Analysis of the Relationships between Quality of Life, Resilience, and Life Satisfaction Variables in Retired Individuals

Abstract

Quality of life, resilience, and life satisfaction are influential variables during periods of change and adaptation, such as retirement. To assess the relationships between these variables and to analyze differences based on sex and length of time in retirement. This descriptive-correlational study was conducted with a sample of 63 participants, aged 50 to 84 years, who were effectively retired and residing in Spain. Participants completed a form measuring levels of resilience, quality of life, life satisfaction, and sociodemographic data. The data showed a positive and significant correlation between resilience and life satisfaction, and between quality of life and life satisfaction. Significant differences were found in quality of life based on the length of time in retirement. This study has elucidated the relationships between quality of life, resilience, and life satisfaction, as well as the influence of sociodemographic variables on these factors. These insights will aid in developing effective intervention programs for the retirement stage that promote quality of life, resilience, and life satisfaction among retired individuals.

1. Introduction

1.1. The Aging Process and Its Implications on the Elderly Population

The increase in life expectancy allows people to enjoy a longer retirement period [1], while simultaneously impacting the social systems supporting the retirement and aging process, necessitating the provision of adequate, affordable, and sustainable systems for the population [2]. Due to this increase in life expectancy, Guallo et al. [3] emphasize the importance of promoting health, disease prevention, and healthy lifestyles to delay the onset of negative consequences of aging. As a society, preparing for this stage must encompass economic issues associated with health care expenses and treatment duration, social issues related to the quality and accessibility of care services, or psychological needs. Thus, seniors in good physical, mental, social, and emotional health could contribute to generating social, economic, and psychological value after retirement. Conversely, compromised health directly impacts the economy through direct costs associated with health care and/or indirect costs, such as reduced consumption, productivity, civic participation, or increased use of social services facilities [2].

1.2. Factors That Encapsulate the Aging Process and Population

The World Health Organization (WHO) [4] views aging as a process affecting all individuals, varying in pace and nature based on individual factors such as genetics, lifestyle, and environmental conditions. Furthermore, the WHO [4] details the different dimensions of a person affected by the aging process: the biological dimension, the psychological dimension, and the social dimension. Additionally, it considers participation, health, and safety as the three pillars of active aging, with autonomy, independence, quality of life, and life expectancy as relevant factors [5]. Thus, to delineate the concept of old age, individual and environmental factors must be considered, differentiating between various types of aging [6]. Concerning the factors influencing aging, the WHO [7] associates this aging process with life transitions, considering retirement as one of them.

1.3. Retirement

Retirement can be considered a turning point in a person’s life within the aging process, involving personal development and social participation while posing risks to physical and mental health [4], influencing their perception of quality of life [8]. Martínez-Lugo and Rodríguez-Montalbán [9] conceptualize retirement as a life transition experienced by a working individual, representing the redefinition of their activities from work-related to personal life-related ones. The perspective from which individuals perceive retirement may vary, making risk and protective factors areas to work on to define this perception. Risk factors that could lead to a negative perception of retirement are associated with changes in social role, family modifications, reduced economic income, feelings of uselessness, anonymity, and decreased physical and mental capacity. Conversely, protective factors include the recovery of lost freedom and the availability of leisure time, which previously, due to involvement in the labor force, was not possible [10].

1.4. Positives and Negatives of Retirement

Kuhn [11] and Sirlin [12] found that retirement can have positive or negative effects on physical and mental health: (1) Positive effects: improved mental health by reducing stress and anxiety associated with work-related tensions; improved sleep quality by eliminating work schedules; increased social participation by having more free time, greater family dedication, a sense of freedom, creative use of time, and the opportunity to develop hobbies. (2) Negative effects: increased sedentary behavior leading to overweight or obesity, deteriorating physical health, and increasing the risk of chronic diseases; reduced income; lower development of personal capabilities; increased uncertainty about the future; diminished interpersonal relationships, leading to social isolation and increased risk of loneliness and depression; conflicts with partners; anxiety and psychosomatic disorders; and decreased self-esteem, resulting in decreased sense of identity. Additionally, retirement can be evaluated as a positive or negative depending on resources, conditions, and attitudes. The characteristics of the retirement process can help understand why retirement may be satisfactory for some individuals and not for others [13]. Concerning economic resources, upon retirement, Sánchez-Izquierdo [14] associates it with the cessation of paid work and the subsequent receipt of associated pensions. However, this cessation of paid work would not occur due to the inability to perform paid work but rather due to legislation and age constraints determined by current regulations [14,15]. Once retirement becomes effective, the individual faces a transition period involving a role change. To define this process, a retirement adaptation model was proposed, suggesting that retirees pass through different phases until assuming the definitive retiree role. Different authors [13,14,16,17,18,19]; addressed the phases described in Atchley’s model: (1) pre-retirement, (2) retirement, (3) disenchantment, (4) reorientation, (5) stability or routine, and (6) completion. Aymerich et al. [16] highlight that during the retirement adaptation process, levels of perceived life satisfaction vary between phases, with the adaptation process lasting between six months and a year and a half. By accepting retirement as a loss of the worker role and the age associated with it as a turning point in a person’s life in the transition to old age, retirement could become a stressful event for the individual (Jordan, 1999 cited in [20]) due to the changes and events inherent to this stage affecting social, physical, and psychological levels.

1.5. Coping Strategies for Retirement

Psychologically, stress can be considered one of the risk factors that can significantly influence the health and quality of life of older adults [21]. From Lazarus and Folkman’s psychological stress model [22], retirement is considered a potentially stressful psychosocial factor that can have a negative impact on a person’s health. Lazarus and Folkman [22] defined stress as “a particular relationship between the individual and the environment that is appraised by the individual as taxing or exceeding his or her resources and endangering his or her well-being” (p. 43). It is important to understand the factors that influence coping with changes to explore the assessment that individuals and society make of retirement [18]. Regarding coping strategies for change, concepts such as resilience, as a capacity for growth and development in adversity, become particularly significant [23], as well as their potential influence on quality and satisfaction of life.

1.6. The Concept of Resilience

Resilience can be considered as individuals’ capacity to face, overcome, or successfully adapt to adversities (cited in [24]). This mechanism is fundamental in coping with stressful conditions, situations, or conflicts [24]. Resilience could reduce the intensity of stress and the appearance of anxious or depressive symptoms, being a relevant factor in aging (cited in [24]). The American Psychological Association [25] defines resilience as an adaptive process to adversity, traumatic situations, threats, and stressful situations, as well as the ability to recover after experiencing difficult events. Resilience is related to other psychological constructs such as quality and satisfaction of life. In order to explore this relationship between resilience and quality of life in older adults, Varas and Saavedra [26] conducted a study to examine the relationship between quality of life and resilience levels in a sample of 82 older adults. They found a positive and significant correlation between resilience and quality of life variables. On the other hand, Tan et al. [27] agree that older adults with higher resilience present higher quality of life (finding a significant and positive correlation between both variables). In addition, Zheng et al. [28], in their study with a sample of 418 adults aged 60 or older, found a significant and positive relationship between resilience and life satisfaction. Furthermore, the authors indicate that women have higher levels of resilience than men [28]. In this regard, Vilte [24] also finds that women have higher levels of resilience than men. Regarding retired time, Pimentel and Freitas [29] did not find a significant relationship between this variable and levels of resilience.

1.7. Quality of Life and the Implications of Quality of Life

To analyze quality of life at any age, including old age, it is considered necessary to study individuals’ living conditions [30]. Analyzing these conditions would allow detecting how they influence quality of life and exploring if they are susceptible to change to maintain or improve quality of life. Despite its growing momentum, the concept of quality of life is relatively recent and faces difficulties in agreeing on a definition, with numerous definitions of the concept [31,32,33,34,35]. For the development of this work, the definition of quality of life proposed by the WHO [34] has been taken into account: “An individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns. It is a concept that includes the physical health of the individual, their psychological state, the level of independence, their social relationships, and their relationship with the environment and the spiritual domain” [34] p. 29. In research related to quality of life in older adults, studies such as Guerrero et al. [36] analyze levels of quality of life in a sample of 29 individuals aged 50–85 years through sociodemographic variables analysis and the The World Health Organization Quality of Life (WHOQOL-BREF) scale [37], obtaining results showing approximately 80% satisfaction with quality of life and health adequacy for their age in this population. Regarding the importance of sociodemographic variables, statistically significant differences in perceived quality of life have been found [38] between men and women, with women reporting higher quality of life than men using the WHOQOL-BREF scale [37]. On the other hand, in the study by García and Lara-Machado [39], women also reported higher quality of life than men. However, in the study by Maldonado and Mendiola [40], no significant differences in quality of life were found based on sex, which also occurs in the study by Tan et al. [27] where no significant differences in quality of life between men and women were found. Regarding the influence of retired time on quality of life, Betanzos-Díaz et al. [41] did not find statistically significant differences. Along with quality of life, several authors [42,43,44] agree on the importance of life satisfaction as one of the main indicators of psychological health. In recent decades, the concept of life satisfaction has gained meaning in relation to “an individual’s overall evaluation of their life quality in the face of their circumstances” (cited in [42], p. 2). On the other hand, Pérez-Escoda [44] considers life satisfaction as “the personal perception of one’s own situation in life based on personal goals, expectations, values, and interests influenced by the cultural context of reference” (p. 3). In research on the influence of retirement and life satisfaction, Aymerich et at. [16] and Cándido et al. [17] present the results obtained in the initial studies conducted on the subject [16,17]. For this reason, Richardson and Kilty [cited in 16,17] conducted a longitudinal study where they found a decline in life satisfaction during the first six months after retirement. Additionally, other authors [16,17] observed that once retirement becomes effective [16] and after three years have passed since retirement [17], the levels of satisfaction increase, becoming similar to those prior to retirement. However, Pimentel and Freitas [29] did not find statistically significant differences in life satisfaction based on retired time. Another sociodemographic variable that has been studied in relation to life satisfaction is sex; in the study by Zheng et al. [28], no statistically significant differences were found between men and women. Recently, life satisfaction in retirement has been reanalyzed. Şahin et al. [45], in their study conducted with 517 individuals aged 65 or older, indicate that there is a significant and positive relationship between quality and life satisfaction in older adults.

1.8. Objectives

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Explore the quality of life levels among retired individuals.

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Measure the life satisfaction levels among retired individuals.

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Assess the resilience levels among retired individuals.

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Investigate the relationships between quality of life, resilience, and life satisfaction variables.

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Describe the relationships between quality of life, resilience, life satisfaction, and sociodemographic variables.

1.9. Hypotheses

H1: 

Higher scores on the resilience scale are associated with higher scores on the quality of life scale.

H2: 

Higher scores on the quality of life scale are associated with higher scores on the life satisfaction scale.

H3: 

Higher scores on the resilience scale are associated with higher scores on the life satisfaction scale.

H4: 

There are differences in the mean scores of quality of life, resilience, and life satisfaction based on gender.

H5: 

There are differences in the mean scores of quality of life, resilience, and life satisfaction based on the length of retirement.

2. Method

2.1. Participants

To be able to participate in this study, the following inclusion criteria were established: Individuals with effective retirement and residents in Spain. People under 50 years old and institutionalized individuals were excluded.

In total, 80 individuals participated, of which 8 were excluded for not meeting the inclusion criterion of being retired, 1 was excluded for not meeting either the age or retirement criteria, 1 was excluded for not meeting the age criterion, and 7 were excluded because they marked multiple response options in at least 1 question when responding to the questionnaire. Therefore, the final sample consisted of a total of 63 individuals, of which 31 were men and 32 were women. The age range varied between 51 and 84 years (M = 68; SD = 5.54). Regarding marital status, 6.35% were single, 69.84% were married, 7.94% were widowed, and 15.87% were divorced or separated. In terms of time since retirement, 11.11% had been retired for less than six months, 9.52% from six months to one year, 19.05% between one and two years, and 60.32% for two years or more. Finally, regarding the type of retirement, 57.14% underwent ordinary retirement, 41.27% early retirement, and 1.59% partial retirement. There were no participants with flexible retirement.

2.2. Instruments

• Questionnaire of Sociodemographic Variables: age, sex, marital status, type of residence, type of retirement, and time since retirement.
• The Satisfaction with Life Scale (SWLS) developed by Diener et al. [46] in its translated and adapted version to Spanish [47]. The Spanish adaptation has a Cronbach’s alpha reliability coefficient of 0.84, implying good internal consistency. The internal consistency in our study was 0.83 [47]. This scale consists of five items that are responded to using a five-point Likert scale (5: Totally Agree; 4: Agree; 3: Neutral; 2: Disagree; 1: Totally Disagree) [47].
• Brief Resilience Scale (BRS) [48] in its Spanish adaptation by Rodríguez-Rey et al. [49]. This adaptation has a reliability assessed by Cronbach’s alpha of 0.83 [49]. The internal consistency in our study was 0.69. This scale consists of six items that are responded to using a five-point Likert scale (5: Totally Agree; 4: Agree; 3: Neutral; 2: Disagree; 1: Totally Disagree).
• The World Health Organization Quality of Life (WHOQOL-BREF, a shortened version of the WHOQOL-100, developed by The Whoqol Group [37]) adapted in its Spanish version by Lucas-Carrasco [50]. This scale will be used to measure quality of life. Regarding the WHOQOL-BREF, correlations of 0.90 were found with scores of the WHOQOL-100 [37]. In a Spanish-speaking sample, the scale has an internal consistency of 0.94, indicating reliability [51]. The internal consistency in our study was 0.85.

2.3. Procedure

A non-probabilistic sampling method, specifically snowball sampling, was used. Initially, the Google Forms questionnaire, along with the privacy policy and informed consent, was sent to the project supervisor. Upon approval, data collection was carried out using the questionnaire sent through instant messaging services, emails, and social media platforms (WhatsApp, Telegram, LinkedIn, Facebook, and a QR code were used, which was placed on flyers in health centers, town halls, and retirement centers in a town in Toledo (Spain)).

Participation in this study was entirely voluntary and anonymous, with participants not receiving any incentives for participation. Completing the survey posed no risk to the participants; additionally, a contact email with the researcher was provided to address any questions that may arise. To complete the form, participants had to read and accept the informed consent and privacy policy; it was not possible to respond to the questionnaire without accepting and consenting to them. This study was conducted following the principles of the Declaration of Helsinki. After ethical approval was obtained from the Ethics Committee of University International of Valencia (Research Approval No. CEID_21/0012), the data collection process began. On the first page of the online survey link, the participants were informed about this study, including its purpose, benefits, and expectations from them. Those who agreed to participate in this study declared that they agreed to participate in this study by clicking the relevant button on the information page. The data were collected anonymously, and no personal information was sought from the participants. The authors employed several methods to ensure the data received were from individuals meeting the inclusion and exclusion criteria: Potential participants completed an initial screening questionnaire that collected essential information such as age, retirement status, and other sociodemographic details, allowing verification that only individuals aged 50 and above who were retired were included in this study. Responses were cross-checked for consistency, with any discrepancies triggering further scrutiny or exclusion. Participants were excluded if they marked multiple response options on any questionnaire question, ensuring clear and reliable responses. In some cases, follow-up contact through a phone call or additional brief questionnaire was conducted to verify critical details. The inclusion criteria were being aged 50 and above and retired, while the exclusion criteria included not meeting the age or retirement criteria and providing unclear or inconsistent responses. As a result of these verification methods, one respondent was excluded for not meeting either the age or retirement criteria, another for not meeting the age criterion, and seven for marking multiple response options, ensuring the final sample of 63 individuals (31 men and 32 women) was accurately composed of retired persons aged 50 and above.

2.4. Statistical Analysis

A descriptive analysis of quality of life, resilience, and life satisfaction was conducted. Subsequently, the assumption of normality was checked using the Kolmogorov–Smirnov test. Since two of the three variables did not follow a normal distribution, the presence of correlations was evaluated using Spearman’s correlation coefficient. Mean differences by sex were assessed using independent samples t-test assuming equal variances (following the verification of homoscedasticity assumption using Levene’s test) for the quality of life variable, and using the Mann–Whitney U test for resilience and life satisfaction variables. Finally, mean differences based on years of retirement were evaluated using a one-way ANOVA for the quality of life variable, and using the Kruskal–Wallis test for resilience and life satisfaction variables. All data analyses were conducted using the statistical software SPSS version 23 with a significance level of 0.05%.

3. Results

3.1. Descriptive Analysis

The statistics of central tendency (mean) and dispersion (standard deviation, range, minimum score, and maximum score) of the resilience, quality of life, and life satisfaction variables have been calculated. The obtained results are shown in

Table 1. Descriptive statistics.

Variable	Minimum	Maximum	Mean	SD
QOL	65	116	93.24	11.67
Resilience	9	26	19.48	2.77
LS	10	23	17.41	2.89

Note: QOL: quality of life; LS: life satisfaction; SD: standard deviation.

.

3.2. Normality Test

Since the total sample size was over 50 participants, the normality analysis was conducted using the Kolmogorov–Smirnov test. The results obtained are shown in

Table 2. Normality test.

Variable	SD	d.f	p-Value
QOL	0.073	63	0.2
Resilience	0.14	63	0.004
LS	0.12	63	0.025

Note: QOL: quality of life; LS: life satisfaction; SD: standard deviation; d.f.: degrees of freedom.

.

It is observed that only the variable “quality of life” is normally distributed (p > 0.05).

3.3. Inferential Analysis

Due to only the quality of life being normally distributed, the analysis of the first three hypotheses (correlational hypotheses) was conducted using the non-parametric Spearman correlation test.

A correlation of r = 0.079, p = 0.269 was obtained between resilience and quality of life, indicating that the correlation between these variables is not significant, rejecting hypothesis 1. Between quality of life and life satisfaction, a correlation of r = 0.45, p = 0.05 was obtained, indicating a significant and positive correlation between the two variables, confirming hypothesis 2. Between resilience and life satisfaction, the correlation is r = 0.25, p = 0.024, indicating a significant and positive correlation between the two variables, confirming hypothesis 3.

To test the fourth hypothesis, as the variable quality of life is normally distributed, Student’s t-test for two independent samples was used (see

Table 3. Differences in quality of life scores by sex.

Sex	M	SD	Statistic	d.f	p-Value
Men	90.35	10.68	1.97	61	0.053
Women	96.03	12.08

Note: SD: standard deviation; d.f.: degrees of freedom.

). Previously, the assumption of homoscedasticity was tested using Levene’s test, obtaining a p-value of 0.285, indicating that the assumption of equal variances can be assumed. On the other hand, since resilience and life satisfaction are not normally distributed, the Mann–Whitney U test was used (see

Table 4. Differences in means of resilience and life satisfaction by sex.

Variable	Sex	Sum of Rank	Statistic	p-Value
Resilience	Men	29.11	406.5	0.213
	Women	34.8
QOL	Men	32.4	483.5	0.863
	Women	31.61

Note: QOL: quality of life.

).

After conducting the data analysis, it is observed that there are no statistically significant differences between the means of the variables quality of life, resilience, and life satisfaction based on sex. These results do not allow us to confirm the fourth hypothesis.

To test the fifth hypothesis regarding quality of life, since the assumption of normality is met, a one-way ANOVA was conducted. As statistically significant differences were found in quality of life based on the time since retirement (see

Table 5. Differences in quality of life based on retirement time.

	SS	d.f.	MS	F	p-Value
Intergroups	1043.57	3	347.86	2.77	0.049
Error	7403.86	59	125.49
Total	8447.43	62

Note. SS: sum of squares; d.f.: degrees of freedom.; MS: mean squares; F: test statistic F-value.

), post hoc multiple comparisons were performed using Tukey’s test. Tukey’s test was chosen because it allows for all possible pairwise comparisons (see

Table 6. Pairwise comparisons.

Retirement Time i	Retirement Time j	MD (i-j)	SD Error	p-Value
Less than 6 months	6 months to 1 year	17.74	6.23	0.03
	1 to 2 years	7.07	5.33	0.55
	2 years or more	8.78	4.61	0.237
6 months to 1 year	1 to 2 years	−10.67	5.6	0.237
	2 years or more	−8.96	4.92	0.274
1 to 2 years	2 years or more	1.71	3.71	0.967

Note. MD: Mean difference; SD: standard deviation.

).

It is observed that there is a statistically significant difference in the mean quality of life between individuals who have been retired for less than six months and those who have been retired for six months to one year, with those who have been retired for less than six months showing higher quality of life.

Since the variables resilience and life satisfaction did not follow a normal distribution, the fifth hypothesis was tested using the Kruskal–Wallis test. The results are shown in

Table 7. Differences in resilience and life satisfaction based on retirement time.

Variable	Chi-Square	d.f.	p-Value
Resilience	1.046	3	0.79
LS	1.81	3	0.612

Note: LS: life satisfaction; SD: standard deviation; d.f.: degrees of freedom.

.

It is observed that there are no statistically significant differences in either resilience or life satisfaction based on the time since retirement. While statistically significant differences were found in quality of life based on the time since retirement, hypothesis five is only partially confirmed.

4. Discussion

The aim of the current study was to explore the relationship between resilience, quality of life, and life satisfaction in a group of retired individuals. Additionally, this study examined potential differences in these variables based on sociodemographic variables (sex and time since retirement). Following the analysis, the first hypothesis could not be confirmed as no statistically significant relationship was found between resilience and quality of life. This result differs from Varas and Saavedra [26], who found a positive and significant correlation between resilience and quality of life in older adults. Similarly, it differs from the findings of Tan et al. [27], who found that adults with higher levels of resilience had higher levels of quality of life. Regarding the second hypothesis, a significant and positive correlation was found between quality of life and life satisfaction, confirming this hypothesis. This result is consistent with Şahin et al. [45], who found that individuals over 65 with a higher quality of life exhibited greater life satisfaction. Concerning the third hypothesis, a significant and positive correlation was found between resilience and life satisfaction, confirming this hypothesis. This result aligns with Zheng et al. [28], who found that older adults with higher resilience had greater life satisfaction. Regarding the fourth hypothesis, no statistically significant differences were found in the means of quality of life, resilience, and life satisfaction based on sex. These results are consistent with Maldonado and Mendiola [40], who found no statistically significant differences in quality of life based on sex. Similarly, they are consistent with Tan et al. [27], who also found no statistically significant differences in the mean quality of life based on sex. Concerning quality of life, these results contradict what was found by other authors [38,39], who found that women had higher quality of life than men. Regarding resilience, the results oppose Vilte [24] and Zheng et al. [28], who found that women had higher levels of resilience than men. Additionally, concerning life satisfaction, the findings are in line with Zheng et al. [28], who found no statistically significant differences in life satisfaction based on sex. Lastly, for the fifth hypothesis, statistically significant differences were found in the means of quality of life based on time since retirement, specifically, individuals retired for less than six months had higher quality of life than those retired between six months and one year. However, no statistically significant differences were found in the means of resilience or life satisfaction based on time since retirement. The result regarding quality of life contradicts Betanzos-Díaz et al. [41], who found no statistically significant differences in quality of life based on time since retirement. Regarding resilience, the result aligns with Pimentel and Freitas [29], who also found no statistically significant differences in resilience based on time since retirement. Similarly, the finding regarding life satisfaction aligns with Pimentel and Freitas [29], who found no statistically significant differences in life satisfaction based on time since retirement. Additionally, it contradicts Cándido et al. [17], who found that newly retired individuals had lower levels of life satisfaction compared to those retired for more than three years. The observed discrepancy in this study’s results compared to previous research could be due to variations in the samples studied, the measurement instruments used, or even contextual and cultural factors. The lack of a significant relationship between resilience and quality of life in this study suggests that other factors, not measured in this analysis, might be mediating or moderating this relationship among retirees. On the other hand, the results highlight the importance of quality of life as a crucial determinant of life satisfaction in the retired population, emphasizing the need for interventions focused on improving quality of life to enhance overall satisfaction during this stage. Additionally, resilience appears to play an essential protective role, helping retirees better manage the challenges and changes associated with retirement, which contributes to greater life satisfaction. The observed discrepancies may be related to cultural, socioeconomic, or methodological factors, indicating the need for further research to better understand sex differences, which may be associated with factors related to gender construction. Overall, these results underscore the complexity of the retirement experience and emphasize the importance of considering the duration of retirement as a significant variable in future studies.

5. Limitations

Limitations of this study include the small sample size and the unequal distribution of participants across retirement time groups. Another limitation is that resilience and life satisfaction were not normally distributed, necessitating the use of non-parametric tests, which may limit the generalizability of the results to the population. Additionally, this study’s reliance on self-report measures may introduce biases such as acquiescence or social desirability, although the applied tests did not indicate such biases. Furthermore, the cross-sectional nature of this study does not allow for causal inferences, necessitating longitudinal studies for such assertions.

6. Future Research

Future research directions include conducting longitudinal studies to overcome the limitations of the current cross-sectional study, considering different stages of the retirement process. It is also suggested to balance the retirement time variable to ensure equal sample sizes in each group. Finally, future studies could investigate whether voluntariness or type of retirement is a variable that influences quality of life, resilience, or life satisfaction. In conclusion, retirement is a life stage that presents certain challenges as individuals experience a change in role, necessitating the study of various variables that may influence adaptation to this new stage. When individuals retire, they still have several years during which their socio-sanitary conditions allow for personal development and contribution to society economically, socially, and culturally. Quality of life, resilience, and life satisfaction were chosen as study variables due to their influence on retirees. Additionally, considering the evolution of population pyramids, it is necessary to address the needs of this life stage, which is increasingly represented, potentially reducing social and health costs associated with poor mental health during this stage. Furthermore, understanding the relationship between resilience, quality of life, and life satisfaction in retirement can aid in the development of intervention programs that promote these variables during this stage. Currently, there are various programs that promote active aging through cognitive stimulation, nutrition, sleep hygiene, emotional management, and physical exercise, but expanding their scope to promote psychological development, which involves enhancing quality of life, resilience, and life satisfaction addressed in this study, is necessary.

7. Conclusions

This study has illuminated the interconnectedness between quality of life, resilience, and life satisfaction in the context of retirement. The significant correlations found among these variables underscore the importance of fostering resilience to enhance life satisfaction among retirees. Additionally, the observed differences in quality of life based on time in retirement highlight the dynamic nature of this life stage and the need for tailored interventions. Understanding the influence of sociodemographic factors on these variables enables the development of targeted programs that can support retirees in maintaining high levels of quality of life and satisfaction. Future research and interventions should focus on these relationships to better support individuals in their transition to and during retirement.