Identifying Language Features Associated With Needs of Ovarian Cancer Patients and Caregivers Using Social Media

Lee, Young Ji; Jang, Hyeju; Campbell, Grace; Carenini, Giuseppe; Thomas, Teresa Hagan; Donovan, Heidi S.

doi:10.1097/ncc.0000000000000928

Cited by 8 publications

(4 citation statements)

References 46 publications

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“…Fourth, these platforms provide cancer patients medical information allowing to reduce their distress (Bender et al, 2021). Fifth, using social media allows patients to share medical and personal information with their doctors and nurses (Lee et al, 2021). Sixth, thanks to social media, patients better understand hospitals' internal functioning, which helps them to participate in medical procedures in a more efficient way (Guan et al, 2021).…”

Section: Cancer Hospitals' Corporate Communication Strategiesmentioning

confidence: 99%

Promoting Health Brands through Social Media. A Quantitative Analysis about the World’s Best Cancer Hospitals

Medina-Aguerrebere

Medina

Pacanowski

2022

Communication & Society

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Cancer hospitals enforce different initiatives to accelerate digital transformation, such as mobile health or artificial intelligence. Nevertheless, some health professionals are not willing to adopt these technologies. In order to change some employees’ perspectives, these hospitals resort to social media platforms. This paper aims to evaluate how the worlds’ best cancer hospitals manage social media platforms, as well as their corporate website, with the aim of disseminating brand-related content and reinforce their reputation. Therefore, we reviewed literature on cancer hospitals’ corporate communication strategies, brand, social media platforms and online patient communities. We then resorted to 48 quantitative indicators to analyze how the 200 best cancer hospitals in the world managed Facebook, Twitter and YouTube, as well as their corporate website, for branding purposes. In order to identify the 200 best hospitals, we explored the World’s Best Specialized Hospitals 2021, an annual ranking published by Newsweek and Statista. The 48 indicators covered different elements concerning the hospitals’ identity and communication activities, as well as patient engagement on social media platforms. Our quantitative analysis proved that most cancer hospitals had a corporate website (70.5%) as well as a profile on Facebook (74%), Twitter (74.5%) and YouTube (67.5%). Nevertheless, most of them did not respect the 48 key performance indicators. Finally, we proposed three main conclusions: a) cancer hospitals should establish a Corporate Communication Department employing different experts in communication, health and big data; b) they should promote an integrated corporate communication approach; and c) they should implement brand ambassador programmes.

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Section: Cancer Hospitals' Corporate Communication Strategiesmentioning

confidence: 99%

Promoting Health Brands through Social Media. A Quantitative Analysis about the World’s Best Cancer Hospitals

Medina-Aguerrebere

Medina

Pacanowski

2022

Communication & Society

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“…We used logistic regression with bagof-word features for this task as it is a simple and interpretable classifier. Moreover, it has shown promising results in recent work on predicting patient needs from social media conversations, with limited training data [23,27]. We involved healthcare professionals and medical students for annotating 5K conversations to train the classifiers.…”

Section: Data Modelmentioning

confidence: 99%

ConVIScope: Visual Analytics for Exploring Patient Conversations

Li¹,

Hoque²,

Carenini³

et al. 2021

Preprint

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The proliferation of text messaging for mobile health is generating a large amount of patient-doctor conversations that can be extremely valuable to health care professionals. We present ConVIScope, a visual text analytic system that tightly integrates interactive visualization with natural language processing in analyzing patient-doctor conversations. ConVIScope was developed in collaboration with healthcare professionals following a user-centered iterative design. Case studies with six domain experts suggest the potential utility of ConVIScope and reveal lessons for further developments.

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“…Considering the massive number of online sources that may contain ADRD caregiving discussions, it is crucial for researchers to develop machine learning algorithms that can efficiently identify the relationship between caregivers and persons living with dementia based on their online posts, which will be a valuable social determinant that can be applied to online social support-based research. Various machine learning algorithms have been developed to extract relevant information from massive, noisy online data to facilitate biomedical research [ 36 ], including, but not limited to, predicting mental health status [ 37 ], disseminating study information during the COVID-19 pandemic [ 38 ], and learning the needs of patients with ovarian cancer and their caregivers [ 39 ]. However, most studies in the ADRD caregiving field have either identified online ADRD caregiving discussions [ 26 ] or summarized caregiving challenges [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

Examining Online Behaviors of Adult-Child and Spousal Caregivers for People Living With Alzheimer Disease or Related Dementias: Comparative Study in an Open Online Community

Ni,

Song,

Malin

et al. 2023

J Med Internet Res

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Background Alzheimer disease or related dementias (ADRD) are severe neurological disorders that impair the thinking and memory skills of older adults. Most persons living with dementia receive care at home from their family members or other unpaid informal caregivers; this results in significant mental, physical, and financial challenges for these caregivers. To combat these challenges, many informal ADRD caregivers seek social support in online environments. Although research examining online caregiving discussions is growing, few investigations have distinguished caregivers according to their kin relationships with persons living with dementias. Various studies have suggested that caregivers in different relationships experience distinct caregiving challenges and support needs. Objective This study aims to examine and compare the online behaviors of adult-child and spousal caregivers, the 2 largest groups of informal ADRD caregivers, in an open online community. Methods We collected posts from ALZConnected, an online community managed by the Alzheimer’s Association. To gain insights into online behaviors, we first applied structural topic modeling to identify topics and topic prevalence between adult-child and spousal caregivers. Next, we applied VADER (Valence Aware Dictionary for Sentiment Reasoning) and LIWC (Linguistic Inquiry and Word Count) to evaluate sentiment changes in the online posts over time for both types of caregivers. We further built machine learning models to distinguish the posts of each caregiver type and evaluated them in terms of precision, recall, F1-score, and area under the precision-recall curve. Finally, we applied the best prediction model to compare the temporal trend of relationship-predicting capacities in posts between the 2 types of caregivers. Results Our analysis showed that the number of posts from both types of caregivers followed a long-tailed distribution, indicating that most caregivers in this online community were infrequent users. In comparison with adult-child caregivers, spousal caregivers tended to be more active in the community, publishing more posts and engaging in discussions on a wider range of caregiving topics. Spousal caregivers also exhibited slower growth in positive emotional communication over time. The best machine learning model for predicting adult-child, spousal, or other caregivers achieved an area under the precision-recall curve of 81.3%. The subsequent trend analysis showed that it became more difficult to predict adult-child caregiver posts than spousal caregiver posts over time. This suggests that adult-child and spousal caregivers might gradually shift their discussions from questions that are more directly related to their own experiences and needs to questions that are more general and applicable to other types of caregivers. Conclusions Our findings suggest that it is important for researchers and community organizers to consider the heterogeneity of caregiving experiences and subsequent online behaviors among different types of caregivers when tailoring online peer support to meet the specific needs of each caregiver group.

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Identifying Language Features Associated With Needs of Ovarian Cancer Patients and Caregivers Using Social Media

Cited by 8 publications

References 46 publications

Promoting Health Brands through Social Media. A Quantitative Analysis about the World’s Best Cancer Hospitals

Promoting Health Brands through Social Media. A Quantitative Analysis about the World’s Best Cancer Hospitals

ConVIScope: Visual Analytics for Exploring Patient Conversations

Examining Online Behaviors of Adult-Child and Spousal Caregivers for People Living With Alzheimer Disease or Related Dementias: Comparative Study in an Open Online Community

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