The relationship between time spent in volunteering activities and quality of life in adults over the age of 50 years: A systematic review

Abstract

Introduction

Increased attention has focused on the importance of time spent by ageing adults in volunteering. The aim of this systematic review was to analyse literature exploring the relationship between time spent volunteering and quality of life for adults over the age of 50 years.

Method

Electronic searches of nine databases located relevant articles involving adults over the age of 50 in volunteering activities that included psychological, physical and social quality of life domains. The quality of the selected articles was assessed and data extracted using preferred reporting items for systematic reviews and meta-analyses.

Results

Of the 65 articles retrieved, 22 were reviewed and eight included in the final review. Studies included one randomised controlled trial, one cross-sectional and six longitudinal studies. Levels of time spent volunteering by participants within the studies varied considerably. Articles retrieved reported positive quality of life outcomes including increases in life satisfaction, self-esteem and social support and a slowed functional decline.

Conclusion

Volunteering is identified as an important occupation for adults over the age of 50, although the relationship between time spent volunteering and the impact on quality of life outcomes is still not fully understood. Future research is required to better understand the impact of time spent volunteering on quality of life.

Keywords

Volunteering ageing occupation leisure wellbeing

Introduction and literature review

The participation and engagement of older adults in productive activities, such as volunteering, is receiving increased attention in modern society (Morrow-Howell, 2010). Volunteering provides a growing number of ageing adults with opportunities to remain active in older age, resulting in lives that are longer, healthier, more independent and more satisfying (Ayalon, 2008). Historically, older adults have turned to volunteering to remain active, to help ease the transition from full-time work to retirement, to provide structure and to promote positive wellbeing (Chilvers et al., 2010; Haski-Leventhal, 2009).

The definition ‘older adult’ is often problematic and perhaps at times misleading. For example, the World Health Organization (WHO) defines older adult as aged 60+ years (WHO, 2016). In Australia, older Australians are seen as over the age of 65; however, indigenous Australians are defined as older adults over the age of 50 (Australian Institute of Health and Welfare, 2017). Therefore, for the purpose for this study, we will be focusing on older adults aged 50 years and above. In the western world, the number of people who are aged over the age of 65 as a proportion of the population is increasing (WHO, 2011). For example, in Australia in 2013 there were 3.2 million people aged 65 years and over, and this is expected to triple to an estimated 11.1 million by 2061 (Australian Bureau of Statistics (ABS), 2013). In the United Kingdom the population is getting older, with 20.4% the population aged 65 years and over (United Kingdom Office for National Statistics, 2017). Given these predictions of ageing populations, fostering older adult lifestyles that promote healthy ageing and quality of life (QoL) is therefore important to minimise pressure on national health care systems (WHO, 2011).

The United Nations (2011) defined volunteering as a process when ‘individuals give freely of their time, without coercion or remuneration, to a formally structured organisation with the purpose of benefitting others’ (4). Volunteering as an occupation has been associated with significant social and economic benefits to the community, as well as an impact on morbidity rates, functional health indices, health and life satisfaction (ABS, 2008; Warburton et al., 2007).

Defining QoL is extensively debated and made inherently difficult due to the interactional nature of each individual’s subjective experience, within his or her objective context (Constanza et al., 2007). The World Health Organization defined QoL as an individual’s subjective perspective of their position and place in life, relative to their desires and goals (WHO, 2011). In particular, the definition highlights the importance of the required physical, psychological and social domains that contribute to QoL (WHO, 2011). QoL domain outcomes associated with volunteering include increased life satisfaction, self-esteem (Casiday et al., 2008) and a lower risk of mortality (Harris and Thoresen, 2005).

Time use is a phenomenon that is often associated with occupation, when attempting to comprehend associated value and meaning of activity (Edgelow and Krupa, 2011; Hunt and McKay, 2015). Chilvers et al. (2010) examined the time use of older adults and found that older adults who spent decreased time in self-care and more time in leisure and productive activities positively contributed to healthy ageing. It is important for occupational therapists to understand why ageing adults engage in volunteering activities and the meanings these activities hold to assist in designing therapeutic interventions of relevancy that may improve the health of older adults and reduce the strain on health care services (Stav et al., 2012). In particular, Whalley Hammell (2014) suggested that occupational therapists need to examine the benefits of activities such as volunteering and their impact on QoL. Further, little is known regarding if there is a relationship between the time spent volunteering and the postive impact on QoL domains (Ayalon, 2008).

The aim of this systematic review was thus to review literature exploring the relationship between time spent in volunteering activities and impact on quality of life for adults aged 50 and over. The objectives included: (a) analysing the literature for the amount of time spent in volunteering activities; (b) analysing the literature for the impact of volunteering on the physical, psychological and social domains that contribute to QoL.

Method

Searches for literature that focused on the key words-MeSH headings: ‘volunteering’, ‘time spent’, ‘quality of life’, ‘mature adults’ and ‘older adults’ were conducted in April 2014 within nine electronic databases in order to obtain relevant articles. Databases searched included Medline via the Offshore Vessel Inspection Database (OVID), the Cochrane Database, Cumulative Index for Nursing and Allied Health Literature (CINAHL), Wiley Online Library, PsychINFO, OTseeker, PubMed, Australian Public Affairs Information Service – Health (APAIS-Health) and the Allied and Complementary Medicine Database (AMED). Due to time constraints, a hand search was not possible. The search terms used were ‘volunteer*’ OR ‘altruism’ OR ‘civic participation’ OR ‘civic engagement’ OR ‘productive activity*’AND ‘older adults’ OR ‘elders’ OR ‘aged’ OR ‘geriatric’ OR ‘later life’ OR ‘older people’ OR old age* AND ‘quality of life’ OR well-being OR wellbeing OR well being OR health.

Searches for each database were given a search parameter from January 2000–December 2017. The rationale for this time period was that the term ‘quality of life’ begins to appear after development of the international classification of functioning and international classification of diseases (WHO, 2012). Studies were included if they included participants aged 50 years or over and examined the effects of time spent volunteering and/or QoL physical, psychological and social domains. Studies in languages other than English or that were published prior to the year 2000 were excluded, as were books, dissertations, opinion pieces, editorials and any articles from grey literature. Only peer reviewed articles were included, which resulted in 65 available studies. Following removal of duplicates, 35 articles were retrieved and the titles and abstracts were reviewed by the third author in full-text form, to determine whether they fully met all of the exclusion and inclusion criteria. Removal of papers resulted in 22 full-text articles that were eligible for review.

The 22 articles retrieved were quantitative in nature; therefore, a decision was made to determine the methodological quality of the retrieved articles using the Kmet et al. (2004) assessment tool. The tool is a justified scoring system that ‘provides a systematic, reproducible and quantitative means of simultaneously assessing the quality of research encompassing a broad range of study designs’ (11). The scoring system consists of 14 possible criteria and the reviewer utilised the attached instructions to guide decision-making (see Table 1) on the quality of each reviewed article. For each of the 14 criteria, the article has the potential to be awarded points (yes = 2, partial 1, no = 0), with a maximum of 20 (qualitative) and 28 (quantitative) points available. Points were then converted into a percentage. A quality score of >80% is strong, 70–80% is defined as good, 55–70% is considered adequate and >55% is considered to be limited (Kmet et al., 2004). The cut off score for exclusion within this review was determined to be less than 55%. The second author conducted the initial scoring, which was then reviewed by the third and first authors. Any discrepancies were resolved through collaboration and discussion with all three authors. Of the 22 retrieved articles reviewed, 14 articles were then further excluded, where amount of time spent volunteering was not specified or the quality score was below 55% (see Figure 1).

Table 1.

Checklist for assessing the quality of quantitative studies (Kmet et al., 2004).

	Criteria
1	Question/objective sufficiently described?
2	Study design evident and appropriate?
3	Method of subject/comparison group selection or source of information input variables described and appropriate?
4	Subject (and comparison group, if applicable) characteristics sufficiently described?
5	If interventional and random allocation was possible, was it described?
6	If interventional and blinding of investigators was possible, was it reported?
7	If interventional and blinding of subjects was possible, was it reported?
8	Outcome and (if applicable) exposure measure(s) well defined and robust to measurement/misclassification bias? Means of assessment reported?
9	Sample size appropriate?
10	Analytic methods described/justified and appropriate?
11	Some estimate of variance is reported for the main results?
12	Controlled for confounding?
13	Results reported in sufficient detail?
14	Conclusions supported by the results?

Figure 1.

Selection of studies using a modified PRISMA flow diagram (Moher et al. (2009).

Following assessment of methodological quality, eight papers remained (see Table 2). The methodological quality of the remaining studies varied from good to very strong (73%–96%). The second author extracted data from the studies using a modified data extraction form based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) (Moher et al., 2009). The following PRISMA headings were utilised to extract the data: citation; amount of time spent volunteering; QoL domains examined; measurement tools used and statistical significance (see Table 3). The majority of these articles utilised data from existing longitudinal surveys and founded their research on established psychosocial theories such role or activity theory (Lemon et al., 1972; Longino and Karl, 1982; Stryker, 1968).

Table 2.

Methodological quality of selected studies using KMET (Kmet et al., 2004) assessment tool.

Study location and type	Quality of evidence	Population/comparison	Participants (n)	Comparison
Choi and Kim (2011) USA Longitudinal	90% (20/22) Limitations: Self-rated scales for wellbeing domains not provided	Age: 55–84 years (55–64 = 50.1%, 65–74 = 30.2%, 75–84 = 19.7%) Gender: female = 54% Race: Caucasian = 90% (African American mean = 0.07, Hispanic mean = 0.04) Education: high school diploma or higher = 83.1% Median household income per annum: US$42,000	Individuals involved in volunteering. (n = 917)	Made between volunteers and individuals who engaged in charitable donations
Hao (2008) USA Longitudinal	86% (19/22) Limitations: Participants’ characteristics not clearly described	Age: 55–66 years (mean = 59) Gender: female = 56% Race: Caucasian = majority. African American mean = 0.16, Hispanic mean = 0.08 Education: mean = 12.20 years Household income per annum: mean = US$40,500	Individuals involved in high-level volunteering (>100 hours per annum) and low-level volunteering (<100 hours per annum) Individuals involved in paid work (n = 7069)	Volunteers and non-volunteers. Dual-activity participants and single-activity participants
Lum and Lightfoot (2005) USA Longitudinal	Quality score = 82% (18/22) Limitations: No estimation of variance given Confounding factors not controlled for	Age = 70+ years (in 1993) (mean = 77) Gender: Female = 60% Race: Caucasian = 88% Education: 13% = college degree, 15% = some college education, 31% = high school diploma, 42% = no high school diploma Household income per annum: mean = US$25,879 Partnered: 52% (widowed = 40%)	(n = 7322)	Individuals who are not involved in volunteering for = > 100 hours per annum
Luoh and Herzog (2002) USA Longitudinal	Quality score = 90% (20/22) Limitations: No estimation of variance given	Age = 70 + (mean = 76.4) Gender: female = 63% Race: 89% Caucasian Education: average = 11 years Household income per annum: US$26,000 Partnered: 42%	Individuals involved in volunteering (n = 4860)	Comparison between paid work and volunteering and between low and high levels of volunteering hours. Additional comparison made between combination of volunteering and employment (for at least 100 hours per annum) and those who were not employed. Individuals involved in volunteering for = > 100 hours per annum. Individuals who are not involved in volunteering for = > 100 hours per annum.
Matz-Costa et al. (2014) USA Longitudinal	73% (16/22) Limitations: method of subject selection not appropriate Large selection bias Subject/comparison group differentials not sufficiently described	Age = 50 + (mean = 62.2 years) Gender: female = 74.9% Race: 97% Caucasian Education: Graduate degree = 68.6% Household income per annum: mean = US$80,000	Individuals involved in paid work Individuals involved in volunteering (mean = 8.84 hours per week) Individuals involved in caregiving (n = 300)	Made between participant groups and between non-involved individuals
Morrow-Howell et al., (2003) USA Longitudinal	96% (21/22) Limitations: Elements of results not reported in sufficient detail	Age: (mean = 70.1) Gender: female = 67% Race: Caucasian = 69% Education: (mean = 10.3 years) Household income per annum: mean = US$17,522	Individuals involved in volunteering (mean = 71.5 hours per annum) (n = 1669)	Non-volunteers
Pilkington et al. (2012) AUS Cross-sectional	90% (20/22) Limitations: Small sample size for survey No considerations of racial demographics	Age = 55–94 years (mean = 65.2) Gender: female = 51.5% Race: Not mentioned Education: 52.9% = less than 15 years of education. Partnered: 73.3%	Individuals involved in moderate level volunteering: < 7 hours per week (mean = 149 hours P/A). Individuals involved in high-level volunteering > 7 hours per week (mean = 635 hours P/A) (n = 561)	Non-volunteers
Rook and Sorkin (2003) USA Randomised controlled trial	96% (25/26) Limitations: Small sample size	Age: 60–92 years (mean = 70.52) Gender: female = 65.6% Education: Majority = high school diploma Household Income P/A: Majority = US$10,000–US$15,000 Partnered: 63.9% widowed, divorced or single	Participated in foster grandparent programme (n = 52, time spent = 20 hours per week) (n = 180)	Control group 1 n = 69 Control group 2 n = 59

Table 3.

Extraction of information from included studies based on modified PRISMA guidelines (Moher et al., 2009).

Study	Time spent volunteering	Health/QoL domains	Measurement tools for health/QoL domains	Results
Choi and Kim (2011)	Median = 80 hours per month	Psychological wellbeing domains: Self-acceptance Autonomy Environment mastery Purpose in life Personal growth. Controlled for: Social wellbeing Domain: Social integration	The Ryff scales of psychological wellbeing Self-evaluation of quality of relationships with others and with their community (on seven point scale) and number of social meetings attended	Volunteering between one to 10 hours per month was found to have a positive direct effect on psychological wellbeing (p = < 0.05). Volunteering > 10 hours per month (more than 120 hours per year) was found to have no positive long-term effect (p = 0.06) on psychological wellbeing
Hao (2008)	< 100 hours of volunteering per annum = 21% of participants. > 100 hours of volunteering per annum = 12% of participants	Psychological wellbeing domains: Depression/psychological distress Controlled for: Self-assessed health and functional disability	The Centre for Epidemiologic Studies – Depression (CESD) Scale Self-assessed by indicating number of chronic diseases Self-rated number of ADL and IADL with perceived difficulties	Protective effects for psychological wellbeing were found for < 100 hours of volunteering per annum (p = –0.018) Engagement in two productive activities (low-level volunteering for < 100 hours per annum and paid employment) was found to promote a reduced rate of decline in mental health (p = –0.028)
Lum and Lightfoot (2005)	= > 100 hours in 12 months prior to interview = 13% of participants Mean = 305 hours in 12 months prior to interview	Physical wellbeing Domains: Health Medical conditions Functional difficulties Mortality Psychological wellbeing Domain: Depression	Self-rated perception of health (on scale from 1 = poor to 5 = excellent). Number of physician-diagnosed medical conditions Self-rated number of ADL and IADL with perceived difficulties Percentage of participant deaths at next interview CESD Scale	Any amount of time spent volunteering was positively correlated with levels of depression, self-reported health and function (p = < .001) Older adult volunteers had a decreased risk of mortality and were 28% less likely to die prior to next interview. Volunteering ≥ 100 hours per annum = slower decline in health and physical function (p < .001), had slower increases in depression levels (p < .001) and lower risk of mortality (p < .01). A curvilinear relationship was found between perceived health benefits and the number of hours spent volunteering for < four full days per week.
Luoh and Herzog (2002)	< 100 hours per annum = 85.55% of participants = > 100 hours Per annum = 14.45% of participants	Physical wellbeing Domains: Difficulties with ADL Self-rated health Major chronic conditions Mortality	Self-rated number of ADL and IADL with perceived difficulties / requiring assistance Self-rated perception of health (on scale from 1 = poor to 5 = excellent) Number of physician-diagnosed medical conditions Percentage of participant deaths at next interview	Participants who volunteered ≥ 100 hours were significantly less likely to report limitations in ADL and poor health (p < .01). ‘The relationship between activities and health was not linear but reflected a threshold between no or little activity and a substantial amount’ (499). Volunteering > than 100 hours per annum was found to have a protective effect on decline in health. Risk of mortality was significantly lower for volunteers who participated in = > 100 hours per annum (p < .01), in comparison to those who did not (5.6% vs. 16.8%).
Matz-Costa et al. (2014)	M = 8.84 hours per week = 36% of participants	Psychological wellbeing Domains: Life satisfaction Mental health status Engagement in occupations Controlled for: Physical wellbeing Domain: Self-rated health	Self-rated perception of life satisfaction and mental health status (on an 11-point scale from 0 = worst to 10 = best) Adapted version of the Utrecht Work Engagement Scale Self-rated perception of health (on scale from 0 = worst to 10 = best)	Time spent volunteering was not associated with psychological wellbeing differences, relative to non-volunteers. High levels of engagement in volunteering and paid work was associated with significantly higher levels of psychological wellbeing (p < .001), relative to those who were less engaged.
Morrow-Howell et al. (2003)	M = 71.5 hours per annum	Psychological wellbeing Domain: Depression Physical wellbeing Domains: Self-rated health Functional dependency/decline Controlled for: Social wellbeing Domain: Social integration	CESD Scale Self-rated perceived level of dependency/assistance needed in ADL and IADL (from one to four, four = most severe level of impairment) Self-rated amount of contact with friends (telephone and in person); (from one to six, with six being no contact)	Self-evaluated health and function, depression and degree of functional dependency were all positively affected by volunteering (p < .01). Study found that volunteering hours > 100 per annum was not associated with positive wellbeing. > 100 hours per annum was associated with a decline in levels of mental health and self-rated health. A curvilinear relationship was found between volunteering and QoL/health benefits. The benefits increased with time spent volunteering, until reaching a maximum amount of benefit reached at 100 hours per annum or approximately 2–3 hours weekly. Perceived benefit to others was not found to be influential on the relationship between volunteering and depression (p = .99), self-rated health (p = .45) or functional dependency (p = .30).
Pilkington et al. (2012)	< 7 hours per week n = 220 > 7 hours per week n = 55	Psychological wellbeing Domain: Life Satisfaction Positive and negative affect Social wellbeing Domains: Availability of social support Positive and negative social exchanges Physical wellbeing Domain: Self-rated health	Self-rated life satisfaction was measured using the Satisfaction with Life Scale The Positive and Negative Affect Schedule (PANAS) A subset of items from the Lubben Social Network Scale was used to measure availability of support from family, friends and neighbours Self-rated assessment of the quality of their social exchanges using two subscales adapted from the Positive and Negative Social Exchanges scale Self-rated perception of physical health using the RAND-12 Physical Health Component (PHC) score	Moderate levels ( < 7 hours per week) and high levels ( > 7 hours per week) of volunteering were associated with significantly higher levels of positive affect (p = < .001). When social support was controlled for, the relationship was no longer significant. Volunteering and negative affect = no association found.
Rook and Sorkin (2003)	20 hours per week n = 52	Psychological wellbeing Domains: Self-esteem Depression Loneliness	Self-esteem was assessed with the 10-item Rosenberg Self-Esteem Scale. CESD Scale Loneliness was measured using 10 items from the 20-item UCLA Loneliness Scale	No significant differences between groups for depression, self-esteem or loneliness

ADL: activities of daily living; IADL: instrumental activities of daily living; UCLA: University of California Los Angeles.

Results

Time spent volunteering and impact on quality of life

Seven out of the total eight studies were conducted in the cultural and societal context of the USA. The majority of the study participants were women, Caucasian, with median household incomes ranging from US$10,000–US$80,000 and a variety of education levels (see Table 2). Levels of time spent volunteering by participants within the studies varied considerably. The lowest recorded amount was two to three hours per month (Morrow-Howell et al., 2003), while some participants spent up to 1878 hours per year (Lum and Lightfooot, 2005). The mean number of hours spent volunteering ranged from 71.5 per year (Morrow-Howell et al., 2003) to 636 per year (Pilkington et al., 2012).

Morrow-Howell et al. (2003) found that volunteering had a positive effect on all three QoL domains (physical, psychological and social QoL). This effect was found to be curvilinear, wherein increased benefits were found with increased time commitment, up to 100 hours per year. The author found that benefits were established from a minimum of two to three hours monthly, up to a maximum amount of two to three hours weekly (100 hours per year). This positive relationship was found to be significantly associated with the QoL of older adults (p = <.01). Higher amounts than 100 hours annually were not found to be associated with increased wellbeing benefits. The study also found that a minimum of only 2–3 hours per month was needed for a positive relationship to occur. A similar curvilinear relationship was found in Lum and Lightfoot’s (2005) study; however, perceived health benefits did not begin to decrease until volunteer hours reached approximately four full days a week (see Table 3). A linear relationship was not found in Luoh and Herzog’s (2002) study, in which only volunteering at greater than 100 hours per year was found to have protective effects against a decline in health outcomes.

Physical domain of quality of life

Three studies measured physical health through assessing the number of accumulated chronic medical conditions (Hao, 2008; Lum and Lightfoot, 2005; Luoh and Herzog, 2002). In two of these studies, the medical condition was self-identified by the participants (Hao, 2008; Luoh and Herzog, 2002), while one of the studies stipulated that the chronic medical condition had to be physician diagnosed (Lum and Lightfoot, 2005). Luoh and Herzog (2002) used the number of medical conditions as a control, while Lum and Lightfoot (2005) used the number of medical conditions to measure the effects of volunteering on physical health decline. No significant differences were found for risk of accumulating chronic medical conditions and volunteering in Lum and Lightfoot’s study (2002).

Morrow-Howell et al. (2003) found that there was an association between functional decline and age. The association found that as age increases, so does functional dependency. However, this association was found to be weaker for volunteers, in comparison to non-volunteers. Thus, volunteering may potentially moderate the relationship between increasing age and functional dependency. In Hao’s (2008) study, participation in one or more productive activities (volunteering or volunteering in combination with paid employment) was measured using regression analysis against physical health outcomes of self-perceived health, difficulties with activities of daily living (ADL) and number of chronic medical conditions. Hao (2008) found that participants who participated in dual-activities (both volunteering and paid employment) exhibited better physical health, in comparison to single-activity participants. Similarly, Luoh and Herzog (2002) found that volunteer work in combination with paid employment for a minimum of 100 hours per year yielded increased survival and self-perceived health benefits.

Psychological domain of quality of life

Psychological QoL was measured by seven out of eight studies, through utilisation of self-rated scales for: general mental health, purpose in life, life satisfaction, self-esteem, loneliness, positive affect and negative affect (Choi and Kim, 2011; Hao, 2008; Lum and Lightfoot, 2005; Matz-Costa et al., 2014; Morrow-Howell et al., 2003; Pilkington et al., 2012; Rook and Sorkin, 2003). Choi and Kim (2011) found that between one and 10 hours of volunteering per month (or up to 120 hours annually) had a significant positive effect on psychological QoL (see Table 3). Any more than 10 hours of volunteering per month was not found to have long-term positive effects on psychological wellbeing. Hao (2008), using growth curve modelling, identified how volunteering was associated with decreased depression levels. In this study, both low-level (<100 hours per annum) and high-level (≥100 hours per annum) volunteers were found to have lower baseline levels of depressive symptomology, relative to non-volunteers. Baseline low-level volunteering was also found to predict a slower rate of decline in psychological wellbeing. Dual-activity and single-activity participants were also found to have higher baseline psychological wellbeing levels. Dual-activity participants enjoyed slightly higher levels of baseline psychological wellbeing, relative to single-activity participants, according to the magnitude of the coefficient, which was stronger for dual-activity participants. Both low-level volunteering and full-time employment were found to have protective effects against mental health decline (Hao, 2008). Life satisfaction was assessed in two of the included studies. Life satisfaction was assessed in the study by Pilkington et al. (2012), through use of the Pavot et al. (1991) Satisfaction with Life Scale. A statistically significant association was found between moderate level volunteering (<7 hours per week) and higher life satisfaction (p < .001). In the study conducted by Matz-Costa et al. (2014), life satisfaction scores were combined with overall, subjective scores of mental health status, to determine levels of psychological wellbeing. The study found that those involved in volunteer work or paid work did not report higher levels of psychological wellbeing, in comparison to non-volunteers. Participants who were involved with caregiving were found to report lower levels of psychological wellbeing, relative to those not involved.

Social wellbeing domain of quality of life

Pilkington et al. (2012) found that both moderate (<7 hours per week) and higher levels of volunteering (>7 hours per week) provided greater availability of social support from friends and neighbours. Additionally, moderate level volunteers reported increased availability of social support from family and more positive social exchanges, relative to non-volunteers. Pilkington et al. (2012) discovered that this increased availability of social support from family members positively influenced the association between wellbeing and volunteering.

In Rook and Sorkin’s (2003) randomised controlled trial, participants in the intervention (volunteer) group were more likely to form new positive social ties, in comparison to the two control groups. However, they were also more likely to form new negative social ties. Therefore, these new social ties were found to function as a source of both positive and negative social exchanges.

Discussion

This systematic review presents a summary of existing literature, exploring the impact of time spent volunteering on QoL domains for adults over the age of 50. The findings provide evidence to suggest that time spent in volunteering is beneficial for this age group and positively impacts on psychological, social and physical QoL domains. The eight studies identified through the search criteria suggest there is no agreed or ideal amount of required time spent in volunteering activities when investigating any positive impact of volunteering on QoL domains for adults over the age of 50. The findings of the systematic review identify that high levels of time spent in volunteering activities (100 hours or more per year) were often associated with positive QoL domain outcomes, including decreased levels of depression (psychological QoL domain). This finding is supported by Casiday et al.’s (2008) study, which was undertaken to determine the health impact of volunteering and found that volunteering increased mental health, positive healthy behaviours and overall life satisfaction. The systematic review also provides evidence of the positive impact of volunteering on the physical domain of QoL and includes a decreased risk of mortality (physical QoL domain) (Lum and Lightfoot, 2005; Luoh and Herzog, 2002) (see Table 3). Harris and Thoresen (2005) found that more frequent volunteering was often associated with delayed mortality when controlling for the effects of socio-demographics, medical and disability characteristics and self-ratings of physical activity.

Conversely, Morrow-Howell et al. (2003) found that spending more than 100 hours volunteering per year was to a certain extent detrimental to the QoL of participants. In fact, their study found that very low amounts of volunteering were sufficient for a positive relationship to occur. This raises the interesting point that, for many people, the overall quality of the volunteering experience plays a significant factor on their own QoL. As Morrow-Howell et al. (2003) suggest, QoL outcomes are more likely to be impacted by factors of the volunteer experience including the volunteer physical, social and institutional organisational environment and culture.

The findings of this systematic review are then not definitive and raise questions regarding issues associated with the impact of the type of volunteering, the value ascribed by the participant and other potential influencing environmental factors that might impact on the outcomes of the experience; however, it has been suggested that there are no differential benefits based on participants’ personal characteristics (Morrow-Howell et al., 2003). While no definitive connections can be made with the specific amount of time, there is a clear indication that time spent volunteering may provide opportunities for adults over the age of 50 to remain physically and cognitively active in older age, resulting in lives that are longer, healthier, more independent and more satisfying (Ayalon, 2008).

While physical decline is to be expected in an ageing adult, it was found that people who volunteered might experience positive physical health (Hao, 2008), especially when also engaged in some form of paid employment. Volunteering generally requires some form of physical activity, which may benefit the health of the older adult, and there is evidence from the reviewed studies to suggest that volunteering as an occupation may have significant additional benefits in promoting active physical health strategies that may increase functional ability (Lum and Lightfoot, 2005); however, there is debate about whether volunteering improves health (Morrow-Howell et al., 2003).

The impact of time spent in volunteering on psychological QoL is supported by the findings of the systematic review and it is apparent that only small amounts of volunteering had significant impact on the mental health of participants. These findings are consistent with studies that have found positive correlations between volunteering and perceived health, life satisfaction and a negative correlation to depression (Haski-Leventhal, 2009). These findings are of importance, as older adults who work with occupational therapists may find engaging in significant amounts of volunteering activity unsustainable, for both physical and cognitive reasons. Interventions may be able to focus on small levels of voluntary engagements, to achieve positive psychological outcomes. While studies of QoL outcomes are considered an important way to understand health and wellbeing, it is most likely for many volunteers that their own perceived quality of life may not be a driving factor and they are instead motivated to volunteer for altruistic reasons (Kahana et al., 2013).

The results indicate the importance of social connectedness and volunteering. Pilkington et al. (2012) identified that social support significantly influenced the relationship between time spent volunteering, health and QoL for older individuals. It has been suggested that volunteers who have more social connections are likely to be less lonely and have the opportunity to be more informed and hence empowered (Haski-Leventhal, 2009). It may be that occupying multiple roles (including volunteer roles) as an older adult has more positive health outcomes because multiple roles increase social networks (Morrow-Howell et al., 2003). Similarly, volunteering as an activity that encapsulates the essence of positive meaningful engagement in activity as well (Anderson et al., 2014; Fisher, 2013; Jonsson et al., 2001) is not to be dismissed. Maintaining ageing adults within their current volunteer role or introducing volunteering as an occupational intervention may well have therapeutic benefits (Anderson et al., 2014). A better understanding of the relationship between time spent volunteering and the kind of positive impact on QoL domains would therefore be of significant benefit when planning interventions with older adults.

Limitations

Studies included were mainly conducted in the United States (USA) and involved Caucasian women. This is a major limitation in terms of sample representation and generalisability to other groups and cultures within western society. The majority of the studies identified within the systematic review utilised longitudinal designs, which can be subject to high levels of bias or the Hawthorne effect (Baker, 2006). Another potential source of bias to the studies included is referral or volunteer bias. Volunteer bias may result in unrepresentative numbers of volunteers participating in the studies, as volunteers are ‘more likely to participate in unpaid research’ (Pilkington et al., 2012: 258). A limitation of the identified studies within the systematic review is the method used to measure time as most used self-report methodology. Kan and Pudney (2008) have argued that time-use measurement methodology is often prone to error and may bias the results of subsequent statistical modelling. Likewise, causation may be difficult to determine between variables and result in residual cofounding (Fewell et al., 2007).

The studies predominately used adapted self-rated scales to measure health and QoL outcomes, which may have influenced their validity and reliability. The use of valid and reliable global QoL or health measurement tools across the studies may have strengthened their findings, such as the World Health Organization Quality of Life Assessment (WHOQOL) (World Health Organization [WHO], 1995). The WHOQOL has been successfully tested and has excellent sensitivity when used with older adults (Silva et al., 2014) to comprehend QoL. The results of these studies indicate that additional research is merited to further investigate the mediating effect of social support, using study designs of a higher level of evidence (Baker, 2006), with adequate sample sizes and similar baseline psychological health.

Conclusion

The findings from the systematic review indicate that time spent in volunteering is beneficial for adults over the age of 50 years and positively impacts upon QoL domains. This said, the evidence appears to suggest that there is no general consensus regarding the ideal amount of time spent volunteering to optimise health and QoL domain outcomes. As the population ages within western societies and there is the likelihood of an increasing number of individuals continuing paid work in later life, understanding how volunteering may provide opportunities for leisure and maintenance of health and wellbeing is then crucial. Occupational therapists are in a unique position to facilitate QoL outcomes amongst this population. Understanding around satisfaction and occupational wellbeing and its relationship to volunteering then requires further investigation. Substantiation of these findings and further evidence may be utilised to encourage increased numbers of older adults to engage in volunteer work, due to its relationship to QoL. Time spent volunteering may act to assist adults’ transition from full-time employment to retirement and subsequently support their levels and experience of QoL.

Key findings

This systematic review identifies that high levels of time spent in volunteering activities (100 hours or more per year) were associated with positive QoL domain outcomes, including decreased levels of depression.

There is no general consensus regarding the ideal amount of time spent volunteering to optimise health and quality of life domain outcomes.

Understanding around satisfaction and quality of life and its relationship to volunteering requires further investigation.

What the study has added

This a first step in exploring the association between time spent in volunteering activities and its impact on quality of life outcomes for adults over the age of 50 years.

Footnotes

Research ethics

Ethics approval was not required for this study.

Consent

Informed consent was not required for this systematic review.

Declaration of conflicting interests

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

Funding

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

Contributorship

All three authors were involved in the conceptualisation and design of the study. Jaya Saraswati carried out data retrieval. All authors were involved in data analysis and drafting of the manuscript. All authors were involved in continued revisions of the manuscript.

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