Mobile Apps and Quality of Life in Patients With Breast Cancer and Survivors: Systematic Literature Review

Introduction

Background

Breast cancer remains the leading cause of cancer-related deaths among women worldwide [1]. Even so, thanks to improvements in early detection and breast cancer treatment, most Western countries have seen a reduction in mortality rates [1,2]. As a result, many breast cancer survivors live multiple productive years after treatment completion [3]. However, the majority of cancer treatments severely affect quality of life (QOL), causing both physical and psychosocial side effects that may disrupt patients’ physical function and mental well-being [4]. These side effects may persist and follow into survivorship. Physical symptoms, including chronic pain, paresthesia, allodynia, menopausal symptoms, weight problems, and fatigue, along with psychological distress, including the fear of recurrence, sleep disturbances, sexual issues, and cognitive problems, often persist [5-7]. Furthermore, evidence suggests that breast cancer survivors are at an increased risk of adverse mental health outcomes such as anxiety and depression [8].

Various lifestyle and behavioral interventions have been shown to improve the side effects experienced during and after breast cancer treatment as well as improve survival outcomes [9-14]. Regular physical activity (PA) after diagnosis has been found to be inversely associated with both breast cancer mortality and all-cause mortality, and even low-volume PA has been found to improve survival outcomes compared with inactivity [15,16]. Furthermore, there is strong evidence supporting the positive effects of PA on cancer and treatment-related side effects [17,18]. Integrative therapies, such as yoga and mindfulness, have been found to have a positive effect, particularly on the psychological health of patients with breast cancer and survivors, improving mental health, sleep disturbances, and perceived stress [12,19-22]. Another important factor improving survival outcomes in patients with breast cancer is continued adherence to adjuvant endocrine therapy, yet nonadherence is common [23,24]. Behavioral interventions using reminders and encouraging self-reporting medication adherence have been shown to increase adherence to adjuvant endocrine therapy, thus improving survival outcomes [25]. However, with the increasing numbers of cancer diagnoses and cancer survivors, the resource needs cannot always be met, in particular in patients progressing from their primary to follow-up treatments. Thus, the development and validation of easily accessible treatments have become a crucial need for this patient group.

There is a growing body of evidence supporting the use of digital health technologies in cancer care, helping patients to self-manage symptoms and side effects, improving QOL, and potentially increasing survival outcomes [26,27]. Mobile health (mHealth), a subset of digital health, is defined as the use of mobile devices to support the delivery of health practices, often taking the form of a mobile app [28]. Compared with internet-based interventions, mobile apps are more user-friendly because they perform at a much faster speed than a website and may offer basic content and features even without an internet connection. Providers of mHealth interventions can easily send push notifications to users, and interaction-enabled features and gestures (tapping, dragging, holding, and swiping) are much more elaborative in an mHealth intervention than in an intervention accessed via an internet site where design and features are constrained by web browsers. A limitation of mHealth is the low regulatory approval [29]. Another subset of digital health, digital therapeutics (DTx), is however highly regulated, backed by clinical trials, and supported by real-world outcomes [30]. DTx apps deliver disease-specific interventions via high-quality software programs with the aim to treat, manage, or prevent disease through behavior changes [30-32]. With the majority of the world population being smartphone users, mHealth and DTx present a cost-effective solution to the growing need for accessible care [33,34], a solution considered by patients to be a useful complementary tool to usual care [35].

Objectives

Prior reviews support the use of mHealth interventions in general cancer care, suggesting that they may support self-management as well as decrease symptom burden, fatigue, and psychological distress [36,37]. A recent meta-analysis concluded that the use of mHealth apps improves health-related QOL in patients with cancer, with the strongest evidence found for PA, cognitive behavioral therapy, and mindfulness [38]. However, the need for disease-focused solutions over generic ones has been emphasized [39]. In a 2017 review focusing on QOL in patients with breast and prostate cancer, only 5 studies met the inclusion criteria. The authors concluded that the majority of these studies were of low-to-medium quality and that there was a lack of rigorous trials [40]. A 2019 review summarizing the effects of available apps on various outcomes in breast cancer found indications of their effectiveness in promoting weight loss, improving QOL, and decreasing stress [41]. In a very recent publication, Patel et al [42] point out that digital innovation in oncology lags behind other therapeutic areas despite there being a high unmet need among patients, health care providers, and caregivers. Importantly, there is a lack of data on the impact of digital treatments on QOL, which challenges optimal treatment decision-making. Thus, with increasing numbers of breast cancer survivors, continual development and release of new breast cancer mHealth interventions, and the use of digital health apps being projected to rise rapidly, an updated synthesis of current research is timely. The aim of this review was to provide an overview of breast cancer–specific, mobile app–driven lifestyle or behavioral interventions in patient care through to survivorship and their impact on QOL and mental well-being.

Methods

Study Design

A systematic review of the literature was performed following the PRISMA-checklist (see Multimedia Appendix 1). The aim of a systematic review is to make available evidence more accessible by identifying, evaluating, and synthesizing the findings of relevant individual studies on a specific topic [43].

Search Strategy

An extended bibliography search was conducted on March 21, 2022, on PubMed, Scopus, and Web of Science. The search focused on mHealth in patients with breast cancer and survivors and the effect on QOL. The following search query was used: ((“digital therapeutics”) OR (“digital health”) OR (mhealth) OR (“mobile application”) OR (app) OR (smartphone)) AND ((breast cancer) OR (breast neoplasm)) AND ((lifestyle) OR (“quality of life”) OR (QOL) OR (anxiety) OR (depression) OR (mental health)). The search was limited to include results that contained the word “trial”.

Selection of Studies

No lower or upper published date limit was set on the search results. Only original research published in English was considered for inclusion. The inclusion criteria were further limited to research pertaining to mHealth, mobile apps, or DTx; breast cancer care or survivorship; and QOL or well-being. In this instance, lifestyle or behavioral interventions were defined as any intervention intended to modify or encourage certain behavior, such as exercise, nutrition, self-management, stress management, and medication adherence. Only studies using either direct QOL measurements or measurements related to mental well-being, such as anxiety or depression scales, were considered for inclusion.

Studies that did not include an intervention involving a mobile app and did not include patients with breast cancer or survivors as the study population were excluded. Only studies directly related to breast cancer care or survivorship were considered for inclusion. Studies involving mobile apps that were not directly applied to the study population (eg, health care professionals using mHealth apps to manage breast cancer care) were excluded, as were studies using an app without a lifestyle intervention (eg, symptom monitoring without self-management or lifestyle modification information). In addition, we excluded web-based interventions, telehealth interventions, and other digital health interventions that did not involve a mobile app. Furthermore, studies pertaining to app development were excluded. Only original research was included, and reviews, editorials, and protocols were excluded. Titles and abstracts were screened to identify appropriate articles. The initial screening and inclusion of articles was performed by SRS. Both authors independently reviewed the remaining articles for the final selection.

Data Extraction

Data were extracted and inputted into a Google Sheets file (Google LLC) by 1 reviewer (SRS) and then verified by a second reviewer (SLG). The following data were extracted for each included study: author and year of study; location of study, study population, and number of participants; brief description of the intervention delivered, intervention duration, and, when applicable, the follow-up period; control condition (if any); measurements; and key outcomes. Any discrepancies were resolved by discussion.

Quality Assessment of the Included Studies

The quality of each of the included studies was evaluated using the Cochrane Collaboration’s 6-domain tool for assessing risk of bias in randomized trials. Study characteristics are classified as having high, low, or unclear risk of bias [44]. For each study, all items were first rated by 1 reviewer (SRS) and compiled in a Google Sheets file. Any doubts over unclear items were resolved by discussion between the authors.

Results

Study Selection

A total of 346 articles were identified, of which, once duplicates were removed, 258 (74.6%) remained for primary analysis. Of these 258 articles, 55 (21.3%) were identified as involving a mobile app intervention with patients with breast cancer or survivors as the study population.

Subsequently, the full-text publications of these 55 articles were screened. In line with the defined exclusion criteria, the full-text screening excluded studies that were not breast cancer specific, involved commercially available health or wellness apps, were web based, had no quantitative measures, or had no QOL or well-being measures. In addition, we excluded interventions that involved smartphones or tablet devices but did not include a specific mobile app [45,46]. Some of the studies (2/55, 4%) were excluded because they did not have a lifestyle or behavior modification element despite using an app [47,48]. We also excluded studies where the feasibility of an app or the app functionality or engagement was being tested rather than the effectiveness of its contents on QOL and well-being [49,50]. Furthermore, all secondary analyses were excluded, as were pilot or feasibility studies if subsequent randomized controlled trial (RCT) studies had been published. Thus, of the initial 346 studies identified via database search, 17 (4.9%) were included in the final review. The flow diagram in Figure 1 details the study screening and selection process.

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Study Characteristics

The articles included were published between January 2017 and March 2022. Among the 17 articles, there were 10 (59%) RCTs, 5 (29%) pilot or feasibility studies, 1 (6%) nonrandomized controlled prospective cohort study, and 1 (6%) prospective quasi-randomized trial. All included articles studied an adult female population, either patients with breast cancer or survivors. The studies included were conducted in Asia (8/17, 47%), North America (5/17, 29%), and Europe (4/17, 24%). The sample size ranged from 23 to 356 participants, with 24% (4/17) of the studies having a sample of <50 participants, 35% (6/17) having a sample of between 50 and 100 participants, and 41% (7/17) having a sample of >100 participants. The majority of the studies (14/17, 82%) had a control group receiving care as usual or an active control group receiving a separate intervention.

Of the 17 reviewed studies, 7 (41%) delivered an app-only intervention, and 10 (59%) combined an app with additional supporting materials. The majority of the studies delivering a combined intervention used only 1 form of supporting material (7/10, 70%), whereas a minority used up to 3 forms of supporting materials (3/10, 30%). The supporting materials used included a combination of message-based reminders (SMS text message: 2/10, 20% and email: 1/10, 10%), wearables (pedometer: 1/10, 10% and Fitbit: 1/10, 10%), coaching calls (2/10, 20%), printed material (1/10, 10%), group support video calls (1/10, 10%), messaging group (1/10, 10%), other web-based material (2/10, 20%), and in-person rehabilitation sessions (1/10, 10%).

The reviewed articles all delivered interventions that had the goal, either primary or secondary, of improving QOL or mental well-being in some way, consistent with the inclusion criteria. The outcome measures varied across the studies, and the majority of the studies (15/17, 88%) measured more than 2 outcome variables. The most common measurements (6/17, 35%) used for QOL were the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire Core 30 (EORTC QLQ-C30) and the European Organization for Research and Treatment of Cancer Breast Cancer–Specific Quality-of-Life Questionnaire (EORTC QLQ-BR23). Many of the studies (4/17, 24%) also used the Functional Assessment of Cancer Therapy-Breast (FACT-B) or the Functional Assessment of Cancer Therapy-Endocrine Symptoms (FACT-ES). For anxiety or depressive symptoms, the most common scales used (4/17, 24%) were the Hospital Anxiety and Depression Scale (HADS) and the State-Trait Anxiety Inventory (STAI). However, other measurements were also used. The length of the interventions varied from 3 weeks to 12 weeks, with a minority of the studies including a follow-up period after intervention completion (4/17, 24%).

All reviewed studies included a sample of women with breast cancer or breast cancer survivors. Of the 17 studies, 6 (35%) focused on aiding patients with breast cancer during the active treatment phase (excluding ongoing hormone therapy), whereas the remaining 11 (65%) focused on survivorship. Table 1 summarizes the study characteristics, intervention design, and study results.

Mobile Apps During Active Treatment

Symptom management was the primary focus for the majority of the articles identified (5/6, 83%) that delivered an intervention during active treatment [52-56]. However, many of the interventions (3/6, 50%) also connected patients with health care professionals [51-53], some (2/6, 33%) focused on mental health [51,55], some (3/6, 50%) focused on social support [51,53,55], and 1 (17%) of these 6 studies included a component on exercise and nutrition [53]. All studies used an mHealth app, one of which was a mobile game–based app [56]; however, none of the studies specified using a DTx app. All studies indicated some positive effects on QOL or well-being measurements [51-56].

Of the 6 studies, 4 (67%) specifically related to patients with breast cancer undergoing chemotherapy [52,54-56]. Fjell et al [52] randomized 149 patients with breast cancer undergoing neoadjuvant chemotherapy to receive access to an mHealth app—Interaktor—or care as usual. Patients self-reported symptoms within the app, which offered education on symptom self-management and remote patient monitoring (RPM). At the end of the intervention duration, which varied depending on each patient’s chemotherapy schedule, the intervention group reported significantly lower prevalence of chemotherapy-related side effects, higher emotional functioning, and lower overall symptom distress as well as physical symptom distress [52]. Zhu et al [55] randomized 114 patients with breast cancer about to commence chemotherapy to receive a breast cancer e-support mHealth app or care as usual for 12 weeks. The app was intended for education, symptom management, and social support. It included a learning forum, a discussion forum, a personal stories forum, and an ask-the-expert forum. After commencement of chemotherapy, a decrease in QOL and self-efficacy was observed in both groups, but the decrease was significantly less in the intervention group, as was the decrease in symptom interference. No significant difference was observed for symptom severity, social support, anxiety, or depression. At the end of the 6-month follow-up, no significant differences were observed between the groups [55]. Kim et al [56] randomized 76 patients with metastatic breast cancer to receive access to a mobile game app or care as usual for 3 weeks. The mobile game was intended to improve self-management and reduce chemotherapy-related side effects. The game included educational content as well as the control of a personalized avatar. There was an increase in medication adherence and QOL as well as lower rates in reported adverse events in the intervention group compared with the control group. No significant differences were observed for depression or anxiety. However, more than half of the participants in the intervention group reported finding the game difficult to use [56]. In their prospective controlled cohort study, Grašič Kuhar et al [54] gave the intervention group (n=55) access to an mHealth app, mPro Mamma. The app allowed for recording of symptoms and severity and delivered symptom self-management techniques and RPM. The control group had undergone treatment in the year prior, when the app was not yet fully developed. At the end of treatment, the QOL summary scores were significantly higher in the intervention group than in the control group [54].

Hou et al [53] focused on newly diagnosed patients with breast cancer, randomizing 112 participants to receive a symptom self-management app or care as usual for 12 weeks. The app included educational content, exercises, dietary advice, symptom tracking, emotional support, and experience sharing, as well as expert consulting. Although both groups reported an increase in total QOL EORTC QLQ-C30), the increase was significantly more in the intervention group, as was the increase in functional scores [53].

One of the studies delivering mHealth alongside clinical care focused primarily on mental health. Ghanbari et al [51] randomized 82 patients with breast cancer to receive either an intervention (a self-management psychoeducational app) or care as usual. The app included educational information as well as stress and anger management techniques, along with self-esteem promotion. In addition, there was a social support group on the messaging app WhatsApp, where the patients in the intervention group could interact with each other as well as with a psychiatric nurse. After the 4-week intervention, the intervention group showed a significant reduction in anxiety (state, trait, and total) as well as a significant increase in self-esteem when compared with the control group [51].

Mobile Apps in Survivorship

The intervention focus varied for the reviewed studies focusing on mobile apps in survivorship. More than one-third (4/11, 36%) of the studies either focused on, or included an element of, PA as part of the intervention [57,60,62,67]. Some of the studies (3/11, 27%) included a focus on symptom burden [59,61,62], 9% (1/11) of the studies included RPM [59], 18% (2/11) addressed medication adherence [63,66], 9% (1/11) focused on lymphedema management [58], 9% (1/11) focused on social support [65], and 9% (1/11) specifically addressed the fear of recurrence [64]. All studies used an mHealth app, most of them (9/11, 82%) in conjunction with supporting materials [57,58,60-63,65-67]; however, none of the studies specified using a DTx app.

The studies that focused on PA had mixed results regarding QOL measurements. Ochi et al [57] randomized 50 breast cancer survivors to receive an mHealth app and a smartwatch or a smartwatch alone for 12 weeks. The app delivered a home-based exercise program, habit-B, with exercises designed to incrementally increase the patients’ level of strength. The intervention group showed significant improvements in some physical functions, including aerobic capacity (peak oxygen uptake) and leg strength, compared with the control group. However, no significant differences were observed for QOL measurements [57]. In the RCT conducted by Lozano-Lozano et al [60], which involved 80 breast cancer survivors who were overweight or obese at diagnosis, both groups received access to an mHealth app, BENECA, but the intervention group also received an in-person rehabilitation program. The app encouraged monitoring of daily dietary and PA habits to monitor energy feedback. The rehabilitation program included group sessions that focused on symptoms, therapeutic exercises, and psychomotricity, which refers to movements intended to enhance potential development or recovery and encompasses aspects of self-awareness [68,69]. At the end of the 8-week intervention, an improvement in QOL measures was found in both groups, but the increase was significantly greater in the intervention group, as was upper limb functionality and active range of motion of the shoulder [60]. Uhm et al [67] compared a 12-week exercise regimen delivered through an mHealth app along with a pedometer with the same program delivered in brochure form in a sample of 356 breast cancer survivors. Both groups were found to have a significant increase in QOL, physical function, and self-reported PA. The difference between the groups was not significant [67].

Nápoles et al [62] had a mixed focus on symptom burden, self-efficacy, and PA in their feasibility study. In this small study, 23 Spanish-speaking breast cancer survivors received access to an mHealth app, trackC, with an integrated activity tracker, hard-copy informational material, and telecoaching. The app included individual treatment history as well as information on potential side effects, healthy lifestyles, and survivorship resources. The integrated activity tracker was intended to promote PA through daily step goals. At the end of the 2-month intervention, significant improvements were observed in fatigue, health distress, and emotional well-being compared with baseline. Daily steps and self-reported knowledge of cancer care and resources increased significantly. However, no significant change was observed in self-efficacy [62]. Another study focusing on Spanish-speaking breast cancer survivors also included a focus on symptom burden. In their pilot study, Yanez et al [61] randomized 80 Latina breast cancer survivors to receive 1 of 2 mHealth apps. The intervention group received access to MyGuide, an mHealth app designed to reduce symptom burden and improve QOL through educational content, medication adherence, social support and psychosocial adaptation, stress management, and coping strategies. The control group received access to MyHealth, an mHealth app designed to promote healthy lifestyle behaviors such as nutrition and PA. Both groups also received telecoaching. At the end of the 6-week intervention, an improvement in symptom burden was observed in both groups; however, no significant differences were observed between the groups [61].

Krok-Schoen et al [63] focused on increasing adherence to adjuvant hormone therapy. In this pilot study, 39 postmenopausal breast cancer survivors received daily SMS text message reminders as well as access to an mHealth app intended for self-reporting medication adherence. At the end of the 3-month intervention, self-reported medication adherence increased significantly from baseline, and blood tests confirmed lower hormone levels, suggesting accuracy in the self-report measurements. Moreover, significant improvements were observed in mental health functioning and perceived stress [63]. In their pilot study, Graetz et al [66] randomized 44 breast cancer survivors who had been prescribed aromatase inhibitors (AI) to have access to an app that encouraged tracking medication adherence and treatment-related symptoms. The intervention group had access to the app and also received weekly SMS text message or email reminders to use the app whereas the control group received app only. At the end of the 8-week intervention, both groups showed an increase in symptom burden after AI initiation; although the increase was less in the intervention group, it did not reach a statistical significance. The intervention group reported higher AI adherence and higher weekly app use [66].

Fu et al [58] focused on lymphedema prevention and management. Breast cancer survivors (n=120) reporting pain or lymphedema symptoms were randomized to 1 of 2 web- and mobile-based programs. The intervention group received a program called The-Optimal-Lymph-Flow (TOLF), which included web-based educational information and lymphatic exercises as well as an mHealth app for performing the exercises on the go. The control group received an arm precaution program with web-based information on precautionary lifestyle behaviors as well as mobility exercises, also accessible via an mHealth app. At the end of the 12-week intervention, the TOLF group reported significantly fewer cases and less severity of chronic pain than the arm precaution group. Furthermore, the TOLF group reported significantly fewer cases of arm or hand swelling, heaviness, redness, and limited mobility in the arm and shoulder. However, neither the mean number of lymphedema symptoms nor the cases of general bodily pain differed between the groups. Significant improvements were observed in QOL measurements in both groups [58].

The study by Visser et al [65], which included 122 breast cancer survivors, focused on psychosocial support and the efficacy of group medical consultations (GMCs). Participants were randomized to receive face-to-face GMCs along with access to an mHealth app, myGMC, or care as usual. The intervention group received an iPad with the myGMC app, along with a video chat app (FaceTalk), a reading app with additional information (iBooks), and a contact information app. The app included videos of interviews with breast cancer survivors. Online group support sessions were held via FaceTalk. No significant differences were observed between the intervention group and the control group in terms of measurements of distress, empowerment, cancer worry, or QOL; however, a small yet significant improvement was found in medication adherence in the intervention group. The intervention group reported significantly more peer support in the face-to-face meetings than in the online group support meetings, and overall app satisfaction was low [65].

Only 2 (18%) of the 11 studies delivered an app-only intervention to breast cancer survivors. Çınar et al [59] randomized 64 breast cancer survivors undergoing hormone therapy to an mHealth app intervention or a control group for 12 weeks. The app featured educational content, relaxation techniques, and a symptom diary, as well as daily personalized reminders related to patient care.A positive impact was observed on the majority of the QOL measurements (FACT-ES) as well as a significant reduction in distress levels in the intervention group compared with the control group [59]. Imai et al [64], who also delivered an app-only intervention, addressed the fear of recurrence. In their pilot study, 38 breast cancer survivors received problem-solving therapy (PST) through an mHealth app. The app included sessions outlining PST and its principles and skills. After gaining an understanding of PST, the participants used a worksheet within the app to work on problems that were triggering a fear of recurrence. At the end of the 8-week intervention, overall fear of recurrence reduced significantly from baseline [64].

Risk-of-Bias Assessment

Studies that included a randomization element were scored using the Cochrane risk-of-bias tool. The studies not included in the bias assessment were nonrandomized pilot and feasibility studies [62-64] and a nonrandomized prospective cohort study [54]. In all studies (n=13), at least 1 domain was scored as high risk of bias or unclear risk of bias. Among the 13 studies, random sequence generation was scored as high risk of bias in 1 (8%) and unclear risk of bias in 4 (31%). Allocation concealment was scored inadequate or unclear risk of bias for the majority of the studies (9/13, 69%). Blinding of participants and personnel was not performed or unclear in 11 (85%) of the 13 assessed studies. None of the studies were classified as high risk of bias for incomplete outcome data; however, 1 (8%) of the 13 studies was deemed to have an unclear risk of bias. No studies were deemed to have a high risk of bias for selective reporting. Of the 13 studies, 2 (15%) were considered to have a high risk of bias for other sources of bias. Risk of bias in multiple domains was present in the majority of the studies (8/13, 62%). The majority of the studies (10/13, 77%) were deemed to have an unclear risk of bias on at least 1 domain. The results of the risk-of-bias assessment are presented in Figure 2 [51-53,55-61,65-67].

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Discussion

Principal Findings

This study synthesizes the literature on the effects of lifestyle interventions via mHealth apps on QOL and well-being in patients with breast cancer. As digital interventions and health apps continue to grow in popularity, critical reviews of the available evidence in this field must follow with the aim of easily accessible, evidence-based, and clinically accepted DTx becoming available to all patients with breast cancer and survivors. A total of 17 studies were identified that delivered a lifestyle or behavioral intervention to patients with breast cancer or survivors with the support of a mobile app, including measurements of QOL or well-being. All apps identified in the results were mHealth apps; however, none of the studies mentioned DTx, indicating that the interventions have not been through a regulated approval process. Overall, the results of the review indicate that mobile apps are a promising avenue for improving QOL and well-being in patients with breast cancer and survivors.

All mobile app interventions delivered during active treatment resulted in some form of positive effect on QOL or well-being. The majority of the studies (5/6, 83%) focused on symptom management [52-56]. Although some of the studies (2/6, 33%) included measurements for anxiety [55,56], only 1 (17%) of the 6 studies focused on mental health as the primary outcome [51] and was the only study to observe a significant reduction in anxiety. This may speak to a need for including mental health–focused elements in addition to symptom management when designing mHealth apps for patients with breast cancer.

Among the studies focusing on symptom management in patients with breast cancer, the majority (4/5, 80%) focused on patients undergoing chemotherapy [52,54-56]. However, only 1 (25%) of these 4 studies specifically addressed women with metastatic breast cancer [56]. This may point to a lack of available mobile apps that aim to improve QOL in women with advanced stage breast cancer.

Although all studies delivering a mobile app intervention during active clinical care observed positive effects on QOL or well-being, only 1 (17%) of these 6 studies included a long-term follow-up period [55]. At 6 months after active treatment, no significant differences were observed between the intervention and control groups. Although self-efficacy improved and QOL reduction was less in the intervention group, the positive effects were not sustained after completion of chemotherapy [55]. This may hint at either a need for continued support or an alternative intervention strategy after completion of chemotherapy. Furthermore, not all interventions covered the full duration of active clinical treatment, which, combined with the lack of follow-up, means that the long-term effects of the mobile app interventions cannot be accurately predicted. Similarly, for breast cancer survivors, only 2 (18%) of the 11 studies included a follow-up period [61,65]; of these 2 studies, 1 (50%) observed some sustained positive effect at the 2-week follow-up [61]. This highlights the need to gain further knowledge of the long-term effects of mobile app–driven lifestyle interventions on QOL and well-being in patients with breast cancer and survivors.

Overall, the results for breast cancer survivors varied more so than those for patients with breast cancer. Of the 3 studies focusing primarily on PA [57,60,67], only 2 (67%) observed a significant positive effect on QOL [60,67]; of these 2 studies, 1 (50%) also included an in-person rehabilitation program, to which some of the positive effects could be attributed [60]. Improvements in QOL were also observed when the intervention combined multiple factors affecting QOL, such as PA, reduction of symptom burden, and nutrition [61,62]. This might highlight a need for a multifaceted solution combining PA and symptom management strategies to improve QOL and well-being in breast cancer survivors.

Of the 6 studies involving patients with breast cancer, 5 (83%) delivered an app-only intervention [52-56], whereas of the 11 studies identified as aiding breast cancer survivors, only 2 (18%) delivered an app-only intervention [59,64]. The remaining studies used various supporting materials in addition to the app, such as wearables [57,62], printed materials [62], non–app-based reminders [57,63,66], web-based information [58,65], non–app-based coaching or group support [51,61,62,65], and an in-person group rehabilitation program [60]. Ease of use has been identified as an important preference when it comes to mHealth interventions in breast cancer care [70]. Using multiple supporting materials, such as printed materials, a website, and an app, could cause participants to feel overwhelmed or confused as to where to seek information and support. Considering that undergoing and recovering from breast cancer treatment can cause psychological distress [7,8], it is important to avoid potentially adding to this distress with overly complicated intervention materials. In addition, spreading out the information across multiple sources may lead to confusion, reduced motivation, and ultimately reduced long-term adherence. Furthermore, the majority of the studies (8/10, 80%) observed positive effects on QOL or well-being variables [58-64,67]; however, because of the various supporting materials used, the positive effects observed cannot be attributed to the mHealth apps alone. Equally, it may be worth researching which supporting materials could be incorporated into the app to aid ease of use. An important aspect is also the design of the mHealth app itself. A successful mobile intervention for breast cancer is dependent upon collaboration among the designers, patients, and various health professionals, including nurses [71].

In the studies focusing on patients with breast cancer, all control groups received the usual standard of care. However, for breast cancer survivors, the condition for the control group, when there was one, differed greatly. Many of the control groups also received access to an mHealth app, either an alternative app (2/8, 25%) [58,61] or the same app but without certain supporting materials (2/8, 25%) [60,66], and many observed an increase in QOL measures for both groups (3/8, 38%) [58,60,61]. However, this does warrant more research into identifying which aspects of the mobile app–driven interventions are the most effective in improving QOL and well-being as well as the ideal content for a placebo app.

Intervention length varied, ranging from 3 to 12 weeks for patients with breast cancer and 6 to 12 weeks for breast cancer survivors. All studies involving patients with breast cancer observed some positive effects on QOL or mental well-being, regardless of intervention length. In terms of breast cancer survivors, most of the studies (8/11, 73%) observed some positive effects on QOL or mental well-being. The shortest intervention [61] observed QOL improvements that were similar to those of the longer ones [58,60,62-64,67]. Further research is needed to determine the optimal intervention length during active treatment as well as the ideal length and focus of a long-term support program.

This is the first review to focus on breast cancer–specific mobile apps and their effect on QOL. The review is based on a strict search strategy and a clear focus on lifestyle interventions and QOL. However, certain limitations need to be addressed. Only English-language articles were included; we neither performed a statistical analysis nor evaluated the studies for quality. Furthermore, although the majority of the included studies (10/17, 59%) were RCTs, a number of them (5/17, 29%) were feasibility or pilot studies [61-64,66], which limits the strength of the results. The studies that included a randomization element were assessed for risk of bias, and the assessment revealed that the most common risk of bias identified was related to blinding. Blinding participants and researchers to allocation to study group is challenging in the case of a lifestyle intervention, in particular because knowledge of the optimum dose of such interventions is not known. Thus, designing a placebo version of a mobile app may not be feasible, and blinding may therefore be difficult. Despite the limitations of this review, the results indicate that the use of mobile apps to improve QOL and well-being in patients with breast cancer and survivors is promising. Further research that includes mental health and psychosocial components is needed. In addition, further research delivering mobile app interventions without supporting materials is needed to fully determine the effectiveness of such apps. Future research would benefit from investigating long-term effects of mobile app–delivered lifestyle interventions in both patients with breast cancer and survivors.

Conclusions

On the basis of this new and updated synthesis of current research on mobile apps for QOL and well-being in breast cancer care, suggestive conclusions can be drawn despite limitations owing to methodological differences of the studies. In particular, positive effects on QOL were observed in patients undergoing active treatment in all reviewed studies, whereas the effects were less clear in the months after chemotherapy and in long-term survivors. This may indicate a need for better understanding of patient needs when developing mHealth interventions for long-term survivors in terms of personalized approaches and adaptive therapies that can adjust to the changing needs of cancer survivors. Lifestyle and behavioral digital interventions are still being developed, and future solutions may become more sophisticated; however, the available data suggest that current mHealth apps aid patients with breast cancer and survivors and that the likelihood of adverse effects is low. Therefore, although research and improvements should still be pursued, the use of mHealth solutions in breast cancer care should be encouraged because they provide a cost-effective and accessible way to improve QOL and well-being.