Abstract
Keywords
Introduction
In suicide research, there has been an increase in studies employing real-time data collection methods such as ecological momentary assessments (EMA) and wearable sensor data. While a review of available EMA studies on suicide-related thoughts and behaviors (STBs) conducted in 2015 identified only four published studies, 1 23 studies were included in a review published in 2022. 2
Potentials of real-time data collection in suicide research
Advantages of EMAs over conventional methods like retrospective self-reports include a reduction of recall bias
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as well as high ecological validity and a fine-grained high temporal resolution matching clinically relevant time frames of hours and days.4–6 Wearable devices have been suggested as tools to assess the physiological correlates of STBs with the aim of predicting suicidal crises through physiological markers in real-time.
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Wearable data is thus not affected by potential disclosure problems regarding STBs or limited insight in STBs and might be specifically relevant for individuals experiencing no suicide ideation prior to a suicide attempt.
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Wearables are used, for example, to measure objective sleep disturbances (i.e. changes in duration and quality) as predictors of next-day suicidal ideation or acute increases in suicidal ideation8,9 or to assess heart rate variability, which has been shown to be negatively associated with decreases in STBs.
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In light of these advantages and potentials, EMA and wearables have been acknowledged as promising methods for evaluating and monitoring STBs and related physiological correlates in persons at risk, offering the opportunity to intervene
Measurement reactivity
Despite these promising opportunities EMAs and wearables offer for suicide research and treatment of persons at high risk of STBs, the effect of repeated measurements over days, weeks, or even months on the assessed constructs and on the participants remains somewhat unclear.
Previous studies addressing reactivity
A recent systematic review identified nine EMA studies addressing aspects related to feasibility and reactivity. 2 Most studies focused on changes in the underlying construct, targeting only one aspect of measurement reactivity. With regard to potential iatrogenic effects, these studies reported no symptom worsening (i.e. increased frequency of suicidal thoughts 18 ) no changes in intensity 19 or in the occurrence of suicidal ideation 20 with repeated prompts. Asked about the impact of EMA on suicidal ideation, 9% to 16% of participants reported feeling stressed or burdened by EMA or that it had triggered bad thoughts.21,22 On the other hand, 28% of participants felt generally better after EMA 23 and 3% reported a decrease in frequency and urge of suicidal thoughts 21 or an increased awareness of symptoms. 24 Interestingly, the majority of participants (approx. 60%) in a recent study 14 did neither report a positive nor a negative effect on their mood. Yet, 18% of participants observed a triggering effect of EMA on their SI and 10% a worsening of SI (particularly those with higher psychopathological burden at baseline, for example, higher levels of SI, depression, anxiety or borderline personality traits). In contrast, linear multilevel models found no effects of the number of assessments per day on affective states or suicide ideation. 14
Gaps in current research
We are not aware of any STB real-time studies focusing in particular on behavioral changes. Compliance and attrition rates often serve as indicators of altered response behavior (e.g. fatigue effects), but to date there have hardly been any findings on changes in everyday behavior or other changes in response behavior in EMA studies. 14 Compliance ranged from 44% to 75% in studies lasting 21 to 28 days (with ≥3 prompts/day) with lower rates in clinical populations and a decline of compliance with longer study duration (i.e. suggesting a general fatigue effect and associated change of response behavior2,25). In general, lower compliance and higher drop-out rates are associated with participant and study characteristics. For example, male and more severely burdened participants show lower compliance rates. 26 Moreover, interference of the assessments with everyday life (such as interrupting social contacts or travel) is associated with higher drop-out rates; 27 this effect is assumed to be even more pronounced in studies with a longer assessment period. 26 With increasing interference, the adaptation of daily routines or behaviors as well as disturbances of interactions with other persons might be more likely. To our knowledge, no study examining aspects of reactivity associated with the use of wearable devices in the field of suicide research is available to date. In other research areas, findings indicate that movement behavior is reactive in real-time studies. 28 Wearable use has been associated with reduced psychological distress (mediated by increased self-care and perception), 29 and positive affect. 30 In behavioral activation interventions, wearables have been perceived positively (e.g. increasing self-awareness) and negatively (e.g. being inconvenient or not interesting) by depressed individuals. 31 In addition, most study designs entail observation periods between a few days and 4 weeks,2,25 but data on the effects of studies with long observation intervals of weeks and months involving real-time assessments in populations at high risk of STBs is lacking. This stands in stark contrast to the fact that STB risk is heightened for several weeks or months after inpatient treatment, requiring long-term monitoring of STBs in persons at risk. 32 Moreover, available studies rarely focus on participant experiences of the frequent assessment of STBs and other items addressing affect, cognitions, or context. 14
To extend this limited evidence, further studies focusing on measurement reactivity of EMA in STB-related research are needed. Including the participant perspective is necessary in order to address ethical concerns regarding the burden on this vulnerable group and to understand potential limitations regarding the validity of EMA data. Hence, it is recommended to combine quantitative and qualitative methods, because quantitative indices, such as completion rate or mean level of assessed items, do not fully represent the experiences of participants. 14 In addition, several aspects such as positive or unexpected reactivity effects as well as changes in daily routines cannot be sufficiently captured by quantitative methods. 33
Objective and aims
The present study therefore sought to examine the experiences of individuals at high risk of STB during their participation in a study with a long observation interval employing data collection with EMAs and wearables. Specifically, we collected quantitative and qualitative data on measurement reactivity in a study consisting of two consecutive sampling periods (
The following research questions were addressed:
Ratings of reactivity:
Did the participants perceive changes in daily routines, mood, and contact with other people due to EMAs? Did the participants perceive changes in daily routines and physical activity due to the wearable use? Association of reactivity ratings with study and participant characteristics:
Did perceived reactivity differ according to the sampling scheme (EMA 1 or EMA 2)? Did participants with high compliance differ in their average perceived reactivity ratings compared to participants with low compliance? Participant experiences:
How many participants experienced or observed changes in their symptoms, mood and behavior during study participation? What sort of changes in their behavior or mood did the participants describe as a result of participating in the study? Did the experiences differ according to the sampling scheme (EMA 1 and EMA 2)? Would the participants participate again in a similar study?
Methods
Participants and procedure
The data was collected in the context of an ongoing multicenter study on risk factors for postdischarge STBs. Recruitment started in March 2022. By February 2024, N = 184 participants were included. All participants were recruited while they received inpatient psychiatric treatment. Inclusion criteria were being admitted due to suicide attempt/suicidal crisis, being aged 18 to 75 years, fluent in German and able to give informed consent. Exclusion criteria were admission due to other reasons, insufficient German language skills, acute psychosis, and cognitive impairment. Research staff regularly attended routine meetings in seven clinics in Leipzig and the Ruhr Area around Essen to identify inpatients fulfilling these criteria. Eligible inpatients were approached and informed about the study (see Figure 1 for participant flow). In case of inclusion, a baseline assessment was conducted. After that, participants were given a wearable (Polar Unite) and instructed to download a smartphone app on their private phones (Catalyst by Metricwire Inc.). The wearable was synchronized with the app. When the patients’ discharge from the psychiatric ward was scheduled, they informed the study team via the app about the date and were briefed about the EMA assessment/wearable use via telephone. During the briefing, participants were instructed on technical aspects of data collection (i.e. wearing and regularly charging the Polar Unite; use of the app, battery status, …), guidelines for the EMA survey (i.e. responding promptly, relevance of high response rate, and incentives) as well as on safety procedures (i.e. in-app emergency contacts, drop-out in case of severe symptom increase because of the repeated assessments). EMA 1 (high frequency) started 1 to 3 days prior to discharge and ran between 21 to 24 days. Participants received a morning questionnaire at 8:00 am and four semirandom prompts (main survey) between 8:00 am and 10:00 pm per day (minimum interval of 120 minutes between prompts). The morning questionnaire included three items on sleep and the main survey 31 to 33 momentary items that could be responded to in 1 to 3 minutes. EMA 2 (low frequency) followed EMA 1 and lasted for 26 weeks. During EMA 2, participants received the same 31 to 33 items of the main survey on two randomly chosen consecutive days per week. EMA surveys were accessible for 20 minutes and expired if they had not been started. Once started, the surveys had to be completed within 10 minutes. In EMA 1 and EMA 2, participants were reminded via push-notifications to put on the wearable in the morning and to synchronize and load the device in the evening. After EMA 1 and EMA 2, the study team conducted a clinical interview via telephone (including a short debriefing). EMA compliance rates were accessible to participants in the app. In addition, compliance rates were regularly monitored by the study team during the entire sampling period. Participants received feedback on their compliance via push notifications once a week in EMA 1 and every 2 weeks in EMA 2. In case of a substantial decrease of compliance or nonresponse, the participants were contacted to check if any technical issues had evolved (e.g. app updates, smartphone loss/change). Participants received up to 150 euros for their participation (depending on the compliance rates as well as completion of the interviews during the EMA 1 and EMA 2 period).

Study flow. Notes: T0 = baseline assessment following inclusion, T1 = interview via telephone 21 to 24 days after discharge, T2 = interview via telephone 6 months after discharge.
For the present analysis, data of those participants, who had either finished EMA 1 or EMA 1 and EMA 2 and took part in an extensive debriefing session held in February 2023 (see Figure 1) were analyzed. Debriefing data is available for
Sociodemographic and clinical characteristics.
All diagnoses drawn from the medical records at the psychiatric wards.
The responsible ethics committees at the two study sites approved the study protocol (University of Leipzig/Medical Faculty no. 382/17-ek and University of Duisburg-Essen no. EA-PSY19/23/03102023). All participants gave written informed consent prior to participation. For a detailed description of the study procedure, as well as full list of EMA items see https://osf.io/axnws.
Measures
In the debriefings after EMA 1 and EMA 2, participants were invited to share their experiences and thoughts on study participation using several quantitative items and open questions. The debriefings were conducted via telephone and all questions were self-designed by the study team. The study staff recorded all answers in writing. Items and questions are available in the supplementary material. In the present analysis, we considered those items asking about the impact of the EMA survey and of the wearable on daily routines, mood, social contacts, and physical activity, respectively. Participants were asked to rate the reactivity impact (“
EMA data was preprocessed following the recommendations and template of Revol et al.
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(see https://osf.io/25utw/ for the preprocessing report). Compliance rates were separately calculated for EMA 1 and EMA 2. In EMA 1, participants received up to 96 prompts. The average compliance was 57.4% in EMA 1 (range 0.1% to 100%,
Statistical analyses
Results
Impact ratings of EMA surveys and wearable use on mood, daily routines, and physical activity
Participants, on average, reported no perceived change due to the high-frequency EMA assessments on their daily routines, mood, and contact in the EMA 1 phase. Mean ratings were close to zero for all items. If at all, a slightly negative impact on mood was perceived across all participants (see Table 2). As for the perceived change due to the wearable use on daily routines and physical activity, participants reported slightly positive changes with regard to average mean values.
Impact ratings of EMA surveys and wearable.
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In the EMA 2 phase, participants reported no to slightly positive perceived changes due to the prompts on routines, mood, and contact as well as slightly positive perceived changes of the wearable use on daily routines and activity (see Table 2).
Differences between participants with high versus low compliance
There was no difference in perceived changes between participants with high versus low compliance in EMA 1. Participants with high compliance in EMA 2 rated the perceived changes due to the wearable use on routines and physical activity significantly more positively than participants with low compliance rates (see Table 2).
Participant experiences
The inductively developed categories addressed different domains (e.g. STBs, mood, cognitive processes such as rumination and introspection, behavioral changes) and directions of perceived changes (i.e. worsening or improving) (see Table 3).
Changes after EMA 1 and EMA 2 according to subcategories.
Categories were developed using consensual coding via content-structuring qualitative content analysis (Kuckartz, 2012).
EMA 1
When asked if they had experienced any changes in their behavior or mood as a result of taking part in EMA 1 (
EMA 2
After EMA 2, participants were asked again whether they had experienced any changes in their behavior or mood as a result of taking part in the study (
Future study participation
In the telephone interview following EMA 2, participants tended to indicate they would participate in a comparable study again (on a scale from 1 = definitely to 7 = not at all;
Discussion
The present study sought to investigate the impact and experiences of patients at high risk of STB participating in a study with 6 months observation period incorporating EMA as well as wearables. It led to three key findings: (1) the perceived impact of the EMA surveys and the wearable on mood, daily routines, or social contacts based on participants’ reactivity ratings was small (irrespective of low vs. high sampling density and study duration). In contrast, the wearable use had a (positive) impact; (2) when asked with an open question, about two-thirds of participants reported individual changes (both positive and negative) due to study participation but would on average participate in comparable studies in the future; (3) quantitative and qualitative indicators provided diverging information and should be combined in studies examining measurement reactivity. In the following, we will address these findings in more detail and highlight strengths and limitations of the analysis.
Impact on mood, routines, and social contacts/physical activity
The reactivity ratings show that neither daily routines nor social contacts appear to be influenced by the prompts in EMA 1 and EMA 2. Only mood appears to be slightly negatively influenced by the prompts in EMA 1 (but not in EMA 2). Overall, these results suggest that measurement reactivity in terms of behavioral changes or worsening of mood seems to be negligible, if participants are asked to rate the perceived impact of the EMA survey retrospectively. This is in line with other studies looking into affective reactivity.14,18,20 However, two aspects should be viewed critically. First, the bipolarity of the ratings might pose difficulties to the participants experiencing
Associations with study and participant characteristics
The findings did not generally differ between the high- versus low-frequency sampling scheme/duration of EMA 1 and EMA 2. Out of all possible outcomes, mood appeared to be perceived the most reactive with prompts that are more frequent. The compliance (high vs. low) of the participants was not significantly associated with the reactivity ratings of EMA prompts. It might, however, play a role that participants feeling most distressed or affected by the EMA surveys had a higher chance of dropping out of the study (i.e. did not participate in the follow-up and debriefing session, suggesting a general compliance bias 38 ). It has been shown that higher psychopathological symptom burden is associated with increased reporting of iatrogenic effects (EMAs triggering or worsening SI) 14 as well as with lower compliance and retention rates in general. 26 Since the available clinical diagnoses of the participants were reflecting the state at admission, we do not know which symptoms remained, remitted or re-occurred during the EMA phases and cannot test their association with perceived reactivity. It might be worthwhile for future studies to account for current symptom levels or additional engagement in treatment. However, participants with high compliance reported a positive impact of the wearable use on daily routines and physical activity. Most likely, getting feedback on physical activity level has led to a positive feedback loop and supported a positive reactivity effect related to the use of wearables for some participants. Getting individual feedback has been shown to increase engagement with the study 39 and is known to promote self-awareness. 12 The wearable might provide this opportunity (somewhat unintentionally). The functionalities of the device (e.g. indicators of activity or sleep) were accessible to the participants and might have been used by those generally showing interest in it. When participants perceive the use of the wearable as inconvenient or not interesting, 31 they might dismiss the wearable during the study or do not consent to wear it upon inclusion in the study. Indeed, 10.9% of participants decided against the use of the wearable. Again, participants with higher psychopathological symptom burden might be overwhelmed by regularly charging, wearing, and synchronizing the device or solving technical difficulties.
Participant experiences
At both follow-ups, about two-thirds of the participants indicated that they had experienced a change in their behavior or mood as a result of study participation. And 38% (34%) of participants were not aware of any changes in their behavior or mood at debriefing following EMA 1 (EMA 2). This rate is considerably lower than in previous studies (e.g. 60% reporting neither positive nor negative effects of EMA in reference [14]) One possible explanation is provided by the composition of our sample. In comparison to other EMA studies, we specifically recruited participants at high risk of STB. Since the level of psychopathological symptoms appears to influence affective reactivity, it is conceivable that severely burdened participants may experience the EMA as more stressful and burdensome than respondents in other studies (experiencing predominately SI, with lower rates of lifetime suicide attempts). 14 At EMA 1, a majority of participants described having experienced an improvement of introspection and self-reflection (63%), a worsening of mood (22%), or increased rumination (10%). At EMA 2, participants mainly reported having experienced an improvement of introspection and self-reflection (68%) and a worsening of mood (28%). The large proportion of participants who perceived an improvement in introspection and self-reflection during the study clearly represents reactivity as a result of participating in the study and has been shown before. 40 Individual quotes highlight that the increased awareness can be experienced both, as beneficial or burdensome by participants. With 22% to 28% of participants experiencing a worsening of mood, the results are in line with other studies reporting a share of 9% to 22% of participants feeling distressed or burdened by EMA.41,14,21,22 In addition, increased self-reflection my even increase the likelihood of reporting reactivity effects. Becoming more aware of one's own mood could lead to a higher sensibility for the detection of the effects of EMA (i.e. noticing mood changes when an EMA survey is prompted).
Even though these were only a few individual cases, some people (5%–6%) stated that participation in the study had led to a worsening of suicidal thoughts and behavior. EMA studies focusing on iatrogenic effects in the assessment of suicidal ideation and behaviors concluded that repeated questions about suicidal ideation do not increase their occurrence or intensity.19,18 However, in an EMA study across 21 days,
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as many as 18% of participants subsequently reported that the questions had triggered suicidal thoughts. Since individual participant experiences do not necessarily correspond to statistical models examining reactivity effects (i.e. by examining altered response patterns),2,33 it seems worthwhile to address both aspects in future research. Since different experiences in relation to reactivity can exist simultaneously, questions, and items intending to asses it should be designed very carefully. Since specifically in participants at high risk of STB, researchers should carefully balance the potential burden of study length and assessment intensity with the expected gain in knowledge. Besides the absence of empirically observed measurement reactivity in terms of symptom or mood worsening and no indication of relevant adaptions of daily routines based on quantitative data, EMAs over a long observation interval
Limitations and strengths
The study was not specifically designed to examine measurement reactivity and is thus explorative in nature. Reactivity was assessed using items and questions that were self-designed by the authors and have neither been pilot-tested nor validated before. The wording and the rating scale used could have affected the findings in the quantitative analysis (i.e. close to zero ratings in the items reflecting the participants’ efforts to convey mixed experiences in one score). Moreover, the relatively small sample size in the debriefings limits the power to detect effects. Most importantly, the drop-out of participants during the study represents a possible selection bias, that is, the participants experiencing the most positive or negative reactivity effects might have refrained from completing the study. For this reason we assume that reactivity might be underestimated in our study (as well as in other studies in the field) due to a compliance bias. 38 Accordingly, generalizability of the findings is limited. Since the reactivity ratings of the EMA prompts and the wearable as well as participant experiences were assessed retrospectively, recall biases might have confounded the findings.3,6 Future studies would benefit from prompt-based measures of reactivity, objective assessments of behavior and the inclusion of experiences from participants that had dropped-out of the study to enhance our understanding of these processes. The experiences of the participants were further not recorded verbatim, but documented by the study team and might have been shaped by their view and interpretation.
Beyond the limitations mentioned above, the study has some major strengths, for example, the combination of quantitative and qualitative data and the nature of the sample (i.e. representing a severely burdened clinical population with high risk of STB). To our knowledge, this study is the first that particularly focusses on the effects of EMAs and wearable use over weeks and months in a sample at high risk of STB and provides unique insights into measurement reactivity and participant experiences in this context.
Supplemental Material
sj-docx-1-dhj-10.1177_20552076251339265 - Supplemental material for Promising or discouraging? Potentials and reactivity of real-time data collection in monitoring suicide-related thoughts and behaviors over weeks and months. Participants’ views on ecological momentary assessments and wearable use
Supplemental material, sj-docx-1-dhj-10.1177_20552076251339265 for Promising or discouraging? Potentials and reactivity of real-time data collection in monitoring suicide-related thoughts and behaviors over weeks and months. Participants’ views on ecological momentary assessments and wearable use by Lena Spangenberg, Luise Böhler, Tina-Marie Hoke, Jana Serebriakova, Jannik Eimen, Thomas Forkmann, Maria Strauss, Katarina Stengler and Heide Glaesmer in DIGITAL HEALTH
Footnotes
Acknowledgements
ORCID iDs
Ethical considerations
Consent to participate
Author contributions
Funding
Declaration of conflicting interests
Data availability statement
Supplemental material
References
Supplementary Material
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