The impact of stroke on quality of life

ORIGINAL ARTICLE

STADULNI, Andreia Rodrigues Parnoff ^[1], SOUSA, Aline Faria de ^[2], SLEIFER, Pricila ^[3], SCHOCHAT, Eliane ^[4]

STADULNI, Andreia Rodrigues Parnoff et al. The impact of stroke on quality of life. Revista Científica Multidisciplinar Núcleo do Conhecimento. Year 10, Ed. 06, Vol. 01, pp. 111-132. June 2025. ISSN: 2448-0959, Access link: https://www.nucleodoconhecimento.com.br/health/impact-of-stroke, DOI: 10.32749/nucleodoconhecimento.com.br/health/impact-of-stroke

ABSTRACT

Numerous limitations are caused by stroke, and these are directly related to quality of life and the impact such limitations have on individuals’ lives, in functional, social, and psychological aspects. Objective: To obtain a profile of the impact that stroke has on the quality of life of these individuals through the use of a specific questionnaire for hemiplegic patients in a virtual environment. Method: The Stroke Specific Quality of Life (SSQOL) questionnaire, designed for hemiplegic individuals, was applied in a closed social media group composed of people who had suffered a stroke. Results: The questionnaire was answered by 299 participants, of whom 223 (74.6%) were female and 76 (25.4%) male. The most prevalent age group was 40 to 59 years, n = 169 (56.5%), followed by 18 to 39 years, n = 96 (32.1%), and over 60 years, n = 34 (11.4%). The most prevalent type of stroke in this sample was ischemic stroke, n = 181 (60.5%), followed by hemorrhagic stroke, n = 85 (28.4%), brainstem stroke, n = 5 (1.7%), and unknown type, n = 7 (2.3%). In this study, the most affected specific domains according to the SSQOL were: Social Roles, Energy, Personality, Family Roles, Mood, and Work/Productivity. Conclusion: Stroke significantly impacts individuals’ quality of life, especially in the emotional aspect, highlighting the need for follow-up that includes not only physical rehabilitation but also emotional support.

Keywords: Stroke, Quality of life, Depression.

1. INTRODUCTION

Among the top 10 global causes of death (PAHO/WHO, 2018), stroke remains in second place and is one of the leading causes of death worldwide, accounting for a total of 15.2 million deaths in 2016. For those who survive this condition, physical and cognitive disabilities are common, leading to the need for rehabilitation. Of these survivors, approximately 70% do not return to work, and 30% require assistance to walk (Furini et al., 2008; Santos et al., 2011).

The impairments caused by stroke make it a major global public health problem, as a large proportion of survivors begin a new stage of life marked by the disabilities it generates. The assessment of Quality of Life (QoL) is crucial for understanding the impact of the disease on these individuals’ lives, facilitating the development of strategies to minimize these effects (Moreira et al., 2015).

When using the term Health-Related Quality of Life, it is important to understand that it refers to a set of physical, emotional, and social aspects that can be affected by changes in an individual’s health status. Thus, QoL measures should be incorporated alongside clinical procedures to gain a better understanding and more accurate metrics of the impact of a disease on the patient’s life, as well as the effectiveness of therapeutic programs used. These evaluations are particularly relevant for patients living with the sequelae of stroke, which often involve a wide range of disabilities and a broad set of symptoms (Hopman & Verner, 2003; Costa & Silva, 2022).

According to the WHO, quality of life is “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.” Many studies have interpreted this term broadly, including physical, psychological, and spiritual well-being, as well as social, economic, and political aspects (Hopman & Verner, 2003; Hsiung et al., 2005; Pedroso & Pilatti, 2009).

Having an instrument to assess quality of life is an important clinical indicator, as it allows for the verification and understanding of the implications of the disease from the individual’s perspective, while also contributing to scientific knowledge in health (Terroni et al., 2009; Vyas et al., 2024).

Some findings indicate deficits in the domains and in health-related quality of life after stroke (Fróes et al., 2011; Canuto et al., 2016).

Since these patients present with sequelae that limit daily activities and compromise physical, psychological, and social aspects, their quality of life is significantly altered, often leading to depression—identified as the main variable associated with worsening in these individuals (Kim & Kim, 2003; Villa et al., 2018).

The objective of our study is to analyze the impact of stroke on the quality of life of affected individuals through the application of the Stroke Specific Quality of Life (SSQOL) questionnaire for hemiplegic patients (Santos, 2000), and to describe the main findings obtained from the participants’ responses.

2. METHODOLOGY

This is a quantitative study with a descriptive and survey design. Data were collected through a structured electronic questionnaire, developed using the Google Forms platform, composed exclusively of closed-ended questions.

The sample consisted of volunteers recruited by convenience sampling, through the dissemination of the questionnaire in closed social media groups aimed at individuals affected by stroke. Participation was voluntary, anonymous, and conditional upon agreement with the Informed Consent Form (ICF), presented on the first page of the instrument. If the participant did not accept the terms, access to the subsequent stages was automatically terminated.

Data collection took place between January and May 2019, resulting in a total of 299 valid responses. The instrument used for data collection was an adapted version of the Stroke-Specific Quality of Life Scale (SSQOL), designed to measure the Quality of Life (QoL) of individuals with mild to moderate sequelae of stroke. The scale had been previously translated and culturally adapted into Portuguese and was considered valid and specific for identifying significant changes in quality of life related to symptoms experienced by patients. Due to its comprehensive structure, the SSQOL is particularly useful for capturing the specificities and most impacted domains in the post-stroke context.

The scale encompasses a broad range of aspects associated with the three dimensions of the International Classification of Functioning, Disability and Health (ICF) — body, activity, and participation — which gives it greater explanatory power compared to instruments that assess only one of these spheres (Duncan, Jorgensen, & Wade, 2000; Williams et al., 1999). It also stands out for including domains frequently neglected, such as language, cognition, and manual function.

The SSQOL questionnaire consists of the following domains: 1) energy, 2) family roles, 3) language, 4) mobility, 5) mood, 6) personality, 7) self-care, 8) social roles, 9) memory/concentration, 10) upper extremity function, 11) vision, and 12) work/productivity, totaling 49 items. Responses are based on experiences during the week prior to administration, using a 5-point scale. The total possible score ranges from 49 to 245 points, with higher scores indicating better quality of life. For analytical purposes, low quality of life was defined as a score below 60% of the maximum score (i.e., below 147 points) (Rangel, Belasco, & Diccini, 2013; Ebinger et al., 2005). Among the evaluated domains, “mood” was considered clinically especially relevant for identifying depressive symptoms (Williams et al., 1999).

The electronic administration of the SSQOL allowed for greater territorial reach, enabling participation from individuals across different regions of Brazil. The questionnaire was made available through the Google Forms platform, and access was shared in closed social media groups targeted at people affected by stroke.

The SSQOL has been widely recognized in the literature for its validity, reliability, and sensitivity to changes over time (Santos, 2000; Kim & Kim, 2020). In its original English version, it also demonstrates strong psychometric properties and is extensively used in clinical and epidemiological studies. The Brazilian version retains these qualities, being considered easy to administer, understand, and interpret (Galea & Trancy, 2007).

This study was approved by the Research Ethics Committee of the Federal University of Rio Grande do Sul (UFRGS) and the Ethics Committee of the Faculty of Medicine of the University of São Paulo (FMUSP), under protocol number 77900517.2.0000.5334.

3. RESULTS

Of the total respondents to the questionnaire, n = 299 (100%), 223 (74.6%) were female and 76 (25.4%) were male. Among the female participants, 22% were using contraceptives.

Table 1. Distribution of participants by gender

In Table 2, we can observe the data regarding the type of stroke. The distribution is according to the type of stroke (hemorrhagic, ischemic, brainstem, mixed [hemorrhagic and ischemic], or unknown at the time of responding to the questionnaire).

Table 2. Distribution of participants by type of stroke (n = 299)

Regarding harmful health habits, 16.1% of the sample were smokers, and 12% reported alcohol and drug use. Conversely, 35.5% of the sample did not have harmful health habits. The most prevalent age group was 40 to 59 years, n = 169 (56.5%), followed by 18 to 39 years, n = 96 (32.1%), and over 60 years, n = 34 (11.4%).

Table 3 presents the questionnaire domains and their findings. We observed the lowest scores in the domains of “social roles” (21.7%) and “energy” (29.1%).

Table 3 – Data on the Stroke-Specific Quality of Life Scale (SSQOL)

4. DISCUSSION

Of the total respondents to the questionnaire, as shown in Table 1, we observed a sample size of n = 299 (100%), with 223 (74.6%) female and 76 (25.4%) male participants. These results differ from some studies that report a majority of male participants. However, other studies found a predominance of females in their samples—53.3%, 52.09%, and 61.4% respectively—aligning with the present study (Reis et al., 2008; Souza-Pereira et al., 2010; Costa et al., 2015).

Some studies report that women affected by stroke exhibit poorer quality of life. According to these authors, this may be explained by women leading much more active lives, as many work both outside and inside the home, resulting in a greater impact on their quality of life (González et al., 2011; Nir, Gilad, & Bensashit, 2009).

Among the causes of stroke, since the majority of individuals in our study are female, 22% reported using contraceptives before the stroke, and among these, 7% stated that their stroke was due to contraceptive use. Oral contraceptives are a significant risk factor for ischemic stroke and, to a lesser extent, for hemorrhagic stroke. The risk for hemorrhagic stroke related to contraceptive use is lower compared to ischemic stroke. This method of contraception promotes blood stasis and hypercoagulability, increasing the risk of venous thrombosis and predisposing to clot formation by shortening coagulation time and thromboplastin activity in the venous wall, thereby elevating the risk of cardiovascular diseases that can lead to stroke. The risk is further increased when contraceptive use is combined with smoking, age over 35 years, and a history of hypertension. Conversely, risks decrease with the use of lower hormonal doses, according to the Brazilian Society of Cardiology (2024). In one study, 18.5% of women used this contraceptive method, corroborating our findings (Lee et al., 2022; Souza-Pereira et al., 2010).

Another noteworthy finding regarding pre-stroke habits is that 16.1% of the sample were smokers, and 12% reported alcohol and drug use. Conversely, 35.5% of the sample did not have harmful health habits.

Among the risk factors for stroke described in the literature, hypertension, smoking, and alcohol consumption are the most important and strongly correlated with stroke (Siegenthaler et al., 2010; Pires, Gagliardi, & Gorzoni, 2004; Souza-Pereira et al., 2010; Rodrigues et al., 2024). Some studies have identified smoking and alcohol use as prevalent habits among their participants prior to stroke (Souza-Pereira et al., 2010; Lima et al., 2015; Rodrigues et al., 2024), consistent with our sample.

Regarding age groups, the most prevalent was 40 to 59 years, n = 169 (56.5%), followed by 18 to 39 years, n = 96 (32.1%), and over 60 years, n = 34 (11.4%). We also observed a significant shift compared to other studies, indicating that stroke is increasingly affecting individuals in more productive phases of life, rather than only the elderly, as previously reported (Brazilian Association of Physical Medicine and Rehabilitation [ABMFR], 2023; Feigin et al., 2021; Lima, 2010; Lima et al., 2015; Ribeiro et al., 2012). These studies showed a higher incidence in people with a mean age lower than that cited in the literature, which may reflect population characteristics and the occurrence of stroke in younger individuals (Rangel, Belasco, & Diccini, 2013; Lotufo, Goulart, & Bensenor, 2007).

Studies report that the age of patients suffering a stroke has shifted, with a significant increase in cases under 65 years old, particularly in low- and middle-income countries (Feigin et al., 2021; Souza-Pereira et al., 2010; Owolabi et al., 2022). A population-based systematic review on stroke incidence and early post-stroke mortality shows a statistically significant and divergent trend in stroke incidence rates over the last four decades, with a 42% decrease in incidence in high-income countries and an increase of over 100% in low- and middle-income countries, along with a significant rise in younger age groups (Feigin et al., 2021). Another explanation for the changing age distribution may reflect the impact of unhealthy lifestyle habits in modern society, leading to earlier stroke events.

However, some researchers have observed that age is not a significant factor in quality of life changes (Souza et al., 2023; Silva, Oliveira, & Costa, 2023).

There is evidence that elderly individuals can psychologically adjust well to their health condition, accepting their limitations, resulting in an impact on quality of life that differs from that of younger individuals (Hackett & Pickles, 2014). For economically active individuals under 60 years of age, physical limitations affecting their ability to work have a greater impact (Santos, Silva, & Oliveira, 2023; Oliveira, Costa, & Silva, 2023).

Regarding the time since stroke occurrence, most participants had their stroke more than 5 years ago, n = 79 (26.4%), followed by 1 to 2 years, n = 69 (23.1%). For shorter durations, less than 1 year, there were n = 4 (1.3%) and n = 15 (5%). The majority of individuals experienced stroke over 5 years ago, consistent with some studies (Costa & Silva, 2022).

As shown in Table 2, the most prevalent type of stroke in this sample was ischemic stroke, n = 181 (60.5%), followed by hemorrhagic stroke, n = 85 (28.4%), brainstem stroke, n = 5 (1.7%), and unknown type, n = 7 (2.3%), confirming the predominance of ischemic stroke found in other studies (Lotufo et al., 2023; Rangel, Belasco, & Diccini, 2013; Lima et al., 2015; Ribeiro et al., 2012; Scalzo et al., 2010).

Some individuals experienced recurrent strokes, with significant numbers of ischemic and hemorrhagic stroke recurrence. The number of participants with recurrent stroke was 21 (7.0%), a finding already noted in the literature (Souza et al., 2023; Lima, 2010). It is observed that recurrence may increase in samples with older individuals (Poulsen & Hansen, 2023; Yang, Zhang, & Zhang, 2023). Recurrence was 20% among subjects aged over 60 years; however, in the study by Broman et al. (2023), with subjects under 50 years, recurrence was also 20%.

According to the WHO, transient ischemic attacks occur in 15% of patients who have experienced a stroke, and one-third of these patients have recurrent events (Souza et al., 2023; Lima et al., 2015; Monteiro et al., 2013). Individuals who have experienced stroke suffer impairments not only physical but also emotional, greatly contributing to clinical-functional decline. This underscores the importance of preventive educational policies to raise awareness of risk factors and prevent recurrent episodes.

In most cases, impairments resulting from hemorrhagic stroke are severe, considering similar factors such as lesion location and extent, sex, and age (Boman, Lindgren, & Sundström, 2024; Smith, 2015). However, since quality of life is not assessed solely by physical parameters, ischemic stroke patients sometimes exhibit worse quality of life than hemorrhagic stroke patients, highlighting the complexity of quality of life, which includes emotional, physical, and social aspects (Lima et al., 2008).

When asked if they knew the cause of their stroke, 62 (20.7%) did not know the reason for their stroke. Among those with a diagnosis, hypertension stood out with 66 (22.1%), followed by stress with 46 (15.4%). Mathrubhumi (2023) and Ribeiro et al. (2012) reported in their study that 47% of individuals did not know the cause of their stroke, and among those who did, 86% identified hypertension as the main cause—findings consistent with our research and other studies (Souza-Pereira et al., 2010; Lima et al., 2015; Scalzo et al., 2010).

It is important to note that not knowing the cause of the stroke negatively impacts acute stroke treatment and hinders appropriate patient guidance to prevent future episodes.

Among the risk factors associated with stroke, hypertension is one of the most important and strongly correlated factors, corroborating our study (Nature Reviews Cardiology, 2024; American Stroke Association, 2024; Gagliardi, 2015).

Regarding physical activity, the majority, 127 (42.5%), were considered sedentary, as they did not engage in any physical activity; 87 (29.1%) exercised sporadically, and 85 (28.4%) exercised regularly. According to the Ministry of Health (2013), sedentarism and obesity are cited as risk factors for stroke, confirming this finding in the studies by Cunha (2022), Silva et al. (2020), and Feigin et al. (2009). These authors describe that in developing countries, lack of physical activity is an important factor contributing to the disproportionately high incidence of stroke compared to developed countries (Silva et al., 2020; Feigin et al., 2009).

Quality of life (QoL), weighted by the dimensions or domains that compose the individual’s personal context, is generally affected as a consequence of the presence of pre-existing chronic diseases, acute conditions, and established comorbidities. As shown in Table 3, in the present study, the specific domains most impaired according to the SSQOL were: Social Roles, Energy, Personality, Family Roles, Mood, and Work/Productivity.

Findings of poorer quality of life in this questionnaire regarding work, energy, and social roles align with our results (Cordini, Oda, & Furlanetto, 2005). Moreira et al. (2015), in another study, found lower QoL scores in the domains of energy, social roles, family roles, and personality; meanwhile, Lima (2010) highlighted personality, social roles, and energy. Lima et al. (2008) reported the Work/Productivity domain as having the lowest score (121); in our study, this score was 136, which is quite similar. The highest score was in the Self-Care domain (246), compared to ours (211), also close. Regarding the lowest score, it was in the Energy domain (87), and the highest in Vision (257), similar to Moreira et al. (2015). These findings are reinforced by Saha et al. (2024), who identified social roles, family roles, and productivity as the most compromised domains in post-stroke patients.

Energy levels are related to fatigue and also show low scores. This suggests both direct and indirect physical and psychological influences of stroke on patients’ daily lives, who perceive the clinical diagnosis as a serious condition that affects their vitality (Scalzo et al., 2010).

It is evident that stroke affects various dimensions of quality of life, particularly altering social and family relationships, restricting these individuals. This may be one of the most challenging aspects to identify, often overlooked by rehabilitation professionals and close family members. This highlights the importance of having a comprehensive instrument to support therapeutic interventions.

The young population affected by stroke, although having a better survival prognosis compared to individuals over 50 years old, is subject to higher rates of morbidity and mortality, recurrent events, and physical and emotional sequelae. Representing the economically active population, there is a notable individual and socioeconomic impact due to physical limitations that affect their ability to work. Some studies show that about 50% of survivors do not return to their previous occupation (Hoekstra et al., 2017; Moura et al., 2023). Despite advances in therapies and diagnostics, this prevalence continues to contribute to a high rate of early retirements (Scalzo et al., 2010).

The mood domain, the creator of the SSQOL questionnaire emphasized, remains of utmost importance for detecting the effects of depressive symptoms, and this domain showed a low score in our study (Williams, 1999). Additionally, the abbreviated version of the questionnaire, the SS-QOL-17, validated by El Osta et al. (2022), includes mood-related items such as “I was irritable” and “I was discouraged about my future,” which demonstrated a significant correlation with overall quality of life in post-stroke patients. This reinforces the importance of evaluating emotional aspects, including mood, during the rehabilitation of these patients.

Depression, the most frequent psychiatric disorder following ischemic stroke, negatively affects functional survival outcomes, response to rehabilitation, and quality of life. Approximately one-third of stroke survivors suffer from post-stroke depression. Furthermore, depression adversely impacts patients’ ability to participate in rehabilitation therapies (Villa, Ferrari, & Moretti, 2018).

A meta-analysis of 43 studies reported a cumulative incidence of depression ranging from 39% to 52% within 5 years after stroke, and a pooled prevalence of 29% at any time within 10 years. Interestingly, a significant fraction of patients who developed early depression following the acute event recovered in subsequent assessments (Lepage et al., 2014).

Another meta-analysis conducted in 2014, including 61 studies, reported that depression occurred in 31% of patients at any time up to five years post-stroke (Hackett & Pickles, 2014), reinforcing findings from an earlier 10-year review, which found a frequency of 33% (Hackett & Anderson, 2005). These findings highlight the need for evidence-based screening, prevention, and treatment strategies, as post-stroke depression remains relatively underdiagnosed, undertreated, and under-researched. Recently, a comprehensive meta-analysis of 108 studies on mood disorders identified 147 cases between 2 days and 7 years post-stroke and demonstrated a prevalence of 33.5% for any depressive disorder (Mitchell et al., 2017; Shaikh et al., 2024).

Post-stroke depression is associated with severe disability, anxiety, lower quality of life, speech and language dysfunction, anhedonia, feelings of despair, functional and cognitive impairment, greater dependence on activities of daily living (ADLs), and poor medication adherence (Lepage et al., 2014; Almeida et al., 2014; Shaikh et al., 2024).

The most frequently cited predictors in the extensive (albeit somewhat divergent) literature are: female sex, personal history of depression prior to stroke, physical disability, anxiety, aphasia, stroke severity, cognitive and physical impairment, level of independence, dysphagia, and psychosocial factors such as pre-stroke life events and lack of family and social support (Hackett & Anderson, 2005; Almeida et al., 2014; Shi et al., 2017).

We can conclude that the results obtained in this study corroborate findings in the literature by demonstrating a reduction in quality of life (QoL) among stroke survivors, especially in domains related to social, emotional, and productive functioning. The sample profile, composed predominantly of individuals in economically active age groups, underscores the functional and psychosocial impact of stroke on this population. Furthermore, the low score in the “mood” domain indicates the presence of depressive symptoms, which are often underdiagnosed, suggesting the need for more comprehensive psychosocial assessments during patient follow-up. Regarding the subjects in our sample, we observed a majority of female participants and, concerning age, it is noteworthy that stroke is affecting individuals in more productive phases of life, not only the elderly as previous studies indicated.

5. FINAL CONSIDERATIONS

In the present study, we observed that by using the stroke-specific questionnaire for hemiplegic patients, combined with online data collection, we were able to profile the impact of stroke on individuals’ quality of life. Regarding the emotional aspect, the quality of life scores highlight the need for follow-up care that includes not only physical rehabilitation but also emotional support.

There is a need for more clinical studies applying this instrument to post-stroke individuals in Brazil, to allow for broader comparisons and to ensure the questionnaire’s psychometric properties, applicability, and the best mode of administration (self-administered or interview; online or in-person).

We did not focus on identifying the side of hemiplegia/hemiparesis, as some studies show that the predominance of the sequela has little impact on quality of life (Hopman & Verner, 2003; Vestergaard Rogeberg & Isachsen, 2005; Santos, 2021). However, future researchers may find this data relevant for quality of life outcomes.

Cognitive deficits occur in up to 35% of hemiplegic post-stroke individuals. These cognitive impairments, correlated with physical deficits, are associated with poorer functional prognosis, resulting in greater dependency in daily life. Therefore, cognitive assessment combined with other physical, functional, and quality of life evaluations is crucial to enhance rehabilitation programs. Evaluation should never be limited to a single characteristic when applied within a rehabilitation program.

ACKNOWLEDGMENTS

This work was carried out with the support of the Coordination for the Improvement of Higher Education Personnel – Brazil (CAPES) – Financing Code 001.

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NOTE

The authors used the Artificial Intelligence Releasing GPT-4.1 to check spelling in some paragraphs. However, all searches for content, quality assessment of articles, and verification were conducted independently by the authors.

^[1] PhD in Rehabilitation Sciences from USP; Master’s degree in Speech-Language Pathology from PUC-SP; Specialization in Audiology (Lato Sensu) from IPA Methodist University of Porto Alegre; Bachelor’s degree in Speech-Language Pathology from ULBRA Canoas, RS. ORCID: https://orcid.org/0000-0002-1879-5126.

^[2] PhD in Sciences from the Faculty of Medicine at USP. Master’s degree in Rehabilitation Sciences from USP. Holds a bachelor’s degree in Speech-Language Pathology from USP and professional training in cochlear implant at HCFMUSP. Specialization in Municipal Public Management from UNIFESP and MBA in Data Science and Analytics from USP/ESALQ. ORCID: https://orcid.org/0000-0002-7186-2471.

^[3] Co-supervisor. PhD in Medical Sciences: Pediatrics from the Federal University of Rio Grande do Sul (2008); Master’s degree in Medical Sciences: Pediatrics from the Federal University of Rio Grande do Sul (2006); Specialization in Audiology from CRF (2007); Specialization in Speech-Language Pathology from UFSM (1996); Bachelor’s degree in Speech-Language Pathology from the Federal University of Santa Maria (1994). ORCID: https://orcid.org/0000-0001-6694-407X.

^[4] Postdoctoral Fellowship at Dartmouth Medical School (USA); PhD in Linguistics from the University of São Paulo (1994); Master’s degree in Linguistics from the University of São Paulo (1991); Bachelor’s degree in Speech-Language Pathology from the Pontifical Catholic University of São Paulo (1979). ORCID: https://orcid.org/0000-0002-1775-7603.

Received: March 31, 2025.

Peer-reviewed and approved: May 30, 2025.

Edited material approved by the authors: June 11, 2025.