Digital health developments and drawbacks: a review and analysis of top-returned apps for bipolar disorder

Lagan, Sarah; Ramakrishnan, Abinaya; Lamont, Evan; Ramakrishnan, Aparna; Frye, Mark A.; Torous, John

doi:10.1186/s40345-020-00202-4

Cited by 38 publications

(34 citation statements)

References 43 publications

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“…18 The goal of this database is to make information transparent and to provide an accessible space where any interested users can filter apps. The framework underscoring MIND has been validated in analyses of apps for schizophrenia, 19 bipolar disorder, 20 and Spanish language speakers. 21 As each app in MIND is evaluated across 105 dimensions, the database offers a novel source to assess questions around current offerings, their quality, features, and overlap.…”

Section: Introductionmentioning

confidence: 99%

Assessing mental health apps marketplaces with objective metrics from 29,190 data points from 278 apps

Lagan

D’Mello

Vaidyam

et al. 2021

Acta Psychiatr Scand

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Objective: Utilizing a standard framework that may help clinicians and patients to identify relevant mental health apps, we sought to gain a comprehensive picture of the space by searching for, downloading, and reviewing 278 mental health apps from both the iOS and Android stores. Methods: 278 mental health apps from the Apple iOS store and Google Play store were downloaded and reviewed in a standardized manner by trained app raters using a validated framework. Apps were evaluated with this framework comprising 105 questions and covering app origin and accessibility, privacy and security, inputs and outputs, clinical foundation, features and engagement style, and interoperability. Results: Our results confirm that app stars and downloads-even for the most popular apps by these metrics-did not correlate with more clinically relevant metrics related to privacy/security, effectiveness, and engagement. Most mental health apps offer similar functionality, with 16.5% offering both mood tracking and journaling and 7% offering psychoeducation, deep breathing, mindfulness, journaling, and mood tracking. Only 36.4% of apps were updated with a 100-day window, and 7.5% of apps had not been updated in four years. Conclusion: Current app marketplace metrics commonly used to evaluate apps do not offer an accurate representation of individual apps or a comprehensive overview of the entire space. The majority of apps overlap in terms of features offered, with many domains and other features not well represented. Selecting an appropriate app continues to require personal matching given no clear trends or guidance offered by quantitative metrics alone. K E Y W O R D S digital health, apps, internet therapy Significant outcomes• App store star ratings and number of downloads are not associated with app features, function, or evidence. • Mood/symptom tracking, journaling, mindfulness, psychoeducation, and deep breathing are the five most common offering of mental health apps. • Nearly 1/3 of apps may update in a 100-day period, suggesting need to for constant evaluation.

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Section: Introductionmentioning

confidence: 99%

Assessing mental health apps marketplaces with objective metrics from 29,190 data points from 278 apps

Lagan

D’Mello

Vaidyam

et al. 2021

Acta Psychiatr Scand

Self Cite

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“…Rising suicide and depression rates reflect an exigent, unmet need for innovative treatment options (Torous and Wykes, 2020). Despite significant advancements in healthcare technology, digital health solutions for mental health continue to fall short of their potential across both clinical practice and in terms of clinical efficacy (Lagan, 2020 a , 2020 b ). The utility and impact of medicine, including digital medicine, hinges on relationships and trust, particularly in the field of mental health (Torous and Roberts, 2017).…”

Section: Introductionmentioning

confidence: 99%

Cross cultural and global uses of a digital mental health app: results of focus groups with clinicians, patients and family members in India and the United States

et al. 2021

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Background Despite significant advancements in healthcare technology, digital health solutions – especially those for serious mental illnesses – continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India. Methods Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality. Results Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement. Conclusion People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary – not substitutive – of therapeutic care from a clinician.

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“…Many people own and use a smartphone and smartphones comprise a unique platform for unobtrusive and continuous monitoring. Due to the limited access to treatment facilities, during the past 10 years, and especially during the COVID-19 pandemic, there has been an increase in the international interest in the use of mHealth technologies within mental health (Insel 2017 ; Wang et al 2018 ; Anthes 2016 ; Patoz et al 2021 ; Lagan 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Voice analyses using smartphone-based data in patients with bipolar disorder, unaffected relatives and healthy control individuals, and during different affective states

Faurholt‐Jepsen

Rohani

Busk

et al. 2021

Int J Bipolar Disord

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Background Voice features have been suggested as objective markers of bipolar disorder (BD). Aims To investigate whether voice features from naturalistic phone calls could discriminate between (1) BD, unaffected first-degree relatives (UR) and healthy control individuals (HC); (2) affective states within BD. Methods Voice features were collected daily during naturalistic phone calls for up to 972 days. A total of 121 patients with BD, 21 UR and 38 HC were included. A total of 107.033 voice data entries were collected [BD (n = 78.733), UR (n = 8004), and HC (n = 20.296)]. Daily, patients evaluated symptoms using a smartphone-based system. Affective states were defined according to these evaluations. Data were analyzed using random forest machine learning algorithms. Results Compared to HC, BD was classified with a sensitivity of 0.79 (SD 0.11)/AUC = 0.76 (SD 0.11) and UR with a sensitivity of 0.53 (SD 0.21)/AUC of 0.72 (SD 0.12). Within BD, compared to euthymia, mania was classified with a specificity of 0.75 (SD 0.16)/AUC = 0.66 (SD 0.11). Compared to euthymia, depression was classified with a specificity of 0.70 (SD 0.16)/AUC = 0.66 (SD 0.12). In all models the user dependent models outperformed the user independent models. Models combining increased mood, increased activity and insomnia compared to periods without performed best with a specificity of 0.78 (SD 0.16)/AUC = 0.67 (SD 0.11). Conclusions Voice features from naturalistic phone calls may represent a supplementary objective marker discriminating BD from HC and a state marker within BD.

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Digital health developments and drawbacks: a review and analysis of top-returned apps for bipolar disorder

Cited by 38 publications

References 43 publications

Assessing mental health apps marketplaces with objective metrics from 29,190 data points from 278 apps

Assessing mental health apps marketplaces with objective metrics from 29,190 data points from 278 apps

Cross cultural and global uses of a digital mental health app: results of focus groups with clinicians, patients and family members in India and the United States

Voice analyses using smartphone-based data in patients with bipolar disorder, unaffected relatives and healthy control individuals, and during different affective states

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