Systematic Literature Review of Text Messaging Medication Adherence Promotion Interventions in People with Serious Mental Illness

Abstract

Objective:

Mobile health tools are feasible options for patients with serious mental illness () to encourage behavior change. The umbrella of “mobile health tools” varies widely, both in platforms used and content delivered. This literature review assessed the use of text messaging adherence enhancement interventions. It reviews original research on text messaging interventions to promote medication adherence in patients with serious mental illness.

Methods:

A systematic literature review using PRISMA guidelines evaluated short message service (SMS)/texting messaging interventions for medication adherence in serious mental illness. Databases included PubMed, Cochrane, CINAHL, and PsycINFO. Data extraction included demographics, disorder characteristics, intervention components, medication class, adherence measures, research design, and study outcomes. Study quality was also assessed.

Results:

Of 114 full-text articles screened, 10 papers were selected from nine unique trials (N=937 people with serious mental illness). Study durations ranged from 30 days to 18 months, with frequency of SMS ranging from twice weekly to 12 times daily. Of the 9 unique trials, the majority reported using an automated server to deliver SMS messages (k=7), 2-way SMS capabilities (k=6), customized message content and/or timing (k=7), and additional components (k=7; e.g., provider contact, educational content, monetary rewards). Seven of the 10 papers reported statistically significant improvement in adherence and at least one clinical outcome.

Conclusions:

Evidence to date indicates that text-messaging interventions are not only feasible but also appear to improve medication adherence and clinical outcomes in patients with serious mental illness. Future research should assess implementation approaches and how to scale-up efforts in non-research settings.

I. Introduction

Serious mental illness can impact cognitive, social, and occupational functioning, add stress to family units, and ultimately decrease quality of life^1–5. The scientific literature maintains that adherence to evidence-based medications can dampen symptomatic disease and, in turn, improve global functioning and quality of life^6–10. However, medication non-adherence is a pervasive problem for individuals with serious mental illness with rates of partial or total non-adherence between 40 to 50%^11–14. Drivers of non-adherence are complex, including unintentional non-adherence factors (i.e. forgetfulness), which in part stem from illness symptomology and baseline functioning (e.g. poor insight into illness, impaired cognition, apathy), and intentional non-adherence factors (e.g., negative attitudes towards medications, aversion to side effects, past treatment ineffectiveness)^11,12,15.

Furthermore, defining what constitutes “non-adherence” is also complex. For example, categorizing patients into binary adherent versus non-adherent groups fails to capture the difference between those who takes none of their medications versus those who take it 50% of the time. It would also neglect other potentially clinically relevant dimensions such as the timing of taking medications or what circumstances surround missing doses. Indeed, expert consensus on capturing adherence suggest using multiple methods to define adherence and quantifying the proportion of missed drug is a better approach¹⁶.

Technological platforms are increasingly utilized as a means to promote patient wellness and treat disease across many diverse illnesses and patient populations^17–20. Given the potential for downstream effects on patient and clinical outcomes, medication adherence has been a target of such platforms. In the era of the COVID-19 pandemic, the normativity and culture around remote healthcare delivery is rapidly shifting with long-term implications^21,22. However, “technological platforms” represent a heterogeneous group of services – from mobile applications, video conferencing, and web browsers to smart home technology and wearable devices^23–26 – with equally diverse intervention content and goals. This creates a practical challenge for researchers and clinicians interested in implementing technological platforms effectively.

A large body of research suggests that mHealth interventions are feasible, acceptable and efficacious in those with serious mental illness^27–38. In an early systematic literature review on mobile and web-based text messaging in mental health, a notable rise in efforts to implement mHealth platforms was observed starting around 2006 across several diverse patient populations, but studies were predominately assessing feasibility and acceptability by patients²⁷. Similarly, another systematic literature review reported acceptance and feasibility of online, social media, and mobile technologies in treating psychosis²⁸. Earlier systematic literature reviews also reported on the expansion of technology to address medication adherence specifically in patients with mental health concerns, such as schizophrenia^31–33. Furthermore, more recent systematic literature reviews provided greater evidence for improved outcomes, such as increased clinical engagement and medication adherence, through mHealth interventions in populations with serious mental illness^30,35,38.

On the whole, most of the previous reviews have included a variety of intervention delivery platforms, treatment goals and/or permissible clinical diagnoses. This systematic literature review aimed to supplement the current literature on mHealth platforms targeting treatment in individuals with serious mental illness by focusing on a specific subset of intervention delivery methods, treatment goals, and clinical conditions, namely mobile text messaging, or short messaging service (SMS), in patients with serious mental illness to promote medication adherence. This focus may be particularly practical considering favorable estimates of cell phone ownership, a relatively low skill set required for usability³⁹, and the importance of daily medication adherence in people with serious mental illness. In this systematic literature review, serious mental illness was defined to include schizophrenia spectrum disorders, bipolar disorders, major depressive disorder, and otherwise unspecified psychosis, as there is clear evidence for the need for pharmacotherapy in the treatment of these conditions^40–42. We used the systematic approach outlined below to answer four questions: 1) What is the literature on the use of text messaging to promote medication adherence? 2) What properties of a text messaging intervention have been shown to be efficacious in enhancing medication adherence? 3) What are common limitations or pitfalls to using text messaging to promote adherence? 4) What questions or next steps in research are suggested by the current body of work?

II. Methods

A. Literature Search

PubMed (Medline), Cochrane, CINAHL, and PsychINFO databases were searched in February 2021. Boolean logic was used to combine search terms to find relevant indexing to represent adherence promotion interventions with text messaging. The literature search used the following terms: “medication adherence,” “serious mental illness,” and “text-messaging” along with other closely related or synonymous words.

B. Inclusion and Exclusion Criteria

Inclusion of articles were based upon the following criteria: 1) English language peer-reviewed literature; 2) original research reports; 3) prospective interventional studies; 4) research involving humans only; 5) research involving any age group; and 6) research involving patients with an serious mental illness diagnosis, which was defined as major depressive disorder, bipolar disorder, schizophrenia/schizoaffective disorder, or other psychotic disorder based on self-report, clinical evaluation, standardized diagnostic interview, or medical record diagnosis. Additionally, the study intervention must assess or promote medication adherence using a standardized medication questionnaire or quantitative measure of medication, and not solely by assessing changes in attitudes around medication or endorsing “yes/no” regarding taking medications as prescribed at only two time points. The intervention must also include a text messaging component which offered the following: medication reminders, health education, encouragement/health promotion, or prompts to which a patient could respond, but was not simply appointment reminders or for the sole purpose of data collection. The SMS component could be automated or delivered by a clinician, nurse, researcher, etc. and participants could have additional diagnoses other than serious mental illness. Similarly, medication adherence did not need to be specific to medications prescribed for serious mental illness (i.e. adherence to hypertension medications in patients with major depressive disorder would be permissible).

Exclusion criteria from the study included: 1) studies where the SMS intervention was a simple notification regarding an appointment or for the sole purpose of data collection; 2) interventions where patients used mobile applications to receive messages or interact but no SMS was used; 3) studies that only assessed medication adherence based on patients’ opinions or attitudes towards medication without any measurement of how often the patient is taking any given medication; 4) opinion pieces/editorials; 5) other literature reviews; 6) literature that only described research methods with no interventional component; 7) case studies (N ≤ 5); 8) studies that only reported on access or availability of technology; 9) reports that only describe methods (no outcome data), 10) book chapters, and 11) posters or conference abstracts.

C. Data Extraction

Data extracted included the components of the intervention, psychiatric disorder, care setting, number of participants, primary outcomes, secondary outcomes, comorbidities, adherence measurements, duration of intervention, medication class, one-way versus two-way SMS, frequency of SMS, automated versus care provider generated messages, SMS content, research design, medication adherence change, and participants’ age, gender, race/ethnicity, and socioeconomic status/employment. Both qualitative and quantitative data were collected regarding text messaging and medication adherence.

D. Study Quality Assessment

Quality assessment of the articles was completed using the adapted Methodological Quality Ratings Scale (MQRS)⁴¹. The MQRS is a widely used tool to evaluate the quality of studies based on several components: 1) study design, 2) replicability, 3) baseline, 4) quality control, 5) follow-up length, 6) dosage, 7) collaterals, 8) objective verification, 9) dropouts and attrition, 10) statistical power, 11) independent, 12) analyses, and 13) multisite. The possible scoring range on the MQRS was 0 to 16 with higher scores indicating greater methodological quality.

III. Results

A. Study characteristics

Of 114 publications identified, 11 met initial inclusion criteria. One publication was excluded because it was an additional analysis of the same study sample and no new adherence data were reported. One publication represented an extension of a previously reported intervention that was included because it provided additional medication adherence data. Thus, 10 publications, including 9 unique interventions, underwent data extraction (see CONSORT diagram)^42–52. Characteristics of the 10 papers are shown in Table 1. Seven of the 10 studies were randomized controlled trials (RCTs) including one stepped-wedge RCT. One study was a prospective cohort study, and one study piloted an intervention without a comparison group. Finally, one study employed non-randomized allocation of participants into intervention or comparison groups.

Table 1.

Study Characteristics - Demographics, Setting, and Duration

Study (first author, publication year)	Mean Age (Years)	Sex (n, [%] of women)	SES	Race/Ethnicity (%)	Location	Recruitment Care Setting	Study Duration	Methodological Quality Ratings Scale (MQRS)
Xu et al., 2019 (42)	46.0	154 (55.4)	Low	NR	China (rural)	Enrolled in community treatment program	5.5 months	14
Mohammadi et al., 2016 (43)	33.1	37 (61.7)	Moderate	NR	Iran (urban)	Outpatient psychiatry clinic(s)	6 weeks	9
Cullen et al., 2020 (44)	49.1	17 (42.5)	NR	85 B 7.5 W 7.5 O	U.S.	Enrolled in community treatment program	6 months	11
Beebe et al., 2014 (45)	48.7	19 (63.3)	NR	50 B 50 W	U.S. (SE)	Enrolled in community treatment program	3 months	10
Granholm et al., 2012 (46)	48.7	13 (31)	NR	7 B 74 W 10 H	U.S. (San Diego)	Outpatient residential and treatment settings	12 weeks	8
Montes et al., 2012 (47)	39.6	85 (33.5)	NR	NR	Spain	Outpatient psychiatry clinic(s)	6 months; 3 months of intervention	13
Menon et al., 2018 (48)	37.9	63 (47.7)	Low	NR	India	Academic Medical Center, outpatient psychiatry clinic(s)	6 months; 3 months of intervention	12
Levin et al., 2019 (49)	51.5	20 (53)	NR	73.7 B 23.7 W 2.6 O	U.S. (urban)	Academic Medical Center	3 months; 2 months of intervention	10
Moore et al., 2015 (50)	47.2	6 (12)	NR	54 W	U.S. (San Diego)	Research Program at a University	30 days	11
Cai et al., 2020 (51)*	--	--	--	--	--	--	18 months; 6 or 12 months of intervention	13
AVG/TOTAL	44.6	414 (44.1)						11.1

Note:SES = socioeconomic status, SE = southeast, NR = not reported, B = Black, W = white, A = Asian, H = Hispanic, O = other

^*Represents an extension of Xu et al., 2019; blank columns remained the same across the two studies

A total of 937 people with serious mental illness were analyzed across the studies. Of the 9 unique study samples, the diagnostic breakdown of participants included 610 with schizophrenia, 47 with schizoaffective disorder, 220 with bipolar disorder, and 60 with major depressive disorder. All participants were outpatients. Care settings included community-based mental health programs, psychiatric clinics, residential programs, and academic medical or research centers. The majority of the study samples were collected in the U.S. (k = 5), while the other studies were conducted in rural China, urban Iran, Spain, and India.

The average age of participants was 44.6, and 44.1% of the participants were women. Socioeconomic status (SES) was reported for three of the study populations: two had a majority of low SES while the other had a majority of moderate SES. The five US-based populations included the following racial and/or ethnic data: in two studies, the majority of participants were Black (85% and 73.7%, respectively); in one study, 50% of participants were Black; and in two studies, the majority of participants were white (74% and 54%, respectively).

Study durations ranged from 30 days to 18 months (Table 1) with some studies capturing data after a period without the intervention, allowing for analysis of extinction or maintenance of study outcomes^42,47,48,51. One study obtained baseline data for a month prior to implementing the intervention, providing more robust baseline data than self-report alone^49,52.

B. Interventions

1. SMS intervention delivery, structure, and frequency

While all 9 interventions used SMS, the format, timing, and frequency of these messages was heterogeneous (Tables 2 and 3). The majority of the 9 interventions reported use of an automated server to deliver messages (k=7) and allowed for or prompted a response from participants (i.e. 2-way SMS capabilities, k = 6). One of the studies delivered messages via the principal investigator⁴⁵ and one did not report delivery method⁴⁸. In 3 of the studies, no responses were provided by participants (i.e., 1-way SMS capabilities)^43,47,48. Participants were able to customize the content of the messages (k= 5) and/or the timing they received the messages (k=5) in the majority of the interventions. This included simple choices, such as selecting reminder or reinforcement stems from a predetermined list⁵⁰, patient-created symptom surveillance⁴⁴, or reminder content^49,50.

Table 2.

SMS Delivery

Study (first author, publication year)	1-way vs 2-way SMS	Automated vs Manual	Customized Message Content	Customized Message Timing	Frequency Minimum	Text Follow-up	Provider Follow-up	Content Themes	Content details
Xu et al., 2019 (42)	2	Automated	No	No	BID	No	Yes	MR, EC, SRS	MR, EC – daily SRS – monthly
Mohammadi et al., 2016 (43)	1	Automated	No	NR	BID	No	No	MR, EC, ER	MR or EC – daily ER – daily
Cullen et al., 2020 (44)	2	Automated	Yes	Yes	BID	Yes	Yes	MR, EC, SRS, ER	SRS - QD minimum EC and/or ER - QD minimum MR or EC or ER - 1QD
Beebe et al., 2014 (45)	2	Manual	Yes	NR	QD	Yes	No	MR, SRS, ER	MR or SRS or ER - QD
Granholm et al., 2012 (46)	2	Automated	Yes	Yes	12 daily	Yes	No	MR, SRS, EC	MR, SRS, EC - each 4 times daily, total of 12 messages per day
Montes et al., 2012 (47)	1	Automated	No	Yes	QD	No	No	MR	MR - QD
Menon et al., 2018 (48)	1	NR	No	Yes	2 per week	No	No	MR	MR - QD
Levin et al., 2019 (49)	2	Automated	Yes	Yes	3+ daily*	Yes	No	MR, EC, SRS, ER	Month 1: EC, SRS – each QD Month 2: MR - QD per medication, ER, SRS – each QD
Moore et al., 2015 (50)	2	Automated	Yes	Yes	3+ daily*	Yes	No	MR, ER	MR – QD per medication ER – QD minimum
Cai et al., 2020 (51)†	--	--	--	--	QD	--	--	--	MR – QD EC – once every other day SRS – monthly

Note:QD = quaque die (once a day), BID = bis in die (twice daily), NR = not reported, MR = medication reminder, EC = education/coping strategy, ER = encouragement/reinforcement, SRS = symptom/relapse surveillance

^*baseline minimum dependent on # of medications

^†Represents an extension of Xu et al., 2019;

blank columns remained the same across the two studies

Table 3.

Intervention Components

Study	Intervention or Trial Name	SMS only?	Additional interventions (NONE, educational materials/sessions, phone calls, monetary rewards/gifts, provider/support person involvement)
Xu et al., 2019 (42)	LEAN	No	Monetary rewards/gifts; Provider/support person involvement
Mohammadi et al., 2016 (43)	--	No	Educational materials/sessions
Cullen et al., 2020 (44)	T4RP	No	Provider/support person involvement
Beebe et al., 2014 (45)	TIPS*	No	Phone calls
Granholm et al., 2012 (46)	MATS	No	Monetary rewards/gifts
Montes et al., 2012 (47)	--	Yes	NONE
Menon et al., 2018 (48)	--	Yes	NONE
Levin et al., 2019 (49)	iTAB-CV	No	Educational materials/sessions
Moore et al., 2015 (50)	iTAB	No	Educational materials/sessions

^*TIPS (Telephone Intervention Problem Solving for Schizophrenia) was adapted to include SMS

One of the more complex and diverse elements of the study interventions was the frequency of text messages. Frequency of SMS messages ranged from as little as twice weekly⁴⁸ to 12 times daily⁴⁶. Customized to meet specific patient needs, two of the studies – both variations of the individualized texting for adherence building (iTAB) technology – determined the number of reminders based on individual medication schedules^49,50. Additionally, these interventions created a system to re-engage participants who had not responded to several messages with outreach messages or phone calls. One of the interventions had algorithmic systems that modified the frequency and message content based on participant responses⁴⁴.

2. SMS themes and content

Beyond the “mechanics” of intervention delivery, the thematic elements of the messages delivered varied, both within a given intervention and across studies. Generally, the themes included the following: medication reminders, coping strategies or educational content, symptom surveillance, and encouragement or reinforcement (Table 2). All of the interventions included some form of medication reminder, with two studies using medication reminders as their only SMS content^47,48. Medication reminders varied from simple, closed-ended remarks (“Please remember to take your medication”⁴⁷) to more complex, personalized messages (“John, your meds r important. It is time to take ur meds. Take ur big blue pill now. Pls reply (A) took (D) didn’t (G) snooze”⁵⁰).

Coping strategies, such as incorporation of cognitive behavioral therapy techniques embedded into messages, or education was provided in 5 of the 9 interventions (Table 2)^{42–44,46,49}. Educational content focused on medication side effects^42–44, symptom management, relapse prevention (“If I don’t take my meds, I may become manic/hypomanic or very irritable”⁴⁹; “Adhering to your medication on time and on the prescribed dose is the key to control your symptoms. We are here to help you.” ⁴²), self-care, and social resources⁴².

Symptom surveillance or relapse monitoring was provided in 5 of the 9 interventions (Table 2). The content was disease and/or patient centered. For example, Granholm et al.⁴⁶ included inquiry about hallucinations and socialization, both components of Schizophrenia Spectrum Disorders, while Cullen et al. created patient-selected signs of relapse⁴⁴. Conversely, in two of the studies that centered around individuals with bipolar disorder, surveillance focused on monitoring participants’ daily mood^49,50.

Finally, encouragement or reinforcement messages were provided in 5 of the 9 interventions (Table 2). Many were reactionary to participants’ responses. For example, the testing for relapse prevention (T4RP) intervention provided a supportive follow-up statement when a participant denied the presence of a relapse symptom⁴⁴. In iTAB-CV (iTAB-Cardiovascular), the second month of intervention followed-up medication reminders with messages such as “You’re doing wonderfully with taking your meds” with the option to customize the reinforcement⁴⁹.

3. Additional intervention components

Table 3 reports a summary of additional components of the interventions. Only two of the interventions were solely SMS-based without another element to the intervention^47,48. One study included a comparison group in which participants received both SMS and phone calls to enhance medication adherence⁴⁵. Two studies involved embedded additional support people in the intervention design. The Lay health supporters, E-platform, Award, and iNtegration (LEAN) trial required a health supporter who could receive and send text messages for each participant and allowed for village doctors and/or psychiatrists to be contacted if signs of relapse were endorsed^42,51. Similarly, the intervention by Cullen et al. included a customized threshold of symptom endorsement that would trigger contacting a provider, who would then follow up with participants within 24 hours⁴⁴.

Three of the studies provided participants with educational content in addition to the SMS intervention. Themes from these sessions included benefits of adhering to medications, coping with serious mental illness diagnosis, strategies for adherence and medication side effects. Finally, two of the studies provided participants with small monetary rewards or gifts in response to engagement with the intervention^42,46,51.

C. Medications and measuring adherence

The medication classes targeted for enhancing adherence included oral psychotropic medications (typical and atypical antipsychotics, mood stabilizers, anti-parkinsonism, hypnotics, anti-anxiolytics, antidepressants, anticonvulsants), long acting injectables, oral medications for physical illness (antihypertensives, antiretrovirals), or otherwise unspecified oral medications (Table 4). Studies differed in terms of how medication requirements affected participant inclusion or intervention target. For example, Montes et al. specified that participants must be prescribed only one oral antipsychotic to be included⁴⁷. Conversely, both iTAB studies explicitly targeted a minimum of two medications including an appropriate psychotropic medication and an appropriate medication to address the comorbid medical condition of the study population (i.e., HIV or hypertension, respectively)^49,50.

Table 4.

Medication Adherence

Study	Medications of Interest	Adherence Measurement	Significant improvement in medication adherence*	Medication Adherence Outcome of interest	Medication attitudes	Additional Standardized Scales	Significant Clinical Improvements
Xu et al., 2019 (42)	Oral psychotropic medication	Pill count, Medication refill, BARS	Yes	Greater proportion of pills taken by intervention group in non-adherence subgroup (p = 0.047)	DAI-10	CGI, WHODAS	Reduction in risk of relapse in intervention group, reduction in risk of rehospitalization in intervention group
Mohammadi et al., 2016 (43)	Antidepressant medication	Self-report questionnaire	No	No significant difference in depression score or medication adherence (p=0.06 and 0.31)	None	BDI-II-Persian	--
Cullen et al., 2020 (44)	Oral medications (not specified), Long Acting Injectable (LAI)	Proportion of injections received, BARS	Yes	Oral: Improved medication adherence at 3/6 months (p-0.11). LAI: Significantly higher adherence at 6 months only (p = 0.02)	None	PANSS, RAS-R, MADRS, BUES, YMRS	Positive subset of PANSS lower in intervention group at 6 months; RAS-R recovery scores significantly higher at 3 months in intervention group
Beebe et al., 2014 (45)	Oral non-psychiatric medications, Oral and LAI psychotic medication	Pill count, Proportion of injection received	No	No significant difference in medication adherence for psychiatric or nonpsychiatric medication (p=0.31, p=0.71)	None	BPRS	Significant main effect for group for BPRS scores (mean lower scores on BPRS in TIPS and texting group than TIPS alone or texting alone groups, respectively)
Granholm et al., 2012 (46)	Atypical antipsychotics, typical antipsychotics, antidepressants, mood stabilizers	Self-report: daily ambulatory monitoring outcome assessment question	Yes	Significant improvement in medication adherence in participants living independently (p=0.05)	Self-report	PANSS, BDI-II, ILSS, ANART	Time in the intervention increased the odds of having more social interactions and of reporting less auditory hallucinations
Montes et al., 2012 (47)	Oral antipsychotics	MAQ	Yes	Significant reduction in MAQ scores from baseline to 3 months (p=0.02). Maintenance of reduced MAQ score at 6 (p = 0.04)	DAI-10	CGI-SCH (SI and DC), SUMD, EQ-5D	Reduction in negative symptoms subscale of CGI-SCH-SI, greater improvement in negative, cognitive and global symptom subscales of CGI-SCH-DC at 3 months, improvement in quality of life via EQ-5D in intervention group
Menon et al., 2018 (48)	Antipsychotic mood stabilizers	MMAS	Yes	Significant improvement in medication adherence at baseline to 3 months (p<0.001). Maintenance of improved medication adherence at 6 months for both ITT and completer analyses (p<0.001)	DAI-10	WHOQOL	--
Levin et al., 2019 (49)	Antipsychotic mood stabilizers Anticonvulsants Anti- hypertensives	eCAP TRQ	Yes	Significant decrease from screening to baseline following 2 months of intervention for both Bipolar Disorder and HTN medication adherence (p<0.001). No significant decrease between any time points for eCAP.	None	BPRS, MADRS, YMRS, SRHI	Decreased systolic blood pressure, improved BPRS scores, and lower MADRS scores, and higher habit formation between screening and follow-up time points during intervention
Moore et al., 2015 (50)	Psychotropics antiretrovirals	eCAP self-report visual analogue scale	No	No significant difference in adherence to psych or antiretroviral medications	None	YMRS, BDI-II	--
Cai et al., 2020 (51)†	--	--	Yes	Greater proportion of pills taken during extended intervention period (p = 0.004)	--	--	Decrease in illness severity via CGI reduction in hospitalizations during intervention periods compared to control period

^*For at least one analysis related to medication adherence

^†Represents an extension of Xu et al., 2019; blank columns remained the same across the two

Abbreviation Guide for Table4:

Clinical Global Impression (CGI)

Clinical Global Impression-Schizophrenia Scale, severity of illness and degree of change (CGI-SCH, SI and DC)

Morisky Green Adherence Questionnaire (MAQ)

WHO Disability Assessment Schedule 2.0 (WHODAS)

WHO Quality of Life Instrument (WHOQOL)

Positive and Negative Syndrome Scale (PANSS)

Beck Depression Inventory-II-Persian (BDI-II-Persian)

The Montgomery- Asberg Depression Rating Scale (MADRS)

Recovery Assessment Scale Revised (RAS-R)

Brief Adherence Rating Scale (BARS)

Boston University Empowerment Scale (BUES)

Brief Psychiatric Rating Scale (BPRS)

Independent Living Skills Survey (ILSS)

American National Adult Reading Test (ANART)

Drug Attitude Inventory-10 (DAI-10)

Morisky Medication Adherence Scale (MMAS)

Tablets Routine Questionnaire (TRQ)

Self-Report Habit Index (SRHI)

In terms of measuring medication adherence, most of the studies used self-report either exclusively or in combination with objective measures (k= 8). Two used the Brief Adherence Rating Scale, two used the Morisky Green Adherence Questionnaire, one used the Tablets Routine Questionnaire, and the remaining three used study-specific measures. In addition to self-report, four of the studies also used objective measures, such as random pill counts, medication refill records, number of pill bottle openings or proportion of injections received. Beebe et al. was the only study to use exclusively objective data, using proportion of pills or injections received based on pill counts or injection schedule, respectively⁴⁴.

D. Outcomes

1. Medication adherence

In 7 of the 10 papers, significant improvement in medication adherence was observed from baseline to post-intervention and/or in intervention groups compared to controls (Table 4). Particularly robust results were observed in the LEAN trial where a significantly greater proportion of pills taken by the intervention group compared to control group was maintained in subgroup analysis of baseline non-adherent participants, representing efficacy of the intervention in particularly vulnerable participants⁴². Furthermore, after a 3-month hiatus from the intervention, reintroduction for an extended 3 months reaffirmed significant improvement in adherence, albeit to a smaller magnitude⁵¹. Two studies, which reassessed adherence 3 months after intervention, found maintenance of adherence gains after intervention completion^47,48.

Of the studies that did not find significant improvement in medication adherence, lack of study power was cited as a potential contributor^43,45. Additionally, in an attempt to create a rigorous control, one study sent a daily text message, albeit not the full intervention, to the control group, which was suggested by the authors as driving the high adherence (compared to pilot data in similar populations) in both the intervention and control condition⁵⁰. Similarly, in the study by Granholm et al., only the subset of individuals living independently showed significant improvement in medication adherence, likely a function of high baseline medication adherence secondary to staff support given to individuals in assisted living⁴⁵.

2. Attitudes toward medication

Five of the 10 papers assessed for participant attitudes towards medication (Table 4). Four used a version of the Drug Attitudes Inventory (DAI), including both of the LEAN trial studies (same study sample but reported on different time intervals)^42,47,48,51. Granholm et al. used self-report data collected directly via the intervention⁴⁵. The two LEAN trial reports did not find a significant change in attitudes via DAI, but the other two studies did report significantly improved attitudes, one of which saw maintenance of effects 3 months after intervention completion⁴⁷. Finally, a significant decrease in negative attitudes was observed via self-report data by Granholm et al.⁴⁵

3. Clinical outcomes

All ten papers measured at least one clinical outcome, such as serious mental illness symptoms, mood, quality of life, hospitalizations, and rates of suicide (Table 4). Of these, seven reported at least one statistically significant improvement in clinical outcomes or reduction in symptomology.

4. Study Quality Assessment

The MQRS results are found in Table 1. Scores for the included studies ranged from 8 to 14 and averaged 11.1 ± 1.91. Strengths in study quality included the predominance of RCTs (k=7) and inclusion of pre-intervention baseline and post-intervention follow-up analysis (k=4). Lack of randomization and/or lack of inclusion of a control group limited three of the studies^43,46,49, and under-powered or ceiling effects were cited in studies that lack significant findings in regards to medication adherence ^43,50. Finally, although most of the studies collected data over the course of several months, medication adherence in those with serious mental illness is a typically life-long commitment. Thus, study duration limits the validity of the results on the long-term time scale.

IV. Discussion

The delivery of clinical interventions using mobile technology is increasingly commonplace, including for those with serious mental illness³⁹. Furthermore, the demands of the current COVID-19 pandemic have accelerated the delivery of healthcare services via mobile technology⁵³. However, the heterogeneity in the platforms of mobile technology (SMS, phone calls, web browsers, smartphone applications, video meetings, etc.), the content delivered (appointments, reminders, education), and the goals of the interventions (medication adherence, healthcare delivery, disease surveillance) creates a challenge to those interested in utilizing remote delivery services in terms of how to be most effective. In those with serious mental illness, this challenge is exacerbated by the interaction of the patients’ underlying illness with treatment engagement^11,54.

Improvement in attitudes towards medications was observed across several studies^47,48,52. This has potential implications as to how the interventions are driving increased medication adherence. Although in its simplest form, text messaging can serve as a reminder to take medications, targeting unintentional non-adherence alone (i.e. forgetfulness) only addresses one of the drivers of patient behavior. Attitudes and beliefs around medication, side effect profile, and insight into illness have been proposed as prominent components of medication non-adherence in populations with serious mental illness^12,55. Interestingly, two of the studies which reported improved attitudes toward medication, Montes et al. and Menon et al., represented the most minimalist interventions of those included.^47,48 Both used a 1-way SMS messaging model with medication-reminder-only content, provided no additional interventional components, and only messaged once daily or twice weekly, respectively. Furthermore, both included a 3-month follow up and showed maintenance of the improved adherence. As all of the other interventions included multiple content themes and supplemental interventional components, these two studies offer evidence that even simple SMS messaging has the potential to drive robust changes in patient behavior.

In contrast, two of the studies provided evidence that inclusion of providers and support persons for patients with mental illness is a feasible and efficacious extension of texting platforms. Xu et al. integrated local physicians, psychiatrists, and personal support members into their intervention in the LEAN trial⁴¹. The integration of support was particularly compelling given the rural setting of the study, where technology like SMS can have an even greater impact on enhancing connectivity. Beyond improved medication adherence, risk of relapse and rates of rehospitalization were significantly reduced in this integrated model. This aligns with general treatment ideologies for serious mental illness, and schizophrenia in particular (the diagnosis of patients in the LEAN trial), where intradisciplinary approaches to treatment have been encouraged⁵⁶, including integration of family members⁵⁷. Cullen et al. incorporated direct contact with patient providers when a predetermined, patient-specific threshold of symptom endorsement was met via SMS responses⁴⁴. The opportunity to intervene by providers at early signs of relapse is an exciting prospect in disease management. It conceptually aligns with best-care strategies for treating schizophrenia, where higher rates of relapse have been demonstrated in those with medication non-adherence in both placebo controlled trials and reviews of hospitalization records⁵⁸.

Another promising expansion of more recent interventions includes targeting comorbidities beyond serious mental illness through SMS platforms. In the iTAB and iTAB-CV studies, antiretroviral and antihypertensive medication adherence, respectively, was also integrated into the model^48,49. Antiretrovirals were taken closer to their intended time window in those in the iTAB intervention group. In iTAB-CV, significant reduction in systolic blood pressure was observed from baseline to post-intervention. High rates of cardiovascular disease have been reported in those with bipolar disorder⁵⁹ and there is a disproportionate prevalence of HIV in those with psychiatric conditions⁶⁰. Non-adherence to medications for chronic physical health conditions have their own consequences on patient well-being, which can impact one’s ability to manage their mental health. Furthermore, increasing numbers of medications creates increased demands on patients in terms of organization and routine, thus platforms that address multiple conditions and/or medications offer a low-cost high yield collaborative care model, particularly for high-need patients.

Our review illustrates that many practical questions remain in terms of how to most effectively deliver an SMS intervention to individuals with serious mental illness. Despite a rather narrow set of inclusion criteria, the interventions varied widely and few clear themes emerged in terms of what is most effective. Both one- and two-way messaging, customized and standardized content, and highly infrequent to several daily messages led to appreciable improvement in medication adherence. Additionally, measurement of medication adherence, although captured in each study, was largely via self-report or by methods that allow for introduction of additional confounding variables. Furthermore, study limitations, such as poorly powered studies, lack of control group, ceiling effects, and relatively short study durations (particularly in light of the chronic nature of medication therapy required for most of the included conditions) hinders interpretation of what is likely to make a clear impact on clinical outcomes.

Future studies are needed to address remaining limitations both in terms of study methodology and real-world application. Creating multiple study conditions, each of which captures a single dimension of an intervention would allow for more clarity as to which specific components are effective. As one example, having two groups, one that receives one-way and one that receives two-way messaging, or groups that receive varying numbers of messages a day, would aid in finding the “sweet spot” between sufficient reminders and fatiguability. In terms of real-world application, studies that follow participants for years (with or without continual interventional support) would illuminate the durability of study effects, the timescale for habit formation and the potential need to reinstate interventions after certain intervals without them. Finally, increasing the objectivity of “improved adherence” by using automated pill counts or patient-recorded video clips of taking medications may strengthen the quality of the data but must be balanced with proper controls to reduce the risk of introducing potential confounders.

V. Conclusions

This review provides evidence that increasing medication adherence via SMS platforms among people with serious mental illness is likely feasible and achievable. The majority of the interventions found significant improvement in medication adherence with SMS and associated improvement on clinical measures including reduced rehospitalization, improved quality of life, and decreased symptom burden^42,47,49,51. Promisingly, these findings were in several diverse patient populations with differing geographical locations, race, and socioeconomic status captured across the included studies. However, caution should be used in presuming the robustness of these findings, as many of the measures of improvement medication adherence were subjective in nature.

Future studies are needed with 1) better controls for confounds to allow for identification of what is driving study outcomes, 2) longer study durations to confirm durability of effects, 3) more objective measurement of medication adherence, and 4) methodology that evaluates the minimal time needed to establish a habit of medication adherence and how to maintain it once it has been established.

Highlights:

• This systematic review demonstrates that increasing medication adherence via SMS platforms among people with serious mental illness is feasible and achievable.

• Both one- and two-way messaging, customized and standardized content, and highly infrequent to several daily messages led to appreciable improvement in medication adherence.

• Of 10 selected publications, 7 found a significant improvement in medication adherence following the intervention and at least 1 significant improvement in a clinical outcome.

• Future research is needed to assess implementation approaches and how to scale-up interventions in a clinical setting.

List of abbreviations:

SMS

short messaging service

RCT

randomized controlled trial

MQRS

Methodological Quality Ratings Scale

SES

socioeconomic status

iTAB

individualized texting for adherence building

T4RP

testing for relapse prevention

LEAN

Lay health supporters, E-platform, Award, and iNtegration

DAI

Drug Attitudes Inventory