Relax, Release, Reboot: My Key To Unlock Undetected Depression

Remember to relax, release, and reboot because without your brain, you cannot walk; without your brain, you cannot feel; without your brain.
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Allen, Nancy Bearg, Rita Foley, In short, this is not a book about "change management" but rather a book about "changing both you AND your business model. When Enzo's dog, Frisket, finds a microchip that Megabyte wants, the villain decides to kidnap the boy to get his dog, in a story based on the computer-animated television program. Even when elements of the original versions are maintained, memories of them influence the narrative encounter. This book considers reimagined texts from several l. Remember to relax, release, and reboot because without your brain, you cannot walk; without your brain, you cannot feel; without your brain, you cannot talk; without your brain, you cannot heal.

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The preview features footage from the original film and sees Rusty Griswold Ed Helms take his wife Christina Applegate and children Skyler Gisondo Two apps provided exercise-based therapy consisting of breathing techniques and yoga. One app focused on diet and one provided activity suggestions. There were ten apps that provided cognitive behavioral therapy and were classified under the multipurpose category.

Fifty psychoeducation apps were general e-books about depression, of which two were fiction and seven were reference manuals ie, medication library , 12 apps provided tips or advice on how to overcome depression, and 11 apps provided education through learning modules or lessons. Five apps provided a collection of resources such as news and journal articles. Five of these were general e-books, one provided tips, and one provided lessons. External sources were reported 21 times and used 11 different questionnaires. The Psychological Tests App contained multiple depression questionnaires.

The 11 expert-sourced apps did not provide a specific questionnaire but mentioned in the description that a medical professional ie, physician or psychologist developed the app or that the questionnaire was used in practice. One app contained a questionnaire based on patient lived experience. With the exception of five apps, all the apps were text-only.

Nine apps allowed users to track their moods and eight tracked lifestyle factors eg, mood, sleep, diet, medication, exercise. Two apps allowed users to keep a journal, and one app used a checklist system. One app reported the content source and cited an external source. Two apps provided resources online and offline and references for help. The other two apps connected users to a community via online forums. Ten of these apps specifically focused on cognitive behavioral therapy CBT , while seven used a questionnaire and allowed users to track depression over time.

One app used a proprietary questionnaire Treatment Depression Inventory. Two apps did not specify the questionnaire. One app provided therapeutic treatment through meditation exercises and also provided psychoeducation about the exercises and CBT. Figure 2 presents a summary and distribution of the different app functions. This review found that depression apps provided support on five different dimensions: Through the iterative development of this typology and understanding of the available commercial information, the results provided some insights into the user experience of those seeking depression support through apps.

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The apps excluded from this study indicate that metadata may play a role in this phenomenon. For example, one-fifth of the search yield made no mention of depression anywhere in the app title or store description. Many of these apps were white-labeled ie, essentially identical but marketed for different purposes or under different developer names and were evident by the identical store descriptions see Figure 3. White labeling was primarily observed for e-book and audio therapy apps.

Last, although some apps made reference to depression, their main purpose was to address a different condition eg, weight loss or acne apps may describe how being obese or having acne may lead to depression. An example of white labeling where the apps have the same description but are labeled as different apps. The word depression circled in red is only one in a list of unrelated terms and is an example of how such lists allow non-depression apps to enter the search. Of the apps included in the study, there were three times more text-only apps than any other media category; furthermore, almost all the text-only apps with static interfaces were found in the psychoeducation app category.

The reviewers found that these apps, based on screenshots and descriptions, were rudimentary in function and minimal in design. The proliferation of these apps may be a result of the low barrier to entry into the marketplace in the form of prerequisite resources and skills, thereby allowing those with minimal programming skills and resources to develop and publish their own apps [ 46 ]. This finding could explain why only one-third of the unique developers adequately described or indicated their affiliation and the proportionately low number of apps from formal institutions.

Furthermore, only a third of the app store descriptions reported content sources. Many other app reviews [ 18 - 23 , 30 , 47 - 51 ] have also found that the app development process often failed to involve health care professionals or academics and to include content aligned with clinical guidelines or behavior change theories or techniques.

The majority of these apps were categorized under the main purposes of psychoeducation and therapeutic treatment. The lack of apps that incorporate authoritative sources remains problematic. It has been estimated that one in five of paid apps claim to treat or cure medical ailments [ 28 ]. Similar to the potential shortcomings of information found on the Internet, the information or therapies provided by apps may be incomplete or based on insufficient scientific evidence.

This presents a potential health hazard for consumers who interpret this information incorrectly or try inappropriate treatments [ 52 ]. For example, reading about a disease may increase health anxiety, reinforce hypochondriasis, cause unnecessary concerns, or lead people to purchase harmful drugs or engage in risky health behaviors [ 53 ].

These harms, however, are often a cautionary claim, as most research on the utility of online health information has focused on the quality of information rather than its effects [ 54 , 55 ]. Only a few studies actually reported instances of harm [ 56 ]. This gap between evidence-based recommendations and app functionality continues to be a common theme across different health conditions [ 20 , 21 , 47 , 51 , 57 - 59 ].

The proceedings were founded on the premise of false advertising rather than public safety [ 61 ]. This case has led to a call for the US Food and Drug Administration FDA to regulate mobile medical apps; however, there is debate about the appropriateness of this measure [ 62 ]. In September , the FDA issued guidance for developers of apps that perform as medical devices, defined as apps that diagnose or treat disease whereby malfunctions can carry significant risks of harm [ 63 ].


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Based on the app store categories used in this study, 42 apps were defined as medical; however, this category included apps that are considered innocuous, such as those that help patients organize their health information or look up information about treatments [ 64 ]. Perhaps these apps would be better suited for other categories, such as health and fitness, lifestyle, and books, where more than half of the included apps were found. Apps found in these non-medical categories are considered low risk as long as they do not provide specific treatments or treatment suggestions.

They may provide benefits to the patient, such as those associated with using a mood tracker to maintain a symptom diary [ 65 ]. To help users navigate the app marketplace, Happtique a subsidiary company of the Greater New York Hospital Association developed standards for an app certification program in early Unfortunately, these efforts were brought to a halt when an audit found that 2 of the 19 Happtique-certified apps had privacy issues [ 66 ].

There are other initiatives to help curate apps, such as the iMedicalApps website; however, it is a tremendous task to benchmark. Policing the quality of apps is a near-impossible endeavor that is reminiscent of the early days of appraising online health information [ 67 ].

Deshpande and Jadad have found that past initiatives to assess the quality of online health information or tools had limited success and recommend that efforts be hedged towards an open, distributed, and collaborative approach similar to Wikipedia [ 68 ]. The most common function of depression apps provides users with information about depression through an e-book modality.

Despite the potential to translate books or bibliotherapeutic guides, only 13 of the 50 e-books cited a content source. The majority of these books were self-help guides, often with titles that claimed they would help users overcome depression. While these non-sourced books do pose the potential to distribute erroneous or biased information to people seeking help, the Google dataset shows that two-thirds of these apps are installed less than times and indicates that users do exercise some discretion before purchasing or installing apps.

Nettleton et al [ 69 ] suggested that users are able to make reasonable assessments of health information in the context of other health information seeking practices to complement their formal care. This behavior extends to mobile phone apps: For example, an e-book app that cited the US National Institutes of Health was downloaded within the 10, installs range.

One study suggested that consumers exercise more caution when having to purchase apps than when downloading them for free due to the burden of price [ 71 ]. The same study also showed that ranking, customer ratings, and content size affect downloading when the app is free. Consumers depend more on their own information and experiences rather than on rankings or ratings when the app requires payment. They closely consider low ratings, including complaints, not mean score when they have to pay [ 71 ]. The relationship between price, affiliation, source, downloads, and satisfaction via ratings and comments could be a potential area to explore in future studies.

Medical assessment was the only app category with a high rate of reporting content source. All of these apps were screening tools that allowed users to self-diagnose for depression. There is an absence of published data investigating the impact of patient self-diagnosis using apps or the Internet; however, some studies have identified false positive assessments as a potential source of harm [ 53 , 72 - 74 ].

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Despite this shortcoming, medical assessment apps could help to address some systemic barriers to diagnosing depression in primary care [ 75 ]. Depression is often under-detected in the health care system, and the practice of routine screening is a contentious and unresolved issue [ 76 ]. Medical assessment apps may help to bridge this gap by assisting individuals in identifying mental health issues, thereby providing the impetus to approach and engage their health care providers.

Clarke and Yarborough described this effect as a lowering of threshold of entry-level mental health services so that it extends the reach of care to people who do not seek traditional treatment for depression [ 5 ]. Audio therapy apps may have a similar potential to that of medical assessment apps [ 77 , 78 ]. The effectiveness of audio therapy, regardless of mode of delivery, is not fully understood and is often under scrutiny [ 47 , 79 - 81 ].

There are many gaps in knowledge regarding the psychological effects of brainwave entrainment and hypnosis on depression [ 82 , 83 ]. Systematic reviews [ 81 ] and meta-analysis [ 84 ] of existing research have found mixed results on the effectiveness of these types of interventions. A similar review of a hypnosis app found on iTunes reported that none of the identified apps were tested for efficacy or were based on evidence [ 47 ]; however, the study did not discuss potential harms associated with using non-evidence-based, non-evaluated apps. They also warn that certification does not mean that the individual was adequately trained.

The fourth most prevalent function of depression apps was offering behavior training or therapy, with most apps focusing on CBT. Internet-based CBT ICBT has shown to be an effective treatment for depression [ 85 ], with the magnitude of effects depending on level of support and content of the intervention [ 86 ]. ICBT is considered to be well suited for delivery through an app because it would offer users the convenience of recording and tracking their moods and context in real time, as well as accessing psychoeducational materials [ 87 ].

Two-thirds of the CBT apps identified in this study had multiple purposes, which often included tracking, screening, and providing psychoeducation. In practice, one study demonstrated the feasibility of app-based CBT in treating depression, with clinical improvement in the patients [ 26 ]. This app was captured in the sample and provided a very brief description mentioning the CBT program and its affiliation with a hospital; however, the raters felt it did not provide sufficient information about the intervention source.

This shortcoming underscores the importance for app developers to follow a standardized reporting system to advertise the credibility of apps and to prevent empirically tested apps from going unnoticed. Similarly, it might be necessary to develop a framework that could protect both app developers and users from harm, particularly from liability associated with cases of preventable suicide. While the development of regulations and certification standards for assessing the quality of apps is underway, this study used the information available in the app store description ie, developer affiliation and content source to understand how depression apps are advertised to health consumers seeking depression apps.

The information provided about affiliation and content source was accepted prima facie based on the developed inclusion criteria. The high percentage of insufficient reporting of affiliation may be an overestimation, since the developer websites were not examined to corroborate their status.

Who gets depression?

Similarly, the reported content sources were not further examined. It is acknowledged that the apps themselves may contain more information and that not downloading and testing the apps is a limitation of this study. The lack of physical testing mirrors the actual user experience when making the decision to download apps [ 48 ], where the information provided in the description may serve as an initial proxy measure for quality before downloading and trialing an app.

It also underscores the need for a standardized app store description reporting system for vendors to refer or adhere to.

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With over unique developers identified in our eligible sample and many more in the initial sample, consumers may not have the time to view all the developer websites to verify their affiliations. Requiring vendors to outline their affiliations, evidence base, or content source could provide potential users with enough contexts to assess the credibility of the app. A second limitation lies in the possibility that many of the apps excluded from this study because they were not depression specific could potentially be useful for people with depression.

ICBT apps are prime examples of potentially useful non-depression-specific apps. ICBT is regarded as a well-established treatment for depression, panic disorder, and social phobia, but it is also an option for 25 other clinical disorders. While ICBT apps could be the prototypical depression app [ 26 , 88 ], non-depression ICBT apps were excluded to maintain consistency in assessing the relevance of other apps that provided an intervention eg, binaural beats [ 81 ], yoga [ 89 ], spirituality [ 90 ] where a case could be made for their inclusion.

To prevent confirmation biases from entering the sample, it was decided that the app was required to be specific to depression to be eligible. This study represents a snapshot of depression apps found in Canadian app stores in March of This may be a limitation in three ways. First, the landscape of the depression market will have changed at the time of submission of this publication. Second, the findings from this study may not be representative of all the depression apps available on the global market because certain apps may be localized or licensed only to specific countries.

The study by Martinez-Perez et al in Spain found over depression apps available on the five major platforms. In comparison, the current review yielded unique apps, with a large part of the discrepancy attributed to Google Play app count.


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Moreover, a sample of Android apps may be missing because this study was conducted just prior to the Amazon announcement [ 91 ] of expanding access to its Android app store outside of the United States to Canada and other countries. Because development standards vary from different app stores, future content analysis studies should consider including the Amazon marketplace to understand its contributions to the app marketplace. These models provide some important parameters that were not covered in this study eg, data requisition and management, advertising policy, justification of claims.

However, this study demonstrates that most apps would fare poorly against the aforementioned standards and delineates the need for such reporting approaches to be disseminated to mHealth developers to bring the information presented to health consumers to an acceptable level. This study found that finding an appropriate depression app may be challenging due to the large quantity available.

The search results yielded non—depression-specific apps to depression apps at a ratio of 3: Over one-quarter of the apps excluded from the study failed to even mention depression in their description or title and exemplify the role of metadata in populating the search results. The lack of reporting of organizational affiliation and content source brings the credibility into question. Whether the content is evidence-based is a whole other issue.

This lack of information was most common among symptom management apps, followed by therapeutic treatment and psychoeducation apps. Only medical assessment apps, many of which were based on well-established depression questionnaires, adequately described their sources. While efforts are underway to populate the marketplace with certifications and professional vetting, this study delineates the need for standards in reporting and for a framework to enable people with depression or other conditions to use proxy measures to assess the legitimacy of apps. The authors of this study would like to thank Hema Zbogar for her editorial assistance in preparing the manuscript for submission.

National Center for Biotechnology Information , U. Published online Feb This is an open-access article distributed under the terms of the Creative Commons Attribution License http: The complete bibliographic information, a link to the original publication on http: This article has been cited by other articles in PMC.

Abstract Background Depression is highly prevalent and causes considerable suffering and disease burden despite the existence of wide-ranging treatment options. Objectives Our goal was to identify and characterize the different types of mobile phone depression apps available in the marketplace. Methods A search for depression apps was conducted on the app stores of the five major mobile phone platforms: Results Of the apps identified by the search strategy, nearly one-quarter Conclusion Without guidance, finding an appropriate depression app may be challenging, as the search results yielded non-depression—specific apps to depression apps at a 3: Introduction Depression is a serious, common, and recurring disorder linked to diminished functioning, quality of life, medical morbidity, and mortality [ 1 ].

Methods Overview We used a systematic review and content analysis approach based on a study by Bender et al [ 30 ] to guide the collection and characterization of available depression apps. Data Extraction and Coding Information was extracted from the store descriptions of the apps for the following variables: Table 1 Final codebook for content analysis. Source identified but no credential mentioned. Provides referrals for help or connects users with support. Static user interface that provides minimal interaction eg, e-book. Not enough information to determine types of media used.

Open in a separate window. Results General Characteristics The initial search yielded apps, of which 53 were excluded as duplicates 31 were available in two stores, eight in three stores, two in four stores, and one in all stores. Flow diagram illustrating the exclusion of apps at various stages of the study.

Developers and Affiliations There were developers in the sample, with 35 accounting for multiple apps. Depression Apps Ratings Of the rated apps Table 2 Distribution of depression apps by variable and main purpose. Discussion Principal Findings This review found that depression apps provided support on five different dimensions: Evaluation The most common function of depression apps provides users with information about depression through an e-book modality.

Limitations While the development of regulations and certification standards for assessing the quality of apps is underway, this study used the information available in the app store description ie, developer affiliation and content source to understand how depression apps are advertised to health consumers seeking depression apps. Conclusions This study found that finding an appropriate depression app may be challenging due to the large quantity available. Acknowledgments The authors of this study would like to thank Hema Zbogar for her editorial assistance in preparing the manuscript for submission.

Click here to view. Footnotes Conflicts of Interest: The epidemiology of depression across cultures. Annu Rev Public Health. Disability-adjusted life years DALYs for diseases and injuries in 21 regions, The Global Burden of Disease: World Health Organization; Transdiagnostic internet treatment for anxiety and depression: Clarke G, Yarborough BJ. Perceived barriers to psychological treatments and their relationship to depression.

Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: Richards D, Richardson T. Computer-based psychological treatments for depression: Computer-delivered and web-based interventions to improve depression, anxiety, and psychological well-being of university students: J Med Internet Res. Leveraging community for mHealth research and development. Technology Enabled Knowledge Translation for eHealth. Integrating smartphone technology in behavioral healthcare.

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Perspectives on Psychological Science. Smartphones for smarter delivery of mental health programs: The future is in our hands: Aust N Z J Psychiatry. Harrison AM, Goozee R. Commercially available mobile phone headache diary apps: An evaluation of mobile health application tools. Am J Prev Med. A content analysis of popular smartphone apps for smoking cessation.