Predictors of quality of life among older patients with cancer during treatment

Abstract

Background

Improving quality of life in older patients with cancer has become an important goal of healthcare providers.

Aims

The purpose of this study was to identify the predictors of quality of life among older patients with cancer, aged 60 years and over during the treatment period.

Methods

A descriptive correlational study was conducted among 150 patients. The Functional Assessment of Cancer Therapy Scale, Herth Hope Index and Hospital Anxiety and Depression Scale were used.

Results

The results showed that the total quality-of-life mean score was 58.50 (SD = 7.44), indicating low overall quality of life. The social-family well-being subscale had the highest mean (20.50, SD = 3.79) among all subscales of quality of life, while the emotional well-being subscale had the lowest mean (8.06, SD = 4.23). Hope and educational level had statistically significant positive relationships with all subscales of quality of life. However, anxiety was associated negatively with physical, social-family and functional well-being subscales, but positively with the emotional well-being subscale. Anxiety, income, marital status, health insurance, duration of treatment, educational level, gender and hope were identified as predictors of quality-of-life subscales.

Conclusions

The results could help to develop specific programmes that may improve quality of life among older patients with cancer during treatment.

Introduction

Cancer is considered to be a global health problem and is a potentially life-threatening disease that engenders considerable distress for patients (Adler and Page, 2008). The Global Burden of Disease Cancer Collaboration (2015) stated that cancer is the second main cause of mortality worldwide. In 2015, there were 8.8 million deaths from cancer globally. Increasing age is the greatest risk factor for developing cancer (White et al., 2014), therefore cancer is becoming an increasing problem in the geriatric population (Repetto et al., 2012).

Advances in cancer diagnoses, treatment modalities and care have led to an increase in the number of older patients with cancer (DeSantis et al., 2014). It appears that cancer diagnosis and treatment modalities have a negative impact on patients’ physical, social and emotional well-being, in addition to their quality of life (QOL). The QOL reflects subjective characteristics of patients' satisfaction with their physical, social, spiritual, emotional and functional well-being and includes patients' perceptions of the effects of cancer diagnoses and treatment modalities on functional life (Movsas, 2003; Polanski et al., 2016). Accordingly, improving QOL in older patients with cancer has become an important goal of healthcare providers and is necessary for patient-centred care.

It has been reported that there are many factors affecting QOL among older patients with cancer (Yan et al., 2016). Based on previous studies, patient-related factors, treatment-related factors, psychological problems (anxiety and depression) and hope were documented as the most significant.

Several researchers have reported that patient-related factors such as age, educational level, income, marital status, health insurance and treatment-related factors (e.g. type of cancer, duration of treatment and type of treatment) have effects on QOL. It has been indicated that there is a relationship between advancing age (Al-Naggar et al., 2011; Sun et al., 2013), educational level (Li et al., 2016; Lu et al., 2009; Sun et al., 2013), income (Al-Naggar et al., 2011; Farkkila et al., 2013; Kwan et al., 2010; Yan et al., 2016), marital status (Peuckmann et al., 2007), health insurance (Yan et al., 2016) and QOL.

Treatment-related factors have an impact on the QOL of older patients with cancer. Previous evidence has shown that patients who have been treated by radiotherapy have experienced better overall QOL (Lu et al., 2009) and those who have been treated by chemotherapy have had a lower QOL (Yan et al., 2016). Regarding duration of treatment, a previous study indicated a significant improvement in physical, psychological and social well-being subscales and overall QOL over time after treatment (Sun et al., 2013). Moreover, a significant relationship was found between the type of cancer and QOL (Heydarnejad et al., 2011).

Psychological status and hope also affect the QOL of older patients with cancer (Li et al., 2016). Cancer can exacerbate significant emotional and psychological problems. Previous research has documented that older patients with cancer may develop anxiety and depression, and that those with higher levels of depression and anxiety had a lower QOL (Yang et al., 2014). Early studies indicated that hope had an impact on psychological well-being, physical well-being and overall QOL among patients with cancer (Farhadi et al., 2014; Rock et al., 2014).

In Jordan, the definition of old age as 60 years and over is congruent with that of the United Nations (Kinsella and Velkoff, 2001). The last records in 2013 reported that there were 5416 new cancer cases in the Jordanian population and 42.0% of these cases were in people aged 60 years and more (Jordan Cancer Registry, 2013). The Jordanian government takes responsibility for treating patients with cancer. Cancer treatment is provided at no cost to Jordanian citizens through public and military hospitals. Recently, the King Hussein Cancer Center has been running a non-profit cancer insurance programme that partially covers the cost of cancer treatment for participants who pay affordable premiums. Moreover, cancer care in Jordan is focused on treatment, with less effort placed on other elements of the cancer continuum. Although there are several initiatives for cancer control and treatment, Jordan is lacking a national control plan regarding cancer (Abdel-Razeq et al., 2015). In developing countries, there are few studies on the issue of QOL in older patients with cancer. Importantly, the impact of cancer treatment on older patients’ QOL in these countries, including Jordan, is still poorly understood because of a lack of research within these countries. Accordingly, the current study responds to the lack of knowledge in understanding QOL and its predictors among older patients with cancer during treatment, hence the determination of factors that affect QOL measures could provide insights into treatment and care for older patients with cancer (Yan et al., 2016). Such data will increase health professionals’ – especially oncology nurses' – knowledge about the effects of cancer and its treatment modalities on older patients, and assist the development of effective intervention programmes for older patients with cancer that may help decrease symptoms and distress associated with cancer treatment. Thus, the purpose of this study was to identify the predictors of QOL among older patients aged 60 years and more, with different types of cancer, during their treatment period. The specific research questions that guided the study were as follows:

1. What are the levels of QOL and its subscales among older patients with cancer during treatment?

2. What are the relationships among patient-related factors, treatment-related factors, hope, anxiety, depression, and QOL and its subscales among older patients with cancer during treatment?

3. What are the factors predicting the QOL and its subscales among older patients with cancer during treatment?

Methods

Design, setting and sample

A cross-sectional, descriptive-correlational design was used to conduct this study. The participants were selected from the oncology department of the largest government hospital affiliated to the Amman Governorate, which is considered the referral hospital for all patients with cancer from different regions of the country. Amman is considered the central city in Jordan. A convenience-sampling technique was used to recruit older patients with cancer. Using G* power 3.1.7 software and estimating a moderate effect size (R²= 0.15), a power of 0.80, with α = 0.05 and 14 predictors, power analysis indicated the need for 135 participants. To avoid any dropout, the sample was increased to 150 older patients. The eligibility criteria included patients who were (1) Jordanian nationals, (2) aged 60 years and more, (3) diagnosed with different types of cancer, (4) under active care treatment with chemotherapy or radiotherapy, and (5) free of any psychiatric health problems. Older patients with identified psychiatric disorders such as schizophrenia were excluded.

Data collection procedure

The following recruitment strategies were used in this study. First, the researchers conducted a presentation for medical and nursing staff in the hospital setting to provide an overview of the study's purposes, methods and significance. In order to identify eligible participants, a detailed explanation was given to the oncology clinical nurse specialists and the nurses in charge of the oncology ward. They then identified patients who met the eligibility criteria and agreed to participate. Following this, the researcher approached, in person, potential participants, obtained their permission to participate, and subsequently gained access to their contact details, files and medical records. A package comprising an information sheet, consent form and survey instrument was given to each eligible patient. Patients’ approval was obtained to participate and access files. Consenting participants were asked to complete the coded questionnaire. The participants completed the survey packet at the time they were presented with it. The questionnaires needed to be read to some of the participants due to tiredness from treatment, and took around 30–45 minutes to complete. Furthermore, some of the participants completed the questionnaires on their own, whereas others needed help from the researchers to fill them in. When participants had completed the questionnaires, the researchers reviewed the medical chart to extract the relevant disease-related conditions. Also, there were some small challenges for the older patients when filling out the questionnaires, especially for those who had poor vision or wore assistance devices such as glasses or hearing aids, thus the researchers sometimes needed to help.

Study measures

A self-administered structured questionnaire was used and consisted of the following:

• A basic patient-related factors questionnaire including age, gender, marital status, educational level, income per year (in Jordan the average is Jordanian dinar (JOD) 366.3 per household per month, whereas the food poverty line is JOD151.2 per household per month; United Nations Development Programme, 2013), and health insurance.

• A treatment-related factors questionnaire including the type of cancer, and the duration and type of treatment.

• The Functional Assessment of Cancer Therapy Scale (FACT) – the QOL of patients was assessed using the initial FACT scale, FACT-General (FACT-G). The FACT is composed of four subscales: physical well-being (seven items, score range 0–28), social-family well-being (seven items, score range 0–28), functional well-being (seven items, score range 0–28) and emotional well-being (six items, score range 0–24). It is evaluated in an ordinal dimension using a five-point Likert scale ranging from 0 ‘not at all’ to 4 ‘very much’. The FACT-G total score is computed as the sum of the four subscale scores, provided the overall item response is at least 80% (i.e. at least 22 of the 27 items were answered) and has a possible range of 0–108 points, with higher scores indicating higher levels of QOL (Webster et al., 2003). The FACT-G subscales and total score demonstrated good validity and internal consistency reliability (Haugan et al., 2013). The FACT-G demonstrated good internal consistency reliability (≥0.7) (Yost et al., 2013).

• The Herth Hope Index (HHI) – this study adopted the HHI, which was developed and evaluated by Herth (1992) to measure hope with a scale of 12 items rated on a four-point Likert response. The total score ranges from 12 to 48, where the higher scores indicate a greater level of hope. The HHI was found to be a reliable and valid instrument. Cronbach's α was 0.84 and the test-retest reliability was 0.64 (Ripamonti et al., 2018).

• The Hospital Anxiety and Depression Scale (HADS) – the HADS is a brief, self-administered rating scale designed to detect anxiety and depression among individuals with medical illnesses (Snaith, 2003). It is intended to screen for clinically significant depression among medically ill patients and to measure the severity of depression. The HADS focuses on the psychological rather than somatic manifestations of depression, excluding items that are characteristic of both depression and medical illness, such as appetite and sleep disturbance. The HADS contains 14 items with a four-point Likert scale, seven pertaining to depression and seven to anxiety. Each subscale (anxiety and depression) is treated separately. The anxiety level is rated from 0 to 28, where a higher score indicates a higher level of anxiety. This is similar to depression scores, which also range from 0 to 28, with higher scores indicating greater levels of depression. The HADS demonstrated high internal consistency (Cronbach's α was 0.88: 0.83 for anxiety and 0.84 for depression), stability (test-retest was 0.94) and high concurrent validity (Michopoulos et al., 2008).

Because Arabic is the native language in Jordan, the researchers used the Arabic version of the instruments. This version was examined among Jordanian adults with cancer and has been shown to have good internal consistency reliability. Moreover, a pilot study was undertaken on a group of Jordanian older patients with cancer (n = 20) to test the clarity of the questionnaire. According to the pilot study results, the questionnaire was clear to most of the participants. Cronbach's α for the instruments was as follows: FACT-G total score = 0.89 (physical well-being = 0.92, social-family well-being = 0.91, emotional well-being = 0.86 and functional well-being = 0.89), HHI = 0.87 and HADS = 0.93.

Ethical considerations

This study was approved by the ethics committee of the Jordan Ministry of Health and by the participating hospital manager. It was conducted in accordance with the institutional guidelines. All participants received oral and written information about the study’s aim and instructions and about their rights. The information disclosed that participation was voluntary and that refusal or withdrawal from the study guaranteed no effect on their treatment and no harmful effects on them. Furthermore, participants were also assured of the confidential nature of the study and that no individual answers could be identified. Anonymity was also maintained throughout the study. Informed consent was obtained before filling out questionnaires.

Data analysis

Statistical analyses were conducted using the Statistical Package of Social Science for Windows, version 23.0. Descriptive statistics including frequencies, percentages, mean and standard deviation (SD) were used for calculating the study variables. Pearson's correlation (r) was used to examine the relationship between the QOL and the continuous variables. However, the point-biserial (p.b) test was used to examine the relationship between QOL and the discrete variables. A multiple regression analysis was used to analyse the combined effects of predictors on subscales of QOL and determine the best predictors for QOL. The significance level was tested at α ≤ 0.05.

Results

Sample characteristics

A total of 150 participants agreed to take part in the present study. As shown in Table 1, the mean age was 64.33 (SD = 3.46) and the range was 60–78 years old. More than half of the sample were male (58.0%) and almost three-quarters (74.7%) were married. The majority of the sample (41.0%) were high school graduates; only 7.0 % (n = 10) were elementary school graduates. More than two-thirds (68.7%) of the sample had a yearly income of less than JOD4000 (<$5633); however, only 1.3% received more than JOD12,000 (>$16,800$). More than two-thirds (64.7%) of the sample had health insurance, which was mainly governmental. The mean duration of the cancer was 3.43 years (SD = 3.38) with the actual range of 1 month to 10 years. More than half (53.3%) of the sample had been treated with chemotherapy. All of the available participants (100%) were diagnosed with breast, colon or lung cancer.

Table 1.

Patient- and treatment-related factors of the study population (n = 150).

Characteristic	n (%)
Age M (SD)	64.33 (3.46)
	Range = 60–78 years
Gender
Male	87 (58.0)
Female	63 (42.0)
Educational level
Elementary school	10 (6.70)
Secondary school	26 (17.3)
High school	61 (40.7)
Baccalaureate degree and over	53 (35.3)
Marital status
Single	003 (02.0)
Married	112 (74.7)
Divorced	005 (3.30)
Widowed	030 (20.0)
Family income/year (JOD)
<4000 (<$5633)	103 (68.7)
4000–8000 ($5633–11,267)	041 (27.3)
>8000–12,000 (>$11,267–16,800)	004 (2.70)
>12,000 (>$16,800)	002 (1.30)
Health insurance
Yes	97 (64.70)
No	53 (35.30)
Duration of treatment M (SD)	3.43 (2.34) year
	Range = 1 month–10 years
Type of treatment
Chemotherapy	80 (53.30)
Radiotherapy	70 (46.70)
Type of cancer
Lung cancer	65 (43.3)
Colorectal cancer	55 (36.7)
Breast cancer	30 (20.00)

JOD: Jordanian dinar.

Levels of QOL and its subscales

As shown in Table 2, the total QOL mean score was 58.50 (SD = 7.44) with actual scores ranging from 40 to 85. The social-family well-being subscale had the highest mean (M = 20.50, SD = 3.79) among all subscales of QOL; however, the emotional well-being subscale had the lowest mean (M = 8.06, SD = 4.23).

Table 2.

Description of the subscales of QOL among older patients with cancer (n = 150).

Subscales	Range	M (SD)
Social-family well-being	11–28	20.50 (3.79)
Functional well-being	0–28	18.38 (5.53)
Physical well-being	0–28	11.40 (5.92)
Emotional well-being	4–24	8.06 (4.23)
Total QOL scale	40–85	58.35 (7.44)

QOL: quality of life.

Relationship with QOL and its subscales

Pearson's correlation was performed to assess the relationship between age, duration of cancer, hope, anxiety, depression and subscales of QOL among older patients with cancer. The results showed a statistically significant relationship among hope, anxiety and all subscales of QOL. Hope had a statistically significant positive relationship with all subscales of QOL. However, anxiety was negatively associated with physical, social-family and functional well-being, but positively with emotional well-being. Furthermore, there was a statistically significant positive relationship between age and social-family and functional well-being. However, income was associated negatively with emotional and functional well-being (see Table 3).

Table 3.

Correlation between patient-related factors, hope, anxiety, depression and QOL and its subscales (n = 150).

Factors	Physical		Social-family		Emotional		Functional
	r	p	r	p	r	p	r	p
Age	0.11	0.16	0.28*	0.001**	0.06	0.43	0.27	0.001**
Hope	0.50	0.000**	0.28	0.001**	0.54	0.000**	0.75	0.000**
Anxiety	−0.63	0.000**	−0.22	0.005**	0.48	0.000**	−0.66	0.000**
Duration of disease	0.004	0.95	−0.03	0.70	0.11	0.15	−0.40	0.000**
	r p.b	p	r p.b	p	r p.b	p	r p.b	p
Gender	−0.01	0.85	0.20	0.01**	−0.08	0.27	−0.10	0.19
Educational level	0.35	0.000**	0.26	0.001**	0.40	0.000**	0.44	0.000**
Marital status	0.01	0.91	0.55	0.000**	0.03	0.66	0.13	0.10
Income	0.14	0.08	0.11	0.17	−0.22	0.007**	−0.26	0.002**
Health insurance	−0.09	0.23	−0.13	0.09	0.22	0.006**	0.18	0.02*
Type of treatment	0.20	0.02*	0.02	0.21	0.04	0.26	0.09	0.34
Type of cancer	0.25	0.03*	0.05	0.31	0.06	0.36	0.05	0.24

r: Pearson correlation; r p.b: Point-Biserial correlation; QOL: quality of life.

^*p ≤ 0.05; ** p ≤ 0.01.

The relationship between gender, educational level, marital status, health insurance, type of treatment, type of cancer and subscales of QOL was examined by using a p.b test. There was a statistically significant positive relationship between the educational level and all subscales of QOL. Health insurance was positively associated with emotional and functional well-being. Furthermore, there was a positive relationship between the social-family well-being subscale, gender and marital status in which male and married patients had higher social-family well-being compared to their counterparts. The duration of disease was negatively associated with the functional well-being subscale. In addition, results showed there were significant relationships among type of treatment, type of cancer and physical well-being (see Table 3).

Predictors of QOL and its subscales

Multiple linear regression analysis was performed to examine the significant predictors of subscales of QOL. The income and type of cancer variables were entered into the regression equation as a dummy-coded variable. The variables that entered the models as predictors for the QOL subscales were age, gender, marital status, educational level, income/year, health insurance, duration of treatment, type of treatment, type of cancer, hope and anxiety.

Regarding the physical well-being subscale of QOL, the full model containing all predictors was statistically significant (F_{(14, 135)} = 9.92; p ≤ 0.01; R = 0.65; R²= 0.43; adjusted R²= 0.40). This indicated that 40% of the variance in the physical well-being subscale was explained by the whole model. The significant predictor of physical well-being was anxiety and yearly income.

Regarding the social-family well-being subscale of QOL, the full model containing all predictors was statistically significant (F_{(14, 135)} = 10.84; p ≤ 0.01; R = 0.66; R²= 0.45; adjusted R²= 0.41). This indicated that 41% of the variance in the social-family well-being subscale was explained by the whole model. Marital status, duration of cancer, and health insurance were significant predictors of the social-family well-being subscale; marital status had the strongest relationship with social-family well-being.

Regarding the emotional well-being subscale of QOL, the full model containing all predictors was statistically significant (F_{(14, 135)} = 10.02; p ≤ 0.01; R = 0.65; R²= 0.42; adjusted R²= 0.37). This indicated that 37% of the variance in the emotional well-being subscale was explained by the whole model. The predictors of the emotional well-being subscale were age, educational level, health insurance and hope. Hope had the strongest relationship with emotional well-being.

Regarding the functional well-being subscale of QOL, the full model containing all predictors was statistically significant (F_{(14, 135)} = 27.82; p ≤ 0.01; R = 0.80; R²= 0.64; adjusted R²= 0.62). This indicated that 62% of the variance in the emotional well-being subscale was explained by the whole model. The gender, educational level, health insurance, duration of disease, anxiety and hope were the predictors of functional well-being. Hope had the strongest relationship with functional well-being (see Table 4).

Table 4.

Predictors of QOL and its subscales among older patients with cancer (n = 150).

Predictors	B	B	t	p-value	95% CI
Physical well-being
Anxiety	−0.51	−0.73	5.46	0.001	−0.47–1.00
Income	0.41	0.37	4.36	0.001	0.23–1.12
R2= 0.43
Adjusted R2= 0.40
Social-family well-being
Marital status	0.67	5.14	7.66	0.001	3.81–6.47
Health insurance	0.55	−1.68	−2.93	0.004	−3.40–1.65
Duration of the disease	−0.27	−0.3	3.47	0.001	−0.12–0.48
R2 = 0.45
Adjusted R2 = 0.41
Emotional well-being
Educational level	0.35	0.89	2.13	0.03	1.70–2.20
Health insurance	−0.17	−1.56	−2.38	0.01	−2.87– −0.26
Hope	0.35	0.28	3.56	0.001	0.43–1.12
R2 = 0.42
Adjusted R2 = 0.37
Functional well-being
Gender	−0.11	−1.23	−2.1	0.03	−2.38– −0.07
Educational level	0.15	0.94	2.35	0.02	0.15– 1.73
Health insurance	−0.11	−1.33	−2.12	0.03	−0.17– −0.01
Duration of treatment	−0.28	−0.47	−4.73	0.001	−0.65– −0.25
Anxiety	−0.28	−0.37	4.04-	0.001	−0.55– −0.19
Hope	0.41	0.42	5.69	0.001	0.27–0.57
R2 = 0.64
Adjusted R2 = 0.62

B: unstandardised; B: standardised; CI: confidence interval; QOL: quality of life.

Discussion

The results of this study indicated that the mean QOL score among older Jordanian patients with cancer was 58.35. This was much lower than that of older patients with cancer in developed countries, documenting 81.0–84.2 (Li et al., 2016). This result could be related to the unavailability of a national palliative care policy and clinical practice guidelines for psychosocial and counselling care for older patients with cancer undergoing treatment (Silbermann et al., 2012). Furthermore, it might be related to the cultural and social characteristics of Jordanian society, which are similar to other Eastern countries’ cultures, where family members take the responsibility for providing care for each other, which could lead to financial difficulties and be a burden on caregivers (Alnazly and Samara, 2014). These reasons might lead to negative effects on QOL among this target group.

One finding of this study is that social-family well-being had the highest mean among all subscales of QOL. This may be related to the fact that a social support system, including a large family or social network that surrounded most of the patients during the treatment period, is considered a crucial factor affecting the advancement of cancer (Ikeda et al., 2013). The availability of supportive social relationships may affect the well-being of patients with cancer (Dreyer and Schwartz-Attias, 2014). Older patients with cancer who obtain psychological caring, comfort and assistance from their families and friends are more likely to manage their problems in positive ways (Li et al., 2016).

This study has shown that most participants experienced low scores in both emotional well-being and physical subscales of QOL. These findings correspond with a previous study revealing that older patients with cancer suffered from both poor psychological and physical subscales of QOL after diagnosis and treatment of cancer (Naughton and Weaver, 2014). A possible explanation for this result might be related to the older patients with cancer experiencing many physical and psychosocial issues, such as coping with common grief and losses, financial status, role changes within their families and societies, and changes in their cognitive and physical abilities (Peuckmann et al., 2007).

Older patients with cancer have different health and coping abilities due to the various impacts of treatment modalities (Adler and Page, 2008). This study demonstrated a positive relationship between age, social-family and functional well-being subscales. Older patients with cancer had better social-family and functional well-being. These results contradict a previous study, which indicated that physical, emotional, cognitive and self-perception dimensions of QOL were similar between older and younger patients with cancer (Cavallin et al., 2015). These results could be related to cultural factors, whereas older people in Arab countries including Jordan tend to live with their children, thus they have better social-family care and support (Sibai et al., 2009).

The findings of this study documented a statistically significant positive relationship between being male and the social-family well-being subscale. Regression analysis indicated that gender was a significant predictor of good functional well-being. The reason for this could be related to gender socialisation, weakness in physical abilities and fragility among older females (Ustundag and Zencirci, 2015). Previous research revealed that females experienced lower physical, functional, social and psychological aspects of QOL than males (Can et al., 2012; Ustundag and Zencirci, 2015).

One finding of this study was that educational level correlated with all subscales of QOL and was a significant predictor of emotional and functional well-being. This result is consistent with previous evidence showing that participants with a higher educational level had a better overall score for QOL and its subscales (Li et al., 2016). A previous study indicated that women with cancer who had a higher educational level showed better adjustment to any difficulties than did those with a lower educational level (Zou et al., 2014).

The findings of the current study suggest that marital status has an effect on the social-family well-being subscale. Married patients had better social-family well-being than those who were single or divorced. Previous research has documented that married patients had a better QOL (Miller et al., 2010; Zou et al., 2014), higher psychological and general well-being (Ustundag and Zencirci, 2015) and more social support from their families and significant others (Miller et al., 2010; Ustundag and Zencirci, 2015; Zou et al., 2014) than those who were single, divorced or widowed. This result might be related to married patients possibly having higher levels of social support from their families and significant others, which could improve the social-family well-being subscale and overall QOL (Ustundag and Zencirci, 2015; Zou et al., 2014).

The QOL of older patients with cancer is influenced by difficulties in economic status. This study has revealed that the majority of the participants had a low yearly income. Furthermore, a negative relationship was demonstrated between income and the emotional and functional well-being subscales of QOL. These results are consistent with a previous study documenting that economic status had a negative effect on QOL (Farkkila et al., 2013). Previous evidence reported that cancer patients with a higher income reported better QOL compared with those with a lower income (Yan et al., 2016; Zou et al., 2014). However, these results are inconsistent with a previous study indicating that no correlation was found between income and QOL in patients with cancer (Heydarnejad et al., 2011). Economic status plays a significant role in improving QOL, therefore income needs to be taken into consideration when providing care to enhance the QOL of older patients with cancer (Farkkila et al., 2013).

The duration of treatment could affect the QOL among older patients with cancer. This study has shown that the duration of disease is a significant predictor of the functional well-being subscale. Cancer treatment modalities cause physical distress and side effects (e.g. pain, fatigue, nausea and vomiting), which may affect the performance of activities of daily living, thus older patients with cancer require more functional assistance (Kwon et al., 2012). A previous study conducted by Kwon et al. (2012) reported that increasing duration of the disease leads to a decreased QOL and lower physical and social functions.

This study has shown that health insurance is a significant predictor of the emotional, functional and social well-being subscales of QOL. This result is consistent with a previous study suggesting that older patients with cancer who had health insurance had better emotional and functional well-being subscales (Li et al., 2016). Health insurance provides economic security and decreases the financial stress of patients and their families during the treatment period. It protects patients from economic risk and the burden of medical healthcare costs, thus it may improve QOL and recovery (Li et al., 2016).

Cancer is a life-threatening disease and is upsetting both emotionally and psychologically. This study has revealed that anxiety had a negative relationship with the physical, social and functional well-being subscales, but a positive relationship with the emotional well-being subscale. This result is consistent with previous studies (Brown et al., 2010; Burgess et al., 2005), indicating that anxiety had an effect on QOL and its subscales. The results indicate that high anxiety is a significant predictor of low QOL. This study has shown that depression had no relationship to QOL and its subscales. This result is not consistent with other literature (Brown et al., 2010; Burgess et al., 2005), which revealed depression had an effect on QOL.

Hope has an important role in improving QOL. The findings of this study are consistent with previous research (Al-Naggar et al., 2011; Farhadi et al., 2014; Rock et al., 2014), indicating that hope had an influence on overall QOL among patients with cancer and was a significant predictor of emotional and functional well-being subscales. Hawro et al. (2014) found that hope had a curative value and a considerable role in maintaining QOL. Another study suggested that hope helps patients with cancer in adapting, maintaining a significant level of well-being, and providing ways and reasons for living (Li et al., 2016). Rock et al. (2014) indicated that patients with cancer who had better levels of hope shared more activities with their families to achieve good social relationships.

Limitations

There are several limitations that need consideration, including the convenience-sampling method, which might limit the generalisation of the results. Furthermore, the research is based on participants' reports, which could be subjective – especially in the aspects related to QOL.

Conclusions

Improving the QOL of older patients with cancer has become an important goal of healthcare providers and has significant public health and social implications. Older patients with cancer reported a low level of QOL, good social-family and functional well-being and low emotional and physical well-being. The predictors of the QOL were anxiety, income, marital status, health insurance, duration of disease, age, educational level, gender and hope.

The study findings address the need to develop nursing interventions and programmes that may improve the QOL of older patients with cancer during treatment. These nursing interventions should target older patients with cancer who are mainly unmarried and female, with no health insurance, a low income, long duration of disease, low educational level and high anxiety level. Moreover, encouraging healthcare providers and policymakers to implement palliative care programmes could be effective. Such programmes include pain and somatic symptom relief and monitoring, psychological and emotional support, as well as religious support. Future research studies are required to include different variables such as social support, pain, stage of cancer, and their effects on the QOL among older patients with cancer during treatment. A random sampling method is recommended in future studies.

Key points for policy, practice and/or research

• Improving quality of life (QOL) in older patients with cancer has become an important goal of healthcare providers and is necessary for patient-centred care.

• QOL level is low among older patients undergoing treatment for cancer.

• There was a significant relationship between educational level, hope, anxiety, depression and all QOL subscales.

• The predictors for overall QOL subscales were anxiety, income, marital status, health insurance, duration of disease, age, educational level, gender and hope.

• There is a need to develop nursing interventions and programmes that may improve the QOL of older patients with cancer during treatment.

Biography

Malakeh Z Malak has a PhD in Community Health Nursing from the Faculty of Nursing at Alexandria University, Egypt, and a Master's degree in Community Health Nursing from the Faculty of Nursing at Jordan University of Science and Technology, Jordan. She started her research career while working as an Assistant Professor at Zarqa University/Jordan. Currently she is working at Al-Zaytoonah University of Jordan at the Amman city in Jordan where she is continuing her work as a researcher in addition to her academic position. She is sits on several editorial boards including Journal of Applied Life Sciences International and SM Addiction Research & Therapy, and reviews for several others. Her research interests are largely related to community health, health promotion and disease prevention.

Loai I Tawalbeh has a PhD in Adult Health Care Nursing from Faculty of Nursing at the University of Jordan, Jordan. He also holds a Master's degree in Adult Health Care Nursing from Faculty of Nursing at Jordan University of Science and Technology, Jordan. He is working as an Associate Professor at AL ALBayt University Jordan where he combines research, reviewing, writing and disseminating his work with teaching.

Loai M Abu-Sharour gained a PhD in Adult Health Care Nursing from the Faculty of Nursing at Griffith University, Australia and a Master's degree in Adult Acute Care Nursing from the Faculty of Nursing at Jordan University of Science and Technology, Jordan. He is an Associate Professor at AL-Zaytoonah University of Jordan where he is works as a researcher in addition to his academic position. Before this he was the Dean of the Faculty of Nursing at Al-Zaytoonah University of Jordan. He regularly reviews for journals as well as presenting his work in papers and presentations. He is active in several health-related organisations.

Declaration of conflicting interests

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

Ethical permission

This research was conducted according to the World Medical Association Declaration of Helsinki. This study was approved by the ethics committee of the Jordan Ministry of Health and by the participating hospital manager. The identification number is MOH REC 170016.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.