Media generations and their advertising attitudes and avoidance: a six-country comparison

Goot, M.J. van der; Rozendaal, Esther; Opree, Suzanna J.; Ketelaar, P.E.; Smit, Edith G.

doi:10.1080/02650487.2016.1240469

Cited by 51 publications

(40 citation statements)

References 39 publications

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“…In the present study, texting, emailing, social media and other internet use were more likely than TV/movies to compete with nonorganized PA across waves. This is consistent with the finding that younger generations use the internet more frequently and watch television less frequently than older generations [47]. Younger generations also have more positive attitudes toward internet advertising than older generations [47].…”

Section: Discussionsupporting

confidence: 90%

“…This is consistent with the finding that younger generations use the internet more frequently and watch television less frequently than older generations [47]. Younger generations also have more positive attitudes toward internet advertising than older generations [47]. This highlights the increasing importance of 'new media', both as a potential competing behavior of PA and as a potential communication channel.…”

Section: Discussionsupporting

confidence: 86%

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‘Social screens’ and ‘the mainstream’: longitudinal competitors of non-organized physical activity in the transition from childhood to adolescence

Kemp

Parrish

Cliff

2020

Int J Behav Nutr Phys Act

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Background: Physical activity (PA) tends to decline during late childhood and adolescence. In Australia, this decline has been shown to occur particularly in non-organized PA (e.g. active play and informal sport). Using a social marketing approach, segments of youth may be identified and targeted based on their profile of alternative activities that compete with non-organized PA during the transition to adolescence. The objectives of this study were to identify and describe segments of youth whose participation in non-organized PA declined between 11 and 13 years, based on changes in other potential competing activities during this period. Methods: Data were sourced from Waves 4 and 5 of the Longitudinal Study of Australian Children. Participation in non-organized PA and thirteen alternative activities (e.g. video games, homework, sleep) were measured using 24-h time-use diaries. Analyses were limited to participants whose non-organized PA had declined between 11 and 13 years (n = 1043). Two-stage cluster analysis was conducted and segments were described using chi-square and ttests. Results: Among the analytic sample, average non-organized PA participation declined by 87 min/day between 11y and 13y (p < 0.001). Two segments were identified (κ = 0.66). The 'Social Screens' segment (n = 143) had large increases in texting, emailing and social media use (+ 56 min/day, p < 0.001) and other internet use (+ 32 min/day, p < 0.001). Conversely, 'the Mainstream' segment (n = 900) had smaller increases in a wider range of activities, including other PA (organized PA, active transport, active chores/work) (+ 16.0 min/day, p < 0.001), homework/study (+ 9.5 min/day, p < 0.001) and electronic gaming (+ 6.7 min/day, p < 0.05). 'Social Screens' were more likely to attend public school, live in urban areas and have more advanced pubertal development (girls only). 'The Mainstream' were more likely to participate in PA and out-of-school activities. Conclusions: The 'Social Screens' segment had a much larger increase in texting, emailing, social media and other internet use, and lower participation in overall PA and out-of-school activities, compared with 'the Mainstream'. Future research may trial PA promotion strategies to replace benefits that this segment may seek in competing activities (e.g. social PA apps).

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 86%

‘Social screens’ and ‘the mainstream’: longitudinal competitors of non-organized physical activity in the transition from childhood to adolescence

Kemp

Parrish

Cliff

2020

Int J Behav Nutr Phys Act

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“…However, it seems reasonable to also consider other explanations -besides SST. An alternative explanation is the notion of media generations: Age groups also constitute different media generations that grew up with different media and thus differ in their attitudes toward those media [20]. The age difference in preference for human contact may be a reflection of the observation that the current younger generations are very familiar with communication through chat interfaces and consequently become more hesitant about talking to people on the phone (potentially experiencing phone anxiety).…”

Section: Age Differences In Motivationsmentioning

confidence: 99%

Exploring Age Differences in Motivations for and Acceptance of Chatbot Communication in a Customer Service Context

Goot¹,

Pilgrim²

2020

Lecture Notes in Computer Science

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This qualitative interview study explores age differences in perceptions of chatbot communication in a customer service context. Socioemotional selectivity theory and research into technology acceptance suggest that older adults may differ from younger adults in motivations to use chatbots, and in perceived complexity and security of this chatbot communication. The in-depth interviews with older adults (54-81 years; N = 7) and younger adults (19-30 years; N = 7) revealed that both groups were aligned in their prime motivation: They used chatbots to get their (simple) customer queries answered in a fast and convenient manner. However, they seemed to differ in their need for additional human contact. In both age groups, there were participants for whom it was easy to communicate with chatbots, and the two groups were united in their frustrations when the chatbot did not understand and answer their queries. They were aligned as well in the difficulty they experienced in assessing the security of the chatbot. The two age groups may differ in the factors that contribute to perceived ease of use and perceived security. Directions for future research and implications for the implementation of chatbots for customer service are discussed.

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“…One study conducted for different media platforms, spread across six different countries, over two continents and three generational cohorts revealed that different generational segments are attached to their traditional medium (van der Goot et al, 2018).…”

Section: Informativeness Entertainment Credibility and Irritationmentioning

confidence: 99%

Influencing Factors Affecting Young People’s Attitude Towards Online Advertising: A Systematic Literature Review

Battista

Curmi

Said

2021

IRMM

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Young people are constantly targeted by online advertisements. This systematic literature review aims to identify the principal factors that influence young people's attitude towards online advertising. It seeks to understand if the influence of online advertising is dependent on gender and age differences in young people. The methodology involves the systematic review of empirical studies published from 1994 to 2020 and identifies the factors that impact young people's attitude towards online advertising. The review commences with a scoping study and follows the PRISMA structure, which includes identifying studies, screening and evaluation, the analysis and synthesis of studies, and the presentation of the final studies. This work reveals two main observations from a thematic content analysis of the appraised studies. The first relates to the principal factors influencing young people's attitude towards advertising. These factors comprise informativeness, entertainment, irritation, credibility, personalisation, and interactivity. In general, studies show that when informativeness, entertainment, credibility and interactivity are present, the more positive the attitude towards advertising is, while irritation fosters an unfavourable attitude. Studies provide a dichotomous stand on personalisation. The second relates to young people's age and gender. Our review notes that earlier studies lack focus on audiences predominantly between 10 and 15 years.

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Media generations and their advertising attitudes and avoidance: a six-country comparison

Cited by 51 publications

References 39 publications

‘Social screens’ and ‘the mainstream’: longitudinal competitors of non-organized physical activity in the transition from childhood to adolescence

‘Social screens’ and ‘the mainstream’: longitudinal competitors of non-organized physical activity in the transition from childhood to adolescence

Exploring Age Differences in Motivations for and Acceptance of Chatbot Communication in a Customer Service Context

Influencing Factors Affecting Young People’s Attitude Towards Online Advertising: A Systematic Literature Review

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