According to a global survey, about 33 percent of adults experienced feelings of loneliness worldwide. Brazil had the highest percentage of people experiencing this, with 50 percent of respondents declaring that they felt lonely either often, always, or sometimes. Turkey, India, and Saudi Arabia followed, with 43 percent to 46 percent of respondents having experienced loneliness at least sometimes. On the contrary, the Netherlands, Japan, Germany, and Russia registered the largest share of interviewees which did not feel lonely.

Coping with loneliness during the pandemic The COVID-19 pandemic has suddenly cut off people from all over the world from their social life, and the lack of companionship has been a difficult situation for many to cope with. In the United States, people who experienced lack of company were, unsurprisingly, individuals living alone, and unemployed, disabled, or unemployed people. In relation to mental health, Americans who reported more symptoms of depression were by far more likely to feel lonely.

Impact of mental health According to a survey conducted in 2021 among G7 countries, about seven in 10 people experienced a worsening of their psychological health during the pandemic. A study on clinician-reported changes in selected health behaviors in the United States showed that during the pandemic patients have suffered more from feelings of loneliness, depression or anxiety, and burnout. Also nutrition and other habits have been impacted. The study reported an increase in alcohol consumption, smoking cigarettes, poor nutrition, and use of other substances.

A survey from 2021 of over 23,000 people from 28 different countries found that 41 percent stated they felt more lonely in the last six months. Turkey and Brazil were the countries with the highest share of people who said they felt more lonely in the last six months prior to the survey. This statistic shows the percentage of adults worldwide who stated over the last six months they became more or less lonely as of 2021, by country.

In the past months, many countries have adopted varying degrees of lockdown restrictions to control the spread of the COVID-19 virus. According to the existing literature, some consequences of lockdown restrictions on people’s lives are beginning to emerge. To inform policies for the current and/or future pandemics, particularly those involving lockdown restrictions, this study adopted a data-driven Machine Learning approach to uncover the short-term effects of lockdown on people’s physical and mental health. An online questionnaire launched on 17 April 2020 was completed by 2,276 people from 66 countries. Focusing on the UK sample (N=382), 10 aggregated variables representing participant’s living environment, physical and mental health were used to train a RandomForest model to predict the week of survey completion. Using an index of importance to identify the best predictor among the 10 variables, self perceived loneliness was identified as the most influential variable. Subsequent statistical analysis showed a significant U-shaped curve for loneliness levels, with a decrease during the 4th and 5th lockdown weeks. The same pattern was replicated in the Greek sample (N = 129). This suggests that for the very first period of time, the adopted lockdown measures affected people’s evaluation of their social support leading to a decreased sense of loneliness.

Estimates of loneliness and personal well-being during the coronavirus (COVID-19) pandemic by country, region, county and local and unitary authorities. This dataset also includes outputs from regression models which consider the personal characteristics significantly associated with levels of loneliness and well-being both during and prior to the pandemic affecting the UK.

ObjectivesLoneliness is a major public health concern. Duration of loneliness is associated with severity of health outcomes, and further research is needed to direct interventions and social policy. This study aimed to identify predictors of the onset vs. the maintenance of loneliness in older adults before and during the pandemic using longitudinal data from the Survey of Health, Age, and Retirement in Europe (SHARE).MethodsGroupings of persistent, situational, and no loneliness were based on self-reports from an ordinary pre-pandemic SHARE wave and a peri-pandemic telephone interview. Predictors were identified and compared in three hierarchical binary regression analyses, with independent variables added in blocks of geographic region, demographics, pre-pandemic social network, pre-pandemic health, pandemic-related individual, and country level variables.ResultsSelf-reported loneliness levels for the persistent, situational, and no loneliness groups were stable and distinct through 7 years preceding the pre-pandemic baseline measure. Shared predictors were chronic diseases, female sex, depression, and no cohabitant partner. Persistent loneliness was uniquely predicted by low network satisfaction (OR: 2.04), functional limitations (OR: 1.40), and a longer country-level isolation period for older adults (OR: 1.24).ConclusionInterventions may target persons with depression, functional limitations, chronic health issues, and no cohabitant partner. The added burden of the length of isolation on those who are already lonely should be taken into account when employing social policies that target older adults. Further research should distinguish between situational and persistent loneliness, and seek to identify predictors of chronic loneliness onset.

A 2022 survey conducted in 16 countries found that feelings of loneliness tend to decrease with age. That year, nearly 60 percent of young adults between 18 and 24 years reported negative effects on wellbeing from feelings of loneliness, while around 22 percent of respondents aged 65 and older reported the same. This statistic shows the percentage of people worldwide who reported negative effects on wellbeing from feelings of loneliness in 2022, by age group.

This is the README file for the scripts of the preprint "Self-Perceived Loneliness and Depression During the COVID-19 Pandemic: a Two-Wave Replication Study" by Carollo et al. (2022)

Access the pre-print here: https://ucl.scienceopen.com/document/read?vid=0769d88b-e572-48eb-9a71-23ea1d32cecf

Abstract: Background: The global COVID-19 pandemic has forced countries to impose strict lockdown restrictions and mandatory stay-at-home orders with varying impacts on individual’s health. Combining a data-driven machine learning paradigm and a statistical approach, our previous paper documented a U-shaped pattern in levels of self-perceived loneliness in both the UK and Greek populations during the first lockdown (17 April to 17 July 2020). The current paper aimed to test the robustness of these results by focusing on data from the first and second lockdown waves in the UK. Methods: We tested a) the impact of the chosen model on the identification of the most time-sensitive variable in the period spent in lockdown. Two new machine learning models - namely, support vector regressor (SVR) and multiple linear regressor (MLR) were adopted to identify the most time-sensitive variable in the UK dataset from wave 1 (n = 435). In the second part of the study, we tested b) whether the pattern of self-perceived loneliness found in the first UK national lockdown was generalizable to the second wave of UK lockdown (17 October 2020 to 31 January 2021). To do so, data from wave 2 of the UK lockdown (n = 263) was used to conduct a graphical and statistical inspection of the week-by-week distribution of self-perceived loneliness scores. Results: In both SVR and MLR models, depressive symptoms resulted to be the most time-sensitive variable during the lockdown period. Statistical analysis of depressive symptoms by week of lockdown resulted in a U-shaped pattern between week 3 to 7 of wave 1 of the UK national lockdown. Furthermore, despite the sample size by week in wave 2 was too small for having a meaningful statistical insight, a qualitative and descriptive approach was adopted and a graphical U-shaped distribution between week 3 and 9 of lockdown was observed. Conclusions: Consistent with past studies, study findings suggest that self-perceived loneliness and depressive symptoms may be two of the most relevant symptoms to address when imposing lockdown restrictions.

In particular, the folder includes the scripts for the pre-processing, training, and post-processing phases of the research.

==== PRE-PROCESSING WAVE 1 DATASET ==== - "01_preprocessingWave1.py": this file include the pre-processing of the variables of interest for wave 1 data; - "02_participantsexcludedWave1.py": this file include the script adopted to implement the exclusion criteria of the study for wave 1 data; - "03_countryselectionWave1.py": this file include the script to select the UK dataset for wave 1.

==== PRE-PROCESSING WAVE 2 DATASET ==== - "04_preprocessingWave1.py": this file include the pre-processing of the variables of interest for wave 2 data; - "05_participantsexcludedWave1.py": this file include the script adopted to implement the exclusion criteria of the study for wave 2 data; - "06_countryselectionWave1.py": this file include the script to select the UK dataset for wave 2.

==== TRAINING ==== - "07_MLR.py": this file includes the script to run the multiple regression model; - "08_SVM.py": this file includes the script to run the support vector regression model.

==== POST-PROCESSING: STATISTICAL ANALYSIS ==== - "09_KruskalWallisTests.py": this file includes the script to run the multipair and the pairwise Kruskal-Wallis tests.

As a proxy measure of socioeconomic status, food insecurity is understudied in mental health-related research. This study aimed to explore the association between food insecurity and loneliness in adolescents. Using cross-sectional data from the Global Student Health Survey (GSHS), 164,993 adolescent participants were included in this study. Food insecurity, loneliness, and other covariates were assessed by self-reported questionnaire. Multivariable logistics regression considering complex survey was used to explore the association between food insecurity and loneliness. The prevalence of loneliness was 10.8% in adolescents. With higher levels of food insecurity, the prevalence of loneliness in general increased, but “most of the time” was the most frequently reported item in terms of food insecurity. Adolescents who reported severe food insecurity had significantly greater odds for loneliness: (1) being most of the time [odd ratio (OR) = 2.54, 95% CI = 2.13–3.02]; (2) always hungry (OR = 1.97, 95% CI = 1.55–2.51). Of all the 53 countries, adolescents from 39 countries reported significantly higher prevalence of loneliness when exposed to food insecurity. The pooled OR was 1.74 (1.60–1.89) with a negligible heterogeneity (higher I-squared was 34.2%). Adolescents with food insecurity were more likely to be exposed to be lonely. Eliminating socioeconomic disparities in adolescents might be a good approach to promote mental health in adolescents. Future studies are encouraged to utilize longitudinal studies to confirm or negate our study findings.

Background The 2019 coronavirus (COVID-19) pandemic has impacted people’s mental wellbeing. Studies to date have examined the prevalence of mental health symptoms (anxiety, depression, loneliness), yet fewer longitudinal studies have compared across background factors and other psychological variables to identify vulnerable sub-groups. This study tests to what extent higher levels of psychotic-like experiences – indexed by schizotypal traits and paranoia – are associated with various mental health variables 6- and 12-months since April 2020. Methods Over 2,300 adult volunteers (18-89 years, female=74.9%) with access to the study link online were recruited from the UK, USA, Greece, and Italy. Self-reported levels of schizotypy, paranoia, anxiety, depression, aggression, loneliness, and stress from three timepoints (17 April to 13 July 2020, N1 =1,599; 17 October to 31 January 2021, N2 =774; and 17 April to 31 July 2021, N3 =586) were mapped using network analysis and compared across time and background variables (sex, age, income, country). Results Schizotypal traits and paranoia were positively associated with poorer mental health through loneliness, with no effect of age, sex, income levels, countries, and timepoints. Loneliness was the most influential variable across all networks, despite overall reductions in levels of loneliness, schizotypy, paranoia, and aggression during the easing of lockdown. Individuals with higher levels of schizotypal traits/paranoia reported poorer mental health outcomes than individuals in the low-trait groups.Conclusion Schizotypal traits and paranoia are associated with poor mental health outcomes through self-perceived loneliness, suggesting that increasing social/community cohesion may improve individuals’ mental wellbeing in the long run. Keywords: Network Analysis; Schizotypy; Anxiety; Depression; Stress; Loneliness; Sleep; COVID-19; Longitudinal; Mental Health.

This survey aims to see if people are feeling more lonely now compared to before the COVID-19 pandemic. The survey also asks if people have been following COVID-19 restrictions in their area and whether or not they would support a second national lockdown in their country if one was deemed necessary.

This statistic displays the share of people feeling often or constantly lonely in Finland in 2018, by level of education. According to the results of the survey, approximately eight percent of all respondents felt often or constantly lonely in the country. With roughly ten percent, the share of people with basic education feeling lonely was approximately two percent higher than the share of people with higher education.

Loneliness-Monitoring Robot Market Outlook

According to our latest research, the global loneliness-monitoring robot market size reached USD 1.42 billion in 2024, reflecting the increasing adoption of advanced robotics in addressing social isolation and mental health concerns across various demographics. The market is expected to grow at a robust CAGR of 18.7% from 2025 to 2033, culminating in a projected value of USD 7.16 billion by 2033. This significant growth is primarily driven by rising awareness of mental health, the aging global population, and rapid advancements in artificial intelligence and sensor technologies, making loneliness-monitoring robots more accessible and effective for end-users worldwide.

One of the primary growth drivers for the loneliness-monitoring robot market is the escalating prevalence of loneliness and social isolation, particularly among the elderly and individuals with chronic health conditions. Societal shifts, such as urbanization, smaller family units, and increased mobility, have contributed to a rise in individuals living alone, thereby heightening the risk of loneliness-related health issues. Loneliness-monitoring robots are increasingly being recognized as a viable solution to bridge the gap between human interaction and independent living, offering real-time companionship, emotional support, and health monitoring. The integration of advanced AI, natural language processing, and emotion recognition technologies has significantly enhanced the ability of these robots to understand and respond to users' emotional states, further fueling their adoption in both residential and institutional settings.

Another critical factor propelling market growth is the increasing investment in healthcare infrastructure and the ongoing digital transformation within the sector. Governments and private organizations are actively seeking innovative solutions to address the mental and emotional well-being of vulnerable populations, particularly in the wake of the COVID-19 pandemic, which highlighted the detrimental effects of prolonged isolation. Loneliness-monitoring robots are now being deployed in hospitals, clinics, and assisted living facilities to supplement human caregivers, reduce the burden on healthcare staff, and provide continuous engagement for patients. The scalability and adaptability of these robots, combined with their ability to collect and analyze behavioral data, make them an attractive option for healthcare providers aiming to deliver personalized and proactive care.

Technological advancements have also played a pivotal role in accelerating the adoption of loneliness-monitoring robots. The convergence of AI, IoT, and sensor technologies has enabled the development of more intuitive, interactive, and cost-effective robots capable of seamlessly integrating into users' daily lives. Modern loneliness-monitoring robots are equipped with features such as voice recognition, facial expression analysis, and remote connectivity, allowing family members and healthcare professionals to monitor users' well-being from a distance. These innovations have not only improved user engagement and satisfaction but have also expanded the potential applications of these robots beyond elderly care to include individuals with disabilities, children, and those recovering from illnesses or surgeries.

From a regional perspective, North America currently dominates the loneliness-monitoring robot market, accounting for over 38% of the global revenue in 2024, followed closely by Europe and Asia Pacific. The high adoption rate in North America can be attributed to the region's advanced healthcare infrastructure, high disposable income, and strong focus on mental health initiatives. Europe is also witnessing substantial growth, driven by government support for elderly care and increasing investments in robotics research. Meanwhile, the Asia Pacific region is emerging as a lucrative market, fueled by its rapidly aging population, growing healthcare expenditures, and rising awareness of the benefits of loneliness-monitoring technologies. Latin America and the Middle East & Africa are expected to experience moderate growth, primarily due to improving healthcare access and gradual technological adoption.

Product Type Analysis

The product landscape of the loneliness-monitoring robot market is diverse, with key segments including companion robots, socially assistive robots, telepresence robots, and others. Companio

Loneliness, as defined by Peplau & Perlman (1982), is the unpleasant feeling that occurs when people perceive their network of social relationships to be quantitatively or qualitatively deficient (Hawkley & Cacioppo, 2010; Heinrich & Gullone, 2006). Stemming from the social needs perspective, several types of loneliness have been described. Emotional loneliness emerges from a lack of close intimate relationships, and social loneliness arises from a lack of desired social networks (Heinrich & Gullone, 2006; Maes et al., 2017, 2022; Russell et al., 1984). There are indications that loneliness occurs more often in adolescents than in other age groups (Mahon et al., 2006; Qualter et al., 2015), possibly due to the various changes in social expectations, roles, and relationships that occur during this life stage (Heinrich & Gullone, 2006; Maes et al., 2017). Adolescents who experience loneliness are more likely to exhibit symptoms of depression and low levels of life satisfaction (Mahon et al., 2006; Moore & Schultz, 1983). Thus, it is important to recognize adolescents’ feelings of loneliness early to prevent poorer mental health. Adolescents may experience loneliness in specific relationships, either in an intimate relationship (e.g., attachment with parent, friendship) or in social relationships (e.g., peer group integration, family integration) when social provisions are unmet. As highlighted by recent research, differentiating between these types of emotional and social loneliness is important for understanding the complexity of loneliness in adolescence. This multidimensional approach acknowledges that loneliness might take multiple forms, offering a useful perspective on the various experiences of adolescents' loneliness across various relational contexts (Heinrich & Gullone, 2006; Maes et al., 2017, 2022; Ribeiro et al., 2019; Russell et al., 1984).

Loneliness among adolescents has been commonly reported in high-income countries, but less is known about loneliness in the South East Asian Nations (ASEAN) (Peltzer & Pengpid, 2017). Peltzer and Pengpid (2017) reported that the prevalence of loneliness (mostly or always feeling lonely) in adolescents in Indonesia (aged 13 - 15 years, mean age = 14.1 years, SD = 0.8) is the second highest among other ASEAN countries (7.4% among males and 11.6% among females). In this study, we will focus on the relation of emotional and social loneliness with well-being, with a focus on depressive symptoms and life satisfaction, during early adolescence in the Indonesian population, while taking positive and negative parenting and peer social support into account.

Positive parenting, characterized by warmth and support, is a significant factor for adolescent healthy development (DeVore & Ginsburg, 2005; Rotenberg & Hymel, 1999; Schofield et al., 2012). Previous studies showed that adolescents report higher levels of life satisfaction and happiness when their parents are perceived as warm, sensitive, and supportive (Loton & Waters, 2017; Stafford et al., 2016; Sumargi & Giovanni, 2021). Strength-Based Parenting (SBP), focusing on cultivating positive qualities in children, has emerged as a promising approach to lead to positive outcomes for adolescents’ well-being (Jach et al., 2017; Sağkal & Özdemir, 2019; L. E. Waters, 2017). We hypothesize that SBP may mitigate the negative effects of loneliness on adolescent well-being by fostering secure attachments and promoting emotional resilience. This prediction is built on the premise that parenting based on acceptance would facilitate adolescent adjustment, promote secure attachment, and protect them from depression. Parents' acceptance would positively connect to developing a secure attachment that constitutes a solid base for adolescents’ social relationships (Cassidy, 2000; Chipuer, 2001; De Minzi, 2006). Conversely, unsupportive parenting, captured by rejection, chaos, and coercion features, can undermine adolescents' sense of relatedness, self-confidence and prevent children from developing psychological autonomy (Skinner et al., 2005). These problems will hinder their ability to form meaningful connections and increase their vulnerability to loneliness (Lanjekar et al., 2022; Zhu & Shek, 2021). Unsupportive parenting can (unintentionally) communicate a message of excessive flaws to adolescents, conducive to the development of a negative self-cognitive schema, causing negative self-experiences, low self-esteem, and self-abandonment, which significantly increases the risk of low levels of life satisfaction and higher levels of depression among adolescents (Kang et al., 2024; Li et al., 2023; Trong Dam et al., 2023).

Next to the role of parents, peers also play an important role in adolescents’ well-being. Adolescents undergo changes in social dynamics, particularly they shift from relying mostly on parents to leaning more on peers for support (Helsen et al., 2000; Meeus & Dekovic, 1995; Qualter et al., 2015; Woodhouse et al., 2012). According to the social needs perspective, peer relationships may fulfill adolescents’ social needs for attachment and integration (Heinrich & Gullone, 2006; Maes et al., 2017; Mahon et al., 1994). Positive peer interactions provide support and validation, and buffer against loneliness (Argyle, 2013). Social support from peers in adolescence is fundamental to many developmental processes, such as coping with stress and adversity, mental and physical health, and higher life satisfaction (Bi et al., 2021; Singstad et al., 2021). Perceived social support refers to a person's emotional experience of being supported, understood, and satisfied with being respected when interacting with others (Lakey & Cassady, 1990). Previous studies have shown that peer social support moderates the relationship between stressful life events and depression during times of high stress (Cheng, 1997; Izaguirre et al., 2021; Rueger et al., 2016). In stressful situations, individuals tend to seek advice, favors, protection, and emotional support from their immediate environment, including family and friends. When adolescents feel capable of overcoming adverse circumstances, this sense of capability, in turn, leads to greater life satisfaction (Izaguirre et al., 2021; Malecki & Demaray, 2003; Rueger et al., 2016). Thus, perceived social support is important in protecting adolescent mental health in stressful situations. In this study, we predict that adolescents with higher perceived peer social support had a weaker impact of loneliness on well-being. This hypothesis is based on the premise that social support can mitigate the negative effects of loneliness by enhancing adolescents’ positive self-assessment and self-concept, leading to improved self-esteem, resilience, self-efficacy, and emotional regulation, thereby protecting them from adverse well-being outcomes (Huang et al., 2022; Kang et al., 2024; Rueger et al., 2016).

In sum, this study aims to investigate the role of parenting (strength-based parenting and unsupportive parenting) and perceived peer social support as moderator variables in the relations between emotional and social loneliness and early adolescents’ well-being, including depressive symptoms and life satisfaction. We will also examine the differential roles of paternal versus maternal parenting. However, we had no a priori hypothesis about possible differences for fathers versus mothers. Therefore, we will conduct an exploratory study to examine any differences. We expect that the results of this study can fill existing gaps in studies on father involvement in parenting.

Using a rich individual level dataset from six countries, we examine the association between job loss and mental wellbeing loss during the first phase of the COVID-19 pandemic. We consider four indicators of mental health status based on their severity, viz. anxiety, insomnia, boredom, and loneliness. We draw our conclusions based on two groups of countries that differ by the timing of their peak infections count. Using a logit model and controlling for endogeneity, we find that the people who lost their jobs due to the pandemic are more likely to suffer from mental wellbeing loss, especially insomnia and loneliness. Additionally, people with financial liabilities, such as housing mortgages, are among the mentally vulnerable groups to anxiety. Women, urban residences, youth, low-income groups, and tobacco users are more prone to mental wellbeing loss. The findings from this research have significant policy implications on infectious disease control measures and mental health status due to lockdowns and social distancing.

A 2023 survey of weekly gamers worldwide found that 87 percent of respondents in Brazil played video games to help them feel less stressed, the highest rate out of all observed markets. About 78 percent of respondents in the United States and the United Kingdom stated the same. In contrast, only 53 percent of gamers in South Korea claimed that video games helped them relieve feelings of stress.

Robotic Pets Market Outlook

The global robotic pets market size is projected to grow from USD 1.42 billion in 2023 to an estimated USD 3.85 billion by 2032, expanding at a CAGR of 11.5% during the forecast period. This growth is driven by technological advancements, the rising need for companionship, and increasing applications in healthcare and education sectors.

Several factors contribute to the growth of the robotic pets market. Key among these is the increasing aging population worldwide. Elderly individuals, particularly those living alone, often face chronic loneliness and emotional distress. Robotic pets, designed to offer companionship and emotional support, have shown significant promise in addressing these issues. Studies suggest that interacting with robotic pets can alleviate feelings of loneliness, reduce stress, and even improve overall mental health. These benefits have led to a growing adoption of robotic pets in elderly care facilities and among individual senior citizens.

Another significant driver is the rapid technological advancements in robotics and artificial intelligence (AI). Modern robotic pets are equipped with sophisticated features such as voice recognition, emotion detection, and interactive capabilities, making them highly responsive and lifelike. These advancements enhance the user experience, making robotic pets more appealing to a broader audience. Additionally, the decreasing cost of manufacturing and technological components has made these advanced robotic pets more affordable, further boosting market growth.

The increasing prevalence of mental health issues among various age groups is also fueling the demand for robotic pets. In educational settings, robotic pets are being used as therapeutic tools to help children with autism and other developmental disorders. These robots can engage children in interactive activities, aiding in their cognitive and social development. In healthcare, robotic pets are employed in therapy sessions for patients dealing with depression, anxiety, and post-traumatic stress disorder (PTSD), providing non-judgmental companionship and helping to improve patient outcomes.

The regional outlook of the robotic pets market shows significant growth potential in North America, driven by high disposable incomes, technological innovation, and a growing elderly population. Europe follows closely, with increased awareness and adoption in healthcare and educational sectors. The Asia Pacific region is expected to witness the highest growth rate, fueled by a combination of rapid technological adoption, rising disposable incomes, and increasing awareness of mental health issues. Latin America and the Middle East & Africa are also expected to show steady growth, although at a slower pace compared to other regions.

Product Type Analysis

Companion robots form a significant segment within the robotic pets market. These robots are designed to provide companionship and emotional support to users, particularly the elderly and individuals experiencing loneliness. Modern companion robots are equipped with advanced AI capabilities, allowing them to interact in a lifelike manner, respond to voice commands, and even recognize and remember user preferences. The growing aging population and the increasing incidence of mental health issues are major factors driving the demand for companion robots. Moreover, manufacturers are continuously innovating to enhance the realism and interactivity of these robots, making them more appealing to consumers.

Therapy robots are another crucial segment, primarily used in healthcare settings. These robots have proven effective in assisting with the treatment of various mental health conditions, including depression, anxiety, and PTSD. Therapy robots are designed to engage with patients in a therapeutic context, offering comfort and emotional support. They are also used in pediatric care to help children cope with hospital stays and medical procedures. The rising awareness about mental health and the increasing acceptance of robotic therapy in clinical settings are expected to drive the growth of this segment in the coming years.

Educational robots are gaining traction in schools and educational institutions. These robots are designed to facilitate learning and development in children, particularly those with special needs. Educational robots can engage children in interactive learning activities, helping to improve their cognitive and social skills. They are also used to teach programming and robotics, providing hands-on experience in STEM (Science, Tec

Local and global estimates of explained variance at the two levels of the multilevel model.

Pet Therapy Robot Market Outlook

The global pet therapy robot market size was valued at approximately USD 1.2 billion in 2023 and is projected to grow to USD 4.8 billion by 2032, exhibiting a robust CAGR of 16.5% over the forecast period. This remarkable growth is driven by an increasing demand for therapeutic interventions that integrate technology with emotional support, particularly in healthcare and elderly care settings. The rising prevalence of mental health issues, coupled with the growing elderly population, has significantly fueled the adoption of pet therapy robots as a viable solution for delivering emotional comfort and companionship.

One of the primary growth factors of the pet therapy robot market is the rising awareness and acceptance of mental health as a crucial component of overall well-being. Modern societies are recognizing the importance of addressing mental health issues, which has led to increased investments in mental health technologies. Pet therapy robots offer a unique blend of emotional support and therapeutic benefits, making them an attractive option for individuals suffering from anxiety, depression, and other mental health conditions. Healthcare professionals are increasingly recommending these robots as a complementary treatment to traditional therapies, further driving market growth.

Another significant growth factor is the expanding elderly population worldwide. As the global population ages, the need for innovative solutions to support elderly care becomes more pressing. Pet therapy robots provide elderly individuals with companionship, reducing feelings of loneliness and isolation. These robots also assist in cognitive stimulation and physical activity, thereby enhancing the overall quality of life for the elderly. Governments and healthcare organizations are increasingly adopting these robots in nursing homes and assisted living facilities, contributing to the market's expansion.

The advancements in artificial intelligence and robotics technology are also playing a pivotal role in the market's growth. The integration of AI enables pet therapy robots to exhibit lifelike behaviors, understand human emotions, and respond appropriately, making interactions more meaningful and effective. Continuous technological innovations are leading to the development of more sophisticated and user-friendly robots, which are gaining traction across various applications. The growing investment in research and development to enhance the capabilities of these robots is expected to propel market growth further.

Regional outlook reveals that North America is expected to dominate the pet therapy robot market, attributed to the high adoption rate of advanced technologies and the presence of key market players. Europe follows closely, driven by a strong focus on healthcare innovation and supportive regulatory frameworks. The Asia Pacific region is anticipated to witness the fastest growth, owing to the increasing elderly population and rising awareness of mental health. Government initiatives and funding in countries like Japan and China are also bolstering market growth in this region.

Product Type Analysis

The pet therapy robot market by product type is segmented into companion robots, therapy robots, and social robots. Companion robots are designed to provide emotional support and companionship, particularly for individuals living alone or in isolation. These robots mimic the behavior of real pets, offering comfort and reducing feelings of loneliness. The increasing number of single-person households and the growing awareness of the benefits of emotional support are driving the demand for companion robots. Technological advancements that enhance the lifelike behavior of these robots are also fueling their popularity.

Therapy robots are specifically designed for therapeutic purposes, targeting individuals with specific health conditions. These robots are used in various therapeutic settings, including hospitals, rehabilitation centers, and nursing homes. They assist in physical therapy, cognitive rehabilitation, and emotional healing. The rising prevalence of chronic diseases and disabilities is propelling the demand for therapy robots. Healthcare professionals are increasingly incorporating these robots into treatment plans to enhance patient outcomes, thus driving market growth.

Social robots, on the other hand, are designed to facilitate social interactions and improve communication skills. These robots are particularly beneficial for individuals with social anxiety, autism, and other social disor