Researchers have long used content analysis techniques to document the frequency of stereotypical representations in the media, but the interest in studying ageism in the media is relatively recent. We approach older people’s representation in the media by considering visual aspects—depictions in visual documents, such as photos and video materials—with a focus on television programs and print and television advertisements. We introduce the concept of “visual ageism”: the social practice of visually underrepresenting older people or misrepresenting them in a prejudiced way. According to previous studies, over time, media representations of older people have moved from visual under- and misrepresentation (negative images) to more positive depictions. Our review of empirical studies conducted since 1950 in Europe and North America reveals that print and television advertisements started the transition towards a more positive visual representation of older people during the last decade of the twentieth century; followed by television programs some years later. This is probably due to the increase in third age rhetoric in the media, picturing younger-old adults as healthy and as potential consumers. Our analysis also shows that the older-old (fourth age) group continues to be underrepresented in the visual media. Finally, we suggest ways of reducing visual ageism by adopting a design for dynamic diversity approach.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

The main purpose of this paper is to review the benefits and factors to be taken into consideration for the design of intergenerational digital games. We conducted a systematic in Scopus, Web of Science, PsicInfo, Pubmed and Science Direct, finally including 16 empirical studies written in English. The identified benefits were found to fall into four main categories, i.e., (1) reinforcing family bond, (2) enhancing reciprocal learning (3) increasing understanding of the other generation and (4) reducing social anxiety. According to the literature, two types of factors are important to take into consideration: player-centric and game-centric factors. We identified the nature of the interactions between older (55–81 year-olds) and younger players (4–22 year-olds), their motivations to play digital games and the difference in abilities as the main player-centric factors to take into account when designing intergenerational games. The most relevant game-centric factors were found to be goal-related and space-related forms of interaction. To gain more insight into how specific benefits of playing digital games are related to a type of game, gender or age of the participant, additional empirical studies (comparative analyses), that take these factors into account are needed.

Introduction: One-day fast track programs for cancer diagnostics and treatment planning are increasingly being implemented in health care. Fast-track programs are highly effective at reducing waiting times, and thus well received by patients and healthcare providers. However, these programs may also burden patients, as patients generally receive a lot of information from multiple healthcare providers within a short time span. This might increase anxiety and negatively impact recall of medical information in newly diagnosed patients. This study examines whether anxiety influences information recall at the moment of diagnosis, and whether this relation differs for younger and older patients. Methods: Data were collected from 78 colorectal cancer patients visiting a one-day fast-track multidisciplinary outpatient clinic. All consultations that took place were recorded on a video. Anxiety was measured at baseline (T1) and immediately after consultations (T2) with the STAI-6. Information recall was assessed by telephone within 36–48 hours after patients’ visit (T3) using open questions. Results: After consultations (T2), 32% of patients experienced clinical anxiety levels. Patients recalled ∼60% of medical information (T3). Information recall was negatively impacted by anxiety (β = –.28, p = .011), and negatively related to higher age (β = –.23, p = .031), and lower education level (β = .27, p = .013). Although older patients (M = 53.99) recalled 11% less information than younger patients (M = 64.84), age was not related to anxiety and did not moderate the anxiety-recall relationship. Conclusion: High levels of anxiety after receiving a cancer diagnosis negatively influence how much information patients remember after visiting a one-day fast-track clinic. This calls for interventions that may reduce patients’ anxiety as much as reasonably possible and support patients’ information recall. Researchers, practitioners, and hospitals are encouraged to continue exploring ways to optimize information provision to cancer patients in current modern healthcare.

ChatGPT is a fascinating AI text generator tool. It is a language model developed by OpenAI, a research and deployment company with the mission, according to OpenAI’s website: “to ensure that artificial general intelligence benefits all of humanity”. ChatGPT is able to generate human-like texts. But how does it work? What about the quality of the texts it provides? And is it capable of being self-reflective? Information sources must be efficient, effective and reliable in education, in order to enhance students’ learning process. For this reason, we started a dialogue with ChatGPT-3 while using, among others, a SWOT analysis it generated about its own functioning in an educational setting. This enabled us, as human authors, to analyze the extent to which this AI system is able to practice self-reflection. Finally, the paper sketches implications for education and future research.

This article investigates the changes in the use of traditional and new media by different technology generations. Focusing on the changes in the use of Email, Chat and Social Network Sites by older people, it explores the process by which new media become ‘old’ and reach a saturation point. Collected survey data suggest differences in media use between the three technology generations distinguished in this study: the ‘mechanical’ generation (born in 1938 or before), the ‘household revolution’ generation (born between 1939 and 1948), and the ‘technology spread’ generation (born between 1949 and 1963). This longitudinal and transnational study provides evidence of media saturation, showing that an increase in both the availability of and access to media does not lead to an increase in use, even in older adults who are behind in the adoption of the new media. Finally, the article discusses the findings, arguing for an interplay between individual and structural lag in later life.