Optimizing smartphone intervention features to improve chronic disease management: A rapid review

Gomolin, Arieh; Lebouché, Bertrand; Engler, Kim; Vedel, Isabelle

doi:10.1177/1460458219891377

Cited by 10 publications

(7 citation statements)

References 28 publications

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“…Moreover, only some include interactive components, such as support for self-care and communication with health care professionals and peers for immediate clinical management [ 7 , 9 - 12 ]. A key aspect of digital interventions is to understand how they operate and how they can be enhanced by assessment of usage and user experiences [ 13 - 17 ].…”

Section: Introductionmentioning

confidence: 99%

Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study

et al. 2020

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Background Using mobile technology for symptom management and self-care can improve patient-clinician communication and clinical outcomes in patients with cancer. The interactive app Interaktor has been shown to reduce symptom burden during cancer treatment. It includes symptom assessment, an alert system for contact with health care professionals, access to self-care advice, and visualization of symptom history. It is essential to understand how digital interventions operate; one approach is to examine engagement by assessing usage and exploring user experiences. Actual usage in relation to the intended use—adherence—is an essential factor of engagement. Objective This study aimed to describe engagement with the Interaktor app among patients with breast or prostate cancer during treatment. Methods Patients from the intervention groups of two separate randomized controlled trials were included: patients with breast cancer receiving neoadjuvant chemotherapy (n=74) and patients with locally advanced prostate cancer receiving treatment with radiotherapy (n=75). The patients reported their symptoms daily. Sociodemographic and clinical data were obtained from baseline questionnaires and medical records. Logged data usage was retrieved from the server and analyzed descriptively and with multiple regression analysis. Telephone interviews were conducted with patients about their perceptions of using the app and analyzed using content analysis. Results The median adherence percentage to daily symptom reporting was 83%. Most patients used the self-care advice and free text message component. Among the patients treated for breast cancer, higher age predicted a higher total number of free text messages sent (P=.04). Among the patients treated for prostate cancer, higher age (P=.01) and higher education level (P=.04), predicted an increase in total views on self-care advice, while higher comorbidity (P=.004) predicted a decrease in total views on self-care advice. Being married or living with a partner predicted a higher adherence to daily symptom reporting (P=.02). Daily symptom reporting created feelings of having continuous contact with health care professionals, being acknowledged, and safe. Being contacted by a nurse after a symptom alert was considered convenient and highly valued. Treatment and time-related aspects influenced engagement. Daily symptom reporting was perceived as particularly meaningful at the beginning of treatment. Requests were made for advice on diet and psychological symptoms, as well as for more comprehensive and detailed information as the patient progressed through treatment. Conclusions Patient engagement in the interactive app Interaktor was high. The app promoted patient participation in their care through continuous and convenient contact with health care professionals. The predictive ability of demographic variables differed between patient groups, but higher age and a higher educational level predicted higher usage of specific app functions for both patient groups. Patients’ experience of relevance and interactivity influenced their engagement positively.

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Section: Introductionmentioning

confidence: 99%

Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study

et al. 2020

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“…Moreover, only some include interactive components, such as support for self-care and communication with health care professionals and peers for immediate clinical management [7,[9][10][11][12]. A key aspect of digital interventions is to understand how they operate and how they can be enhanced by assessment of usage and user experiences [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study (Preprint)

Crafoord¹,

Fjell²,

Sundberg³

et al. 2019

Preprint

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BACKGROUND Using mobile technology for symptom management and self-care can improve patient-clinician communication and clinical outcomes in patients with cancer. The interactive app Interaktor has been shown to reduce symptom burden during cancer treatment. It includes symptom assessment, an alert system for contact with health care professionals, access to self-care advice, and visualization of symptom history. It is essential to understand how digital interventions operate and an approach to research this empirically includes to examine engagement by assessing usage and exploring user experiences. Actual usage in correspondence to the intended use – adherence - is an essential factor of engagement. OBJECTIVE This study aims to describe engagement with the Interaktor app among patients with breast and prostate cancer during their treatment. METHODS All patients from the intervention groups of two separate randomized controlled trials were included. Patients with breast cancer receiving neoadjuvant chemotherapy (n=74) and patients with locally advanced prostate cancer receiving treatment with radiotherapy (n=75). The patients reported their symptoms daily. Sociodemographic and clinical data were obtained from baseline questionnaires and medical records. Logged data usage was retrieved from the server and analyzed descriptively and with multiple regression analysis. Telephone interviews were conducted with patients about their perceptions of using the app and analyzed using content analysis. RESULTS The median adherence to daily symptom reporting was 83%. Most patients used the self-care advice and free text message component. Among the patients treated for breast cancer, higher age predicted a higher total number of free text messages sent (P = .04). Among the patients treated for prostate cancer, higher age (P = .01) and higher education level (P = .04), predicted an increase in total views on self-care advice, whilst higher comorbidity (P = .004) predicted a decrease in total views on self-care advice. Being married or living with a partner predicted a higher adherence to daily symptom reporting (P = .02). Daily symptom reporting created feelings of having continuous contact with health care professionals, being acknowledged, and safe. Being contacted by a nurse after a symptom-alert was considered convenient and highly valued. Treatment and time-related aspects influenced engagement. Daily symptom reporting was perceived as particularly meaningful at the beginning of treatment. Requests were made for advice on diet and psychological symptoms, as well as more comprehensive and detailed information as the patient progressed through treatment. CONCLUSIONS Patient engagement in the interactive app Interaktor was high. The app promoted patient participation in their care through continuous and convenient contact with health care professionals. The predictive ability of demographic variables differs in between patient groups, but higher age and a higher educational level predicts higher usage of specific app-functions for both patient groups. Patients’ experience of relevance and interactivity influence their engagement positively. CLINICALTRIAL RCT Breast cancer NCT02479607 RCT Prostate cancer NCT02477137

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“…Reasons for exclusion included content tailored to a specific disease, protocols or design studies, study registrations, and additional reasons can be found in Figure 1. No further studies were found after back-referencing reviews in digital behaviour change interventions [27,11,13,28,15,24,12].…”

Section: Results Of the Searchmentioning

confidence: 99%

“…Digital health technologies are enabling real-time customisation of care by providing means for monitoring, anticipating, responding, and learning from patients' reported data and vital signs measured [10]. Digital technologies such as internet of things (IoTs) and mobile health systems (mHealth) have been used to exchange real-time data through multiple devices to assess disease progression, intervention effective-ness, acceptability, and other patient's specific parameters [11,12,13,14,15,16].…”

Section: Introductionmentioning

confidence: 99%

Behaviour change interventions based on automated and tailored communication systems to improve health outcomes in adult chronic patients: a systematic review

Martins

Londral

Lapão

2022

Preprint

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Background: Behaviour change digital-assisted interventions can be a low-cost solution to enduring healthy behaviours. Understanding how to automate and tailor such interventions to patients’ needs can improve health outcomes. This study aims at reviewing the evidence of the use of such interventions in a clinical setting in adult chronic patients. Methods: This study followed the PRISMA guidelines for comprehensive search, appraisal, and synthesis of research evidence. A literature search was performed to find studies published between 1 January 2017 and 26 March 2022 in peer-reviewed journals and written in English. Behaviour change interventions in adult chronic patients with automated and tailored communication systems were considered. Results: Seven quantitative studies (6 RCT and a pilot RCT) with sample sizes from 54 to 506 participants and timeframes varying from 4 to 30 weeks met the eligibility criteria. Populations comprehended patients with cardiovascular disease, chronic kidney disease, diabetes, or osteoarthritis. Communication channels included SMS, email, and voice records. Rule-based models were used to automate content in all studies and bidirectional communication was used in four of them. Content and service delivery were tailored given the patient’s goals, needs, functional ability, activity, personal characteristics, and communication channel preferred. Most data management platforms used were developed in prior studies. Interventions were designed based on 9 different behaviour change models. There was no evidence of improvements in clinical outcomes after the intervention. Some studies showed improvements in self-efficacy (n=1), the use of dietary data info (n=1), physical activity (n=2), social support (n=1), and quality of life (n=1). The risk of bias analysis revealed that one study had moderate risk and the remaining had low risk. Conclusion: This study supports researchers that are designing digital behaviour change interventions by putting in evidence the intervention’s features needed to be considered during this step. It revealed that the most efficient solutions were tailored to patients’ needs and disease stages and that further research on the mechanisms of change and content automation needs to be done.

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Optimizing smartphone intervention features to improve chronic disease management: A rapid review

Cited by 10 publications

References 28 publications

Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study

Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study

Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study (Preprint)

Behaviour change interventions based on automated and tailored communication systems to improve health outcomes in adult chronic patients: a systematic review

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