JMIR Cancer最新文献

Background: Given the increasing number of cancer survivors and their rising survival rates, rehabilitation plays an increasingly important role. Social support among patients is an essential element of inpatient and day care rehabilitation. The internet can empower patients with cancer to become more active health care consumers and facilitate information and supportive care needs. By contrast, therapists suspect that high internet use during rehabilitation may severely limit social interactions between patients, thus interfering with the patients' rehabilitation program and jeopardizing treatment success.

Objective: We hypothesized that the extent of internet use would be negatively related to social support among patients with cancer during their clinical stay as well as fewer improvements in patient-reported treatment outcomes from the first to the last day of their clinical stay.

Methods: Patients with cancer participated during their inpatient rehabilitation. Cross-sectional data, such as the extent of participants' internet use and perceived social support among patients, were collected during the last week of their clinic stay. The treatment outcomes, that is, participants' levels of distress, fatigue, and pain, were collected on the first and last day of the clinic stay. We used multiple linear regression analysis to study the association between the extent of internet use and social support among patients with cancer. We used linear mixed model analyses to study the association between the extent of internet use by patients with cancer and the change in patient-reported treatment outcomes.

Results: Of the 323 participants, 279 (86.4%) participants reported that they used the internet. The extent of the internet use (t₃₁₅=0.78; P=.43) was not significantly associated with the perceived social support among the participants during their clinical stay. In addition, the extent of participants' internet use during their clinical stay was not associated with changes in participants' levels of distress (F_1,299=0.12; P=.73), fatigue (F_1,299=0.19; P=.67), and pain (F_1,303=0.92; P=.34) from the first to the last day of their clinical stay.

Conclusions: The extent of internet use does not seem to be negatively associated with the perceived social support among patients with cancer or with the change in patients' levels of distress, fatigue, or pain from the first to the last day of their clinical stay.

Background: The internet is an important source of information for many informal caregivers and patients living with cancer. A better understanding of how individuals use the internet to meet their informational needs is important for guiding intervention development.

Objective: The objectives of this study were to develop a theory describing why individuals living with cancer use the internet to find information, characterize the challenges faced with existing web-based content, and provide recommendations for web-based content design.

Methods: Adults (≥18 years) with a history of being patients with cancer or informal caregivers were recruited from Alberta, Canada. After providing informed consent, participants were engaged through digitally recorded one-on-one semistructured interviews, focus groups, a web-based discussion board, and emails. Classic grounded theory guided the study procedures.

Results: A total of 21 participants took part in 23 one-on-one interviews and 5 focus groups. The mean age was 53 (SD 15.3) years. Breast, gynecological, and hematological cancers were the most common cancer types (4/21, 19% each). In total, 67% (14/21) of patients, 29% (6/21) of informal caregivers, and 5% (1/21) of individuals reporting both roles participated. Participants experienced many new challenges in their cancer journey and used the internet to become better oriented to them. For each challenge, internet searching attempted to address one or more of 3 key orientation questions: why the challenge was happening, what to expect, and options for managing it. Better orientation resulted in improved physical and psychosocial well-being. Content that was well laid out, concise, free of distractions, and that addressed the key orientation questions was identified as the most helpful in assisting with orientation. Creators of web-based content are encouraged to 1) clearly identify the cancer challenge and population the content is addressing, as well as the presence of any potentially distressing information; 2) provide versions of the content in different formats, including printer-friendly, audio, video, and alternative languages; 3) state who created the content, including the individuals, organizations, and processes involved; 4) place hyperlinks after the key orientation questions have been addressed; and 5) ensure that the content is optimized for discovery by search engines (ie, Google).

Conclusions: Web-based content plays an essential role for many living with cancer. Clinicians are encouraged to take active steps to help patients and informal caregivers find web-based content that meets their informational needs. Content creators also have a responsibility to ensure that the content they create assists and does not hinder those navigating the cancer journey. Research is needed to better understand the many challenges that individual

Background: While online portals may be helpful to engage patients in shared decision-making at the time of cancer screening, because of known disparities in patient portal use, sole reliance on portals to support cancer screening decision-making could exacerbate well-known disparities in this health care area. Innovative approaches are needed to engage patients in health care decision-making and to support equitable shared decision-making.

Objective: We assessed the acceptability of text messages to engage sociodemographically diverse individuals in colorectal cancer (CRC) screening decisions and support shared decision-making in practice.

Methods: We developed a brief text message program offering educational information consisting of components of shared decision-making regarding CRC screening (eg, for whom screening is recommended, screening test options, and pros/cons of options). The program and postprogram survey were offered to members of an online panel. The outcome of interest was program acceptability measured by observed program engagement, participant-reported acceptability, and willingness to use similar programs (behavioral intent). We evaluated acceptability among historically marginalized categories of people defined by income, literacy, and race.

Results: Of the 289 participants, 115 reported having a low income, 146 were Black/African American, and 102 had less than extreme confidence in their health literacy. With one exception, we found equal or greater acceptability, regardless of measure, within each of the marginalized categories of people compared to their counterparts. The exception was that participants reporting an income below US $50,000 were less likely to engage with sufficient content of the program to learn that there was a choice among different CRC screening tests (difference -10.4%, 95% CI -20.1 to -0.8). Of note, Black/African American participants reported being more likely to sign up to receive text messages from their doctor's office compared to white participants (difference 18.7%, 95% CI 7.0-30.3).

Conclusions: Study findings demonstrate general acceptance of text messages to inform and support CRC screening shared decision-making.

Background: Adult patients with acute lymphoblastic leukemia (ALL) report substantial disease- and treatment-related impacts on their health-related quality of life (HRQOL). Patient-reported information (PRI) shared on social media may provide a distinct opportunity to understand the patient experience outside of formal research contexts and help inform the development of novel therapies.

Objective: This qualitative social media review aimed to assess PRI shared on social media websites to gain a better understanding of the symptom, HRQOL, and treatment impacts on individuals with ALL.

Methods: We identified English-language posts on 3 patient advocacy websites (Patient Power, The Patient Story, and Leukaemia Care) and YouTube that included PRI about experiences with ALL or ALL treatments shared by adults (aged ≥18 years) with a self-reported ALL diagnosis. Patients' demographic and disease characteristics were extracted from posts (where available), and the posts were analyzed thematically. A network analysis was conducted to delineate possible associations among ALL symptoms, HRQOL impacts, and treatment-related symptoms and impacts.

Results: Of the 935 social media posts identified, 63 (7%) met the review criteria, including 40 (63%) videos, 5 (8%) comments posted in response to videos, and 18 (29%) blog posts. The 63 posts were contributed by 41 patients comprised of 21 (51%) males, 18 females (44%), and 2 (5%) whose gender was not reported. Among the patients, 13 (32%) contributed >1 source of data. Fatigue (n=20, 49%), shortness of breath (n=13, 32%), and bruising (n=12, 29%) were the symptoms prior to treatment most frequently discussed by patients. Patients also reported impacts on personal relationships (n=26, 63%), psychological and emotional well-being (n=25, 61%), and work (n=16, 39%). Although inpatient treatment reportedly restricted patients' independence and social functioning, it also provided a few patients with a sense of safety. Patients frequently relied on their doctors to drive their treatment decisions but were also influenced by family members. The network analysis indicated that disease-related symptoms were primarily associated with patients' physical functioning, activities of daily living, and ability to work, while treatment-related symptoms were primarily associated with emotional well-being.

Conclusions: This social media review explored PRI through a thematic analysis of patient-contributed content on patient advocacy websites and YouTube to identify and contextualize emergent themes in patient experiences with ALL and its treatments. To our knowledge, this is the first study to leverage this novel tool to generate new insights into patients' experiences with ALL. Patients' social media posts suggest that inpatient care for ALL is associated with restricted independence and social functioning. However, i

Background: Cancer is increasingly being treated as a chronic disease rather than an acute one-time illness. Additionally, oral anticancer therapies, as opposed to intravenous chemotherapy, are now available for an increasing number of cancer indications. Mobile health (mHealth) apps for use on mobile devices (eg, smartphones or tablets) are designed to help patients with medication adherence, symptom tracking, and disease management. Several previous literature reviews have been conducted regarding mHealth apps for cancer. However, these studies did not address patient preferences for the features of cancer mHealth apps.

Objective: The primary aim was to review the scientific literature that describes the features and functions of mHealth apps designed for cancer self-management.

Methods: As the purpose of this review was to explore the depth and breadth of research on mHealth app features for cancer self-management, a scoping review methodology was adopted. Four databases were used for this review: PubMed/MEDLINE, Embase, CINAHL, and PsycINFO. Citation and reference searches were conducted for manuscripts meeting the inclusion criteria. A gray literature search was also conducted. Data extracted from manuscripts included author, title, publication date, study type, sampling type, cancer type, treatment, age of participants, features, availability (free or subscription), design input, and patient preferences. Finally, the features listed for each app were compared, highlighting similarities across platforms as well as features unique to each app.

Results: After the removal of duplicates, 522 manuscripts remained for the title and abstract review, with 51 undergoing full-text review. A total of 7 manuscripts (referred to as studies hereafter) were included in the final scoping review. App features described in each study varied from 2 to 11, with a median of 4 features per app. The most reported feature was a symptom or side effect tracker, which was reported in 6 studies. Two apps specified the inclusion of patients and health care providers during the design, while 1 app noted that IT and communications experts provided design input. The utility of the apps for end users was measured in several ways, including acceptability (measuring the end users' experience), usability (assessing the functionality and performance by observing real users completing tasks), or qualitative data (reports from end users collected from interviews or focus groups).

Conclusions: This review explored the literature on cancer mHealth apps. Popular features within these mHealth apps include symptom trackers, cancer education, and medication trackers. However, these apps and features are often developed with little input from patients. Additionally, there is little information regarding patient preferences for the features of existing apps. While the number of

Background: Cascade screening, defined as helping at-risk relatives get targeted genetic testing of familial variants for dominant hereditary cancer syndromes, is a proven component of cancer prevention; however, its uptake is low. We developed and conducted a pilot study of the ConnectMyVariant intervention, in which participants received support to contact at-risk relatives that extended beyond first-degree relatives and encourage relatives to obtain genetic testing and connect with others having the same variant through email and social media. The support that participants received included listening to participants' needs, assisting with documentary genealogy to find common ancestors, facilitating direct-to-consumer DNA testing and interpretation, and assisting with database searches.

Objective: We aimed to assess intervention feasibility, motivations for participating, and engagement among ConnectMyVariant participants and their families.

Methods: We used a mixed methods design including both quantitative and qualitative evaluation methods. First, we considered intervention feasibility by characterizing recruitment and retention using multiple recruitment mechanisms, including web-based advertising, dissemination of invitations with positive test results, provider recruitment, snowball sampling, and recruitment through web-based social networks and research studies. Second, we characterized participants' motivations, concerns, and engagement through project documentation of participant engagement in outreach activities and qualitative analysis of participant communications. We used an inductive qualitative data analysis approach to analyze emails, free-text notes, and other communications generated with participants as part of the ConnectMyVariant intervention.

Results: We identified 84 prospective participants using different recruitment mechanisms; 57 participants were ultimately enrolled in the study for varying lengths of time. With respect to motivations for engaging in the intervention, participants were most interested in activities relating to genealogy and communication with others who had their specific variants. Although there was a desire to find others with the same variant and prevent cancer, more participants expressed an interest in learning about their genealogy and family health history, with prevention in relatives considered a natural side effect of outreach. Concerns about participation included whether relatives would be open to communication, how to go about it, and whether others with a specific variant would be motivated to help find common ancestors. We observed that ConnectMyVariant participants engaged in 6 primary activities to identify and communicate with at-risk relatives: sharing family history, family member testing, direct-to-consumer genealogy genetic testing analysis, contacting (distant) relatives, documentary geneal

Background: The cancer incidence rate is essential to public health surveillance. The analysis of this information allows authorities to know the cancer situation in their regions, especially to determine cancer patterns, monitor cancer trends, and help prioritize the allocation of health resource.

Objective: This study aimed to present the design and implementation of an R Shiny application to assist cancer registries conduct rapid descriptive and predictive analytics in a user-friendly, intuitive, portable, and scalable way. Moreover, we wanted to describe the design and implementation road map to inspire other population registries to exploit their data sets and develop similar tools and models.

Methods: The first step was to consolidate the data into the population registry cancer database. These data were cross validated by ASEDAT software, checked later, and reviewed by experts. Next, we developed an online tool to visualize the data and generate reports to assist decision-making under the R Shiny framework. Currently, the application can generate descriptive analytics using population variables, such as age, sex, and cancer type; cancer incidence in region-level geographical heat maps; line plots to visualize temporal trends; and typical risk factor plots. The application also showed descriptive plots about cancer mortality in the Lleida region. This web platform was built as a microservices cloud platform. The web back end consists of an application programming interface and a database, which NodeJS and MongoDB have implemented. All these parts were encapsulated and deployed by Docker and Docker Compose.

Results: The results provide a successful case study in which the tool was applied to the cancer registry of the Lleida region. The study illustrates how researchers and cancer registries can use the application to analyze cancer databases. Furthermore, the results highlight the analytics related to risk factors, second tumors, and cancer mortality. The application shows the incidence and evolution of each cancer during a specific period for gender, age groups, and cancer location, among other functionalities. The risk factors view permitted us to detect that approximately 60% of cancer patients were diagnosed with excess weight at diagnosis. Regarding mortality, the application showed that lung cancer registered the highest number of deaths for both genders. Breast cancer was the lethal cancer in women. Finally, a customization guide was included as a result of this implementation to deploy the architecture presented.

Conclusions: This paper aimed to document a successful methodology for exploiting the data in population cancer registries and propose guidelines for other similar records to develop similar tools. We intend to inspire other entities to build an application that can help decision-making and make data more accessib

Background: Scan-associated anxiety (or "scanxiety") is commonly experienced by people having cancer-related scans. Social media platforms such as Twitter provide a novel source of data for observational research.

Objective: We aimed to identify posts on Twitter (or "tweets") related to scanxiety, describe the volume and content of these tweets, and describe the demographics of users posting about scanxiety.

Methods: We manually searched for "scanxiety" and associated keywords in cancer-related, publicly available, English-language tweets posted between January 2018 and December 2020. We defined "conversations" as a primary tweet (the first tweet about scanxiety) and subsequent tweets (interactions stemming from the primary tweet). User demographics and the volume of primary tweets were assessed. Conversations underwent inductive thematic and content analysis.

Results: A total of 2031 unique Twitter users initiated a conversation about scanxiety from cancer-related scans. Most were patients (n=1306, 64%), female (n=1343, 66%), from North America (n=1130, 56%), and had breast cancer (449/1306, 34%). There were 3623 Twitter conversations, with a mean of 101 per month (range 40-180). Five themes were identified. The first theme was experiences of scanxiety, identified in 60% (2184/3623) of primary tweets, which captured the personal account of scanxiety by patients or their support person. Scanxiety was often described with negative adjectives or similes, despite being experienced differently by users. Scanxiety had psychological, physical, and functional impacts. Contributing factors to scanxiety included the presence and duration of uncertainty, which was exacerbated during the COVID-19 pandemic. The second theme (643/3623, 18%) was the acknowledgment of scanxiety, where users summarized or labeled an experience as scanxiety without providing emotive clarification, and advocacy of scanxiety, where users raised awareness of scanxiety without describing personal experiences. The third theme was messages of support (427/3623, 12%), where users expressed well wishes and encouraged positivity for people experiencing scanxiety. The fourth theme was strategies to reduce scanxiety (319/3623, 9%), which included general and specific strategies for patients and strategies that required improvements in clinical practice by clinicians or health care systems. The final theme was research about scanxiety (50/3623, 1%), which included tweets about the epidemiology, impact, and contributing factors of scanxiety as well as novel strategies to reduce scanxiety.

Conclusions: Scanxiety was often a negative experience described by patients having cancer-related scans. Social media platforms like Twitter enable individuals to share their experiences and offer support while providing researchers with unique data to improve their understanding of a problem. Ack

Background: Shopping data can be analyzed using machine learning techniques to study population health. It is unknown if the use of such methods can successfully investigate prediagnosis purchases linked to self-medication of symptoms of ovarian cancer.

Objective: The aims of this study were to gain new domain knowledge from women's experiences, understand how women's shopping behavior relates to their pathway to the diagnosis of ovarian cancer, and inform research on computational analysis of shopping data for population health.

Methods: A web-based survey on individuals' shopping patterns prior to an ovarian cancer diagnosis was analyzed to identify key knowledge about health care purchases. Logistic regression and random forest models were employed to statistically examine how products linked to potential symptoms related to presentation to health care and timing of diagnosis.

Results: Of the 101 women surveyed with ovarian cancer, 58.4% (59/101) bought nonprescription health care products for up to more than a year prior to diagnosis, including pain relief and abdominal products. General practitioner advice was the primary reason for the purchases (23/59, 39%), with 51% (30/59) occurring due to a participant's doctor believing their health problems were due to a condition other than ovarian cancer. Associations were shown between purchases made because a participant's doctor believing their health problems were due to a condition other than ovarian cancer and the following variables: health problems for longer than a year prior to diagnosis (odds ratio [OR] 7.33, 95% CI 1.58-33.97), buying health care products for more than 6 months to a year (OR 3.82, 95% CI 1.04-13.98) or for more than a year (OR 7.64, 95% CI 1.38-42.33), and the number of health care product types purchased (OR 1.54, 95% CI 1.13-2.11). Purchasing patterns are shown to be potentially predictive of a participant's doctor thinking their health problems were due to some condition other than ovarian cancer, with nested cross-validation of random forest classification models achieving an overall in-sample accuracy score of 89.1% and an out-of-sample score of 70.1%.

Conclusions: Women in the survey were 7 times more likely to have had a duration of more than a year of health problems prior to a diagnosis of ovarian cancer if they were self-medicating based on advice from a doctor rather than having made the decision to self-medicate independently. Predictive modelling indicates that women in such situations, who are self-medicating because their doctor believes their health problems may be due to a condition other than ovarian cancer, exhibit distinct shopping behaviors that may be identifiable within purchasing data. Through exploratory research combining women sharing their behaviors prior to diagnosis and computational analysis of these data, this study demonstrates

Background: A diagnosis of cancer in adolescence or young adulthood can pose many different and unique challenges for individuals, as well as their families and friends. Drawing on the concept of prehabilitation, the provision of high-quality, accessible, timely, reliable, and appropriate information, care, and support for young adults with cancer and their families is critical to ensure that they feel equipped and empowered to make informed decisions relating to their treatment and care. Increasingly, digital health interventions offer opportunities to augment current health care information and support provision. Co-designing these digital health interventions can help to ensure that they are meaningful and relevant to the patient cohort, thereby maximizing their accessibility and acceptability.

Objective: This study had 4 primary interlinked objectives: understand the support needs of young adults with cancer at the time of diagnosis, understand the potential role of a digital health solution to assist in the delivery of prehabilitation for young adults with cancer, identify appropriate technologies and technological platforms for a digital prehabilitation system of care, and develop a prototype for a digital prehabilitation system of care.

Methods: This was a qualitative study using interviews and surveys. Young adults aged 16 to 26 years diagnosed with cancer within the last 3 years were invited to participate in individual user-requirement interviews or surveys. Health care professionals specializing in the treatment and care of young adults with cancer and digital health professionals working in the industry were also interviewed or completed a survey. Consensus feedback interviews were conducted with 3 young adults and 2 health care professionals after the development of the first generation of the prototype app.

Results: In total, 7 individual interviews and 8 surveys were completed with young adults with a range of cancer diagnoses. Moreover, 6 individual interviews and 9 surveys were completed with health care professionals, and 3 digital health professionals participated in one-on-one interviews. A prototype app with the working name of Cancer Helpmate was developed based on these collective participant data. Overall, feedback from participants across the data collection activities suggests that the concept for the app was positive during these developmental stages. Further insightful ideas for the app's future development were also identified.

Conclusions: Young adults with cancer and health care professionals are responsive to the need for more digitally driven services to be developed. Further development of an app such as Cancer Helpmate, which incorporates key features and functionalities directly informed by users, could help to augment the support provided to young adults with cancer.