An overview of and recommendations for more accessible digital mental health services

Lattie, Emily G.; Stiles‐Shields, Colleen; Graham, Andrea K.

doi:10.1038/s44159-021-00003-1

Cited by 168 publications

(133 citation statements)

References 168 publications

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“…However, best practices would include the incorporation of human-centered design [ 50 - 52 ] and community-based participatory research methodologies [ 53 ] to ensure that likely end users are active collaborators—those with agency—throughout the design and deployment phases. Doing so better ensures that DMH is accessible to and appropriate for the intended users [ 22 , 54 ]. For example, nearly one-third of the sample identified as Hispanic or Latinx, but the tool was only available in the English language.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, the ENERGY System was disseminated through the Rush University Medical Center clinics and community partnerships. Although some users may trust DMH when overseen by a university setting due to institutional review board oversight, others are less inclined to trust university and larger health systems–sponsored DMH due to historical injustices [ 60 ]. Future research should collaborate with community members to assess how the role of academic institution involvement may promote or hinder DMH engagement.…”

Section: Discussionmentioning

confidence: 99%

“…Digital mental health (DMH) tools are one way to enhance the accessibility of evidence-based interventions and resources [ 22 ]. DMH refers to the use of technology platforms, such as websites (ie, eHealth), mobile apps (ie, mobile health), and electronic devices (eg, Fitbit and Apple Watch), to deliver behavioral health assessments and interventions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Digital Screening and Automated Resource Identification System to Address COVID-19–Related Behavioral Health Disparities: Feasibility Study

Stiles‐Shields¹,

Batts²,

Reyes³

et al. 2022

JMIR Form Res

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Background Digital mental health (DMH) tools use technology (eg, websites and mobile apps) to conveniently deliver mental health resources to users in real time, reducing access barriers. Underserved communities facing health care provider shortages and limited mental health resources may benefit from DMH tools, as these tools can help improve access to resources. Objective This study described the development and feasibility evaluation of the Emotional Needs Evaluation and Resource Guide for You (ENERGY) System, a DMH tool to meet the mental health and resource needs of youth and their families developed in the context of the COVID-19 pandemic. The ENERGY System offers a brief assessment of resource needs; problem-solving capabilities; and symptoms of depression, anxiety, trauma, and alcohol and substance use followed by automated, personalized feedback based on the participant’s responses. Methods Individuals aged ≥15 years were recruited through community partners, community events, targeted electronic health record messages, and social media. Participants completed screening questions to establish eligibility, entered demographic information, and completed the ENERGY System assessment. Based on the participant’s responses, the ENERGY System immediately delivered digital resources tailored to their identified areas of need (eg, relaxation). A subset of participants also voluntarily completed the following: COVID-19 Exposure and Family Impact Survey (CEFIS) or COVID-19 Exposure and Family Impact Survey Adolescent and Young Adult Version (CEFIS-AYA); resource needs assessment; and feedback on their experience using the ENERGY System. If resource needs (eg, housing and food insecurity) were endorsed, lists of local resources were provided. Results A total of 212 individuals accessed the ENERGY System link, of which 96 (45.3%) completed the screening tool and 86 (40.6%) received resources. Participant responses on the mental health screening questions triggered on average 2.04 (SD 1.94) intervention domains. Behavioral Activation/Increasing Activities was the most frequently launched intervention domain (56%, 54/96), and domains related to alcohol or substance use were the least frequent (4%, 4/96). The most frequently requested support areas were finances (33%, 32/96), transportation (26%, 25/96), and food (24%, 23/96). The CEFIS and CEFIS-AYA indicated higher than average impacts from the pandemic (ie, average scores >2.5). Participants were satisfied with the ENERGY System overall (65%, 39/60) as well as the length of time it took to answer the questions (90%, 54/60), which they found easy to answer (87%, 52/60). Conclusions This study provided initial support for the feasibility of the ENERGY System, a DMH tool capable of screening for resource and mental health needs and providing automated, personalized, and free resources and techniques to meet the identified needs. Future studies should seek direct feedback from community members to further improve the ENERGY System and its dissemination to encourage use.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Digital Screening and Automated Resource Identification System to Address COVID-19–Related Behavioral Health Disparities: Feasibility Study

Stiles‐Shields¹,

Batts²,

Reyes³

et al. 2022

JMIR Form Res

Self Cite

View full text Add to dashboard Cite

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“…Given these difficulties in accessing mental health care, the need to explore scalable and affordable options for mental health care is imperative as a growing proportion of the population enters old age and requires more services. Over the past 2 decades, a number of digital interventions have been developed to address the general unmet need for mental health care [ 16 ], and research suggests that these can effectively help improve mental health, including depression, anxiety, and stress [ 17 - 20 ]. However, research on whether older adults will engage with or benefit from digital interventions is limited.…”

Section: Introductionmentioning

confidence: 99%

The Effects of a Digital Well-being Intervention on Older Adults: Retrospective Analysis of Real-world User Data

Boucher¹,

Honomichl²,

Ward³

et al. 2022

JMIR Aging

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Background Digital interventions have been shown to be effective for a variety of mental health disorders and problems. However, few studies have examined the effects of digital interventions in older adults; therefore, little is known about how older adults engage with or benefit from these interventions. Given that adoption rates for technology among people aged ≥65 years remain substantially lower than in the general population and that approximately 20% of older adults are affected by mental health disorders, research exploring whether older adults will use and benefit from digital interventions is needed. Objective This study aimed to examine the extent to which older adults engaged with a digital well-being intervention (Happify) and whether engaging with this program led to improvements in both subjective well-being and anxiety symptoms. Methods In this retrospective analysis, we analyzed data from 375 real-world Happify users aged ≥65 years who signed up for the platform between January 1, 2019, and December 23, 2021. Changes in well-being and anxiety symptoms across 42 to 182 days were assessed using responses to the in-app assessment, which users were prompted to take every 2 weeks, and were compared among users who engaged with the program at the recommended level (ie, 2 or more activities per week) or below the recommended level. Results In all, 30% (113/375) of the sample engaged with the platform at the recommended level (ie, completed an average of 2 or more activities per week), and overall, users completed an average of 43.35 (SD 87.80) activities, ranging from 1 to 786, between their first and last assessment. Users were also active on the platform for an average of 19.36 (SD 27.16) days, ranging from 1 to 152 days. Moreover, older adults who engaged at the recommended level experienced significantly greater improvements in subjective well-being (P=.002) and anxiety symptoms (P<.001) relative to those who completed fewer activities. Conclusions These data provide preliminary evidence that older adults engage with and benefit from digital well-being interventions. We believe that these findings highlight the importance of considering older adult populations in digital health research. More research is needed to understand potential barriers to using digital interventions among older adults and whether digital interventions should be modified to account for this population’s particular needs (eg, ensuring that the intervention is accessible using a variety of devices). However, these results are an important step in demonstrating the feasibility of such interventions in a population that is assumed to be less inclined toward digital approaches.

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“…Early work is promising, but does not yet translate to best practices for improved patient outcomes or provide a clear direction for therapist training 11,19,[25][26][27][28] . Methodological improvements are needed to bridge divisions between theoretical schools of thought (e.g., Cognitive Behavioral, Interpersonal, Psychodynamic, Counseling) as to which therapist language patterns correlate with favorable therapy outcomes 4,6,13,15,20,24,29,30 . If known, the linguistic behavior of successful therapists may inform targeted clinical trials to test causality and implementability, subsequently improving clinician training.…”

Section: Main Text Introductionmentioning

confidence: 99%

Uncovering the linguistic characteristics of psychotherapy: a computational approach to measure therapist language timing, responsiveness, and consistency

Miner

Fleming

Haque

et al. 2022

Preprint

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Although individual psychotherapy is generally effective for a range of mental health conditions, little is known about the moment-to-moment language use of effective therapists. Increased access to computational power, coupled with a rise in computer-mediated communication (telehealth), makes feasible the large-scale analyses of language use during psychotherapy. Transparent methodological approaches are lacking, however. Here we present novel methods to increase the efficiency of efforts to examine language use in psychotherapy. We evaluate three important aspects of therapist language use - timing, responsiveness, and consistency - across five clinically relevant language domains: pronouns, time orientation, emotional polarity, therapist tactics, and paralinguistic style. We find therapist language is dynamic within sessions, responds to patient language, and relates to patient symptom diagnosis but not symptom severity. Our results demonstrate that analyzing therapist language at scale is feasible and may help answer longstanding questions about specific behaviors of effective therapists.

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An overview of and recommendations for more accessible digital mental health services

Cited by 168 publications

References 168 publications

Digital Screening and Automated Resource Identification System to Address COVID-19–Related Behavioral Health Disparities: Feasibility Study

Digital Screening and Automated Resource Identification System to Address COVID-19–Related Behavioral Health Disparities: Feasibility Study

The Effects of a Digital Well-being Intervention on Older Adults: Retrospective Analysis of Real-world User Data

Uncovering the linguistic characteristics of psychotherapy: a computational approach to measure therapist language timing, responsiveness, and consistency

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