Sage Journals: Discover world-class research

Abstract

Objectives

To examine whether illness or healthcare experiences have a more significant influence on living well, and which factors in these experiences have the most influence.

Methods

Information collected included demographic data, illness and healthcare experience, and the LTCQ to measure living well. Data was collected via online survey platform Qualtrics. Two separate 2-stage hierarchical multiple regressions were run to investigate how much variance in living well with long-term conditions is accounted for by established and exploratory illness and healthcare experience factors.

Results

70 participants met the inclusion criteria of the study, with 54 included in the analysis. Results showed that illness experience had a significant influence on living well while healthcare experience did not. The factors of illness intrusiveness in illness experience and patient assessment of chronic illness care in healthcare experience significantly impacted living well.

Discussion: This study examines the influences of illness and healthcare experiences on the ability to live well with LTCs. Future research could focus on specific LTCs and compare which factors they find significantly affect living well. The findings pave the way for future explorations into the factors influencing living well differ between LTCs and the best interventions to improve living well with LTCs.

Keywords

Long-term conditions healthcare experience illness experience living well quality of life

Living with health conditions can prominently affect an individual's life, particularly if they have a long-term condition (LTC). In the United Kingdom, almost half of the population report having an LTC, which is a condition that cannot currently be cured but is controlled by medication/other treatment.^1,2 LTCs affect quality of life by limiting activities and worsening mental well-being.^2,3 Quality of life is an individual's perceptions of their position and feeling of overall satisfaction in their life. This concept was expanded on to include the impact that someone's ailment has on different aspects of their life, creating health-related quality of life (HR-QOL).⁴

Recently, HR-QOL has shifted to ‘living well’, particularly living well with an LTC.^5,6 Potter et al. built on this by including not only traditional HR-QOL domains, but also treatment burden and confidence in self-management.⁷ When defining living well, the inclusion of patients’ perspectives allows for inclusive terminology and patient-centred care to be emphasised. Living well with an LTC is measured by the recently developed Long-Term Conditions Questionnaire (LTCQ).⁷ The holistic nature of this questionnaire makes it suitable to use in clinical settings, such as the National Health Service (NHS).

Research on factors impacting living well is in its infancy. While biomedical factors have been explored, emerging evidence suggests further multidimensional interpersonal and psychosocial variables can play a role.^5,6 Therefore, the overarching themes of illness experience and healthcare experience were created to categorise these. Within these, some factors are already established with a multitude of research from a wide range of that emphasised their impact on HR-QOL, while exploratory factors had limited research, focusing on a single condition or area of QOL.⁷

Illness experience contains the established factors of illness intrusiveness, social/role activities limitations, and a negative perception of the illness. Illness intrusiveness is the perceived interference an LTC has on daily life, and has been associated with increased fatigue and worsened physical and mental HR-QOL.⁸ Further research also shows that having a social support network is positively associated with HR-QOL while the stronger the negative perceptions of the illness, the worse the HR-QOL.^9,10 These factors represent aspects of the illness experience, that with further support in a community and healthcare setting, can be positively changed. For example, as the number of LTCs increases with age, older adults experience events such as retirement, death of a spouse, and children leaving the home, lessening their opportunities to participate in social settings.¹⁰ This is a relatively curable hindrance with additional community support programmes. Exploratory factors are energy balance behaviours and pain severity, both of which are subjective and under-researched.^11,12 Research into health distress has been limited to specific conditions, finding that untreated diabetes distress correlates with impaired HR-QOL.^11–13

Healthcare experience includes the established impactful factor of healthcare utilisation, while a lesser established exploratory factor is patient assessment of chronic illness.^14,15 These are significantly more difficult to improve at a fundamental level but lay the foundation for any form of healthcare experience. When examining demographic factors, established variables include the impact of age and socio-economic status, contrasting age at diagnosis and duration/length of LTC, which are exploratory in nature.^16–18

The present study will compare the effects of illness experiences and healthcare experiences on living well with LTCs to examine which factors have a more significant influence on living well. Findings will allow healthcare providers to prioritise exploring focused interventions to target these factors and consequently improve patients’ living well with their LTC.

Methods

Participants

Participants were recruited via social media, posters, and the survey exchange websites. Undergraduate students were recruited through research credit schemes. The study was approved in accordance with the Research Ethics Policy of the University of Chichester.

Of 129 participants who agreed to take part in the study, 70 fit the inclusion criteria of identifying as having a LTC not considered a disability (54%). Among those who fit the criteria, 16 participants did not complete the full questionnaire, resulting in 54 participants being included in the analysis (42% of the original sample). Participants confirmed they had an LTC that they did not define as a disability. Due to sensitivity and stigma around visible and invisible LTCs, participants were not required to reveal their condition.¹⁹ 27.8% of participants were students at the University of Chichester.

Of the analysed data, mean age was 37 years (SD = 14.85, range = 18–71), 80% were female and 99% were cisgender. Participants socio-economic status ranged from 0 (least money, little education, no job) and 9 (most money, highest amount of schooling, respected jobs) on the socio-economic ladder (M = 5.20, SD = 1.78). Participants age at diagnosis ranged from 1 to 60 (M = 24.65, SD = 14.45), while their duration of LTC ranged from 1 year to 54 years (M = 14.11, SD = 12.36). 55.7% of participants identified as heterosexual and 67.1% were white British [See Appendix 1].

Materials

Demographic data included age, sex, gender, sexual orientation, ethnicity, socio-economic status, age at diagnosis of LTC, and duration of LTC [See Appendix 2].

The Adapted Illness Intrusiveness Scale

^20,21 The Adapted Illness Intrusiveness Scale consists of participants indicating their level of agreement with the statement “How much does your illness(es) and/or its treatment interfere with:” for items such as “Your feeling of being healthy?”.

The Energy/Fatigue Scale

^22,23 The Energy/Fatigue Scale consists of participants indicating their level of agreement with the statement “How much time during the past 4 weeks…” for items such as “Did you feel worn out?”.

The Pain Severity Scale

^22,23 The Pain Severity Scale consists of participants rating the severity, frequency, and length of physical discomfort or pain.

The Health Distress Scale

^22,23 The Health Distress Scale consists of participants indicating their level of agreement with the statement “How much time during the past month…” for items such as “Were you discouraged by your health problems?”.

The Social/Role Activities Limitations Scale

²³ The Social/Role Activities Limitations Scale consists of participants indicating their level of agreement with the statement “During the past 4 weeks, how much…” for items such as “Has your health interfered with your hobbies or recreational activities?”.

The Brief Illness Perceptions Questionnaire

²⁴ The Brief Illness Perceptions Questionnaire consists of participants choosing the number that best corresponded to their views.

The Healthcare Utilisation Scale

^23,25 The Healthcare Utilisation Scale consists of participants indicating their answers with a number of visits/times/nights.

The Patient Assessment of Chronic Illness Care Scale

²⁶ The Patient Assessment of Chronic Illness Care Scale consists of participants indicating their level of agreement with the statement “Over the past 6 months, when I received care for my chronic conditions, I was:” for items such as “Asked for my ideas when we made a treatment plan.”.

The Long-Term Conditions Questionnaire

⁷ The LTCQ consists of participants indicating their level of agreement with the statement “Please think about your long-term health condition(s) over the past four weeks. How often have you…” for items such as “Felt able to cope well with your health condition(s)?”.

Procedure

Participants completed the survey using the platform Qualtrics.²⁷ Participants read the information surrounding the research, their right to withdraw, and consented [See Appendix 3]. Participants answered a series of questionnaires and were fully debriefed. All participants were signposted to support for LTCs in and outside the university and given the contact details of the researcher.

Data analysis

The independent variables were divided into two categories: illness experience and healthcare experience. Of these two categories, the variables were categorised as either an established factor in block one, or an exploratory factor in block two (see Table 1).

Table 1.
Factors of illness and healthcare experience categorised into established and exploratory for the regression models.

Illness Experience Healthcare Experience

Established Exploratory Established Exploratory

Illness Intrusiveness Energy Healthcare Utilisation Patient Assessment of Chronic Illness Care

Social/Role Activities Limitations Pain Severity Age Age at Diagnosis

Illness Perception Health Distress Socio-Economic Status Length of LTC

Pearson's correlation coefficient

All statistical analyses were completed in SPSS.²⁸ A Pearson's correlation coefficient was conducted to investigate the extent of association between variables and the degree of variation (see Tables 2 and 3).

Table 2.
A correlation matrix for illness experience variables.

Factor Mean (SD) Living Well Illness Intrusiveness Energy Pain Severity Health Distress Social/Role Activities Limitations Illness Perception

Living Well 59.05 (16.58) x

Illness Intrusiveness 34.59 (12.10) −.70 x

Energy 2.08 (.86) .45 −.45 -

Pain Severity 3.69 (1.32) −.43 .51 −.55 x

Health Distress 3.26 (1.11) −.53 .60 −.42 .50 x

Social/Role Activities Limitations 2.56 (1.05) −.61 .77 −.50 .63 .70** x

Illness Perception 47.65 (7.69) −.29* .45** −.24* .42 .42 .46** x

p < .05, p < .001

d.f. = 54

Table 3.
A correlation matrix for healthcare experiences variables.

Factor Mean (SD) Living Well Healthcare Utilisation 1 Healthcare Utilisation 2 Healthcare Utilisation 3 Healthcare Utilisation 4 Patient Assessment of Chronic Illness Care Age at diagnosis Length of LTC Age Socio economic status

Living Well 59.27 (16.66) x

Healthcare Utilisation 1 2.72 (2.64) −.23 x

Healthcare Utilisation 2 .42 (1.01) −.11 −.14 x

Healthcare Utilisation 3 .11 (.58) −.15 −.12 .74 x

Healthcare Utilisation 4 .11 (.51) .01 −.11 .55 .75 x

Patient Assessment of Chronic Illness Care 2.21 (.92) .38 −.02 .01 −.16 −.14 x

Age at diagnosis 24.08 (14.44) −.21 .37* .02 .01 −.11 .03 x

Length of LTC 15.11 (12.80) .11 −.19 −0.5 −.10 −.08 −.14 −.46 .x

Age 36.62 (14.85) −.13 .21 −.07 −.04 −.12 −.21 .58 .36* x

Socio economic status 5.17 (1.76) .06 .05 −.13 −.11 −.09 .20 .22 −.01 .12 x

*p < .05, **p < .001

d.f. = 53

Multiple hierarchical regression

Examining the assumptions concluded that the data met the assumptions for no multicollinearity, no independent errors, and no outliers [See Appendix 4]. Analysis of scatter plots demonstrated that the assumptions of linearity and homogeneity were satisfied. Therefore, the multiple hierarchical regressions were run (see Tables 4 and 5).

Table 4.
A table providing a summary of the hierarchical regression analysis between the six illness experience predictor variables on levels of living well with LTCs.

Model 1 Model 2

Variable B β B β

Constant 87.90 80.68

Illness intrusiveness −.81 −.59 −.76 −.55

Social activities −2.79 −.18 −.69 −.55

Illness perception .11 .05 .14 .07

Energy 2.58 .13

Pain severity −.06 −.01

Health distress −2.10 −.14

R² .51 .53

F 17.02 8.86

ΔR² .51 .03

ΔF 17.02 .85

Table 5.
A table providing a summary of the hierarchical regression analysis between the nine healthcare experience predictor variables on levels of living well with LTCs.

Model 1 Model 2

Variable B β B β

Constant 63.53 47.03

Healthcare Utilisation 1 −1.46 −.23 −1.18 −.19

Healthcare Utilisation 2 −.049 −.00 −1.65 −.10

Healthcare Utilisation 3 −10.69 −.37 −6.57 −.23

Healthcare Utilisation 4 8.64 .26 8.77 .27

Age −.08 −.07 .12 .11

Socio economic status .58 .06 .00 .00

PACIC 7.35 .41

Age at diagnosis −.20 −.18

Length of LTC .01 .01

R² .13 .27

F 1.11 1.77

ΔR² .13 .14

ΔF 1.11 2.81

Results

Regression one: illness experiences

Pearson's correlations were computed for each variable. Table 2 demonstrates the correlation matrix. A strong positive correlation between illness intrusiveness and social/role activities limitations was observed. Additionally, a strong negative correlation can be observed between living well and illness intrusiveness.

Hierarchical regression analysis

To investigate the extent to which illness experience predicted levels of living well with LTCs, a 2-stage hierarchical multiple regression was conducted (Table 4).

The hierarchical multiple regression revealed that at stage 1, illness intrusiveness, social / role activities limitations, and illness perceptions contributed significantly to the regression model, (F(3, 50) = 17.02, p < .001). The relationship between variables were strong (R = .71) and accounted for approximately 51% (ΔR² = .51) of the variance in living well scores. While illness intrusiveness had a statistically significant impact (β = −.59, t(54) = −3.73, p < .001), both social/role activities limitations and illness perceptions did not. Adding stage 2 to the regression model accounted for an additional 3% (ΔR² = .03) of variation in living well scores and this change in R² was insignificant, (F(3, 47) = .85, p = .473) but the relationship between the variables were strong (R = .73). Illness intrusiveness continued to have a significant impact on living well (β = −.55, t(54) = −3.44, p < .001), and none of the additional stage 2 factors of energy, pain severity, health distress or the stage 1 factors of social/role activities limitations and illness perceptions influenced living well.

The full model of illness intrusiveness, social activities, illness perceptions, energy, pain severity, and health distress to predict levels of living well with LTCs was statistically significant, R² = .53, F(6, 47) = 8.86, p < .001, ΔR² = .03.

Regression two: healthcare experiences

Pearson's correlation coefficient

Pearson's correlations were computed for each variable. Table 3 demonstrates the correlation matrix. There was a strong positive correlation between current age and age at diagnosis. Additionally, a strong negative correlation can be observed between age at diagnosis and length of LTC.

Hierarchical regression analysis

To investigate the extent to which healthcare experience predicted levels of living well with LTCs, a 2-stage hierarchical multiple regression was conducted.

The hierarchical multiple regression revealed that at stage 1, healthcare utilisation, age, and socio-economic status contributed insignificantly to the regression model, (F(6, 46) = 1.11, p = .370). The relationship between variables was weak (R = .36) and accounted for approximately 13% (ΔR² = .13) of the variance in living well scores. Neither healthcare utilisation, age, or socio-economic status in stage 1 had a statistically significant impact.

Adding stage 2 to the regression model accounted for an additional 14% (ΔR² = .14) of variation in living well scores and this change in R² was insignificant, (F(3, 43) = 2.81, p = .051). The relationship between the variables was moderately strong (R = .52).

Patient assessment of chronic illness care (PACIC) had a significant impact on living well at stage 2 (β = .41, t(53) = −3.44, p = .007), while none of the additional stage 2 factors of age at diagnosis or length of LTC, or the stage 1 factors of healthcare utilisation, age, or socio-economic influenced living well.

The full model of healthcare utilisation, age, socio-economic status, PACIC, age at diagnosis, and duration of LTC to predict levels of living well with LTCs was statistically insignificant, R² = .52, F(3, 43) = 1.77, p = .103, ΔR² = .14.

Discussion

The study aimed to examine whether illness or healthcare experiences have a more significant impact on living well LTCs, and which factors in these experiences have the most influence. The full models show that illness experience significantly predicts living well with LTCs, while healthcare experience does not. These findings are consistent with the suggestion that illness experience is subjective and can have a significant impact on both the person experiencing it and the people around them through negatively impacting HR-QOL.^4,29 The experience of LTCs has been established to negatively impact patients’ assumptions of the world, the future, and the self. This can result in depleted capacity to continue living their everyday lives, and potentially increase hospital utilisation.³⁰ These results emphasise the need for psychologists and mental health support services to be involved more routinely in LTC clinics, as they have been proven to lessen time in hospital.¹⁵ However, this may prove difficult due to the current shortage of psychologists within the National Health Service.³¹

Summary of main findings

The finding that healthcare experience was not a significant predictor of living well presents a challenge to previous research. The effect of healthcare experiences on quality of life has been emphasised in multiple studies, finding that the worse a person's experience of healthcare service, the worse their quality of life.^32,33 A potential explanation for the contradiction is that this study, while not explicitly, likely included participants with diverse health conditions, potentially encompassing those with less severe conditions who may require infrequent medical consultations.

This is unlike most LTC studies which focus on one severe LTC, such as Alessy et al.'s finding that a late-stage cancer diagnosis was consistently associated with poorer cancer care experience compared to an early-stage diagnosis.³⁴ Therefore, caution is required when generalising this study's findings, as individuals with different illnesses may attribute varying levels of importance to factors influencing living well. While healthcare providers should focus on illness experience interventions with patients struggling to live well with their LTC, healthcare experience factors should be considered as well.

Illness intrusiveness had a statistically significant impact on living well with LTCs, in both stages (Figure 1). This supports previous research findings that illness intrusiveness is a strong predictor of HR-QOL and can be very detrimental, disrupting their lifestyle, activities, and interests, threatening psychological wellbeing.³⁵ The furthering of emotional distress in this way has shown to impair quality of life, highlighting the need for self-management to be supported by healthcare teams.⁸ When adding the exploratory variables at stage 2, the explanatory power increased by 2%, indicating that energy, pain severity, and health distress are weak predictors. Further research around these factors is needed to clarify their impact on HR-QOL. The second regression revealed that at stage 1, the established healthcare experience variables accounted for approximately 13% of the variance in living well scores. None of the established variables of healthcare utilisation, age, and socio-economic status had a statistically significant impact on living well with LTCs, at stage 1 or 2. This contradicts previous research, possibly explained by the participant sample used in the current study. With nearly one-third of the participants being students, they may have a low health utilisation score due to the possibly mild nature of their condition. When adding the exploratory variables at stage 2, the explanatory power increased by 14%, indicating that they are moderately weak predictors. PACIC significantly impacted living well with LTCs. This supports evidence that in an expected range of illnesses, satisfaction with care correlates with quality of life.^36,37 These results stress the need for healthcare managers to understand the aspects that improve patient care and find ways to support the healthcare providers in continuing these.

Figure 1.
Scatter plots with regression lines for living well with long-term conditions and illness intrusiveness scores (top left), health distress scores (bottom left), age (top right), and patient assessment of chronic care scores (bottom right).

Strengths and limitations

The current study participants did not specify their condition, allowing the results to be applied to a wide variety of people. The results allow for healthcare providers to prioritise supporting patients with the impact of their illness on their usual activities, and advocate for any issues they have with their care. However, specific conditions may benefit from further investigation. Future research could focus on most prevalent LTCs and compare with current findings.

One limitation of the study is that LTCQ uses a self-report measure, which have been criticised as causing possible biased answers and resulting in loss of construct validity.³⁸ However, research highlights the strength of self-report measures, as the extremely personal and individualistic nature of LTCs and their consequences may not be represented by observation from others.^39,40 The current study utilised Potter et al.'s LTCQ to measure living well with LTCs.⁷ The LTCQ is widely applicable to a range of LTCs and provides a reliable, valid, and holistic measure of living well with LTCs.⁷ However, LTCQ has been criticised for lacking clarity on how healthcare providers move forward with the results, such as implementing care pathways or referral processes.⁶ The Living with Long-Term Conditions Scale has recently been developed by Ambrosio et al., to tackle these issues.^5,6 Therefore, future research could replicate the present study using the Living with Long-Term Conditions Scale.

Conclusion

This study used two multiple hierarchical regressions to evaluate the influences of illness and healthcare experiences on the ability to live well with LTCs. Illness experience had a significant impact on living well with LTCs. The established factor of illness intrusiveness and the exploratory factor of PACIC significantly impacted living well. By prioritising patient perspectives in the concept of living well, the holistic nature of patient centred care is enhanced. These findings pave the way for future research to explore if factors influencing living well differ between LTCs and find the best interventions to improve living well with LTCs.

Illness Experience	Healthcare Experience
Illness Intrusiveness	Energy	Healthcare Utilisation	Patient Assessment of Chronic Illness Care
Social/Role Activities Limitations	Pain Severity	Age	Age at Diagnosis
Illness Perception	Health Distress	Socio-Economic Status	Length of LTC

Factor	Mean (SD)	Living Well	Illness Intrusiveness	Energy	Pain Severity	Health Distress	Social/Role Activities Limitations	Illness Perception
Living Well	59.05 (16.58)	x
Illness Intrusiveness	34.59 (12.10)	−.70**	x
Energy	2.08 (.86)	.45**	−.45**	-
Pain Severity	3.69 (1.32)	−.43**	.51**	−.55**	x
Health Distress	3.26 (1.11)	−.53**	.60**	−.42**	.50**	x
Social/Role Activities Limitations	2.56 (1.05)	−.61**	.77**	−.50**	.63**	.70**	x
Illness Perception	47.65 (7.69)	−.29*	.45**	−.24*	.42**	.42**	.46**	x

Factor	Mean (SD)	Living Well	Healthcare Utilisation 1	Healthcare Utilisation 2	Healthcare Utilisation 3	Healthcare Utilisation 4	Patient Assessment of Chronic Illness Care	Age at diagnosis	Length of LTC	Age	Socio economic status
Living Well	59.27 (16.66)	x
Healthcare Utilisation 1	2.72 (2.64)	−.23	x
Healthcare Utilisation 2	.42 (1.01)	−.11	−.14	x
Healthcare Utilisation 3	.11 (.58)	−.15	−.12	.74**	x
Healthcare Utilisation 4	.11 (.51)	.01	−.11	.55**	.75**	x
Patient Assessment of Chronic Illness Care	2.21 (.92)	.38*	−.02	.01	−.16	−.14	x
Age at diagnosis	24.08 (14.44)	−.21	.37*	.02	.01	−.11	.03	x
Length of LTC	15.11 (12.80)	.11	−.19	−0.5	−.10	−.08	−.14	−.46**	.x
Age	36.62 (14.85)	−.13	.21	−.07	−.04	−.12	−.21	.58**	.36*	x
Socio economic status	5.17 (1.76)	.06	.05	−.13	−.11	−.09	.20	.22	−.01	.12	x

	Model 1	Model 2
Constant	87.90		80.68
Illness intrusiveness	−.81	−.59	−.76	−.55
Social activities	−2.79	−.18	−.69	−.55
Illness perception	.11	.05	.14	.07
Energy			2.58	.13
Pain severity			−.06	−.01
Health distress			−2.10	−.14
R²	.51		.53
F	17.02		8.86
ΔR²	.51		.03
ΔF	17.02		.85

	Model 1	Model 2
Constant	63.53		47.03
Healthcare Utilisation 1	−1.46	−.23	−1.18	−.19
Healthcare Utilisation 2	−.049	−.00	−1.65	−.10
Healthcare Utilisation 3	−10.69	−.37	−6.57	−.23
Healthcare Utilisation 4	8.64	.26	8.77	.27
Age	−.08	−.07	.12	.11
Socio economic status	.58	.06	.00	.00
PACIC			7.35	.41
Age at diagnosis			−.20	−.18
Length of LTC			.01	.01
R²	.13		.27
F	1.11		1.77
ΔR²	.13		.14
ΔF	1.11		2.81

Footnotes

Author contributions

This was an undergraduate project by Poppy Dilks supervised by Dr Moitree Banerjee and Isabelle Ball. Poppy Dilks designed and developed the study, collected and analysed the data, and wrote the first version of the manuscript. Dr Moitree Banerjee and Isabelle Ball contributed methodological development and reviewed and revised the manuscript. All the authors read and approved the final manuscript.

Consent to participate

All participants provided written informed consent prior to participating. Participant information was anonymous.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical considerations

This study has received ethics approval in accordance with the Research Ethics Policy of the University of Chichester on January 12, 2024. Respondents gave written consent for review before starting.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Poppy Dilks

Isabelle Ball

Moitree Banerjee

Appendices

References

Department of Health. Long term conditions compendium of information: third edition. UK Goverment, https://www.gov.uk/government/publications/long-term-conditions-compendium-of-information-third-edition (May 30, 2012).

Kerai

Onadeko

Bannister

, et al. UK health indicators: 2019 to 2020. Office for National Statistics, https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandlifeexpectancies/bulletins/ukhealthindicators/2019to2020 (March 29, 2022).

Corchón

Rodríguez-Blázquez

Meneses

, et al. The determinants of living with long-term conditions: an international cross-sectional study. Int J Environ Res Public Health 2021; 18: 10381.

Megari

. Quality of life in chronic disease patients. Health Psychol Res 2013; 1: 27.

Ambrosio

García

JMS

Riverol

, et al. Living with chronic illness in adults: a concept analysis. J Clin Nurs 2015; 24: 2357–2367.

Ambrosio

Hislop-Lennie

Barker

, et al. Living with long term condition scale: a pilot validation study of a new person centred tool in the UK. Nurs Open 2021; 8: 1909–1919.

Potter

Batchelder

A’Court

, et al. Long-Term Conditions Questionnaire (LTCQ): initial validation survey among primary care patients and social care recipients in England. BMJ Open 2017; 7: e019235.

McGill

Hughes

Carroll

, et al. Illness intrusiveness in adults with sickle cell disease: the role of fatigue. J Clin Psychol Med Settings 2023; 30: 866–875.

Sigit

De Mutsert

Lamb

, et al. Illness perceptions and health-related quality of life in individuals with overweight and obesity. Int J Obes 2021; 46: 417–426.

10.

Wilson

Bocell

Bamer

, et al. Satisfaction with social role participation in adults living with chronic conditions: Comparison to a US general population sample. Cogent Psychol 2019; 6: 1–17.

11.

Ludwig

Bailey

Marongiu

, et al. Patient-reported pain severity and health-related quality of life in patients with multiple myeloma in real world clinical practice. Cancer Rep Epub ahead of print June 10, 2021; 5: 1–8.

12.

Olson

Robertson

Chen

, et al. Healthier energy balance behaviors most important for Health-Related Quality of Life in rural cancer survivors in Central Pennsylvania. J Phys Act Health 2023; 20: 752–759.

13.

Parker

White

Russell

. Invisible and visible symptoms of multiple sclerosis. J Neurosci Nurs 2008; 40: 85–95.

14.

Wagner

Austin

Von Korff

. Organizing care for patients with chronic illness. Milbank Q 1996; 74: 511.

15.

Yánez

. Why is mental health care necessary during hospitalization? Int J Public Health Epub ahead of print November 1, 2022; 67: 1–2.

16.

Didsbury

Kim

Medway

, et al. Socio-economic status and quality of life in children with chronic disease: a systematic review. J Paediatr Child Health 2016; 52: 1062–1069.

17.

Heyworth

ITM

Hazell

Linehan

, et al.

How do common chronic conditions affect health-related quality of life?

Br J Gen Pract 2009; 59: e353–e358.

18.

Osborne

Bindemann

Noble

, et al. Changes in the key areas of quality of life associated with age and time since diagnosis of long-term conditions. Chronic Illn 2012; 8: 112–120.

19.

Joachim

Acorn

. Stigma of visible and invisible chronic conditions. J Adv Nurs 2000; 32: 243–248.

20.

Devins

Binik

Hutchinson

, et al. The Emotional Impact of End-Stage Renal Disease: importance of patients’ perceptions of intrusiveness and control. Int J Psychiatry Med 1984; 13: 327–343.

21.

Devins

Mandin

Hons

, et al. Illness intrusiveness and quality of life in end-stage renal disease: comparison and stability across treatment modalities. Health Psychol 1990; 9: 117–142.

22.

Stewart

Ware

. Measuring functioning and well-being: the medical outcomes study approach. Epub ahead of print January 1, 1992. DOI:10.7249/cb361.

23.

Lorig

Stewart

Ritter

, et al. Outcome measures for health education and other health care interventions. Epub ahead of print January 1, 1996. DOI:10.4135/9781452232966.

24.

Broadbent

Petrie

Main

, et al. The Brief Illness Perception Questionnaire. J Psychosom Res 2006; 60: 631–637.

25.

Ritter

Stewart

Kaymaz

, et al. Self-reports of health care utilization compared to provider records. J Clin Epidemiol 2001; 54: 136–141.

26.

Glasgow

Wagner

Schaefer

, et al. Development and validation of the Patient Assessment of Chronic Illness Care (PACIC). Med Care 2005; 43: 436–444.

27.

Qualtrics

. Qualtrics XM - experience management software. Qualtrics, https://www.qualtrics.com/ (2005).

28.

IBM Corp. IBM SPSS Statistics for Windows.

29.

Larsen

. Lubkin’s Chronic Illness: Impact and intervention. Burlington, MA: Jones & Bartlett Learning, 2021.

30.

Reeve

Lloyd-Williams

Payne

, et al. Revisiting biographical disruption: exploring individual embodied illness experience in people with terminal cancer. Health 2010; 14: 178–195.

31.

NHS Health Education England. Psychological professions workforce plan for England. NHS Health Education England, https://www.hee.nhs.uk/sites/default/files/documents/Psychological%20Professions%20Workforce%20Plan%20for%20England%20-%20Final.pdf (December 2021).

32.

Alaloul

Myers

Masterson

, et al. Patient experience factors and health-related quality of life in hospitalized individuals. Oncol Nurs Forum 2019; 26: 238–247.

33.

Crocker

Jenkinson

Peters

. Healthcare experiences and quality of life of adults with coeliac disease: a cross-sectional study. J Hum Nutr Diet 2020; 33: 741–751.

34.

Alessy

Mohammed

Rawlinson

, et al. Factors influencing cancer patients’ experiences of care in the USA, United Kingdom, and Canada: a systematic review. EClinicalMedicine 2022; 47: 101405.

35.

Bouchard

Duquette

Mayo

. Path to illness intrusiveness: what symptoms affect the life of people living with multiple sclerosis? Arch Phys Med Rehabil 2017; 98: 1357–1365.

36.

Akan

Kartal

. The association between Patient Assessment of Chronic Illness Care Scores and quality of life in type 2 diabetes patients. J Res Nurs 2023; 28: 199–211.

37.

Schmittdiel

Mosen

Glasgow

, et al. Patient Assessment of Chronic Illness Care (PACIC) and improved patient-centered outcomes for chronic conditions. J Gen Intern Med 2007; 23: 77–80.

38.

Chan

. So why ask me? Are self-report data really that bad? In: Lance CE and Vandenberg RJ (eds) Statistical and Methodological Myths and Urban Legends: Doctrine, Verity and Fable in the Organizational and Social Sciences. New York: Routledge, 2009, pp.309–336.

39.

Hunter

Fitzpatrick

Jenkinson

, et al. Perspectives from health, social care and policy stakeholders on the value of a single self-report outcome measure across long-term conditions: a qualitative study. BMJ Open 2015; 5: e006986.

40.

Zimmermann

Silva

Galvao

, et al. Health-related quality of life and self-reported long-term conditions: a population-based survey. Braz J Psychiatry 2016; 39: 62–68.

Illness Experience		Healthcare Experience
Established	Exploratory	Established	Exploratory
Illness Intrusiveness	Energy	Healthcare Utilisation	Patient Assessment of Chronic Illness Care
Social/Role Activities Limitations	Pain Severity	Age	Age at Diagnosis
Illness Perception	Health Distress	Socio-Economic Status	Length of LTC

	Model 1		Model 2
Variable	B	β	B	β
Constant	87.90		80.68
Illness intrusiveness	−.81	−.59	−.76	−.55
Social activities	−2.79	−.18	−.69	−.55
Illness perception	.11	.05	.14	.07
Energy			2.58	.13
Pain severity			−.06	−.01
Health distress			−2.10	−.14
R²	.51		.53
F	17.02		8.86
ΔR²	.51		.03
ΔF	17.02		.85

Living well with long-term conditions: A quantitative investigation into the influences of illness and healthcare experiences

Abstract

Objectives

Methods

Results

Keywords

Methods

Participants

Materials

The Adapted Illness Intrusiveness Scale

The Energy/Fatigue Scale

The Pain Severity Scale

The Health Distress Scale

The Social/Role Activities Limitations Scale

The Brief Illness Perceptions Questionnaire

The Healthcare Utilisation Scale

The Patient Assessment of Chronic Illness Care Scale

The Long-Term Conditions Questionnaire

Procedure

Data analysis

Pearson's correlation coefficient

Multiple hierarchical regression

Results

Regression one: illness experiences

Hierarchical regression analysis

Regression two: healthcare experiences

Pearson's correlation coefficient

Hierarchical regression analysis

Discussion

Summary of main findings

Strengths and limitations

Conclusion

Footnotes

Author contributions

Consent to participate

Declaration of conflicting interests

Ethical considerations

Funding

ORCID iDs

Appendices

References