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      Refocusing of Attention on Positive Events Using Monitoring-Based Feedback and Microinterventions for Patients With Chronic Musculoskeletal Pain in the PerPAIN Randomized Controlled Trial: Protocol for a Microrandomized Trial

      research-article
      , MSc 1 , , PhD 1 , , PhD 2 , , PhD 2 , , MSc 3 , , MD 3 , , MSc 3 , , MSc 4 , , PsyD 2 , , PhD 4 , 5 , 6 , 7 , , MD 8 , , PhD 8 , , PhD, Dr hc 2 , , MD 3 , , PhD 1 , 9 , 10 ,
      (Reviewer), (Reviewer)
      JMIR Research Protocols
      JMIR Publications
      experience sampling method, ESM, ecological momentary intervention, EMI, microrandomized trial, mobile health, mHealth, positive intervention, complex intervention, mobile phone

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          Abstract

          Background

          Chronic musculoskeletal pain (CMSP) affects between 13% and 47% of the population, with a global growth rate of 20.3% within the last 15 years, suggesting that there is a high need for effective treatments. Pain diaries have long been a common tool in nonpharmacological pain treatment for monitoring and providing feedback on patients’ symptoms in daily life. More recently, positive refocusing techniques have come to be used, promoting pain-free episodes and positive outcomes rather than focusing on managing the pain.

          Objective

          This study aims to evaluate the feasibility (ie, acceptability, intervention adherence, and fidelity) and initial signals of efficacy of the PerPAIN app, an ecological momentary intervention for patients with CMSP. The app comprises digitalized monitoring using the experience sampling method (ESM) and feedback. In addition, the patients receive 3 microinterventions targeted at refocusing of attention on positive events.

          Methods

          In a microrandomized trial, we will recruit 35 patients with CMSP who will be offered the app for 12 weeks. Participants will be prompted to fill out 4 ESM monitoring questionnaires a day assessing information on their current context and the proximal outcome variables: absence of pain, positive mood, and subjective activity. Participants will be randomized daily and weekly to receive no feedback, verbal feedback, or visual feedback on proximal outcomes assessed by the ESM. In addition, the app will encourage participants to complete 3 microinterventions based on positive psychology and cognitive behavioral therapy techniques. These microinterventions are prompts to report joyful moments and everyday successes or to plan pleasant activities. After familiarizing themselves with each microintervention individually, participants will be randomized daily to receive 1 of the 3 exercises or none. We will assess whether the 2 feedback types and the 3 microinterventions increase proximal outcomes at the following time point. The microrandomized trial is part of the PerPAIN randomized controlled trial (German Clinical Trials Register DRKS00022792) investigating a personalized treatment approach to enhance treatment outcomes in CMSP.

          Results

          Approval was granted by the Ethics Committee II of the University of Heidelberg on August 4, 2020. Recruitment for the microrandomized trial began in May 2021 and is ongoing at the time of submission. By October 10, 2022, a total of 24 participants had been enrolled in the microrandomized trial.

          Conclusions

          This trial will provide evidence on the feasibility of the PerPAIN app and the initial signals of efficacy of the different intervention components. In the next step, the intervention would need to be further refined and investigated in a definitive trial. This ecological momentary intervention presents a potential method for offering low-level accessible treatment to a wide range of people, which could have substantial implications for public health by reducing disease burden of chronic pain in the population.

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          DERR1-10.2196/43376

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          Most cited references88

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          SPIRIT 2013 statement: defining standard protocol items for clinical trials.

          The protocol of a clinical trial serves as the foundation for study planning, conduct, reporting, and appraisal. However, trial protocols and existing protocol guidelines vary greatly in content and quality. This article describes the systematic development and scope of SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013, a guideline for the minimum content of a clinical trial protocol.The 33-item SPIRIT checklist applies to protocols for all clinical trials and focuses on content rather than format. The checklist recommends a full description of what is planned; it does not prescribe how to design or conduct a trial. By providing guidance for key content, the SPIRIT recommendations aim to facilitate the drafting of high-quality protocols. Adherence to SPIRIT would also enhance the transparency and completeness of trial protocols for the benefit of investigators, trial participants, patients, sponsors, funders, research ethics committees or institutional review boards, peer reviewers, journals, trial registries, policymakers, regulators, and other key stakeholders.
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            Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment.

            This large scale computer-assisted telephone survey was undertaken to explore the prevalence, severity, treatment and impact of chronic pain in 15 European countries and Israel. Screening interviews identified respondents aged 18 years with chronic pain for in-depth interviews. 19% of 46,394 respondents willing to participate (refusal rate 46%) had suffered pain for 6 months, had experienced pain in the last month and several times during the last week. Their pain intensity was 5 on a 10-point Numeric Rating Scale (NRS) (1 = no pain, 10 = worst pain imaginable) during last episode of pain. In-depth interviews with 4839 respondents with chronic pain (about 300 per country) showed: 66% had moderate pain (NRS = 5-7), 34% had severe pain (NRS = 8-10), 46% had constant pain, 54% had intermittent pain. 59% had suffered with pain for two to 15 years, 21% had been diagnosed with depression because of their pain, 61% were less able or unable to work outside the home, 19% had lost their job and 13% had changed jobs because of their pain. 60% visited their doctor about their pain 2-9 times in the last six months. Only 2% were currently treated by a pain management specialist. One-third of the chronic pain sufferers were currently not being treated. Two-thirds used non-medication treatments, e.g,. massage (30%), physical therapy (21%), acupuncture (13%). Almost half were taking non-prescription analgesics; 'over the counter' (OTC) NSAIDs (55%), paracetamol (43%), weak opioids (13%). Two-thirds were taking prescription medicines: NSAIDs (44%), weak opioids (23%), paracetamol (18%), COX-2 inhibitors (1-36%), and strong opioids (5%). Forty percent had inadequate management of their pain. Interesting differences between countries were observed, possibly reflecting differences in cultural background and local traditions in managing chronic pain. Chronic pain of moderate to severe intensity occurs in 19% of adult Europeans, seriously affecting the quality of their social and working lives. Very few were managed by pain specialists and nearly half received inadequate pain management. Although differences were observed between the 16 countries, we have documented that chronic pain is a major health care problem in Europe that needs to be taken more seriously.
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              Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults — United States, 2016

              Chronic pain, one of the most common reasons adults seek medical care ( 1 ), has been linked to restrictions in mobility and daily activities ( 2 , 3 ), dependence on opioids ( 4 ), anxiety and depression ( 2 ), and poor perceived health or reduced quality of life ( 2 , 3 ). Population-based estimates of chronic pain among U.S. adults range from 11% to 40% ( 5 ), with considerable population subgroup variation. As a result, the 2016 National Pain Strategy called for more precise prevalence estimates of chronic pain and high-impact chronic pain (i.e., chronic pain that frequently limits life or work activities) to reliably establish the prevalence of chronic pain and aid in the development and implementation of population-wide pain interventions ( 5 ). National estimates of high-impact chronic pain can help differentiate persons with limitations in major life domains, including work, social, recreational, and self-care activities from those who maintain normal life activities despite chronic pain, providing a better understanding of the population in need of pain services. To estimate the prevalence of chronic pain and high-impact chronic pain in the United States, CDC analyzed 2016 National Health Interview Survey (NHIS) data. An estimated 20.4% (50.0 million) of U.S. adults had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain, with higher prevalences of both chronic pain and high-impact chronic pain reported among women, older adults, previously but not currently employed adults, adults living in poverty, adults with public health insurance, and rural residents. These findings could be used to target pain management interventions. NHIS is a cross-sectional, in-person, household health survey of the civilian noninstitutionalized U.S. population, conducted by the National Center for Health Statistics (NCHS).* Data from the 2016 Sample Adult Core for adults aged ≥18 years (33,028; response rate = 54.3%) † were analyzed. Information about pain was collected through responses to the following questions: “In the past six months, how often did you have pain? Would you say never, some days, most days, or every day?” and “Over the past six months, how often did pain limit your life or work activities? Would you say never, some days, most days, or every day?” Chronic pain was defined as pain on most days or every day in the past 6 months, as recommended by the International Association for the Study of Pain, § modified to account for intermittent pain, and used in both the National Pain Strategy and National Institutes of Health Task Force on Chronic Back Pain ( 6 ). As suggested in the National Pain Strategy, high-impact chronic pain was defined as chronic pain that limited life or work activities on most days or every day during the past 6 months ( 5 ). The prevalence of chronic pain and high-impact chronic pain (both crude and age-adjusted, with 95% confidence intervals) were estimated for the U.S. adult population overall and by various sociodemographic characteristics. These characteristics, collected with the Family Core questionnaire, included age, sex, race/ethnicity, education level, current employment status, ¶ poverty status (calculated using NHIS imputed income files),** veteran status, health insurance coverage type (reported separately for adults aged <65 and ≥65 years), and urbanicity. All prevalence estimates met NCHS reliability standards. †† Because pain prevalence varies by age, age-adjusted estimates were used in comparisons of chronic pain and high-impact chronic pain between subgroups. Based on two-tailed Z-tests, all reported differences between subgroups are statistically significant (unless otherwise noted; p<0.05). Analyses were conducted using statistical software that accounts for the stratification and clustering of households in the NHIS sampling design. Estimates incorporated the final sample adult weights adjusted for nonresponse and calibrated to population control totals to enable generalization to the civilian noninstitutionalized population aged ≥18 years. In 2016, an estimated 20.4% of U.S. adults (50.0 million) had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain (Table), with higher prevalence associated with advancing age. Age-adjusted prevalences of both chronic pain and high-impact chronic pain were significantly higher among women, adults who had worked previously but were not currently employed, adults living in or near poverty, and rural residents. In addition, the age-adjusted prevalences of chronic pain and high-impact chronic pain were significantly lower among adults with at least a bachelor’s degree compared with all other education levels. TABLE Prevalence of chronic pain* and high impact chronic pain † among U.S. adults aged ≥18 years, by sociodemographic characteristics—National Health Interview Survey, 2016 Characteristic Chronic pain* High-impact chronic pain† Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Total 50,009,000 20.4 (19.7–21.0) 19.4 (18.7–20.0) 19,611,000 8.0 (7.6–8.4) 7.5 (7.1–7.9) Age group (yrs) 18–24 2,082,000 7.0 (5.8–8.5) —** 446,000 1.5 (0.9–2.3) —** 25–44 11,042,000 13.2 (12.3–14.1) —** 3,681,000 4.4 (3.9–5.0) —** 45–64 23,269,000 27.8 (26.6–29.0) —** 10,044,000 12.0 (11.2–12.9) —** 65–84 11,808,000 27.6 (26.4–29.0) —** 4,578,000 10.7 (9.9–11.6) —** ≥85 1,766,000 33.6 (30.1–37.3) —** 830,000 15.8 (13.2–18.9) —** Sex Male 21,989,000 18.6 (17.7–19.5) 17.8 (17.0–18.7) 8,276,000 7.0 (6.5–7.6) 6.7 (6.2–7.3) Female 28,049,000 22.1 (21.2–23.0) 20.8 (19.9–21.6) 11,296,000 8.9 (8.4–9.4) 8.2 (7.7–8.7) Race/Ethnicity Hispanic 5,856,000 15.1 (13.6–16.7) 16.7 (15.2–18.4) 2,754,000 7.1 (6.0–8.3) 7.9 (6.9–9.2) White, non-Hispanic 36,226,000 23.0 (22.2–23.8) 21.0 (20.3–21.8) 13,230,000 8.4 (7.9–8.9) 7.4 (7.0–7.9) Black, non-Hispanic 5,148,000 17.9 (16.4–19.6) 17.8 (16.3–19.4) 2,387,000 8.3 (7.2–9.4) 8.1 (7.1–9.2) Other, non-Hispanic†† 2,774,000 13.8 (12.1–15.7) 14.4 (12.7–16.3) 1,326,000 6.6 (5.3–8.1) 7.0 (5.7–8.5) Education Less than high school 7,809,000 26.1 (24.2–28.2) 23.7 (21.7–25.7) 4,069,000 13.6 (12.3–15.2) 12.1 (10.7–13.7) High school/GED 14,441,000 23.7 (22.5–25.0) 22.6 (21.2–23.9) 5,910,000 9.7 (9.0–10.6) 9.1 (8.4–10.0) Some college 17,129,000 22.6 (21.5–23.8) 22.9 (21.8–24.0) 6,518,000 8.6 (7.9–9.4) 8.7 (8.0–9.5) Bachelor's degree or higher 10,383,000 13.4 (12.6–14.3) 12.4 (11.7–13.3) 2,944,000 3.8 (3.4–4.3) 3.5 (3.1–4.0) Employment status Employed 22,085,000 14.7 (14.1–15.5) 14.5 (13.8–15.2) 5,108,000 3.4 (3.1–3.8) 3.2 (2.9–3.6) Not employed; worked previously 25,737,000 31.5 (30.3–32.7) 29.2 (27.8–30.6) 13,318,000 16.3 (15.4–17.2) 16.1 (15.0–17.3) Not employed; never worked 2,083,000 15.9 (13.8–18.2) 18.7 (16.1–21.6) 1,192,000 9.1 (7.6–10.9) 11.1 (9.1–13.4) Poverty status <100% FPL 8,017,000 25.8 (24.2–27.6) 29.6 (27.9–31.3) 4,630,000 14.9 (13.6–16.4) 17.5 (16.1–19.0) 100% ≤FPL<200% 11,357,000 26.2 (24.5–27.9) 25.9 (24.2–27.7) 5,375,000 12.4 (11.3–13.6) 12.3 (11.2–13.5) 200% ≤FPL<400% 14,181,000 20.3 (19.2–21.4) 19.3 (18.3–20.4) 5,100,000 7.3 (6.7–8.1) 6.9 (6.2–7.6) ≥400% FPL 16,441,000 16.3 (15.4–17.2) 14.6 (13.8–15.5) 4,438,000 4.4 (4.0–4.9) 3.9 (3.5–4.4) Veteran Yes 6,379,000 29.1 (27.1–31.2) 26.0 (23.5–28.7) 2,258,000 10.3 (9.1–11.8) 9.2 (7.7–11.1) No 43,519,000 19.5 (18.9–20.2) 19.0 (18.4–19.7) 17,407,000 7.8 (7.4–8.2) 7.5 (7.1–7.9) Health insurance coverage§§ Age <65 yrs Private 20,539,000 15.1 (14.3–15.8) 14.0 (13.3–14.8) 5,713,000 4.2 (3.8–4.7) 3.8 (3.4–4.2) Medicaid and other public coverage 8,215,000 29.3 (27.3–31.5) 30.0 (28.0–32.2) 4,822,000 17.2 (15.6–19.0) 17.8 (16.2–19.6) Other 3,860,000 43.5 (40.0–47.2) 34.8 (31.2–38.7) 2,263,000 25.5 (22.5–28.8) 19.3 (16.4–22.5) Uninsured 3,683,000 16.2 (14.4–18.2) 17.0 (15.2–19.0) 1,319,000 5.8 (4.7–7.2) 6.2 (5.0–7.6) Age ≥65 yrs Private 5,606,000 28.0 (26.3–29.9) 28.1 (26.3–30.0) 1,842,000 9.2 (8.1–10.5) 9.3 (8.2–10.6) Medicare and Medicaid 1,428,000 42.5 (37.6–47.5) 42.5 (37.6–47.5) 816,000 24.3 (20.4–28.6) 24.3 (20.4–28.6) Medicare Advantage 3,094,000 25.5 (23.1–28.1) 25.8 (23.4–28.4) 1,226,000 10.1 (8.5–11.8) 10.3 (8.7–12.1) Medicare only, excluding Medicare Advantage 2,115,000 25.9 (23.1–28.9) 25.9 (23.1–28.9) 939,000 11.5 (9.5–13.7) 11.5 (9.5–13.7) Other 1,229,000 31.6 (27.2–36.3) 31.8 (27.4–36.5) 545,000 14.0 (11.3–17.3) 14.3 (11.5–17.7) Uninsured 106,000 —¶¶ —¶¶ 59,000 —¶¶ —¶¶ Urbanicity*** Urban 38,401,000 19.0 (18.3–19.7) 18.4 (17.7–19.0) 14,754,000 7.3 (6.9–7.8) 7.0 (6.6–7.4) Rural 11,575,000 26.9 (25.4–28.5) 24.0 (22.5–25.6) 4,776,000 11.1 (10.2–12.2) 9.8 (8.8–10.9) Abbreviations: CI = confidence interval; FPL = federal poverty level; GED = General Educational Development certification. * Pain on most days or every day in the past 6 months. † Chronic pain limiting life or work activities on most days or every day in the past 6 months. § The estimated numbers, rounded to 1,000s, were annualized based on the 2016 data. Counts for adults of unknown status (responses coded as “refused,” “don’t know,” or “not ascertained”) with respect to chronic pain and high-impact chronic pain are not shown separately in the table, nor are they included in the calculation of percentages (as part of either the denominator or the numerator), to provide a more straightforward presentation of the data. ¶ Estimates are age-adjusted using the projected 2000 U.S. population as the standard population and five age groups: 18–29, 30–39, 40–49, 50–59, and ≥60 years. ** Not applicable. †† Non-Hispanic other includes non-Hispanic American Indian and Alaska Native only, non-Hispanic Asian only, non-Hispanic Native Hawaiian and Pacific Islander only, and non-Hispanic multiple race. §§ Based on a hierarchy of mutually exclusive categories. Adults reporting both private and Medicare Advantage coverage were assigned to the Medicare Advantage category. “Uninsured” includes adults who had no coverage as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. “Other” comprises military health care including TRICARE, VA, and CHAMP-VA, and certain types of local and state governmental coverage, not including the Children’s Health Insurance Program. ¶¶ Estimates are considered unreliable according to the National Center for Health Statistics’ standards of reliability. *** Based on U.S. Census Bureau definitions of urban and rural areas (https://www2.census.gov/geo/pdfs/reference/ua/Defining_Rural.pdf). Whereas non-Hispanic white adults had a significantly higher age-adjusted prevalence of chronic pain than did all other racial and ethnic subgroups, no significant differences in high-impact chronic pain prevalence by race/ethnicity were observed. Similarly, the age-adjusted prevalence of chronic pain was significantly higher among veterans than among nonveterans, but no significant difference was observed in the prevalence of high-impact chronic pain. Among adults aged <65 years, the age-adjusted prevalences of chronic pain and high-impact chronic pain were higher among those with Medicaid and other public health care coverage or other insurance (e.g., Veteran’s Administration, certain local and state government) than among adults with private insurance or those who were uninsured. Among adults aged ≥65 years, those with both Medicare and Medicaid had higher age-adjusted prevalences of chronic pain and high-impact chronic pain than did adults with all other types of coverage. Discussion Pain is a component of many chronic conditions, and chronic pain is emerging as a health concern on its own, with negative consequences to individual persons, their families, and society as a whole ( 4 , 5 ). Healthy People 2020 (https://www.healthypeople.gov/), the nation’s science-based health objectives, has a developmental objective to “decrease the prevalence of adults having high-impact chronic pain.” This analysis extends previous national studies of chronic pain prevalence by identifying adults with high-impact chronic pain. In 2016, approximately 20% of U.S. adults had chronic pain (approximately 50 million), and 8% of U.S. adults (approximately 20 million) had high-impact chronic pain. This estimate of high-impact chronic pain is similar to or slightly lower than estimates reported in the few studies that have looked at pain using a similar construct. For example, a recent study that used a measure of high-impact chronic pain similar to the one used in this study reported an estimate of 13.7% among a sample of U.S. adult health plan enrollees ( 7 ). Similarly, a 2001 study of adults from a region in Scotland found that 14.1% of survey participants reported significant chronic pain, and 6.3% reported severe chronic pain, and a 2001 study of Australian adults reported that 11.0% of men and 13.5% of women reported chronic pain that interfered, to some degree, with daily life activities ( 3 , 8 ). The results of subgroup analyses in the current study were consistent with findings in these studies ( 3 , 8 ) insofar as the prevalence of high-impact chronic pain was higher among women, adults who had achieved lower levels of education, and those who were not employed at the time of the survey, and was lower among adults with private health insurance compared with public and other types of coverage. In addition, high-impact chronic pain was also found to be higher among adults living in poverty and among rural residents. Socioeconomic status appears to be a common factor in many of the subgroup differences in high-impact chronic pain prevalence reported here. Indicators of socioeconomic status such as education, poverty, and health insurance coverage have been determined to be associated with both general health status and the presence of specific health conditions ( 9 ) as well as with patients’ success in navigating the health care system ( 9 ). Identifying populations at risk is necessary to inform efforts for developing and targeting quality pain services. The findings in this report are subject to at least five limitations. First, data are self-reported and subject to recall bias. Second, data are cross-sectional, precluding drawing causal inferences. This might be particularly relevant for socioeconomic status, which can be both a risk factor for and a consequence of chronic pain or high-impact chronic pain, or both. Third, no information is available on treatment for chronic pain to assess the prevalence of chronic pain and high-impact chronic pain among those with and without treatment. Fourth, NHIS excludes important populations, such as active duty military and residents of long-term care facilities or prisons. And finally, NHIS does not collect data on chronic pain or high-impact chronic pain in children. Despite these limitations, three strengths of this study are that it used a large, nationally representative data source to produce estimates of chronic pain and high-impact chronic pain across many demographic subgroups, it used standard broad definitions of pain that were not limited to one or more specific health conditions (e.g., headache or arthritis), and it used the standard case definition for high-impact chronic pain proposed by the National Pain Strategy. Chronic pain contributes to an estimated $560 billion each year in direct medical costs, lost productivity, and disability programs ( 4 ). The National Pain Strategy, which is the first national effort to transform how the population burden of pain is perceived, assessed, and treated, recognizes the need for better data to inform action and calls for estimates of chronic pain and high-impact chronic pain in the general population ( 5 ). This report helps fulfill this objective and provides data to inform policymakers, clinicians, and researchers focused on pain care and prevention. Summary What is already known about this topic? Chronic pain has been linked to numerous physical and mental conditions and contributes to high health care costs and lost productivity. A limited number of studies estimate that the prevalence of chronic pain ranges from 11% to 40%. What is added by this report? In 2016, an estimated 20.4% of U.S. adults had chronic pain and 8.0% of U.S. adults had high-impact chronic pain. Both were more prevalent among adults living in poverty, adults with less than a high school education, and adults with public health insurance. What are the implications for public health practice? This report helps fulfill a National Pain Strategy objective of producing more precise estimates of chronic pain and high-impact chronic pain.
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                Author and article information

                Contributors
                Journal
                JMIR Res Protoc
                JMIR Res Protoc
                ResProt
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                1929-0748
                2023
                20 September 2023
                : 12
                : e43376
                Affiliations
                [1 ] Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University Mannheim Germany
                [2 ] Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University Mannheim Germany
                [3 ] Department of General Internal Medicine and Psychosomatics, Heidelberg University Heidelberg Germany
                [4 ] Data Analysis and Modeling, Mannheim Institute for Intelligent Systems in Medicine, Medical School Mannheim, Heidelberg University Mannheim Germany
                [5 ] Central Institute for Scientific Computing, Heidelberg University Heidelberg Germany
                [6 ] Central Institute for Computer Engineering, Heidelberg University Heidelberg Germany
                [7 ] CZS Heidelberg Center for Model-Based AI, Heidelberg University Heidelberg Germany
                [8 ] Interdisciplinary Center for Clinical Trials, Johannes Gutenberg University Medical Center Mainz Germany
                [9 ] Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London London United Kingdom
                [10 ] ESRC Centre for Society and Mental Health, King´s College London London United Kingdom
                Author notes
                Corresponding Author: Ulrich Reininghaus Ulrich.Reininghaus@ 123456zi-mannheim.de
                Author information
                https://orcid.org/0000-0001-8007-0153
                https://orcid.org/0000-0002-2043-0353
                https://orcid.org/0000-0003-0566-8002
                https://orcid.org/0000-0001-7337-2559
                https://orcid.org/0000-0002-2818-0088
                https://orcid.org/0000-0001-9337-0921
                https://orcid.org/0000-0002-0118-7124
                https://orcid.org/0000-0001-9718-2637
                https://orcid.org/0000-0003-2458-973X
                https://orcid.org/0000-0002-4001-1164
                https://orcid.org/0000-0002-7958-0161
                https://orcid.org/0000-0003-4823-0430
                https://orcid.org/0000-0003-4809-5398
                https://orcid.org/0000-0003-3268-7778
                https://orcid.org/0000-0002-9227-5436
                Article
                v12i1e43376
                10.2196/43376
                10551789
                37728983
                1450aaee-caeb-4c60-9cf8-ee72b4952940
                ©Leonie Ader, Anita Schick, Martin Löffler, Annette Löffler, Eva Beiner, Wolfgang Eich, Stephanie Vock, Andrei Sirazitdinov, Christopher Malone, Jürgen Hesser, Michael Hopp, Christian Ruckes, Herta Flor, Jonas Tesarz, Ulrich Reininghaus. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 20.09.2023.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                : 11 October 2022
                : 4 April 2023
                : 13 July 2023
                : 17 July 2023
                Categories
                Protocol
                Protocol

                experience sampling method,esm,ecological momentary intervention,emi,microrandomized trial,mobile health,mhealth,positive intervention,complex intervention,mobile phone

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