Table 1 Characteristics of studies using ecological momentary assessments to monitor health outcomes after injury

Albanese et al. 2021 [18]

Test whether distress intolerance predicted traumatic intrusions following a trauma film.

Prospective cohort study.

Florida, United States (unspecified date)

n = 70 aged ≥18 years with mild traumatic brain injury (mTBI) or anxiety sensitivity.

Interval.

1. 3 h after film;

2. 10 am, 3 pm, & 8 pm each day for 13 days after film.

1. Text messages with survey link to Qualtrics online survey.

N/A

1.Natualistic trauma intrusions.

2.Depression Anxiety & Stress Scale (DASS-21).

N/A

N/A

Betthauser et al. 2021 [19]

Assessed the feasibility of design elements of a yoga-based interventional trial for post-concussive headaches among Veterans with mTBI, as well as the acceptability of the intervention.

Randomised controlled acceptability and feasibility trial.

United States (2017–2019)

n = 27 to 54 Veterans aged ≥18 years with mTBI at various intervention stages.

Event.

1. Study follow-up visits at time 3, 4 & 5.

1. Either text message, web-based or pen & paper.

1. Brief Pain Inventory.

2. Headache Impact Test (HIT-6) impact of headaches on activities of daily living (ADL).

3. K Scale: Survey of Headache Impact (KS-SHI).

4. Short-Form McGill Pain Questionnaire (SF-MPQ).

5. Medication taken to treat headaches.

1. Neuro-behavioural Symptom Inventory (NSI).

2. Perceived Stress Scale (PSS).

1. Patient-Reported Outcomes Measurement Information System (PROMIS).

2. Short-Form Health Survey (SF-36).

3. Barriers & facilitators to activity participation.

4. Home yoga practice.

Facilitators:

1. Feasibility of web-based ecological momentary assessment (EMA) demonstrated.

2. Study results support the use of EMA procedures to track an intervention.

3. A modification to EMA facilitated the study team to contact and encourage participants.

Barriers

N/A

Forster et al. 2020 [20]

To establish the feasibility of using EMA (i.e., in terms of patients’ compliance) in patients with an acquired brain injury (ABI).

To map fluctuations in patients’ responses.

To determine whether patients’ compliance and their fluctuations in response behaviour were related to their level of functioning.

Prospective cohort pilot study

Germany (unspecified date)

n = 15 individuals with an ABI with cognitive and motor impairments.

Aged 18–70 years.

Random.

8 prompts per day for 7 days. Prompts were given between 8 am and 8 pm with at least an hour between prompts.

1. The software movisensXS, App version 1.3.0 via Android smartphones (Motorola Moto G, third generation)

N/A

1. Rasch-based Depression Screening using a five-point Likert scale.

2. Attention Network Test to assess attention and reaction time computer-based reaction time.

3. The Verbal Learning and Memory Test to measure declarative verbal memory, learning performance, long-term encoding, and recognition performance.

1. Ability to conduct 10 basic daily functions using the Barthel Index.

Facilitators

1. Patients’ compliance did not differ between weekdays and weekend.

2. Patients able to assess and monitor their own symptoms.

3. Ability for results to be shared with the treating clinician.

4. Sustains ecologically valid results.

Barriers

1. Compliance decreased with every passing testing day.

2. The higher frequency of EMA prompts correlated with lower compliance as burden increased.

3. Difficult to gauge how reliable and realistic the patients answers were.

4. Participant mood and emotion may have been influenced by high frequency of prompts.

5. The use of EMA might also be limited by other psychological factors such as social desirability and patients’ individual differences.

Hart et al. 2019 [21]

To describe and provide the rationale for a randomized controlled trial for depression or anxiety after moderate to severe TBI, which will test two treatments based on behavioural activation (BA).

Randomised controlled trial

United States (unspecified date)

n = 60 individuals with TBI that was sustained at least 6 months prior to enrolment.

Consciousness must be altered and depression and anxiety present.

Participants aged≥18 years.

Random.

5 times per day within a 14-h window for 8 weeks.

1. Collected via the LifeData System via RealLife Exp (a mobile app).

N/A

1. Emotional status/ behaviour - Global Severity Index of the Brief Symptom Inventory (BSI) -18, Environmental Reward Observation Scale (EROS), the Behavioral Activation for Depression Scale (BADS).

1. Participant Assessment with Recombined Tools-Objective (PART-O) to assess societal/ community participation.

2. Satisfaction with life Scale (SWLS).

3. Quality of life after brain injury (QOLIBRI).

4. Patient Global Impression of Change.

5. Cognitive/ functional status using Wechsler Abbreviated Scale of Intelligence.

6. Functional status - Extended Glasgow Outcome Scale.

Facilitators

1. The incorporation of commonly used technology in the form of smartphone apps has the potential to enhance the delivery of treatment in this population.

Barriers

N/A

Juengst et al. 2015a [22]

Juengst et al. 2019b [23]

A) Pilot feasibility and validity of a mobile health (mHealth) system for tracking mood-related symptoms after TBI.

B) To investigate within-person variability in daily self-reported emotional and fatigue symptoms and factors associated with high within person variability among individuals with chronic TBI.

A) Prospective cohort pilot study.

B) Secondary analysis of prospective cohort pilot study

United States (unspecified date)

A) n = 20 individuals with TBI and aged ≥18 years.

B) n = 18 adults with chronic TBI (2–27 years post-injury) who owned and could independently use an Apple or Android device.

Participants aged 22–60 years.

Interval.

Daily assessments for 8 weeks.

1. Conducted via mHealth system delivered through iPerform application.

N/A

1. Depressive symptoms using the Patient Health Questionnaire 2 (PHQ2).

2. Generalised Anxiety Disorders (GAD2).

3. Positive and Negative Affect Scale (PANAS).

4. Patient Health Questionnaire 9 (PHQ9).

5. Generalised Anxiety Disorders 7 (GAD7).

1. Impact of fatigue on daily life using a 7-point Likert scale

A) Facilitators

1. Participants showed good compliance and high satisfaction with the method of EMA.

2. Ecological valid results were demonstrated.

3. The simple interface on the app proved to be helpful with participants with TBI and could successfully complete assessments.

4. A schedule feature resulted in great compliance and satisfaction.

Barriers

1. Some participants frequently completed the wrong assessment.

2. Some participants completed too many assessments per day.

B) Facilitators

1. Feasibility of mobile phone-based EMA demonstrated.

2. Use of EMA may reduce misidentification of individuals with clinically significant symptoms.

3. Higher frequency repeated symptom assessment in a natural environment over a short period could provide a more valid measure of emotional symptoms and a better indicator of clinically meaningful change at the individual level.

Barriers

1. Single daily assessments may not be a valid representation of symptoms/ progression.

2. Method of self-reporting may contribute to variability.

Lenaert et al. 2019 [24]

1. To investigate the feasibility of using the experiencing sampling method (ESM) in individuals with ABI.

2. To explore the usability of ESM data on a clinical level by illustrating the interactions between person, environment, and affect.

Prospective cohort study.

The Netherlands

(July 2014–March 2015)

n = 17 individuals with ABI aged 18–65 years.

Random.

10 semi-random beeps throughout the day between 7.30 am and 10.30 pm for 6 days.

1. PsyMate (smart eHealth GmbH, Luxembourg) - a small electronic device with a touch-screen interface.

1. Physical well-being using a 7-point Likert scale.

1. PANAS.

2. Mood and self-esteem using a 7-point Likert scale.

1. Context and activities related questions using a multi-choice format.

2. Appraisal of context and activities using a bipolar scale ranging from −3 to + 3.

Facilitators

1. Data collection method had little interference on daily activities despite high volume of beeps.

2. User-friendly interface allowed for easy completion of assessments.

3. Familiarity with the questions over time reduced time and energy needed to answer them.

4. Data collection method had little influence on mood and feelings promoting ecological validity.

5. Users were able to monitor own progress and rehabilitation.

Barriers

N/A

Pavliscsak et al. 2016 [25]

1. To examine engagement with a mobile application (i.e. mCare) for wounded Veterans rehabilitating in their communities.

2. To examine associations between Veterans’ background characteristics and their engagement with mCare.

Prospective Randomised Controlled Trial

United States

(Unspecified specified)

n = 95 participants who received mCare. This included individuals with TBI (no distinction was made between those with TBI and those with other health issues).

Participants were aged ≥18 years.

Interval.

Daily assessment (unspecified time) for 36 weeks.

1. EMA delivered via the mCare mobile application.

2. Text messages to notify of new information on the mCare application.

N/A

N/A

1. General participation.

Facilitator

1. Findings suggest mCare can and will be adopted by Veterans in a community setting, even those with cognitive and emotional difficulties.

Barriers

1. Participants’ exposure to mCare declined systematically as Veterans out processed from rehabilitation.

Rabinowitz et al. 2020 [26]

To illustrate a novel framework for conceptualizing, collecting, and analysing concussion symptom data.

Prospective cohort pilot study

United States

(Unspecified date).

n = 10 recently concussed adolescents and young adults aged 15–35 years.

Interval.

Five assessments per day for 20 days. (morning, early afternoon, late afternoon, evening, and night)

1. Collected via the LifeData System (via RealLife Exp (a mobile app)).

N/A

N/A

1. 22-item Post-concussion Symptom Scale (PCSS).

N/A

Rabinowitz et al. 2021 [27]

To describe where, with whom, and how time was spent daily, and to characterise positive and negative affect, boredom, enjoyment, and perceived accomplishment as a function of time, activity, location, and social context, in people with chronic moderate-severe TBI and depression/anxiety.

Prospective cohort study.

United States

(5 April 2018–1 Feb 2020)

n = 23 individuals with TBI and at least mild depression or anxiety.

Mean age 47.7 years.

Random.

Notified 5 times in 14-h window for ~ 2 weeks.

1. Collected via the LifeData System (via RealLife Exp (a mobile app)).

N/A

1. Positive and Negative Affect using 20-item PANAS.

1. General well-being and activity using multi-choice.

2. Free-text responses were able to be provided for each question to qualify responses.

3. Activities in last hour recorded, including who primarily doing activity with.

Facilitators

N/A

Barriers

1. Closer monitoring with more proactive troubleshooting could have improved participants’ response rates.

Smith et al. 2012 [28]

To assess the utility of mHealth technologies, including personal digital assistant-based EMA and two-way interactive text (SMS) messaging, for providing treatment feedback to clinicians, encouraging and motivating Veterans throughout treatment, and monitoring participants for relapse after treatment discharge.

Prospective cohort pilot study

United States

(Unspecified date).

n = 27 male veterans suffering from PTSD and/or mTBI. Distinctions between those with PTSD from those with mTBI were not made.

Age unspecified.

Interval, Random and Event.

Active phase:

1. Daily assessment. Was initially randomised then at routine intervals.

Follow-up phase 3 months post-discharge:

1. Daily at either 9 am or 5 pm.

1. Electronic survey tool designed to support data collection via PDAs was used in active phase.

2. Assessments sent and completed via SMS (provided by LifeWIRE corporation) in follow-up phase

1. Level of pain using a 1–10 Likert scale.

2. Symptoms Checklist-6.

1. Depressive symptoms using BriefCOPE, and Beck Depression Inventory-II.

1. Types of hassles and uplifts.

2. General activities.

Facilitators

1. After data collection was changed from random to routine intervals, response rate improved.

Barriers

1. EMA at random times during waking hours was disruptive to participants’ schedules and led to low response rate.

2. Participants were resistant to carrying two electronic devices and routinely left their assigned PDA in the housing unit during the day, which contributed to the low EMA response rate.

3. The PDAs were viewed as being clunky and out of date compared with smart phones.

4. Participants indicated that they did not believe the data they were providing were doing any good because they could not see any effect on their treatment. On a few occasions participants temporarily ceased participating in EMA data collection after researchers and clinicians failed to respond to a stress or crisis event recorded in EMA data.

Suffoletto et al. 2013 [29]

To examine whether patients with mTBI receiving text message-based education and behavioural support had fewer and less severe post-concussive symptoms than those not receiving text messaging support, and determine the feasibility of using text messaging to assess daily symptoms and provide support to patients with mTBI.

RCT pilot

United States, (July–September 2012

n = 43 adults aged ≥18 years with mTBI.

n = 18 in intervention group and n = 25 in control group.

Interval.

Three daily questions at 9 am, 1 pm and 5 pm over

14 days

SMS messages.

1. Pain scale via have you had a headache in the last 24 h rating using 4-item Likert scale.

1. Difficulty concentrating in last 24 h rated using 4-item Likert scale.

2. Irritability or anxiety in last 24 h rated using 4-item Likert scale.

N/A

Facilitators

1. Provision of self-care support messages focused on symptom-specific education, reassurance, and management guidance lowered irritability or anxiety during the acute recovery period.

Barriers

N/A

Sufrinko et al. 2019 [30]

To evaluate mobile EMA as an approach to measure sport-related concussion symptoms, explore the relationships between clinical outcomes and mobile EMA, and determine whether mobile EMA was advantageous for predicting recovery outcomes compared to traditional symptom report.

Prospective cohort study.

United States

(September 2016 – December 2016)

n = 20 athletes aged 12–19 years with SRC.

Random.

Pseudo-randomised in 3 time blocks (i.e. Mon-Fri 7-8 am, 3-4 pm and 9-10 pm and Sat-Sun 9-10 am, 3-4 pm and 9-10 pm) daily for 4 weeks and clinical assessment at visit 1 and visit 2.

1. EMA surveys were administered via mobile EMA mobile application (Ilumivu, Inc).

2. The application utilized push notifications prompting the participant to open the application.

1. Vestibular/ Ocular Motor Screening rated using 0–10 Likert-scale assessing intensity for 4 symptoms (i.e. headache, dizziness, nausea, and fogginess).

1. Neurocognitive using the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT).

1. 22-item Post-concussion Symptom Scale (PCSS) rated using 7-point Likert scale.

Facilitators

1. Mobile EMA better predicted recovery time than Post-Concussion Symptom Scale (PCSS).

2. Mobile EMA data across recovery better predicted recovery duration compared with PCSS score at any clinic visit, but illustrated symptom patterns that may further inform clinical profiles and guide treatment recommendations.

Barriers

1. Participants were less likely to respond as days since injury increased.

2. Results reflected a diminishing response rate throughout the course of the study. May be due to:

a. Mobile EMA data collected for a longer duration than previous studies.

b. Intervals were less frequent than other studies that yielded higher compliance with more intervals.

c. Participants’ symptoms resolving and disinterest in completing mobile EMA.

Trbovic et al. 2021 [31]

To use actigraphy and mobile EMA to examine the relationship between sleep parameters and next day symptoms.

Prospective cohort study.

United States

(September 2016 – December 2016)

n = 17 athletes aged 12–19 years with recent concussion.

Interval.

Thee scheduled assessments per day within 1 h of prompt (i.e. morning – 7 am school days and 9 am weekends, afternoon – 3 pm, evening – 9 pm). By fourth week around half the participants had recovered, and sample size was underpowered beyond 3 weeks post-injury.

1. EMA surveys were administered via mobile EMA mobile application (Ilumivu, Inc).

2. The application utilized push notifications prompting the participant to open the application.

3. Participants wore an Actigraph GT3x + on their nondominant wrist for 24 h per day.

1. Somatic symptoms using PCSS and 7-point Likert scale.

1. Affective symptoms using PCSS and 7-point Likert scale.

1. PCSS to capture symptom intensity, including sleep-related symptoms.

2. Sleep and activity were measured by the Actigraph GT3x + .

3. Sleep-related symptoms rated using 7-point Likert scale.

N/A

Wiebe et al. 2016 [32]

To determine the feasibility of EMA following youth concussion, gather real-time reports of cognitive and physical activity, and compare objective measures with real-time reported symptoms among youths during recovery after concussion.

Prospective cohort pilot study

United States.

(Unspecified date).

n = 34 recently concussed adolescents aged 11–19 years.

Random.

Several random prompts daily for approximately 2 weeks after their initial office visit.

1. Participants wore an accelerometer2. iPod Touch (Apple) loaded with an app that gave random prompts

N/A

1. Daily cognitive rest and exertion were measured as number of text messages sent, minutes of screen time and gaming and minutes of reading or school work.

1. PCSS.

2. Activity questionnaire

Facilitators

1. Ecological validity was shown.

Barriers

N/A

Worthen-Chaudhari et al. 2017 [33]

To evaluate whether a mobile health application that employs elements of social game design could compliment medical care for unresolved concussion symptoms.

Prospective cohort study.

United States

(Phase I – 13 Aug 2014–7 Jan 2015; Phase II – 7 Jan 2015–4 Nov 2015)

Phase I n = 20; Phase II n = 19 adolescents aged 13–18 years, with concussion symptoms ≥3 weeks post-injury.

Event.

Participants asked to log activity at the frequency of one logged activity per day for 5 days each week, for a target of 15 logged activities over the first 3 weeks between pre-and post-test.

1. EMA conducted via a mobile application - SuperBetter.

1. Depression, measured by the Center for Epidemiological Studies–Depression Child (CES-DC)

1. Optimism, measured by the Life Orientation Test-Revised (LOT-R)

1. Severity of 22 Concussion symptoms using Sports Concussion Assessment Tool-3 (SCAT-3) checklist.

Facilitators

1. Youth were able to use the SuperBetter app in conjunction with traditional medical care for post-concussive symptoms and were satisfied with use of the app.

2. Participants who used the app to complement medical care had more relief from concussion symptoms than those who had traditional medical care alone.

3. The gameful and/or social interactive design of SuperBetter was effective to improve optimism.

4. Patients able to assess and monitor their own symptoms.

Barriers

N/A

Carlozzi et al. 2018 [34]

Investigated the most efficient means of measuring pain intensity and pain interference comparing EMA to end of day (EOD) data, with the highest level of measurement reliability as examined in individuals with spinal cord injury (SCI).

Prospective observational study.

United States (unspecified date)

n = 131 individuals with SCI aged ≥18 years. Participants also required to endorse ≥4 out of 10 average pain.

Interval.

1. Five times throughout the day (upon waking, 11 am, 3 pm, 7 pm, and bedtime)

1. Wrist-worn accelerometer enhanced with a user interface for entry of self-report data (i.e. the PRO-Diary; CamNTech, Cambridge, UK).

1. Pain 5-point Likert scale.

2. PROMIS pain intensity.

3. SCI-QOL pain interference.

4. 10-item short form pain interference

5. Pain interference 5-point Likert scale.

N/A

N/A

Facilitators:

1. EMA is easy to complete as responses are less reliant on memory.

2. The timing of EMA assessments does not impact reliability.

Barriers:

1. EMA requires more sophisticated analytical hardware for monitoring and data capture.

2. EMA is potentially a time burden for study participants.

3. The presence of a floor effect for EMA pain interference presented an analytical challenge in our data.

4. Calibration data may over- or under-estimate the pain ratings of participants in this study.

5. Pain in SCI is multifaceted, and thus ratings of pain intensity do not capture the full breadth of the pain experience in individuals with SCI.

Carlozzi et al. 2021 [35]

Examined the effect of sleep quality on same day Health Related Quality of Life (HRQoL).

Prospective cohort study.

United States (unspecified date)

n = 170 individuals with SCI aged ≥18 years

Interval.

1. Three times a day (i.e. morning, afternoon, evening) for 7 days.

1. Smart phone or paper diary.

2. E4 wristband (Empatica) recorded heart rate variability, electrodermal activity, body movement (accelerometer data), & skin temperature.

1. Pain 10-point Likert scale.

2. PROMIS pain intensity.

3. PROMIS pain interference.

1. Thinking 10-point Likert scale.

2. PROMIS cognitive function abilities.

3. PROMIS depression.

4. PROMIS anxiety.

1. Fatigue 10-point Likert scale.

2. PROMIS sleep disturbances.

3. PROMIS sleep-related impairment.

4. PROMIS fatigue.

5. PROMIS ability to participate in social roles and activities.

Facilitators:

1. Does not take very long for participants to habituate to a monitoring device (i.e. E4).

2. Ability to examine temporal relationships among symptoms.

3. Data collection minimises recall bias.

4. Maximises ecological validity of responses.

Barriers:

1. The E4 wristband does not have established algorithms for evaluating sleep in the general population or in individuals with SCI.

2. Self-reported sleep quality and objective sleep measured by E4 was not consistent – potentially due to lack of established sleep algorithms for E4 and/or challenges for a wrist-worn device in capturing information on sleep for a SCI population with limited mobility and neurophysiological challenges.

3. EMA is a relatively intense data collection procedure that can be burdensome on the participant.

4. Potential for individuals to change behaviour when they are being monitored.

Kratz et al. 2017a [36]

Kratz et al. 2017b [37]

Kim et al. 2020c [38]

A) To examine whether pain acceptance moderates the momentary associations of pain intensity with pain interference and physical activity in people with chronic pain and SCI.

B) To examine study compliance, protocol acceptability, and reactivity of intensive data collection methods in adults with chronic pain and SCI.

C) To examine the moderating effect of within- and between-person pain acceptance on associations between pain and physical and psychosocial functioning.

A) Prospective observational cohort study.

B) Secondary analysis of prospective observational cohort study.

C) Secondary analysis of prospective observational cohort study.

A) United States

(June 2014–January 2016)

n = 128 individuals with chronic pain and SCI aged ≥18 years.

Interval and event.

1. Five times throughout the day for a week (upon waking, 11 am, 3 pm, 7 pm, and bedtime)

1. A wrist-worn accelerometer called the (PRO-Diary).

2. EOD electronic diaries (online collection site).

1. Average physical activity per minute.

2. Brief Pain Inventory on 10-point scale.

3. Chronic Pain Coping Inventory-42 (CPCI).

4. Chronic Pain Acceptance 8 (CPAQ8).

5. Pain Catastrophizing using the catastrophizing subscale from the Coping Strategies Questionnaire.

6. Spinal Cord Injury – Quality of Life (SCI-QOL).

1. Depressive symptoms using the PHQ-9.

1. Ability to Participate in Social Roles and Activities using 6 items from the SCI-QOL v1.

2. Positive Affect and Well-Being using the SCI-QOL v1.0.

3. Mobility assessed using the Basic Mobility items in the Spinal Cord Injury-Function Index.

A)

Facilitators

1. Dynamically demonstrates ecological validity.

2. Combination of objective and subjective measures reduced problems related to overlapping method variance.

B)

Facilitators

1. EMA ratings were completed on a wrist-worn monitor that was constantly accessible.

2. Audible cue prompted the participant to enter data which increased midday compliance.

3. Compliance stayed consistent over the 7-day period.

4. Technologies were not cumbersome and allowed for easy completion of assessment.

Barriers

1. User error or internet connection difficulties interfered with completion of assessments.

2. It was more difficult for subjects to enter ratings during busy wake and bed-time routines, which, for people with SCI, often involve lengthy and assisted self-care routines (e.g. bowel and bladder care).

C) Facilitators

1. Daily assessments captured daily fluctuations in pain-related variables.

2. Ecological validity is demonstrated.

Barriers

1. Subjective daily measures may be inaccurate.

2. Measuring pain-related variables at the end of the day, prevented consideration of within-day variability.

Todd et al. 2018a [39]

Todd et al. 2019b [40]

A) To utilize EMA to measure intra-individual diurnal variations in neuropathic pain and effect on exercise and non-exercise days.

B) To describe strategies necessary to adapt EMA to measure neuropathic pain in adults with SCI, and explore participant perceptions of using EMA to measure pain sensations.

A) Prospective cohort study.

B) Secondary analysis of prospective cohort study.

Canada

(Unspecified date)

n = 6 physically active men with SCI greater than 1 year post-injury with low neuropathic pain.

Participants aged 27–50 years

Random.

A total of 6 prompts per day, over 6 days.

1. EMA surveys were administered via mobile EMA mobile application (Ilumivu, Inc).

2. The application utilised push notifications prompting the participant to open the application.

3. Fitbit Surge wrist-worn heart rate (HR) monitors were worn by participants to collect HR data.

1. Modified Neuropathic Pain Scale rated using 10-item Likert scale.

1. 11-point, single item Feeling Scale (FS) measured affect.

2. Felt Arousal Scale (FAS) measured arousal.

1. Heart rate captured using the Fitbit surge HR monitor.

A)

Facilitators

1. Little missing data and no participant dropout.

2. The measurement schedule was not cumbersome, and therefore minimized the probability of reduced data quality and quantity.

Barriers

1. Pain may have been exacerbated due to repeatedly asking participants to think about their pain levels.

B)

Facilitators

1. Participants provided positive responses regarding the practicality and usefulness of EMA to accurately capture their neuropathic pain experience.

2. Ecological validity was demonstrated.

3. Participants appreciated minimal morning/ night-time interference.

4. Random EMA allowed for the dynamic phenomenon of neuropathic pain to be captured, while minimizing daily interference to participants.

5. The 6-day protocol could partially explain participants’ support for six assessments per day as the protocol length may have reduced the overall burden experienced by participants.

6. Easy user interface allowed for participants’ positive observations related to the “quick” nature of assessments.

7. Use of notifications to prompt participants was viewed as useful.

Barriers

1. Participants reported that receiving multiple EMA prompts negatively influenced their neuropathic pain perception.

Gonzalez-Borato et al. 2021 [41]

To evaluate Psixport’s ability to gather real-time information about injured athletes’ psychological responses during the rehabilitation, to test the users’ perceived usability of Psixport, and to compare the reliability and differences between real-time data gathered with Psixport and the data gathered through the one-time retrospective method.

Prospective cohort feasibility study

Spain (unspecified date)

n = 28 severely injured athletes that require surgery and have a rehabilitation prescription therapist after surgery.

Participants aged≥18 years.

Event.

Daily after completing rehab session for 15 days.

1. Questionnaires completed on Psixport app via mobile phones.

1. Two questions from the Universal Pain Assessment Tool were included in Wong-Baker’s Faces Pain Rating Scale format

1. An adaptation of the picture-oriented Self-Assessment Manikin to assess emotional valence and arousal.

2. Behavioural Responses captured using Sports Injury Rehabilitation Adherence Scale (SIRAS).

1. Psychological Responses to Sports Injury Inventory (PRSII) assessed cognitive appraisals regarding injuries on 6 dimensions: devastation, dispirited, re-organisation, feeling cheated, restlessness, and isolation.

Facilitators

1. Users found interface app interface simple and easy.

2. Relatively short questionnaire length allowed for commitment by participants.

3. Ecological validity and validity of responses maximised.

4. Users were able to monitor own progress and rehabilitation.

Barriers

1. Compliance reduced with each passing day.

Pacella et al. 2018 [42]

To examine changes in post- concussive symptoms (PCS) over the acute post-injury recovery period, focusing on how daily PCSs differ between mTBI and other injury types.

Prospective cohort study.

United States

(April 2013 – March 2014)

n = 108 adults with traumatic injury aged ≥18 years.

Interval.

3 times per day (9 am, 1 pm, 5 pm) for 14 days. Different symptoms (i.e. somatic, cognitive, emotional) were assessed at each interval.

1. Assessments sent and completed via text message.

1. Somatic measures (i.e. headaches) using a 5-point scale of headache intensity.

1. Cognitive difficulty measures (i.e. concentration) using a 5-point scale.

2. Emotional anxiety and irritability using a 5-point scale.

N/A

Facilitators

1. Simple technology and using text-message allowed for easy completion for participants.

Barriers

1. There may be reporting and recall biases associated with the EMA pattern.

Pacella et al. 2018 [43]

To apply ESM via daily text messaging to monitor and detect relationships among psychosocial factors and post-injury pain across the first 14 days after emergency department (ED) discharge.

Prospective observational cohort study.

United States

(January 2016 – May 2017)

n = 75 adults with a trauma-related injury aged 18–60 years.

Interval.

Five assessments at 5 pm for 14 days.

1. Five assessments sent and completed via text message.

1. Pain rated on a 1–10 Likert scale.

1. Hyperarousal rated on a 1–7 Likert scale.

1. Social support rated on a 1–7 Likert scale.

2. Intrusions rated on a 1–7 Likert scale.

3. Avoidance rated on a 1–7 Likert scale.

Facilitators

1. ED patients were receptive to the manner of which assessments were conducted.

2. High compliance rate despite relatively high volume of text messages.

Barriers

1. Validity was limited as assessment was completed once per day.

Price et al. 2014 [44]

To determine the proportion of trauma patients that would consent to receiving daily text messages assessing mental health, determine response rates to daily text messages among trauma patients, identify predictors of higher rates of responding, assess patient satisfaction, and determine provider burden.

Prospective cohort pilot study

United States

(Unspecified date)

n = 29 individuals with a traumatic injury.

Mean age of 37.1 years.

Interval.

A daily assessment for 15 days.

One and three month follow-up.

1. Assessments sent and completed via text message.

1. Pain rated using a 1–10 Likert scale

1. Hypervigilance rating using a 1–7 Likert scale.

2. Avoidance rated using a 1–7 Likert scale

3. Re-experiencing rated using a 1–7 Likert scale.

1. Social support rated using a 1–7 Likert scale

Facilitators

1. Text messages are an efficient method of implementing a “watchful waiting” program after a traumatic event.

Barriers

1. Technical difficulties reported as the primary reason for non-response.

Price et al. 2017 [45]

To evaluate the use of a mobile phone application to collect symptom data during the acute post-trauma period.

Prospective cohort study.

United States

(Unspecified date)

n = 23 individuals with traumatic injury.

Mean age of 27.6 years.

Random.

Daily assessments between 7 am-8 pm for 30 days.

One and three month follow-up.

1. Conducted via mobile application, Metricwire (Waterloo, ON).

2. Follow-up interviews were conducted via telephone.

1. Pain rated using a 1–10 Likert scale

1. Arousal rated using a 1–7 Likert scale.

2. Avoidance rated using a 1–7 Likert scale

3. Re-experiencing rated using a 1–7 Likert scale.

4. Free-text response to what concerned them most that day.

1. Sleep rated using a 1–7 Likert scale.

Facilitators

1. The use of mobile devices to monitor symptoms presents a low-burden and low-cost method with substantial reach to learn about recovery.

2. Most participants felt that 1 survey per day was appropriate.

3. Participants stated that the notifications to complete tasks were helpful.

4. Ease of use of the interface, familiarity with the mobile device, and brevity of the survey allowed for easy completion of survey.

5. Using an individual’s personal device significantly reduced the cost associated with conducting studies or delivering intervention.

Barriers

1. Participants may have preferred an opportunity to respond more frequently but did not feel an overwhelming obligation to do so.

2. Participants found the inclusion of the same questions in each survey repetitive, which may have diminished their willingness to respond to subsequent assessments.

3. Participants requested personalized questions and personalized feedback for a better experience.

4. Responding to assessments via a mobile device may be burdensome to the patient and might result in noncompliance.

Price et al. 2018 [46]

To evaluate the acceptability of administering PTSD symptom assessments via a mobile application throughout the acute post-trauma period.

Prospective cohort study

United States

(Unspecified date)

n = 90 individuals with traumatic injury (n = 1 participant was injured following a physical assault).

Mean age of 35.1 years.

Random.

Daily assessments between 7 am-8 pm for 30 days.

One and three month follow-up.

1. Conducted via mobile application, Metricwire (Waterloo, ON).

1. Pain rated on a 1–10 Likert scale.

1. Post- Traumatic Stress Disorder (PTSD) checklist-5 (PCL-5) to assess PTSD symptoms (8-items).

2. Free-text response to what concerned them most that day.

1. Sleep assessment using PCL-5.

Facilitators

1. Assessments were perceived as moderately helpful and minimally burdensome.

2. Demonstrates possibility to obtain free response and Likert scale response via EMA.

Barriers

1. A subset of participants may not complete daily assessments due to technical difficulties or a lack of interest.

2. Variability in response time. Many took advantage of the 14-h response window.