Abstract
Background
Globally there is an increased prevalence of chronic conditions, which has a negative impact on quality of life (QOL)and places increased demand on the healthcare system. There is a need to understand the most suitable QOL instruments for adults with chronic health conditions in primary care settings to inform and evaluate tailored interventions. Aims of this study were to: (1) Examine and compare the QOL of middle and older aged adults with chronic conditions in primary care settings in South Australia; (2) Explore the feasibility and suitability of using the QOL-ACC in primary care settings, as compared with a more established instrument (the EQ-5D-5L).
Methods
A prospective cross-sectional study using an online survey was conducted in general practice primary care settings in Adelaide, Australia, with a measurement at one time-point between July 2023-February 2024. Inclusion criteria: People aged 40–85 years who had ≥ one chronic condition, who attended one of ten participating practices. Descriptive statistics were calculated for all utility scores on QOL measures, and a Mann-Whitney U Test for differences in these scores between the participants separated into two groups based on their age. Statistical significance was set at p < 0.05.
Results
Two hundred twenty-four participants completed surveys (mean (SD) age = 58.1 (9.5) years). A large proportion of participants indicated they had poor QOL in domains of Pain Management (43.8% had their pain well managed most of the time), Leisure Activities and Hobbies (31.3% most of the time, 21.9% some of the time) on the QOL-ACC; and moderate pain or discomfort (85.3%), anxiety and depression (62.5%), and performing their usual activities (49.1%) on the EQ-5D-5L, respectively. There were no significant differences in utility between the younger and older age groups for the EQ-5D-5L nor the QOL-ACC (except for the emotional wellbeing dimension).
Conclusions
The QOL-ACC is a feasible and suitable QOL measure to use in primary care settings. Further validation of the QOL-ACC with middle-older adults with chronic conditions in primary care is warranted.
Trial registration
Australian New Zealand Clinical Trials Registration Number: ACTRN12623000939695 Registration Date: 31/08/2023.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12875-025-03147-8.
Keywords: Chronic conditions, Health care services, Middle and older aged, Primary health care, Quality of life
Background
Chronic conditions have a substantial negative impact on quality of life (QOL) [1]. Globally, healthcare systems face increasing rates of chronic and complex diseases, posing significant clinical and economic challenges that hinder the optimal delivery of healthcare services [2]. Chronic conditions, also commonly referred to as noncommunicable diseases, are generally slow in progression, long in duration and require ongoing support and care [3, 4]. Common chronic conditions include cardiovascular disease, cancers, chronic respiratory diseases and asthma, and are collectively responsible for 74% of deaths worldwide [4]. Many people with chronic disease have more than one chronic condition, which is referred to as multimorbidity [5]. Internationally, population data related to chronic conditions and multimorbidity is examined from middle age, defined as 40 years and above [6]. It is estimated that between 51 and 75% of the Australian population overall have at least one chronic condition [7, 8] and in middle-age (defined as 45–64 years) specifically, 30% of the population have one, and a further 30% multiple, chronic conditions [9].
Care for most chronic conditions is provided through primary health care settings by general practitioners (GPs), primary care nurses and allied health professionals [10]. In the Australian primary care context, over half of patients of GPs have at least one chronic condition [7, 11]. Effective primary health care can reduce unnecessary hospital admissions, and improve health outcomes [10]. Due to the complexity of managing people with multiple chronic conditions, effective interventions are most likely to be complex, multifaceted and require the need to be person centred to address the combined needs of individuals [12]. A Cochrane systematic review found that evidence supports the use of interventions that are targeted at the management of multiple specific risk factors (for example diabetes and depression or heart disease), or focused on areas where people have difficulties, such as with functional ability or medicines management, with multidisciplinary interventions [12]. Despite this, there is limited literature that considers economic analysis in chronic condition interventions, despite the recognised health burden on individuals and health systems, to inform policy makers decisions of where to invest in health services [12].
Improving and maintaining QOL is acknowledged as the ultimate aim of healthcare according to the World Health Organization (WHO), especially care for people living with chronic conditions [13, 14]. QOL is usually assessed through self-report of an individual, and at a conceptual level incorporates a person’s own judgement of their current health and wellbeing in comparison to their expectations for themselves. Practically, individuals self-report their QOL most commonly using one of the many available questionnaires designed for this purpose [15]. Over the past 20 years, many systematic reviews have identified the consistent inverse relationship between chronic conditions, multimorbidity and QOL [6, 16–18]. Studies have found the negative impact of chronic conditions on QOL across middle aged adults (40–65 years) [6, 19, 20] and older adults (65 + years) [16, 17, 19, 21, 22]. Predominantly in the literature, chronic conditions (particularly multimorbidity) are associated with a reduced QOL with a strong association on the physical domains [16, 18, 21, 23], however there is lack of clarity on the relationship between chronic conditions and social or psychological domains of QOL [18, 24].
Internationally there is significant heterogeneity in the use of instruments to measure QOL with chronic conditions in the published literature [16]. The most commonly used instruments include the Short Form Health Survey instruments [25], and EuroQOL scales, for example the EQ-5D-5L questionnaires [16–18, 26]. These instruments are long-standing and have been widely used in the literature, but have generally been developed with a ‘top-down approach’ where researchers or other experts decide which aspects of QOL are important to include and how to measure them [27]. While instruments like the EQ-5D-5L have been extensively validated and used in the literature among a range of populations experiencing acute conditions, exploration of the EQ-5D-5L across more complex populations (such as older people with multimorbidity receiving aged care services) has highlighted different interpretations of the questions, with the dimensions of mobility, usual care and personal care having the most response issues [28]. The EQ-5D-5L also has a focus on physical health, using language common in medical contexts – such as mobility, pain, and anxiety/depression.
By comparison, the recently developed Quality of Life Aged Care Consumers (QOL-ACC) instrument was developed with a ‘bottom-up approach’, from its inception with older people receiving long-term care services. Extensive qualitative research with older people was undertaken as the first stages of its development, to identify the aspects of QOL which were important to include, and to inform the language used in the measure [29]. Particularly the qualitative foundation for the QOL-ACC highlighted the importance of positive framing (i.e. focusing on what the person is able to do, rather than their limitations) in measuring QOL of older people. Older people also highlighted how important it was that questions were structured such that a chronic health condition or poor health due to the aging process itself would not necessitate a poor rating of QOL, but that people are able to reflect in the measure when they are able to continue to maintain their QOL in spite of health challenges. Additionally, the qualitative work enabled the QOL-ACC to draw on the language of older people to best describe the domains of QOL. For example, the instrument doesn’t use the terms depression or anxiety or mental health, as older people during the qualitative phase felt these terms were stigmatising. The QOL-ACC has been extensively validated within the long-term care system for older people, with people receiving care both at home and in residential facilities. It has been implemented as part of the National Mandatory Quality Indicator Program for Aged Care services in Australia since 2023 [30, 31]. Similarly to the EQ-5D-5L, it is suitable for use in economic evaluation of healthcare interventions, in the cost-utility analysis (CUA) framework, the ‘gold standard’ of economic evaluation which forms part of the systems for approving new healthcare interventions or pharmaceuticals for provision via public funds in Australia, as well as other countries around the world [32–35]. However to date, feasibility and suitability of using the QOL-ACC in primary care settings for people with chronic conditions has not been evaluated.
Therefore, there is a need to understand the most suitable QOL instrument for adults with chronic health conditions in primary care settings. Particularly there is a need to understand how the responses to a questionnaire developed with a ‘bottom-up’ approach and a focus on more diverse dimensions of QOL differ to responses to a traditional health-related QOL questionnaire, with more medical-focused technology and developed without significant consumer input. The aims of this study were to: (1) To examine and compare the QOL of middle and older aged adults with chronic conditions in primary care settings in South Australia; (2) To explore the feasibility and suitability of using the QOL-ACC in primary care settings, as compared with a more established instrument (the EQ-5D-5L).
Methods
Study design
This prospective cross-sectional study was conducted in general practice primary care settings in Adelaide, Australia, with a measurement at one time point between July 2023 to February 2024. Ethics approval was gained through the Flinders University Human Research Ethics Committee (ID number 6132).
Participants and setting
The population included a convenience sample of people aged 40–85 years, representing a middle aged and older aged population, who self-identified as having ≥ one chronic conditions on attendance in general practices. The context for this data collection was a funded Australian Government quality improvement project for early ageing initiatives in primary care. Ten general practices in the Adelaide metropolitan region of Australia were purposefully selected by the Adelaide PHN and consented to participate. These ten general practices were selected to give geographical representation across the region and included high numbers of people attending the practice with chronic disease.
The Adelaide PHN is one of two PHNs in the state of South Australia, one of 31 across Australia. PHNs are independent organisations that are funded to coordinate primary health care, whose function is to assess the needs of their community and commission health services to provide coordinated care to people in their region [36]. It is estimated that 1.3 million people reside in the Adelaide PHN region, 5% of the total Australian population with the median age of 39 years [37]. In 2021, people aged 60 years and older constituted approximately 25% of the region’s population, slightly higher than the proportions nationally (23% respectively) [37].
Procedure
An online survey was distributed via Qualtrics [38] to targeted patients of general practices meeting the eligibility criteria. Practice managers, practice nurses, and GPs promoted uptake of the survey to patients with chronic conditions during their primary care consultations. Flyers promoting the survey were also distributed within the waiting rooms of the general practices. If patients preferred to complete a paper copy of the survey, this was provided by the practice staff and stored for collection by the research team and entered manually into Qualtrics. Survey data responses were anonymous. Participant information was provided as a preamble to the survey. All participants provided informed consent to participate in commencement of the online survey, prior to completion.
Measurements and instruments
Participants were asked to specify their age, and then completed the QOL questionnaires. Firstly, participants were asked to complete the QOL-ACC, which was recently developed to measure QOL among older people receiving aged care services, and is suitable for application in economic evaluation. The QOL-ACC descriptive system is a six-item questionnaire each with five possible response levels, ranging from the person experiencing the best possible experience in that domain all of the time (considered the best possible response), most of the time, some of the time, a little of the time or none of the time (worst possible response). The QOL-ACC can be self-administered, and covers six dimensions of QOL (Mobility, Pain management, Emotional Wellbeing, Independence, Social connection and Activities). It was developed from first principles with older people through extensive qualitative research [29, 39, 40]. The QOL-ACC has been extensively validated for use in older people receiving aged care services both in the community and in residential settings [30, 41]. The QOL-ACC also has an associated general population preference-based scoring algorithm, which can be used to generate utility scores for participant responses to the questionnaire anchored on a 0 to 1 score, where 0 indicates a state equivalent to death, and 1 indicates a state equivalent to living in full health [42]. Negative values to -0.56 are possible indicating a state considered worse than death.
Participants were also asked to complete the EQ-5D-5L. The EQ-5D-5L is a widely used measure of QOL, originally developed in 1990 for use with the adult population with three potential levels of response to each of the five questions. It has since been updated to have five possible levels of response (ranging from no problems with that particular item, to severe problems/unable to perform that particular item) to make the instrument more sensitive to change in QOL over time [43]. The descriptive system covers five dimensions including Mobility, Self-care, Usual activities, Pain and Discomfort, and Anxiety and Depression [26]. It has been widely validated with a range of populations, and similarly to the QOL-ACC, it has an associated general population preference-based algorithm which can generate utility scores on the scale between 0 and 1 for a range of different countries [26]. Our study has used the algorithm developed by Norman and Colleagues for Australia [44]. The EQ-5D-5L also contains a visual analogue scale [45], where participants are asked to rate their general health today on a scale between 0 (indicating the worst health you can imagine) and 100 (indicating the best health they can imagine). The EQ-5D-5L has been applied extensively in many countries, and population ‘norms’ are available for comparison [45].
Statistical analysis
Responses to the QOL-ACC and EQ-5D-5L were reported for the entire sample, and for two subgroups defined according to the age of the respondent. Frequencies were reported for all given levels, as well as dichotomized into no problems (Level 1) vs. any problems (response levels 2 to 5) as is standard practice in reporting the results of the EQ-5D-5L [26]. The age subgroups were defined as younger age group (those aged between 40 to less than 65 years old), and older age group (those aged from 65 to 85 years old). Chi-squared test for independence was used to test for any relationship between age group and responses to the QOL-ACC and EQ-5D-5L. We also generated utility scores for the QOL-ACC and EQ-5D-5L for each participant. Given the skewed nature of the data (as expected for QOL scores), we report both measures of central tendency including both mean, standard deviation, median and interquartile range for the utility scores for both instruments, and the EQ-5D-5L VAS scores. This is reported for the entire sample and the two subgroups according to age additionally, and Mann-Whitney U Test is used to test for significant differences in these scores between the two age groups. Finally, the utility scores for both instruments and for the EQ-5D-VAS for all participants are presented in histograms. We assessed the feasibility of using the QOL-ACC in primary care settings drawing on the COSMIN guidelines for evaluating measurement properties of person-reported instrument and Classical Test Theory Based psychometric properties [46, 47]. For example, that the percentage of missing data for the items of the questionnaire are less than 5%, that participants report across the wide range of possible responses of the questionnaire, and that reporting is broadly consistent across both questionnaires, unless there is a priori hypothesis as to why the two measures may perform differently. For example, we expected that the positive framing in the mobility question may result in more people reporting higher levels of QOL using the QOL-ACC than for the EQ-5D-5L. Additionally, we expected that the framing of the pain management question in the QOL-ACC (focusing more on the good management of pain rather than the complete absence of pain) would result in a high level of QOL than when using the EQ-5D-5L. Additionally, we expected that more people would be willing to report lower levels of Emotional Wellbeing using the QOL-ACC than when using the EQ-5D-5L due to the stigma people may feel about self-reporting they experience anxiety/depression. Statistical significance was set at p < 0.05.
Results
Two hundred and twenty four people completed both the QOL-ACC and EQ-5D-5L questionnaires. The average age of participants was 58.1 years (SD 9.5).
Table 1 gives the responses to the QOL-ACC for the entire sample, plus the younger age group (those aged between 40 to ≤ 64 years old), and older age group (those aged from 65 to 85). Over half of participants rated themselves as at the best possible level for the domains of Mobility, Social relationships and Independence. By comparison, evidence of impaired QOL was greater for the domains of Pain Management (only 25% of participants rated their pain as well managed all of the time), and Leisure Activities and Hobbies (30% rated themselves as having leisure activities/hobbies they enjoyed all of the time). Significantly, only 17% of participants rated themselves as generally happy all of the time (Emotional Wellbeing item of the QOL-ACC). We found no significant differences in responses to the QOL-ACC by age group excepting for the Emotional Wellbeing item, with a higher proportion older people exhibiting no limitations to their Emotional wellbeing (25%) as compared to our younger age group (14%).
Table 1.
Reponses to QOL-ACC (frequency and %) for the total sample, plus the two age groups
| Dimension | Level | Total sample (n = 224) |
Young Age Group
40-≤64 years (n = 156) |
Old Age Group
65 − 85 years (n = 68) |
Chi-Squared test (p-value) |
|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | |||
| Mobility | All the time | 147(65.6) | 106 (67.9) | 41 (60.3) | 8.53 (0.074) |
| Most of the time | 51(22.8) | 32 (20.5) | 19 (27.9) | ||
| Some of the time | 12(5.4) | 11 (7.1) | 1 (1.5) | ||
| A little of the time | 4(1.8) | 1 (0.6) | 3 (4.4) | ||
| None of the time | 10(4.5) | 6 (3.8) | 4 (5.9) | ||
| Pain Management | All the time | 57(25.4) | 35 (22.4) | 22 (32.4) | 4.84 (0.304) |
| Most of the time | 98(43.8) | 71 (45.5) | 27 (39.7) | ||
| Some of the time | 44(19.6) | 31 (19.9) | 13 (19.1) | ||
| A little of the time | 19(8.5) | 13 (8.3) | 6 (8.8) | ||
| None of the time | 6(2.7) | 6 (3.8) | 0 (0.0) | ||
| Emotional wellbeing | All the time | 38(17) | 21 (13.5) | 17 (25.0) | 9.36 (0.025) |
| Most of the time | 134(59.8) | 99 (63.5) | 35 (51.5) | ||
| Some of the time | 44(19.6) | 33 (21.2) | 11 (16.2) | ||
| A little of the time | 8(3.6) | 3 (1.9) | 5 (7.4) | ||
| None of the time | |||||
| Independence | All the time | 135(60.3) | 94 (60.3) | 41 (60.3) | 1.77 (0.778) |
| Most of the time | 67(29.9) | 49 (31.4) | 18 (26.5) | ||
| Some of the time | 16(7.1) | 9 (5.8) | 7 (10.3) | ||
| A little of the time | 3(1.3) | 2 (1.3) | 1 (1.5) | ||
| None of the time | 3(1.3) | 2 (1.3) | 1 (1.5) | ||
| Social Relationships | All the time | 121(54) | 82 (52.6) | 39 (57.4) | 3.25 (0.518) |
| Most of the time | 76(33.9) | 54 (34.6) | 22 (32.4) | ||
| Some of the time | 21(9.4) | 16 (10.3) | 5 (7.4) | ||
| A little of the time | 5(2.2) | 4 (2.6) | 1 (1.5) | ||
| None of the time | 1(0.4) | 0 (0.0) | 1 (1.5) | ||
| Leisure Activities/Hobbies | All the time | 69(30.8) | 45 (28.8) | 24 (35.3) | 3.222 (0.521) |
| Most of the time | 70(31.3) | 48 (30.8) | 22 (32.4) | ||
| Some of the time | 49(21.9) | 38 (24.4) | 11 (16.2) | ||
| A little of the time | 27(12.1) | 20 (12.8) | 7 (10.3) | ||
| None of the time | 9(4) | 5 (3.2) | 4 (5.9) |
Table 2 gives the responses to the EQ-5D-5L for the total sample and subgroups defined by age. Consistent with the findings when using the QOL-ACC, there was also evidence of impaired health-related QOL when participants used the EQ-5D-5L, with around half or more of participants reporting some level of problem (i.e. either slight problems, moderate problems, severe problems or extreme problems/unable) with Pain or Discomfort (85.3%), Anxiety and Depression (62.5%), performing their Usual Activities (49.1%). We note however a significant proportion of participants (44%) reported either slight Pain/Discomfort (44%) or moderate Pain/Discomfort (27.2%). A lower proportion of the sample reported no problems with their mobility when using the EQ-5D-5L (i.e. 53% compared with 66% for the QOL-ACC). Interestingly, a larger proportion of participants rated themselves as experiencing the best possible level on the EQ-5D-5L Anxiety/Depression item (37.5%) compared with the QOL-ACC (17%). There were no significant differences in responses to the EQ-5D-5L by age group for any of the dimensions.
Table 2.
Reponses to EQ-5D-5L (frequency and %) for the total sample, plus the two age groups
| Dimension | Level | Total sample |
Young Age Group
40-≤64 years (n = 156) |
Old Age Group
65 − 85 years (n = 68) |
Chi squared (p-value) |
|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | |||
| Mobility | No Problems | 119(53.1) | 84 (538) | 35 (51.5) | 2.1 (0.760) |
| Slight problems | 60(26.8) | 42 (26.9) | 18 (26.5) | ||
| Moderate problems | 27(12.1) | 18 (11.5) | 9 (13.2) | ||
| Severe problems | 15(6.7) | 9 (5.8) | 6 (8.8) | ||
| Unable | 3(1.3) | 3 (1.9) | 0 (0) | ||
| Self-care | No Problems | 188(83.9) | 130 (83.3) | 58 (85.3) | 2.8 (0.590) |
| Slight problems | 23(10.3) | 17 (10.9) | 6 (8.8) | ||
| Moderate problems | 9(4) | 7 (4.5) | 2 (2.9) | ||
| Severe problems | 3(1.3) | 1 (0.6) | 2 (2.9) | ||
| Unable | 1(0.4) | 1 (0.6) | 0 (0.0) | ||
| Usual activities | No Problems | 114(50.9) | 78 (50.0) | 36 (52.9) | 2.0 (0.733) |
| Slight problems | 64(28.6) | 46 (29.5) | 18 (26.5) | ||
| Moderate problems | 28(12.5) | 18 (11.5) | 10 (14.7) | ||
| Severe problems | 15(6.7) | 11 (7.1) | 4 (5.9) | ||
| Unable | 3(1.3) | 3 (1.9) | 0 (0.0) | ||
| Pain/Discomfort | No pain or discomfort | 33(14.7) | 23 (14.7) | 10 (14.7) | 2.4 (0.665) |
| Slight pain or discomfort | 99(44.2) | 73 (46.8) | 26 (38.2) | ||
| Moderate pain or discomfort | 61(27.2) | 41 (26.3) | 20 (29.4) | ||
| Severe pain or discomfort | 27(12.1) | 16 (10.3) | 11 (16.2) | ||
| Extreme pain or discomfort | 4(1.8) | 3 (1.9) | 1 (1.5) | ||
| Anxiety/Depression | Not anxious or depressed | 84(37.5) | 53 (34.0) | 31 (45.6) | 3.7 (0.449) |
| Slightly anxious or depressed | 79(35.3) | 59 (37.8) | 20 (29.4) | ||
| Moderately anxious and depressed | 47(21) | 33 (21.2) | 14 (20.6) | ||
| Severely anxious or depressed | 12(5.4) | 9 (5.8) | 3 (4.4) | ||
| Extremely anxious or depressed | 2(0.9) | 2 (1.3) | 0 (0.0) |
Table 3 gives the comparison of the utility scores derived from the QOL-ACC and EQ-5D-5L and EQ-5D-VAS for the total sample and two age groups. Mean and median utility measured using the QOL-ACC was higher (0.777 and 0.832 respectively) compared to those measured using the EQ-5D-5L (0.637 and 0.704). There were no significant differences in utility between the younger and older age groups for either the QOL-ACC or EQ-5D-5L. For both instruments, responses covered a large proportion of the possible range, with range of utility scores generated by the QOL-ACC instrument covering from − 0.428 to 1, for the EQ-5D-5L from 0.033 to 1 and the total possible 0 to 100 for the EQ-5D-VAS.
Table 3.
Comparison of QOL-ACC and EQ-5D-5L utility and VAS scores for the two age groups
| Measure | Total Sample | Young age group | Old age group | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| N | Mean (SD) | Median (IQR) | N | Mean (SD) | Median (IQR) | N | Mean (SD) | Median (IQR) | Mann-Whitney U Test (p-value) | |
| EQ-5D-5L VAS | 224 | 73.1 (19.3) | 90 (80) | 156 | 72.7 (19.3) | 80 (25) | 68 | 74.0 (19.3) | 80 (30) | 5097 (0.642) |
| EQ-5D-5L utility | 224 | 0.637 (0.302) | 0.704 (0.349) | 156 | 0.631 (0.304) | 0.675 (0.33) | 68 | 0.652 (0.300) | 0.728 (0.39) | 5049 (0.568) |
| QOL-ACC Utility | 224 | 0.777 (0.201) | 0.832 (0.264) | 156 | 0.779 (0.198) | 0.827 (0.24) | 68 | 0.773 (0.210) | 0.841 (0.28) | 5274 (0.946) |
Figures 1, 2 and 3 show histograms of the utility scores generated from the EQ-5D-5L VAS, the QOL-ACC, and EQ-5D-5L scores. As expected with QOL data, they display a significantly skewed character, with a large proportion of respondents clustered towards the right-hand side of the scale (indicating they experience fairly good QOL and health, as is expected in community dwelling Australian populations). However, the histograms also demonstrate the large variability in self-reported health and QOL within this sample, covering the entire range of possible responses on the instruments, including scores on or near to zero (indicating a health state equivalent to death) and negative values (which indicate a health state considered worse than death).
Fig. 1.
Histogram of the distribution of EQ-5D-5L-VAS Scores for all ages
Fig. 2.
Histogram of the distribution of the EQ-5D-5L utility scores for all ages
Fig. 3.
Histogram of the distribution of the QOL-ACC utility scores for all ages
Discussion
This study examined the QOL of middle and older aged adults with chronic conditions in general practice primary care settings in South Australia. Our study makes several key contributions to the evidence base in this area. Firstly, community dwelling adults with chronic conditions experienced particularly low QOL levels compared with a representative sample of the Australian population, across both the middle-aged and older-aged subgroups. We note similar distribution of limitations to the domains of Mobility and Independence as sample of over 1,000 older people living in residential aged care [48]. Concerningly, we identified higher levels of limitation in the domains of Pain Management, Emotional Wellbeing, Social Relationships, and Leisure activities/Hobbies in our community-dwelling sample of adults aged between 40 and 85 years, than in the sample reported by Huang et al. [48], all drawn from residential aged care and aged between 82 and 93 years. It should be noted that residential aged care is generally reserved for older adults with significant health and care needs in Australia, with the vast majority of care for older people occurring within their own homes in the community. When considering older people receiving care services at home, our study of over 200 older adults demonstrated similar levels of impairment in the domains of Mobility, Emotional Wellbeing, Social Relationships, and Leisure Activities/Hobbies to older adults receiving the Commonwealth Home Support Programme (the basic “entry-level” of aged care provided in Australia) [30] but better responses than those receiving the Home Care Package program (which provides a greater level of care with more restrictions for entry than the Commonwealth Home Support Program). Another study reporting QOL measured by the QOL-ACC among older people receiving aged care services at home, reported a mean utility value of 0.69 (SD 0.25) [49]. These findings confirm previous studies on the significant impact of chronic conditions on QOL for middle and older aged adults [6, 16, 17, 19, 22]. Additionally, the limitations to QOL identified in our middle-aged sample highlight the importance of measuring QOL for people with chronic conditions early, commencing in middle-age, to provide an opportunity to implement appropriate strategies and evaluate their effectiveness in enhancing QOL.
Secondly, our sample experienced particularly marked QOL deficits across the QOL-ACC dimensions of Pain Management, and Leisure Activities/Hobbies and across the EQ-5D-5L dimensions of Pain/Discomfort, Anxiety/Depression, and Usual Activities. Thus, our sample of community dwelling middle and older aged adults with chronic conditions appear to be experiencing higher levels of limitations in domains such as Pain Management, Emotional Wellbeing, Social Relationships, and Leisure Activities/Hobbies than older adults with significant health and care needs necessitating admission to permanent residential aged care is concerning [48]. It potentially highlights significant gaps in provision of care to middle and older adults with chronic conditions in these domains, particularly care focusing beyond ‘physical’ health such as in wellbeing, engagement, community connection and purpose. These findings are a significant addition to the literature, which has previously focused on the physical health deficits and their impact on QOL in people living with chronic conditions [16, 21, 23], particularly in primary care [18]. Our findings indicate that future work should consider a focus on engagement in leisure activities, social inclusion, and primary care interventions for pain management, anxiety and depression for people with chronic conditions, alongside the traditional focus on the management of physical health symptoms.
Thirdly, the QOL-ACC and EQ-5D-5L both generally demonstrated satisfactory performance in measuring the QOL for this sample. Both instruments had high rates of completion with no missing data, and provided similar information on QOL in the samples, except for differences which were in line with expectations of the authors. We expected to see lower levels of limitations reported using the QOL-ACC compared to the EQ-5D-5L for the domains of Mobility and Pain Management or Pain/Discomfort due to wording which allowed participants to include their walking aids in their mobility considerations and the quality of the management of their pain rather than its presence or absence per se. Additionally we expected to see a greater level of reporting of limitations to Emotional Wellbeing using the QOL-ACC than for the Anxiety/Depression item when using the EQ-5D-5L due to the use of language which is less stigmatising for older people in the QOL-ACC than that used in the EQ-5D-5L. All three of these hypotheses appeared to be supported by our data.
However, it is notable that for the EQ-5D-5L there were no differences between the older and younger age groups in the responses to the mobility dimension, compared to the pattern seen with the QOL-ACC mobility item, where a significantly higher proportion of older people reported limitations to their mobility than for the younger age group. This finding could be due to the differences in the wording of the questions across the two instruments – the QOL-ACC Mobility item specifically asks participants to consider their mobility when using their regular mobility aid (e.g. a four-wheeled walker, wheelchair) based on the feedback from older people during the qualitative stages of the instrument development. By comparison, the EQ-5D-5L does not specify how to answer the question if a mobility aid is used. This ambiguity may lead to participants reporting their mobility as impaired despite their mobility aid providing support for their independent mobility, and in turn improving their day to day QOL, as identified in a previous study with older adults in residential long-term care services [28]. This requires further exploration, as previous research exploring QOL for people with chronic conditions (particularly multimorbidity), found that a reduced QOL was associated with physical domains [16, 18, 21, 23]. For these reasons, the QOL-ACC may be a more appropriate instrument to use for adults with chronic conditions in primary care [24]. Further validation of the QOL-ACC with middle-older adults with chronic conditions in primary care and community settings is recommended.
Limitations
The sample may not be representative of the entire population of middle-older adults with chronic conditions in Adelaide region or more broadly. Sample participants were not asked to specify the type and duration of the chronic conditions, hence characteristics of diseases, such as type of illness, duration and severity of symptoms, are not known. These factors could influence QOL, and it is recommended that future research exploring QOL measurement in chronic conditions, include these characteristics in data collection to allow more nuanced comparisons, and further demographic information including gender, socioeconomic status and ethnicity which has been shown to influence QOL.
However, despite these limitations this research adds knowledge by demonstrating the real-world application of collecting QOL in the primary care setting, with 224 participants completing both the EQ-5D-5L and the QOL-ACC with no missing data. This study provides information about the relationship between chronic conditions and social or psychological domains of QOL, which has been less understood [18, 24]. Interestingly in this study, Anxiety and Depression was more highly reported in this group, compared to previous explorations of QOL and older people who generally under-report psychological symptoms [50, 51].
Further investigation of the QOL-ACC’s psychometric validity with middle-older adults with chronic conditions in primary care and community settings, including larger sample sizes, gender differences, discriminant validity and responsiveness to change, is indicated. An increased understanding of the most valid QOL, or combination thereof, to use for people with chronic conditions across the ageing trajectory will support not only more tailored personalised interventions, but also enable a more systematic approach to evaluating their effectiveness in terms of health outcomes and economic evaluations, including cost-utility [52]. This will support policy makers in decisions of where to provide investment in intervention approaches to optimise health care services and promote QOL outcomes for people with chronic conditions.
Conclusions
QOL levels are particularly low for middle and older aged adults with chronic conditions within general practice primary care settings, irrespective of age. Our findings support the feasibility and suitability of using the QOL-ACC measure in primary care settings. Further validation of the QOL-ACC with middle-older adults with chronic conditions in primary care is warranted.
Supplementary Information
Acknowledgements
The authors acknowledge the ten general practices who participated in this project and assisted with survey distribution including those which consented to being acknowledged : Allcare Medical Centre, Chandlers Hill Surgery, Firle Medical Centre, Galway Medical Centre, Health Sense Medical Centre Golden Grove, Morphett Vale Family Practice and Woodville South General Practice. The authors acknowledge consultants involved in this project: Mitch Fox (BHSc MBA, Director of Simple Healthcare Solutions); Dr Chris Bollen (MBBS MBA FRACGP FACHSM, Director Bollen Health), and Jane Bollen (RN, Cert IV TAE, Dip(Acct), GAICD, Nurse Consultant Bollen Health).
Abbreviations
- VAS
Visual Analogue Scale
- GPs
General Practitioners
- QOL
Quality of life
- QOL
ACC–Quality of Life Aged Care Consumers
- PHN
Primary Health Network
- WHO
World Health Organization
Authors’ contributions
SG, SN, HB, AS, MF and RM were involved in the study conceptualisation, design and methodology. HB facilitated data collection. RM and MF conducted data analysis. SG, SN, HB, AS, MF, ED, AD and RM authors interpreted findings, contributed to writing the manuscript, read and approved the final manuscript.
Funding
This research was supported with funding by the Adelaide Primary Health Network.
Data availability
The data is not available on a public platform.
Declarations
Ethics approval and consent to participate
Ethics and consent to participate was approved This research has been performed in accordance with the Declaration of Helsinki with ethics approval through Flinders University Human Research Ethics Committee (ID number 6132).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Supplementary Materials
Data Availability Statement
The data is not available on a public platform.