The Digital Navigator: Standardizing Human Technology Support in App-Integrated Clinical Care

Abstract

Background:

Mental health apps offer scalable care, yet clinical adoption is hindered by low user engagement and integration challenges into clinic workflows. Human support staff called digital navigators, trained in mental health technology, could enhance care access and patient adherence and remove workflow burdens from clinicians. While the potential of this role is clear, training staff to become digital navigators and assessing their impact are primary challenges.

Methods:

We present a detailed manual/framework for implementation of the Digital Navigator within a short-term, cognitive-behavioral therapy-focused hybrid clinic. We analyze patient engagement, satisfaction, and digital phenotyping data quality outcomes. Data from 83 patients, for the period spanning September 2022 to September 2023, included Digital Navigator satisfaction, correlated with demographics, mindLAMP app satisfaction, engagement, and passive data quality. Additionally, average passive data across 33 clinic patients from November 2023 to January 2024 were assessed for missingness.

Results:

Digital Navigator satisfaction averaged 18.8/20. Satisfaction was not influenced by sex, race, gender, or education. Average passive data quality across 33 clinic patients was 0.82 at the time this article was written. Digital Navigator satisfaction scores had significant positive correlation with both clinic app engagement and perception of that app.

Conclusions:

Results demonstrate preliminary support and patient endorsement for the Digital Navigator role and positive outcomes around digital engagement and digital phenotyping data quality. Through sharing training resources and standardizing the role, we aim to enable clinicians and researchers to adapt and utilize the Digital Navigator for their own needs.

Introduction

CHALLENGES OF INTEGRATION

Smartphone apps and related software present a significant opportunity to enhance the scalability and quality of mental health care. Smartphone apps have clearly demonstrated potential for increasing access to mental health care.^1
–3 However, the impact of apps as self-help tools has been limited by lack of sustained user-level engagement, which is difficult to address outside of an institutional structure. While low engagement has been acknowledged for nearly 20 years,⁴ in 2022, it finally gained widespread recognition as the “Achilles Heel”⁵ and was labeled the single greatest barrier to progress in digital mental health in 2023.⁶

This engagement crisis has prompted interest in adding human support. Recent reviews on the role of human support for digital mental health technologies reveal heterogeneity in the nature of the person (ranging from volunteers to licensed psychologists), the mode of contact (ranging from text messages to face-to-face meetings), the frequency of contact (ranging from daily to a one-time meeting), and the nature of that support (ranging from purely technical to emotional).^7,8 While varied approaches are useful in ensuring that the human support offered can match the local needs of each study or clinic, it also creates a barrier to replication, let alone implementation of the role.

Toward these goals, our team has developed and freely shared training and resources around the Digital Navigator role. The Digital Navigator is a training member of the clinical team, whose goal is to support the uptake and implementation of technology into care. The role focuses on supporting the use of smartphones as these are now used by 85% of adults in the United States,⁹ and are commonly used by patients,¹⁰ compared with computers.

While the role is flexible so that responsibilities will vary with context, in our clinic, they include (1) helping patients in need access technology and offering digital literacy skills training to anyone in need, (2) supporting the selection of apps and engagement with app-based exercises for patients to use between visits, and (3) facilitating the integration of app data into care by providing interpretation of app data to patients and clinicians in a clinically relevant format to help guide care⁸ (Fig. 1).

Fig. 1.

Digital navigator weekly responsibilities.

While we have trained many teams for the role¹¹ and successfully deployed the role in our own clinic,¹² calls for digital navigators have expanded. In 2022, the National Council for Wellbeing noted the potential of the role and how peers could serve in it to help ensure that all individuals, including the most disadvantaged, have access to and can use information technologies, including affordable internet, internet-enabled devices, technical skills, and application support.¹³

In 2023, the California Institute for Behavioral Health Solutions began offering the training to support community mental health centers across the state, and the national SMI Adviser program also launched a free online version of the training.¹⁴ With this expansion of the role, questions around how Digital Navigator training is customized to unique clinics and the impact of the role on outcomes have become more relevant.

Based on examples from our own clinic, this article shares the workflow of the Digital Navigator and offers a comprehensive guide that simplifies the process of replicating this role in other clinical settings. Toward this end, we have outlined the work protocols for a given Digital Navigator along with the training and assessment of qualifications. Finally, we share the results of initial analyses on the relationship between patient demographics, patient self-reported experience using the app, patient time spent on the app, and the quality of passive data collected through the app.

mindLAMP/DIGITAL PHENOTYPING AND THE DIGITAL CLINIC

While the role of the digital navigator is designed to support computer, wearable, and smartphone technology, our clinic focuses on support for the open-source mindLAMP app,¹⁵ which we utilize in our clinic model. The clinic offers hybrid care, with synchronous telehealth visits offered by clinicians and digital navigators supporting asynchronous use of the mindLAMP app between clinical visits.

In this role, the digital navigators are responsible for helping ensure that patients are able to use the mindLAMP app to (1) capture data for interpretation during clinical visits and (2) complete daily therapeutic skills homework exercises. The mindLAMP app captures digital phenotyping data from patients' smartphones to provide behavioral insights about sleep, physical activity, home time, and other related metrics. The accuracy of such metrics is dependent on high-quality data (defined as the percent of actual data captured/requested data)—sensor data from the phone—as resulting behavioral metrics are only as accurate as the data used to infer them.

However, in most clinical studies, the mean percentage of digital phenotyping has a high degree of missingness, starting off at 27% missing and increasing each week.¹⁶

THE ROLE OF THE DIGITAL NAVIGATOR

The Digital Navigator supports patients by teaching digital literacy skills as needed, customizing the mindLAMP app to the clinical needs determined by the patient–clinician dyad each week, and offering engagement support through data monitoring and regular meetings with patients. The Digital Navigator supports clinical integration by screening digital phenotyping data from the app for data quality, assessing for any overriding trends, and generating visualizations and summaries of data for clinicians (Fig. 2).

Fig. 2.

A schematic of the hybrid clinic workflow.

Standardizing the role

Creating a protocol for the clinic and digital navigator role aided in ensuring standardization of training and procedures. The manual provided below in Appendix A of Supplementary Data includes training materials provided to digital navigators, including a description of mindLAMP, how it is used, and instructions on clinical implementation.

This incorporates instructions for adherence and proficiency improvement methods; for example, troubleshooting strategies, such as how to improve low-quality data collected by the app through appropriate phone setting configuration, and avoiding phone features that limit data collection, such as battery optimization. The manual contains specific descriptions of the visualizations derived from the clinical data as well as how to effectively communicate them.

Training

The manual encompasses a quick protocol guide for training digital navigators. The Digital Navigator position requires roughly 10 h of training before working with patients and can operate as a full-time job. It is also feasible for volunteers with large vocational workloads (full-time job or full-time student) without significant burden. Extensive clinical experience or knowledge is not required to become a digital navigator. After a short interview, passing the volunteer screening process, completing the necessary Health Insurance Portability and Accountability Act compliance training through Beth Israel Deaconess Medical Center, and completing the Digital Navigator training module on https://smiadviser.org/dhn , the trainee is provided with a brief 1-h orientation of the mindLAMP app and an overview of the Digital Clinic's operations.

The trainee is then provided with a test account on mindLAMP, as well as Supplementary Data that explain the app's various features and documents detailing the clinic's protocols, to help them become familiar with both the app and the clinic's procedures. Digital Navigator applicant interest questions, interview questions, and grading rubric can be found in Appendices B and C of Supplementary Data (Fig. 3).

Fig. 3.

A screenshot from the free SMIAdviser.org/DHN online digital navigator training.

Over the course of several weeks, the trainee is permitted to observe two Digital Navigator meetings (with the express permission of the patient) to shadow an experienced digital navigator. Subsequently, simulated Digital Navigator sessions are held in which one of the experienced digital navigators role-plays as a patient and the trainee takes on the role of the digital navigator. These scripts are created to cover areas that may be challenging such as more complex technical support issues, resistance to app engagement, and procedures around patient safety concerns (Table 1).

Table 1.

Digital Navigator Trainee Assessment Criteria

CRITERIA	ASSESSED BY
Participant interaction and support	How effectively the trainee communicates with the patient
Technical proficiency	Trainee understanding and application of mindLAMP troubleshooting standard errors
Knowledge of content	How accurately the trainee answers common patient questions, which may range from the qualifications of the clinicians to data storage practices
Process adherence	Trainee's commitment to protocols and documentation. This includes, but is not limited to, the trainee's use of supplemental aid materials and documentation of patient concerns or feedback
Feedback implementation	How well the trainee responds to and incorporates feedback to improve performance between mock sessions
Punctuality	Trainee's consistency in being on time for meetings
Quality of service	Provision of accurate, comprehensive, and insightful information in response to patient questions and in communicating patient data. If the trainee provides inaccurate information or incomplete responses at any point, points will be deducted in this category

During the simulated Digital Navigator sessions, the trainees are assessed based on seven different criteria: participant interaction and support, technical proficiency, knowledge of content, process adherence, feedback implementation, punctuality, and quality of service. Each criterion will be graded on a scale from 1 to 5, described as poor, fair, good, very good, or excellent. Feedback is given to the trainees on all aspects of the mock session.

Trainees will need to show successful completion of a mock session by the third mock session to begin seeing patients in a supervised manner. Upon successful completion of this mock session, the trainee begins working with patients in a supervised manner. Supervision lasts for 1–3 months depending on feedback from the trainee, supervisor, and patients.

Methods

The published protocol for implementation can be found in the study by Macrynikola et al.¹²

This study was approved by the BIDMC IRB: 2023P000231.

MEASURES

To evaluate the interactions and support provided by Digital Navigator in our study, a customized Digital Navigator Satisfaction Scale was developed. This scale aims to assess the quality of time spent with the Digital Navigator, the information provided, and the overall satisfaction with the interaction. The Digital Navigator Satisfaction Scale comprises four items, each rated on a 5-point Likert scale ranging from 1 (poor) to 5 (excellent). Scores on the Digital Navigator Satisfaction Scale are calculated by summing responses to individual items, with higher scores indicating higher perceived satisfaction of interaction with the Digital Navigator (Table 2).

Table 2.

Digital Navigator Satisfaction Scale Items, Means, and Standard Deviations of Item Responses

ITEM AND RANGE	Mean	SD
1 (poor) to 5 (excellent)
What was the quality of time you spent with your DN?	4.6	0.76
What was the quality of information provided by the DN?	4.7	0.67
DN was willing to understand my questions and concerns.	4.7	0.69
DN explained things in a way I understood.	4.8	0.54

DN, Digital Navigator; SD, standard deviation.

Using descriptive statistics, we compared the Digital Navigator Satisfaction Scale scores collected from 83 patients who received care in the clinic from September 2022 to September 2023 against the mindLAMP user experience rating. mindLAMP user experience was rated on an ordinal scale of 1 (very difficult to use) to 5 (very easy to use). Demographic features were also considered, including age, gender, ethnicity, and race.

ANALYSIS

A two-way analysis of variance was performed and Spearman's correlation was calculated to compare the percentage of days engaged by the patients, the Digital Navigator satisfaction score, and the total time spent on the app. A linear regression was conducted to compare Digital Navigator satisfaction score ratings of patients of different ages, ethnicities, and races. Spearman's correlation was performed to show the correction between the Digital Navigator satisfaction score and mindLAMP user experience. Additionally, any outliers were filtered out by calculating the Mahalanobis distance between the percentage of days engaged by the patients and the Digital Navigator satisfaction score at a threshold of 0.05.

Finally, we assessed average participant passive data quality across their time in the clinic and for the 33 participants utilizing the mindLAMP app for the duration of 8 weeks from November 2023 to January 2024. Total passive data quality is the total volume of data collected from a given sensor, for example, Global Positioning System (GPS) or accelerometer, as a proportion of the data sampling frequency. Both GPS and accelerometer are assigned to collect data at a frequency of 5 Hz.

Total average passive data quality is calculated by taking the average of the total passive data collected divided by the total amount of time the participant was in the Digital Clinic and is represented by a decimal proportion of 1, a passive data quality of 1 indicating no missingness in either the GPS or accelerometer.

Results

DIGITAL NAVIGATOR SATISFACTION

Results for Digital Navigator satisfaction scores are presented below in Table 2. Overall, the responses reflect good satisfaction across all questions. The average Digital Navigator Satisfaction Scale item score (range 1–5) was 4.7, indicating high satisfaction.

ENGAGEMENT WITH mindLAMP

The percentage of days engaged metric was calculated by measuring how many days the patient used mindLAMP during their time in the Digital Clinic divided by the total number of days they were engaged. The results of Spearman's correlation comparing the percentage of days engaged by the patients and the Digital Navigator satisfaction scores are shown in Table 3. There was a significant positive correlation between the percentage of days of app engagement and the Digital Navigator satisfaction scores.

Table 3.

Spearman's Correlation of Digital Navigator Satisfaction Score and Percentage of Days Patients Engaged with mindLAMP

	N	MEAN	SD	p	CORRELATION
Digital Navigator satisfaction score	83	18.76	2.17	0.034	0.232
Percentage of days engaged	83	81.82	26.25	0.034	0.232

DEMOGRAPHIC VARIABLES

A linear regression was conducted to compare Digital Navigator satisfaction score ratings of patients of different age, ethnicity, and race groups. The results were not significant for any variable and confirmed that there is no association between these demographic variables and Digital Navigator satisfaction scores.

mindLAMP USER AND DIGITAL CLINIC EXPERIENCE

Results for Spearman's correlation between the Digital Navigator satisfaction score and mindLAMP user experience showed a statistically significant correlation of 0.4 at a p-value of <0.01 for 136 patients from September 2022 to January 2024. Details are shown in Table 4. Additionally, opportunities for open feedback were given and, although minimal, it was largely positive, as evidenced by the verbatim responses shown in Table 5.

Table 4.

Spearman's Correlation of Digital Navigator Satisfaction Score and mindLAMP User Experience Score

	N	MEAN	SD	p	CORRELATION
Digital Navigator satisfaction score	136	18.76	2.17	0.000299	0.40
mindLAMP user experience score	136	4.18	0.90	0.000299	0.40

Table 5.

Verbatim Qualitative Feedback

	NEGATIVE	POSITIVE
Patient	This structure feels like a good intro to therapy. I think overall it was very useful, small bugs on the app were annoying, but overall the system and notifications were good. I would try to streamline so there aren't so many appointments between the DN and the clinician, with using this app, this is fairly time consuming. I think the frequency of meeting with a digital navigator can be reduced to once every two weeks.	I enjoyed the App and the experts were very helpful. My experience with the clinic was so unequivocally positive, I don't really have any suggestions. The results of the clinical work exceeded my best expectations, I'm coming out of the process feeling great and supported. Every aspect of care was excellent, thank you so much! Very helpful program in all respects. Both clinician and app were integral to my progress. The clinician was critical to success in understanding and best using cbt techniques supported in the app. Really need both. Would be great to have more sessions. It was a unique experience for me. I did find it very useful in my situations. I very much enjoyed the interaction with the digital clinic and the app. It was very helpful to me and has set me up with skills I will use in the future.
Digital navigators	For some patients who are more tech savvy and motivated, the weekly sessions could be reduced to every other week.	Because these sessions are separate from therapy, there is no pressure on the patient or myself to feel like I must be able to support the patient outside of my capabilities as a Digital Navigator.

TOTAL AVERAGE PASSIVE DATA QUALITY

The average passive data quality derived from participants for the 8 weeks of care was 0.82 of 1. On average, 82% of the time there were no gaps or missing passive data coming from participants' mobile devices.

Discussion

We outlined an implementation of the Digital Navigator role within a digitally supported, hybrid mental health clinic and showed how the role may impact aspects of app engagement and satisfaction. We also showed that satisfaction with the Digital Navigator role was high across recorded gender, age, and race groups, suggesting the potential of this role to assist diverse populations. In seeking to replicate these results for other teams, we offer standardization provided through curricula, online training, checklists, and procedures. As other teams are able to expand off this foundation, higher rates of uptake and engagement with digital mental health technology may be possible.

Given the challenges of app engagement across all digital health interventions, especially mental health,¹⁷ the potential for the Digital Navigator to aid in engagement is notable. Our results are in line with prior reviews that suggest human support is one of the most effective means to boost app engagement. However, these prior efforts around human support have been heterogeneous and thus not easy (or at times even possible) to replicate.

With standardized procedures and public resources to support the role, we hope other teams will also be able to assess the impact of digital navigators on app engagement. A further benefit of the role is that digital navigators can also facilitate data utilization by clinicians, as our clinical model demonstrated. This is notable as a 2023 review of app-integrated therapy discovered that less than half of these treatments have the means to share data between the app and clinician.¹⁸

Our results also suggest that the Digital Navigator may aid in improving digital phenotyping data quality. The 82% data quality captured in the Digital Clinic is higher than that reported in most research studies¹⁶ and in the same range of data quality captured by our team using mindLAMP in clinical studies.¹⁹ This ability to provide research-grade, digital phenotyping data in clinical settings offers a practical translation of academic work into real-world use, facilitated by the Digital Navigator working directly to support patients.

Our work must be understood in the broader context of the digital health ecosystem. With access to smartphones and the internet now more common,²⁰ people have ready access to thousands of health apps that frequently change, are often not evidence based, are not engaging, and provide inadequate privacy protections.^21,22 The digital navigator can help ensure that everyone now has access to digital literacy so that they can use their devices for health and can help focus on the right apps that are safer and more effective, all while driving engagement.

While the outcomes cited above are the result of incorporating Digital Navigator into our own clinical program, the role can be customized to different clinical settings. Digital navigators may support app recommendation, utilizing a framework discussed by Camacho et al.²³ and teaching digital literacy groups in the community to ensure equity of access to digital health.²⁴

Other teams may find that they only need the Digital Navigator for a single role compared with the three (clinic, app evaluation, and digital literacy) that we utilize. However, the training resources and online education programs do cover all three aspects to provide flexibility. Other teams and clinics will likely find novel use cases for the role.

LIMITATIONS

The work has several limitations. While integration of mindLAMP into care is within the scope of Digital Navigator, clinician integration of the app into council visits and assignment of app activities in conjunction with therapy are other core factors in determining engagement and may have influenced our results. High scores for the Digital Navigator Satisfaction Scale and mindLAMP user experience reports may be driven by patient desirability, and agreeableness, over actual satisfaction.

Additionally, the results generated from the current sample size may not be reflected in larger adaptations. Finally, the information enclosed in this article encompasses specific implementation of the Digital Navigator role at Beth Israel Deaconess Medical Center, and integration logistics, as well as patient satisfaction, may be subject to different contexts.

Conclusions

The Digital Navigator role is designed to be a scalable solution to the challenges of leveraging mental health apps to provide care. In particular, it is designed to address skill barriers and issues of motivation and to integrate the app effectively into care. The standardized procedures and manual provide information about training required for this Digital Navigator format, as well as procedural information (such as daily Digital Navigator checklists).

While this protocol focuses on one specific implementation of the Digital Navigator, it provides a concrete in-depth example of precise integration of the role into a clinic in a manner that is scalable, straightforward to utilize, and easy to adapt to new contexts.

Footnotes

Acknowledgments

The authors thank the participants; digital navigators, Elana Perlmutter, Amrik Eadara, and Shruti Gajjar; and clinicians, Nanik Ram, Jesse Verhoeven, Katie Jurek, Lara Ferreira Gutsche, Namya Bhutani, and Kurt Louiseau.

Authors' Contributions

K.C., E.L., and J.T. conceptualized the article. K.C., J.B., and S.C. completed the data analysis. K.C., E.L., S.C., and J.T. composed the initial drafts of the manuscript. All authors critically revised the work and approved the final version of the manuscript. All authors contributed to development of the clinical protocol discussed here and outlined in the manual.

Disclosure Statement

J.T. is a cofounder of Precision Mental Wellness, unrelated to this article. The other authors report no conflicts of interest.

Funding Information

The authors did not receive any funds, grants, or other financial support for this work.

Supplementary Material

Supplementary Data

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Supplementary Material

Please find the following supplemental material available below.

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