted from the GSWH
survey (Nnoaham et al., 2011). The pain medication question was
simplified from the GSWH and asked ‘for pain associated with
endometriosis’ rather than for each type of pelvic pain. Participants
were asked to select from a list of complementary providers they had
consulted in the previous 12 months for their endometriosis and
whether they have a Chronic Disease Management Plan for care of
their endometriosis (both in no/yes format).
Self-management
There is no available single measure of self-management. Therefore, a
combination of study-specific and standardized questions to assess
components of self-management were used, as follows:
• Self-efficacy was measured using the ‘Self-efficacy for Managing
Chronic Disease’ six-item scale (Lorig et al., 2001a,b; Stanford
Patient Education Research Center, 2007). Respondents were asked
to rate their confidence as ‘not at all confident’ (1) to ‘totally confi-
dent’ (10). Higher scores indicate greater self-efficacy and the scale
has good internal consistency (alpha ¼ 0.91; Stanford Patient
Education Research Center, 2007).
• Self-management capacity: The revised partners in health (PIH)
scale is a 12-item measure, developed in Australia, which assesses
the degree of involvement among people with a chronic disease in
self-management behaviours (Smith et al., 2016). It measures four
aspects of self-management including knowledge of illness, patient-
health professional partnership, recognition and management of
symptoms and coping with illness (Smith et al., 2016). Items are
rated as ‘very little (0) to a lot (8)’, ‘never (0) to always (8)’ and
‘not very well (0) to very well (8)’. The scale has good internal
consistency (Cronbach alpha ¼ 0.81) (Smith et al., 2019), and
higher scores indicate greater involvement in self-management
behaviours.
• Self-care: A study-specific multi-choice question assessed whether
respondents had engaged in any of the 12 listed self-care activities
to assist them to manage their endometriosis symptoms in the pre-
vious 3 months (e.g. changing diet, exercise, taking supplements).
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.Respondents were also provided with an opportunity to list other
self-care activities they had engaged in.
Demographic characteristics
Study-specific questions were used to collect socio-demographic data
including whether the participant had private health insurance for hos-
pital or ‘extras’ (no/yes), age (integer), their postal code, highest level
of education (from listed options) and have a partner (no/yes).
Respondents were also asked how they manage on the income they
have available (‘it is impossible’, ‘difficult all the time’, ‘difficult some of
the time’, ‘not too bad’, ‘it is easy’).
Data management
Data were downloaded from Qualtrics (Qualtrics, Provo, UT, USA)
and imported to SPSS v24 (IBM Corp. Armonk NY, USA). Responses
for the SF36v2 items were imported into Quality Metric’s proprietary
scoring software (v5.1). Missing data for these items were imputed
based on Quality Metric’s ‘maximum data recovery method’ in the
software (Quality Metric Incorporated, 2017). The two SF36v2 sum-
mary component scores (PCS and MCS) were generated and trans-
formed into T-scores (norm-based scores). The scoring algorithm
within Quality Metric’s Proprietary software standardizes the imported
scores using 2009 US general population scores which have a mean of
50 and SD of 10 (Maruish, 2011). Once the survey data had been
scored these summary measures were imported into SPSS for analysis.
Binary variables were created to indicate whether participants had
seen at least one complementary provider (no/yes) or had any type
of health insurance (e.g. ‘hospital and/or extras’ or none). A total
score was calculated for self-efficacy by calculating the average across
the six items (Lorig et al., 2001a,b). Good internal consistency for the
self-efficacy scale was observed in this dataset (Cronbach alpha ¼
0.91). A total score for the partners in health scale was generated by
adding together the scores for each item (Smith et al., 2016). Good in-
ternal consistency was observed for the partners in health scale in this
dataset (Cronbach alpha ¼ 0.79). A total score for the number of
self-care activities that a participant engaged in was calculated. Using
postcode, the respondents’ ‘remoteness area’ were determined based
on the 2011 Australian Bureau of Statistics Remoteness Structure
(Australian Bureau of Statistics, 2013). Each postcode is allocated to a
category (major city, inner regional, outer regional, remote and very
remote), these were then collapsed into a binary variable (‘major or
inner regional’ and ‘outer regional, remote or very remote’). Binary
variables were created for income sufficiency (‘difficult or impossible’
and ‘not too bad or easy’) and education (‘no university education’
and ‘university education’). Missing data were not imputed for the in-
dependent variables.
Statistical analysis
The aim of the analysis was to explore the factors associated with
quality of life. Frequencies for categorical data and mean, SD and 95%
CI of the mean for continuous data are reported. Mean SF36v2 sum-
mary measures (PCS and MCS) from this study were compared to
previously published Australian female general population scores for
these summary measures (Hawthorne et al., 2007) using the one-
sample Student’s t-test. Two hierarchical multiple regression analyses
were conducted to assess the association of each of the outcome
measures (SF36v2-PCS and MCS) with socio-demographic, pain sever-
ity, treatment approaches and self-management variables. First, bivari-
ate analyses were conducted to assess the association of each
independent variable with PCS and MCS. All variables that were signifi-
cantly associated with the outcome variables (P< 0.05) were entered
into the respective hierarchical regression analyses, which is consistent
with other quality of life studies in this area (De Graaff et al., 2013).
The enter method was used for the two hierarchical multiple regres-
sions with variables entered into the model. The order of entering the
variables was based on a review of the literature. The variables were
entered in the following order: demographics to control for confound-
ing of variables that may be associated with quality of life (Block 1); fol-
lowed by pain severity (Block 2), which has been highlighted in other
research to be associated with lower PCS and MCS (De Graaff et al.,
2013); treatment approaches (Block 3) and self-management variables
(Block 4), which served as new elements to be explored in this article.
For each model regression coefficients, 95% CI, F statistics, R2 and
change in F and R2 are presented. Data from participants who
reported being pregnant (n¼ 23) at the time of the survey were ex-
cluded from the regression analyses as some endometriosis treatments
may be contraindicated during pregnancy and pregnancy may be asso-
ciated with altered quality of life.
Results
Participantcharacteristics
Summary data were available for 620 women with endometriosis,
aged 18–71 years (Fig. 1 and Table I) and all participants completed
the survey online.
Almost 70% of participants had menstruated in the last 3 months, a
few were pregnant (3.7%) or had experienced menopause (10.2%).
The majority of participants lived in a major city (69.8%) and are
Australian born (86.9%). Many participants reported ongoing symp-
toms, such as dysmenorrhoea, dyspareunia and chronic pelvic pain.
The sample was more educated, likely to speak English and be born in
Australia when compared to Australian census data from females of
the same age (Table I).
Participants reported an average self-efficacy score of 5.1 (out of 10,
SD¼ 2.1) and average PIH score of 69.7 (out of 96, SD¼ 12.8).
Women engaged in an average of 5.2 (SD¼ 2.6) self-care activities in
the previous 3 months.
Quality of life
Respondents’ average component scores on the SF36v2 were 42.9
(SD¼ 9.2) for the physical component (PCS) and 36.8 (SD¼ 11.3) for
the mental component (MCS). Both scores were below the norm-
based scores of 50 from the 2009 US general population (Maruish,
2011). Both SF36v2 summary measures (PCS and MCS) were signifi-
cantly lower when compared with the mean scores of the Australian
female general population (P< 0.001; Table II).
Physical quality of life (SF36v2-PCS)
In Model 1, income sufficiency was the only variable to make a signifi-
cant contribution to the model with 14.7% of the variance of physical
quality of life score explained. In Model 2, income was retained and
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pain severity also was a significant predictor of physical quality of life
score explaining 22.2% of the variance. In Model 3, in addition to in-
come and pain severity, all treatment approaches (prescription pain
medications, complementary practitioners and CDM plan) were signifi-
cant predictors of physical quality of life, explaining 31.2% of the
variance.
In the final model (Model 4), 7 of the 11 variables made a significant
contribution to the physical component quality of life scores
(Table III). Model 4 explained 39.8% of the variance in physical quality
of life scores. PCS was positively associated with income sufficiency
and greater self-efficacy, but negatively associated with older age, pain
severity, use of prescription medications, having a CDM plan and num-
ber of self-care activities (Table III). The addition of treatment
approaches (Model 3) and self-management variables (Model 4) led to
statistically significant increases in the explained PCS variance.
Mental quality of life (SF36v2-MCS)
In the first model (Table IV), socio-demographic factors, such as age,
having a partner, income sufficiency and university education were sig-
nificant factors associated with mental quality of life, explaining 16.3%
of the variance. In Model 2, the socio-demographic variables were
retained and pain severity was associated with a reduction in mental
quality of life, explaining 18.5% of the variance. In Model 3, in addition
to the socio-demographic variables and pain severity, prescription pain
medications were a significant predictor of mental quality of life,
explaining 20.4% of the variance.
In the final model (Model 4), 5 of the 12 variables made a significant
contribution to the mental component quality of life scores (Table IV).
The final model explained 34.2% of the variance in mental quality of
life scores. MCS was positively associated with older age, being part-
nered, having a university education, increasing self-efficacy and partner
in health scores. The addition of treatment approaches (Model 3) and
self-management variables (Model 4) led to statistically significant
increases in the variance explained of MCS.
Discussion
These data from a cross-sectional survey, which included standardized
measures, is the first to investigate self-management factors associated
with quality of life among women with endometriosis.
Strengths and limitations
Self-reported surveys are regarded as a valid method for obtaining in-
formation about endometriosis in the absence of registry data (Saha
et al., 2017). The sample included participants from geographically di-
verse locations including major cities, regional and remote areas of
Australia. The sample size was large enough to establish outcomes
with sufficient precision. Data were collected using a structured instru-
ment, which included standardized measures for which comparative
data were available, and multivariable analyses included a range of rele-
vant covariates.
A range of recruitment and advertising strategies, both online and
offline, were used with the intention of recruiting a diverse sample of
women with endometriosis. Specific organizations were contacted to
ensure that women from culturally and linguistically diverse back-
grounds, women of Indigenous heritage and women living in rural and
remote areas were afforded the opportunity to take part in the sur-
vey. Despite these measures, we acknowledge that the sample only in-
cluded a small proportion of women from culturally and linguistically
diverse backgrounds and that the findings might not represent their
experiences.
All participants completed the survey online despite the offer of
paper-based or interview options. Online surveys may be less accessi-
ble to people without computer proficiency, internet access, or English
fluency, or who are in lower socio-economic positions, whose experi-
ences might be underestimated here. Recruitment was for the most
part conducted through endometriosis organizations and support
groups, of which not all women with endometriosis are members, and
to whom the findings may not be generalizable. Finally, cross-sectional
surveys are able to identify associations among variables but not causal
relationships. Notwithstanding the limitations, we believe that these
findings contribute to understanding the quality of life of women with
endometriosis and can inform health policy to better meet their
needs.
Quality of life
We found that women with endometriosis had worse quality of life
(indicated by the SF36v2 Physical and Mental Component Scores) than
women in the general population in Australia. These findings are
Figure 1. Participant flowchart in a study of self-manage-
ment factors associated with quality of life among women
with endometriosis.
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.similar to those from multi-country studies, which generated data from
high-, upper-middle and lower-middle income nations (Nnoaham
et al., 2011; De Graaff et al., 2013).
Having a CDM Plan (Department of Health, 2014) and the use of
prescription pain medications were associated with worse physical
quality of life. As the data are cross-sectional it is not possible to es-
tablish causal relationships for this somewhat perplexing finding. One
interpretation is that a GP might initiate a CDM Plan for women with
more severe symptoms who might benefit from the care provided by
diverse health care providers in a multidisciplinary team (Department
of Health, 2014). Similarly, it might be more likely that prescription
pain medication is required for women experiencing more severe
pain-related disability (in these data, more severe pain was also associ-
ated with lower physical quality of life).
Self-efficacy is the concept capturing the person’s beliefs that they
canperform a particular health action or exert control over their
health (Bandura, 2004). It is a core determinant of health behaviour,
with higher self-efficacy associated with more goal setting, commitment
............................................................................................................................................................................................................................
Table I Participant characteristics in a study of quality of life among women with endometriosis.
Characteristics n % Mean (SD) 95% CI Australian Census
Data %
Demographics
Age (years) (n¼ 618)a,b 34.6 (9.5) 33.87–35.37
Live in major city of Australia (n¼ 609) 425 69.8
University degree (n¼ 620)a,b 303 48.9 27.5
Have a partner (n¼ 619)b 491 79.3
Australian born (n¼ 620) 539 86.9 61.7
Speak language other than English at home (n¼ 619) 24 3.9 23.2
Have private health insurance (n¼ 617)a,b 473 76.7
Manage on income available (not too bad/it is easy) (n¼ 614)a,b 281 45.8
Menopause (n¼ 616) 63 10.2
Pregnant (n¼ 618) 23 3.7
Symptoms in the last 3 months
Pelvic pain with periods (n¼ 619) 407 65.8
Pelvic pain with intercourse (n¼ 619) 378 61.1
Pelvic pain at other times (n¼ 618) 511 82.7
Pain severity (on average) (n¼ 607)a,b 4.8 (2.4) 4.61–5.00
Treatment approaches
Hormonal treatments (last 3 months) (n¼ 618) 366 59.2
Prescription pain medications (last 3 months) (n¼ 616)a,b 290 47.1
Seen any complementary provider (last 12 months) (n¼ 601)a,b 258 42.9
Have chronic disease management plan (n¼ 615)a,b 95 15.4
Self-management
Self-efficacy score (out of 10) (n¼ 606)a,b 5.1 (2.1) 4.97–5.31
Partners in health (out of 96) (n¼ 596)a,b 69.7 (12.8) 68.65–70.71
Number of self-care activities undertaken (n¼ 554)a,b 5.2 (2.6) 5.02–5.46
Source of Australian Census Data: Filtered to females of the same age: Australian Bureau of Statistics (ABS) 2017, Census 2016, Table Builder, viewed 9 December 2018, https://
guest.censusdata.abs.gov.au/webapi/jsf/tableView/ tableView.xhtml.
aFactor included in the physical component score (PCS) hierarchical regression.
bFactor included in the mental component score (MCS) hierarchical regression.
............................................................................................................................................................................................................................
Table II Summary measures quality of life.
Component Participants (n 5 615) Australian Female General
Population (n 5 1462)a
P-value
PCS [mean (SD)] 42.9 (9.2) 48.7 (11.1) <0.001
MCS [mean (SD)] 36.8 (11.3) 49.0 (10.7) <0.001
aHawthorne et al. (2007).
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https://guest.censusdata.abs.gov.au/webapi/jsf/tableView/
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Table III Factors associated with physical quality of life (PCS) (n¼ 492).
Model 1 Model 2 Model 3 Model 4
Variables B 95% CI B 95% CI B 95% CI B 95% CI
Age �0.058 �0.148 .032 �0.084 �0.171 .002 �0.127* �0.210 �0.044 �0.149** �0.228 �0.071
Health insurance 0.675 �1.092 2.442 0.323 �1.368 2.015 0.527 �1.093 2.146 0.073 �1.474 1.621
Income 6.203** 4.607 7.800 5.572** 4.035 7.108 4.275** 2.791 5.759 3.309** 1.888 4.729
University education 1.583 �0.013 3.178 1.153 �0.377 2.683 0.756 �0.690 2.203 0.705 �0.660 2.070
Pain severity �1.131** �1.454 �0.807 �0.899** �1.212 �0.585 �0.615** �0.917 �0.312
Prescription pain medications �4.405** �5.870 �2.941 �3.042** �4.462 �1.621
Complementary practitioners �1.867* �3.219 �0.516 �0.696 �2.082 0.690
CDM plan �3.200* �4.997 �1.403 �2.607* �4.330 �0.883
Self-efficacy score 1.308** 0.910 1.705
Partners in health 0.006 �0.055 0.066
Self-care activities �0.410* �0.687 �0.133
R2 0.147 0.222 0.312 0.398
F 20.92** 27.74** 27.38** 28.82**
DR2 0.147 0.075 0.090 0.086
DF 20.92** 47.09** 21.07** 22.78**
Note: Women who were pregnant were excluded from this analysis.
DF, change in F; DR2, change in variance; B, regression coefficient; CDM, chronic disease management; F, F statistic from model ANOVA; R2, variance explained by the independent
variables.
*P< 0.05.
**P< 0.001.
............................................................................................................................................................................................................................
Table IV Factors associated with mental quality of life (MCS) (n¼491).
Model 1 Model 2 Model 3 Model 4
Variables B 95% CI B 95% CI B 95% CI B 95% CI
Age 0.255** 0.146 0.365 0.237** 0.128 0.346 0.209** 0.099 0.318 0.185** 0.085 0.286
Partner 3.576* 1.404 5.747 3.859** 1.709 6.009 3.855** 1.715 5.996 3.512** 1.554 5.470
Health insurance 1.656 �0.496 3.809 1.437 �0.692 3.566 1.463 �0.681 3.607 0.132 �1.858 2.122
Income 4.174** 2.229 6.120 3.737** 1.801 5.672 3.242* 1.279 5.206 1.482 �0.342 3.306
University education 2.691* 0.752 4.630 2.411* 0.490 4.332 2.267* 0.358 4.177 1.832* 0.081 3.583
Pain severity �0.753** �1.161 �0.346 �0.632* �1.047 �0.218 �0.284 �0.672 0.105
Prescription pain medications �3.073* �5.006 �1.140 �1.596 �3.417 0.224
Complementary practitioners �0.924 �2.709 0.861 0.320 �1.458 2.098
CDM plan 1.257 �1.122 3.636 1.151 �1.068 3.371
Self-efficacy score 1.550** 1.039 2.061
Partners in health 0.162** 0.084 0.240
Self-care activities �0.286 �0.641 0.070
R2 0.163 0.185 0.204 0.342
F 18.86** 18.31** 13.67** 20.70**
DR2 0.163 0.022 0.019 0.138
DF 18.86** 13.208** 3.752* 33.49**
Note: women who were pregnant were excluded from this analysis.
*P< 0.05.
**P< 0.001.
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to achieving goals, belief that effort will lead to favourable health out-
comes and a perceived ability to overcome health challenges
(Bandura, 2004). Patients with higher self-efficacy are more able to
cope with painful stimuli and more able to limit the interference
of pain with daily life (Bandura et al., 1987). We found that greater
self-efficacy was associated with a higher physical and mental quality of
life. This suggests that women with endometriosis who have higher
self-efficacy may manage pain more effectively and be more able to
participate socially and economically, and thereby maintain a higher
quality of life.
The partners in health scale measures knowledge of illness, patient-
health professional partnership, recognition and management of
symptoms and coping with illness (Smith et al., 2016). In this study,
higher scores on the partners in health scale were associated with a
greater mental quality of life but not physical quality of life. This indi-
cates that capacities to form a trusting alliance with a health profes-
sional, and to take an active approach to problem-solving, including by
acquiring knowledge about the illness, are associated with improved
psychological wellbeing, whether or not physical symptoms are
diminished.
Self-care tasks are those a person undertakes to manage their illness
at home (Clark et al., 1991). The inverse relationship found here be-
tween self-care and physical quality of life is perplexing. It is perhaps
because only the total number of self-care activities was assessed
rather than specific types of self-care activities. A recent Australian
study found that self-rated effectivenessvaried between self-care activi-
ties (Armour et al., 2019). Using cannabis, heat and dietary changes
were reported to be the most effective in reducing endometriosis-
associated pain, whilst yoga and stretching were reported as less effec-
tive (Armour et al., 2019). Some self-care activities were associated
with adverse outcomes, for example, participants reported that exer-
cise was associated with increased pelvic pain and fatigue (Armour
et al., 2019). This suggests that not all self-care activities act in the
same way and that some might be ineffective or actually worsen
symptoms.
Practical and research implications
Overall, these data indicate that endometriosis affects the mental and
physical quality of life of women, which has implications for clinical
practice and future research.
In this study, higher self-efficacy appears to be associated with
greater personal agency, improved health outcomes and higher quality
of life. The direction of this association cannot be ascertained in this
study, but nevertheless the finding suggests that encouraging women
with endometriosis to become knowledgeable about the condition
and to be active in making decisions about treatments is likely to be
associated with improved health outcomes. This process may be assis-
ted by providing up-to-date information about the condition and treat-
ment options, encouraging women to ask questions about these,
proposing activities they can do to assist with symptom management
or referring the patient to a CDM programme. The Stanford Chronic
Disease Management (SCDM) program, for example, is a community-
based, peer-led programme, which is designed to help participants de-
velop self-management skills (Lorig et al., 2001a,b). Lorig et al.
(2001a,b) evaluated it in a randomized controlled trial, in a community
setting in CA, USA, among 831 participants with chronic disease
(heart disease, lung disease, stroke or arthritis). It led to improved
self-efficacy, a reduction in emergency department/outpatient visits
and a reduction in health distress (Lorig et al., 2001a,b).
The data have also revealed areas where further research is needed.
At present, there is uncertainty about which self-care activities might
or might not be effective and the potential efficacy of CDM pro-
grammes for women with endometriosis, and these warrant investiga-
tion in well-designed trials.
Conclusion
This research highlights that women with endometriosis are likely to
have an impaired quality of life. Greater self-efficacy was associated
with improved physical and mental quality of life. Supporting
women with endometriosis to improve self-efficacy through a struc-
tured CDM programme may lead to improvements in this aspect of
wellbeing.
Data availability
Due to the nature of this research, participants of this study did not
agree for their data to be shared publicly, so supporting data are not
available.
Acknowledgements
The authors would like to thank Thach Tran at Monash University for
his statistical advice.
Authors’ roles
R.O: project design, design of survey instrument, completed data col-
lection and analysis, interpreted the analysis, manuscript drafting and
approval of final manuscript for publication. H.R: supervision of project,
contributed to expert review of the survey instrument, interpretation
of findings, manuscript drafting and approval of final manuscript for
publication. J.F: supervision of project, contributed to expert review of
the survey instrument, interpretation of findings, manuscript drafting
and approval of final manuscript for publication.
Funding
R.O. undertook this research as part of her PhD, which was supported
by an Australian Government Research Training Program Stipend. J.F.
is the Finkel Professor of Global Public Health, which was funded by
the Finkel Family Foundation.
Conflict of interest
There are no conflicts of interest to declare.
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References
Armour M, Sinclair J, Chalmers KJ, Smith CA. Self-management strat-
egies amongst Australian women with endometriosis: a national
online survey. BMC Complement Altern Med 2019;19:17.
Australian Bureau of Statistics. 81460DO002_201617 Household
Use of Information Technology. Australia, 2016-17. 2018. https://
www.abs.gov.au/ausstats/abs@.nsf/mf/8146.0 (9 December
2018, date last accessed).
Australian Bureau of Statistics. 270.0.55.005—Australian Statistical
Geography Standard (ASGS): Volume 5—Remoteness Structure, July
2011. Canberra: Australian Bureau of Statistics, 2013.
Australian Prudential Regulation Authority. Privately Insured People
with Hospital Treatment Cover, Annual Analysis by Sex, Age and State,
2017. Sydney: Australian Prudential Regulation Authority, 2018.
Bandura A. Health promotion by social cognitive means. Health Educ
Behav 2004;31:143–164.
Bandura A, O’Leary A, Taylor CB, Gauthier J, Gossard D. Perceived
self-efficacy and pain control: opioid and nonopioid mechanisms.
J Pers Soc Psychol 1987;53:563–571.
Barlow J, Wright C, Sheasby J, Turner A, Hainsworth J. Self-manage-
ment approaches for people with chronic conditions: a review.
Patient Educ Couns 2002;48:177–187.
Clark NM, Becker MH, Janz NK, Lorig K, Rakowski W, Anderson L.
Self-management of chronic disease by older adults a review and
questions for research. J Aging Health 1991;3:3–27.
Creer TL, Holroyd KA. Self-management of chronic conditions: the
legacy of Sir William Osler. Chronic Illn 2006;2:7–14.
De Graaff AA, D’Hooghe TM, Dunselman GAJ, Dirksen CD,
Hummelshoj L, Simoens S, Bokor A, Brandes I, Brodszky V, Canis M,
et al.; WERF EndoCost Consortium. The significant effect of endo-
metriosis on physical, mental and social wellbeing: results from an in-
ternational cross-sectional survey. Hum Reprod 2013;28:2677–2685.
De Graaff AA, Dirksen CD, Simoens S, De Bie B, Hummelshoj L,
D’Hooghe TM, Dunselman GAJ. Quality of life outcomes in
women with endometriosis are highly influenced by recruitment
strategies. Hum Reprod 2015;30:1331–1341.
Department of Health. Chronic disease management: provider informa-
tion. In: Health TDo (ed). Canberra: Australian Government, 2014.
http://www.health.gov.au/internet/main/publishing.nsf/Content/
mbsprimarycare-chronicdiseasemanagement (22 August 2016, date
last accessed).
Duckett SJ. Living in the parallel universe in Australia: public Medicare
and private hospitals. Can Med Assoc J 2005;173:745–747.
Dunselman GAJ, Vermeulen N, Becker C, Calhaz-Jorge C,
D’Hooghe T, De Bie B, Heikinheimo O, Horne AW, Kiesel L,
Nap A et al. ESHRE guideline: management of women with endo-
metriosis. Hum Reprod 2014;29:400–412.
Gao X, Yeh YC, Outley J, Simon J, Botteman M, Spalding J. Health-
related quality of life burden of women with endometriosis: a liter-
ature review. Curr Med Res Opin 2006;22:1787–1797.
Hawthorne G, Osborne RH, Taylor A, Sansoni J. The SF36 Version
2: critical analyses of population weights, scoring algorithms and
population norms. Qual Life Res 2007;16:661–673.
Holman H, Lorig K. Patient self-management: a key to effectiveness
and efficiency in care of chronic disease. Public Health Rep 2004;
119:239–243.
Leyland N, Casper R, Laberge P, Singh SS, Allen L, Arendas K,
Leyland N, Allaire C, Awadalla A, Best C et al. Endometriosis diag-
nosis and management: SOGC clinical practice guideline. J Obstet
Gynaecol Can 2010;32:S1–S32.
Lorig K, Holman H. Self-management education: history, definition,
outcomes, and mechanisms. Ann Behav Med 2003;26:1–7.
Lorig K, Ritter P, Stewart AL, Sobel DS, Brown BW Jr, Bandura A,
Gonzalez VM, Laurent DD, Holman H. Chronic disease self-management program: 2-year health status and health care utiliza-
tion outcomes. Med Care 2001a;39:1217–1223.
Lorig KR, Sobel DS, Ritter PL, Laurent D, Hobbs M. Effect of a self-
management program on patients with chronic disease. Eff Clin
Pract 2001b;4:256–262.
Marinho MCP, Magalhaes TF, Fernandes LFC, Augusto KL, Brilhante
AVM, Bezerra L. Quality of life in women with endometriosis: an
integrative review. J Womens Health (Larchmt) 2018;27:399–408.
Maruish ME. User’s Manual for the SF36v2 Health Survey. Lincoln, RI:
Quality Metric Incorporated, 2011.
Newland J, Zwar N. General practice and the management of chronic
conditions–where to now? Aust Fam Physician 2006;35:16–19.
Nnoaham KE, Hummelshoj L, Webster P, d’Hooghe T, de Cicco
Nardone F, de Cicco Nardone C, Jenkinson C, Kennedy SH,
Zondervan KT. Impact of endometriosis on quality of life and
work productivity: a multicenter study across ten countries. Fertil
Steril 2011;96:366–373.e368.
O’Hara R, Rowe H, Roufeil L, Fisher J. Should endometriosis be
managed within a chronic disease framework? An analysis of na-
tional policy documents. Aust Health Rev 2018;42:627–634.
Quality Metric Incorporated. Quality Metrics Health Outcome Scoring
Software 5.1 User’s Guide. Lincoln, RI: Quality Metric Incorporated, 2017.
Qualtrics. Qualtrics. Utah: Qualtrics, 2018.
Saha R, Marions L, Tornvall P. Validity of self-reported endometriosis
and endometriosis-related questions in a Swedish female twin
cohort. Fertil Steril 2017;107:174–178.
Sensis. Sensis social media report. 2016. https://www.sensis.com.
au/asset/PDFdirectory/Sensis_Social_Media_Report_2016.PDF (9
December 2016, date last accessed).
Smith D, Harvey P, Lawn S, Harris M, Battersby M. Measuring
chronic condition self-management in an Australian community:
factor structure of the revised Partners in Health (PIH) scale. Qual
Life Res 2017;26:149–159.
Smith D, Lawn S, Harvey P, Battersby M. Concurrent validity of the
Partners in Health scale against general self-rated health in chronic
conditions: a short report. Chronic Illn 2019;15:74–77.
Stanford Patient Education Research Center. Chronic Disease Self-
Management Program Questionnaire Code Book. California: Stanford
University, 2007.
Young K, Fisher J, Kirkman M. Endometriosis and fertility: women’s
accounts of healthcare. Hum Reprod 2016;31:554–562.
Zondervan KT, Becker CM, Koga K, Missmer SA, Taylor RN, Viganò
P. Endometriosis. Nat Rev Dis Primers 2018;4:9.
Self-management of endometriosis and quality of life 655
D
ow
nloaded from
 https://academ
ic.oup.com
/hum
rep/article/36/3/647/6055872 by guest on 13 April 2021
https://www.abs.gov.au/ausstats/abs&hx0040;.nsf/mf/8146.0
https://www.abs.gov.au/ausstats/abs&hx0040;.nsf/mf/8146.0
https://www.abs.gov.au/ausstats/abs&hx0040;.nsf/mf/8146.0
http://www.health.gov.au/internet/main/publishing.nsf/Content/mbsprimarycare-chronicdiseasemanagement
http://www.health.gov.au/internet/main/publishing.nsf/Content/mbsprimarycare-chronicdiseasemanagement
https://www.sensis.com.au/asset/PDFdirectory/Sensis_Social_Media_Report_2016.PDF
https://www.sensis.com.au/asset/PDFdirectory/Sensis_Social_Media_Report_2016.PDF
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