Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling

There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community.


| INTRODUCTION
Over the past few decades, the availability of cochlear implant (CI) surgery has increased exponentially. 1 Despite this, the relative uptake of CIs among patients eligible for surgery remains poor, with rates of utilisation/provision as low as 6% in the United States and considerable disparity in uptake among different age groups. 2,3 Much of the current literature on cochlear implantation has focused on evaluating pre-defined health-related outcomes, such as communication/hearing scores and Quality of Life metrics. 4 In contrast, there is a paucity of research examining patient experiences of CIs, with survey-based studies often limited by small sample sizes of under 100 participants. [5][6][7] These studies may be poorly representative of the CI community, while their findings may be further constrained by the closed question-answer style format and limited analysis of patient concerns. To overcome these issues, it may be useful to explore non-traditional methods of evaluating the experiences and concerns of CI users, their families and other stakeholders.
Health researchers are increasingly utilising social media as a resource to generate data-driven insights. 8  There are several active online CI communities on different social media platforms, where CI users and individuals interested in CIs can access and share information. 11 Among these is the CI community that can be found on the online forum Reddit, a platform where people may anonymously converse by posting in community-based subforums known as subreddits. The CI subreddit, 'r/CochlearImplants,' currently has over 2400 members. 12 Although Reddit is increasingly recognised as a valuable source of data in many other medical specialties, 13 r/CochlearImplants has not been examined thus far. An exploration of this subreddit, to identify common questions posed by prospective CI users, would allow clinicians to provide more detailed information to those wishing to consider implantation. Most importantly, understanding the experiences of existing and prospective CI users voiced in 'non-clinician' controlled spaces may also give a different and perhaps more valid representation of their concerns, fears and what is valued compared to issues raised in clinician-user interactions.
In parallel to the emergence of social media as a resource for health research is the growing emphasis on using automated methods to analyse the potentially large volumes of data available. The field of natural language processing offers techniques to analyse text at scale, requiring considerably fewer resources compared to manual qualitative approaches. 14 Topic modelling, where probabilistic algorithms are used to extract popular topics from a collection of documents, is one of these techniques and has been applied to a variety of bioinformatics tasks. 15 However, the use of topic modelling techniques in Ear, Nose and Throat-related research is rare, and there is limited manual evaluation of the accuracy of automatically generated topics. 16,17

| Objectives
The aims of the present study were twofold. First, we sought to examine posts from the r/CochlearImplants Reddit forum to determine what were the most popular topics discussed by users. Second, we sought to investigate the utility of a state-of-the-art automated topic modelling technique applied to our dataset and assess its suitability for automated topic analysis in future Otolaryngology-related research.

| Data collection
We used the Pushshift Multithread API Wrapper (PMAW) 18 to access the Reddit API and extract all posts from the r/CochlearImplants subreddit forum. 12 Reddit was selected as the social media site for analysis due to its open accessibility and structured subreddit format.
Ethical approval was not required as all data is in the public domain.
Created on 1 March 2015, r/CochlearImplants is a self-described 'subreddit for cochlear implant users to share their stories, maintenance tips, advice, and have a general discussion about cochlear implants', 12 consisting of 2400 members. Data were retrieved on 11 November 2021. No date restrictions were imposed. The following

Key Points
• There is limited research examining patient experiences of cochlear implants (CI).
• We conducted a cross-sectional study of the online Reddit r/CochlearImplants forum using natural language processing.
• We retrieved 987 posts which were categorised into 23 separate topics; Cohen's kappa was similar between human-human and human-machine categorisation.
• The most popular topics related to CI connectivity, adults considering getting a CI, surgery-related posts and dayto-day living with a CI.
• Our validation of natural language processing methods shows that automated analysis of similar otolaryngologyrelated content is a viable and accurate alternative to manual qualitative approaches.
T A B L E 1 Overview of topics from the r/CochlearImplants Reddit forum, ordered by prevalence.  and '\n' (denoting a new line) was removed.

| Topic modelling
We used a natural language processing approach to initially cluster Reddit posts (herein termed documents) into appropriate topic categories. Topics were identified using BERTopic, a topic modelling technique that utilises a Transformer model alongside a Class-based Term Frequency-Inverse Document Frequency (c-TF-IDF) procedure to cluster topics. 19 Full details on the BERTopic algorithm are provided in Appendix S1.
After applying the BERTopic algorithm to our dataset, the topics generated were inspected to confirm semantic similarity between documents. Overarching topic headings were then identified using a combination of the keywords extracted by BERTopic and manual identification of common themes. To verify the accurate classification of documents into each topic, two co-authors (CW and RL) manually and independently reviewed each document within a topic. Any documents deemed a poor fit with the given topic were identified and assigned to either a more appropriate topic or the uncategorised group. Disagreements between reviewers were resolved by consensus. The uncategorised group was subsequently inspected in duplicate and posts were manually assigned to either a new topic, an existing topic, or left as uncategorised. A summary of the initial clustering of documents into topics by BERTopic, and final topic categorisations, can be found in Table S1.

| Ethical considerations
This study was deemed exempt from ethical approval as all data is freely available in the public domain.

| Reporting guideline
The manuscript was prepared in accordance with the STROBE reporting guidelines for cross-sectional studies (Appendix S2).

| RESULTS
We extracted 1061 Reddit posts from the r/CochlearImplants forum.
Among these, 74 were found to have been censored or removed by  (Table 1). An overview of the original (i.e. BERTopic output) and final (human-modified) classification of Topics is shown in Figure 1.

| Common themes
The evolution of topic popularity over time is shown in Figure 2. The most popular topics related to CI connectivity (Topic 1, n = 112), adults considering getting a CI (Topic 2, n = 107), surgery-related   Table S1. posts (Topic 3, n = 89) and day-to-day living with a CI (Topic 4, n = 85) ( Table 1). CI connectivity posts (Topic 1) commonly mentioned questions about connecting to other devices or related to digital CI accessories such as smart watches, baby monitors and phone clips.

Surgery-related posts (Topic 3) typically sought advice on what to
expect from the surgery, common side effects, and how best to prepare for recovery post-op. Among the posts discussing day-to-day living with a CI, the issues raised varied greatly and included questions on which sports CI users can play and whether certain environments or appliances are safe, alongside complaints about difficulty wearing headgear with a CI and from users wishing to prevent their CI from falling off.
Two distinct groups of posts emerged among users broadly discussing whether to get a CI. A larger group (Topic 2, n = 107) consisted of adults considering getting a CI and looking for more information about it. While not all posts in this group mentioned the user's age, those which did were predominantly middle to older age individuals who were considering getting a CI later in life. This contrasts a second group (Topic 6, n = 73) of posts which related to supporting someone else and considering them for a CI. Here, often a family member was seeking advice when supporting a young son/daughter who is being considered for a CI. A third group also consisted of posts gathering information about CIs (Topic 7, n = 64), but these requests were for general interest or academic projects rather than people wishing to explore getting a CI. The remaining topics covered a broad range of CI-related content.
These include sharing links to videos (n = 45), sharing other CI forums (n = 26), discussing miscellaneous symptoms (n = 16), external appearances and attitudes towards CIs (n = 15), CI mappings (n = 10) and CI-related movies (n = 4).  F I G U R E 2 Evolution of topic popularity among r/CochlearImplants posts over time.

| Limitations
Our study has several limitations. It is difficult to establish how representative Reddit is in relation to the cochlear implant community as a whole. It is possible that some prospective/actual CI users either do not have access to Reddit and other social media forums or choose not to engage with other CI users online. However, a previous study has confirmed that a strong presence of CI users exists online from a variety of social media sources. 11 Due to the pseudonymous nature of Reddit, we also could not obtain detailed demographic information about the age, gender or ethnicities of users posting about a particular topic. Future research must consider differences among minority groups to ensure that patient experiences and concerns are equitably identified across the population.

| CONCLUSION
To our knowledge, this is the first study to explore the content of social media discussions among the online cochlear implant community. Analysis of social media posts allowed us to identify common attitudes, experiences and concerns among patients either living with, or seeking, a cochlear implant. Importantly, these perspectives may not otherwise have been expressed during a patient's interactions with their otolaryngologist, or captured by researchers using existing survey-based techniques. Our validation of natural language processing methods to categorise topics in this setting further shows that automated analysis of similar otolaryngology-related content is a viable and accurate alternative to manual qualitative approaches.

AUTHOR CONTRIBUTIONS
Christopher Y. K. Williams designed the work; Christopher Y. K. Williams and Rosia X. Li acquired and analysed data; all authors drafted, revised and approved the manuscript, and agree to be accountable for all aspects of the work.