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PurposeThe findings are based on experience at Aberystwyth Universities libraries using surveys and user experience (UX) activities to identify and understand user requirements.Design/methodology/approachThis paper was initially conceived and developed as a presentation for the LibPMC Conference in July 2023. It is included in this special conference issue for this conference.FindingsThere are challenges to successful integration of UX into user engagement processes across the library and IT services. To improve shared analysis and collaborative ideas generation we developed an interactive data dashboard.Originality/valueThe research is based on practical approaches to improving our understanding of student use and requirements at Aberystwyth University libraries. It explores mechanisms used to collect findings from all areas of UX, including library surveys, focus groups and UX activities to be able to analyse and share all student experience data – to be able to analyse themes and generate ideas and actions for development.

The mobility needs of society are constantly increasing, resulting in congested urban areas. New mobility concepts such as e-scooters can help to reduce traffic. In particular, commuting paths, which generally remain within a specific distance, are short and manageable via an intermodal travel chain. In combination with public transport, commuting paths could be beneficial. To evaluate the potential of e-scooters used with commuting paths, a literature research focusing on mobility behavior and characteristics was conducted. In addition, an end-user survey was used to identify the ecological and economical potential for typical work routes. The research results indicate that both the mobility preferences of the users, e.g., acceptance of intermodal travel, and the technical specification of e-scooters, e.g., speed and range, meet the needs of commuting. The assessment of typical work routes shows that the use of e-scooters for the first and last mile, in combination with public transport, is highly beneficial. Furthermore, e-scooters have the potential to provide individual advantages in the areas of travel time and costs. From an ecological perspective, CO2-equivalent emissions may also be reduced for some users depending on the substituted modes.

Background:The chronic nature of depression and limited availability of evidence-based treatments emphasize the need for complementary recovery-oriented services, such as peer support interventions (PSIs). Peer support is associated with positive effects on clinical and personal recovery from mental illness, but little is known about the processes of engagement that foster change, and studies targeting individuals with depression specifically are limited.Objective:This study aimed to evaluate whether the level of user engagement, assessed on several dimensions, in an online peer support community for individuals with depression promotes empowerment and the use of self-management strategies and reduces symptom severity and disability.Methods:In a longitudinal survey conducted from June 2019 to September 2020, we analyzed the data of the users of Depression Connect (DC), an online peer support community hosted by the Dutch Patient Association for Depression and the Pro Persona Mental Health Care institute, on measures of empowerment, self-management, depression, and disability. Of the 301 respondents, 49 (16.3%) respondents completed the survey again after 3 months and 74 (24.6%) respondents, after 6 months. Analysis of 3 parameters (ie, total time spent on the platform, number of page views, and number of posts) derived from their data logs yielded 4 engagement profiles. Linear mixed models were fitted to determine whether the outcomes had significantly changed over time and differed for the various profiles.Results:Baseline engagement with the online peer support community was “very low” (177/301, 58.8%) or “low” (87/301, 28.9%) for most of the participants, with few showing “medium” (30/301, 9.9%) or “high” engagement patterns (7/301, 2.3%), while user profiles did not differ in demographic and clinical characteristics. Empowerment, self-management, depressive symptoms, and disability improved over time, but none were associated with the intensity or nature of user engagement.Conclusions:With most DC members showing very low to low engagement and only a few being identified as high-engaged users, it is likely that this flexibility in use frequency is what provides value to online PSI users. In other more formal supportive environments for depression, a certain level of engagement is predetermined either by their organizational or by their societal context; at DC, users can adapt the intensity and nature of their engagement to their current needs on their personal road to recovery. This study added to the current knowledge base on user engagement for PSIs because previous studies targeting depression with an online format focused on active users, precluding passive and flexible engagement. Future studies should explore the content and quality of the interactions in online PSIs to identify optimal user engagement as a function of current, self-reported clinical parameters and reasons to engage in the PSI.

PurposeMedia reporting is one of many circumstances that nursing homes have to relate to, because of the reputational risks. The aim of this article is to investigate media representations of Swedish nursing homes in relation to reports on an annual national user survey.Design/methodology/approachThe empirical data consist of 381 Swedish newspaper articles about the survey results. The questions guiding the analysis were: what messages on nursing homes are communicated, and how are claims organized in order to appear factual?FindingsThe data show that press reports focus on comparisons of care units' survey results, eldercare representatives' explanations of the results, and what improvements will be made in order to do better in the next year's survey. With their use of truth-making rhetoric, press articles construct survey results as credible and valid, thus mirroring user perceptions and ultimately nursing home quality. The selection of nursing home representatives' comments equally reinforces the validity of claims.Originality/valueGiven nursing homes' problems with demonstrating success, the authors argue that media reports on the user survey is a way for eldercare organizations to achieve results in an otherwise resultless field, and while media reports might be seen as prompting change in nursing home care, what is ultimately achieved is the legitimation of a costly survey with low response rate.

Purpose With the development of the internet, huge numbers of reviews are generated, disseminated, and shared on e-commerce and social media websites by internet users. These reviews usually indicate users’ opinions about products or services directly, and are thus valuable for efficient marketing. The purpose of this paper is to mine online users’ attitudes from a huge pool of reviews via automatic question answering. Design/methodology/approach The authors make use of online reviews to complete an online investigation via automatic question answering (AQA). In the process of AQA, question generation and extraction of corresponding answers are conducted via sentiment computing. In order to verify the performance of AQA for online investigation, online reviews from a well-known travel website, namely Tuniu.com, are used as the experimental data set. Finally, the experimental results from AQA vs a traditional questionnaire are compared. Findings The experimental results show that results between the AQA-based automatic questionnaire and the traditional questionnaire are consistent. Hence, the AQA method is reliable in identifying users’ attitudes. Although this paper takes Chinese tourism reviews as the experimental data, the method is domain and language independent. Originality/value To the best of the authors’ knowledge, this is the first study to use the AQA method to mine users’ attitudes towards tourism services. Using online reviews may overcome problems with using traditional questionnaires, such as high costs and long cycle for questionnaire design and answering.

BackgroundBlack Africans (BA) are disproportionately affected by HIV in England, comprising 38% of heterosexuals diagnosed in 2017, 57% of whom were diagnosed late. Late diagnosis was even higher in BA men (69%).HIV self-testing is a preferred way to test among BA (Sigma, 2015). Despite increasing online availability of self-tests, Terrence Higgins Trust(THT) noted a lower uptake amongst BA than others. One reason provided includes a reluctance to receive kits in shared accommodation.With public funding, we added Click&Collect delivery to explore if this would help reduce HIV self-testing barriers.Methods20,000 self-tests offered online to key communities, including BA, from October–December 2018.Click&Collect option provided, with 4,000+ collection points. While open to all, enhanced promotion went to BA.Users were sent two follow-up SMSs requesting results. All those with a reactive result received THT support calls.A user survey assessed reasons for using the service.Results18,597 tests dispatched; 3,291 to BA.50% BA reported results, compared to 61% overall.Click&Collect uptake: 10% overall; 18% BA men.11 BA reported reactive results, one of whom used Click&Collect. The reactivity rate for BA was 0.7%. From the user survey:Over 48% of Click&Collect users stated primary reasons for choosing it were not wanting anyone they lived with accidentally opening package, or finding out they were taking an HIV test.50% of BA Click&Collect users chose self-test for confidentiality – compared to 34% of all other Click&Collect users, for whom it was not a top reason.ConclusionClick&Collect may address privacy/confidentiality issues for BA where this is a primary issue. The proportion of BA men using Click&Collect was higher than in other groups. As self-testing services increase, Click&Collect offers a way to increasing HIV testing uptake in a group highly affected by late diagnosis.DisclosureNo significant relationships.

Background Systematic reviews are vital to the pursuit of evidence-based medicine within healthcare. Screening titles and abstracts (T&Ab) for inclusion in a systematic review is an intensive, and often collaborative, step. The use of appropriate tools is therefore important. In this study, we identified and evaluated the usability of software tools that support T&Ab screening for systematic reviews within healthcare research. Methods We identified software tools using three search methods: a web-based search; a search of the online “systematic review toolbox”; and screening of references in existing literature. We included tools that were accessible and available for testing at the time of the study (December 2018), do not require specific computing infrastructure and provide basic screening functionality for systematic reviews. Key properties of each software tool were identified using a feature analysis adapted for this purpose. This analysis included a weighting developed by a group of medical researchers, therefore prioritising the most relevant features. The highest scoring tools from the feature analysis were then included in a user survey, in which we further investigated the suitability of the tools for supporting T&Ab screening amongst systematic reviewers working in medical research. Results Fifteen tools met our inclusion criteria. They vary significantly in relation to cost, scope and intended user community. Six of the identified tools (Abstrackr, Colandr, Covidence, DRAGON, EPPI-Reviewer and Rayyan) scored higher than 75% in the feature analysis and were included in the user survey. Of these, Covidence and Rayyan were the most popular with the survey respondents. Their usability scored highly across a range of metrics, with all surveyed researchers ( n  = 6) stating that they would be likely (or very likely) to use these tools in the future. Conclusions Based on this study, we would recommend Covidence and Rayyan to systematic reviewers looking for suitable and easy to use tools to support T&Ab screening within healthcare research. These two tools consistently demonstrated good alignment with user requirements. We acknowledge, however, the role of some of the other tools we considered in providing more specialist features that may be of great importance to many researchers.

PubMed is the most extensively used database and search engine in the biomedical and healthcare fields. However, users could experience several difficulties in acquiring their target papers facing massive numbers of search results, especially in their unfamiliar fields. Therefore, we developed a novel user interface for PubMed and conducted three steps of study: step A, a preliminary user survey with 76 medical experts regarding the current usability for the biomedical literature search task at PubMed; step B is implementing EEEvis, a novel interactive visual analytic system for the search task; step C, a randomized user study comparing PubMed and EEEvis. First, we conducted a Google survey of 76 medical experts regarding the unmet needs of PubMed and the user requirements for a novel search interface. According to the data of preliminary Google survey, we implemented a novel interactive visual analytic system for biomedical literature search. This EEEvis provides enhanced literature data analysis functions including (1) an overview of the bibliographic features including publication date, citation count, and impact factors, (2) an overview of the co-authorship network, and (3) interactive sorting, filtering, and highlighting. In the randomized user study of 24 medical experts, the search speed of EEEvis was not inferior to PubMed in the time to reach the first article (median difference 3 sec, 95% CI -2.1 to 8.5, P = 0.535) nor in the search completion time (median difference 8 sec, 95% CI -4.7 to 19.1, P = 0.771). However, 22 participants (91.7%) responded that they are willing to use EEEvis as their first choice for a biomedical literature search task, and 21 participants (87.5%) answered the bibliographic sorting and filtering functionalities of EEEvis as a major advantage. EEEvis could be a supplementary interface for PubMed that can enhance the user experience in the search for biomedical literature.

Plain Language Summaries (PLS) offer a promising solution to make meta-analytic psychological research more accessible for non-experts and laypeople. However, existing writing guidelines for this type of publication are seldom grounded in empirical studies. To address this and to test two versions of a new PLS guideline, we investigated the impact of PLSs of psychological meta-analyses on laypeoples’ PLS-related knowledge and their user experience (accessibility, understanding, empowerment). In a preregistered online-study, N = 2,041 German-speaking participants read two PLSs. We varied the inclusion of a disclaimer on PLS authorship, a statement on the causality of effects, additional information on community augmented meta-analyses (CAMA) and the PLS guideline version. Results partially confirmed our preregistered hypotheses: Participants answered knowledge items on CAMA more correctly when a PLS contained additional information on CAMA, and there were no user experience differences between the old and the new guideline versions. Unexpectedly, a priori hypotheses regarding improved knowledge via the use of a disclaimer and a causality statement were not confirmed. Reasons for this, as well as general aspects related to science communication via PLSs aimed at educating laypeople, are discussed.

In the current digital era, massive amounts of unreliable, purposefully misleading material, such as texts and images, are being shared widely on various web platforms to deceive the reader. Most of us use social media sites to exchange or obtain information. This opens a lot of space for false information, like fake news, rumors, etc., to spread that could harm a society’s social fabric, a person’s reputation, or the legitimacy of a whole country. Therefore, preventing the transmission of such dangerous material across platforms is a digital priority. However, the main goal of this survey paper is to thoroughly examine several current state-of-the-art research works on rumor control (detection and prevention) that use deep learning-based techniques and to identify major distinctions between these research efforts. The comparison results are intended to identify research gaps and challenges for rumor detection, tracking, and combating. This survey of the literature makes a significant contribution by highlighting several cutting-edge deep learning-based models for rumor detection in social media and critically evaluating their effectiveness on recently available standard datasets. Furthermore, to have a thorough grasp of rumor prevention to spread, we also looked into various pertinent approaches, including rumor veracity classification, stance classification, tracking, and combating. We also have created a summary of recent datasets with all the necessary information and analysis. Finally, as part of this survey, we have identified some of the potential research gaps and challenges that need to be addressed in order to develop early, effective methods of rumor control.