A survey of video game preferences in adults: Building better games for older adults

Highlights

• Games should be easy to learn & play, while still being challenging.

• Having variety & being easy to hop in and out of are also important game features.

• Puzzle and strategy games are the most commonly played game genre.

• Most games are still played alone (especially those played by older adults).

• After television, the desktop computer is the most commonly used device.

Abstract

As the average North American gets older, there is an increasing need to develop better rehabilitation and wellness software for the aging. Although the use of computerized entertainment is becoming more prevalent with older adults, knowledge of their preferences and usage habits is still limited. In order to understand how preferences might change over a lifespan, we conducted a survey of older and younger adults (N = 426). The goal of this analysis was to determine in what ways the electronic preferences and activities of older adults differed from younger cohorts. Our results showed that older adult respondents generally indicated a preference for games that were easy to learn and play, but also challenging, with puzzle & strategy games being the most popular. Older adults also indicated that they played games alone rather than with friends. Finally, although younger adults used a wider variety of electronic devices, most older adults reported regularly using at least one device capable of accessing video games such as a desktop computer. These results broaden our knowledge of older adults’ preferences and usage patterns for computerized entertainment, as compared to a younger cohort. These survey results can serve as a resource for game designers.

Introduction

Despite a growing interest in the topic, research investigating the computer and video game preferences of older adults is still lacking. Although video game playing is typically associated with younger audiences, several studies are beginning to tap into its therapeutic potential by designing and seeking to validate gaming interventions. Gaming interventions have included those tailored to minimize age-related decline in cognition (e.g., [1]; and see Hertzog et al. [2] for a monograph on the subject), minimize decline in mobility (e.g., [3]; for a review, see Brox et al. [4]), and provide rehabilitation to patient populations experiencing a loss or decrease of function, such as after a stroke [5] or Parkinson’s disease [6]. Improving or maintaining daily functioning is a highly tangible concept that appeals to a large demographic that includes the aging baby boomer population, which constitutes the largest age cohort in Canada [7], [8] and one of the largest in the United States [9]. This demand is increasing as the number of older adults continues to reach an unprecedented level. This is not unique to Canada and the USA; as the United Nation’s Department of Economic and Social Affairs [10] reports, the trend is being mirrored globally. Thus, there remains a huge need for effective and fun interventions that can combat many of the side effects of aging, including cognitive decline.

The economic impact of cognitive decline and dementia become more evident as the global population ages (e.g., [11]), and the benefits of potential successful cognitive training extend beyond individual gain. Lengthening the duration of seniors’ independence promises to reduce healthcare costs (e.g., [2]). Furthermore, the timely targeting of individual cognitive interventions can also lead to lower healthcare costs. For example, Reeder et al. [12] showed that an intervention targeting executive functioning in persons with schizophrenia could reduce their disability and resultant health and social care costs. In another example, a preliminary investigation by Pressler et al. [13] showed that there may be a basis for cognitive training administered to patients with heart failure, a condition which can have adverse effects on aspects of cognition relevant to everyday functioning and compliance with treatment regimens. Even precursor symptoms of more high profile conditions can put a strain on healthcare; as a case in point, Ryan et al. [14] found that mild cognitive impairment placed the same level of demand on healthcare providers as Alzheimer’s disease, a condition which it often foreshadows. These studies, from a still young field of research, demonstrate the potential benefits which may arise from interventions that can ameliorate cognitive decline.

However, there is still much debate within the field about the strength of the evidence for beneficial effects of ‘brain-training’. For example, the Standford Centre for Longevity and the Max Planck Institute for Human Development issued a statement signed by over 70 scientists stating that “continued careful research” is needed but there is currently “no compelling scientific evidence” to date that “brain games” can “reduce or reverse cognitive decline” [14]. This controversial statement lead to an Open Letter response [15] signed by 127 scientists saying that they strongly disagreed that the assertion that the former statement represented a true scientific consensus, and that they could not agree with the statement that there was “no compelling evidence” in this field. In this Open Letter response, they go on to say that there is in fact a “substantial and growing body of evidence that shows that certain cognitive training regimens can significantly improve cognitive function, including ways that generalize to everyday life” [15]. These arguments have been summarized and evaluated in a recent review of evidence found on company websites by Simons et al. [15], who conclude that while brain-training clearly results in improvement on trained and related tasks, there is still an important need for more research to establish whether there is an actual benefit to everyday function. These conclusions are consistent with a recent, more comprehensive systematic review by Lampit et al. [16], who reported significant effects of cognitive training in healthy older adults, but importantly, these effects are moderated by type of cognitive training and targeted domain, and training factors such as supervision, length and frequency of training.

In addition, the success of any intervention will depend on an individual’s adherence to the program, which is often predicted by how “fun” the intervention is (see [17]). “Gamifying” interventions, or designing interventions that feel more like playing a game, may have more success due to faster rates of adoption and fewer issues with attrition. Indeed, some companies have tried to directly build and mass-market games they claim to improve cognitive functioning (reviewed in Simons et al. [15]). The lack of strong evidence for health care benefits has been highlighted by the recent charge of deceptive advertising by the American Federal Trade Commission [18] directed at Lumosity, a web-based platform of mini-games. The company agreed to pay $2 million to settle the FTC deceptive charge as a part of a $50 million judgment [18], underscoring the danger of over-stating the benefits of your product when the scientific proof is not compelling.

Despite the current limitations of available research, research teams around the world have begun to recognize both the potential of digital games and the challenge of designing games specifically for older adults, given the typical changes in sensori-motor and cognitive function with aging (for a comprehensive review of technology design needs for older adults, see [19]). For example, a European research group has compiled a list of design recommendations for games aimed at older adults, accounting for age-related cognitive changes in perception, attention, learning, and activities of daily living [20]. Recommendations include enhanced colour and luminance contrast on screens, and reducing words-per-minute and background noise. Gamberini et al. [20] also recommend minimizing the number of steps necessary to complete in-game tasks, and creating and emphasizing error messages and help materials. Gerling et al. [21] suggest that, to reduce memory demands on older adults, game designers should simplify rules and physical operations necessary for gameplay (such as button-press sequences on a console). In a study by Aison et al. [22], difficulty of using controls and joysticks was the most common factor cited by a group of older adults as detracting from game enjoyment. In accordance with this, Pham and Theng [23] found that older adults completed a game faster when using a mixed-input game console that required a single button and a single gesture, as compared to consoles that required learning multiple button or gesture sequences.

In addition to issues of usability, age differences in motivation to play games must be considered. Game-based learning is less familiar to older adults than it is to younger generations, and games may not be immediately regarded as effective learning tools without further education about their potential benefits [24]. It should also be emphasized that whether or not older adults choose to engage with technology may be dependent upon their assessment of its relevance and advantages. Games for older adults must not focus on usability at the expense of interest and intrigue, or they will not confer enough advantages to be used at all [25]. Although older adults have not yet been highly targeted as a gaming demographic, De Schutter and Malliet [26] have developed a preliminary taxonomy of older adults’ motivations to play games. Primary categories were context (playing to pass the time, to substitute for activities the player is unable to access, or to avoid doing less desirable activities), and content (learning from games, enjoyment of gameplay). However, more investigation is needed to compare the needs and desires of different age demographics, and to determine the extent to which aspects of game design may be generalized across populations.

Additionally, researchers have begun to frame engagement in the context of flow, a concept originally outlined by Csikszentmihalyi [27], with the idea of using it as a measure of participants’ holistic engagement during training (e.g., [28]). Flow is attained through the performance of a task whose difficulty lies at the edge of one’s abilities, such that it feels accomplishable but still highly fulfilling [28], [29]. For a game to lead to a state of flow, it must be appropriate to an individual’s perceptual and cognitive capabilities, while also being captivating and challenging enough to engage them. In accordance with this, Aison et al. [22] found that the most common factor cited as contributing to enjoyment of video games by a group of older adults was the challenge of the game, followed by involvement in the game, and then by the social interaction of playing with others.

While all of the aforementioned literature carries substantial implications for informing game design and inferring the habits of game players, little is known about the specifics of older adults’ gaming preferences, particularly those in the 65+ age demographic [25]. The information we do have typically comes from a small subsection of work, for example, the Pew Research Internet Project [30] and the frequent Entertainment Software Agency surveys (e.g. [31]). Both provide general descriptive statistics about their surveyed populations’ hardware and software preferences, and briefly examine respondents’ motivations to play (e.g., for parent/child interaction), but do not contain a lot of information about older adults, specifically. According to Charlier et al. [24], older adults displayed a preference for puzzle games above all other genres. A 2005 BBC UK survey also found a large preference for puzzle, board, and quiz games in adults aged 51–65 [32], while the most common suggestion for game designers from a group of older adults as reported in Aison et al. [22] was sports-focused games. Another recent survey of seniors in Florida by Blocker et al. [33] reported a preference for puzzle and educational games, as well as a lack of preference for fantasy themes in seniors.

In terms of the social value of gaming, De Schutter and Vandenabeele [34] reported that most older adults stressed social connectedness as an important game factor. However, some older adults have negative attitudes toward online multiplayer gaming [33], [35] and report less enjoyment of it compared to young adults [36]. In-person multiplayer gaming may be better received [35], [36] with Gajadhar et al. [36] finding that older adults enjoyed playing with a co-located player.

The available information could be supplemented, particularly to better dissociate the preferences and attitudes of adults of various ages and examine data from different populations.

Therefore, we conducted a more detailed exploratory survey on computerized entertainment preferences across three age demographics, which will hopefully enable the development of therapeutic games that best appeal to the aging population, and by consequently improving intervention attrition and engagement, improve the efficacy of such programs to alleviate some of the strain on healthcare resources.

Although our survey explored many facets of leisure activity preferences, the goal of this paper was to address four large-scale themes; (1) the features that participants look for in a video game, (2) the types of games that they play, (3) who they play games with, and (4) the devices and hardware they use.

Given the value that interventions can play in older populations, and the importance of maximizing adherence to these programs by making them “fun” and game-like, it was important to identify what features and genres of games older adults cared the most about, as well as what types of games they were already playing. Knowing with whom older adults typically played games with would also help in designing multiplayer games that are engaging for older adults and their co-players. Finally, asking which devices older adults typically used would allow for the development of games designed to run on the hardware that older adults are already comfortable using.

The questionnaire was administered to all self-identifying “healthy” adults over the age of 19, but given our research teams’ interest in the possibility of developing game interventions for older adults our analyses and discussion of the data focuses on the way older adults are different from their younger cohorts. That said, the figures are presented in a way that responses from all age demographics are represented, and these results could be of value to those interested in the responses of younger adult gamers as well.