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. Author manuscript; available in PMC: 2023 Jan 23.
Published in final edited form as: J Ment Health. 2022 Jan 28;31(6):833–841. doi: 10.1080/09638237.2021.2022619

Assessing a digital peer support self-management intervention for adults with serious mental illness: feasibility, acceptability, and preliminary effectiveness

Karen L Fortuna a, Amanda L Myers b, Joelle Ferron a, Arya Kadakia c, Cynthia Bianco a, Martha L Bruce a, Stephen J Bartels d
PMCID: PMC9329481  NIHMSID: NIHMS1782237  PMID: 35088619

Abstract

Objective:

To assess the feasibility, acceptability, and preliminary effectiveness of digital peer support integrated medical and psychiatric self-management intervention (“PeerTECH”) for adults with a serious mental illness.

Methods:

Twenty-one adults with a chart diagnosis of a serious mental illness (i.e., schizophrenia, schizoaffective disorder, bipolar disorder, or treatment-refractory major depressive disorder) and at least one medical comorbidity (i.e., cardiovascular disease, obesity, diabetes, chronic obstructive pulmonary disease, hypertension, and/or high cholesterol) aged 18 years and older received the PeerTECH intervention in the community. Nine peer support specialists were trained to deliver PeerTECH. Data were collected at baseline and 12-weeks.

Results:

This pilot study demonstrated that a 12-week, digital peer support integrated medical and psychiatric self-management intervention for adults with serious mental illness was feasible and acceptable among peer support specialists and patients and was associated with statistically significant improvements in self-efficacy to manage chronic disease and personal empowerment. In addition, pre/ post non-statistically significant improvements were observed in psychiatric self-management, medical self-management skills, and feelings of loneliness.

Conclusions:

This single-arm pre/post pilot study demonstrated preliminary evidence peer support specialists could offer a fidelity-adherent digital peer support self-management intervention to adults with serious mental illness. These findings build on the evidence that a digital peer support self-management intervention for adults with serious mental illness designed to improve medical and psychiatric self-management is feasible, acceptable, and shows promising evidence of improvements in clinical outcomes. The use of technology among peer support specialists may be a promising tool to facilitate the delivery of peer support and guided evidence-based self-management support.

Conclusions:

People with serious mental illness (SMI; defined as individuals diagnosed with schizophrenia spectrum disorder, bipolar disorder, or treatment-refractory major depressive disorder) are increasingly utilizing peer support services to support their health and recovery. Peer support is defined as shared knowledge, experience, emotional, social, and/or practical assistance to support others with similar lived experiences (Solomon, 2004). Most recently the definition also includes the provision of evidence-based peer-supported self-management services (Fortuna et al., 2020). Mental health peer support can augment the traditional mental health treatment system through providing support services to maintain recovery between clinical encounters (Solomon, 2004) and is classified by the World Health Organization as an essential element of recovery (World, Health, and Organization, About social determinants of health, 2017).

Keywords: Peer support, mHealth, self-management, serious mental illness

Digital peer support is Medicaid reimbursable in 47 states and has rapidly expanded due to the necessity to offer community-based services using telehealth during the COVID-19 pandemic (Fortuna, in press). Digital peer support is defined as live or automated peer support services delivered through any technology medium (e.g., videogames, videoconferences, smartphone applications, cell phones, virtual reality) (Fortuna et al., 2020). Technology has the potential to expand the reach of peer-supported evidence-based services, increase the dose of peer support services without the need for in-person sessions, increase engagement in mental health services, and support fidelity-adherent delivery of evidence-based practices (Fortuna et al., 2018, 2019). Digital peer support interventions for people with SMI use a variety of technology modalities (i.e., smartphones, social media, video conferencing) and have shown to be a promising tool for self-management of medical and psychiatric conditions (Fortuna et al., 2020). As an emerging area of investigation, the feasibility, acceptability, and potential effectiveness of digital peer support has not been established (Fortuna et al., 2019).

The current pilot study is part of an iterative design process to develop and test a “PeerTECH” a digital peer support self-management intervention. This paper reports the findings from this pilot study designed to assess the feasibility, acceptability, and potential effectiveness of PeerTECH. Specific outcomes of potential effectiveness include self-efficacy to manage chronic disease and empowerment, psychiatric self-management, medical self-management skills, hope, empowerment, social support, and loneliness evaluated over 12 consecutive weeks.

PeerTECH intervention

“PeerTECH” is an adaptation of a 12-month clinician-delivered evidence-based intervention–Integrated Illness Management and Recovery (I-IMR) (Whiteman et al., 2016). Research has indicated that, regardless of practitioner background (peer specialists included), consumers who received an IMR intervention demonstrated significant improvement (Garber-Epstein et al., 2013). This demonstrates that the scale can be effectively administered by peer support specialists despite their limited professional experience. A randomized trial of I-IMR among adults with SMI found increased medical and psychiatric self-management skills and decreased hospitalizations compared to usual care (Bartels et al., 2014; 2014). In developing PeerTECH, we employed the Peer and Academic partnership framework (Fortuna et al., 2019) and partnered with peer support specialists through intervention development. This partnership conducted a series of clinic-based usability tests to iteratively refine the intervention (Fortuna et al. 2017; Whiteman et al., 2017) and align PeerTECH with evidence-based design principles for people with SMI (Rotondi et al., 2007, 2017). PeerTECH is a mobile technology platform designed to facilitate the delivery of evidence-based principles that have been shown to promote self-management in people with SMI (i.e., coping skills training, psychoeducation, medical management, relapse prevention planning, healthy behaviors, and peer support) (Bartels et al., 2014; 2014). Previous pilot studies found that PeerTECH (N = 8) was delivered with high fidelity by peer support specialists (Fortuna et al., 2018), and associated with improvements in medical and psychiatric self-management and self-efficacy to manage chronic disease among both peer support specialists and patients (Fortuna et al., 2018). The first PeerTECH study led to the following intervention modifications: enhancement of peer support specialists PeerTECH training; non-interventionist’s fidelity rating scale; inclusion of participants aged 18+ years; intervention content on social health (i.e., developing relationships and addressing feelings of loneliness); an electronic library guided PeerTECH sessions were available on the smartphone app (not on a separate website only accessible through a tablet).

PeerTECH mobile technology platform

The PeerTECH mobile technology platform includes a smartphone application and a peer support specialists’ care management dashboard. The smartphone application is designed for people with SMI to reinforce skills learned from in-person sessions with a peer support specialist. The smartphone application includes: (a) access to personalized self-management support; (b) intervention components that correspond to patients’ needs and goals; (c) a HIPAA-compliant chat feature for use between peer support specialists’ care management dashboard and patients ’ smartphone application; and (d) an on-demand library of peer-led self-management narrative videos. The PeerTECH library includes classes designed to be reviewed together by a peer support specialist and patient on a smartphone during one-hour, weekly, in-person or telephone-based classes (see Table 1). Each library class includes peer-led videos and guiding materials to discuss the interconnection between mental health, physical health, and social health, the role of stress in the development of or worsen mental health and physical health conditions, coping skills training, and unscripted lived experiences of self-management challenges and successes. Library features can be accessed offline and also can be accessed multiple times throughout the 12-week PeerTECH intervention.

Table 1.

PeerTECH Library.

Class #1: Introductions, smartphone orientation, and recovery and health
Class #2: Good mental health starts with good physical health and social health (vice versus)
Class #3: Recovery is a daily process
Class #4: How stress impacts our health
Class #5: Smoking and living a healthy lifestyle
Class #6: Healthy sleep
Class #7: Developing and maintaining relationships
Class #8: Dental health
Class #9: Exercise
Class #10: Getting the help you want from communities and the physical healthcare and mental health system
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Peer care management dashboard

The peer care management dashboard is stored on a secure website that monitors patients’ personalized recovery goals, their personalized wellness plan, and the chat between peer support specialists and patients. Peer support specialists sign in securely to the dashboard on a desktop or laptop to send secure, HIPAA-compliant mobile messaging to the smartphone application. Dashboard data is managed by a peer support specialist and monitored by the PI (Karen Fortuna) (see Figure 1).

Figure 1.

Figure 1.

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The PeerTECH System.

Methods

A single-arm pre/post pilot study was conducted in collaboration with a community mental health center that provides care management, coordination of services, and referrals for adults with SMI, aged 18 years and older. Peer support specialists provided PeerTECH within a community setting (e.g., outdoor park), the participants’ home, and or virtually (via telephone) four times per month (over a 12 week period) and text messaged participants a minimum of three times per week throughout the study. Study instruments were administered at baseline and 12-weeks (conclusion of intervention). Baseline assessments were conducted by a trained rater at the participant’s home or in the community mental health center. At the conclusion of the intervention, the 12-week assessments were conducted over the telephone due to COVID-19. This study was approved by Dartmouth Hitchcock Institutional Review Board.

Participants

The pilot study included N = 30 adults aged 18 years and older with SMI and one medical comorbidity. Eligibility for patient study participation included the following: (1) community-dwelling adult; (2) aged 18+; (3) diagnosis of schizophrenia, schizoaffective disorder, bipolar disorder, or major depressive disorder; (4) at least one medical condition defined as cardiovascular disease, obesity (defined as a body mass index of 30 and over), diabetes, chronic obstructive pulmonary disease, chronic pain, hypertension, high cholesterol, or current tobacco use identified through chart review; (5) ability to speak and read English; (6) provide voluntary informed consent; and (7) qualify for Medicaid reimbursements. Study participants were excluded based on the following criteria: (1) major visual or motor impairment as evidenced by turning a smartphone on and reporting they cannot clearly see the screen; (2) a chart diagnosis of dementia, or evidence of significant cognitive impairment as indicated by a Mini-Mental Status Examination (Folstein et al., 1975) score of less than 24. Peer support specialists were recruited from a single community mental health site; eligibility included: (1) trained and accredited certified peer support specialist in the state of Massachusetts; (2) aged 18+; (3) ability to speak and read English; (4) willingness to provide voluntary informed consent; (5) currently in recovery as self-reported by peer support specialist; and (6) employed at community mental health center research site.

Instruments

Study instruments were administered in-person at baseline and over the telephone at 12-weeks by a trained rater. Self-report data were entered into REDCap by the trained rater. Instruments were selected to reflect peer support intervention targets described in the research literature (i.e., hope, empowerment, social support (Jacobson & Greenley, 2001; Corrigan et al., 2004; Resnick et al., 2005)), and mechanisms to promote engagement in medical and psychiatric self-management behaviors (i.e., self-efficacy (Lorig et al., 2001), loneliness (Fortuna et al., 2020)).

To measure hope, the trained rater administered the 12-item Herth Hope Index (HHI) (Herth, 1992), which has shown reliability and validity in medically complex nursing home patients (Haugan et al., 2013) and individuals with cognitive impairments (Hunsaker et al., 2016). Sample questions include the following, “I feel all alone” and “I have short and/or long-range goals.” Response choices include the following, “strongly disagree,” “disagree,” “agree,” and “strongly agree.” Scores on the HHI range from 12 to 48 (note: higher scores indicate higher self-reported levels of hope).

To measure feelings of loneliness, the trained rater administered the 20-item UCLA Loneliness Scale (Russell et al., 1978). Each of the 20 items was self-rated on a four-point scale, with higher values indicating greater feelings of loneliness (i.e., 1 = never; 2 = rarely; 3 = sometimes; 4 = always). Sample items include “how often individuals felt left out” or “isolated from others,” and how often they “felt that there are people that really understand them or that they can talk to.” Consistent with scoring, the number for each item is summed, giving a total score ranging from 20 to 80 (Russell et al., 1978). The original UCLA Loneliness Scale demonstrates good validity and reliability (Russell, 1996; Russell et al., 1980).

To measure empowerment, the trained rater administered the Empowerment Scale (Rogers et al., 2010), which is a widely used valid, reliable 28-item instrument that measures personal empowerment (Rogers et al., 2010; Wowra & McCarter, 1999). Sample questions include the following, “I can pretty much determine what will happen in my life” and “people are only limited by what they think is possible.” Response options include the following, “strongly agree,” “agree,” “disagree,” and “strongly disagree.” Consistent with scoring, scores were aggregated and averaged, in which lower scores indicated higher levels of empowerment. Total scores range from one to four.

The Medical Outcomes Study (MOS) Social Support Survey instrument (Sherbourne & Stewart, 1991) is a valid, reliable 19-item instrument (Sherbourne, 1993) that examines different domains of social support (i.e., emotional/ informational, tangible, affectionate, and social interaction). The trained rater asked participants how often each type of social support was available to them. Response options include the following, “none of the time,” “a little of the time,” “some of the time,” “most of the time,” and “all of the time.” Each domain’s score was averaged across and aggregated. Scores range from 0 to 100, in which higher scores indicate higher levels of social support.

Psychiatric self-management skill development was assessed by administering the Illness Management and Recovery Scale (IMRS) (Sklar et al., 2012). The IMRS is a valid, reliable 15-item instrument that examines domains of illness self-management (Garber-Epstein et al., 2013; Hasson-Ohayon et al., 2008; Salyers et al., 2007). An example item reads, “how much do you know about symptoms, treatment, coping strategies (coping methods), and medication.” Response options include the following, “not very much,” “a little,” “some,” “quite a bit” and “a great deal.” Scores range from 15 to 75. Higher scores indicated higher levels of psychiatric self-management skills.

Medical self-management skill development was assessed using the Self-Rated Abilities for Health Practices Scale (SRAHPS) (Becker et al., 1993). SRAHPS is a 28-item instrument that examines confidence to implement health practices (Becker et al., 1993). SRAHPS has demonstrated reliability and validity with adults with disabilities (Becker et al., 1993). SRAHPS includes four subscales with seven items each. Subscales include the following health practices: (1) exercise, (2) nutrition, (3) responsible health practice, and (4) psychological well-being. The trained rater asked participants to rate the extent to which they are able to execute health practices in each of the domains. An example item reads, “I am able to get help from others when I need it.” Each item is rated on a four-point scale (i.e., zero [not at all] to four [completely]). Subscale ratings were summed to produce subscale scores, and then, totaled to obtain an overall score. Participants could score between 0 and 112 points. Higher scores indicated higher levels of medical self-management skills.

A trained rater implemented the Self-Efficacy for Managing Chronic Disease Scale (SEMCD) (Lorig et al., 2001) to measure self-efficacy. SEMCD is a six-item scale that examines the following domains: symptom control, role function, emotional functioning, and communicating with physicians. SEMCD has established reliability and validity in people with chronic physical health conditions (Lorig et al., 2001; Riehm et al., 2016). Participants answer each item on a 1–10 point scale (i.e., 1 = not confident at all to 10 = totally confident), and the final SEMCD score is the average of the six items. Scores can range from one to ten. Higher scores indicated higher self-efficacy.

Fidelity assessment

The principal investigator monitored intervention fidelity through (1) daily monitoring of the peer care management dashboard and text messages, (2) audio recordings of PeerTECH classes, and (3) weekly discussions between the principal investigator and peer supervisor. The principal investigator completed the non-interventionist PeerTECH fidelity instrument for each PeerTECH class over the 12-week intervention and provided an ongoing evaluation of their work to peer support specialists and the peer supervisor.

Procedures

Peer support recruitment

The peer support specialists’ supervisor at the research site identified peer support specialists to be trained to deliver PeerTECH. The peer support specialists’ supervisor assessed employees’ interests in this study and made recommendations to the PI. All interested peer support specialists were trained in PeerTECH. All peers previously completed the Massachusetts certified peer support specialists training in order to work as certified peer support specialists at the community mental health center. Certified peer specialists were certified by the state of Massachusetts. This state-specific certification training takes place over 10 weeks and includes six day-long trainings and a three-day retreat (Kaufman et al., 2016). Participants included nine peer support specialists between the ages of 25 and 54 years (mean 39 years) who were employed as peer support specialists for 1 to 11 years (mean 4.25 years) and had access to a work-funded smartphone device and data plan. Peer support specialists’ workload did increase during the PeerTECH study from 30 hours to 40 hours. As peer support specialists are employees, a record of their mental health diagnosis was not requested.

PeerTECH training

Once peer support specialists indicated their interest in the study, they completed the PeerTECH training. The PeerTECH training included 16 hours of in-person training over two consecutive days. PeerTECH training included: (1) the importance of addressing both physical health, mental health, and social health, (2) integration of recovery within medical challenges, (3) techniques used in PeerTECH (i.e., psychoeducation, coping skills training, peer support), (4) defining personally meaningful, achievable goals and actions steps with the participant; (5) delivering PeerTECH sessions using the smartphone, (6) the structure of the weekly session and between session text messaging between peers and participants, (7) teaching others how to use technology, (8) maintaining engagement, (9) sharing lived experience intentionally to teach self-management concepts, and (10) experiential training using the smartphone application and the peer care management dashboard. All peers also completed the Digital Peer Support Certification (Fortuna et al., 2020) throughout the course of the study. The Digital Peer Support Certification is a 12-week training lead by the PI that includes two education and simulation training sessions, and ongoing synchronous and asynchronous support services and audit and feedback. Training focuses on digital communication skills; technology literacy; technology usage skills with the PeerTECH system (e.g., downloading apps, sending SMS text messages, entering goals, saving information, increasing the volume on a smartphone, watching videos in the library, and offering digital peer support services); available digital peer support technologies; organizational policies and compliance issues; separating work and personal life; digital crisis intervention; and privacy and confidentiality.

Peer supervision

Peer support specialists individually met in person or over the telephone with a peer supervisor (also a peer support specialist and a trained supervisor) once a week for one hour. Discussions centered on concerns working with participants as part of PeerTECH and problems with PeerTECH technology. Peer supervision revealed if the peer needed additional technical support regarding PeerTECH or if participants needed extra services or technical assistance with the PeerTECH smartphone application.

Patient participant recruitment

The PI met with the clinical team leader to discuss the purpose of the study and the recruitment process. The clinical team leader was a licensed clinical social worker who reviewed current patient caseloads along with other peer support specialists. Together, they identified potential participants that met inclusion criteria and telephoned the potential participants to speak with the individual about the study. The clinical team leader read a scripted one-page summary of the study over the telephone to the potential participant. If they were interested in the study, they verbally agreed to meet with a trained rater and the peer support specialist in a location of their choosing.

Patient participant informed consent

During the scheduled in-person baseline data collection meeting, potential participants were provided a description of the study, shown the PeerTECH smartphone application, and informed their information was confidential and that their participation in the study was voluntary. Potential participants were evaluated for study criteria. If the participant met the criteria and provided informed consent to participate in the study, the trained rater completed the baseline assessments independently with the participant using REDCap in a private room within the community mental health center or the participant’s home. Thereafter, the peer support specialist scheduled with the participant. Participants were loaned a ZTE Blade Vantage 2 Prepaid Android phone and 12-week data plan (at no cost to the participant).

Peer support specialists informed consent

During peer support specialist training, potential peer participants were provided a description of the study, shown the PeerTECH smartphone application and care management dashboard, and informed their information was confidential and that their participation in the study was voluntary. If the participant met the criteria and provided informed consent to participate in the study, peer support specialists were included in the study and in a group environment independently completed paper-based baseline assessments. Data from paper-based assessments were entered into REDCap by the trained rater.

Statistical analyses

Descriptive statistics were conducted to describe the sociodemographic characteristics of the study sample. A Paired-sample t-test and chi-squares were conducted to assess the difference between baseline and 12-week scores for statistical significance. Descriptive statistics and analyses were computed using STATA version 13.1. The significance of changes in outcomes was corrected for multiple testing using the Bonferroni method.

Results

Sociodemographic characteristics of the study sample

A total of 30 patient participants completed baseline and 21 patient participants completed the follow-up assessment. Among the 21 participants assessed at the follow-up visit, 71.4% were female (n = 15), with a mean age of 39.85 (SD = 12.41). The majority of participants were white (n = 20, 95.2%), had never been married (n = 11, 52.4%), completed high school/GED (n = 18, 85.8%), lived independently (n = 12, 57.1%) and were unemployed (n = 15, 71.4%). Participants had a primary mental health diagnosis of schizophrenia spectrum disorders (n = 12, 57.1%), bipolar disorder (n = 6, 28.6%), and major depressive disorder (n = 3, 14.3%). This was self-reported and later verified through clinical records. Fifteen participants reported they were smartphone owners and had used a smartphone before participating in this study.

Nine patient participants were lost to follow-up. Of these nine, seven participants did not respond to repeated telephone calls to schedule the 12-week interview. One individual decided after hearing about the study and completing the informed consent that he/she was not interested in participating in the study; the other met with a peer once times and decided he/she did not want to work with their assigned peer support specialist and no longer wanted to be involved with the study. The remaining twenty-one participants completed the PeerTECH intervention. Fifteen participants owned a smartphone and used their own smartphone and data plan for the study. Of the six participants using loaned smartphones, the smartphone was configured only to deliver the intervention and not for personal use. One smartphone broke during the study and was returned to the PI.

Feasibility and acceptability

Out of the thirty patient participants, 70% (n = 21) participated in 10 or more in-person sessions, consistent with the original I-IMR study definition of adequate exposure (Bartels et al., 2014) and indicating an acceptable rate of engagement in PeerTECH. Peers used the care management dashboard to send asynchronous text messages to participants. Over the course of the study, peer support specialists sent 110 total text messages and participants sent a total of 114 text messages (each peer support specialist texted an average of six texts per week and participants texted an average of two text messages per week). The majority of participants (72%) entered personalized goals on the app. Each peer support specialist offered services to one-three participants.

Peer support specialists identified recommendations to enhance the utility of the PeerTECH system. Peers recommended PeerTECH library content include the role of trauma in early mortality in people with SMI and self-management skill development. Additionally, through implementing PeerTECH in the field, peer support specialists reported challenges using a desktop or laptop to access the care management dashboard.

Preliminary effectiveness outcomes

On average, patient-participants demonstrated a significant increase in self-efficacy to manage the chronic disease as measured by the Self-Efficacy for Managing Chronic Disease Scale (see Table 2). They also demonstrated an average change on the Empowerment Scale from 2.12 at baseline to 1.77 post-treatment. As noted above, lower scores on the Empowerment Scale indicated higher levels of empowerment. Promising evidence of improvement (though not statistically significant) was demonstrated on positive changes in psychiatric self-management as measured by the IIMR scale, medical self-management as measured by the SHRAPS, and feelings of loneliness as measured by the UCLA loneliness measure. Decreases were found related to negative changes in hope and social support.

Table 2.

Changes in outcomes from baseline to post-treatment (12-weeks) for study participants.

Instrument Baseline M ± SD Post-treatment M ± SD Change in Raw Score P valuea
SRAHP 72.71 ± 24.16 77.1 ± 23.64 4.43 .370†
IMRS 54.76 ± 7.56 55.05 ± 14.07 .29 .917†
Herth hope index 36.05 ± 5.80 35.19 ± 12.71 −0.86 .757†
SEMCD 5.95 ± 2.55 7.01 ± 1.96 1.06 .024**
MOS social support 69.42 ± 4.34 64.31 ± 24.17 −5.11 .112†
UCLA loneliness 31.19 ± 8.89 31.05 ± 9.91 −0.14 .912†
Empowerment scale 2.12±.28 1.77±.60 −.35 .007**
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a

Two-tailed, paired t-test used to assess statistical significance.

†

ns, nonsignificant at the .05 probability level.

**

statistically significant at the .05 probability level.

Note: Lower scores on the Empowerment indicate improvement; MOS Social Support = The Medical Outcomes Study Social Support Survey; IMRS = Illness Management and Recovery Scale; SRAHPS = Self-Rated Abilities for Health Practices Scale; SEMCD = Self-Efficacy for Managing Chronic Disease Scale.

Fidelity assessment

Daily monitoring of PeerTECH in-person or telephone classes through audio recordings and text messages through peer care management dashboard indicated adherence to the intervention. First, peer specialists’ initially experienced difficulty signing into the dashboard and needed additional technical assistance. Second, peer specialists needed additional encouragement from the PI regarding the requirement to text message patients at least three times a week. Third, peer support specialists supported one another and patients in working through technical difficulties (e.g., lost password). Finally, most peer support specialists did not read the class content verbatim but offered their own expertise, thus most used the library as a guide and offered health-related information based on their own personal experiences with managing medical and mental health issues.

Discussion

The pilot study demonstrated that 12-week digital peer support integrated medical and psychiatric self-management intervention (“PeerTECH”) is feasible and acceptable for both the peer support specialists and people with SMI. The pilot study demonstrated further evidence that it is possible to train peers to deliver technology-supported evidence-based practices with fidelity. PeerTECH was associated with statistically significant improvements in self-efficacy to manage chronic disease and empowerment. In addition, improvements were found (trending towards significant) in psychiatric self-management, medical self-management skills, and feelings of loneliness. No improvements were found in hope or social support (i.e., slight decreases were found). Improvements were surprising due to the low power in this study. As such, it is promising to note that this pilot non-powered study has shown improvements in addition to feasibility and acceptability.

Feasibility and acceptability by peer support specialists were demonstrated through their ability to use the care management dashboard to text message patients with SMI and offer PeerTECH classes with fidelity. Specifically, 21 participants (80%) participated in 10 or more classes, and over the course of the study. Overall, nine participants dropped out of the study, indicating a 70% retention rate, which is consistent with the first PeerTECH pilot study (Fortuna et al., 2018). Interestingly, this study’s 3-month follow-up was conducted in March 2020 (during the lockdown in Massachusetts), and as such, may have impacted follow-up rates. Nonetheless, potential efforts to increase retention may include hiring peer support specialists (non-PeerTECH interventionists) to promote engagement with the PeerTECH study. As peer support specialists have consistently shown to increase engagement in services (Chinman et al., 2014), the same may be true for research study participation. This study highlights promising findings that digital peer support interventions are feasible and acceptable among peer support specialists and adults with SMI.

Self-management skill development reported in this study is comparable to outcomes observed in other I-IMR intervention studies (Bartels et al., 2014; Mueser et al., 2006) and the earlier PeerTECH pilot study (Fortuna et al., 2018). Further, this PeerTECH study has also shown statistically significant improvements in empowerment. Higher levels of empowerment in people with SMI have been shown to be related to a reduction in the length of inpatient treatment (Corrigan, 2002) and increases patients ’ quality of life (Tveiten et al., 2011). It is likely that our finding of significant changes in empowerment was achieved by the co-production of PeerTECH with peer support specialists as partners. Past literature has already demonstrated the potential efficacy of peer-led shared decision-making in producing optimal clinical outcomes by improving patient satisfaction and communication, reducing decisional conflict, and facilitating patient motivation and participation in goal setting (Simmons et al., 2017; Yamaguchi et al., 2017; Zisman-Ilani et al., 2017). In the development of PeerTECH, peer support specialists indicated the need to provide patients with SMI the skills they need to take care of themselves; rather than relying on a clinical provider or institution. As such, PeerTECH is designed to support patients in the community (outside of a clinical setting) through offering on-demand and live features over eight hours a day (Sunday to Saturday). Thus, patients with SMI could increase the dose of intervention as needed through the use of the app without scheduling an appointment.

Previous peer support specialists’ recommendations to the PeerTECH system expressed the need to focus on participants’ social goals as a mechanism to improve overall self-management behaviors (Fortuna et al., 2018). However, decreases were found in patients’ feelings of hope and social support. Potentially due to the timing of the 12-week data collection during COVID-19 lockdown measures in the state of Massachusetts impacted these specific outcomes. Previous infectious disease outbreaks (i.e., SARS-CoV in 2003) have been found to impact feelings of loneliness, social isolation, and worsening mental health symptoms leading to suicide in the general population (Gunnell et al., 2020). In contrast, the first PeerTECH study demonstrated improvements in feelings of hope and social support. As such, the ecological validity of these intervention targets is not clear and requires additional exploration under controlled conditions less susceptible to cohort effects.

Peer support specialists offered new recommendations to the PeerTECH system. The PeerTECH system in the current study did not focus on the role of trauma in early mortality, although experiences of trauma are an established risk factor for early mortality in the general population (Tremeau, 2016). Prevalence rates of trauma are significantly higher in people with SMI than in the general population (Mauritz et al., 2013). Through the refinement of the PeerTECH system, trauma-informed principles and the role of trauma in early mortality may enhance individuals’ understanding and potentially engagement in integrated self-management behaviors. Further, the PeerTECH system did not fit the social, cultural, and environmental context of peer support specialists. Peer support specialists were not provided a laptop for this study, thus, in order to use the chat feature in PeerTECH, they had to physically drive into the office. As most peer support specialists work in the community, a desktop management dashboard is not practical. Peer support specialists also reported difficulties using a computer to access the dashboard. Potentially, a mobile-to-mobile system may be more ecologically relevant and accessible for this population within their respective socio-environmental contexts.

Our study findings should be interpreted with caution due to several important limitations. First, this pilot study consisted of a small sample size consistent with our principal objective of examining feasibility and acceptability among peer support specialists and patients. As such, this study was not powered to detect statistically significant pre/ post differences. Second, this single-arm study did not include a control group. Thus, it is not possible to determine if improvements were related to the use of the PeerTECH system or other confounding factors. Third, we recruited certified peer specialists from one state. As peer certification training varies by state, we do not know if these findings generalize beyond the state of Massachusetts. Future studies with a fully-powered sample will allow us to explore nested designs to account for variation in intervention delivery. Fifth, the sample purposefully included a heterogeneous grouping of psychotic disorders and mood disorders to mimic real-world conditions in community mental health centers. As such, we do not expect that SMI diagnostic heterogeneity impacted results as prior self-management skills training studies that include people with diverse SMI diagnoses found no differences by diagnosis with respect to self-efficacy and self-management outcomes (Bartels et al., 2014; 2014). However, the sample was racially and ethnically homogenous, limiting generalizability to non-racially and ethnically diverse individuals. Sixth, due to PeerTECH technology system constraints, engagement measures regarding time spent on the app in the library outside of audio recorded PeerTECH classes are not known.

Conclusion

The pilot study added promising evidence to the potential feasibility and benefits of training peer support specialists to use technology to deliver an evidence-based psychiatric and medical self-management intervention with the augmented use of a smartphone app. Despite the small sample size, PeerTECH was associated with statistically significant improvements in self-efficacy to manage chronic disease and personal empowerment. In addition, pre/post, non-statistically significant improvements were observed in psychiatric self-management, medical self-management skills, and feelings of loneliness. These findings suggest promising evidence that a digital peer support intervention designed to improve medical and psychiatric self-management is feasible, acceptable, and may impact self-efficacy and self-management skill development among adults with SMI and chronic health conditions. Further research with a design and sample size that is more significantly powered to test improvement is warranted.

Funding

This study was supported by Dr. Fortuna’s NARSAD Young Investigator Grant from the Brain and Behavior Foundation (#26800), Alvin R. Tarlov & John E. Ware Jr. Doctoral Dissertation and Post-Doctoral Awards in Patient Reported Outcomes, and K01 award from the National Institute of Mental Health (K01MH117496).

Footnotes

Disclosure statement

No potential conflict of interest was reported by the author(s).

References

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