Distant mood monitoring for psychiatric disorders: A systematic review

Background: Whilst electronic self-monitoring and intervention programmes for mood disturbances in psychiatric disorders may promote self-management and patient empowerment, some level of interaction with professionals (such as clinicians, counsellors, and researchers) coupled with support is still positively valued by patients. This can allow for a more personalised approach, improve the efficiency of treatment, and adverse events can be managed in a time-appropriate manner, thereby mitigating some of the risks associated with mood fluctuations. Methods: This systematic review synthesises quantitative and qualitative evidence on the effectiveness and feasibility of daily/weekly/monthly remote mood monitoring by distant supporters (clinicians, lay counsellors, and researchers) (or with regular feedback by distant supporters in cases where mood monitoring was self-assessed), in participants with any psychiatric disorder. Effectiveness was defined by the change in depression and/or mania scores. Feasibility was determined according to completion/attrition rates and participant feedback. Studies were assessed for quality using the Mixed Methods Appraisal Tool (MMAT) version 2018. Results: Eight studies met our inclusion criteria. Distant mood monitoring was effective in improving depression scores but not mania scores. Feasibility, as measured through compliance and completion rates and participant feedback, varied. Conclusion: Distant mood monitoring with feedback is an appealing intervention, particularly in low resourced settings; however, further studies are needed to better understand the utility, feasibility, and effectiveness of these interventions in routine clinical care.


Introduction
Broadening our knowledge of the longitudinal course of mood symptoms in psychiatric disorders is central to our understanding of patterns of chronicity, episodicity, relapse, and recurrence. Temporal changes in mood symptoms are a cardinal feature of depressive and bipolar disorder (Proudfoot et al., 2014;Sadock & Sadock, 2007).
Persistent mood symptoms are often accompanied by a variety of other symptoms (e.g. anxiety, cognitive, and functional disturbances) (Iosifescu, 2012). Additionally, persistent mood symptoms have been documented in patients with other psychiatric disorders including schizophrenia, anxiety, post-traumatic stress, and substance use disorders (Sadock & Sadock, 2007). Mood symptoms in these disorders have consistently been shown to impact on treatment outcomes, function, and prognosis (Strejilevich et al., 2013). Investigation of the longitudinal course of mood symptoms can contribute to knowledge of pathophysiological mechanisms of chronicity, episodicity, relapse, and recurrence; assist in guiding and optimising treatment (e.g. dose, duration) (Glasziou, Irwig, & Mant, 2005); and inform the development of novel and more effective treatments (van der Watt, Suryapranata, & Seedat, 2018).
Previous research indicates that patients with psychiatric disorders readily engage in the use of information technology (IT) platforms such as telemonitoring (Ure et al., 2011) and mobile technology (Bopp et al., 2010;Miklowitz et al., 2012) for mood assessment, monitoring, and treatment. These technologies allow for more regular data collection to track mood symptom trajectories. A systematic review of the validity of electronic self-monitoring of mood using IT platforms in adults with bipolar disorder found evidence for their validity when compared to clinical rating scales for depression (Faurholt-Jepsen, Munkholm, Frost, Bardram, & Kessing, 2016). Furthermore, weekly telemonitoring or text messaging has been shown to improve access to professional care in patients with bipolar disorder (Depp et al., 2015;Wenze, Armey, & Miller, 2014). Additionally, bipolar patients endorsed lower levels of illness experienced during facilitated integrated mood management (Miklowitz et al., 2012). Telemonitoring and text messaging to monitor patients' mood fluctuations, whilst not costfree, are far less expensive methods than traditional clinical interviews (Miklowitz et al., 2012;Wenze et al., 2014). These interventions can also assist in increasing adherence to treatment which is of benefit as non-adherence is a major, and costly, concern in the treatment of psychiatric disorders (see for example Wenze et al., 2014).
Whilst electronic self-monitoring and intervention programmes may promote self-management and patient empowerment; keeping some sort of interaction underpinned by professional support (such as with clinicians, lay counsellors, and researchers) is positively valued by patients (van der Watt, Roos, Beyer, & Seedat, 2018). Additionally, it provides a more personalised approach, improves efficiency of treatment (Newman, Szkodny, Llera, & Przeworski, 2011;Proudfoot et al., 2014;Todd, Jones, Hart, & Lobban, 2014), and allows for adverse events to be managed in a time-appropriate manner, thereby mitigating some of the risks associated with mood fluctuations (Newham & Martin, 2013).
This systematic review evaluates the effectiveness and feasibility of distant mood monitoring involving clinicians, lay counsellors, and researchers, in individuals with psychiatric disorders.

Objectives
We synthesised quantitative and qualitative evidence on the effectiveness and feasibility of daily/weekly/monthly remote mood monitoring in participants with any psychiatric disorder by clinicians, lay counsellors, and researchers (hereafter referred to as distant supporters), or where regular feedback was provided by distant supporters in cases where mood states were self-assessed.
Assessment of effectiveness was based on the change in depression and/or mania scores. Feasibility was determined according to completion/attrition rates and participant feedback. Studies were assessed for quality using the Mixed Methods Appraisal Tool (MMAT) version 2018.

Methods
This review has been registered on PROSPERO (CRD42017057227).

Literature search
The following data bases were searched by the first author to identify eligible articles: i.
Academic search premier-EBSCOhost ii.

SAGE journals
Additionally, the reference lists of included studies were searched to identify potentially relevant studies that may have been missed by electronic searches (Greenhalgh, 2005). After the first phase of the screening process (see Figure 1), relevant articles to which we did not have full text access were flagged. These articles were requested through an inter-library loan process at Stellenbosch University. The full text of one article (Whalen et al., 2006) could not be accessed and was excluded.

Search strategy
The following keywords (and MeSH terms) were used in searching for relevant literature:

Study design
All quantitative studies were included as well as studies that qualitatively assessed participants' perceived effectiveness of distant mood monitoring offered by distant supporters. Systematic reviews and commentaries were excluded. Studies that had been included in systematic reviews that met our inclusion criteria were included, but not the systematic reviews themselves.

Method of monitoring
Only studies in which the mood monitoring was done distantly were included, and the monitoring had to take place without any face-to-face contact (i.e. physical presence) between the patient and the person conducting the distant mood monitoring. Thus, studies where mood monitoring took place via telephone, internet, smartphone, e-mail, and/or pen-and-paper methods were included. This monitoring had to be done by a distant supporter. Studies where mood monitoring was done by the patient him/herself, were only included if a distant supporter provided feedback upon the patient completing a self-monitoring assessment.
Studies that focused only on participants' self-monitoring of mood states were excluded. Additionally, we excluded studies where mood monitoring was not conducted by a distant supporter, but by the patient him/herself, and where feedback was only computer generated without the assistance of a distant supporter. The decision to focus on mood monitoring conducted by a distant supporter (or which at least included some feedback by a distant supporter) was based on research indicating the effectiveness of participants being listened to (Billsborough et al., 2014) or simply talking to a researcher who is interested in what they have to say (Lowes & Paul, 2006). As such, mood monitoring which involves contact, albeit distant, with a distant supporter may have therapeutic benefits in and of itself (van der Watt, Roos, et al., 2018). Moreover, research has indicated that participants often take part in research studies, such as mood monitoring, in order to gain the aforementioned therapeutic benefits (Patel, Doku, & Tennakoon, 2003).

Screening process
Articles identified through the search were exported to Rayyan (Ouzzani, Hammady, Fedorowicz, & Elmagarmid, 2016) where the first and second author independently assessed their eligibility, using the blind function in Rayyan. As indicated in Figure 1, the screening process consisted of three phases: (i) Removing duplicates; (ii) Title and abstract screening; and (iii) Full text screening. After each phase, the blind function was turned off in order to resolve conflicts between the screeners.
The quality of included studies was independently assessed by the first and second author using the Mixed Methods Appraisal Tool (MMAT) version 2018 (Hong, Gonzalez-Reyes, & Pluye, 2018;Pace et al., 2012). However, since two of the included studies [blinded] were authored by the first author, a third independent researcher was asked to assess the quality of these two studies. A summary is presented in Table 3. Overall, the included studies were deemed to be of acceptable quality.
Of the 43 full text articles screened, 35 articles were excluded due to: lack of full text access (n = 1); monitoring/feedback taking place in person (n = 2); review papers (n = 2) or protocol papers (n = 1); lack of feedback to participants (n = 6); studies of participants without any psychiatric diagnosis (n = 8); and studies that did not report on mood outcomes (n = 15).

Data collection
The first author extracted the relevant information from the included studies, and the second author corroborated the information. The data extracted included study design, setting, sample, psychiatric disorder, method of monitoring, any additional information deemed important, and study findings.

Outcomes
The two main outcomes for which the data were sought were (i) effectiveness, and (ii)   Description of participants, assessments, and outcomes As indicated in Table 1, participants mainly comprised patients with mood and/or anxiety disorders (n = 6 studies Cole et al., 2006;Gensichen et al., 2009;Ross et al., 2008;van der Watt, Roos, et al., 2018;van der Watt, Suryapranata, et al., 2018); only studies by Rosen and colleagues (2013) and Timko and colleagues (2019) included patients with comorbid psychiatric disorders (viz., depression, anxiety disorder, substance use disorder, schizophrenia, or bipolar disorder). The proportion of females across the studies ranged from 6.7% (Ross et al., 2008), to 89.2% (van der Watt, Roos, et al., 2018). The age ranges varied widely (see Table 1

Effectiveness
We defined effectiveness (or lack thereof) in terms of an increase and/or decrease in depression and/or mania scores on a rating scale. Based on this definition, two studies Rosen et al., 2013) reported no significant improvement in depression and/or mania scores over the course of the study. Whilst Ross and colleagues (2008) at first reported lower depression scores and a lower rate of diagnoses for their intervention group, as compared to the control group; at study completion this difference was not significant.
Three studies (Cole et al., 2006;Gensichen et al., 2009;van der Watt, Suryapranata, et al., 2018) reported significant improvement in depression scores over the course of the study. In addition, one study (van der Watt, Roos, et al., 2018) reported that participants qualitatively reported mood monitoring to be effective. Furthermore, Timko and colleagues (2019)  In the present review, the only study that included subjective qualitative reports (van der Watt, Roos, et al., 2018), indicated high acceptability of distant mood monitoring. However, it should be noted that the subjective qualitative findings reported by van der Watt, Roos, and colleagues (2018) mostly included participants who completed the study, with only a few participants who dropped out of monitoring reporting their experiences. As such, these findings should be interpreted with caution.

Conclusion And Recommendations
This systematic review focused on the effectiveness of distant mood monitoring offered by clinicians, lay counsellors, or researchers, to patients with psychiatric disorders. Patient (self-) assessments were also included, provided that feedback was distantly provided by distant supporters. Mood monitoring was not specifically compared to other interventions. Only eight studies were found to be eligible for inclusion. The majority of studies were conducted in patients where mood disorder was the primary or co-morbid diagnosis. The studies used varying methodologies. Given the differences in sample characteristics, methodology, and outcome measures it is difficult to draw comparisons across the studies.
From the above findings, we tentatively conclude that distant mood monitoring may be effective in improving depression scores, but not mania scores. Feasibility, as measured through compliance and completion rates and participant feedback, varied. These findings are based on eight studies only, of which one included a placebo-control group and four a treatment-as-usual control group. Additionally, effectiveness and feasibility were loosely defined across studies. Changes in depression and mania scores may not necessarily correlate with improvement in quality of life or functioning. Furthermore, the present study is limited by the fact that only the first author located relevant studies through a systematic search of limited databases. Important databases such as PsychInfo could not be accessed since the study university did not have access to it. An additional independent systematic search would have been preferable. This, however, was not possible due to resource constraints. Yet, the use of a second, blinded, author in the screening process did add rigour to the study.        Yes: Participants were randomized with a balanced ration of 1:1 to receive either an intervention Android smartphone (the intervention group) or a control Android smartphone (the control group) for a 6-month trial period.
Yes: The data safety and monitoring board stratified the practices according to the size of the city and performed computerbased randomization. Participant random assignment status was nested within the practice status.
Yes: Rando gender, and wars in Iraq done centra randomizat to participa histories.

Are the groups comparable at baseline?
Yes: Randomization was stratified on age (<29 or ≥29 years) and former hospitalization (yes/no) since these were considered to be possible prognostic variables, and a fixed block size of 10 within each stratum was used.
Yes: See Table 2 in the article. There was no statistical difference between the two groups' characteristics at baseline.

Yes: See Ta
There was between th characteris 3. Are there complete outcome data? Yes: 82.62% of the intervention group data, and 87.18% of the control group data could be analysed.
Yes: 86.13% of the intervention group data, 91.14% of the control group data could be analysed at 12 month assessment.

Are outcome assessors blinded to the intervention provided?
Partial: Due to the type of intervention, this trial was singleblinded since blinding of the participants, the clinicians, and the study nurse handling the intervention was not possible.
No: Because of the practice staff training required for the behavioural intervention, participants, health care assistants, family physicians, and researchers were not blinded to assignment once the trial was started.
No: Due to intervention possible.

Did the participants adhere to the assigned intervention?
Yes: A total of 3.7% of participant visits were missing (3.6% in the intervention group and 3.8% in the control group) due to participants not attending.
Unclear: Follow-up data is reported for 84.8% of the participants at 6 months and 84.2% at 12 months). However, it is not clear how many completed the weekly/monthly assessments. No: There is no rationale provided 1. Are the participants representative of the target population?
Yes: Possib depression through fiv All patients offered par initiative. T indicates w approached 2. Are the different components of the study effectively integrated to answer the research question?
Yes: The qualitative and quantitative components complement each other and function well as a unified whole to answer the research question.

Are the measurements appropriate regarding both the outcome and intervention (or exposure)?
Yes: Depres using the P and valid m symptoms.

Are the outputs of the integration of qualitative and quantitative components adequately interpreted?
Yes: The qualitative component provides detailed evidence for acceptability and perceived effectiveness of mood monitoring and reasons for participant dropout. This information is effectively supported by quantitative data including baseline assessment and post-discharge assessment using established questionnaires.

Are there complete outcome data?
Yes: 68.57% analysed.

Are divergences and inconsistencies between quantitative and qualitative results adequately addressed?
Unclear: There appears to be no mention of any divergence or inconsistencies between quantitative and qualitative results.

Are the confounders accounted for in the design and analysis?
Yes: A deta provided on analysis ac

Do the different components of the study adhere to the quality criteria of each tradition of the methods involved?
Yes: It is reflected in the analysis and reporting of the data.

During the study period, is the intervention administered (or exposure occurred) as intended?
No: Becaus reported di version of t assessmen few weeks [1] Demographic data only presented for participants who completed the study.
[2] Demographic data only presented for participants who completed the study. Figure 1 Screening Process

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