Evidence map›Paper›PMID 41269096›Full record

ArticleThe Gerontologist2025

Campaigning an educational website on ageism: lessons from a failed attempt.

Liat Ayalon, Sarit Okun

Abstract read
In one paragraph

Article in The Gerontologist, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Liat AyalonLouis and Gabi Weisfeld School of Social Work, Bar Ilan University, Ramat Gan, Israel.ORCID 0000-0003-3339-7879
Sarit OkunLouis and Gabi Weisfeld School of Social Work, Bar Ilan University, Ramat Gan, Israel.

Funding

Impact Centre for the Study of Ageism and Older Age
6 · The paper itself

Abstract

BACKGROUND AND

objectivesAgeism, defined as stereotypes, prejudices, and discrimination based on age, significantly impacts the health and well-being of older persons. It also has tremendous financial and social impacts on society at large. In response, this study evaluates a digital marketing campaign aimed at raising awareness of ageism through an educational website, "A site for all ages" (no2ageism.com). RESEARCH DESIGN AND

methodsThe researchers implemented a mixed-methods approach: Study 1 utilized an online experiment to measure ad effectiveness (positive vs negative age messages) in attracting website traffic; Study 2 surveyed website visitors' perceptions of the ads; and Study 3, which was added due to the low response rate to Study 2, relied on an online survey to assess perceptions of the ads. Data were analyzed using descriptive statistics and thematic analysis.

resultsFollowing the introduction of paid ads, Study 1 showed an increase in website traffic, but not in engagement, with a moderate preference for the positive ad. Study 2 revealed that curiosity was the main drive behind clicking ads, while Study 3 demonstrated that older individuals, women, and those with higher educational level, preferred the positive ad highlighting inclusivity in their message. DISCUSSION AND IMPLICATIONS: This study resulted in successful traffic generation, although engagement with the website was limited, when ads were used. The limited engagement with the website, despite an increase in traffic, represents a failure given the tremendous efforts put into featuring an interactive, engaging website. Lessons learned can improve campaign design and implementation.

Indexed as

AdvertisingAgeismInternetAdultAgedFemaleHumansMaleMiddle AgedSurveys and QuestionnairesAdvertisementAgeismOlder adultsSocial campaignsSocial media

Identifiers

PMID41269096
PMCPMC12715309

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.