Next Article in Journal
Visual Intratumor Heterogeneity and Breast Tumor Progression
Previous Article in Journal
Association between Gastric Cancer and Osteoporosis: A Longitudinal Follow-Up Study Using a National Health Sample Cohort
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Cancer Patients’ Perspectives and Requirements of Digital Health Technologies: A Scoping Literature Review

by
Ioulietta Lazarou
*,
Anna-Maria Krooupa
,
Spiros Nikolopoulos
,
Lazaros Apostolidis
,
Nikos Sarris
,
Symeon Papadopoulos
and
Ioannis Kompatsiaris
Information Technologies Institute (ITI), Centre for Research and Technology Hellas (CERTH), 6th km Charilaou-Thermi Road, P.O. Box 6036, 57001 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(13), 2293; https://doi.org/10.3390/cancers16132293
Submission received: 21 May 2024 / Revised: 14 June 2024 / Accepted: 19 June 2024 / Published: 21 June 2024

Abstract

:

Simple Summary

Digital health technologies can help manage the growing cancer burden, but understanding patients’ needs is crucial for these tools to be effective. Our study reviewed existing research on what cancer patients want from digital health technologies. We analysed 128 studies, focusing on web-based platforms, mobile apps, and wearable devices used in cancer care. Patients highlighted the importance of these technologies being easy to use, effective in managing their care, and enhancing communication with healthcare providers. Our findings offer insights for future research to develop digital health tools that meet cancer patients’ preferences, potentially improving their healthcare experience and outcomes.

Abstract

Digital health technologies have the potential to alleviate the increasing cancer burden. Incorporating patients’ perspectives on digital health tools has been identified as a critical determinant for their successful uptake in cancer care. The main objective of this scoping review was to provide an overview of the existing evidence on cancer patients’ perspectives and requirements for patient-facing digital health technologies. Three databases (CINAHL, MEDLINE, Science Direct) were searched and 128 studies were identified as eligible for inclusion. Web-based software/platforms, mobile or smartphone devices/applications, and remote sensing/wearable technologies employed for the delivery of interventions and patient monitoring were the most frequently employed technologies in cancer care. The abilities of digital tools to enable care management, user-friendliness, and facilitate patient–clinician interactions were the technological requirements predominantly considered as important by cancer patients. The findings from this review provide evidence that could inform future research on technology-associated parameters influencing cancer patients’ decisions regarding the uptake and adoption of patient-facing digital health technologies.

1. Introduction

Cancer constitutes a global health issue with 19.3 million new cases occurring in 2020, while cancer incidence is projected to significantly increase in the coming years, reaching 28.4 million new cases annually by 2040 [1]. Meanwhile, advances in early detection and cancer treatment have improved survival rates, leading to steadily rising numbers of long-term cancer survivors [2]. The growing population of people diagnosed and living with cancer together with the complex healthcare needs that this population faces place a substantial strain on health services, often resulting in cancer patients and their caregivers not accessing or receiving timely and adequate care and support [3]. Emerging digital health technologies have the potential to contribute towards alleviating the increasing cancer burden exerted on healthcare services by leveraging technology to improve care quality, accessibility, and cost-effectiveness [4].
Digital health technologies are digital products, encompassing both hardware and software solutions and services, for healthcare and related uses intended to benefit people and the wider health and social care system [5,6]. Such technologies may comprise smartphone applications, electronic medical records, wearable monitoring or reporting devices, decision support systems, and online tools for treating or diagnosing conditions, preventing ill health, or for improving system efficiencies [6,7]. Numerous beneficial applications of digital health technologies to healthcare delivery and practice have been reported, including the remote monitoring of patients’ symptoms and conditions; the provision of electronic decision support, resources, and interventions; and the facilitation of distant patient–clinician communication [7,8]. Based on these, the incorporation of digital health technologies into national health systems worldwide has been identified as a key priority [9].
In cancer care, where patients’ symptom burden tends to be high due to disease progression or treatment-associated side-effects, the use of digital health technologies can facilitate the collection of patient-generated data, including patient-reported outcomes. This can help in overcoming the challenges associated with conventional clinician-led symptom monitoring, which can often lead to the under-reporting of patients’ symptoms [10]. Routine symptom assessment enabled by digital health technologies thus has the potential to improve symptom management, resulting, in turn, in improvements in healthcare resource utilisation and patients’ quality of life compared with standard clinical assessment [10]. A further advantage of digital technology applications is that they can increase the equity of cancer care delivery by extending access to care for patients in remote or rural areas or those living with socioeconomic disadvantages, mitigating, therefore, geographical and socioeconomic disparities in cancer outcomes that are associated with limited access to care [11,12]. Moreover, using digital health technologies to support patient education has the potential to improve compliance with care pathways and aid self-management to address the complex healthcare needs of people diagnosed with cancer [7,13]. Despite these advantages, however, the adoption of digital health technologies remains limited both in healthcare overall and in cancer care in particular [10,14].
Incorporating patients’ perspectives into the development of digital health tools has been identified as a critical determinant for the successful uptake of these technologies in healthcare [15]. Understanding end-users’ needs and preferences for technological innovations has been found to increase their acceptance, feasibility, and long-term use in clinical populations [16,17]. To this end, the active engagement of patients and other key stakeholders throughout all stages of technology development via the use of participatory and iterative approaches is recommended and has been shown to be particularly useful for the development of technologies intended to be used by patients with ongoing healthcare and educational needs, such as those experienced by patients diagnosed with cancer [18,19,20].
In spite of the reported added value of encompassing end-users’ perspectives into the development of technological innovations, there is limited information available to date regarding cancer patients’ needs and perceptions of digital health technologies, while existing evidence has not yet been systematically reviewed and synthesised. The purpose of the present review, therefore, is to provide an overview of the available evidence regarding cancer patients’ requirements for patient-facing digital health technologies, aiming to enhance our understanding of the needs and preferences of this population for the technologies integrated into their care. This comprehension can contribute towards guiding the development of patient-facing digital technologies to ensure that they meet the expectations of cancer patients and do not place additional burdens on their care, thereby improving their uptake and continued use.

2. Materials and Methods

2.1. Review Question and Objectives

The main objective of the scoping review was to systematically map and synthesise the existing evidence on cancer patients’ perspectives and requirements for patient-facing digital health technologies, i.e., digital technologies with which patients interact to participate in healthcare or clinical activities [21]. To form the review question, the Population, Intervention, Comparison, and Outcomes (PICO) framework was adopted (Table 1). The review was registered with Review Registry (ID: reviewregistry1816).

2.2. Search Strategy

The search strategy comprised two steps. A database, MEDLINE (via PubMed), was initially searched to identify primary research studies reporting on cancer patients’ perceptions of digital health technologies. Relevant text words contained in the title, abstract, and authors’ keywords of identified papers and database index terms were compiled to produce a list of search terms. Three databases were then searched, CINAHL, MEDLINE, and Science Direct, using a combination of subject headings and free-text terms for cancer patients, digital health technologies, and user perceptions (see Figure 1 for the search strategy used for MEDLINE).

2.3. Eligibility Criteria

  • Articles were included if they met all the following a priori specified criteria:
  • Primary research studies.
  • Full-text research articles.
  • English-language publications.
  • Studies conducted with adult (>18) cancer patients.
  • Studies reporting cancer patients’ perspectives on patient-facing digital technologies.
Papers were excluded if they were reporting on the following:
  • Non-primary studies, including systematic reviews.
  • Opinion articles, editorials, or book chapters.
  • Case-report studies and studies providing no information about sample size.
  • Non-English-language publications.
  • Studies with non-adult (<18) cancer patients.
  • Studies reporting the use of provider-facing digital health technologies.
  • Studies reporting clinicians’/caregivers’ perceptions of the use of patient-facing digital technologies.

2.4. Selection Procedure

The study selection process involved three phases. First, all records yielded by the database searches were reviewed for eligibility by title. Then, a selection process based on abstract information was conducted. Finally, a full-text review of studies that met the inclusion criteria according to the initial two phases was performed. Two reviewers (IL, AMK) independently assessed the obtained records for eligibility. Discrepancies at each stage of study selection were resolved through discussion. Finally, citation chaining (forward and backward) was undertaken to ensure that all relevant publications were identified and included, if eligible.

2.5. Data Extraction

Two reviewers (IL, AMK) independently extracted relevant data on each included study, the technologies used, and user perceptions using a standardised form developed for the purposes of this review. For each study, the following information was extracted and entered into the form: author(s), date of publication, study design, study population, sample size, technology used, and purpose of technology use. Data on users’ perceptions of technologies were also extracted using the same form and were categorised based on a modified version of the technology evaluation categories of the Human, Organization and Technology-fit (HOT-fit) evaluation framework for Health Information Systems [22]. These categories included perceptions relating to the quality of the technological system, its content/available information, its service quality, and other relevant characteristics and features reported by cancer patients. The results of data extraction were compared and any disagreements between reviewers were resolved by consensus.

3. Results

3.1. Search Results

Database searches yielded a total of 7836 records. After duplicates were removed, 7793 studies were screened based on their titles, and 709 studies were screened on the basis of their abstracts. Following the screening of titles and abstracts, 391 potentially eligible articles remained, which were examined in full. Of these studies, 107 met the criteria for inclusion. A further 21 eligible studies were identified through forward and backward citation chaining, resulting in 128 included studies (see Figure 2 or the PRISMA flow diagram of the study selection process [23]).

3.2. Description of Included Studies

Overall, the included studies were published within the last 20 years (2002–2022), with the overwhelming majority (n = 110, 85.9%) being published from 2013 onwards (Figure 3). Studies were predominantly conducted in the USA (n = 53), Australia (n = 15), the UK (n = 12), Canada (n = 11), and the Netherlands (n = 9). Different research designs were employed by the included studies, with most (n = 55) being interventional, predominantly full-scale or pilot randomised controlled trials (RCTs), or small-scale observational investigations nested within interventional studies (e.g., an evaluation study nested within an RCT). Data collection in all studies was conducted prospectively. Sample size varied greatly between studies, ranging from 3 to 4737 participants, reflecting the diverse objectives and research designs employed by the included studies. The participant population mostly consisted of breast (n = 38), prostate (n = 14), lung (n = 8), colorectal (n = 8), and head and neck (n = 7) cancer patients receiving or awaiting treatment and survivors. The remaining studies (n = 46) included patients with various cancer types or did not provide type-specific information.

3.3. Description of Identified Patient-Facing Digital Technologies

Patient-facing digital technologies identified across the included studies can be broadly categorised as follows: Web-based software/platforms (n = 53), mobile/smartphone devices/applications (n = 33), telephone-based services and tools (n = 13), and remote sensing and wearable technologies (n = 4) [24,25,26,27]. Telephone-based services and tools were mostly identified in studies published before 2014, while newer studies (published between 2015 and 2022) predominantly reported the use of Web- and smartphone-based technologies or remote sensing devices. Sixteen studies reported using more than one patient-facing digital technology, mostly including wearable devices combined with additional technologies such as smartphone applications or Web-based platforms (n = 13). In two studies [28,29], an existing social media platform (i.e., Facebook) was used together with other digital health technologies. Identified wearable technologies in all cases comprised activity-tracking devices which were predominantly wrist-worn (n = 15). One study included an upper-arm wearable sensor [24], whist in another study participants were asked to use an accelerometer on their waist [30]. Other technologies, not classified in the abovementioned categories, were reported in nine studies. These included automated chatbots simulating human conversations through text or voice interactions (n = 3) [31,32,33], a touch-screen computer monitor for self-reporting psychosocial information in an ambulatory cancer clinic (n = 1) [34], an electronic health system facilitating patient-reported outcome data collection (n = 1) [35], a virtual reality platform supporting post-treatment rehabilitation (n = 1) [36], a voice-activated, interactive computer model enabling virtual conversations (n = 1) [37], a non-invasive optical technology for the remote screening of severe neutropenia (n = 1) [38], and a telemonitoring system consisting of a small point-of-care haematology analyser linked to a telecommunication hub facilitating the self-testing of patients’ blood counts (n = 1) [39]. Figure 4 presents the number of included studies by technology category.
The majority of the reported technologies (n = 77) were predominantly used for delivering interventions to cancer patients at various stages of disease progression (Figure 5). Of these, 23 provided interventions aiming to assist the self-management of patients’ symptoms and/or overall conditions. In a further 15 studies, interventions were designed to increase patients’ cancer-related knowledge, mostly by providing information and resources on different treatment and care management options. Technologies were particularly used for educating patients on clinical trial participation in one study [40], whilst in another study cancer-related educational materials were developed both for patients and their partners, thus delivering a couple-focused intervention [41]. Sixteen studies described using digital health technology-assisted interventions for promoting patients’ physical activity and health behaviour habits, while a further twelve studies reported delivering therapeutic or educational interventions for the management of psychosocial symptoms. Assisting patient rehabilitation after surgery or chemotherapy was the focus of technological interventions in five of the included studies in this category, whereas an equal number of studies (n = 5) delivered interventions aimed at improving cancer patients’ medication adherence. One study reported the use of speech-generating devices to support telephone or face-to-face communication after total laryngectomy [42].
Other intended uses of digital health technologies described in the identified studies included the reporting and/or monitoring of patients’ symptoms and physiological parameters and enabling patient–clinician or peer-to-peer communication. Specifically, the remote reporting and/or monitoring of patients’ conditions, vital signs, and symptoms conducted through self-reported or automatically collected data via wearable technologies was described as the primary intent of digital health technology use in 39 studies. Similarly, the principal purpose of technology employment was the facilitation of remote patient–clinician consultations or peer interactions in nine and three of the included studies, respectively.

3.4. Evaluation of Digital Health Technologies

Cancer patients’ perceptions of digital health technologies were almost exclusively investigated by the included studies in the context of evaluations of existing or newly developed patient-facing technologies/technological interventions following their development (n = 115) (Table 2). Only a small number of studies (n = 13) explored patients’ perspectives in the design and/or development phases of technologies. Assessment objectives differed significantly between studies, with 68 papers reporting two or more objectives. Among these, the most frequently evaluated were user satisfaction (n = 43) and the acceptability (n = 41), feasibility (n = 38), and utility/usability (n = 31) of the technologies. Twenty-three studies described exploring cancer patients’ perceptions and/or experiences of using digital health technologies, while the main objective in five studies was the examination of patients’ technological needs and requirements. Despite a plethora of evaluation objectives being described across the studies, there was a significant overlap in the definitions of assessed concepts, with the terms “acceptability”, “satisfaction”, “utility/usability”, and “user perceptions/experiences” being used interchangeably in a number of studies
In terms of the methods employed for the evaluation of identified technologies, 68 studies reported using mixed (i.e., both qualitative and quantitative) or multiple assessment methods, while in 60 studies a single quantitative or qualitative method was utilised. Patient-reported measures, predominantly questionnaires (n = 68), comprised the most frequently described means of technology evaluation, followed by different metrics, such as technology interaction duration and rates, login data, and completion rates, collected either through participants’ self-reports or extracted from technology tracking data (n = 42). Qualitative methods, and particularly individual or group interviews and textual data provided by patients, were utilised in 32 studies. In most cases (n = 62), evaluation methods (questionnaires, scales, interview guides) were developed or adapted/modified from measures and guides used in previous research for the purposes of individual studies without any prior validation (i.e., ad hoc methods). Thirty-two studies described using validated evaluation measures and existing theoretical frameworks for the development of interview guides. Of these, the most commonly employed were the System Usability Scale (n = 10) [43], the Mobile App Rating Scale (MARS; n = 4) [44], and the Technology Acceptance Model (TAM; n = 3) [45].
The included studies overwhelmingly reported positive findings for the patient-facing technology appraisals performed by cancer patients, with 120 studies describing the evaluated technologies being perceived as acceptable, feasible, and/or useful to patients overall. Only eight studies reported mixed findings, concluding with suggested improvements in distinct technological features spanning from content changes to hardware adjustments to increase the usability and acceptance of technologies [25,46,47,48,49,50,51,52].

3.5. User Perspectives and Requirements

In line with the HOT-fit evaluation framework for Health Information Systems [22], cancer patients’ perceptions of digital health technologies were grouped into four main categories: system, information/content, service, and other requirements. System requirements concern the inherent features of digital health technologies, including the system performance and user interface. Information/content requirements relate to the characteristics of the information delivered to patients through health technologies. Service requirements refer to the extent to which support is provided to patients in the use and handling of technologies. Other requirements cover any additional issues and perspectives raised by cancer patients, not covered by the aforementioned categories. Table 3 and Figure 6 provide an overview of the identified user perceptions and requirements.
In the system requirements category, ease of use (n = 70) and overall system performance (n = 28) were the technological characteristics most frequently assessed as important by cancer patients. Other system features considered by patients included system reliability in terms of the stability of different features (n = 15) and flexibility (n = 15) in being able to return to or skip certain parts or modules and alter their responses. The ease of setting up technologies for the first time and the attractiveness of the overall design and/or user interface were reported as important characteristics by participants in 11 and 15 studies, respectively. In 13 studies, cancer patients highlighted the importance of being able to easily learn how to operate technologies, whilst the system ensuring that provided patient data are secure and protected was reported as a digital health technology requirement in 8 studies.
In the information/content category, the extent to which the content of the technological intervention was considered useful for the management of patients’ symptoms or overall conditions was the most frequently reported feature among participants of the included studies (n = 86). Using language that is easy to understand and lay terms was raised as an important content feature by participants in 30 studies, while in 26 studies cancer patients noted that alternative means of information presentation, such as videos, pictures, and graphs, are helpful in aiding comprehensibility. The extent to which the presented content is relevant to the patients’ situations and the comprehensiveness of the provided information in terms of covering all important aspects of a given topic were noted by participants in 23 and 21 studies, respectively. In 18 studies, cancer patients reported finding the content of the technological interventions to be tailored to their own needs and situation, which was considered a feature that increased the usability of technologies, whilst in other studies participants commented on the importance of information clarity (n = 12), quantity (n = 10), and reliability (n = 8). Using culturally and gender-sensitive, as well as inclusive, language was noted as an important content characteristic by cancer patients in five studies.
For the service requirements, cancer patients mostly reported the need to receive appropriate instructions and/or training (n = 20) in the use of technologies, either in the form of a training manual or one-to-one sessions with people who could guide them through the process of setting up and interacting with the technologies. Additional service requirements included technical support being available for the duration of interactions with technologies (n = 9) and receiving feedback on whether given tasks were completed in line with the relevant guidance (n = 4).
Further issues reported by cancer patients which could not be grouped in the aforementioned categories included the technology enabling patient–clinician (n = 50) and peer-to-peer (n = 18) interactions. Specifically, patients highlighted the importance of being able to communicate their symptoms or overall condition with the clinical teams involved in their care through health technologies, either via their data being directly shared with their consulting clinicians or by being able to produce alerts in case of emergencies. Furthermore, in 33 studies participants reported that in the development phase of digital health technologies, consideration should be given to the amount of time that needs to be invested by end-users in order for the appropriate data to be collected, especially in the case of cancer patients where increased symptom burden may not allow for lengthy amounts of time to be devoted to technology interactions. In 18 studies, participants commented that they would appreciate having access to aggregate forms and graphical representations of their own data reported through/gathered from health technologies. Further issues were raised related to the coverage/connectivity of health technologies to internet/telecommunication networks (n = 12), and to the limited battery life of medical devices/wearables (n = 8), deterring patients from using technologies due to additional costs and burden. Lastly, comfort of use was reported as a requirement for technological devices, especially wearables, by patients in nine of the included studies.
Table 2. Study characteristics.
Table 2. Study characteristics.
Author(s), YearCountryStudy DesignStudy PopulationnTechnologyPurpose of Technology UseTechnology Description
Abernethy et al., 2009 [53]USAProspective observational studyMetastatic breast cancer patients66Tablet-based softwareSymptom and quality-of-life reporting Tablets used by patients for symptom and quality-of-life self-reported assessments
Admiraal et al., 2017 [54]NetherlandsRCTBreast cancer patients 138Web-based platformDelivery of a tailored psychoeducation programmeFeatures included assessments of patients’ distress and prevailing problems and psychoeducational materials tailored to their reported needs
Aiello et al., 2006 [55]USARCTBreast cancer patients160Tablet-based softwareEnabling electronic data collection on breast cancer risk factorsPassive digitizer tablet computer with a plastic pointer to complete electronic questionnaires through Microsoft Access
Albrecht et al., 2011 [56]GermanyMixed methods studyBreast cancer patients9Video-based decision aidProviding guidance in patient decision-making and communicating preferencesAdaptation of existing 55 min video on different surgical treatment options (lumpectomy vs. mastectomy) in the German context using synchronised voice-over
Allenby et al., 2002 [34]AustraliaRCTPatients with various cancer types451Platform accessed through touch-screen computer Self-reporting of psychosocial informationTouch-screen monitor for patient symptom reporting using software developed utilising the Visual Basic Version 6 programming language; data stored in Microsoft Access 97 databases
Allicock et al., 2021 [30]USAPilot RCTAfrican American breast cancer survivors22Smartphone-based application, waist-worn wearable (ActiGraph wGT3X-BT)Improving survivors’ physical activity and diet behavioursApp accessed through Samsung Galaxy Core Prime devices used to complete daily ecological momentary assessments; accelerometer for physical activity monitoring
Alshoumr et al., 2021 [57]Saudi ArabiaQualitative studyPatients with various cancer types22Web-based platform and monitorProviding patient education, enabling communication with clinicians, aiding self-management of care and symptomsInpatient portal presented on 55-inch high-resolution monitors placed in front of a patient’s bed in clinical wards
Appleyard et al., 2021 [58]UKMixed methods observational studyAdvanced prostate cancer patients40Tablet-based platformEnabling the electronic collection of patient-reported outcomesPlatform facilitating patient completion of health-related quality-of-life questionnaires on a tablet
Badr et al., 2016 [59]USAQualitative studyOral cancer survivors13Web-based platformImproving survivor self-management and survivor/caregiver quality of lifeEducation for the management of side-effects, facilitation of connections with peers, and provision of self-monitoring features
Basch et al., 2007 [60]USAProspective observational studyCancer patients receiving chemotherapy180Web-based platformEnabling the electronic collection of patient-reported outcomesPlatform features include the real-time report generation of patient symptoms and an alert system for clinicians
Basch et al., 2017 [61]USAFeasibility study nested within an RCTCancer patients receiving radiation treatment152Web-based platformEnabling patient reporting of symptomatic adverse eventsOnline patient-reported outcome items for the systematic identification of adverse events in clinical trials
Basch et al., 2020 [62]USAMulticentre RCTPatients with various cancer types496Web-based platformEnabling remote patient symptom monitoringOnline patient-reported outcome items for the systematic identification of adverse events in clinical trials
Beaver et al., 2012 [63]UKExploratory RCTColorectal cancer patients65Telephone serviceDelivery of follow-up consultationsAudio-recorded telephone sessions pre-registered on computerised hospital information systems together with patients’ medical records
Beaver et al., 2009 [64]UKRCTBreast cancer patients374Telephone serviceDelivery of follow-up consultationsNurse-led telephone follow-up intervention using a standardised protocol to address various patient concerns, including symptoms, information needs, and psychosocial support, ensuring comprehensive and consistent patient care remotely
Bender et al., 2022 [65]CanadaPilot feasibility studyProstate cancer patients29Web-based applicationDelivery of peer support for care managementTrue North PN: Web-based peer navigation programme for prostate cancer patients using a matching algorithm, private messaging, health resources, and case management
Bender et al., 2013 [66]CanadaMulti-method studyBreast cancer patients100Web-based synchronous text message communication platformDelivery of online support groupsOnline communities–websites that offer discussion forums or chat rooms to support breast cancer survivors by providing information, symptom management, and emotional support
Bennett et al., 2016 [67]USAProspective observational studyPatients with various cancer types112Web-enabled tablet computer, interactive voice response system (IVRS)Collection of patient-reported outcomesIVRS accessed through mobile phones or landlines. Touch-screen tablets provided to users at clinic visits
Benze et al., 2019 [68]GermanyProspective feasibility study Advanced cancer patients40Smartphone-based applicationEnabling the electronic collection of patient-reported outcomesMeQoL app for ePROs in advanced cancer patients (symptoms, pain intensity, quality-of-life data)
Bol et al., 2013 [69]NetherlandsProspective randomised trialOlder lung cancer patients357WebsiteDelivery of cancer-related informationPersonalised audio–visual information in addition to text on website satisfaction and recall of cancer-related online information
Bolle et al., 2016 [70]NetherlandsThink-aloud studyOlder cancer patients and survivors15Existing cancer information toolsProviding cancer-related information3 cancer information websites, 3 Web-based question prompt lists, 1 decision aid based on the values clarification method
Brennan et al., 2022 [71]IrelandProspective feasibility studyUpper gastrointestinal cancer survivors12Web-based platformDelivery of a multidisciplinary rehabilitation programmeClinically tested digital therapy platform for hosting video calls (one-to-one and group), providing exercise prescription, and appointment scheduling
Cadmus-Bertram et al., 2019 [72]USAPilot RCTBreast and colorectal cancer survivors50Wrist-worn wearable (Fitbit) linked to electronic health recordMonitoring of and education on physical activityFitbit activity trackers linked to electronic health records (EHRs), along with email-based coaching and an educational handbook
Chaix et al., 2019 [31]FranceProspective observational studyBreast cancer patients4737ChatbotImproving medication adherenceThe chatbot provides personalised text responses to user questions using machine learning methods
Chee et al., 2017 [73]USAProspective observational studyAsian American breast cancer survivors5Web-based platform Delivery of culturally appropriate patient education Culturally tailored internet cancer support group for Asian American breast cancer survivors. Pilot test for enhancing women’s breast cancer survivorship experience
Cheville et al., 2018 [74]USARCTLate-stage cancer patients516Web-based platform, pedometer, telephone serviceRemote monitoring and management of symptoms and physical activityWeb-based interface and telephone-based IVR used for collection of pain and function patient-reported outcomes; pedometers used for step count
Childes et al., 2017 [42]USAOnline questionnaire surveyHead and neck cancer patients after total laryngectomy 265Text-to-speech-based applications/software programmes accessed using various devicesProviding verbal communication supportSpeech-generating devices (SGDs) to support telephone or face-to-face communication post-laryngectomy along with text-to-speech for both face-to-face and phone communication and teletypewriter devices as an alternative communication method for individuals post-laryngectomy
Chow et al., 2021 [28]USAPilot RCTHaematologic malignancy survivors41Smartphone-based application, wrist-worn wearable (Fitbit), social media platform (Facebook)Delivery of an intervention to improve diet and physical activitymHealth-supported intervention utilising a Fitbit wearable wristband for tracking daily steps, the Healthwatch360 app for monitoring dietary intake (sodium, saturated fats, and added sugars), and a private Facebook peer support group for social interaction and educational support among haematologic malignancy survivors
Chow et al., 2019 [75]USAProspective observational studyPatients receiving active cancer treatment52Short Message Service (SMS) over networks of mobile operators, Web-based platformEnabling distress monitoringWeekly distress screeners via text message on their personal smartphones, utilising secure links delivered through a Qualtrics SMS Survey tool. The PHQ-4, a validated measure of distress, was completed online, with geolocation data automatically logged upon completion to track screening locations. Automated alerts were triggered for high distress scores
Cleeland et al., 2011 [76]USARCTPatients following cancer-related thoracotomy100Automated telephone servicePostoperative symptom monitoringAutomated telephone calls monitored postoperative symptoms for thoracotomy patients via interactive voice response system. Symptom alerts were sent to clinicians for severe symptoms via email
Collins et al., 2017 [77]AustraliaPilot RCTHead and neck cancer patients30Web-based platformDelivering acute symptom monitoring, nutritional management, and swallowing and communication rehabilitationParticipants used PCs, smartphones, or tablets with cameras and microphones to connect with RBWH clinicians via a secure telehealth portal, employing videoconferencing units and webRTC technology. The telehealth system included training sessions for both patients and clinicians, ensuring effective use of the technology for remote consultations
Crafoord et al., 2020 [78]SwedenMixed methods studyBreast and prostate cancer patients149Smartphone/tablet-based applicationReducing symptom burden during cancer treatmentApp components: symptom self-assessment, evidence-based self-care advice, summaries/graphs of reported symptoms, urgent/persistent system notifications to health professionals
Crawford et al., 2019 [79]USADevelopment and feasibility testing studyPatients with various cancer types30Smartphone-based applicationDelivering patient education on oral anticancer medicationsThe app interfaces with patients’ electronic medical records and is designed based on learning style and adherence theories, providing information through text, pictures, animations, and audio voiceovers (adherence barriers and features for dose scheduling, refill reminders, and feedback collection through reflective questions)
Denis et al., 2014 [80]FranceProspective pilot studyLung cancer patients42Web-based platformRemote symptom monitoringPatients self-report symptoms weekly via the internet for lung cancer follow-up—Software tracks weight and 10 symptoms, enabling early relapse detection
Duffecy et al., 2013 [81]USAProspective pilot studyPost-treatment cancer survivors31Website Skill management training for distress education Components included lessons on basic cognitive behavioural concepts, interactive tools, self-monitoring features, and a discussion board
Eakin et al., 2012 [82]AustraliaRCTBreast cancer patients143Telephone serviceDelivery of an exercise interventionTelephone-delivered intervention with mixed aerobic and resistance exercise guidance to deliver personalised exercise programs and offer remote support, ensuring accessibility for women living in rural areas
Ferguson et al., 2016 [83]USARCTBreast cancer survivors47Videoconferencing equipment and platformDelivery of Cognitive Behavioural Therapy-based trainingVideoconference technology (Tandberg centric 1700 MXP units) to deliver Memory and Attention Adaptation Training (MAAT) and supportive therapy (ST) remotely to breast cancer survivors, improving access to cognitive rehabilitation for participants in various locations
Finlay et al., 2020 [46]AustraliaRCTProstate cancer survivors71Web-based platformDelivery of a physical activity interventionWeb-based computer-tailored interventions with different website architectures (free choice vs. tunnelled) to promote physical activity among prostate cancer survivors, with engagement differing based on the navigational structure of the site
Foley et al., 2016 [84]IrelandRCTBreast cancer patients39Tablet-based applicationDelivery of information on basic breast cancer biology, different treatments, and surgical methodsApp for iPad to assess its impact on anxiety levels in patients undergoing surgery for breast cancer
Fu et al., 2016 [85]USAProspective useability study Breast cancer survivors30Web- and smartphone-based platformDelivery of education on self-care strategies for lymphedema symptom managementTOLF: Web and mobile-based health IT system for lymphedema management—avatar technology for self-care strategies and symptom evaluation
Galiano-Castillo et al., 2016 [86]SpainRCTBreast cancer survivors81Web-based platformDelivery of a tailored exercise programmeWeb-based interventions used for cancer survivorship support. Telehealth system with internet-based tailored exercise programme for cancer rehabilitation
Galsky et al., 2017 [87]USASingle-arm clinical trialProstate cancer patients15Videoconferencing platformEnabling remote patient research-related visitsPlatform used on PI’s desktop and patients’ smartphones
Gell et al., 2017 [88]USASingle-arm clinical trialCancer survivors24Wrist-worn wearable (Fitbit), SMS over networks of mobile operators, accelerometer (Actigraph GT3X+)Supporting physical activityIntervention includes text messages, Fitbit self-monitoring, and health coaching.
Measures physical activity with waist-worn accelerometer and portable GPS
Gilbertson-White et al., 2019 [89]USAMixed methods study Patients with various cancer types56Web-based platform Enabling symptom self-managementeHealth symptom self-management intervention, OASIS. It features multimedia graphics and uses HTML5 for animations to enhance accessibility for users with limited literacy
Girgis et al., 2017 [35]AustraliaMixed methods studyPatients with various cancer types42Electronic health systemCollecting and utilising patient-reported outcome measures for personalised careSystem components included self-report assessments, links to online self-care resources, health professional review, and access to patient reports
Graetz et al., 2018 [90]USARandomised controlled feasibility trialOvarian cancer patients 26Web-based platformEnabling real-time symptom monitoringWeb-based app for postoperative care in gynaecological oncology patients.
Reminders for discharge instructions and symptom monitoring through smartphones, iPads, or Web-enabled devices
Greenway et al., 2022 [36]UKQualitative studyHead and neck cancer patients7Virtual reality platformEnabling access to cancer-related information and resourcesWebXR platform ‘recovery’ to simulate a virtual reality experience within a virtual room. This platform allows patients to navigate and interact with targeted resources and specific learning materials related to their cancer journey, featuring natural landscapes and architectural principles to enhance user experience and facilitate self-management of post-treatment recovery needs
Greer et al., 2019 [32]USAPilot RCTYoung adults after cancer treatment45Online chatbot Delivery of a cognitive and behavioural intervention to increase positive emotionsVivibot delivers positive psychology skills via prewritten material online.
Users interact with an automated system through a decision tree structure
Groarke et al., 2021 [91]IrelandNested mixed methods study within an RCTCancer survivors with obesity or overweight36Wrist-worn wearable (Fitbit), SMS over networks of mobile operatorsDelivery of a behaviour-change interventionmHealth intervention using a Fitbit activity monitor and SMS contact for an 8-week physical activity goal-setting programme. The Fitbit activity monitor provided real-time physical activity feedback, while SMS contact delivered personalised goal setting and behavioural prompts, integrating behaviour-change techniques such as self-monitoring, feedback on behaviour, and goal setting
Gustavell et al., 2020 [92]SwedenProspective observational studyPatients following pancreatic cancer surgery26Tablet- and smartphone-based applicationFacilitating person-centred careApp features: assessment of self-reported symptoms, risk assessment models for alerts, access to evidence-based self-care, summaries of symptom history
Harless et al., 2009 [37]USAProspective observational studyBreast cancer patients39Voice-activated, interactive computer modelDelivery of educational dialoguesTelehealth intervention using Health Buddy System for head and neck cancer (daily education, guidance, and encouragement)
Head et al., 2011 [93]USAMixed methods studyHead and neck cancer patients44Telemessaging device (Health Buddy® System)Providing an interface for patient–healthcare provider communicationDevice that attached to land phone line; questions displayed on device screen appliance; responses given by pressing buttons below the screen
Head et al., 2009 [94]USARCTHead and neck cancer patients75Telemessaging device (Health Buddy® System)Providing an interface for patient–healthcare provider communicationHealth Buddy device communicates intervention algorithms for symptom management. Device plugs into telephone line and electrical outlet for operation
Heiney et al., 2012 [95]USAEvaluation study nested within an RCTAfrican American breast cancer patients39Teleconferencing platformDelivery of therapeutic group sessionsTeleconference support group intervention for African American women with breast cancer utilised structured sessions delivered over 8 weeks, with additional boosters. The intervention featured story sharing and coping strategies, facilitated by two experienced African American group therapists using process-focused leadership techniques
Hochstenbach et al., 2016 [96]NetherlandsMixed methods studyCancer outpatients11Web- and tablet-based applicationEnabling self-management of pain Mobile app for patients with daily monitoring and graphical feedback and nurses with patient data analysis and decision support
Jacobsen et al., 2022 [24]GermanyProspective observational studyPatients with aggressive haematologic malignancies67Upper-arm wearable Vital sign and physical activity monitoringWearable including photoplethysmography, temperature probe, and accelerometery sensors; parameters (heart rate, temperature, respiratory rate, physical activity) calculated using proprietary firmware algorithms
Kanera et al., 2016 [97]NetherlandsPCT process evaluationEarly cancer survivors with various cancer types23Web-based portalCoping with psychosocial issues and promoting a healthy lifestylePortal providing self-management training modules covering return to work, fatigue, anxiety and depression, social relationship and intimacy issues, physical activity, diet, and smoking cessation, and a general information module on residual symptoms
Katz et al., 2016 [98]USAProspective pilot studyPatients after pancreatic surgery for any neoplasm15Videoconferencing via tabletClinical follow-up following surgical proceduresExisting videoconferencing software (Vidyo, Hackensack, NJ, USA) used on Apple iPad tablets provided to patients
Kearney et al., 2006 [99]UKProspective feasibility studyCancer patients
receiving chemotherapy
18Handheld-computer softwareFacilitating patient monitoring and supportFeatures provided: assessment of self-reported symptoms, pre-defined symptom-scoring algorithm alerting health professionals to the presence of persistent/urgent symptoms, tailored self-care advice, summaries of symptom history
Kelleher et al., 2019 [100]USARCTPatients with breast, lung, prostate, or colorectal cancer89Videoconferencing platform, websiteDelivery of behaviour training in pain coping skillsFour 45 min videoconferencing sessions with a therapist, a website that provides patients with training materials and information, social networking, and daily assessments used to personalise videoconferencing sessions
Kenfield et al., 2019 [101]USARCTProstate cancer patients 76Website, wrist-worn wearable (Fitbit), text messagesFacilitate adoption of lifestyle changesWebsite included information and recommendations on four topic areas (get active, eat well, stop smoking, and find support); wearable used to track activity levels, text messages used to reinforce adoption, and continued repetition of the recommendations
Kim et al., 2018 [102]South KoreaRCTBreast cancer patients 72Smartphone-based gameFacilitate patient education3-week programme using typical multiplayer, social network, and platform-based features
Kim et al., 2016 [103]USAQualitative study nested within an RCTCancer patients receiving chemotherapy12Tablet-based applicationPromote active patient engagement and improve care coordinationPersonalised social network built around a patient for collaboration with others involved in their care to enable patient-centred health
Kokts-Porietis et al., 2019 [25]CanadaQualitative study Breast cancer survivors 28Wrist-worm wearable (Polar A360®) Physical activity monitoringActivity tracker with a built-in heart rate sensor
Kondylakis et al., 2020 [104]ItalyProspective pilot studyBreast and prostate cancer patients135ICT platformAid cancer care and symptom managementIntegrated platform containing serious games, psychoemotional monitoring, a personal health system, and a decision support tool
Kubo et al., 2019 [105]USARCTCancer patients receiving chemotherapy82Website and smartphone-based applicationMindfulness training programmeCommercially available mindfulness programme (HeadspaceTM)
Lamaj et al., 2022 [38]USA, SpainMixed methods observational studyCancer patients receiving chemotherapy154Medical device based on optical imaging (PointCheck)Neutropenia monitoringNon-invasive device operating through imaging the blood flowing through the capillaries in the finger
Lambert et al., 2022 [106]CanadaRCTProstate cancer patients 49Web-based platformDelivery of a psychosocial and physical activity self-management programmePlatform including five modules: needs assessment, goal setting and action planning, coping planning, sources of support and motivational tools, celebrating successes achieved, and an information library
Lee et al., 2018 [107]South KoreaRetrospective review of prospectively collected dataBreast cancer survivors88Smartphone-based application, wearableSelf-exercise programme provisionApplication providing individual aerobic and resistance training programmes provided by physiatrists; pedometer (InBodyBand) for step count
Livingston et al., 2006 [108]AustraliaRCTMale colorectal and prostate cancer patients100Telephone serviceProvide support and care informationPhone calls by nurse counsellors to patients on a range of cancer information and management issues
Livingston et al., 2020 [109]AustraliaRCTNewly diagnosed cancer patients43Smartphone/tablet-based applicationProvide support and care informationFeatures include information provision on cancer symptom management and care services, self-report questionnaires, medical appointment diary, and scheduling
Loh et al., 2022 [110]USAProspective pilot studyOlder patients with myeloid neoplasms38Website, smartphone-based application, wearable deviceHome-based individually tailored exercise programme provision and monitoring of physical activityWeb-based clinician dashboard for patient physical activity monitoring, app for self-reporting of physical activity and provision of exercise prescriptions, wearable activity tracker for step count
Lopez et al., 2021 [111]CanadaQualitative component of a multi-method studyCancer survivors12Videoconferencing platformDelivery of cancer rehabilitation programmesPublicly funded virtual care platform developed by the Ontario Telemedicine Network
Lozano-Lozano et al., 2019 [112]SpainProspective feasibility studyBreast cancer survivors80Smartphone-based applicationPatient monitoring and provision of feedback on healthy eating and physical activityFeatures included self-report questionnaires, notifications on daily energy balance, and recommendations on physical activity and diet
Lucas et al., 2018 [113]USAQualitative component of a mixed methods studyBrain and lung cancer patients3Smartphone-based application, wearable deviceRemote monitoring of patients’ health status App for symptom self-reporting; wearable sensor (Mio Alpha Sports Watch) for heart rate and physical activity monitoring
Lyons et al., 2015 [114]USAProspective observational studyBreast cancer survivors31Telephone serviceDelivery of an intervention to optimise functional recoveryTelephone-delivered sessions on exercise, managing stress, and functioning better at work and home
Ma et al., 2021 [33]USAProspective observational studyHead and neck cancer patients undergoing radiation therapy84Automated chatbotSymptom reporting and self-management education provisionInteractive Web-based communication system
MacDonald et al., 2020 [115]CanadaProspective pilot studyCancer survivors35Smartphone-based application, wearable device, telephone service, Web-based platformDelivery of a rehabilitation and exercise programmeApp (Physitrack®) providing progressive exercise prescription, wearable (Fitbit) for activity tracking, telephone calls for health coaching, online learning platform comprising self-management e-modules
Mark et al., 2008 [116]USASurvey studyPatients with various cancer types100Tablet-based platformEnabling patient symptom screening and reportingPen-based e/tablet that operates through a wireless network hosting a platform providing symptom assessment questionnaires
Matthew et al., 2007 [117]CanadaRCTProstate cancer patients152Personal digital assistantPatient health-related quality-of-life monitoringPDA using stylus for completion of self-reported questionnaires
McCann et al.,
2009 [118]
UKRCTBreast, lung, and colorectal cancer patients 56Mobile-based platform (ASyMS©)Symptom monitoring and managementPlatform developed for completion of self-reported symptom questionnaire and input of physiological data, including a risk model for alerting health professionals to the presence of persistent/urgent symptoms
Meropol et al., 2016 [40]USARCTPatients with various cancer types623Web-based applicationEducation on patient participation in clinical trialsPlatform delivering tailored educational content based on assessed patients’ knowledge and attitudinal barriers
Milbury et al., 2022 [119]USAPilot RCTFemale non-small cell lung cancer patients54Videoconferencing platform (Zoom)Mindfulness training or psychoeducation deliveryPlatform accessed through patients’ own devices to attend sessions led by specialists certified in mindfulness-based stress reduction
Mirkovic et al., 2014 [47]NorwayMixed methods studyPatients with various cancer types7Smartphone- tablet-based applicationEnabling the management of health-related issuesApp developed using οpen-source framework for building cross-platform mobile apps (PhoneGap) containing four features; messaging with health professionals, symptom assessment, symptom management information, forum to connect with peers
Myall et al., 2015 [120]UKQualitative process evaluation of an exploratory RCTPatients following primary cancer treatment12Web-based platformSelf-management of cancer-related fatiguePlatform features included self-reported assessments, educational sessions, and guidance for structured activities
Nguyen et al., 2017 [26]AustraliaQualitative studyBreast cancer survivors14Wearable activity trackersIncreasing physical activity and reducing sedentary behaviourSix devices used: Fitbit One, Jawbone Up24, Garmin Vivofit2, Garmin Vivosmart, Garmin Vivoactive, and Polar A300; selected for providing a step count function and an associated app
Nguyen et al., 2019 [121]NetherlandsRCTNewly diagnosed cancer patients232Mode-tailored websitesPatient education as preparation before consultation on diagnosis and treatmentFour different versions of website developed containing the same information, presented in different modalities (via text, images, and/or patient videos)
Nimako et al., 2013 [39]UKProspective pilot studyOncology patients receiving chemotherapy10Telemonitoring systemBlood, body temperature, and symptom monitoringSystem consisted of a small point of care haematology analyser, coupled to a telecommunication hub (tele-hub), enabling patients to self-test their own blood count. The tele-hub consists of a touch screen and keypad and acts as the patient interface, communicating results to a server
O’Brien et al., 2020 [122]AustraliaOnline surveyFemale breast cancer patients202Interaction database (IMgateway)Patient education on complementary and alternative medicineDatabase sets out potential interactions between various complementary and alternative medicines and pharmaceutical drugs
Ormel et al., 2018 [123]NetherlandsRandomised feasibility studyPatients with various cancer types16Smartphone-based applicationSelf-monitoring of physical activityExisting GPS fitness-tracking app for iOS and Android
Owens et al., 2020 [124]USAQualitative studyAfrican American lung cancer survivors12Smartphone-based applicationEducation on strategies to combat symptoms related to lung cancerApp (Breathe Easier) contains a combination of audio-directed breathing practices, meditations, and yoga exercises demonstrated using instructional text and images of African American and Caucasian adults aged 55 years or older performing various poses
Ownsworth et al., 2022 [125]AustraliaMixed methods pilot studyBrain tumour patients8Videoconferencing platformDelivery of psychological supportPlatform (Metro South telehealth portal) used by health professionals to provide remote consultations to people in their own homes or local health services
Pavic et al., 2020 [126]SwitzerlandProspective observational studyPalliative cancer patients30Smartphone-based application, wearableMonitoring of patients’ vital signs, physical activity, and symptomsApp consisted of a patient interface providing digital questionnaires to rate subjective pain and distress, a sensor logging module for recording and transmitting signals from smartphone sensors, and an interface to record wearable sensor signals and transmit these to a secured server. Wearable is a sensor-equipped upper-arm bracelet (Biovotion) measuring physiological and activity parameters
Peipert et al., 2021 [127]USARCTBreast or colorectal cancer patients65Interactive platform, touch-screen deviceEducation provision on cancer care and treatment optionsMultimedia touch-screen device for data collection; educational software with the option to select modules of interest
Pope et al., 2019 [29]USAProspective pilot studyBreast cancer survivors10Smartphone-based application, social media platform, wearable accelerometerMonitoring and promoting physical activity and overall health Commercially available GPS tracking physical activity app (MapMyFitness), Facebook for intervention delivery, Actigraph GT3X+ accelerometer for physical activity assessment
Post et al., 2013 [128]USAPilot RCTBreast cancer patients undergoing chemotherapy27Personal digital assistantDelivery of educational videos on symptom communicationLow-tech, non-interactive device used for the delivery of race-concordant videos on how to communicate about pain, depression, and/or fatigue
Price and Brunet, 2021 [129]CanadaProspective mixed methods studyYoung adult cancer survivors7Videoconferencing platformDelivery of a behaviour-change intervention for promoting physical activity and fruit and vegetable consumptionTeleconferencing technology of participants’ choosing (e.g., Skype)
Purdy et al., 2022 [130]CanadaProspective feasibility studyMultiple myeloma patients29Online applicationDelivery of a home exercise programmeNon-commercial app developed by the University of Alberta (HEAL-Me) providing virtually supervised group workouts, independent home workouts, and independent aerobic exercise
Puszkiewicz et al., 2016 [131]UKProspective one-arm, pre–post studyCancer survivors11Smartphone-based applicationPromoting physical activityCommercial app (GAINFitness) for iOS operating platform providing a physical activity programme based on users’ goals, fitness levels, and equipment they have access to
Reilly et al., 2021 [48]UKQualitative component of a pilot RCTCutaneous melanoma patients13Tablet-based applicationEnabling total self-skin examinationApp hosted on Android tablets including an individualised digital skin map and the ability to send electronic reports of any skin concerns, including photographs, to a remote Dermatology Nurse Practitioner
Rezaee et al., 2022 [132]IranProspective observational studyBreast cancer survivors25Smartphone-based applicationProviding educational content to improve resilience and quality of life App developed with the component-based programming approach and user interface developed within the Android Studio environment, including features on the calculation of resilience scores, exercise programmes, patient assessments, and experience sharing among peers
Richards et al., 2020 [133]UKMixed methods prospective pilot studyPatients after discharge following cancer-related upper gastrointestinal surgery40Web-based platformEnabling remote symptom monitoringSystem components include a patient website, a Web-based symptom-report questionnaire software, and a Web application interface for the secure transfer of data to electronic health records. Algorithms are programmed into self-report scoring system, allowing severity-specific tailored self-management advice to be provided to patients
Rossi et al., 2018 [27]USAProspective observational studyEndometrial cancer survivors30Wrist-worn wearable (Fitbit)Physical activity monitoringFitbit Alta™ used for step count
Ruland et al., 2013 [134]NorwayQuestionnaire-based survey nested within an RCTBreast and prostate cancer patients103Web-based applicationIllness management supportApp developed at the Oslo University Hospital that includes components on symptom assessment, self-management information and activities, information on condition and treatment options, and communication with peers and health professionals
Ruland et al., 2003 [135]NorwayPilot RCTCancer outpatients52Tablet-based applicationProvision of patient support on shared decision-making in symptom managementApp components include a symptom assessment tool, shared decision-making, and a care-planning component highlighting to clinicians symptoms patients are experiencing
Russell et al., 2019 [136]AustraliaPilot RCTMelanoma patients69WebsiteDelivery of mindfulness interventionFeatures included short videos and downloadable PDF transcript of the videos, MP3 audio files of guided meditations, general information about meditation
Skrabal Ross et al., 2022 [137]AustraliaProof-of-concept trialCancer patients receiving oral chemotherapy22Online SMS gateway, medication adherence monitoring device (MEMS device)Supporting adherence to oral chemotherapySMS consisted of a one-way (no need to reply) message used to provide reminders to take oral chemotherapy and information about the management of side-effects via hyperlinks to portable document format online documents. MEMS consisted of a pill bottle with a cap that contains a microelectronic chip and tracks the date and time the medication bottle cap is opened and, therefore, the assumed dose taken
Smith et al., 2022 [138]AustraliaQualitative studyAdult cancer patients13Various telephone and video telehealth platformsDelivery of clinical consultationsTelephone and videoconferencing used to facilitate real-time communication between health professionals, patients, and caregivers during the COVID-19 pandemic
Song et al., 2021 [41]USAPilot feasibility studyProstate cancer patients62Web-based programmeDelivery of couple-focused patient educationProgramme accessible from patients’ preferred devices (e.g., smartphone, tablet, or computer), including modules about how couples can work effectively as a team, assess and manage prostate cancer treatment-related side-effects and symptoms, and improve healthy behaviours, and a social support feature with post-module assignments, a moderated online forum, meetings with a health educator, and a resource centre
Spoelstra et al., 2016 [139]USARCTPatients with various cancer types75SMS over networks of mobile operators Promoting adherence to oral anticancer agent medicationText messages developed according to Social Cognitive Theory using 160 characters or less, delivered through an automated platform storing associated data
Stephen et al., 2014 [140]CanadaQualitative studyCancer patients and survivors80Online chat platformDelivery of professionally led cancer support groupsSynchronous text communication in password-protected chat rooms
Sundberg et al., 2015 [141]SwedenProspective observational studyProstate cancer patients receiving radiotherapy9ICT platform for smartphone useAiding the early assessment and management of patient-reported symptomsPlatform components include patient symptom assessments, a risk assessment model based on symptom occurrence and frequency sending alerts to nurses by text message if symptoms are of concern, continuous access to self-care advice related to symptoms and links to relevant websites, and symptom history presented in graphs over time
Suzuki et al., 2016 [49]Japan Prospective observational studyCancer patients receiving radiation therapy152Tablet-based software Delivery of a psychosocial questionnaireElectronic touch-screen tablet operated via a stylus used for the completion of patient reported outcomes
Valle et al., 2017 [142]USAPilot RCTAfrican American breast cancer survivors35Wireless scale, wearable activity tracker, Web-based platformPromoting weight gain prevention through self-regulation behavioursActivity tracker (Withings Pulse) interfaced with a Bluetooth and Wifi-enabled wireless scale (Withings WS-30, Cambridge, MA) and synced data to a single online account accessed through a mobile app or website which contained graphs of weight and physical activity trends
Van Blarigan et al., 2019 [143]USAPilot RCTColorectal cancer survivors42SMS over networks of mobile operators, wrist-worn wearable (Fitbit)Promoting increases in physical activityDaily text messages providing physical activity prompts and recommendations; Fitbit Flex wristband for tracking physical activity, including steps, distance, active minutes, and calories burned
Van der Linden et al., 2021 [144]NetherlandsRCTBrain tumour patients62Tablet-based applicationDelivery of cognitive rehabilitation programmeApp containing educational modules on cognitive functions, influences, compensation, attention, planning and control, and memory. In each module, information about cognitive functions is given and compensatory strategies are provided, together with fill-in exercises to practice the strategies
Visser et al., 2018 [50]NetherlandsRCTBreast cancer patients109Tablet-based applicationsDelivery of support group sessions, clinical contact, and illness-specific information iPad containing existing apps connected through a shared iCloud account for each group (iBooks for educational materials, FaceTime for remote group sessions, contact app including the email addresses of participants, clinical nurse specialist, and the researcher. Calendar app containing dates of the scheduled video sessions)
Vogel et al., 2019 [145]USAPilot RCTOvarian cancer patients104Smartphone-based applicationProvide information on the usefulness of genetic counsellingiOS (Apple) app providing educational materials on genetic counselling and motivational messages, positive feedback, videos, graphics, and triggers to encourage app use
Vogel et al., 2013 [51]USARCTOvarian cancer patients35WebsitePromoting advance care planningPrototype website developed using Microsoft. NET framework with Ajax to bring together the HTML and CSS at the front end, and Internet Information Services for Microsoft Windows Servers, an SQL database, and SSL encryption at the back end
Walle et al., 2020 [146]GermanyRCTPatients with solid tumours undergoing cancer therapy66Videoconferencing applicationDelivery of follow-up clinical consultationsThe Minxli—Arzt via Video Chat application for smartphones was utilised, including features for scheduling encrypted video calls with verified physicians and a chat function with options to upload pictures
Wallwiener et al., 2017 [147]GermanyProspective feasibility studyAdvanced breast cancer patients15Web-based platformEnabling reporting of patient-reported outcomesReal-time registry containing molecular data adapted to include patient-reported outcomes
Wan et al., 2021 [52]SingaporeDevelopment and evaluation studyPatients undergoing elective colorectal cancer surgeries5Smartphone-based applicationImproving health outcomes for patients and family caregivers App on BuddyCare platform encompassing the following features: a surgical timeline (29-day perioperative phase where users receive information packages listing important tasks about how to prepare for surgery, postsurgery monitoring, and discharge care), search functionality, introduction to mindfulness-based practices, daily tasks, alerts, reminders, motivational messages
Waterland et al., 2021 [148]AustraliaImpact evaluation study Patients preparing for major cancer surgery31Videoconferencing platform Delivery of prehabilitation education sessionZoom used for webinar delivery
Weaver et al., 2007 [149]UKProspective observational studyColon cancer patients6Mobile telephone-based softwareSymptom monitoring and managementPatients self-reported symptoms using the phone keypad; data were automatically transmitted to a dedicated server. Each patient’s cumulative toxicity chart was displayed both on individualised Web pages (for review by the study nurse) and on the patient’s phone (for information). If incoming readings gave rise to concern, alerts were generated according to criteria stored both on the phone and the server, and appropriate management actions were communicated to patients
Wickline et al., 2022 [150]USAMixed methods studyAdvanced ovarian cancer patients134Web-based programmeEnabling symptom monitoring and self-managementSystem where patients can report and track their symptoms, quality-of-life measures, and decision-making preferences during cancer therapy, delivering self-care instructions targeted to reports of moderate–severe symptoms and providing tips on symptom communication with clinicians
Wilkie et al., 2003 [151]USAMixed methods studyCancer inpatients and outpatients116Desktop-based softwareEnabling pain assessmentMicrosoft® Windows 95/98 personal desktop computer with a touch-screen (Elo™ monitor) was used to complete the electronic version of the McGill Pain Questionnaire
Wu et al., 2021 [152]UKProspective observational studyPatients awaiting cancer treatment139Telephone or video callsDelivery of a prehabilitation education programmeTelephones or videoconferencing platforms used to deliver home-based prehabilitation including personalised training exercises, dietary advice, medical optimisation therapies, and psychological support
Yap et al., 2013 [153]SingaporeProspective observational studyAmbulatory cancer patients60SMS over networks of mobile operatorsChemotherapy-induced nausea and vomiting managementSeries of questions sent via SMS daily for 5 days post-chemotherapy, following a predeveloped clinical algorithm in consultation with clinical pharmacists; each SMS contained several options in which patients were required to respond by selecting the option number that best reflected their symptoms
Zini et al., 2019 [154]ItalyProspective pilot studyHead and neck cancer patients undergoing concurrent chemo-radiotherapy10Smartphone-based applicationReporting of clinical parameters, quality of life, and symptoms App running on Android designed to collect patients’ symptoms, clinical parameters, and provide educational materials, daily self-management suggestions, therapy-cost recording, and peer networking and facilitate interactions with clinicians
Table 3. Cancer patients’ perceptions of digital health technologies.
Table 3. Cancer patients’ perceptions of digital health technologies.
SystemInformation/ContentServiceOther
Ease of UseEase of LearningEase of Set-UpSystem FlexibilitySystem ReliabilitySystem SecurityPerformanceVisual AppealUsefulnessRelevanceClarityComprehensivenessComprehensibilityReliabilityTailored InformationInformation QuantityPresentation Format Inclusive LanguageTechnical Support Instructions/TrainingFeedback/Follow-UpComfort of Use Battery Life/PortabilityCoverage/ConnectivityPeer InteractionInteraction with CliniciansTime ConsiderationsAccess to Data
Abernethy et al., 2009 [53]X X X X
Admiraal et al., 2017 [54] X XX
Aiello et al., 2006 [55]X X
Albrecht et al., 2011 [56] X XXX XX
Allenby et al., 2002 [34]X X X XX X
Allicock et al., 2021 [30] X X XX X X
Alshoumr et al., 2021 [57]X X XXX X X X
Appleyard et al., 2021 [58]X X X X
Badr et al., 2016 [59]X X XXX XXX X X XX
Basch et al., 2007 [60]X X X
Basch et al., 2017 [61]X X X X
Basch et al., 2020 [62]X XX X XX
Beaver et al., 2012 [63] X X
Beaver et al., 2009 [64] X X X
Bender et al., 2022 [65]X X X X X
Bender et al., 2013 [66]X X X X X
Bennett et al., 2016 [67]X X XX
Benze et al., 2019 [68]X X X
Bol et al., 2013 [69] X X X X
Bolle et al., 2016 [70]XX XX XXX X X
Brennan et al., 2022 [71]X X X XXXXX
Cadmus-Bertram et al., 2019 [72] X X X
Chaix et al., 2019 [31]X X X X X
Chee et al., 2017 [73] X X X
Cheville et al., 2018 [74]X X X
Childes et al., 2017 [42] X X X X
Chow et al., 2021 [28]X X X X XX XX
Chow et al., 2019 [75]XX X X X XX
Cleeland et al., 2011 [76]X X
Collins et al., 2017 [77]X X XX
Crafoord et al., 2020 [78]XX X XX X X XXX
Crawford et al., 2019 [79] XXX X X X X X X
Denis et al., 2014 [80]X X
Duffecy et al., 2013 [81] X X
Eakin et al., 2012 [82] X X
Ferguson et al., 2016 [83] X X
Finlay et al., 2020 [46] X XX
Foley et al., 2016 [84] X X
Fu et al., 2016 [85]XX X XXXXXX X
Galiano-Castillo et al., 2016 [86] X X X X X
Galsky et al., 2017 [87]X X
Gell et al., 2017 [88]X X X
Gilbertson-White et al., 2019 [89]XX XX XX X
Girgis et al., 2017 [35]X X XXXXXXX X XX
Graetz et al., 2018 [90] X XX
Greenway et al., 2022 [36]X XXX XX XX
Greer et al., 2019 [32] X X
Groarke et al., 2021 [91] X X X
Gustavell et al., 2020 [92] X X XXX
Harless et al., 2009 [37]X X X X
Head et al., 2011 [93]X X X X X
Head et al., 2009 [94] X X X X
Heiney et al., 2012 [95] X X
Hochstenbach et al., 2016 [96]XX X XX XX X X X
Jacobsen et al., 2022 [24] XX
Kanera et al., 2016 [97] XX X
Katz et al., 2016 [98] X X X
Kearney et al., 2006 [99]X X X X
Kelleher et al., 2019 [100] X
Kenfield et al., 2019 [101] X X X XX
Kim et al., 2018 [102]X X X
Kim et al., 2016 [103]X X X X
Kokts-Porietis et al., 2019 [25] X X X
Kondylakis et al., 2020 [104]X X
Kubo et al., 2019 [105] X X X X X
Lamaj et al., 2022 [38]XX X
Lambert et al., 2022 [106]X X XX X
Lee et al., 2018 [107]X X X X
Livingston et al., 2006 [108] X X XX
Livingston et al., 2020 [109]XX X X X
Loh et al., 2022 [110] X XXX
Lopez et al., 2021 [111] X X X
Lozano-Lozano et al., 2019 [112] X XXXX X X
Lucas et al., 2018 [113]X X XX X XX X X
Lyons et al., 2015 [114] XX X
Ma et al., 2021 [33]X X X
MacDonald et al., 2020 [115] X X X XXXX
Mark et al., 2008 [116]X X X
Matthew et al., 2007 [117] X X X
McCann et al., 2009 [118]X X X X X XX
Meropol et al., 2016 [40] X XX X
Milbury et al., 2022 [119]X X X X XX
Mirkovic et al., 2014 [47]X X XXX X
Myall et al., 2015 [120]X X X X X X X
Nguyen et al., 2017 [26]XXX X XX X XX XXXX
Nguyen et al., 2019 [121] X X X
Nimako et al., 2013 [39]X X X X XX
O’Brien et al., 2020 [122]X XX X X
Ormel et al., 2018 [123] X X
Owens et al., 2020 [124] X X X
Ownsworth et al., 2022 [125] X X X X X
Pavic et al., 2020 [126]X XXX X XX X X
Peipert et al., 2021 [127] X X
Pope et al., 2019 [29] X X X
Post et al., 2013 [128]X X X
Price and Brunet, 2021 [129] X X X
Purdy et al., 2022 [130]XX X X
Puszkiewicz et al., 2016 [131] X XX X
Reilly et al., 2021 [48] X X X
Rezaee et al., 2022 [132]XX X XX X X
Richards et al., 2020 [133] X X XX X X X X X X
Rossi et al., 2018 [27]XXX X
Ruland et al., 2013 [134] X XX
Ruland et al., 2003 [135]XX X X X
Russell et al., 2019 [136] X X X X X
Skrabal Ross et al., 2022 [137] XX X
Smith et al., 2022 [138] X X X XX
Song et al., 2021 [41]X X
Spoelstra et al., 2016 [139] X
Stephen et al., 2014 [140] X X X X
Sundberg et al., 2015 [141]X X X X X XXX
Suzuki et al., 2016 [49]X X X
Valle et al., 2017 [142]X X X
Van Blarigan et al., 2019 [143] X X
van der Linden et al., 2021 [144]X X X X
Visser et al., 2018 [50] X XX
Vogel et al., 2019 [145]X X XXX
Vogel et al., 2013 [51]X XX X X
Walle et al., 2020 [146]X X X X
Wallwiener et al., 2017 [147]X X X
Wan et al., 2021 [52] XXX XX
Waterland et al., 2021 [148]X X X
Weaver et al., 2007 [149]X X X
Wickline et al., 2022 [150]X XX X X
Wilkie et al., 2003 [151]X XXX X X XX
Wu et al., 2021 [152] X X X
Yap et al., 2013 [153] X X XX XX
Zini et al., 2019 [154]X X X X X

4. Discussion

4.1. Main Findings

This scoping review aimed to identify and synthesise existing evidence on cancer patients’ perspectives and requirements for patient-facing digital health technologies. We found 128 studies published between 2002 and 2022 reporting on users’ perceptions and evaluations of patient-centred digital technologies intended to be used as part of cancer patients’ care. A significant surge in publications was observed from 2013 onwards (n = 110, 85.9%), suggesting a growing interest and investment in leveraging digital solutions to address cancer care needs. Identified technologies predominantly comprised Web-based software or platforms (n = 53), mobile or smartphone devices and/or applications (n = 33), remote sensing and wearable technologies (n = 17) used either in combination with other technologies (n = 13) or as standalone digital applications (n = 4), and telephone-based services and tools (n = 13). This diverse range of technologies mirrors the broader technological advancements seen in healthcare, where the emphasis on user-centred design and accessibility has propelled the development and deployment of a wide array of digital tools tailored to specific patient populations [155]. The perceived usefulness of technologies for the management of patients’ symptoms and overall conditions (n = 86), their user-friendliness in terms of ease of use (n = 70), their ability to facilitate patient–clinician interactions (n = 50), and the time investment required to operate the technologies (n = 33) were the most frequently reported technological requirements considered by cancer patients.
The delivery of interventions mostly aiming to educate patients on the self-management of their care (n = 77) and the systematic reporting and/or monitoring of patients’ symptoms and physiological parameters (n = 39) constituted the principal purposes of technology employment among the included studies. Similar findings were reported in previously published reviews investigating the applications of digital technologies in patients living with chronic conditions, such as dementia [156] and serious mental illness [157]. This suggests that people with complex and ongoing healthcare needs may have broadly similar requirements and needs for the digital technologies employed to aid their care regardless of their individual diagnoses.
Limited digital literacy is a common barrier to digital technology adoption among clinical populations [7,15]. Patients need to have the necessary skills to engage with digital tools independently and meaningfully. These skills comprise a patient’s digital literacy [11]. The user-friendliness of technologies (n = 70), receiving appropriate instructions and/or training in setting up and engaging with technologies, and technical support being readily available for the duration of interactions with technologies (n = 9) were identified as key requirements by patients participating in the studies included in this review. These requirements together with end-users’ digital literacy levels ought to be considered by digital technology companies when designing and developing tools for health purposes so that these can accommodate patients with varying digital literacy levels and ensure that all patients can benefit from digital tools [11].
Patients in a large proportion of studies (n = 50) considered the ability of digital technologies to facilitate patient–clinician communication and interaction an important feature of these tools. Previous research has found that the use of digital health interventions can positively influence patient–clinician communication and relationships by enabling patients to feel more comfortable about disclosing information to their clinicians and by reducing the imbalance of power between the patient and clinician [158,159]. For this to be achieved, it is critical that clinicians work collaboratively with patients to establish mutually agreed goals, boundaries, and expectations for technology engagement [160]. Failing to set and adhere to these may lead to the overburdening of clinical staff, patients experiencing disappointment and frustration, and, ultimately, challenged patient–clinician relationships [161,162]. Given than the ethical implications of digital health communication are complex in terms of the boundaries of the patient–clinician relationship and the professional duty of care, there is a need for guidelines on good practice in the use of technology-enabled communication to be established both at the institutional and national levels [158].
In line with previous research, technological features that enable the personalisation of information and care were highly endorsed by cancer patients participating in studies included in the present review [15,163]. In the context of digital technology, personalisation refers to the process of tailoring the user experience of a digital tool to an individual’s specific needs, preferences, behaviours, and characteristics [15]. In this review, the extent to which the content presented through technologies was tailored (n = 18) and relevant (n = 23) to the patients’ individual situations and was perceived as useful for the management of their own care (n = 86) were identified as desirable technological characteristics. The personalisation of information and content received through digital health technologies has been shown to empower patients to have greater ownership over the management of their health and to contribute towards shifting the power balance from health providers making care decisions on behalf of patients to a shared decision-making process [15,164]. It is thus recommended that a personalised approach is undertaken in the development and operation of digital health technologies as it could be pivotal in increasing patient engagement with their care [15].
Almost all studies included in this review (n = 120) reported predominantly positive appraisals of patient-facing digital technologies in terms of acceptability, feasibility, and/or utility. Since studies were not evaluated for their methodological quality, as this was outside the scope of the present review, any reported findings by individual studies should be interpreted with caution. Nevertheless, these findings echo those of other research, suggesting that cancer patients may be overall amenable to the incorporation of digital health technologies into their care [165,166]. Therefore, future research should direct its efforts into exploring strategies for the successful implementation of digital health technologies into routine cancer care practice, including the identification of both individual- and institutional-level barriers and facilitators to the sustainable long-term use of such technologies in this context. The findings from the present review could contribute to this direction by providing evidence to guide investigations into the technology-associated parameters influencing patients’ decisions regarding the adoption of such technologies.

4.2. Strengths and Limitations

A comprehensive approach to locate relevant articles was undertaken in this review, using three databases and a combination of subject headings and free-text terms without applying any date restrictions and performing a rigorous forward and backward citation search for all records meeting the inclusion criteria. Nevertheless, there may have been publications which were missed. The identification of 21 additional eligible publications through citation searching may be suggestive of this. Moreover, the exclusion of grey literature and non-English-language publications may mean that studies providing evidence on cancer patients’ perspectives and requirements for patient-facing digital technologies published outside the traditional academic channels or in languages other than English were also missed. Despite these limitations, a large number of eligible studies were identified and included in this review (n = 128), enabling a rich synthesis of evidence.
In line with the broad scope of this review, studies reporting on cancer patients’ perceptions of digital technologies employed for their care were considered eligible for inclusion regardless of their research design or the methods employed for the assessment of patients’ perceptions. However, more than half of the included studies (n = 68) used either standardised or ad hoc questionnaires as their primary means of evaluating patients’ perceptions of digital health technologies. This means that the technological parameters considered by patients were limited to those included in the measures used by individual studies. It is possible, therefore, that the patient requirements presented in this review do not adequately reflect all technological parameters considered important by cancer patients, and that potentially relevant technological requirements were missed. Furthermore, although no restrictions on cancer type were applied in our search, a large number of the included studies (n = 75) were conducted with breast, prostate, lung, colorectal, and head and neck cancer patients and survivors. Hence, the reported findings may not capture the views of or be applicable to cancer patient and survivor populations outside of those represented in the present review.

5. Conclusions

To the authors’ knowledge, the present scoping review is the first to systematically map and synthesise the existing evidence on cancer patients’ perspectives and requirements for patient-facing digital technologies. An increasing number of studies are using digital technologies to support cancer care. These predominantly comprise Web-based software/platforms, mobile or smartphone devices and/or applications, and remote sensing and wearable technologies, mostly employed for the delivery of self-management interventions and the monitoring of patients’ symptoms and physiological parameters. Several technological features and parameters are considered important by cancer patients. Of these, the most commonly reported include the utility of technologies in enabling the management of patients’ symptoms and overall conditions, their user-friendliness, and their ability to facilitate patient–clinician interactions. The findings from this review provide evidence that could inform future research on technology-associated parameters influencing cancer patients’ decisions regarding the uptake and adoption of patient-facing digital health technologies.

Author Contributions

I.L.—Conceptualisation, Evidence Identification and Extraction, Analyses, Writing—Original Draft and Redrafting. A.-M.K.—Conceptualisation, Evidence Identification and Extraction, Analyses, Writing—Original Draft and Redrafting. S.N.—Supervision, Resources, Writing—Review and Editing. L.A.—Resources, Writing—Review and Editing. N.S.—Resources, Writing—Review and Editing. S.P.—Resources, Writing—Review and Editing. I.K.—Resources, Writing—Review and Editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the RELEVIUM project, which received funding from H2020 under grant agreement No. 101057821 (https://www.releviumproject.eu/ accessed on 18 June 2024).

Data Availability Statement

The data presented in this study are available in this article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef]
  2. Leach, C.R.; Weaver, K.E.; Aziz, N.M.; Alfano, C.M.; Bellizzi, K.M.; Kent, E.E.; Forsythe, L.P.; Rowland, J.H. The complex health profile of long-term cancer survivors: Prevalence and predictors of comorbid conditions. J. Cancer Surviv. Res. Pract. 2015, 9, 239–251. [Google Scholar] [CrossRef]
  3. Prager, G.W.; Braga, S.; Bystricky, B.; Qvortrup, C.; Criscitiello, C.; Esin, E.; Sonke, G.S.; Martínez, G.A.; Frenel, J.S.; Karamouzis, M.; et al. Global cancer control: Responding to the growing burden, rising costs and inequalities in access. ESMO Open 2018, 3, e000285. [Google Scholar] [CrossRef]
  4. Shaffer, K.M.; Turner, K.L.; Siwik, C.; Gonzalez, B.D.; Upasani, R.; Glazer, J.V.; Ferguson, R.J.; Joshua, C.; Low, C.A. Digital health and telehealth in cancer care: A scoping review of reviews. Lancet Digit. Health 2023, 5, e316–e327. [Google Scholar] [CrossRef]
  5. U.S. Food & Drug Administration (FDA). What is Digital Health? 2020. Available online: https://www.fda.gov/medical-devices/digital-health-center-excellence/what-digital-health (accessed on 12 July 2023).
  6. National Institute for Health and Care Excellence (NICE). Evidence Standards Framework For Digital Health Technologies. 2018. Available online: https://www.nice.org.uk/corporate/ecd7 (accessed on 12 July 2023).
  7. Kemp, E.; Trigg, J.; Beatty, L.; Christensen, C.; Dhillon, H.M.; Maeder, A.; Williams, P.A.H.; Koczwara, B. Health literacy, digital health literacy and the implementation of digital health technologies in cancer care: The need for a strategic approach. Health Promot. J. Aust. 2021, 32, 104–114. [Google Scholar] [CrossRef]
  8. Pan, L.; Wu, X.; Lu, Y.; Zhang, H.; Zhou, Y.; Liu, X.; Liu, S.; Yan, Q. Artificial intelligence empowered digital health technologies in cancer survivorship care: A scoping review. Asia Pac. J. Oncol. Nurs. 2022, 9, 100127. [Google Scholar] [CrossRef]
  9. World Health Organization (WHO). Global Strategy On Digital Health 2020–2025. 2021. Available online: https://www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf (accessed on 12 July 2023).
  10. Parikh, R.B.; Basen-Enquist, K.M.; Bradley, C.; Estrin, D.; Levy, M.; Lichtenfeld, J.L.; Malin, B.; McGraw, D.; Meropol, N.J.; Oyer, R.A.; et al. Digital Health Applications in Oncology: An Opportunity to Seize. J. Natl. Cancer Inst. 2022, 114, 1338–1339. [Google Scholar] [CrossRef]
  11. Arora, S.; Ryals, C.; Rodriguez, J.A.; Byers, E.; Clewett, E. Leveraging Digital Technology to Reduce Cancer Care Inequities. Am. Soc. Clin. Oncol. Educ. Book 2022, 42, 559–566. [Google Scholar] [CrossRef]
  12. Morris, B.B.; Rossi, B.; Fuemmeler, B. The role of digital health technology in rural cancer care delivery: A systematic review. J. Rural. Health 2022, 38, 493–511. [Google Scholar] [CrossRef]
  13. Osborn, J.; Ajakaiye, A.; Cooksley, T.; Subbe, C.P. Do mHealth applications improve clinical outcomes of patients with cancer? A critical appraisal of the peer-reviewed literature. Support. Care Cancer 2020, 28, 1469–1479. [Google Scholar] [CrossRef]
  14. Jimenez, G.; Spinazze, P.; Matchar, D.; Koh Choon Huat, G.; van der Kleij, R.M.J.J.; Chavannes, N.H.; Car, J. Digital health competencies for primary healthcare professionals: A scoping review. Int. J. Med. Inform. 2020, 143, 104260. [Google Scholar] [CrossRef] [PubMed]
  15. Madanian, S.; Nakarada-Kordic, I.; Reay, S.; Chetty, T.h. Patients’ perspectives on digital health tools. PEC Innov. 2023, 2, 100171. [Google Scholar] [CrossRef] [PubMed]
  16. Helleman, J.; Johnson, B.; Holdom, C.; Hobson, E.; Murray, D.; Steyn, F.J.; Ngo, S.T.; Henders, A.; Lokeshappa, M.B.; Visser-Meily, J.M.A.; et al. Patient perspectives on digital healthcare technology in care and clinical trials for motor neuron disease: An international survey. J. Neurol. 2022, 269, 6003–6013. [Google Scholar] [CrossRef] [PubMed]
  17. Lazarou, I.; Stavropoulos, T.G.; Mpaltadoros, L.; Nikolopoulos, S.; Koumanakos, G.; Tsolaki, M.; Kompatsiaris, I.Y. Human Factors and Requirements of People with Cognitive Impairment, Their Caregivers, and Healthcare Professionals for mHealth Apps Including Reminders, Games, and Geolocation Tracking: A Survey-Questionnaire Study. J. Alzheimer’s Dis. Rep. 2021, 5, 497–513. [Google Scholar] [CrossRef] [PubMed]
  18. Siglen, E.; Vetti, H.H.; Lunde, A.B.F.; Hatlebrekke, T.A.; Strømsvik, N.; Hamang, A.; Hovland, S.T.; Rettberg, J.W.; Steen, V.M.; Bjorvatn, C. Ask Rosa–The making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer. Patient Educ. Couns. 2022, 105, 1488–1494. [Google Scholar] [CrossRef] [PubMed]
  19. Stavropoulos, T.G.; Lazarou, I.; Diaz, A.; Gove, D.; Georges, J.; Manyakov, N.V.; Pich, E.M.; Hinds, C.; Tsolaki, M.; Nikolopoulos, S.; et al. Wearable Devices for Assessing Function in Alzheimer’s Disease: A European Public Involvement Activity About the Features and Preferences of Patients and Caregivers. Front. Aging Neurosci. 2021, 13, 643135. [Google Scholar] [CrossRef] [PubMed]
  20. Woudstra, K.; Reuzel, R.; Rovers, M.; Tummers, M. An Overview of Stakeholders, Methods, Topics, and Challenges in Participatory Approaches Used in the Development of Medical Devices: A Scoping Review. Int. J. Health Policy Manag. 2023, 12, 6839. [Google Scholar] [CrossRef] [PubMed]
  21. Polhemus, A.M.; Kadhim, H.; Barnes, S.; Zebrowski, S.E.; Simmonds, A.; Masand, S.N.; Banner, J.; Dupont, M. Accelerating Adoption of Patient-Facing Technologies in Clinical Trials: A Pharmaceutical Industry Perspective on Opportunities and Challenges. Ther. Innov. Regul. Sci. 2019, 53, 8–24. [Google Scholar] [CrossRef]
  22. Yusof, M.M.; Kuljis, J.; Papazafeiropoulou, A.; Stergioulas, L.K. An evaluation framework for Health Information Systems: Human, organization and technology-fit factors (HOT-fit). Int. J. Med. Inform. 2008, 77, 386–398. [Google Scholar] [CrossRef]
  23. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef]
  24. Jacobsen, M.; Rottmann, P.; Dembek, T.A.; Gerke, A.L.; Gholamipoor, R.; Blum, C.; Hartmann, N.U.; Verket, M.; Kaivers, J.; Jäger, P.; et al. Feasibility of Wearable-Based Remote Monitoring in Patients During Intensive Treatment for Aggressive Hematologic Malignancies. JCO Clin. Cancer Inform. 2022, 6, e2100126. [Google Scholar] [CrossRef] [PubMed]
  25. Kokts-Porietis, R.L.; Stone, C.R.; Friedenreich, C.M.; Froese, A.; McDonough, M.; McNeil, J. Breast cancer survivors’ perspectives on a home-based physical activity intervention utilizing wearable technology. Support. Care Cancer 2019, 27, 2885–2892. [Google Scholar] [CrossRef] [PubMed]
  26. Nguyen, N.H.; Hadgraft, N.T.; Moore, M.M.; Rosenberg, D.E.; Lynch, C.; Reeves, M.M.; Lynch, B.M. A qualitative evaluation of breast cancer survivors’ acceptance of and preferences for consumer wearable technology activity trackers. Support. Care Cancer 2017, 25, 3375–3384. [Google Scholar] [CrossRef] [PubMed]
  27. Rossi, A.; Frechette, L.; Miller, D.; Miller, E.; Friel, C.; Van Arsdale, A.; Lin, J.; Shankar, V.; Kuo, D.Y.S.; Nevadunsky, N.S. Acceptability and feasibility of a Fitbit physical activity monitor for endometrial cancer survivors. Gynecol. Oncol. 2018, 149, 470–475. [Google Scholar] [CrossRef]
  28. Chow, E.J.; Doody, D.R.; Di, C.; Armenian, S.H.; Baker, K.S.; Bricker, J.B.; Gopal, A.K.; Hagen, A.M.; Ketterl, T.G.; Lee, S.J.; et al. Feasibility of a behavioral intervention using mobile health applications to reduce cardiovascular risk factors in cancer survivors: A pilot randomized controlled trial. J. Cancer Surviv. Res. Pract. 2021, 15, 554–563. [Google Scholar] [CrossRef]
  29. Pope, Z.; Lee, J.E.; Zeng, N.; Lee, H.Y.; Gao, Z. Feasibility of smartphone application and social media intervention on breast cancer survivors’ health outcomes. Transl. Behav. Med. 2019, 9, 11–22. [Google Scholar] [CrossRef] [PubMed]
  30. Allicock, M.; Kendzor, D.; Sedory, A.; Gabriel, K.P.; Swartz, M.D.; Thomas, P.; Yudkin, J.S.; Rivers, A. A Pilot and Feasibility Mobile Health Intervention to Support Healthy Behaviors in African American Breast Cancer Survivors. J. Racial Ethn. Health Disparities 2021, 8, 157–165. [Google Scholar] [CrossRef]
  31. Chaix, B.; Bibault, J.E.; Pienkowski, A.; Delamon, G.; Guillemassé, A.; Nectoux, P.; Brouard, B. When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot. JMIR Cancer 2019, 5, e12856. [Google Scholar] [CrossRef]
  32. Greer, S.; Ramo, D.; Chang, Y.J.; Fu, M.; Moskowitz, J.; Haritatos, J. Use of the Chatbot “Vivibot” to Deliver Positive Psychology Skills and Promote Well-Being Among Young People After Cancer Treatment: Randomized Controlled Feasibility Trial. JMIR Mhealth Uhealth 2019, 7, e15018. [Google Scholar] [CrossRef]
  33. Ma, D.; Orner, D.; Ghaly, M.M.; Parashar, B.; Ames, J.W.; Chen, W.C.; Potters, L.; Teckie, S. Automated health chats for symptom management of head and neck cancer patients undergoing radiation therapy. Oral. Oncol. 2021, 122, 105551. [Google Scholar] [CrossRef]
  34. Allenby, A.; Matthews, J.; Beresford, J.; McLachlan, S.A. The application of computer touch-screen technology in screening for psychosocial distress in an ambulatory oncology setting. Eur. J. Cancer Care 2002, 11, 245–253. [Google Scholar] [CrossRef] [PubMed]
  35. Girgis, A.; Durcinoska, I.; Levesque, J.V.; Gerges, M.; Sandell, T.; Arnold, A.; Delaney, G.P. eHealth System for Collecting and Utilizing Patient Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care) Among Cancer Patients: Mixed Methods Approach to Evaluate Feasibility and Acceptability. J. Med. Internet Res. 2017, 19, e330. [Google Scholar] [CrossRef] [PubMed]
  36. Greenway, K.; Frisone, C.; Placidi, A.; Sanjay, K.; Guest, W.; Winter, S.C.; Shah, K.; Henshall, C. Using immersive technology and architectural design to assist head and neck cancer patients’ recovery from treatment: A focus group and technology acceptance study. Eur. J. Oncol. Nurs. 2022, 62, 102261. [Google Scholar] [CrossRef] [PubMed]
  37. Harless, W.G.; Zier, M.A.; Harless, M.G.; Duncan, R.C.; Braun, M.A.; Willey, S.; Isaacs, C.; Warren, R.D. Evaluation of a virtual dialogue method for breast cancer patient education. Patient Educ. Couns. 2009, 76, 189–195. [Google Scholar] [CrossRef] [PubMed]
  38. Lamaj, G.; Pablo-Trinidad, A.; Butterworth, I.; Bell, N.; Benasutti, R.; Bourquard, A.; Sanchez-Ferro, A.; Castro-Gonzalez, C.; Jiménez-Ubieto, A.; Baumann, T.; et al. Usability Evaluation of a Noninvasive Neutropenia Screening Device (PointCheck) for Patients Undergoing Cancer Chemotherapy: Mixed Methods Observational Study. J. Med. Internet Res. 2022, 24, e37368. [Google Scholar] [CrossRef] [PubMed]
  39. Nimako, K.; Lu, S.K.; Ayite, B.; Priest, K.; Winkley, A.; Gunapala, R.; Popat, S.; O’Brien, M.E. A pilot study of a novel home telemonitoring system for oncology patients receiving chemotherapy. J. Telemed. Telecare 2013, 19, 148–152. [Google Scholar] [CrossRef] [PubMed]
  40. Meropol, N.J.; Wong, Y.N.; Albrecht, T.; Manne, S.; Miller, S.M.; Flamm, A.L.; Benson, A.B., 3rd; Buzaglo, J.; Collins, M.; Egleston, B.; et al. Randomized Trial of a Web-Based Intervention to Address Barriers to Clinical Trials. J. Clin. Oncol. 2016, 34, 469–478. [Google Scholar] [CrossRef] [PubMed]
  41. Song, L.; Guo, P.; Tan, X.; Chen, R.C.; Nielsen, M.E.; Birken, S.A.; Koontz, B.F.; Northouse, L.L.; Mayer, D.K. Enhancing survivorship care planning for patients with localized prostate cancer using a couple-focused web-based, mHealth program: The results of a pilot feasibility study. J. Cancer Surviv. Res. Pract. 2021, 15, 99–108. [Google Scholar] [CrossRef] [PubMed]
  42. Childes, J.M.; Palmer, A.D.; Fried-Oken, M.; Graville, D.J. The Use of Technology for Phone and Face-to-Face Communication After Total Laryngectomy. Am. J. Speech-Lang. Pathol. 2017, 26, 99–112. [Google Scholar] [CrossRef]
  43. Bangor, A.; Kortum, P.T.; Miller, J.T. An Empirical Evaluation of the System Usability Scale. Int. J. Hum. Comput. 2008, 24, 574–594. [Google Scholar] [CrossRef]
  44. Stoyanov, S.R.; Hides, L.; Kavanagh, D.J.; Zelenko, O.; Tjondronegoro, D.; Mani, M. Mobile app rating scale: A new tool for assessing the quality of health mobile apps. JMIR Mhealth Uhealth 2015, 3, e27. [Google Scholar] [CrossRef] [PubMed]
  45. Davis, F.D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
  46. Finlay, A.; Evans, H.; Vincent, A.; Wittert, G.; Vandelanotte, C.; Short, C.E. Optimising Web-Based Computer-Tailored Physical Activity Interventions for Prostate Cancer Survivors: A Randomised Controlled Trial Examining the Impact of Website Architecture on User Engagement. Int. J. Environ. Res. Public. Health 2020, 17, 7920. [Google Scholar] [CrossRef] [PubMed]
  47. Mirkovic, J.; Kaufman, D.R.; Ruland, C.M. Supporting cancer patients in illness management: Usability evaluation of a mobile app. JMIR Mhealth Uhealth 2014, 2, e33. [Google Scholar] [CrossRef]
  48. Reilly, F.; Contstable, L.; Brant, W.; Rahman, K.; Durrani, A.; Burrows, N.; Proby, C.; Allan, J.; Johnston, M.; Johnston, D.; et al. Achieving integrated self-directed Cancer aftercare (ASICA) for melanoma: How a digital intervention to support total skin self-examination was used by people treated for cutaneous melanoma. BMC Cancer 2021, 21, 1217. [Google Scholar] [CrossRef]
  49. Suzuki, E.; Mackenzie, L.; Sanson-Fisher, R.; Carey, M.; D’Este, C.; Asada, H.; Toi, M. Acceptability of a Touch Screen Tablet Psychosocial Survey Administered to Radiation Therapy Patients in Japan. Int. J. Behav. Med. 2016, 23, 485–491. [Google Scholar] [CrossRef] [PubMed]
  50. Visser, A.; Prins, J.B.; Jansen, L.; Radema, S.A.; Schlooz, M.S.; van Dalen, T.; van Laarhoven, H.W.M. Group medical consultations (GMCs) and tablet-based online support group sessions in the follow-up of breast cancer: A multicenter randomized controlled trial. Breast 2018, 40, 181–188. [Google Scholar] [CrossRef]
  51. Vogel, R.I.; Petzel, S.V.; Cragg, J.; McClellan, M.; Chan, D.; Dickson, E.; Jacko, J.A.; Sainfort, F.; Geller, M.A. Development and pilot of an advance care planning website for women with ovarian cancer: A randomized controlled trial. Gynecol. Oncol. 2013, 131, 430–436. [Google Scholar] [CrossRef]
  52. Wan, S.W.; Chong, C.S.; Toh, E.L.; Lim, S.H.; Loi, C.T.; Lew, Y.F.H.; Chua, M.C.H.; Jee, X.P.; Liu, G.; Zhu, L.; et al. A Theory-Based, Multidisciplinary Approach to Cocreate a Patient-Centric Digital Solution to Enhance Perioperative Health Outcomes Among Colorectal Cancer Patients and Their Family Caregivers: Development and Evaluation Study. J. Med. Internet Res. 2021, 23, e31917. [Google Scholar] [CrossRef]
  53. Abernethy, A.P.; Herndon, J.E.; Wheeler, J.L.; Day, J.M.; Hood, L.; Patwardhan, M.; Shaw, H.; Lyerly, H.K. Feasibility and Acceptability to Patients of a Longitudinal System for Evaluating Cancer-Related Symptoms and Quality of Life: Pilot Study of an e/Tablet Data-Collection System in Academic Oncology. J. Pain. Symptom Manag. 2009, 37, 1027–1038. [Google Scholar] [CrossRef]
  54. Admiraal, J.M.; van der Velden, A.W.G.; Geerling, J.I.; Burgerhof, J.G.M.; Bouma, G.; Walenkamp, A.M.E.; de Vries, E.G.E.; Schröder, C.P.; Reyners, A.K.L. Web-Based Tailored Psychoeducation for Breast Cancer Patients at the Onset of the Survivorship Phase: A Multicenter Randomized Controlled Trial. J. Pain. Symptom Manag. 2017, 54, 466–475. [Google Scholar] [CrossRef]
  55. Aiello, E.J.; Taplin, S.; Reid, R.; Hobbs, M.; Seger, D.; Kamel, H.; Tufano, J.; Ballard-Barbash, R. In a randomized controlled trial, patients preferred electronic data collection of breast cancer risk-factor information in a mammography setting. J. Clin. Epidemiol. 2006, 59, 77–81. [Google Scholar] [CrossRef] [PubMed]
  56. Albrecht, K.; Simon, D.; Buchholz, A.; Reuter, K.; Frosch, D.; Seebauer, L.; Härter, M. How does a German audience appraise an American decision aid on early stage breast cancer? Patient Educ. Couns. 2011, 83, 58–63. [Google Scholar] [CrossRef] [PubMed]
  57. Alshoumr, B.; Yu, P.; Hailey, D.; Bindayel, F.; Alanazi, S.; Alshammary, S. Understanding cancer patients’ use and perceptions of inpatient portal: A case study at a tertiary hospital in Saudi Arabia. Int. J. Med. Inform. 2021, 148, 104398. [Google Scholar] [CrossRef] [PubMed]
  58. Appleyard, S.E.; Larkin, M.J.W.; Stewart, E.M.; Minton, O.; Gilbert, D.C. Digital Medicine in Men with Advanced Prostate Cancer–A Feasibility Study of Electronic Patient-reported Outcomes in Patients on Systemic Treatment. Clin. Oncol. 2021, 33, 751–760. [Google Scholar] [CrossRef] [PubMed]
  59. Badr, H.; Lipnick, D.; Diefenbach, M.A.; Posner, M.; Kotz, T.; Miles, B.; Genden, E. Development and usability testing of a web-based self-management intervention for oral cancer survivors and their family caregivers. Eur. J. Cancer Care 2016, 25, 806–821. [Google Scholar] [CrossRef] [PubMed]
  60. Basch, E.; Artz, D.; Iasonos, A.; Speakman, J.; Shannon, K.; Lin, K.; Pun, C.; Yong, H.; Fearn, P.; Barz, A.; et al. Evaluation of an Online Platform for Cancer Patient Self-reporting of Chemotherapy Toxicities. J. Am. Med. Inform. Assoc. 2007, 14, 264–268. [Google Scholar] [CrossRef] [PubMed]
  61. Basch, E.; Pugh, S.L.; Dueck, A.C.; Mitchell, S.A.; Berk, L.; Fogh, S.; Rogak, L.J.; Gatewood, M.; Reeve, B.B.; Mendoza, T.R.; et al. Feasibility of Patient Reporting of Symptomatic Adverse Events via the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) in a Chemoradiotherapy Cooperative Group Multicenter Clinical Trial. Int. J. Radiat. Oncol. Biol. Phys. 2017, 98, 409–418. [Google Scholar] [CrossRef]
  62. Basch, E.; Stover, A.M.; Schrag, D.; Chung, A.; Jansen, J.; Henson, S.; Carr, P.; Ginos, B.; Deal, A.; Spears, P.A.; et al. Clinical Utility and User Perceptions of a Digital System for Electronic Patient-Reported Symptom Monitoring During Routine Cancer Care: Findings From the PRO-TECT Trial. JCO Clin. Cancer Inform. 2020, 4, 947–957. [Google Scholar] [CrossRef]
  63. Beaver, K.; Campbell, M.; Williamson, S.; Procter, D.; Sheridan, J.; Heath, J.; Susnerwala, S. An exploratory randomized controlled trial comparing telephone and hospital follow-up after treatment for colorectal cancer. Color. Dis. 2012, 14, 1201–1209. [Google Scholar] [CrossRef]
  64. Beaver, K.; Tysver-Robinson, D.; Campbell, M.; Twomey, M.; Williamson, S.; Hindley, A.; Susnerwala, S.; Dunn, G.; Luker, K. Comparing hospital and telephone follow-up after treatment for breast cancer: Randomised equivalence trial. BMJ (Clin. Res. Ed.) 2009, 338, a3147. [Google Scholar] [CrossRef] [PubMed]
  65. Bender, J.L.; Flora, P.K.; Soheilipour, S.; Dirlea, M.; Maharaj, N.; Parvin, L.; Matthew, A.; Catton, C.; Jamnicky, L.; Pollock, P.; et al. Web-Based Peer Navigation for Men with Prostate Cancer and Their Family Caregivers: A Pilot Feasibility Study. Curr. Oncol. 2022, 29, 4285–4299. [Google Scholar] [CrossRef] [PubMed]
  66. Bender, J.L.; Katz, J.; Ferris, L.E.; Jadad, A.R. What is the role of online support from the perspective of facilitators of face-to-face support groups? A multi-method study of the use of breast cancer online communities. Patient Educ. Couns. 2013, 93, 472–479. [Google Scholar] [CrossRef] [PubMed]
  67. Bennett, A.V.; Dueck, A.C.; Mitchell, S.A.; Mendoza, T.R.; Reeve, B.B.; Atkinson, T.M.; Castro, K.M.; Denicoff, A.; Rogak, L.J.; Harness, J.K.; et al. Mode equivalence and acceptability of tablet computer-, interactive voice response system-, and paper-based administration of the U.S. National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Health Qual. Life Outcomes 2016, 14, 24. [Google Scholar] [CrossRef] [PubMed]
  68. Benze, G.; Nauck, F.; Alt-Epping, B.; Gianni, G.; Bauknecht, T.; Ettl, J.; Munte, A.; Kretzschmar, L.; Gaertner, J. PROutine: A feasibility study assessing surveillance of electronic patient reported outcomes and adherence via smartphone app in advanced cancer. Ann. Palliat. Med. 2019, 8, 104–111. [Google Scholar] [CrossRef] [PubMed]
  69. Bol, N.; Smets, E.M.; Rutgers, M.M.; Burgers, J.A.; de Haes, H.C.; Loos, E.F.; van Weert, J.C. Do videos improve website satisfaction and recall of online cancer-related information in older lung cancer patients? Patient Educ. Couns. 2013, 92, 404–412. [Google Scholar] [CrossRef] [PubMed]
  70. Bolle, S.; Romijn, G.; Smets, E.M.; Loos, E.F.; Kunneman, M.; van Weert, J.C. Older Cancer Patients’ User Experiences With Web-Based Health Information Tools: A Think-Aloud Study. J. Med. Internet Res. 2016, 18, e208. [Google Scholar] [CrossRef] [PubMed]
  71. Brennan, L.; Sadeghi, F.; O’Neill, L.; Guinan, E.; Smyth, L.; Sheill, G.; Smyth, E.; Doyle, S.L.; Timon, C.M.; Connolly, D.; et al. Telehealth Delivery of a Multi-Disciplinary Rehabilitation Programme for Upper Gastro-Intestinal Cancer: ReStOre@Home Feasibility Study. Cancers 2022, 14, 2707. [Google Scholar] [CrossRef] [PubMed]
  72. Cadmus-Bertram, L.; Tevaarwerk, A.J.; Sesto, M.E.; Gangnon, R.; Van Remortel, B.; Date, P. Building a physical activity intervention into clinical care for breast and colorectal cancer survivors in Wisconsin: A randomized controlled pilot trial. J. Cancer Surviv. Res. Pract. 2019, 13, 593–602. [Google Scholar] [CrossRef]
  73. Chee, W.; Lee, Y.; Im, E.O.; Chee, E.; Tsai, H.M.; Nishigaki, M.; Yeo, S.A.; Schapira, M.M.; Mao, J.J. A culturally tailored Internet cancer support group for Asian American breast cancer survivors: A randomized controlled pilot intervention study. J. Telemed. Telecare 2017, 23, 618–626. [Google Scholar] [CrossRef]
  74. Cheville, A.L.; Moynihan, T.; Basford, J.R.; Nyman, J.A.; Tuma, M.L.; Macken, D.A.; Therneau, T.; Satelel, D.; Kroenke, K. The rationale, design, and methods of a randomized, controlled trial to evaluate the effectiveness of collaborative telecare in preserving function among patients with late stage cancer and hematologic conditions. Contemp. Clin. Trials 2018, 64, 254–264. [Google Scholar] [CrossRef] [PubMed]
  75. Chow, P.I.; Drago, F.; Kennedy, E.M.; Chambers, N.; Sheffield, C.; Cohn, W.F. Examining the feasibility, acceptability, and potential utility of mobile distress screening in adult cancer patients. Psycho-Oncology 2019, 28, 1887–1893. [Google Scholar] [CrossRef] [PubMed]
  76. Cleeland, C.S.; Wang, X.S.; Shi, Q.; Mendoza, T.R.; Wright, S.L.; Berry, M.D.; Malveaux, D.; Shah, P.K.; Gning, I.; Hofstetter, W.L.; et al. Automated symptom alerts reduce postoperative symptom severity after cancer surgery: A randomized controlled clinical trial. J. Clin. Oncol. 2011, 29, 994–1000. [Google Scholar] [CrossRef] [PubMed]
  77. Collins, A.; Burns, C.L.; Ward, E.C.; Comans, T.; Blake, C.; Kenny, L.; Greenup, P.; Best, D. Home-based telehealth service for swallowing and nutrition management following head and neck cancer treatment. J. Telemed. Telecare 2017, 23, 866–872. [Google Scholar] [CrossRef] [PubMed]
  78. Crafoord, M.T.; Fjell, M.; Sundberg, K.; Nilsson, M.; Langius-Eklöf, A. Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study. J. Med. Internet Res. 2020, 22, e17058. [Google Scholar] [CrossRef] [PubMed]
  79. Crawford, S.Y.; Boyd, A.D.; Nayak, A.K.; Venepalli, N.K.; Cuellar, S.; Wirth, S.M.; Hsu, G.I.H. Patient-centered design in developing a mobile application for oral anticancer medications. J. Am. Pharm. Assoc. 2019, 59 (Suppl. S2), S86–S95.e1. [Google Scholar] [CrossRef]
  80. Denis, F.; Viger, L.; Charron, A.; Voog, E.; Dupuis, O.; Pointreau, Y.; Letellier, C. Detection of lung cancer relapse using self-reported symptoms transmitted via an internet web-application: Pilot study of the sentinel follow-up. Support. Care Cancer 2014, 22, 1467–1473. [Google Scholar] [CrossRef] [PubMed]
  81. Duffecy, J.; Sanford, S.; Wagner, L.; Begale, M.; Nawacki, E.; Mohr, D.C. Project onward: An innovative e-health intervention for cancer survivors. Psycho-Oncology 2013, 22, 947–951. [Google Scholar] [CrossRef] [PubMed]
  82. Eakin, E.G.; Lawler, S.P.; Winkler, E.A.; Hayes, S.C. A randomized trial of a telephone-delivered exercise intervention for non-urban dwelling women newly diagnosed with breast cancer: Exercise for health. Ann. Behav. Med. 2012, 43, 229–238. [Google Scholar] [CrossRef]
  83. Ferguson, R.J.; Sigmon, S.T.; Pritchard, A.J.; LaBrie, S.L.; Goetze, R.E.; Fink, C.M.; Garrett, A.M. A randomized trial of videoconference-delivered cognitive behavioral therapy for survivors of breast cancer with self-reported cognitive dysfunction. Cancer 2016, 122, 1782–1791. [Google Scholar] [CrossRef]
  84. Foley, N.M.; O’Connell, E.P.; Lehane, E.A.; Livingstone, V.; Maher, B.; Kaimkhani, S.; Cil, T.; Relihan, N.; Bennett, M.W.; Redmond, H.P.; et al. PATI: Patient accessed tailored information: A pilot study to evaluate the effect on preoperative breast cancer patients of information delivered via a mobile application. Breast 2016, 30, 54–58. [Google Scholar] [CrossRef] [PubMed]
  85. Fu, M.R.; Axelrod, D.; Guth, A.A.; Wang, Y.; Scagliola, J.; Hiotis, K.; Rampertaap, K.; El-Shammaa, N. Usability and feasibility of health IT interventions to enhance Self-Care for Lymphedema Symptom Management in breast cancer survivors. Internet Interv. 2016, 5, 56–64. [Google Scholar] [CrossRef] [PubMed]
  86. Galiano-Castillo, N.; Cantarero-Villanueva, I.; Fernández-Lao, C.; Ariza-García, A.; Díaz-Rodríguez, L.; Del-Moral-Ávila, R.; Arroyo-Morales, M. Telehealth system: A randomized controlled trial evaluating the impact of an internet-based exercise intervention on quality of life, pain, muscle strength, and fatigue in breast cancer survivors. Cancer 2016, 122, 3166–3174. [Google Scholar] [CrossRef] [PubMed]
  87. Galsky, M.D.; Shahin, M.; Jia, R.; Shaffer, D.R.; Gimpel-Tetra, K.; Tsao, C.K.; Baker, C.; Leiter, A.; Holland, J.; Sablinski, T.; et al. Telemedicine-Enabled Clinical Trial of Metformin in Patients With Prostate Cancer. JCO Clin. Cancer Inform. 2017, 1, 1–10. [Google Scholar] [CrossRef] [PubMed]
  88. Gell, N.M.; Grover, K.W.; Humble, M.; Sexton, M.; Dittus, K. Efficacy, feasibility, and acceptability of a novel technology-based intervention to support physical activity in cancer survivors. Support. Care Cancer 2017, 25, 1291–1300. [Google Scholar] [CrossRef] [PubMed]
  89. Gilbertson-White, S.; Yeung, C.W.; Saeidzadeh, S.; Tykol, H.; Vikas, P.; Cannon, A. Engaging Stakeholders in the Development of an eHealth Intervention for Cancer Symptom Management for Rural Residents. J. Rural. Health 2019, 35, 189–198. [Google Scholar] [CrossRef] [PubMed]
  90. Graetz, I.; Anderson, J.N.; McKillop, C.N.; Stepanski, E.J.; Paladino, A.J.; Tillmanns, T.D. Use of a web-based app to improve postoperative outcomes for patients receiving gynecological oncology care: A randomized controlled feasibility trial. Gynecol. Oncol. 2018, 150, 311–317. [Google Scholar] [CrossRef] [PubMed]
  91. Groarke, J.M.; Richmond, J.; Mc Sharry, J.; Groarke, A.; Harney, O.M.; Kelly, M.G.; Walsh, J.C. Acceptability of a Mobile Health Behavior Change Intervention for Cancer Survivors With Obesity or Overweight: Nested Mixed Methods Study Within a Randomized Controlled Trial. JMIR Mhealth Uhealth 2021, 9, e18288. [Google Scholar] [CrossRef] [PubMed]
  92. Gustavell, T.; Sundberg, K.; Langius-Eklöf, A. Using an Interactive App for Symptom Reporting and Management Following Pancreatic Cancer Surgery to Facilitate Person-Centered Care: Descriptive Study. JMIR Mhealth Uhealth 2020, 8, e17855. [Google Scholar] [CrossRef]
  93. Head, B.A.; Keeney, C.; Studts, J.L.; Khayat, M.; Bumpous, J.; Pfeifer, M. Feasibility and Acceptance of a Telehealth Intervention to Promote Symptom Management during Treatment for Head and Neck Cancer. J. Support. Oncol. 2011, 9, e1–e11. [Google Scholar] [CrossRef]
  94. Head, B.A.; Studts, J.L.; Bumpous, J.M.; Gregg, J.L.; Wilson, L.; Keeney, C.; Scharfenberger, J.A.; Pfeifer, M.P. Development of a telehealth intervention for head and neck cancer patients. Telemed. J. E-Health 2009, 15, 44–52. [Google Scholar] [CrossRef] [PubMed]
  95. Heiney, S.P.; Adams, S.A.; Wells, L.M.; Johnson, H.; King, J.M. Participant evaluation of teleconference support for African American women with breast cancer. Cancer Nurs. 2012, 35, E24–E30. [Google Scholar] [CrossRef] [PubMed]
  96. Hochstenbach, L.M.J.; Zwakhalen, S.M.G.; Courtens, A.M.; van Kleef, M.; de Witte, L.P. Feasibility of a mobile and web-based intervention to support self-management in outpatients with cancer pain. Eur. J. Oncol. Nurs. 2016, 23, 97–105. [Google Scholar] [CrossRef] [PubMed]
  97. Kanera, I.M.; Willems, R.A.; Bolman, C.A.; Mesters, I.; Zambon, V.; Gijsen, B.C.; Lechner, L. Use and Appreciation of a Tailored Self-Management eHealth Intervention for Early Cancer Survivors: Process Evaluation of a Randomized Controlled Trial. J. Med. Internet Res. 2016, 18, e229. [Google Scholar] [CrossRef] [PubMed]
  98. Katz, M.H.; Slack, R.; Bruno, M.; McMillan, J.; Fleming, J.B.; Lee, J.E.; Bednarski, B.; Papadopoulos, J.; Matin, S.F. Outpatient virtual clinical encounters after complex surgery for cancer: A prospective pilot study of “TeleDischarge”. J. Surg. Res. 2016, 202, 196–203. [Google Scholar] [CrossRef] [PubMed]
  99. Kearney, N.; Kidd, L.; Miller, M.; Sage, M.; Khorrami, J.; McGee, M.; Cassidy, J.; Niven, K.; Gray, P. Utilising handheld computers to monitor and support patients receiving chemotherapy: Results of a UK-based feasibility study. Support. Care Cancer 2006, 14, 742–752. [Google Scholar] [CrossRef] [PubMed]
  100. Kelleher, S.A.; Winger, J.G.; Dorfman, C.S.; Ingle, K.K.; Moskovich, A.A.; Abernethy, A.P.; Keefe, F.J.; Samsa, G.P.; Kimmick, G.G.; Somers, T.J. A behavioral cancer pain intervention: A randomized noninferiority trial comparing in-person with videoconference delivery. Psycho-Oncology 2019, 28, 1671–1678. [Google Scholar] [CrossRef]
  101. Kenfield, S.A.; Van Blarigan, E.L.; Ameli, N.; Lavaki, E.; Cedars, B.; Paciorek, A.T.; Monroy, C.; Tantum, L.K.; Newton, R.U.; Signorell, C.; et al. Feasibility, Acceptability, and Behavioral Outcomes from a Technology-enhanced Behavioral Change Intervention (Prostate 8): A Pilot Randomized Controlled Trial in Men with Prostate Cancer. Eur. Urol. 2019, 75, 950–958. [Google Scholar] [CrossRef] [PubMed]
  102. Kim, H.J.; Kim, S.M.; Shin, H.; Jang, J.S.; Kim, Y.I.; Han, D.H. A Mobile Game for Patients With Breast Cancer for Chemotherapy Self-Management and Quality-of-Life Improvement: Randomized Controlled Trial. J. Med. Internet Res. 2018, 20, e273. [Google Scholar] [CrossRef]
  103. Kim, K.K.; Bell, J.F.; Bold, R.; Davis, A.; Ngo, V.; Reed, S.C.; Joseph, J.G. A Personal Health Network for Chemotherapy Care Coordination: Evaluation of Usability Among Patients. Stud. Health Technol. Inform. 2016, 225, 232–236. [Google Scholar]
  104. Kondylakis, H.; Bucur, A.; Crico, C.; Dong, F.; Graf, N.; Hoffman, S.; Koumakis, L.; Manenti, A.; Marias, K.; Mazzocco, K.; et al. Patient empowerment for cancer patients through a novel ICT infrastructure. J. Biomed. Inform. 2020, 101, 103342. [Google Scholar] [CrossRef]
  105. Kubo, A.; Kurtovich, E.; McGinnis, M.; Aghaee, S.; Altschuler, A.; Quesenberry, C., Jr.; Kolevska, T.; Avins, A.L. A Randomized Controlled Trial of mHealth Mindfulness Intervention for Cancer Patients and Informal Cancer Caregivers: A Feasibility Study Within an Integrated Health Care Delivery System. Integr. Cancer Ther. 2019, 18, 1534735419850634. [Google Scholar] [CrossRef]
  106. Lambert, S.D.; Duncan, L.R.; Culos-Reed, S.N.; Hallward, L.; Higano, C.S.; Loban, E.; Katz, A.; De Raad, M.; Ellis, J.; Korman, M.B.; et al. Feasibility, Acceptability, and Clinical Significance of a Dyadic, Web-Based, Psychosocial and Physical Activity Self-Management Program (TEMPO) Tailored to the Needs of Men with Prostate Cancer and Their Caregivers: A Multi-Center Randomized Pilot Trial. Curr. Oncol. 2022, 29, 785–804. [Google Scholar] [CrossRef]
  107. Lee, H.; Uhm, K.E.; Cheong, I.Y.; Yoo, J.S.; Chung, S.H.; Park, Y.H.; Lee, J.Y.; Hwang, J.H. Patient Satisfaction with Mobile Health (mHealth) Application for Exercise Intervention in Breast Cancer Survivors. J. Med. Syst. 2018, 42, 254. [Google Scholar] [CrossRef]
  108. Livingston, P.; White, V.; Hayman, J.; Hill, D. How acceptable is a referral and telephone-based outcall programme for men diagnosed with cancer? A feasibility study. Eur. J. Cancer Care 2006, 15, 467–475. [Google Scholar] [CrossRef]
  109. Livingston, P.M.; Heckel, L.; Orellana, L.; Ashley, D.; Ugalde, A.; Botti, M.; Pitson, G.; Woollett, A.; Chambers, S.K.; Parente, P.; et al. Outcomes of a randomized controlled trial assessing a smartphone Application to reduce unmet needs among people diagnosed with CancEr (ACE). Cancer Med. 2020, 9, 507–516. [Google Scholar] [CrossRef]
  110. Loh, K.P.; Sanapala, C.; Watson, E.E.; Jensen-Battaglia, M.; Janelsins, M.C.; Klepin, H.D.; Schnall, R.; Culakova, E.; Vertino, P.; Susiarjo, M.; et al. A single-arm pilot study of a mobile health exercise intervention (GO-EXCAP) in older patients with myeloid neoplasms. Blood Adv. 2022, 6, 3850–3860. [Google Scholar] [CrossRef]
  111. Lopez, C.J.; Edwards, B.; Langelier, D.M.; Chang, E.K.; Chafranskaia, A.; Jones, J.M. Delivering Virtual Cancer Rehabilitation Programming During the First 90 Days of the COVID-19 Pandemic: A Multimethod Study. Arch. Phys. Med. Rehabil. 2021, 102, 1283–1293. [Google Scholar] [CrossRef]
  112. Lozano-Lozano, M.; Cantarero-Villanueva, I.; Martin-Martin, L.; Galiano-Castillo, N.; Sanchez, M.J.; Fernández-Lao, C.; Postigo-Martin, P.; Arroyo-Morales, M. A Mobile System to Improve Quality of Life Via Energy Balance in Breast Cancer Survivors (BENECA mHealth): Prospective Test-Retest Quasiexperimental Feasibility Study. JMIR Mhealth Uhealth 2019, 7, e14136. [Google Scholar] [CrossRef]
  113. Lucas, A.R.; Bass, M.B.; Rothrock, N.E.; O’Connor, M.L.; Sorkin, M.R.; Nawyn, J.; Albinali, F.; Wagner, L.I. Development of an eHealth System to Capture and Analyze Patient Sensor and Self-Report Data: Mixed-Methods Assessment of Potential Applications to Improve Cancer Care Delivery. JMIR Med. Inform. 2018, 6, e46. [Google Scholar] [CrossRef]
  114. Lyons, K.D.; Hull, J.G.; Kaufman, P.A.; Li, Z.; Seville, J.L.; Ahles, T.A.; Kornblith, A.B.; Hegel, M.T. Development and initial evaluation of a telephone-delivered, behavioral activation, and problem-solving treatment program to address functional goals of breast cancer survivors. J. Psychosoc. Oncol. 2015, 33, 199–218. [Google Scholar] [CrossRef]
  115. MacDonald, A.M.; Chafranskaia, A.; Lopez, C.J.; Maganti, M.; Bernstein, L.J.; Chang, E.; Langelier, D.M.; Obadia, M.; Edwards, B.; Oh, P.; et al. CaRE @ Home: Pilot Study of an Online Multidimensional Cancer Rehabilitation and Exercise Program for Cancer Survivors. J. Clin. Med. 2020, 9, 3092. [Google Scholar] [CrossRef]
  116. Mark, T.L.; Fortner, B.; Johnson, G. Evaluation of a tablet PC technology to screen and educate oncology patients. Support. Care Cancer 2008, 16, 371–378. [Google Scholar] [CrossRef]
  117. Matthew, A.G.; Currie, K.L.; Irvine, J.; Ritvo, P.; Santa Mina, D.; Jamnicky, L.; Nam, R.; Trachtenberg, J. Serial personal digital assistant data capture of health-related quality of life: A randomized controlled trial in a prostate cancer clinic. Health Qual. Life Outcomes 2007, 5, 38. [Google Scholar] [CrossRef]
  118. McCann, L.; Maguire, R.; Miller, M.; Kearney, N. Patients’ perceptions and experiences of using a mobile phone-based advanced symptom management system (ASyMS) to monitor and manage chemotherapy related toxicity. Eur. J. Cancer Care 2009, 18, 156–164. [Google Scholar] [CrossRef]
  119. Milbury, K.; Kroll, J.; Chen, A.; Antonoff, M.B.; Snyder, S.; Higgins, H.; Yang, C.C.; Li, Y.; Bruera, E. Pilot Randomized Controlled Trial in Women With Non-Small Cell Lung Cancer to Assess the Feasibility of Delivering Group-Based Psychosocial Care via Videoconference. Integr. Cancer Ther. 2021, 20, 15347354211052520. [Google Scholar] [CrossRef]
  120. Myall, M.; May, C.R.; Grimmett, C.; May, C.M.; Calman, L.; Richardson, A.; Foster, C.L. RESTORE: An exploratory trial of a web-based intervention to enhance self-management of cancer-related fatigue: Findings from a qualitative process evaluation. BMC Med. Inform. Decis. Mak. 2015, 15, 94. [Google Scholar] [CrossRef]
  121. Nguyen, M.H.; Smets, E.M.; Bol, N.; Loos, E.F.; van Laarhoven, H.W.; Geijsen, D.; van Berge Henegouwen, M.I.; Tytgat, K.M.; van Weert, J.C. Tailored Web-Based Information for Younger and Older Patients with Cancer: Randomized Controlled Trial of a Preparatory Educational Intervention on Patient Outcomes. J. Med. Internet Res. 2019, 21, e14407. [Google Scholar] [CrossRef]
  122. O’Brien, K.; Moore, A.; Percival-Smith, S.; Venkatraman, S.; Grubacevic, V.; Scoble, J.; Gilham, L.; Greenway, T.; Coghill, K.; Wale, J. An investigation into the usability of a drug-complementary medicines interactions database in a consumer group of women with breast cancer. Eur. J. Integr. Med. 2020, 33, 101004. [Google Scholar] [CrossRef]
  123. Ormel, H.L.; van der Schoot, G.G.F.; Westerink, N.L.; Sluiter, W.J.; Gietema, J.A.; Walenkamp, A.M.E. Self-monitoring physical activity with a smartphone application in cancer patients: A randomized feasibility study (SMART-trial). Support. Care Cancer 2018, 26, 3915–3923. [Google Scholar] [CrossRef]
  124. Owens, O.L.; Smith, K.N.; Beer, J.M.; Gallerani, D.G.; McDonnell, K.K. A Qualitative Cultural Sensitivity Assessment of the Breathe Easier Mobile Application for Lung Cancer Survivors and Their Families. Oncol. Nurs. Forum 2020, 47, 331–341. [Google Scholar] [CrossRef]
  125. Ownsworth, T.; Cubis, L.; Prasad, T.; Foote, M.; Kendall, M.; Oram, J.; Chambers, S.; Pinkham, M.B. Feasibility and acceptability of a telehealth platform for delivering the Making Sense of Brain Tumour programme: A mixed-methods pilot study. Neuropsychol. Rehabil. 2022, 32, 378–406. [Google Scholar] [CrossRef]
  126. Pavic, M.; Klaas, V.; Theile, G.; Kraft, J.; Tröster, G.; Guckenberger, M. Feasibility and Usability Aspects of Continuous Remote Monitoring of Health Status in Palliative Cancer Patients Using Wearables. Oncology 2020, 98, 386–395. [Google Scholar] [CrossRef]
  127. Peipert, J.D.; Lad, T.; Khosla, P.G.; Garcia, S.F.; Hahn, E.A. A Low Literacy, Multimedia Health Information Technology Intervention to Enhance Patient-Centered Cancer Care in Safety Net Settings Increased Cancer Knowledge in a Randomized Controlled Trial. Cancer Control J. Moffitt Cancer Cent. 2021, 28, 10732748211036783. [Google Scholar] [CrossRef]
  128. Post, D.M.; Shapiro, C.L.; Cegala, D.J.; David, P.; Katz, M.L.; Krok, J.L.; Phillips, G.S.; McAlearney, A.S.; Lehman, J.S.; Hicks, W.; et al. Improving symptom communication through personal digital assistants: The CHAT (Communicating Health Assisted by Technology) project. J. Natl. Cancer Inst. Monogr. 2013, 2013, 153–161. [Google Scholar] [CrossRef]
  129. Price, J.; Brunet, J. Feasibility and acceptability of a telehealth behavior change intervention for promoting physical activity and fruit and vegetable consumption among rural-living young adult cancer survivors. J. Psychosoc. Oncol. 2021, 39, 715–733. [Google Scholar] [CrossRef]
  130. Purdy, G.M.; Venner, C.P.; Tandon, P.; McNeely, M.L. Feasibility of a tailored and virtually supported home exercise program for people with multiple myeloma using a novel eHealth application. Digit. Health 2022, 8, 20552076221129066. [Google Scholar] [CrossRef]
  131. Puszkiewicz, P.; Roberts, A.L.; Smith, L.; Wardle, J.; Fisher, A. Assessment of Cancer Survivors’ Experiences of Using a Publicly Available Physical Activity Mobile Application. JMIR Cancer 2016, 2, e7. [Google Scholar] [CrossRef]
  132. Rezaee, R.; Asadi, S.; Yazdani, A.; Rezvani, A.; Kazeroon, A.M. Development, usability and quality evaluation of the resilient mobile application for women with breast cancer. Health Sci. Rep. 2022, 5, e708. [Google Scholar] [CrossRef]
  133. Richards, H.S.; Blazeby, J.M.; Portal, A.; Harding, R.; Reed, T.; Lander, T.; Chalmers, K.A.; Carter, R.; Singhal, R.; Absolom, K.; et al. A real-time electronic symptom monitoring system for patients after discharge following surgery: A pilot study in cancer-related surgery. BMC Cancer 2020, 20, 543. [Google Scholar] [CrossRef]
  134. Ruland, C.M.; Maffei, R.M.; Børøsund, E.; Krahn, A.; Andersen, T.; Grimsbø, G.H. Evaluation of different features of an eHealth application for personalized illness management support: Cancer patients’ use and appraisal of usefulness. Int. J. Med. Inform. 2013, 82, 593–603. [Google Scholar] [CrossRef]
  135. Ruland, C.M.; White, T.; Stevens, M.; Fanciullo, G.; Khilani, S.M. Effects of a computerized system to support shared decision making in symptom management of cancer patients: Preliminary results. J. Am. Med. Inform. Assoc. JAMIA 2003, 10, 573–579. [Google Scholar] [CrossRef]
  136. Russell, L.; Ugalde, A.; Orellana, L.; Milne, D.; Krishnasamy, M.; Chambers, R.; Austin, D.W.; Livingston, P.M. A pilot randomised controlled trial of an online mindfulness-based program for people diagnosed with melanoma. Support. Care Cancer 2019, 27, 2735–2746. [Google Scholar] [CrossRef]
  137. Skrabal Ross, X.; Gunn, K.M.; Suppiah, V.; Patterson, P.; Boyle, T.; Carrington, C.; Tan, S.L.; Ryan, M.; Joshi, R.; Olver, I. A smartphone program to support adherence to oral chemotherapy in people with cancer: Proof-of-concept trial. Asia-Pac. J. Clin. Oncol. 2022, 18, e378–e387. [Google Scholar] [CrossRef]
  138. Smith, S.J.; Smith, A.B.; Kennett, W.; Vinod, S.K. Exploring cancer patients’, caregivers’, and clinicians’ utilisation and experiences of telehealth services during COVID-19: A qualitative study. Patient Educ. Couns. 2022, 105, 3134–3142. [Google Scholar] [CrossRef]
  139. Spoelstra, S.L.; Given, C.W.; Sikorskii, A.; Coursaris, C.K.; Majumder, A.; DeKoekkoek, T.; Schueller, M.; Given, B.A. Proof of Concept of a Mobile Health Short Message Service Text Message Intervention That Promotes Adherence to Oral Anticancer Agent Medications: A Randomized Controlled Trial. Telemed. J. E-Health 2016, 22, 497–506. [Google Scholar] [CrossRef]
  140. Stephen, J.; Collie, K.; McLeod, D.; Rojubally, A.; Fergus, K.; Speca, M.; Turner, J.; Taylor-Brown, J.; Sellick, S.; Burrus, K.; et al. Talking with text: Communication in therapist-led, live chat cancer support groups. Soc. Sci. Med. 2014, 104, 178–186. [Google Scholar] [CrossRef]
  141. Sundberg, K.; Eklöf, A.L.; Blomberg, K.; Isaksson, A.K.; Wengström, Y. Feasibility of an interactive ICT-platform for early assessment and management of patient-reported symptoms during radiotherapy for prostate cancer. Eur. J. Oncol. Nurs. 2015, 19, 523–528. [Google Scholar] [CrossRef]
  142. Valle, C.G.; Deal, A.M.; Tate, D.F. Preventing weight gain in African American breast cancer survivors using smart scales and activity trackers: A randomized controlled pilot study. J. Cancer Surviv. Res. Pract. 2017, 11, 133–148. [Google Scholar] [CrossRef]
  143. Van Blarigan, E.L.; Chan, H.; Van Loon, K.; Kenfield, S.A.; Chan, J.M.; Mitchell, E.; Zhang, L.; Paciorek, A.; Joseph, G.; Laffan, A.; et al. Self-monitoring and reminder text messages to increase physical activity in colorectal cancer survivors (Smart Pace): A pilot randomized controlled trial. BMC Cancer 2019, 19, 218. [Google Scholar] [CrossRef]
  144. Van der Linden, S.D.; Rutten, G.M.; Dirven, L.; Taphoorn, M.J.B.; Satoer, D.D.; Dirven, C.M.F.; Sitskoorn, M.M.; Gehring, K. eHealth cognitive rehabilitation for brain tumor patients: Results of a randomized controlled trial. J. Neuro-Oncol. 2021, 154, 315–326. [Google Scholar] [CrossRef]
  145. Vogel, R.I.; Niendorf, K.; Petzel, S.; Lee, H.; Teoh, D.; Blaes, A.H.; Argenta, P.; Rivard, C.; Winterhoff, B.; Lee, H.Y.; et al. A patient-centered mobile health application to motivate use of genetic counseling among women with ovarian cancer: A pilot randomized controlled trial. Gynecol. Oncol. 2019, 153, 100–107. [Google Scholar] [CrossRef]
  146. Walle, T.; Erdal, E.; Mühlsteffen, L.; Singh, H.M.; Gnutzmann, E.; Grün, B.; Hofmann, H.; Ivanova, A.; Köhler, B.C.; Korell, F.; et al. Completion rate and impact on physician-patient relationship of video consultations in medical oncology: A randomised controlled open-label trial. ESMO Open 2020, 5, e000912. [Google Scholar] [CrossRef]
  147. Wallwiener, M.; Heindl, F.; Brucker, S.Y.; Taran, F.A.; Hartkopf, A.; Overkamp, F.; Kolberg, H.C.; Hadji, P.; Tesch, H.; Ettl, J.; et al. Implementation and Feasibility of Electronic Patient-Reported Outcome (ePRO) Data Entry in the PRAEGNANT Real-Time Advanced and Metastatic Breast Cancer Registry. Geburtshilfe Frauenheilkd 2017, 77, 870–878. [Google Scholar] [CrossRef]
  148. Waterland, J.L.; Chahal, R.; Ismail, H.; Sinton, C.; Riedel, B.; Francis, J.J.; Denehy, L. Implementing a telehealth prehabilitation education session for patients preparing for major cancer surgery. BMC Health Serv. Res. 2021, 21, 443. [Google Scholar] [CrossRef]
  149. Weaver, A.; Young, A.M.; Rowntree, J.; Townsend, N.; Pearson, S.; Smith, J.; Gibson, O.; Cobern, W.; Larsen, M.; Tarassenko, L. Application of mobile phone technology for managing chemotherapy-associated side-effects. Ann. Oncol. 2007, 18, 1887–1892. [Google Scholar] [CrossRef]
  150. Wickline, M.; Wolpin, S.; Cho, S.; Tomashek, H.; Louca, T.; Frisk, T.; Templin, J.; Loechl, A.; Goff, B.; Berry, D. Usability and acceptability of the electronic self-assessment and care (eSAC) program in advanced ovarian cancer: A mixed methods study. Gynecol. Oncol. 2022, 167, 239–246. [Google Scholar] [CrossRef]
  151. Wilkie, D.J.; Judge, M.K.; Berry, D.L.; Dell, J.; Zong, S.; Gilespie, R. Usability of a computerized PAINReportIt in the general public with pain and people with cancer pain. J. Pain. Symptom Manag. 2003, 25, 213–224. [Google Scholar] [CrossRef]
  152. Wu, F.; Rotimi, O.; Laza-Cagigas, R.; Rampal, T. The Feasibility and Effects of a Telehealth-Delivered Home-Based Prehabilitation Program for Cancer Patients during the Pandemic. Curr. Oncol. 2021, 28, 2248–2259. [Google Scholar] [CrossRef]
  153. Yap, K.Y.; Low, H.X.; Koh, K.S.; Un, M.; Shih, V.; Chan, A. Feasibility and acceptance of a pharmacist-run tele-oncology service for chemotherapy-induced nausea and vomiting in ambulatory cancer patients. Telemed. J. E-Health 2013, 19, 387–395. [Google Scholar] [CrossRef]
  154. Zini, E.M.; Lanzola, G.; Quaglini, S.; Bossi, P.; Licitra, L.; Resteghini, C. A pilot study of a smartphone-based monitoring intervention on head and neck cancer patients undergoing concurrent chemo-radiotherapy. Int. J. Med. Inform. 2019, 129, 404–412. [Google Scholar] [CrossRef]
  155. Yeung, A.W.K.; Torkamani, A.; Butte, A.J.; Glicksberg, B.S.; Schuller, B.; Rodriguez, B.; Ting, D.S.W.; Bates, D.; Schaden, E.; Peng, H.; et al. The promise of digital healthcare technologies. Front. Public. Health 2023, 11, 1196596. [Google Scholar] [CrossRef]
  156. Di Lorito, C.; Bosco, A.; Rai, H.; Craven, M.; McNally, D.; Todd, C.; Booth, V.; Cowley, A.; Howe, L.; Harwood, R.H. A systematic literature review and meta-analysis on digital health interventions for people living with dementia and Mild Cognitive Impairment. Int. J. Geriatr. Psychiatry 2022, 37, gps5730. [Google Scholar] [CrossRef]
  157. Batra, S.; Baker, R.A.; Wang, T.; Forma, F.; DiBiasi, F.; Peters-Strickland, T. Digital health technology for use in patients with serious mental illness: A systematic review of the literature. Med. Devices 2017, 10, 237–251. [Google Scholar] [CrossRef]
  158. Ignatowicz, A.; Slowther, A.M.; Elder, P.; Bryce, C.; Hamilton, K.; Huxley, C.; Forjaz, V.; Sturt, J.; Griffiths, F. Ethical implications of digital communication for the patient-clinician relationship: Analysis of interviews with clinicians and young adults with long term conditions (the LYNC study). BMC Med. Ethics 2018, 19, 11. [Google Scholar] [CrossRef]
  159. Qudah, B.; Luetsch, K. The influence of mobile health applications on patient-healthcare provider relationships: A systematic, narrative review. Patient Educ. Couns. 2019, 102, 1080–1089. [Google Scholar] [CrossRef]
  160. Lordon, R.J.; Mikles, S.P.; Kneale, L.; Evans, H.L.; Munson, S.A.; Backonja, U.; Lober, W.B. How patient-generated health data and patient-reported outcomes affect patient–clinician relationships: A systematic review. Health Inform. J. 2020, 26, 2689–2706. [Google Scholar] [CrossRef]
  161. Gammon, D.; Strand, M.; Eng, L.S.; Børøsund, E.; Varsi, C.; Ruland, C. Shifting Practices Toward Recovery-Oriented Care Through an E-Recovery Portal in Community Mental Health Care: A Mixed-Methods Exploratory Study. J. Med. Internet Res. 2017, 19, e145. [Google Scholar] [CrossRef]
  162. Wannheden, C.; Åberg-Wennerholm, M.; Dahlberg, M.; Revenäs, Å.; Tolf, S.; Eftimovska, E.; Brommels, M. Digital Health Technologies Enabling Partnerships in Chronic Care Management: Scoping Review. J. Med. Internet Res. 2022, 24, e38980. [Google Scholar] [CrossRef]
  163. Bally, E.L.S.; Cheng, D.; van Grieken, A.; Ferri Sanz, M.; Zanutto, O.; Carroll, A.; Darley, A.; Roozenbeek, B.; Dippel, D.W.J.; Raat, H. Patients’ Perspectives Regarding Digital Health Technology to Support Self-management and Improve Integrated Stroke Care: Qualitative Interview Study. J. Med. Internet Res. 2023, 25, e42556. [Google Scholar] [CrossRef]
  164. Schofield, P.; Shaw, T.; Pascoe, M. Toward Comprehensive Patient-Centric Care by Integrating Digital Health Technology With Direct Clinical Contact in Australia. J. Med. Internet Res. 2019, 21, e12382. [Google Scholar] [CrossRef]
  165. Kabukye, J.K.; Kakungulu, E.; Keizer, N.d.; Cornet, R. Digital health in oncology in Africa: A scoping review and cross-sectional survey. Int. J. Med. Inform. 2022, 158, 104659. [Google Scholar] [CrossRef]
  166. Curry, J.; Patterson, M.; Greenley, S.; Pearson, M.; Forbes, C.C. Feasibility, acceptability, and efficacy of online supportive care for individuals living with and beyond lung cancer: A systematic review. Support. Care Cancer 2021, 29, 6995–7011. [Google Scholar] [CrossRef]
Figure 1. Search terms applied in database searches.
Figure 1. Search terms applied in database searches.
Cancers 16 02293 g001
Figure 2. PRISMA flow diagram of the article screening and selection process [23].
Figure 2. PRISMA flow diagram of the article screening and selection process [23].
Cancers 16 02293 g002
Figure 3. Number of identified studies by publication year.
Figure 3. Number of identified studies by publication year.
Cancers 16 02293 g003
Figure 4. Number of identified studies by technology category.
Figure 4. Number of identified studies by technology category.
Cancers 16 02293 g004
Figure 5. Number of included studies by intended technology use.
Figure 5. Number of included studies by intended technology use.
Cancers 16 02293 g005
Figure 6. Identified user patient-facing digital health technology requirements by classification category.
Figure 6. Identified user patient-facing digital health technology requirements by classification category.
Cancers 16 02293 g006
Table 1. Review question (PICO).
Table 1. Review question (PICO).
PopulationInterventionComparisonOutcome
Cancer patients/survivorsPatient-facing digital health technologiesN/AUser perspectives/requirements
N/A: Not applicable.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lazarou, I.; Krooupa, A.-M.; Nikolopoulos, S.; Apostolidis, L.; Sarris, N.; Papadopoulos, S.; Kompatsiaris, I. Cancer Patients’ Perspectives and Requirements of Digital Health Technologies: A Scoping Literature Review. Cancers 2024, 16, 2293. https://doi.org/10.3390/cancers16132293

AMA Style

Lazarou I, Krooupa A-M, Nikolopoulos S, Apostolidis L, Sarris N, Papadopoulos S, Kompatsiaris I. Cancer Patients’ Perspectives and Requirements of Digital Health Technologies: A Scoping Literature Review. Cancers. 2024; 16(13):2293. https://doi.org/10.3390/cancers16132293

Chicago/Turabian Style

Lazarou, Ioulietta, Anna-Maria Krooupa, Spiros Nikolopoulos, Lazaros Apostolidis, Nikos Sarris, Symeon Papadopoulos, and Ioannis Kompatsiaris. 2024. "Cancer Patients’ Perspectives and Requirements of Digital Health Technologies: A Scoping Literature Review" Cancers 16, no. 13: 2293. https://doi.org/10.3390/cancers16132293

APA Style

Lazarou, I., Krooupa, A. -M., Nikolopoulos, S., Apostolidis, L., Sarris, N., Papadopoulos, S., & Kompatsiaris, I. (2024). Cancer Patients’ Perspectives and Requirements of Digital Health Technologies: A Scoping Literature Review. Cancers, 16(13), 2293. https://doi.org/10.3390/cancers16132293

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop