The New School has long been renowned for its prowess in the social sciences, design, and performing arts. But today the university is reaching beyond its traditional spheres, cultivating knowledge and expertise in the most innovative technology in human history: quantum computing.
Partnering with IBM Global University Program and IBM Skills Academy, The New School has launched a revolutionary quantum computing initiative that challenges students and researchers to explore applications to art, design, education, business, and even social justice. The university’s first quantum computing course was spearheaded by Dr. Lin Zhou, senior vice president and chief information officer of The New School, and Sven Travis, associate professor of media and design. Premiering at Parsons’ School of Art, Media, and Technology last year, the class yielded groundbreaking results for the university and the industry at large.
Individuals who have taken part in the IBM Skills Academy course can earn certificates indicating their mastery. So far, only 96 IBM Skills Academy Quantum Practitioner Certificates have been distributed, 12 percent of which belong to New School students, staff, and faculty. In other words, New Schoolers are officially among the first innovators to have access to this technology, and they are actively leading its development. Dr. Robert Sutor, who holds the title chief quantum exponent at IBM and has spoken in Zhou and Travis’ classroom, confirms that Parsons students are part of the first generation in their disciplines to be exposed to quantum computing. “They have a running head start,” he says.
According to Zhou, keeping up with disruptive technology and investing in computer science is essential for any academic institution hoping to remain relevant in this decade, let alone this century. He argues that literacy is now defined not just as the ability to read and write but also as the ability to engage with and program computers. “When I joined The New School, I felt we had an obligation to prepare the next generation of talent for the technology-concentrated future,” he explains.
Zhou believes The New School has an important role to play in the development of quantum computing. He says that to harness the technology’s full potential, we’ll need to integrate quantum capability into daily life in thoughtful ways. As a university that’s been committed to social change and progressive innovation since its inception, The New School is uniquely positioned to research how quantum computing can be applied to the world in distinctly human-centered forms. “Preparing our society for this technology is largely the responsibility of liberal arts schools, of scholars,” says Zhou. “So we need to step up and better the social DNA of quantum, rather than solely put it on steroids.”
Parsons’ quantum computing course was designed for students with little or no computer science experience. After an introduction to quantum physics and computing, students in the class accessed IBM’s quantum machines through the cloud and developed programs using an open-source framework called Qiskit. To Zhou and Travis’ delight, students excelled in grasping the novel technology and submitted final projects that reflected the creative thinking Parsons is known for.
According to Travis, students were encouraged to engage with their subject critically, as they would be in any other Parsons course. “No one has really looked at the technology and said, ‘Well, how does this change the way society might be looking at computers?’” he explains. It’s important to advance that kind of inquiry while quantum technology is still in its infancy, rather than after it’s been fully unleashed and we’re stuck addressing consequences retroactively, as we’ve had to do with innovations like social media. “Working with these new technologies, it’s increasingly important to look at issues of social justice and equity,” Travis adds. “As designers, we can’t solve the wicked problems just by viewing technology as a tool; we have to embrace technology as an intelligence amplifier that is going to allow us to solve design problems in fundamentally different ways.”
Indeed, students in the course devised projects that brought quantum technology to a human scale. Their work ranged from solutions for managing traffic and strengthening QR code security to cultural pursuits like music and fine art. Quantum computing is still in its early stages, and student work reflected this raw quality. But it was clear that the New School way of thinking is moving the technology toward new realms of possibility.
Zhou and Travis are enthusiastic about the impact their course has had on students’ career opportunities. “Quantum computing has been heavily invested in by industries ranging from finance and natural resources to pharmaceuticals, automobile companies, and genetics,” says Zhou. Having knowledge of quantum technology can open up numerous and diverse pathways for students.
Parsons’ quantum computing effort has also won major accolades. This year, the Quantum Computing for Design and Social Research project entry won a FutureEdge 50 Award, which recognizes the most advanced trials and applications of emerging technologies in business. This overwhelming success only enhances the potential of The New School’s unique collaboration with IBM. Zhou and Travis hope to channel growing momentum into the creation of a computer science graduate program. This would further solidify the university’s role in the development of quantum technology and establish a real STEM presence in an already diverse, transdisciplinary institution.
Like quantum systems themselves, The New School’s quantum offerings are still in their early stages, developing according to need and opportunity in equal measure. But as with the technology itself, there is no doubt of the limitless potential in this sphere. As Zhou says, “This opens a new frontier for The New School.”
The minor in Robotics is designed to provide students with a solid and coherent introduction to the field and consists of two parts: four required core courses (9 credit hours) to supply students a strong, working foundation in the associated technology and three elective courses (9 credit hours) that allow students to explore various sub-areas within the field or specialize more deeply in one area.
Robotics Core Courses
To graduate with a minor in Robotics, students must earn an average GPA of 2.0 in six courses (18 credit hours).
Robotics Elective Courses
With elective courses, some course substitutions are possible - a list of acceptable substitutions will be maintained by the Coulter School of Engineering in conjunction with the Mechanical and Aeronautical Engineering department, the Electrical and Computer Engineering department, and the Computer Science department and updated annually.
Electrical and Computer Engineering
Mechanical and Aeronautical Engineering
Microcredentials are stackable digital credentials that are endorsed by Clarkson University and that represent earners’ Tested knowledge, skills, and experiences. When you enroll in a microcredential module, you’ll participate in a short learning experience, e.g., an online course, workshop, or internship. You earn microcredentials by successfully demonstrating your knowledge or skills via expert-designed assessments. Microcredentials you earn can be shared on digital résumés, LinkedIn, ePortfolios, personal web pages—nearly any digital context where you want to show employers what you know and can do.
More than a decade ago, Marc Andreessen, the internet entrepreneur and venture capitalist, famously declared, “Software is eating the world.”
The winners, Mr. Andreessen wrote in The Wall Street Journal, would be mainly “entrepreneurial technology companies that are invading and overturning established industry structures.”
His essay was a distillation of a long-held article of faith in Silicon Valley.
Clearly, some traditional businesses such as advertising and retailing have been upended by software-fueled companies like Google, Facebook and Amazon, the new giants on the corporate landscape.
But there is also a very different software story, according to James Bessen, executive director of the Technology & Policy Research Initiative at the Boston University School of Law.
In a new book, Mr. Bessen challenges what he terms the “disruption myth.” He makes the case that big companies in one industry after another have built complex software systems for managing their sales, marketing, operations and product offerings that are essentially moats against competitors.
This mastery of software by major corporations, he argues, helps explain rising economic concentration, increasing inequality and slowing innovation.
“This is a broad swath of the economy — way beyond a handful of big tech companies in Silicon Valley,” Mr. Bessen said. “There is an advantage to software that economists haven’t really reckoned with yet. Software isn’t accelerating creative destruction today. Software is suppressing it.”
Mr. Bessen brings an unusual perspective to his economic analysis. He is a former software entrepreneur from the personal computer era who founded an early desktop publishing software company, which he ran for a decade. When he sold his venture to a larger company in 1993, he made millions. It was pocket change by the standards of today’s tech start-ups, but it meant career freedom for Mr. Bessen.
Mr. Bessen then got in touch with his former roommate at Harvard University, Eric Maskin, who had become an economics professor at their alma mater. Mr. Bessen explained that he had ideas about the software industry that might be of interest to economists, Mr. Maskin recalled. The two went on to write a research paper on why patents often worked against innovation in software, an industry that prospered when information was shared.
The joint study helped start Mr. Bessen’s career as an academic. His research has focused mainly on the economics of innovation and the broad impact of technology. The title of his book, “The New Goliaths: How Corporations Use Software to Dominate Industries, Kill Innovation, and Undermine Regulation” (Yale University Press), suggests a strident critic. But his past research has also come down on the side of technology.
In 2015, amid rising concerns that automation was a job killer, Mr. Bessen published a paper that examined the impact of computer automation on 317 occupations from 1980 through 2013. His summary conclusion: “Employment grows significantly faster in occupations that use computers more.”
Mr. Bessen himself is an entrepreneurial outsider to the field of economics. He has forged an unorthodox career in academia, rising to prominence gradually over the years, one intriguing research project at a time. He has become respected in economic circles without a Ph.D.
“Jim’s not a professionally trained economist, so he has an original take,” said Mr. Maskin, his former college roommate, who won a Nobel Prize in economics in 2007. “That’s played to his advantage and to the profession’s advantage.”
Blending data analysis with narrative case studies is the hallmark of Mr. Bessen’s research. He is a business historian and a fluid writer. His book contains accounts of the evolving use of software in many industries, including autos, banking, retailing, insurance, garbage hauling, logistics and trucking.
Mr. Bessen’s observations about increasing market concentration, rising inequality, and slowing innovation and productivity echo those of other researchers. Most of those studies, though, are high-level economic research.
His focus is a more detailed look within industries and at individual companies, seeking the underlying technology engine behind the broad economic trends.
“He has a new, complementary perspective on what we’re seeing,” said Chiara Criscuolo, an economist at the Organization for Economic Cooperation and Development. “It gives you much more of the mechanism for why we got to where we got.”
That mechanism is what Mr. Bessen calls “proprietary software.” He defines it broadly as not only code but also the data that companies collect on their customers and operations, the skills of their workers and the organizational changes they have made to exploit the technology.
His measure of proprietary software does not include spending on the standard business software from companies like Oracle, SAP and Salesforce. Instead, it is the investment that companies make in custom software from those suppliers and others, and in their own in-house applications. Some of the software may be freely available open-source code, he notes, but the overall system is closed.
Mr. Bessen’s analysis is based on government and industry data, supplemented by information on jobs and salary estimates from Lightcast, a labor market research firm, which recently changed its name from Emsi Burning Glass. The total investment in proprietary software grew 74 percent to $239 billion over the decade that ended in 2019, the most latest government statistics. The big companies use this technology to manage complexity and gain competitive advantage, according to Mr. Bessen.
The big banks use their software and customer data to customize credit card offerings to individuals in a way that smaller rivals cannot. Walmart and Amazon use their proprietary software to streamline logistics and personalize marketing. Google and Facebook use it to target ads.
Insurers use it to tailor and market health plans to individuals. Pharmacy benefit management companies use it to navigate the complexity of drug reimbursement plans. And the list goes on. Evidence of the proprietary software advantage is abundant and convincing, in Mr. Bessen’s view.
The software-enabled winners in industries are more productive than their smaller rivals, and they pay more — 17 percent more on average for the same jobs, Mr. Bessen estimates.
But their success, he argues, has come at too great a price. Competition has suffered. Since the late 1990s, the chances of unseating a dominant firm — typically, one of the top four by sales in an industry — have declined by half. And technology, he contends, is spreading and being adopted across industries more slowly than in the past, which exacerbates the trends of inequality and market concentration.
His policy answer is not to break up dominant companies, but to nudge or force them to open up. For example, IBM, under antitrust pressure, unbundled its software from its hardware business in 1969. That move, Mr. Bessen writes, led to a flourishing software industry.
Today’s proprietary platforms, he asserts, could be opened through access to their software platforms or to customer data they have harvested — a prescription that policymakers in Europe and America are considering.
Mr. Bessen points to a seemingly unlikely protagonist: Amazon. Opening its computing infrastructure, he said, created the cloud computing industry. “In some ways,” he said, “Amazon is a model of what I’d like to see other firms do,” though with appropriate regulatory oversight.
One critique of Mr. Bessen’s analysis is that he is observing a wave of technology adoption that still has a long way to run, and that his concerns are overstated.
“These superstar firms are very productive,” said Robert Atkinson, president of the Information Technology and Innovation Foundation, a policy research group. “The question is why aren’t other companies as productive yet?” He added that they were likely to catch up.
And seemingly entrenched companies are not immune to truly innovative, technology-powered newcomers: Amazon challenging Walmart in retailing, and Tesla taking on the Detroit automakers, for example.
Both are exceptions, but ones that partly support his argument, Mr. Bessen insists. Both have become powerhouse corporations, he said, largely because of their prowess in designing and exploiting complex software.
“Technology,” Mr. Bessen said, “is playing a different role than it has in the past — less to disrupt than entrench.”
India’s ‘techade’ will witness several business trends accelerate, from hybrid workplace to contactless delivery. To transform and keep pace with these trends, businesses will need to become more agile and responsive to the market. This business imperative is making hybrid cloud the prevalent IT architecture. A hybrid cloud architecture combines best-of-breed cloud services and functionality from multiple cloud vendors, flexibility in choosing optimal cloud computing environments for each workload and moving those workloads freely between public and private cloud as circumstances change.
Organizations are finding great value from the early stages of hybrid cloud adoption for improving product and service delivery while fostering innovation. In fact, a latest IBM Institute for Business Value study estimates the value of hybrid cloud investments multiplies up to 13x on average when combined with other levers of transformation. This is why 99% of organizations in India are now using varied combinations of hybrid cloud architecture.
However, the question to ask is, are we adopting the right strategy to make the most of this opportunity? Here are five major challenges in the way of hybrid cloud mastery, which organizations must pay special attention to leverage its full potential.
Architecture that provides a suite of cloud services
During the pandemic, several companies in India had to adopt new hybrid cloud architectures at speed, assembling public, private and on-premises environments without proper integration. There was no organised structure or platform to bind them. Mastering hybrid cloud will require integrating cloud assets with a clear vision, starting with a hybrid cloud platform architecture that defines a “fabric” of cloud services across multiple environments.
A modern hybrid cloud infrastructure is starting to coalesce around a unified hybrid multi-cloud platform that includes support for cloud native application development, a single operating system and automating the deployment of applications across all cloud environments.
For instance, Bharti Airtel has built a telco network cloud using hybrid cloud and cognitive enterprise capabilities to deliver a better customer experience through enhanced network performance, improved availability, operations automation and scaling the network to the edge.
Breaking the silos
Indian companies are facing a shortage of talent, which makes it difficult to cover all areas of cloud management. Moreover, they are faced with a lack of a single infrastructure for seamless work experience which leads to work getting done in silos. Mastering hybrid cloud requires employees with critical cloud skills to do their work effectively in an integrated way across a common hybrid cloud operating model. To do it right, organizations should design operating models for incorporating cloud native, efficient, and connected working practices across the hybrid environment, addressing gaps in skills, talent, and experience.
Scale with security
Security has always been a key concern for organizations on their digitization journey, but with unintegrated cloud architecture the risk is greater, leading to data breaches, financial impact, reputational damage, regulatory enforcement actions and more. Organizations need to adopt a security-aware and security-first culture, ensuring robust security protocols and capabilities across the hybrid platform in a consistent way. For example, in a hybrid cloud architecture, you can reserve behind-the firewall private cloud resources for sensitive data and highly regulated workloads and use more economical public cloud resources for less-sensitive workloads and data. This allows organizations to foresee any potential threats across operations and mitigate them.
Maximizing returns on cloud investment
Managing cloud investments becomes very difficult when costs rise or are unpredictable. In certain cases, the cost of moving the data could go as high as 50%. In a hybrid cloud environment, organizations can manage their cloud cost through a single window to assess how cloud services are disbursed across the whole enterprise, allowing them to optimise the cloud cost by directly matching it with business priorities.
The Godrej Group, for example, has deployed cloud solutions which are expected to help them save 10% on the total cost of ownership over a period of five years, along with zero security incidents and a 100% increase in disaster recovery coverage.
Unlocking value with partner ecosystem
Deploying hybrid cloud often requires a whole ecosystem of partners, whether external or internal, who come with their own competing interests. Mastering hybrid cloud requires getting these naturally competing interests to embrace open innovation and co-creation through an aligned strategy to deliver a successful program.
To conclude, Indian organizations need to take a closer look at their hybrid cloud journey. Consider the five challenges and determine actions required to course correct. Not every organization will have a templatized approach to adopting hybrid cloud. They need to find a sweet spot between building hybrid cloud capabilities and the roadmap for better business performance in a software-driven world. Once mastered, businesses will create new value propositions and become a lever of innovation in the techade.
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Views expressed above are the author's own.
New Jersey, United States – Cybersecurity Market 2022 – 2028, Size, Share, and Trends Analysis Research Report Segmented with Type, Component, Application, Growth Rate, Region, and Forecast | key companies profiled -IBM (US), Cisco (US), Check Point (Israel), and others.
The development of the Cybersecurity Market can be ascribed to the developing complexity of digital assaults. The recurrence and power of digital tricks and violations have expanded over the course of the past 10 years, bringing about gigantic misfortunes for organizations. As cybercrimes have expanded essentially, organizations overall have directed their spending security advances to reinforce their in-house security foundations. Designated assaults have seen an ascent lately, invading targets’ organization framework and all the while keeping up with secrecy. Aggressors that have a particular objective as a top priority generally assault endpoints, organizations, on-premises gadgets, cloud-based applications, information, and different other IT frameworks. The essential thought process behind designated assaults is to interfere with designated organizations or associations’ organizations and take basic data. Because of these designated assaults, business-basic tasks in associations are adversely affected by business disturbances, protected innovation misfortune, monetary misfortune, and loss of basic and touchy client data. The effect of designated digital assaults influences designated associations as well as homegrown and worldwide clients.
According to our latest report, the Cybersecurity market, which was valued at US$ million in 2022, is expected to grow at a CAGR of approximate percent over the forecast period.
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Cybersecurity Market necessities develop at a higher rate than spending plans intended to address them. The majority of the little firms come up short on a financial plan and IT security mastery to take on improved network protection answers to defend their organizations and IT foundations from different digital assaults. The restricted capital subsidizing can be a significant controlling component for a few little and medium-sized organizations embracing the online protection model. Emerging companies in emerging nations across MEA, Latin America, and APAC frequently face a test to secure money and suitable subsidizing to embrace network protection answers for their business. The capital financing in these organizations is significantly procured for defending business-basic activities, now and again leaving less or no subsidizing for improving high-level network protection arrangements. Besides, network safety financial plans in the arising new companies are lacking to execute Next-Generation Firewalls (NGFWs) and Advanced Threat Protection (ATP) arrangements.
The distributed computing model is generally embraced because of its strong and adaptable framework. Numerous associations are moving their inclination toward cloud answers for improving on the capacity of information, and furthermore, as it gives far off server access on the web, empowering admittance to limitless registering power. The execution of a cloud-based model empowers associations to deal with every one of the applications as it gives a particular testing examination that runs behind the scenes. The execution of cloud can permit associations to join valuable Cybersecurity Market advancements, for example, programming characterized edges, to make vigorous and exceptionally secure stages. States in numerous nations issue extraordinary rules and guidelines for cloud stage security, which drives the Cybersecurity Market development across the globe. SMEs are continually looking to modernize their applications and foundations by moving to cloud-based stages, like Software-as-a-Service (SaaS) and Infrastructure-as-a-Service (IaaS).
Based on components, the cybersecurity market is segmented into hardware, software, and services. Cybersecurity technology is offered by various vendors as an integrated platform or a tool that integrates with enterprises’ existing infrastructure. Vendors also offer cybersecurity hardware associated with services that help organizations in implementing the required solution in their current infrastructure. In latest years, several developments have been witnessed in cybersecurity software and related hardware development kits.
Cybersecurity services are classified into professional and managed services. Professional services are further segmented into consulting, risk, and threat assessment; design and implementation; training and education; and support and maintenance. The demand for services is directly related to the adoption level of cybersecurity solutions. The adoption of cybersecurity solutions is increasing for securing business-sensitive applications.
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North America, being a technologically advanced region, tops the world in terms of the presence of security vendors and cyber incidents. As the world is moving toward interconnections and digitalization, protecting enterprise-critical infrastructures and sensitive data have become one of the major challenges. North America is an early adopter of cybersecurity solutions and services across the globe. In North America, the US is expected to hold a larger market share in terms of revenue. The increasing instances of cyber-attacks are identified as the most crucial economic and national security challenges by governments in the region.
Businesses in this region top the world in terms of the adoption of advanced technologies and infrastructures, such as cloud computing, big data analytics, and IoT. Attacks are increasing dramatically and becoming more sophisticated in nature and targeting business applications in various industry verticals. Sophisticated cyber attacks include DDoS, ransomware, bot attacks, malware, zero-day attacks, and spear phishing attacks.
The infrastructure protection segment accounted for the largest revenue share in 2022, of the overall revenue. The high market share is attributed to the rising number of data center constructions and the adoption of connected and IoT devices. Further, different programs introduced by governments across some regions, such as the Critical Infrastructure Protection Program in the U.S. and the European Programme for Critical Infrastructure Protection (EPCIP), are expected to contribute to market growth. For instance, the National Critical Infrastructure Prioritization Program (NIPP), created by the Cybersecurity and Infrastructure Security Agency (CISA), helps in identifying the list of assets and systems vulnerable to cyber-attacks across various industries, including energy, manufacturing, transportation, oil & gas, chemicals, and others, which is damaged or destroyed would lead to national catastrophic effects.
Major vendors in the global cybersecurity market include IBM (US), Cisco (US), Check Point (Israel), FireEye (US), Trend Micro (Japan), NortonLifeLock (US), Rapid7 (US), Micro Focus (UK), Microsoft (US), Amazon Web Services (US), Oracle (US), Fortinet (US), Palo Alto Networks (US), Accenture (Ireland), McAfee (US), RSA Security (US), Forcepoint (US), Sophos PLC (UK), Imperva (US), Proofpoint (US), Juniper Network (US), Splunk (US), SonicWall (US), CyberArk (US), F-secure (Finland), Qualys (US), F5 (US), AlgoSec (US), SentinelOne (US), DataVisor (US), RevBits (US), Wi-Jungle (India), BluVector (US), Aristi Labs (India) and Securden (US).
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The pandemic created enormous changes in our workforce and educational systems. Employees, who possess skills that match the needs of today’s evolving industry needs, are in shortage. This “skills gap” makes it a challenge for employers to find workers with appropriate skills and talents. An emerging solution to this comes from higher education. Micro-credentials were created to fill this “gap.”
Stackable credentials and digital badges are ways for individuals to acquire knowledge and skills in small portions. Learning can be directly aligned with workforce needs. By obtaining an assortment of credentials, rather than a single degree, learners progress in a current or future career pathway. By using digital badges and stackable credentials learners are finding opportunities to develop technical and soft skills to demonstrate their proficiencies.
Digital badges are one way to show that you acquired a skill, achievement or experience that can increase your employability. Digital badges may be obtained from a college or university. Online platforms such as edX, or large companies like Google, Microsoft, and IBM offer competency-based digital badges that demonstrate the learner’s mastery of knowledge. Learners can use these pieces of data to verify the training they have received. The metadata holds information about the awarding organization, date of completion, and a description of the curriculum. There are many benefits to obtaining digital badges. They are more affordable and flexible than traditional education. Some are even free. It takes less time to earn a digital badge than a degree, certificate or diploma. In most cases, an individual can increase their skills in months, rather than years. Students can share digital badge information through social networks and communicate this information to employers, associations, or organizations. Badges can be shared on LinkedIn, social media, resumes or CVs and e-portfolios, as well as on college applications. Some badges can be earned in a work setting or in a community volunteer position. Digital badge opportunities are available for students of any age, background and educational level.
One example of an organization that provides useful badges for today’s workplace is Google Cloud. They have over 700 learning activities that include labs, documents, videos and quizzes in a variety of modules. A link to their catalog of badges can be found at https://www.cloudskillsboost.google/.
Stackable credentials make higher education more affordable, manageable and relevant. Stackable credential pathways consist of sequential awards that allow learners to earn higher-level credentials or build a “lattice” of interconnected credentials. Since stackable credentials are obtained in small chunks, it allows more flexibility for the learner. New skills can be stacked onto prior education or training. They can be accumulated over time or help to move the learner along a career pathway. Students have more opportunities to move between college and career or to continue lifelong learning. Like digital badges, stackable credentials focus on critical skills.
In California, with 116 community colleges to choose from, one can find a wide variety of stackable credentials. It is also becoming much more common for four-year institutions to offer shorter term certificate programs to enhance the student’s major. Metropolitan State University, Denver is a leader in the movement of stackable credentials. They are focusing on industries that are in high demand. MSU Denver is concentrating their credentials in cybersecurity, healthcare, space flight, journalism and mass media as well as business. All are obtainable in a short period of time.
To meet the need of a rapidly evolving economy in California, a new online community college emerged in 2021. In April of 2022, Calbright College had awarded its 100th Certificate of Competency. Calbright is an entirely free online college for any adult Californian with a high school diploma or equivalent. It has been designed to support non-traditional learners. Calbright College prepares students to earn industry-valued certifications. They use competency-based education that puts an emphasis on what students learn rather than time spent in class. It allows students to work at their own pace and fit study into their unique schedules. Calbright offers academic and career support. The certificates offered are entirely career-focused and in high demand. Most courses can be completed in less than a year. Currently Calbright College has offered certificates in the fields of medical coding, cybersecurity, information technology and customer relationship management (CRM) administration. A link to their program can be found at https://www.calbright.org/.
Our workforce and educational systems will continue to evolve. Micro-credentials may help bridge the skills gap to help meet the needs of our future labor market.
Rose Murphy is a retired high school counselor now working as an independent educational consultant. She can be reached at email@example.com or her website at abestfitcollege.com
Previous research has shown that older women use more formal care than older men (Einiö et al., Reference Einiö, Guilbault, Martikainen and Poulain2012; Dorin et al., Reference Dorin, Krupa, Metzing and Büscher2016), while older men use more informal care (McCann et al., Reference McCann, Donnelly and O'Reilly2012), and especially spousal care, than women (Dorin et al., Reference Dorin, Krupa, Metzing and Büscher2016; Schmidt, Reference Schmidt2017). The differences in morbidity and mortality between older women and men are considered important drivers of these gender differences in long-term care (LTC) use. Women report poorer health (Boerma et al., Reference Boerma, Hosseinpoor, Verdes and Chatterji2016) and tend to suffer more often from long-term disabling conditions (Bird et al., Reference Bird, Shugarman and Lynn2002; Meinow et al., Reference Meinow, Wastesson, Kåreholt and Kelfve2020), whereas men more often have fatal conditions (Crimmins et al., Reference Crimmins, Shim, Zhang and Kim2019). In addition, men are usually older than their wives (McCann et al., Reference McCann, Donnelly and O'Reilly2012). Hence women tend to outlive their husbands and are more often dependent on formal LTC services. Another reason for this gender gap is that care use is deeply rooted in and intertwined with family relations and social and cultural norms. In traditional gender roles, caregiving has been considered more natural to women than men (Williams et al., Reference Williams, Giddings, Bellamy and Gott2017). Such norms can promote female caregiving for male partners, parents and relatives. In addition, men have been reported to prefer informal care use more often than women (Pinquart and Sorensen, Reference Pinquart and Sorensen2002) and to have higher expectations regarding informal caregiving from their partner (Williams et al., Reference Williams, Giddings, Bellamy and Gott2017). Thus, both health and social factors contribute to older men using more informal care – especially spousal care – than women, and to women using more formal care than men.
Such an individual-level explanation needs to be placed in the context of societal changes: in many countries the health and social resources of the older population as well as LTC policies have changed considerably in the past decades. This may have impacted both the demand for and supply of LTC in the older population (Agree and Glaser, Reference Agree, Glaser and Uhlenberg2009; Broese van Groenou and De Boer, Reference Broese van Groenou and De Boer2016). This raises the question of whether and to what extent men and women have been differently affected by these changes, and whether the gender gap in care use has possibly been affected as a result. The main aim of this study is to explore the robustness of the gender gap in various types of LTC use over a period of two decades (1995–2016) in the Netherlands.
Following the behavioural care model of Andersen and Newman (Reference Andersen and Newman2005), there are three types of individual determinants of care use: the need for care (health), the disposition to use care (e.g. education, mastery) and factors enabling the use of care (e.g. social resources). We add to current knowledge by identifying gender-related factors concerning the need for care, the disposition to use care and the factors enabling the use of care (Andersen and Newman, Reference Andersen and Newman2005). As such, we can identify and discuss, for example, gender-specific barriers to seeking care and access to care services. At the individual level, the model of Andersen and Newman (Reference Andersen and Newman2005) considers gender as a key determinant of health-care use, but there is less research available on how gender is associated with care use and which gender-related factors contribute to differences in care use. Observing the developments in care use over time in a single country study has the advantage that the entire study population experienced the same societal changes. When the individual-level changes are taken into account, better insight into the importance of societal factors, i.e. changes in LTC policies, is obtained. Trends in care use may thus in part be related to changes over time in these individual determinants at the population level and in part to unobserved changes in a societal context such as family relations and social and cultural norms, and LTC policies (Figure 1). Hence, we expect this exploration to add to our insight into how individual- and societal-level developments intertwine.
In the following, we elaborate on various developments in the Netherlands that may have impacted the gender gap in the use and non-use of care among the older population. The types of LTC use under study are formal care (home care and residential care), informal care (spousal care and other types of informal care) and privately paid help (generally in the household). Our research questions are:
(1) To what degree has the gender gap in the five types of care use and non-use of care changed between 1995 and 2016?
(2) To what degree are the gender differences in care use and their possible changes over time explained by individual determinants of care use (i.e. need, dispositional and enabling)?
One important driver of the use of any type of care is health impairment: being in good health predicts the non-use of care, whereas being in poor health predicts the use of care. The fact that women have suffered from long-term disabling conditions more often than men (Bird et al., Reference Bird, Shugarman and Lynn2002; Meinow et al., Reference Meinow, Wastesson, Kåreholt and Kelfve2020) contributes to women's greater use of care. In the context of population ageing, both men's and women's life expectancies are increasing (Jørgensen et al., Reference Jørgensen, Fors, Nilsson, Enroth, Aaltonen, Sundberg, Brønnum-Hansen, Strand Bjørn, Chang and Jylhä2018), and in high-income and high-education countries such as the Netherlands, men's life expectancy is catching up with women's (GBD 2016 Mortality Collaborators, 2017). Yet, even though older men are living longer than before, they still have fewer health problems than older women. Deeg et al. (Reference De Meijer, Bakx, Van Doorslaer and Koopmanschap2018) showed that from 1992 to 2016, the proportion of years spent in poor health remained lower for men than for women. Hence, it is possible that persistent health differences between men and women maintain the gender gap in the use of all types of care.
The disposition to use care reflects to what degree one intends to ask for help from others, and whether one prefers formal, informal or privately paid care. A latest scoping review by Lehnert et al. (Reference Lehnert, Heuchert, Hussain and König2019) concluded that a mix of personal and social characteristics determines the preferred care arrangement, with the wish to remain independent and to avoid becoming a burden to others prevailing. Gender, socioeconomic status, and personality factors are important drivers of care preferences. Women, those with higher education or income and with a greater sense of mastery, generally prefer formal care or privately paid care over informal care (Pinquart and Sorensen, Reference Pinquart and Sorensen2002; Rogero-García and Rosenberg, Reference Rogero-García and Rosenberg2011; Lee et al., Reference Lee, Revelli, Dickson and Marier2022). Traditionally, older men have a greater sense of mastery (Cassidy and Davies, Reference Cassidy and Davies2003) and higher levels of education (Grundy and Holt, Reference Grundy and Holt2001) than older women. Educational levels and sense of mastery have increased significantly among older adults in the past decades (Drewelies et al., Reference Drewelies, Deeg, Huisman and Gerstorf2018), particularly so among older women. If gender differences in level of education and sense of mastery have decreased, this may affect the gender gap in informal, formal and privately paid care use, and reduce the gender gap over time.
The most important driver of the use of partner care obviously is the availability of a spouse. As older men have a spouse more often than older women, men are more likely to use partner care. The relatively greater increase in men's longevity implies that latest older cohorts are more likely to live with a partner than earlier cohorts, which means that partner care is more readily available, in particular for older women (Ryan et al., Reference Ryan, Smith, Antonucci and Jackson2012). This narrowing gender difference in partner status may contribute to a decrease in gender differences in spousal care over time.
Non-spousal informal care is generally provided by adult children. Previous studies have shown that older women receive non-spousal informal care more often than older men (Chappell et al., Reference Chappell, Dujela and Smith2014; Dorin et al., Reference Dorin, Krupa, Metzing and Büscher2016). Several socio-cultural changes may have affected the ability and willingness of adult children to provide care to their parents. In post-modern societies, gender equality in education, work and family roles is more highly valued than before, resulting in increasing numbers of women taking up employment and increasing numbers of men taking up care roles. In addition, the higher retirement age of potential caregivers (Agree and Glaser, Reference Agree, Glaser and Uhlenberg2009; Broese van Groenou and De Boer, Reference Broese van Groenou and De Boer2016) and the weakening of norms regarding family obligations (Fingerman et al., Reference Fingerman, Pilleman, Silverstein and Suitor2012; Tsutsui et al., Reference Tsutsui, Muramatsu and Higashino2013) may pose challenges to informal care provision, particularly for adult children combining work and care. There is no explicit reason to assume that adult children will reduce their help to their father more than to their mother, or the other way around. Thus, the decline in availability of informal care from someone other than a spouse may have affected older men to the same extent as older women. The use of care from adult children is therefore expected to decrease, but it is expected that the gender gap in the use of non-spousal informal care has not changed over time.
As in many other Western European countries, the LTC scheme in the Netherlands has undergone several reforms in the past decades (Da Roit, Reference Da Roit2012; Plaisier et al., Reference Plaisier, Verbeek-Oudjik and de Klerk2017). Originally launched as a generous universal scheme in the 1990s, the supply of residential LTC in the Dutch LTC scheme has been substantially reduced since the 2000s. A brief increase in the supply of formal home care in the early 2000s was followed by restrictions in eligibility in 2007, when responsibility for household help shifted from national to local government. A major reform in 2015 further increased the threshold to residential care, and the allocation of personal and nursing care was decentralised to general practitioners and district nurses. At the same time, these policy efforts were aimed at compensating for the increasing scarcity of formal LTC resources by making care more tailor-made, affording the recipient greater responsibility for arranging their own care according to their personal needs and so increasing the efficiency of formal care provision (De Meijer et al., Reference Deeg, Comijs, Hoogendijk, Van der Noordt and Huisman2015; Janssen et al., Reference Janssen, Jongen and Schroder-Back2016). These policy changes have led to a decrease in residential care (Alders et al., Reference Alders, Comijs and Deeg2017) and an increase in the use of home care (Plaisier et al., Reference Plaisier, Verbeek-Oudjik and de Klerk2017) over time. A more restrictive LTC scheme could change the gender gap in the use of care services. Changes in the availability of publicly provided care, particularly residential and home care services, may also impact the use of informal care or privately paid care. The use of formal and residential care is strongly linked to health and partner status, which explains why older women use formal and residential care more often than older men. Yet, the supply of publicly provided services is also an important factor here. Given that women have been more dependent on formal and residential care than men, they might be affected most by more restrictive LTC policies. Thus, it is expected that the changes in care policies reduce the gender gap in formal home care use and in residential care use.
As laid out above, we assume that differences in care use are in part attributable to differences between cohorts and between men and women in individual resources: in particular, health, education, sense of mastery, and the availability of a spouse and/or children. Moreover, substitution effects between formal, informal and privately paid care must be taken into account. Specifically, reduced formal LTC supply will place increasing pressure on informal care, and reduced availability of formal LTC as well as non-spousal care will increase the volume of care purchased privately. Our analyses will supply insight into (a) the gender difference in the use of informal, formal and privately paid home care, residential care and in non-use over time; (b) the degree to which gender differences in care use are explained by individual determinants of care use (needs, disposition and enabling factors; Andersen and Newman, Reference Andersen and Newman2005) and the substitution between types of care; and (c) the difference in changes in care use over time between men and women (interaction effect of gender and year of observation). Any unexplained gender differences will shed more light on the extent to which unobserved societal changes, i.e. socio-cultural changes or LTC policy changes, may affect the gender differences in care use.
Our data were drawn from the Longitudinal Aging Study Amsterdam (LASA). LASA is an ongoing longitudinal study focusing on the determinants, trajectories and consequences of physical, cognitive, emotional and social functioning (Hoogendijk et al., Reference Hoogendijk, Deeg, Poppelaars, van der Horst, Broese van Groenou, Comijs, Pasman, van Schoor, Suanet, Thomése, van Tilburg, Visser and Huisman2016). The first interviews were carried out in 1992/93 among respondents aged 55–85 (N = 3,107). Measurement waves have been conducted every three to four years. The original LASA trial is based on a nationally representative trial of older adults from three geographic regions in the Netherlands (Huisman et al., Reference Huisman, Poppelaars, van der Horst, Beekman, Brug, van Tilburg and Deeg2011). In addition to the baseline cohort, new cohorts aged 55–65 were added in 2002/03 and 2012/13. In this study, we use face-to-face interview data from seven measurement waves in 1995/96, 1998/99, 2002/03, 2005/06, 2008/09, 2011/12 and 2015/16. In all measurements, interviews have been conducted with both community-dwellers and people living in residential homes. To ensure comparability across different waves, only persons aged 70–88 were included in the samples (6,527 observations/2,655 cases) as data from this age range are available in all waves.
This study concentrates on six outcomes. The five care types studied were informal (personal) care provided by the partner, informal care provided by someone other than the partner, publicly provided formal home care, privately purchased home care, and residential care. Two questions were asked: ‘Do you receive help with personal care, for example, washing, bathing, dressing?’ and ‘Do you receive help with household activities, for example, cleaning, shopping, cooking?’ If answered in the affirmative, the respondent was asked who provided this type of help. For partner care, only personal care was included in this study because there were differences across waves in which household tasks were defined as help from the partner. Informal care by someone other than a partner included personal care and/or household help provided by an unpaid care-giver (son or daughter, other relative or in-law, neighbour or friend). Formal home care included personal care and/or household help provided by a professional care-giver from a home care organisation. Privately paid home care included personal care and/or household help by a privately paid helper, generally not a professional but more likely a household helper. One of the living arrangement options observed by the interviewer was residential care. In the Netherlands, residential care is care offered in a facility round-the-clock for those who are unable to live in the community and who have high care needs. The sixth outcome variable consisted of the use of neither personal care nor household help at home or in residential care and was therefore titled non-use of care.
In line with the Andersen and Newman model, we distinguish the time variable and three domains of explanatory variables indicating to individual determinants of care use (Figure 1). The time variable, i.e. the year of observation in seven measurement years, refers to the historical time period and the specific LTC policy of that time. To indicate need, three indicators of health were included: cognitive functioning as measured by the Mini-Mental State Examination (MMSE) score, which ranges from 0 to 30 (Folstein et al., Reference Folstein, Folstein and McHugh1975); number of functional limitations as measured by six activities: difficulty using stairs, using own or public transport, cutting toenails, dressing and undressing, sitting down and standing up from a chair, and walking outside for five minutes without stopping (range 0–6, the highest score referring to difficulty with all six activities); and number of chronic conditions out of seven major conditions: (a) chronic lung disease, (b) cardiac disease, (c) peripheral arterial disease, (d) diabetes, (e) cerebrovascular accident, (f) osteoarthritis or rheumatoid arthritis and (g) cancer. Disposition variables included education and sense of mastery. Educational level ranged from low (elementary school only) through medium (secondary education) to high (college, university or higher). Sense of mastery, i.e. the feeling that one has control over events and ongoing situations, was measured by a five-item scale, with the sum score ranging from 5 to 25, a higher score indicating a greater sense of mastery (Pearlin and Schooler, Reference Pearlin and Schooler1978). Enabling variables included social resources, i.e. living with a partner (0, 1), having a partner outside the household (0, 1) and number of living children. Age (in years) was used as a control variable in all analyses.
All six outcome variables were dichotomous. Gender compares males (0) with females (1). Year of observation was used as the explanatory variable that refers to the historical time period (Swinkels et al., Reference Swinkels, Suanet, Deeg and Broese van Groenou2016). It was included as a categorical variable in order to be able to detect non-linear trends. Descriptive statistics were provided for all variables under study for men and women separately in all years of observation (Table 1). The possible multicollinearity was tested between the explanatory variables with the variance inflation factor values and coldiag2 (Stata 16), and with correlation coefficients, when applicable. Multicollinearity was not observed. For multivariate statistical analysis, we applied generalised estimating equations logistic regression using IBM Statistics 25 and Stata/S.E. 14.2. This method accounts for the interdependence of observations of individuals who participated in multiple waves. An exchangeable correlation matrix was used. In all analyses, age is included to account for possible differences in the age distribution between years of observation.
For each care type, analyses were run in six or seven steps. First, age, gender and year of observation were included in Model 1 to examine the effect of gender on care use. Next, possible explanatory variables were added to the models separately: the need variables (Model 2), the disposition variables (Model 3), the enabling variables (Model 4) and the use of other types of home care (Model 5). Model 5 was run only for the four types of home care, excluding residential care and non-use. The full models (Model 6) included all the explanatory variables. The interaction models included the interaction effect of gender × year of observation. Based on the interaction models, predictive margins were calculated to demonstrate the interaction between the observation year and gender in graphs (StataCorp, nd); this statistic reports predictions at average values of the covariates.
In this study, we examined gender differences in the use of several sources of care and how these differences may have changed over time. Three conclusions are derived. First, a gender gap was found in the use of all sources of care as men used more personal care provided by the partner, and women used more of all other sources of care. Second, social resources had a substantial association with gender differences in care use. Differences in social resources between men and women explained the gender gap in informal care and formal home care use, and together with health factors, the gender difference in residential care use. On the other hand, individual factors did not explain the gender gap in the use of private home care and non-use of care. Third, the inclusion of explanatory factors revealed several changes in the gender gap over time. Women were more likely than men to use informal care by a partner in 2005/06 versus 1998/99, formal home care in 2005/06 versus 1998/99, and residential care in 2001/02 and 2008/09 versus 1998/99, while non-use increased especially in men (in 2005/06, 2008/09, 2015/16 versus 1998/99). In both genders, overall trends in care use showed an increase in the use of formal home care and a decrease in the use of other care types. Although health and dispositional factors (education and mastery) explained only little of the gender differences in care use, their contribution was not insubstantial regarding informal and formal care use, and they helped gain a better understanding of the gender gap in these types of care.
Our result that gender differences in partner care, other informal care and formal home care were largely due to gender differences in social resources support earlier findings. The importance of partner help is also illustrated by how changes in family structure are linked to the use of LTC: continuously married adults had a similar risk of LTC use to remarried and partnered adults, and lower risk than widowed, divorced/separated and never married adults (Thomeer et al., Reference Thomeer, Mudrazija and Angel2018). In Germany, women often receive help from several informal sources and formal care services, while men rely mainly on their wives for help (Dorin et al., Reference Dorin, Krupa, Metzing and Büscher2016). This is also reflected in the study by Schmidt (Reference Schmidt2017), who found prevailing gender roles in caregiving and care use in Austria. Our data confirmed our assumption that in latest study years women had a co-habitant partner more often than in earlier years, yet the gender difference in having a co-habitant partner remained in favour of men. This result suggests that gender differences in partner care were largely due to the lack of a co-habiting partner among women. The share of those having a partner outside the household increased slightly during the study years. When in poor health, those with a partner living apart are less likely to receive daily care from their partner than co-habiting partners (Broese van Groenou et al., Reference Broese van Groenou, Te Riele and de Jong Gierveld2019). This implies that partners living apart may not be as available for late-life care as partners in co-habiting relationships. However, as the increase in partners living apart was only around six percentage points, its possible effect on our results is minor. Furthermore, adult children are major providers of informal care. In the case of remarriage and stepchildren, stepchildren are less likely to provide care to stepparents in later life (Coleman et al., Reference Coleman, Ganong, Hans, Sharp and Rothrauff2005). The link between changing family structures and the use of informal care is one possible explanatory factor for the decline in informal care use, but unfortunately our data do not allow more detailed research on the subject.
Over the two decades under study, the Netherlands moved towards more restrictive LTC policies. Our findings show an increased use of formal home care and lower use of residential care over time, corresponding with the stricter eligibility criteria, especially after 2005 (De Meijer et al., Reference Deeg, Comijs, Hoogendijk, Van der Noordt and Huisman2015). These changes were not explained by the various individual factors taken into account in our analysis, which supports the attribution of these changes to factors beyond individual characteristics. In fact, our findings of a decrease in residential care use and an increase in formal home care use in both men and women reflect the ‘ageing-in-place’ policy. We expected that the well-known gender gap whereby women use formal care services more often than men (Bird et al., Reference Bird, Shugarman and Lynn2002; Algera et al., Reference Algera, Francke, Kerkstra and Van Der Zee2004) would be reduced as the restrictions should have affected women – the more frequent formal care users – to a greater extent than men. This appeared not to be the case. In fact, the gender gap increased in some, albeit not in all years of observation, after individual health, dispositional factors and social resources were taken into account. This suggests that, although the allocation of formal and residential care is largely based on care needs and the presence of a partner and/or children, there was also a gender bias in the allocation of formal home care and residential care in some but clearly not all years of observation.
Given that formal home care allocation became less generous over the years, one would have expected to see an increase in the use of alternative sources of care, such as informal care and privately paid care. However, it seems that the opposite has been the case as the use of these sources of care declined over time, contributing to the decrease in care use in both genders. Moreover, non-use increased significantly, even when health and social resources were taken into account. Thus, this increase was not driven by possible improvements in health and social resources. This suggests that a more restrictive LTC policy left older people without care even when they had health conditions that would have contributed to care use in earlier years. There is, for example, evidence that over time, the decline in admissions to LTC institutions is not only the result of changes in need (De Meijer et al., Reference Deeg, Comijs, Hoogendijk, Van der Noordt and Huisman2015; Alders et al., Reference Alders, Comijs and Deeg2017), but also of changes in needs-based LTC eligibility criteria. In all, changes in LTC policies are complex and very difficult to grasp into empirical variables. It would be essential to study further to what extent and how the eligibility criteria for access to public formal home care and the related guidelines explain variations in care use over time.
Our findings show that the availability of both a co-resident partner and informal care by someone other than the partner was associated with a lower level of formal care use. This substitution effect suggests that restricting LTC will increase informal care use, but the matter is more complicated: both individual characteristics and family structures, and cultural norms, steer the need for and the use of informal care (Haberkern and Szydlik, Reference Haberkern and Szydlik2010). In countries with a weaker public care service system, people may feel obligated to care for their family members (Cooney and Dykstra, Reference Cooney and Dykstra2011; Verbeek-Oudijk et al., Reference Verbeek-Oudijk, Woittiez, Eggink and Putman2014). Instead, countries with strong national health-care infrastructures are less likely to prefer family-based care (Mair et al., Reference Mair, Quiñones and Pasha2016). In traditional gender roles, women are expected to adopt the role of a caregiver (Sharma et al., Reference Sharma, Chakrabarti and Grover2016), which may make informal care an option considered as a priority. According to Cooney and Dykstra (Reference Cooney and Dykstra2011), also the logistics matter: the shorter living distance between family members may contribute to higher use of informal help. Some people experience receiving help from family or friends instead of formal carers as an expression of independence (Hillcoat-Nallétamby, Reference Hillcoat-Nallétamby2014). It is possible that when care and caring remain ‘in the family’, people feel more independent, and the care is more manageable when compared to formal care service providers, who follow their own work schedule and priorities. Moreover, preference towards informal care is also dependent on the care receiver's level of disability (Mair et al., Reference Mair, Quiñones and Pasha2016); informal care substitutes for formal home care, but the substitution effect disappears as the level of disability of the older person increases (Bonsang, Reference Bonsang2009).
While we started out from the assumption that older women are more affected by societal changes, including LTC policies, than older men, it appears that older men may be affected more than older women by a decrease in the supply of informal and formal care, as the use of care decreased more slowly for women. In men, the increased frequency of non-use may be attributed to cutbacks in formal LTC coupled with a decline in the availability of non-spousal informal care. Women may be more active and persistent in care-seeking (Thompson et al., Reference Thompson, Anisimowicz, Miedema, Hogg, Wodchis and Aubrey-Bassler2016). We observed that women were more likely to use privately paid care than men, and this gender gap remained stable throughout the study years. Hence, it seems that women were more able – or willing – to purchase care from private home care providers. The growing gender gap in not using any care raises concerns especially regarding the possible increase in unmet care needs of older men. Many chronic diseases have become much more manageable over time, and especially men who have survived these previously fatal diseases may have an increased need for care. Research on older men's and women's care trajectories, particularly after widowhood, may help to shed light on whether and why older men use less care than older women.
This study was subject to some limitations. First, the data included only those persons who were able to participate in interviews, which means those in the poorest health were excluded. However, this allowed us to consider important factors contributing to care use such as cognitive functioning (MMSE) and sense of mastery – measures that cannot be provided by proxies. Second, we were able to detect gender differences in care use and changes in care use over time but had only limited possibilities to investigate the underlying causes. In particular, changes in the supply of informal and formal care were unobserved measures in our study and were only reflected in the year of observation variable. The inclusion of more direct measures (e.g. number of LTC beds per year) has proved useful in cross-national comparisons (Suanet et al., Reference Suanet, Broese van Groenou and van Tilburg2012; Wagner and Brandt, Reference Wagner and Brandt2018), but they have limited empirical value in within-country studies due to the lack of variation (e.g. Rostgaard and Szebehely, Reference Rostgaard and Szebehely2012). Third, our focus in this study was on people aged 70–88. Over the years, it is possible that the amount of time lived with severe health problems has increasingly shifted towards the older population, even older than 88 (Deeg et al., Reference De Meijer, Bakx, Van Doorslaer and Koopmanschap2018). The majority of those who live to old age experience a period of chronic illness and an increased need for care, especially when the end of life is approaching (e.g. Forma et al., Reference Forma, Rissanen, Aaltonen, Raitanen and Jylhä2009; Pot et al., Reference Pot, Portrait, Visser, Puts, Broese van Groenou and Deeg2009). As age at death is continuing to rise, older ages are of ever-greater interest as far as studying care use is concerned. It may, therefore, be considered a limitation that we did not include people older than 88 in our study. Fourth, as our trial excludes the most disadvantaged individuals such as those with severe dementia, who make up a significant proportion of residential care users, the share of residential care users in this study is an underestimation. However, we felt that the inclusion of residential care is important to see how the gender gap changes over time when a comprehensive definition of care is used. Fifth, a specific concern for studies on ageing is the high rate of attrition. However, we do not consider attrition a major problem for the reliability of our findings. In LASA, attrition can for the largest part be attributed to mortality and, to a much lesser extent, to refusal or other reasons; attrition due to mortality does not affect trial representativeness because high mortality is characteristic of all older populations. To avoid the negative effects of attrition on trial size, men and the oldest participants were oversampled in LASA (Huisman et al., Reference Huisman, Poppelaars, van der Horst, Beekman, Brug, van Tilburg and Deeg2011). Sixth, this study focuses on the changes in the gender gap in care use in the Netherlands. However, as shown in the theoretical part of this study, studies from different countries show similar gender differences in care use. In addition, the changes in care policies are roughly similar – ageing-in-place and informal care are emphasised in public debate and policy recommendations in many Western countries. The study design we used could be extended to other countries to see if the changes and the explanations for the possible changes are similar.