Physical activity and psychosocial characteristics of individuals with and without chronic low back pain in daily life: A study protocol for the PRIA intensive longitudinal study

Physical activity and psychosocial characteristics of individuals with and without chronic low back pain in daily life: A study protocol for the PRIA intensive longitudinal study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Study protocol Physical activity and psychosocial characteristics of individuals with and without chronic low back pain in daily life: A study protocol for the PRIA intensive longitudinal study Karolina Kolodziejczak-Krupp, Valerie Zipper, Lea O. Wilhelm, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5965211/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Despite the high prevalence of chronic low back pain (cLBP), its underlying mechanisms remain poorly understood. Addressing modifiable psychosocial resources and health behaviors such as physical activity offers a promising avenue for reducing the impact of cLBP. Furthermore, although the relationship between physical activity and pain is theorized as a within-person process, previous research has primarily focused on between-person differences. In this article, we present the protocol for the prospective observational study PRIA (Psychologie und Rückengesundheit im Alltag), which is part of a larger interdisciplinary research consortium investigating preventive, diagnostic and therapeutic aspects of cLBP. Drawing on theories from health and pain psychology, the outlined study examines the interplay between different dimensions of cLBP and back health, physical activity and their psychosocial determinants within individuals in their everyday lives. Methods: This prospective longitudinal study combines online questionnaires with Ecological Momentary Assessment (EMA) of health behaviors, cognitions, affect, social support, and pain using a smartphone-based app (movisensXS) and continuous measurement of physical activity by accelerometry (movisens Move 4). Parameters will be recorded at baseline (T0), daily for the following 14 days, 3 and 6 months later (T1 and T2). A total of 230 participants (115 individuals with cLBP and 115 without cLBP) aged 18 to 64 years will be enrolled. The associations between cLBP and the measured parameters will be examined using multilevel models. Discussion: The use of ambulatory assessment to examine physical activity, psychosocial factors, back health and pain in individuals’ daily lives addresses the limitations of previous research based on cross-sectional designs. This approach is expected to provide novel insights into the intraindividual and temporal dynamics of pain, back health, physical activity and psychosocial risk factors and resources. These findings are expected to contribute to the development of improved diagnostics, recommendations and interventions that leverage advances in mobile technology for more personalized and effective prevention and healthcare solutions. Trial registration: This trial is registered in the German Clinical Trials Register, DRKS-ID DRKS00032978. Date of registration: 22 December 2022. Ecological Momentary Assessment ambulatory assessment accelerometry back health physical activity back posture Health Action Process Approach fear avoidance model of pain Back Health Behavior Model prevention of low back pain Figures Figure 1 Figure 2 Background Low back pain (LBP) is a health complaint responsible for the most years lived with disability worldwide ( 1 ). A population-based study from Germany showed that 52.9% of adults had experienced LBP in the past year, with 15.5% of this cohort reporting back pain for at least three months, referred to as chronic back pain ( 2 ). Despite the high prevalence of chronic low back pain (cLBP) and its substantial contribution to work-related disability ( 3 ), understanding of the aetiology of cLBP and its successful prevention remains limited. Recent research suggests that targeting modifiable behavior-related risk factors such as smoking, high body mass index, and low physical activity could substantially reduce the number of years lived with disability due to cLBP ( 1 , 4 ). This emphasizes the importance of prioritizing health behaviors such as physical activity in the prevention and treatment of cLBP. Therefore, this study aims to examine patterns of physical activity and their linkages with cLBP. Additionally, we aim to identify psychosocial predictors of pain, back health, and physical activity, grounded in behavior change theory, to inform the development of behavioral interventions. The Role of Psychosocial Factors and Physical Activity in cLBP According to the biopsychosocial model of low back pain ( 5 ), cLBP is considered a multidimensional syndrome. Often the persistence of pain is not directly related to the factors that contributed to the initial onset of pain, such as injury or overuse, but rather to the factors that maintain the pain. As non-specific LBP (i.e., back pain without a clear organic origin) persists, psychological, behavioral, and social risk factors may contribute to its progression to cLBP ( 6 , 7 ). Similarly, a growing body of literature shows that the subjective experience of pain (e.g., pain intensity) is highly dependent on psychological risk factors—commonly referred to as "yellow flags". These include, for example, perceived stress, negative affect, depressive symptoms, and cognitive responses to pain such as catastrophizing ( 7 , 8 ). In turn, engaging in health behavior such as physical activity is essential for enhancing overall health and lowering the risk of mortality ( 9 ). The World Health Organization recommends undertaking regular physical activity, including moderate-to-vigorous intensity physical activity and muscle-strengthening physical activity in a considerable amount throughout the week ( 10 ). Although physical activity, and leisure-time physical activity (LTPA) in particular ( 11 , 12 ) is widely acknowledged as an important non-pharmacological strategy for preventing and managing cLBP, there is inconsistent and limited evidence regarding the most beneficial type, intensity, duration, and frequency of LTPA for preventing cLBP ( 11 , 13 ). Understanding the Links Between Pain, Psychosocial Factors and Physical Activity: Towards a Resource-Oriented Approach to cLBP While previous research has often focused on risk factors, such as health risk behaviors ( 1 ) or maladaptive cognitions ( 8 ), the present study takes a more comprehensive approach that includes both risk and salutary factors ( 14 ). Such an approach emphasizes that the absence of disease cannot be equated with health and posits that LBP and back health are distinct concepts ( 15 ). Theoretical perspectives from the psychology of behavior change and the chronification of pain provide a framework for examining the complex relationships between health or disease, psychological and social factors, and health behaviors. In particular, the back health behavior model (BHBM) ( 16 ) represents a systematic, theory-based framework that integrates key insights from pain psychology (i.e., the fear-avoidance model ( 17 ) and the avoidance-endurance model of pain ( 18 )) and health psychology (i.e., the Health Action Process Approach, HAPA ( 19 ) and the Physical Activity Adoption and Maintenance, PAAM ( 20 )). As the BMBM considers both psychological and behavioral resources and risk factors (see Fig. 1 ), it is well suited to a comprehensive examination of cLBP and back health. Taking a closer look at the BHBM ( 16 ), at the behavioral level, health behavior such as LTPA can be seen as a resource-oriented coping and prevention strategy. Importantly, successful engagement in health behaviors requires the involvement of explicit and implicit processes at the psychological level. For instance, an individual’s intention to engage in physical activity is determined by their subjective appraisal of their own resources (e.g., (pain) self-efficacy, (pain-related) social support), but also by their emotional states (e.g., affect) or pain-related beliefs (e.g., fear-avoidance beliefs). In turn, if individuals are motivated to adopt behavioral changes, they need to translate their intentions into behavior using volitional, self-regulatory strategies (e.g., planning). Figure 1 shows the BHBM modified to account for environmental and biomechanical factors ( 21 ). Capturing Fluctuations in Pain Intensity, Back Health and Physical Activity Using Ecological Momentary Assessment Both the experience of pain and related factors often vary over time within individuals ( 22 ). Thus, multiple assessment designs that aim to capture the temporal dynamics between variables are well suited to examining cLBP. The number of studies investigating cLBP using Ecological Momentary Assessment (EMA) designs has increased over time ( 23 ). An EMA design can provide new insights into how psychosocial predictors, health behaviors (i.e., physical activity), and behavior-related outcomes (i.e., pain intensity, back health) evolve at different levels of temporal resolution and with different time lags, for example, moment-to-moment or day-to-day. This in turn allows us to test theoretical assumptions at both the within-person and between-person levels simultaneously ( 24 ). The Present Study Studies examining the associations between physical activity and pain and its theory-based, modifiable predictors are needed to inform the design of behavioral interventions to prevent cLBP. This prospective observational study PRIA (Psychologie und Rückengesundheit im Alltag) considers both risk factors and resources for cLBP, both in terms of health behaviors (e.g., LTPA, back posture and mobility) and psychosocial factors (e.g., self-efficacy, positive affect, social support). Importantly, in line with health conceptualizations ( 15 ), self-reports of LBP are complemented by self-reports of back health to explore the potential utility of health measures in the prevention and treatment of cLBP. Another important aim of the PRIA study is to investigate the intraindividual (i.e., within-person) variation in pain, back health, and physical activity and its theoretical determinants. In doing so, the study aims to improve our understanding of how the temporal dynamics between LBP and back health evolve in the daily lives of individuals with and without cLBP, and how these within-person patterns differ between individuals with different individual characteristics. Specifically, the research objectives of the PRIA study are to a) capture how LBP intensity and back health unfold in daily life, b) identify physical activity patterns in individuals with and without cLBP, c) examine the associations between pain intensity, back health, and physical activity, and d) identify key modifiable psychosocial correlates of and health behaviors related to pain intensity and back health. While seeking for modifiable correlates of cLBP, we will also consider the role of non-modifiable factors. For example, given the accumulating evidence that sex and gender differences are an important source of variation in how individuals experience and respond to pain ( 25 , 26 ), we will consider gender to build a comprehensive model. Between-Person Hypotheses As physical activity, and LTPA in particular ( 12 ) has been conceptualized as a key predictor of LBP and back health, as well as mediating the association between psychosocial factors and LBP and back health (Fig. 1 ), we propose several hypotheses regarding LTPA. First, we hypothesize that individuals with cLBP will differ in their physical activity patterns from individuals without cLBP. Relatedly, we expect that individuals with cLBP will experience more challenges in regulating their health behavior (e.g., lower intention and poorer self-regulation; Fig. 1 ) than participants without cLBP, for example, due to their respective pain- and physical activity-related cognitions (e.g., higher levels of kinesiophobia). Second, we hypothesize that higher average levels of LTPA will be associated with lower levels of pain and better back health, posture and mobility. With regard to psychosocial factors, we expect that higher levels of pain-related and activity-related cognitions that can be considered risk factors for cLBP (e.g., kinesiophobia) will be associated with higher pain intensity and poorer back health, whereas resources (e.g., pain self-efficacy) will be associated with lower pain intensity and better back health. On the contextual variables side, we will explore whether higher levels of perceived general and pain-related social support are associated with lower pain intensity and better back health. In collaboration with the overall research consortium, we will also investigate whether and how spinal morphology, mechanics, and motion are linked to LBP, back health, and physical activity. In terms of the macro-longitudinal perspective, we expect the variables measured at baseline, three months and six months after baseline to be relatively stable over the chosen time intervals, as no intervention has been implemented. Within-Person Hypotheses At the within-person level, we will examine how changes in psychosocial variables covary with changes in physical activity and subsequently with LBP intensity and back health. Among other thigs, we hypothesize that people will report lower pain intensity and better back health at times when they are more physically active in their leisure time than usual. We also expect to observe lower pain intensity, better back health, and more LTPA engagement than usual at times when self-control, pain self-efficacy, and positive affect are higher than usual, and fear of movement and negative affect are lower than usual ( 27 – 30 ). We will explore these relationships at different levels of temporal resolution (e.g., momentary, daily) and for different time lags (e.g., same measurement time, different time points). Methods Study Design This study follows the STROBE guidelines (31) and uses a prospective macro-longitudinal design spanning six months, complemented by a micro-longitudinal phase using EMA over a 14-day period (Figure 2). The study is embedded in an interdisciplinary research consortium, FOR 5177 (32), which is investigating spinal morphology (e.g., spinal shape and geometry), mechanics (e.g., lumbar spinal loading), and motion (e.g., spino-pelvic kinematics and physical activity) as well as interventions and mechanisms, and how they are related to and associated with cLBP. The overall goal of the FOR 5177 research consortium is to improve the understanding of the aetiology and pathogenesis of cLBP, to propose novel strategies for patient stratification, and to advance the prevention and treatment of cLBP. To this end, static imaging (i.e., MRI) and short physical assessments, as they represent the current clinical diagnostic approach in cLBP, are complemented by dynamic investigations of spinal mobility and loading, and assessments of physical activity and psychosocial factors in daily life. In the following, we present the subproject PRIA, including the specific study sample, procedures and measures that constitute the contribution to FOR 5177 and can also serve as an independent analysis sample. Sample and Recruitment Adults are being recruited in the greater Berlin area. Recruitment methods include local advertising at Charité – Universitätsmedizin Berlin, Humboldt Universität zu Berlin, and MSB Medical School Berlin (via postal flyers, notice boards, internet outreach, and social media), outreach to the general public (via newspapers, magazines, podcasts, TV), collaboration with local companies and administrative authorities, and word of mouth. In addition, the study was promoted during the Long Night of Sciences, a public science fair in Berlin in 2022, 2023, and 2024. Participants are e-mailed information material and invited for a brief introductory telephone call to explain the procedure, review the inclusion and exclusion criteria, and schedule a baseline appointment. After receiving verbal and written information for the PRIA study, including information on the sampling scheme and study devices, participants provide written informed consent. In- and Exclusion Criteria Participants must meet the following inclusion criteria: (1) report lumbopelvic pain for the past 12 weeks or longer (i.e., participants with cLBP), report intermittent lumbopelvic pain or no lumbopelvic pain at all (i.e., participants without cLBP), (2) be between 18 and 64 years old, (3) be able to hear an alarm from a smartphone, and (4) be able to read and understand German text on a 6-inch smartphone and a 10-inch tablet. In terms of exclusion criteria, participants were also required not to: (1) be enrolled in other ongoing clinical trials, (2) be currently pregnant, (3) be a professional, competitive, or top athlete, and (4) have a BMI > 28 kg/m 2 . Further exclusion criteria are listed in the FOR 5177 registration in the German Clinical Trials Register (DRKS number: DRKS00027907). Procedure Participants undergo an initial screening at the Charité – Universitätsmedizin Berlin (21). Each participant in the PRIA subproject then completes a battery of self-administered questionnaires at baseline (Time 0, T0), with subsequent follow-up questionnaires (Time 1 and 2, T1 and T2; macro-longitudinal design). Data are collected via an online survey platform (Unipark, Tivian XI GmbH, Cologne, Germany) using a study tablet on-site (T0) or a personal device at home (e.g., computer, tablet, smartphone; T1-T2). Participants are then instructed in the time-sampling procedure, the use of the Android study smartphone (Nokia 6.3) equipped with the movisensXS app (movisens GmbH), and the proper handling of the accelerometer (Move 4, movisens GmbH). For the following 14 days, participants wear the activity sensor to collect data on their physical activity during waking hours. In addition, at five alarm-triggered measurement occasions per day (at 9 am, 12 pm, 3 pm, 6 pm, and 9 pm), participants fill out short self-report questionnaires using the study smartphone and the movisensXS app. Each assessment takes approx. 2 minutes to complete, resulting in a total of 2.5 hours of diary assessments during the entire EMA phase. At the end of the 14-day period, participants return the study devices and are reimbursed €30 for completing the assessment. On day 16, participants are being e-mailed a link to a feedback questionnaire about their experience of the EMA phase. Participants then receive individualized feedback on selected EMA variables. At T1 (three months after T0) and T2 (six months after T0), participants are again being e-mailed links to the follow-up questionnaires. Benefits and Harms Given the non-invasive nature of both the accelerometer measurements and the online questionnaires, we do not anticipate any harm beyond the time commitment required of participants. Reimbursement and individualized feedback on selected variables assessed within the EMA are provided. Participants are encouraged to report any adverse effects they may experience during participation by e-mail, text message or phone call to the study facilitator as they arise. After the EMA phase, participants are requested to provide feedback on the study to improve future assessments. The researchers consulted with the Patient Advisory Board during the study preparation phase. Ethical Approval, Funding and Transparency The university’s ethics committee at the MSB Medical School Berlin approved the study on 03/08/2021 (approval number MSB-2021/59, amendment approved on 11/10/2023, amendment number MSB-2023/145). Ethical approval for the initial screening of FOR 5177 was granted by Charité – Universitätsmedizin Berlin (EA1/058/21). Written informed consent is obtained from each participant prior to enrollment. The PRIA study is funded by the German Research Foundation (DFG; project number 439742772, grant numbers FL 879/2-1 and STE 477/22-1). The trial is registered in the German Clinical Trials Register (DRKS00032978, registration date: 12/22/2022) and is also listed on the International Clinical Trials Registry Platform. Data collection started on 01/09/2023 and the planned study end date is 06/09/2025. Data storage is in accordance with the EU General Data Protection Regulation (GDPR), with all data pseudonymized and securely stored on a server at MSB Medical School Berlin. Measures Macro-Longitudinal Measures Table 1 provides an overview of the variables measured at T0, T1 and T2. At T0, participants provide information on demographic characteristics, LBP chronicity status, LBP intensity and pain-related disability, back health, physical activity, and theory-based psychological variables. Time-sensitive variables are being reassessed at T1 and T2. Primary outcome . Leisure-time physical activity (LTPA) is the primary outcome variable, assessed as non-work-related moderate-to-vigorous physical activity (MVPA). Participants complete an adapted version of the validated German version of the International Physical Activity Questionnaire, IPAQ long (33, 34). The questionnaire covers different intensities of physical activity in four activity domains including housework and gardening, work-related activities, transport, leisure-time physical activity, and sedentary behavior. Participants report the number of hours and/or minutes spent in moderate and vigorous activities within each activity domain over the past 7 days. The IPAQ data will be processed according to the IPAQ protocol (35). The validity of the IPAQ will be evaluated empirically by assessing its agreement with the accelerometer data collected in this study. Secondary outcomes. Secondary outcome variables encompass behavior-related variables related to lower back, such as LBP intensity, back health, back posture and mobility, sedentary behavior, and pain medication. Behavior-related health outcomes. To assess LBP intensity and pain-related disability, we use the Chronic Pain Grade Questionnaire, CPGQ (36, 37), with instructions adapted to focus on LBP. Chronicity of LBP is assessed using a binary ( yes/no ) item including the criterion of constant or almost daily LBP in the previous 12 weeks (2). As an indicator of back health , we adapted a single item from the SF-36 (38), which assesses subjective health: “How would you rate the health of your lower back?”, with a 5-point Likert scale of 1 ( poor ), 2 ( not so good ), 3 ( good ), 4 ( very good ), and 5 ( excellent ). General health-related quality of life is assessed using the German SF-12 Health Survey (SF-12; (38)). Perceived stress is measured with the validated German version of the 10-item Perceived Stress Scale, PSS-10 (39, 40). Behavioral outcomes. To measure back posture and mobility, we use an adapted version of the Back Posture, Movement and Mobility (B-PMM) self-report questionnaire (16). The B-PMM self-report questionnaire consists of 13 items that assess perceived back posture (e.g., “When I work, I pay attention to a posture that is gentle on my back.”), perceived back movement (e.g., “When I am active during my leisure time, my back is also in a lot of movement (e.g., twisting, bending, lifting).”) and back mobility (“I am very flexible in the back.”). Participants can respond to the items using a 6-point Likert scale, ranging from 1 ( not true at all ) to 6 ( extremely true ). For posture and movement, the mean score is calculated from the relevant items. The validity of the B-PMM will be tested by determining the agreement with the Postural Awareness Scale, PAS (41), an established scale to assess the awareness of body posture in patients with chronic pain and used in the PRIA study, and with objective back measurement data from other subprojects of the research consortium. We measure sedentary behavior at work and during leisure time in the past 7 days by self-report using three items adapted from the IPAQ long (33, 34). Finally, to asses pain medication , we use the Medication Quantification Scale, MQS (42). We record drug name, dosage (in milligrams), form (i.e., pill, patch, balm, suppository, other), intake as needed or regular, intake time of day (i.e., in the morning, at noon, in the afternoon, in the evening), pain localization (i.e., LBP, neck pain, headache, other), side effects (i.e., nausea, vomiting, dry mouth, dizziness, sweating, tiredness, disorientation, concentration problems, stomach upset, other), and further comments, separately for each drug. The drug names will be categorized into medication subclasses, for which risk weights are available (43). This information can be used to calculate daily oral morphine equivalents (44). The relative dosage scores will be individually calculated by comparing the participant’s daily dosage with the physicians’ desk reference (current year) recommendations (e.g., (45)). Thereby, three aspects of medications (drug class, dosage, risk) can be quantified. Determinants of behavioral and behavior-related health outcomes. We measure a) cognitions specific to LTPA, b) cognitions specific to pain perception regarding the self and the social environment, and c) general cognitions and affect. Activity-related cognitions. Based on the HAPA (19), we assess risk perception with an adapted 4-item scale introduced by Lippke et al. (46), outcome expectancies with an adapted 8-item scale based on the measurement by Meng et al. (47), intention to be physically active, physical activity-related self-efficacy , and action planning based on the measures implemented by Sniehotta and colleagues (48) and Knoll and colleagues (49) with several adaptations (e.g., for intention, the time reference is to the next seven days instead of the last seven days). Habit strength is measured by the Self-Report Behavioral Automaticity Index (50). Back- and pain-related cognitions. Based on the fear-avoidance model (51, 52), we assess pain-related cognitions, pain catastrophizing using the validated German version of the Pain Catastrophizing Scale, PCS (53), pain self-efficacy using the validated German version of the Pain Self-Efficacy Questionnaire, PSEQ (54), the FESS (55), and fear-avoidance and endurance-related responses to pain using the Avoidance-Endurance Fast Screen, AE-FS (56). Behavior-unspecific, general cognitions and affect. General self-control is measured using the validated German version of the Self-Control Scale, SCS-K-D (57-59). We also measure perceived general social support using the short form of the Social Support Questionnaire (60). We assess positive affect and negative affect using 12 items from the short form of the Positive and Negative Affect Schedule (short form PANAS (61)), based on PANAS (62)) in a German translation by Krohne et al. (63) (translation of one item adapted). Social factors . We assess responses of significant others to pain reported by participants using the validated German version of the West Haven-Yale Multidimensional Pain Inventory (WHYMPI/MPI), Part II (64) (Patienten MPI-D (65)). Part II of the WHYMPI/MPI questionnaire consists of three subscales that capture solicitous , distracting , and punishing responses of a significant other (e.g., spouse) while participants display pain behaviors. Micro-Longitudinal Measures The variables collected during the EMA study phase correspond to the variables in the macro-longitudinal study. The sampling schedule and the wording of the items used in the EMA study are shown in Table 2. Physical Activity. Physical activity is assessed both objectively using accelerometer data and through self-report. Objective data is collected passively during waking hours using the Move 4 activity sensor (66). The sensor, worn on the right hip, continuously records data using a 3D accelerometer, gyroscope, barometric pressure, and temperature. The device has no display and does not provide real-time feedback on activity. Combined with movisens’ DataAnalyzer analysis software, the collected data are used to calculate activity class, body position, steps, energy expenditure, and metabolic equivalent of task (MET). As part of the data cleaning process, the recording time is adjusted using the movisens’ UnisensViewer software to represent exactly 14 study days. The daily wear time is determined by subtracting the non-wear time from the total recording time. According to the guidelines of Troiano and colleagues (67), days with 10 hours or more of wear time are considered valid. Additionally, on each of five measurement occasions per day, participants are asked to indicate a) whether they were physically active in their leisure time (i.e., non-work-related) for at least 10 consecutive minutes, b) the type of activity, and c) the exact times of the activity for up to two activity types per measurement occasion. Low Back Pain. At each measurement occasion, we assess the occurrence of LBP with the binary item: “Since the last questionnaire, have you had or are you currently experiencing low back pain?” ( yes/no ). If pain has occurred, participants report the intensity of their LBP using a single item adapted from the CPGQ (36, 37): “How would you rate your low back pain since the last questionnaire?”, on an 11-point scale ranging from 0 ( no pain ) to 10 ( pain as bad as it could be ). Each evening (i.e., at 9 pm), participants also rate the most intense LBP of the day from 0 ( no pain ) to 10 ( pain as bad as it could be ). Low Back Health. At each measurement, we ask participants to rate their back health using a single item adapted from the SF-36 (38): “How has your lower back felt since the last questionnaire?”, using a 5-point Likert scale of 1 ( poor ), 2 ( not so good ), 3 ( good ), 4 ( very good ), and 5 ( excellent ). Physical Activity-Related Cognitions. We assess physical activity-related self-efficacy by asking: “At the moment, how confident are you that you can manage to be physically active in your leisure time, even if you find it difficult?”, and physical activity-related intention strength with the item: “At the moment, to what extent do you intend to be physically active in your leisure time?”. Both items are rated on a 10-point scale with anchors at 1 ( not at all ) and 9 ( very much ) and are based on research by Inauen, Shrout (24). For each reported leisure activity, participants also indicated whether their activity was planned or spontaneous using two items: “I planned this activity in advance” and “I was spontaneously physically active”, and the 6-point Likert scale from 1 ( I completely disagree ) to 6 ( I completely agree ). Pain-Related Cognitions. If participants report the occurrence of pain since the last questionnaire, we assess kinesiophobia as a potential pain-related risk factor for physical inactivity. To do this, we use a single item adapted from the TSK (68): “At the moment, I’m afraid that I might injure myself if I exercise”, rated on a scale from 1 ( I completely disagree ) to 6 ( I completely agree ). On the resource side, we assess pain self-efficacy with a single item adapted from the PSEQ (54) (FESS (55)): “At the moment, I can still do things that I enjoy doing, such as hobbies or leisure activity, despite pain”, scored on the same response scale as above. Pain Medication. Based on the MQS (42), participants are asked at each measurement occasion whether they had taken any medication since the last questionnaire ( yes/no ). If yes, participants were asked to provide the drug name, dosage (in milligrams), form (i.e., pill, patch, balm, suppository, other), and pain localization (i.e., low back pain, upper back pain, neck pain, headache, other), separately for up to four medications per measurement. In the evening (i.e., at 9 pm), participants report whether any side effects occurred that day. Social Factors. If pain has occurred, participants are asked if they have received support from other people related to their LBP since the last questionnaire ( yes/no ). If participants report having received support, they are asked who the support provider was (partner, family member, friend, professional caregiver, other). Furthermore, we assess received instrumental support as joint problem solving such as discussing the problem with one’s partner and taking concrete actions (69, 70) with the item: “The person discussed possible solutions with me or did something about the problem”, and received emotional support with the item “The person comforted me or hugged me” (71), both on a scale from 1 ( I completely disagree ) to 6 ( I completely agree ). Affect, Perceived Stress and Self-Control. At the beginning of each measurement, we assess positive and negative affect by asking “How … do you feel at the moment?”, presenting five single positive affect items ( inspired, alert, excited, enthusiastic, determined ) and six negative affect items ( afraid, upset, nervous, distressed, jittery, annoyed ). The affect items are rated on a scale of 1 ( very slightly or not at all ), 2 ( a little ), 3 ( moderately ), 4 ( quite a bit ), and 5 ( very much ). The items are derived from the short form of the PANAS (61, 63) (translation of one item adapted). Using the same item format and response scale, we additionally ask participants to rate their perceived stress. Next, we measure self-control using one positively and one negatively framed item adapted from the State Self-Control Capacity Scale (SMS-5, (72)): “At the moment, I feel like I have no willpower left” and “At the moment, I feel balanced”. Both items are rated on a scale from 1 ( fully disagree ) to 7 ( fully agree ). Generalizability . At 9 pm, participants report whether they worked that day and, if so, the exact hours they worked. Participants then report how typical their day was using the item “Now think about your usual activities on a typical weekday or weekend day like today. Was today typical for your everyday life?”, with a 5-point Likert scale of 1 ( not at all or very little ), 2 ( a little ), 3 ( to some extent ), 4 ( a lot ), and 5 ( extremely ). If the answer is “to some extent” or lower, participants are asked to provide additional information on that day. First, with the multiple-choice item “What made today less typical than usual?”, with the response format 1 ( less low back pain than usual ), 2 ( more low back pain than usual ), 3 ( less physical activity than usual ), 4 ( more physical activity than usual ), 5 ( other peculiarities ). Second, with the open-ended question “What was different than usual?”. Power Analysis To test the micro-longitudinal hypotheses, an a priori power calculation for the LTPA outcome indicated that over n =2000 individuals (i.e., number of individuals required) and at least n =14 (i.e., number of repeated measures) would be required to detect small-sized population effects (given the unknown size of the cross-level interaction which is typically smaller than a main effect, (73)) with a power of >=.95. We aim to achieve this, but more realistically, assuming a power of >=.80, a sample size of at least n =200 (accounting for 30% attrition) is required to detect small-sized population effects (74). Data Analyses Statistical analyses will be carried out both throughout the data collection process for monitoring purposes and at the end of the data collection. Descriptive statistics will be calculated for all variables (see Tables 1 and 2), together with plausibility checks, assessment of distribution characteristics, identification of outliers and analysis of missing data. Between-Person Hypotheses The relationship between physical activity and behavior-related health outcomes will be evaluated through regression models. Additionally, path analyses will be employed to test our hypotheses regarding longitudinal direct and indirect associations between theory-based psychological variables and LTPA (Figure 1). Within-Person Hypotheses Intra-class correlations (ICC), Pearson correlations, as well as repeated measures correlations (75) will be calculated. To account for the nested structure of the micro-longitudinal data, multilevel models will be calculated with the primary outcome (i.e., LTPA) and the secondary outcomes (e.g., LBP intensity, back health) as dependent variables. Based on the BHBM (Figure 1), psychosocial variables will be included as level-1 predictors. LBP chronicity status (i.e., participants with and without cLBP) will be considered a person-level predictor, moderating associations between within-person predictors and outcomes. We will specify multilevel models with fixed and random effects. Hypothesis testing for the fixed effects will provide insights into the relationships between LBP intensity, back health, LTPA, and its within-person and between-person predictors. To test the theoretical assumptions (Figure 1), we will specify within-person mediation models and estimate indirect effects. In collaboration with the research consortium, we will also investigate whether the association between LTPA and its predictors is of different size depending on, for example, sex, spinal morphology and mechanics. Dissemination The study registration and this protocol are the first publications of the PRIA study. The results of this research will be reported to the funding agency (DFG), published in peer-reviewed international journals and presented at national and international conferences. In addition, wider dissemination to the public is planned through events such as the Long Night of Sciences (a public science fair) in Berlin and various media channels. Discussion As part of a larger interdisciplinary research consortium, the PRIA study investigates diagnostic, preventive and therapeutic aspects of cLBP. It complements the current clinical diagnostic approach to cLBP by examining LBP intensity and back health in participants with and without cLBP in their everyday lives. In doing so, the study implements methods that go beyond cross-sectional analyses of data collected at a single point in time. The results of this study are expected to contribute to the development of improved diagnostics, for example by looking more closely at how physical activity and LBP intensity unfold in the daily lives of people with cLBP ( 23 , 76 ), and effective, personalized interventions by addressing risk factors and resources for cLBP and back health in daily life. One promising avenue of prevention research is just-in-time adaptive interventions using mobile technology ( 77 ). Research that improves our understanding of the subtle connections between pain and physical activity can help shape psychotherapeutic and behavioral recommendations, potentially improving the health, longevity, and quality of life for people with chronic pain. For the prevention of cLBP, individuals are expected to be able to actively minimize psychosocial risk factors and build on resources, such as engaging in physical activity. In the context of cLBP, the latter may encompass both LTPA ( 11 , 12 ) and adjustment and modification of back posture ( 41 ). Currently, there is no consistent evidence on which types of physical activity (e.g., in terms of intensity, duration, and frequency of LTPA ( 13 )) are most beneficial for people with cLBP to reduce pain intensity and promote back health, and evidence as to how the associations between pain and physical activity unfold at the momentary level ( 76 ). A deeper understanding of the associations between cLBP, different aspects of physical activity, and their theory-based psychological predictors is needed to guide future recommendations and interventions. With its comprehensive approach combining theory, evidence and assessment methods from health and pain psychology, but also drawing on insights from behavioral medicine, biomechanics and movement sciences, the PRIA intensive longitudinal study aims to advance the field of cLBP prevention and treatment. Strengths, Limitations, and Challenges A notable advance of the PRIA study, in line with previous studies in primary prevention of chronic pain ( 16 ), is its shift from a pathological perspective to a more resource-oriented approach to understanding cLBP ( 78 ). While previous research has focused primarily on examining modifiable risk factors such as health risk behaviors (e.g., heavy lifting, prolonged sitting) and negative health-related cognitions (e.g., fear of movement), the PRIA study broadens this scope. It examines these risk factors alongside theory-based, modifiable resources, including physical activity and self-efficacy, providing a more balanced view of cLBP prevention and management. A unique value of the PRIA study is that it examines psychosocial risk factors and resources in a cohort of individuals with and without cLBP. This will allow us to examine not only the role of resources and risk factors in the presence of pain (i.e., cohort of people with cLBP), but also the role of resources and risk factors in promoting back health (i.e., cohort of asymptomatic individuals). This approach will provide valuable insights for the development of effective behavioral interventions aimed at both the prevention of LBP and the promotion of back health. In addition to a traditional macro-longitudinal approach, the PRIA study utilizes an intensive longitudinal design that involves multiple sampling of participants' momentary experiences and behaviors in their everyday environments, rather than relying on isolated laboratory-based assessments. This allows for high temporal data resolution at the intra-individual level, providing new theoretical insights into the within-person dynamics of psychosocial and behavioral risks and resources associated with LBP over time in everyday life ( 79 ). However, this approach also presents challenges, such as the potential for higher dropout rates and increased participant burden. To mitigate these risks, the study includes financial incentives and individualized feedback to improve participant retention and engagement. Another challenge may be the potential adverse effect of repeated pain assessments, which could increase the perception of pain by focusing the participant’s attention on adverse bodily experiences. However, recent research supports the usability and feasibility of EMA on a smartphone to collect real-time data on cLBP ( 80 ). Importantly, the assessment of pain using smartphones does not appear to have a negative impact on pain intensity trajectories ( 15 ). A key strength of the PRIA study is its multi-method approach to assessing physical activity, including both objective measures and self-reports. By using objective data on physical activity, the study helps to mitigate problems commonly associated with method variance, such as inflated correlations between self-reported predictors and self-reported outcomes. In addition, the use of accelerometry reduces the potential for over- or underestimation of physical activity. However, the use of accelerometers has limitations, including the potential for missing or unusable data, participant noncompliance with wearing the device, and technical malfunction. A major disadvantage of accelerometers is their inability to capture detailed information about the specific type of physical activity (e.g., yoga, walking). To address this, the PRIA study combines accelerometer data with self-reported measures of physical activity. Despite the potential risks and limitations, the theoretical insights gained from our observational study are expected to improve the understanding of risk factors and protective resources related to cLBP. In particular, findings on the temporal dynamics of pain and modifiable resources and risk factors are expected to inform the development of mobile technology-based interventions (e.g., just-in-time-adaptive interventions, ( 77 )) that support behavioral approaches to both LBP treatment and back health promotion. Abbreviations AE-FS – Avoidance-Endurance Fast-Screen BHBM – Back Health Behavior Model BMI – Body mass index B-PMM – Back Posture, Movement and Mobility cLBP – chronic low back pain CPGQ – Chronic Pain Grade Questionnaire DFG – Deutsche Forschungsgemeinschaft (German Research Foundation) DRKS – Deutsches Register Klinischer Studien (German Clinical Trials Register) EMA – Ecological momentary assessment EU – European Union FESS – Fragebogen zur Erfassung der schmerzspezifischen Selbstwirksamkeit FOR 5177 – Forschungsgruppe 5177 GDPR – General Data Protection Regulation HAPA – Health Action Process Approach IPAQ – International Physical Activity Questionnaire LBP – Low back pain LTPA – Leisure-time physical activity MPI-D – Multidimensional Pain Inventory, deutsche Version MRI – Magnetic resonance imaging MSB – Medical School Berlin MQS – Medication Quantification Scale MVPA – Moderate-to-vigorous physical activity PAAM – Physical Activity Adoption and Maintenance PANAS – Positive and Negative Affect Schedule PAS – Postural Awareness Scale PCS – Pain Catastrophizing Scale PRIA – Psychologie und Rückengesundheit im Alltag PSEQ – Pain Self-Efficacy Questionnaire PSS-10 – 10-item Perceived Stress Scale SCS-K-D – German version of the Self-Control Scale SF-12 – 12-item Short-Form-Health-Survey SMS-5 – State Self-Control Capacity Scale STROBE – Strengthening the Reporting of Observational studies in Epidemiology T0 – Time 0 (baseline assessment) T1 – Time 1 (first follow-up assessment) T2 – Time 2 (second follow-up assessment) TSK – Tampa Scale for Kinesiophobia WHYMPI/MPI – West Haven-Yale Multidimensional Pain Inventory Declarations Ethics approval and consent to participate The university’s ethics committee at the MSB Medical School Berlin approved the study on 03/08/2021 (approval number MSB-2021/59, amendment approved on 11/10/2023, amendment number MSB-2023/145). Ethical approval for the FOR 5177 initial screening was granted by Charité – Universitätsmedizin Berlin (EA1/058/21). Written informed consent is obtained from each participant before enrollment. Consent for publication Not applicable. Availability of data and materials Due to the research context of a chronic health issue, strict personal data protection is required. Study materials and anonymized data may be accessed upon request after the data collection is completed. Inquiries can be directed to Lena Fleig ( [email protected] ). Competing interests: YES Karolina Kolodziejczak-Krupp’s position as Research Associate at MSB Medical School Berlin, Berlin, Germany is funded from Lena Fleig’s grant obtained by the German Research Foundation (DFG) to conduct the study (grant number: FL 879/2-1). Lena Fleig, Hendrik Schmidt, Matthias Pumberger, and Christoph Stein received funding from the German Research Foundation to conduct research within the FOR 5177. All the other authors do not have any further conflicts of interest to declare. Funding Funding for the PRIA study is provided by the German Research Foundation (project number 439742772) through grants FL 879/2-1 and STE 477/22-1. Authors’ contributions KKK and LF drafted the initial version of the protocol. LOW, LT, CS, TS, MP, and HS contributed valuable feedback for the revised manuscript. LF, CS, and MP serve as principal investigators for the study and secured its funding. HS, as spokesperson of the FOR 5177, is the lead principal investigator responsible for funding acquisition and research consortium oversight. LF, CS, TS, MP, and HS formulated the original research questions and designed the study methodology. KKK, VZ, and LF coordinate the study and collect the data. All authors have approved the final manuscript version. Acknowledgements The authors would like to thank the entire FOR 5177 team, especially the study coordinators responsible for recruitment. 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Examining the association between objective physical activity and momentary pain: A systematic review of studies using ambulatory assessment. J Pain. 2024;25(4):862–74. https://doi.org/10.1016/j.jpain.2023.10.021 . Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, et al. Just-in-Time Adaptive Interventions (JITAIs) in mobile health: Key components and design principles for ongoing health behavior support. Ann Behav Med. 2018;52(6):446–62. https://doi.org/10.1007/s12160-016-9830-8 . Rolli Salathé C, Elfering A. A Health- and Resource-Oriented Perspective on NSLBP. ISRN Pain. 2013;2013:640690. https://doi.org/10.1155/2013/640690 . Treede RD, Rief W, Barke A, Aziz Q, Bennett MI, Benoliel R, et al. Chronic pain as a symptom or a disease: The IASP classification of chronic pain for the International Classification of Diseases (ICD-11). Pain. 2019;160(1):19–27. https://doi.org/10.1097/j.pain.0000000000001384 . Lin WC, Burke L, Schlenk EA, Yeh CH. Use of an ecological momentary assessment application to assess the effects of auricular point acupressure for chronic low back pain. Comput Inf Nurs. 2019;37(5):276–82. https://doi.org/10.1097/cin.0000000000000478 . Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations Competing interest reported. Karolina Kolodziejczak-Krupp’s position as Research Associate at MSB Medical School Berlin, Berlin, Germany is funded from Lena Fleig’s grant obtained by the German Research Foundation (DFG) to conduct the study (grant number: FL 879/2-1). Lena Fleig, Hendrik Schmidt, Matthias Pumberger, and Christoph Stein received funding from the German Research Foundation to conduct research within the FOR 5177. All the other authors do not have any further conflicts of interest to declare. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5965211","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Study protocol","associatedPublications":[],"authors":[{"id":414357917,"identity":"d9b9dfac-b623-4dbc-89d8-5cfea0199052","order_by":0,"name":"Karolina Kolodziejczak-Krupp","email":"data:image/png;base64,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","orcid":"","institution":"MSB Medical School Berlin","correspondingAuthor":true,"prefix":"","firstName":"Karolina","middleName":"","lastName":"Kolodziejczak-Krupp","suffix":""},{"id":414357918,"identity":"29e9871c-59b5-4573-af67-78171557c74f","order_by":1,"name":"Valerie Zipper","email":"","orcid":"","institution":"MSB Medical School Berlin","correspondingAuthor":false,"prefix":"","firstName":"Valerie","middleName":"","lastName":"Zipper","suffix":""},{"id":414357919,"identity":"f8407636-6c22-4b54-8d04-ab394be415e6","order_by":2,"name":"Lea O. Wilhelm","email":"","orcid":"","institution":"MSB Medical School Berlin","correspondingAuthor":false,"prefix":"","firstName":"Lea","middleName":"O.","lastName":"Wilhelm","suffix":""},{"id":414357920,"identity":"ce4617c5-3287-4ea7-a27d-fbfb38c5aa18","order_by":3,"name":"Lara Thiel","email":"","orcid":"","institution":"MSB Medical School Berlin","correspondingAuthor":false,"prefix":"","firstName":"Lara","middleName":"","lastName":"Thiel","suffix":""},{"id":414357921,"identity":"b815ceec-5ff9-4a87-b671-ccd0224696e0","order_by":4,"name":"Christoph Stein","email":"","orcid":"","institution":"Charité – Universitätsmedizin Berlin","correspondingAuthor":false,"prefix":"","firstName":"Christoph","middleName":"","lastName":"Stein","suffix":""},{"id":414357922,"identity":"aafc855d-ff22-45b8-aaf4-e12a9d74f872","order_by":5,"name":"Thomas Schäfer","email":"","orcid":"","institution":"HMU Health and Medical University Erfurt","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Schäfer","suffix":""},{"id":414357923,"identity":"50205d8d-8986-48ff-ae08-3666c9417c3f","order_by":6,"name":"Matthias Pumberger","email":"","orcid":"","institution":"Charité – Universitätsmedizin Berlin","correspondingAuthor":false,"prefix":"","firstName":"Matthias","middleName":"","lastName":"Pumberger","suffix":""},{"id":414357924,"identity":"34bad913-fbff-4e75-9038-fc709dde14c9","order_by":7,"name":"Hendrik Schmidt","email":"","orcid":"","institution":"Berlin Institute of Health at Charité – Universitätsmedizin Berlin","correspondingAuthor":false,"prefix":"","firstName":"Hendrik","middleName":"","lastName":"Schmidt","suffix":""},{"id":414357925,"identity":"de4e35fa-7575-4de8-914f-468631dcfb5b","order_by":8,"name":"Lena Fleig","email":"","orcid":"","institution":"MSB Medical School Berlin","correspondingAuthor":false,"prefix":"","firstName":"Lena","middleName":"","lastName":"Fleig","suffix":""}],"badges":[],"createdAt":"2025-02-05 11:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5965211/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5965211/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79812997,"identity":"c990807a-4000-412e-8fdb-2a95956161da","added_by":"auto","created_at":"2025-04-03 07:07:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75941,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTheoretical Framework of the PRIA Study: Back Health Behavior Model(BHBM)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e The BHMB by Wilhelm et al. (16), based on the fear-avoidance model, the avoidance model of pain, the HAPA, and the PAAM. The Figure has been adapted to represent the 3Ms: (spine) morphology, mechanics, and motion.\u003c/p\u003e","description":"","filename":"floatimage123.png","url":"https://assets-eu.researchsquare.com/files/rs-5965211/v1/e4d11c98acfc5a249e01948b.png"},{"id":79812998,"identity":"9e862afe-a164-4b7d-bb26-6a292d8a01db","added_by":"auto","created_at":"2025-04-03 07:07:50","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":128452,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStudy Design: Macro-longitudinal\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eAn overview of the prospective macro-longitudinal design of the PRIA study spanning six months, with a micro-longitudinal EMA phase of 14 days.\u003c/p\u003e","description":"","filename":"floatimage211.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5965211/v1/08065029078b24ab49c5b330.jpeg"},{"id":85771964,"identity":"87cced90-ccab-4d8e-adc1-bb771c23267e","added_by":"auto","created_at":"2025-07-01 13:38:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1401348,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5965211/v1/5429b557-7345-4201-aae3-1ca810208069.pdf"},{"id":79813000,"identity":"52281dd2-b96d-4d06-adcd-9183a545c7d6","added_by":"auto","created_at":"2025-04-03 07:07:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27064,"visible":true,"origin":"","legend":"","description":"","filename":"Table12.docx","url":"https://assets-eu.researchsquare.com/files/rs-5965211/v1/8b368a069871d5aa092974d2.docx"}],"financialInterests":"Competing interest reported. Karolina Kolodziejczak-Krupp’s position as Research Associate at MSB Medical School Berlin, Berlin, Germany is funded from Lena Fleig’s grant obtained by the German Research Foundation (DFG) to conduct the study (grant number: FL 879/2-1). Lena Fleig, Hendrik Schmidt, Matthias Pumberger, and Christoph Stein received funding from the German Research Foundation to conduct research within the FOR 5177.\nAll the other authors do not have any further conflicts of interest to declare.","formattedTitle":"Physical activity and psychosocial characteristics of individuals with and without chronic low back pain in daily life: A study protocol for the PRIA intensive longitudinal study","fulltext":[{"header":"Background","content":"\u003cp\u003eLow back pain (LBP) is a health complaint responsible for the most years lived with disability worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). A population-based study from Germany showed that 52.9% of adults had experienced LBP in the past year, with 15.5% of this cohort reporting back pain for at least three months, referred to as chronic back pain (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Despite the high prevalence of chronic low back pain (cLBP) and its substantial contribution to work-related disability (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), understanding of the aetiology of cLBP and its successful prevention remains limited. Recent research suggests that targeting modifiable behavior-related risk factors such as smoking, high body mass index, and low physical activity could substantially reduce the number of years lived with disability due to cLBP (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This emphasizes the importance of prioritizing health behaviors such as physical activity in the prevention and treatment of cLBP. Therefore, this study aims to examine patterns of physical activity and their linkages with cLBP. Additionally, we aim to identify psychosocial predictors of pain, back health, and physical activity, grounded in behavior change theory, to inform the development of behavioral interventions.\u003c/p\u003e\n\u003ch3\u003eThe Role of Psychosocial Factors and Physical Activity in cLBP\u003c/h3\u003e\n\u003cp\u003eAccording to the biopsychosocial model of low back pain (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), cLBP is considered a multidimensional syndrome. Often the persistence of pain is not directly related to the factors that contributed to the initial onset of pain, such as injury or overuse, but rather to the factors that maintain the pain. As non-specific LBP (i.e., back pain without a clear organic origin) persists, psychological, behavioral, and social risk factors may contribute to its progression to cLBP (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Similarly, a growing body of literature shows that the subjective experience of pain (e.g., pain intensity) is highly dependent on psychological risk factors\u0026mdash;commonly referred to as \"yellow flags\". These include, for example, perceived stress, negative affect, depressive symptoms, and cognitive responses to pain such as catastrophizing (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn turn, engaging in health behavior such as physical activity is essential for enhancing overall health and lowering the risk of mortality (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The World Health Organization recommends undertaking regular physical activity, including moderate-to-vigorous intensity physical activity and muscle-strengthening physical activity in a considerable amount throughout the week (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Although physical activity, and leisure-time physical activity (LTPA) in particular (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) is widely acknowledged as an important non-pharmacological strategy for preventing and managing cLBP, there is inconsistent and limited evidence regarding the most beneficial type, intensity, duration, and frequency of LTPA for preventing cLBP (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eUnderstanding the Links Between Pain, Psychosocial Factors and Physical Activity: Towards a Resource-Oriented Approach to cLBP\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWhile previous research has often focused on risk factors, such as health risk behaviors (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) or maladaptive cognitions (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), the present study takes a more comprehensive approach that includes both risk and salutary factors (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Such an approach emphasizes that the absence of disease cannot be equated with health and posits that LBP and back health are distinct concepts (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTheoretical perspectives from the psychology of behavior change and the chronification of pain provide a framework for examining the complex relationships between health or disease, psychological and social factors, and health behaviors. In particular, the back health behavior model (BHBM) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) represents a systematic, theory-based framework that integrates key insights from pain psychology (i.e., the fear-avoidance model (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and the avoidance-endurance model of pain (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)) and health psychology (i.e., the Health Action Process Approach, HAPA (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and the Physical Activity Adoption and Maintenance, PAAM (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)). As the BMBM considers both psychological and behavioral resources and risk factors (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), it is well suited to a comprehensive examination of cLBP and back health.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTaking a closer look at the BHBM (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), at the \u003cem\u003ebehavioral\u003c/em\u003e level, health behavior such as LTPA can be seen as a resource-oriented coping and prevention strategy. Importantly, successful engagement in health behaviors requires the involvement of explicit and implicit processes at the \u003cem\u003epsychological\u003c/em\u003e level. For instance, an individual\u0026rsquo;s intention to engage in physical activity is determined by their subjective appraisal of their own resources (e.g., (pain) self-efficacy, (pain-related) social support), but also by their emotional states (e.g., affect) or pain-related beliefs (e.g., fear-avoidance beliefs). In turn, if individuals are motivated to adopt behavioral changes, they need to translate their intentions into behavior using volitional, self-regulatory strategies (e.g., planning). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the BHBM modified to account for environmental and biomechanical factors (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCapturing Fluctuations in Pain Intensity, Back Health and Physical Activity Using Ecological Momentary Assessment\u003c/h2\u003e \u003cp\u003eBoth the experience of pain and related factors often vary over time within individuals (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Thus, multiple assessment designs that aim to capture the temporal dynamics between variables are well suited to examining cLBP. The number of studies investigating cLBP using Ecological Momentary Assessment (EMA) designs has increased over time (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). An EMA design can provide new insights into how psychosocial predictors, health behaviors (i.e., physical activity), and behavior-related outcomes (i.e., pain intensity, back health) evolve at different levels of temporal resolution and with different time lags, for example, moment-to-moment or day-to-day. This in turn allows us to test theoretical assumptions at both the within-person and between-person levels simultaneously (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Present Study\u003c/h3\u003e\n\u003cp\u003eStudies examining the associations between physical activity and pain and its theory-based, modifiable predictors are needed to inform the design of behavioral interventions to prevent cLBP. This prospective observational study PRIA (Psychologie und R\u0026uuml;ckengesundheit im Alltag) considers both risk factors and resources for cLBP, both in terms of health behaviors (e.g., LTPA, back posture and mobility) and psychosocial factors (e.g., self-efficacy, positive affect, social support). Importantly, in line with health conceptualizations (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), self-reports of LBP are complemented by self-reports of back health to explore the potential utility of health measures in the prevention and treatment of cLBP. Another important aim of the PRIA study is to investigate the intraindividual (i.e., within-person) variation in pain, back health, and physical activity and its theoretical determinants. In doing so, the study aims to improve our understanding of how the temporal dynamics between LBP and back health evolve in the daily lives of individuals with and without cLBP, and how these within-person patterns differ between individuals with different individual characteristics.\u003c/p\u003e \u003cp\u003eSpecifically, the research objectives of the PRIA study are to a) capture how LBP intensity and back health unfold in daily life, b) identify physical activity patterns in individuals with and without cLBP, c) examine the associations between pain intensity, back health, and physical activity, and d) identify key modifiable psychosocial correlates of and health behaviors related to pain intensity and back health. While seeking for modifiable correlates of cLBP, we will also consider the role of non-modifiable factors. For example, given the accumulating evidence that sex and gender differences are an important source of variation in how individuals experience and respond to pain (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), we will consider gender to build a comprehensive model.\u003c/p\u003e\n\u003ch3\u003eBetween-Person Hypotheses\u003c/h3\u003e\n\u003cp\u003eAs physical activity, and LTPA in particular (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) has been conceptualized as a key predictor of LBP and back health, as well as mediating the association between psychosocial factors and LBP and back health (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), we propose several hypotheses regarding LTPA. First, we hypothesize that individuals with cLBP will differ in their physical activity patterns from individuals without cLBP. Relatedly, we expect that individuals with cLBP will experience more challenges in regulating their health behavior (e.g., lower intention and poorer self-regulation; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) than participants without cLBP, for example, due to their respective pain- and physical activity-related cognitions (e.g., higher levels of kinesiophobia). Second, we hypothesize that higher average levels of LTPA will be associated with lower levels of pain and better back health, posture and mobility.\u003c/p\u003e \u003cp\u003eWith regard to psychosocial factors, we expect that higher levels of pain-related and activity-related cognitions that can be considered risk factors for cLBP (e.g., kinesiophobia) will be associated with higher pain intensity and poorer back health, whereas resources (e.g., pain self-efficacy) will be associated with lower pain intensity and better back health. On the contextual variables side, we will explore whether higher levels of perceived general and pain-related social support are associated with lower pain intensity and better back health. In collaboration with the overall research consortium, we will also investigate whether and how spinal morphology, mechanics, and motion are linked to LBP, back health, and physical activity.\u003c/p\u003e \u003cp\u003eIn terms of the macro-longitudinal perspective, we expect the variables measured at baseline, three months and six months after baseline to be relatively stable over the chosen time intervals, as no intervention has been implemented.\u003c/p\u003e\n\u003ch3\u003eWithin-Person Hypotheses\u003c/h3\u003e\n\u003cp\u003eAt the within-person level, we will examine how changes in psychosocial variables covary with changes in physical activity and subsequently with LBP intensity and back health. Among other thigs, we hypothesize that people will report lower pain intensity and better back health at times when they are more physically active in their leisure time than usual. We also expect to observe lower pain intensity, better back health, and more LTPA engagement than usual at times when self-control, pain self-efficacy, and positive affect are higher than usual, and fear of movement and negative affect are lower than usual (\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). We will explore these relationships at different levels of temporal resolution (e.g., momentary, daily) and for different time lags (e.g., same measurement time, different time points).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study follows the STROBE guidelines (31) and uses a prospective macro-longitudinal design spanning six months, complemented by a micro-longitudinal phase using EMA over a 14-day period (Figure 2). The study is embedded in an interdisciplinary research consortium, FOR 5177 (32), which is investigating spinal morphology (e.g., spinal shape and geometry), mechanics (e.g., lumbar spinal loading), and motion (e.g., spino-pelvic kinematics and physical activity) as well as interventions and mechanisms, and how they are related to and associated with cLBP. The overall goal of the FOR 5177 research consortium is to improve the understanding of the aetiology and pathogenesis of cLBP, to propose novel strategies for patient stratification, and to advance the prevention and treatment of cLBP. To this end, static imaging (i.e., MRI) and short physical assessments, as they represent the current clinical diagnostic approach in cLBP, are complemented by dynamic investigations of spinal mobility and loading, and assessments of physical activity and psychosocial factors in daily life.\u0026nbsp;In the following, we present the subproject PRIA, including the specific study sample, procedures and measures that constitute the contribution to FOR 5177 and can also serve as an independent analysis sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample and Recruitment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdults are being recruited in the greater Berlin area. Recruitment methods include local advertising at Charit\u0026eacute; \u0026ndash; Universit\u0026auml;tsmedizin Berlin, Humboldt Universit\u0026auml;t zu Berlin, and MSB Medical School Berlin (via postal flyers, notice boards, internet outreach, and social media), outreach to the general public (via newspapers, magazines, podcasts, TV), collaboration with local companies and administrative authorities, and word of mouth. In addition, the study was promoted during the Long Night of Sciences, a public science fair in Berlin in 2022, 2023, and 2024. Participants are e-mailed information material and invited for a brief introductory telephone call to explain the procedure, review the inclusion and exclusion criteria, and schedule a baseline appointment. After receiving verbal and written information for the PRIA study, including information on the sampling scheme and study devices, participants provide written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn- and Exclusion Criteria \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants must meet the following inclusion criteria: (1) report lumbopelvic pain for the past 12 weeks or longer (i.e., participants with cLBP), report intermittent lumbopelvic pain or no lumbopelvic pain at all (i.e., participants without cLBP), (2) be between 18 and 64 years old, (3) be able to hear an alarm from a smartphone, and (4) be able to read and understand German text on a 6-inch smartphone and a 10-inch tablet. In terms of exclusion criteria, participants were also required not to: (1) be enrolled in other ongoing clinical trials, (2) be currently pregnant, (3) be a professional, competitive, or top athlete, and (4) have a BMI \u0026gt; 28 kg/m\u003csup\u003e2\u003c/sup\u003e. Further exclusion criteria are listed in the FOR 5177 registration in the German Clinical Trials Register (DRKS number: DRKS00027907).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants undergo an initial screening at the\u0026nbsp;Charit\u0026eacute; \u0026ndash; Universit\u0026auml;tsmedizin Berlin\u0026nbsp;(21).\u0026nbsp;Each participant in the PRIA subproject then completes a battery of self-administered questionnaires at baseline (Time 0, T0), with subsequent follow-up questionnaires (Time 1 and 2, T1 and T2; macro-longitudinal design). Data are collected via an online survey platform (Unipark, Tivian XI GmbH, Cologne, Germany) using a study tablet on-site (T0) or a personal device at home (e.g., computer, tablet, smartphone; T1-T2).\u003c/p\u003e\n\u003cp\u003eParticipants are then instructed in the time-sampling procedure, the use of the Android study smartphone (Nokia 6.3) equipped with the movisensXS app (movisens GmbH), and the proper handling of the accelerometer (Move 4, movisens GmbH). For the following 14 days, participants wear the activity sensor to collect data on their physical activity during waking hours. In addition, at five alarm-triggered measurement occasions per day (at 9 am, 12 pm, 3 pm, 6 pm, and 9 pm), participants fill out short self-report questionnaires using the study smartphone and the movisensXS app. Each assessment takes approx. 2 minutes to complete, resulting in a total of 2.5 hours of diary assessments during the entire EMA phase.\u003c/p\u003e\n\u003cp\u003eAt the end of the 14-day period, participants return the study devices and are reimbursed \u0026euro;30 for completing the assessment. On day 16, participants are being e-mailed a link to a feedback questionnaire about their experience of the EMA phase. Participants then receive individualized feedback on selected EMA variables. At T1 (three months after T0) and T2 (six months after T0), participants are again being e-mailed links to the follow-up questionnaires.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBenefits and Harms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the non-invasive nature of both the accelerometer measurements and the online questionnaires, we do not anticipate any harm beyond the time commitment required of participants. Reimbursement and individualized feedback on selected variables assessed within the EMA are provided. Participants are encouraged to report any adverse effects they may experience during participation by e-mail, text message or phone call to the study facilitator as they arise. After the EMA phase, participants are requested to provide feedback on the study to improve future assessments. The researchers consulted with the Patient Advisory Board during the study preparation phase.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval, Funding and Transparency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe university\u0026rsquo;s ethics committee at the MSB Medical School Berlin approved the study on 03/08/2021 (approval number MSB-2021/59, amendment approved on 11/10/2023, amendment number MSB-2023/145). Ethical approval for the initial screening of FOR 5177 was granted by Charit\u0026eacute; \u0026ndash; Universit\u0026auml;tsmedizin Berlin (EA1/058/21). Written informed consent is obtained from each participant prior to enrollment. The PRIA study is funded by the German Research Foundation (DFG; project number 439742772, grant numbers FL 879/2-1 and STE 477/22-1). The trial is registered in the German Clinical Trials Register (DRKS00032978, registration date: 12/22/2022) and is also listed on the International Clinical Trials Registry Platform. Data collection started on 01/09/2023 and the planned study end date is 06/09/2025. Data storage is in accordance with the EU General Data Protection Regulation (GDPR), with all data pseudonymized and securely stored on a server at MSB Medical School Berlin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMacro-Longitudinal Measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 provides an overview of the variables measured at T0, T1 and T2. At T0, participants provide information on demographic characteristics, LBP chronicity status, LBP intensity and pain-related disability, back health, physical activity, and theory-based psychological variables. Time-sensitive variables are being reassessed at T1 and T2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;Table 1 around here or further down in this section\u0026gt;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary outcome\u003c/strong\u003e. \u003cem\u003eLeisure-time physical activity\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(LTPA)\u003c/em\u003e is the primary outcome variable, assessed as non-work-related moderate-to-vigorous physical activity\u003cem\u003e\u0026nbsp;\u003c/em\u003e(MVPA).\u003cem\u003e\u0026nbsp;\u003c/em\u003eParticipants complete an adapted version of the validated German version of the International Physical Activity Questionnaire, IPAQ long (33, 34). The questionnaire covers different intensities of physical activity in four activity domains including housework and gardening, work-related activities, transport, leisure-time physical activity, and sedentary behavior. Participants report the number of hours and/or minutes spent in moderate and vigorous activities within each activity domain over the past 7 days. The IPAQ data will be processed according to the IPAQ protocol (35). The validity of the IPAQ will be evaluated empirically by assessing its agreement with the accelerometer data collected in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecondary outcomes.\u0026nbsp;\u003c/strong\u003eSecondary outcome variables encompass behavior-related variables related to lower back, such as LBP intensity, back health, back posture and mobility, sedentary behavior, and pain medication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBehavior-related health outcomes.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eTo assess \u003cem\u003eLBP intensity and pain-related disability,\u003c/em\u003e we use the Chronic Pain Grade Questionnaire, CPGQ (36, 37), with instructions adapted to focus on LBP. \u003cem\u003eChronicity of\u003c/em\u003e \u003cem\u003eLBP\u003c/em\u003e is assessed using a binary (\u003cem\u003eyes/no\u003c/em\u003e) item including the criterion of constant or almost daily LBP in the previous 12 weeks (2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs an indicator of \u003cem\u003eback health\u003c/em\u003e, we adapted a single item from the SF-36 (38), which assesses subjective health:\u0026nbsp;\u0026ldquo;How would you rate the health of your lower back?\u0026rdquo;, with a 5-point Likert scale of 1 (\u003cem\u003epoor\u003c/em\u003e), 2 (\u003cem\u003enot so good\u003c/em\u003e), 3 (\u003cem\u003egood\u003c/em\u003e), \u0026nbsp; 4 (\u003cem\u003every good\u003c/em\u003e), and 5 (\u003cem\u003eexcellent\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eGeneral \u003cem\u003ehealth-related quality of life\u003c/em\u003e is assessed using the German SF-12 Health Survey (SF-12; (38)).\u0026nbsp;\u003cem\u003ePerceived stress\u003c/em\u003e is measured with the validated German version of the 10-item Perceived Stress Scale, PSS-10\u0026nbsp;(39, 40).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBehavioral outcomes.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eTo measure back posture and mobility, we use an adapted version of the Back Posture, Movement and Mobility (B-PMM) self-report questionnaire (16). The B-PMM self-report questionnaire consists of 13 items that assess perceived\u003cem\u003e\u0026nbsp;back posture\u003c/em\u003e (e.g., \u0026ldquo;When I work, I pay attention to a posture that is gentle on my back.\u0026rdquo;), perceived \u003cem\u003eback movement\u003c/em\u003e (e.g., \u0026ldquo;When I am active during my leisure time, my back is also in a lot of movement (e.g., twisting, bending, lifting).\u0026rdquo;) and \u003cem\u003eback mobility\u003c/em\u003e (\u0026ldquo;I am very flexible in the back.\u0026rdquo;). Participants can respond to the items using a 6-point Likert scale, ranging from 1 (\u003cem\u003enot true at all\u003c/em\u003e) to 6 (\u003cem\u003eextremely true\u003c/em\u003e). For posture and movement, the mean score is calculated from the relevant items. The validity of the B-PMM will be tested by determining the agreement with the Postural Awareness Scale, PAS (41), an established scale to assess the awareness of body posture in patients with chronic pain and used in the PRIA study, and with objective back measurement data from other subprojects of the research consortium.\u003c/p\u003e\n\u003cp\u003eWe measure \u003cem\u003esedentary behavior\u003c/em\u003e at work and during leisure time in the past 7 days by self-report using three items adapted from the IPAQ long (33, 34). Finally, to asses \u003cem\u003epain medication\u003c/em\u003e, we use the Medication Quantification Scale, MQS (42). We record drug name, dosage (in milligrams), form (i.e., pill, patch, balm, suppository, other), intake as needed or regular, intake time of day (i.e., in the morning, at noon, in the afternoon, in the evening), pain localization (i.e., LBP, neck pain, headache, other), side effects (i.e., nausea, vomiting, dry mouth, dizziness, sweating, tiredness, disorientation, concentration problems, stomach upset, other), and further comments, separately for each drug. The drug names will be categorized into medication subclasses, for which risk weights are available (43). This information can be used to calculate daily oral morphine equivalents (44). The relative dosage scores will be individually calculated by comparing the participant\u0026rsquo;s daily dosage with the physicians\u0026rsquo; desk reference (current year) recommendations (e.g., (45)). Thereby, three aspects of medications (drug class, dosage, risk) can be quantified.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of behavioral and behavior-related health outcomes.\u0026nbsp;\u003c/strong\u003eWe measure a) cognitions specific to LTPA, b) cognitions specific to pain perception regarding the self and the social environment, and c) general cognitions and affect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eActivity-related cognitions.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eBased on the HAPA (19), we assess \u003cem\u003erisk perception\u003c/em\u003e with an adapted 4-item scale introduced by Lippke et al. (46), \u003cem\u003eoutcome expectancies\u003c/em\u003e with an adapted 8-item scale based on the measurement by Meng et al. (47), \u003cem\u003eintention\u0026nbsp;\u003c/em\u003eto be physically active, physical activity-related \u003cem\u003eself-efficacy\u003c/em\u003e, and \u003cem\u003eaction planning\u003c/em\u003e based on the measures implemented by Sniehotta and colleagues (48) and Knoll and colleagues (49) with several adaptations (e.g., for intention, the time reference is to the next seven days instead of the last seven days). \u003cem\u003eHabit strength\u003c/em\u003e is measured by the Self-Report Behavioral Automaticity Index (50).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBack- and pain-related cognitions.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eBased on the fear-avoidance model (51, 52), we assess pain-related cognitions, \u003cem\u003epain catastrophizing\u003c/em\u003e using the validated German version of the Pain Catastrophizing Scale, PCS (53), \u003cem\u003epain self-efficacy\u003c/em\u003e using the validated German version of the Pain Self-Efficacy Questionnaire, PSEQ (54), the FESS (55), and \u003cem\u003efear-avoidance and\u003c/em\u003e \u003cem\u003eendurance-related responses to pain\u003c/em\u003e using the Avoidance-Endurance Fast Screen, AE-FS (56).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBehavior-unspecific, general cognitions and affect.\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;General self-control\u003c/em\u003e is measured using the validated German version of the Self-Control Scale, SCS-K-D (57-59). We also measure \u003cem\u003eperceived general social support\u0026nbsp;\u003c/em\u003eusing the short form of the Social Support Questionnaire (60). We assess \u003cem\u003epositive affect\u003c/em\u003e and \u003cem\u003enegative affect\u003c/em\u003e using 12 items from the short form of the Positive and Negative Affect Schedule (short form PANAS (61)), based on PANAS (62)) in a German translation by Krohne et al. (63) (translation of one item adapted).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSocial factors\u003c/em\u003e\u003c/strong\u003e. We assess responses of significant others to pain reported by participants using the validated German version of the West Haven-Yale Multidimensional Pain Inventory (WHYMPI/MPI), Part II (64) (Patienten MPI-D (65)). Part II of the WHYMPI/MPI questionnaire consists of three subscales that capture \u003cem\u003esolicitous\u003c/em\u003e, \u003cem\u003edistracting\u003c/em\u003e, and \u003cem\u003epunishing responses of a significant other\u003c/em\u003e (e.g., spouse) while participants display pain behaviors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMicro-Longitudinal Measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe variables collected during the EMA study phase correspond to the variables in the macro-longitudinal study. The sampling schedule and the wording of the items used in the EMA study are shown in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;Table 2 around here or further down in this section\u0026gt;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical Activity.\u003c/strong\u003e Physical activity is assessed both objectively using accelerometer data and through self-report. Objective data is collected passively during waking hours using the Move 4 activity sensor (66). The sensor, worn on the right hip, continuously records data using a 3D accelerometer, gyroscope, barometric pressure, and temperature. The device has no display and does not provide real-time feedback on activity. Combined with movisens\u0026rsquo; DataAnalyzer analysis software, the collected data are used to calculate activity class, body position, steps, energy expenditure, and metabolic equivalent of task (MET). As part of the data cleaning process, the recording time is adjusted using the movisens\u0026rsquo; UnisensViewer software to represent exactly 14 study days. The daily wear time is determined by subtracting the non-wear time from the total recording time. According to the guidelines of Troiano and colleagues (67), days with 10 hours or more of wear time are considered valid.\u003c/p\u003e\n\u003cp\u003eAdditionally, on each of five measurement occasions per day, participants are asked to indicate a) whether they were physically active in their leisure time (i.e., non-work-related) for at least 10 consecutive minutes, b) the type of activity, and c) the exact times of the activity for up to two activity types per measurement occasion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLow Back Pain.\u0026nbsp;\u003c/strong\u003eAt each measurement occasion, we assess the occurrence of LBP with the binary item: \u0026ldquo;Since the last questionnaire, have you had or are you currently experiencing low back pain?\u0026rdquo; (\u003cem\u003eyes/no\u003c/em\u003e). If pain has occurred, participants report the intensity of their LBP using a single item adapted from the CPGQ (36, 37): \u0026ldquo;How would you rate your low back pain since the last questionnaire?\u0026rdquo;, on an 11-point scale ranging from 0 (\u003cem\u003eno pain\u003c/em\u003e) to 10 (\u003cem\u003epain as bad as it could be\u003c/em\u003e). Each evening (i.e., at 9 pm), participants also rate the most intense LBP of the day from 0 (\u003cem\u003eno pain\u003c/em\u003e) to 10 (\u003cem\u003epain as bad as it could be\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLow Back Health.\u003c/strong\u003e At each measurement, we ask participants to rate their back health using a single item adapted from the SF-36 (38):\u0026nbsp;\u0026ldquo;How has your lower back felt since the last questionnaire?\u0026rdquo;, using a 5-point Likert scale of 1 (\u003cem\u003epoor\u003c/em\u003e), 2 (\u003cem\u003enot so good\u003c/em\u003e), 3 (\u003cem\u003egood\u003c/em\u003e), \u0026nbsp;4 (\u003cem\u003every good\u003c/em\u003e), and 5 (\u003cem\u003eexcellent\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical Activity-Related Cognitions.\u0026nbsp;\u003c/strong\u003eWe assess physical activity-related \u003cem\u003eself-efficacy\u003c/em\u003e by asking: \u0026ldquo;At the moment, how confident are you that you can manage to be physically active in your leisure time, even if you find it difficult?\u0026rdquo;, and physical activity-related \u003cem\u003eintention\u003c/em\u003e strength with the item: \u0026ldquo;At the moment, to what extent do you intend to be physically active in your leisure time?\u0026rdquo;. Both items are rated on a 10-point scale with anchors at 1 (\u003cem\u003enot at all\u003c/em\u003e) and 9 (\u003cem\u003every much\u003c/em\u003e) and are based on research by Inauen, Shrout (24). For each reported leisure activity, participants also indicated whether their activity was \u003cem\u003eplanned\u003c/em\u003e or spontaneous using two items: \u0026ldquo;I planned this activity in advance\u0026rdquo; and \u0026ldquo;I was spontaneously physically active\u0026rdquo;, and the 6-point Likert scale from 1 (\u003cem\u003eI completely disagree\u003c/em\u003e) to 6 (\u003cem\u003eI completely agree\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePain-Related Cognitions.\u0026nbsp;\u003c/strong\u003eIf participants report the occurrence of pain since the last questionnaire, we assess \u003cem\u003ekinesiophobia\u003c/em\u003e as a potential pain-related risk factor for physical inactivity. To do this, we use a single item adapted from the TSK (68): \u0026ldquo;At the moment, I\u0026rsquo;m afraid that I might injure myself if I exercise\u0026rdquo;, rated on a scale from 1 (\u003cem\u003eI completely disagree\u003c/em\u003e) to 6 (\u003cem\u003eI completely agree\u003c/em\u003e). On the resource side, we assess \u003cem\u003epain self-efficacy\u003c/em\u003e with a single item adapted from the PSEQ (54) (FESS (55)): \u0026ldquo;At the moment, I can still do things that I enjoy doing, such as hobbies or leisure activity, despite pain\u0026rdquo;, scored on the same response scale as above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePain Medication.\u0026nbsp;\u003c/strong\u003eBased on\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe MQS (42), participants are asked at each measurement occasion whether they had taken any medication since the last questionnaire (\u003cem\u003eyes/no\u003c/em\u003e). If yes, participants were asked to provide the drug name, dosage (in milligrams), form (i.e., pill, patch, balm, suppository, other), and pain localization (i.e., low back pain, upper back pain, neck pain, headache, other), separately for up to four medications per measurement. In the evening (i.e., at 9 pm), participants report whether any side effects occurred that day.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocial Factors.\u0026nbsp;\u003c/strong\u003eIf pain has occurred, participants are asked if they have received support from other people related to their LBP since the last questionnaire (\u003cem\u003eyes/no\u003c/em\u003e). If participants report having received support, they are asked who the support provider was (partner, family member, friend, professional caregiver, other). Furthermore, we assess \u003cem\u003ereceived instrumental support\u0026nbsp;\u003c/em\u003eas joint problem solving such as discussing the problem with one\u0026rsquo;s partner and taking concrete actions (69, 70) with the item: \u0026ldquo;The person discussed possible solutions with me or did something about the problem\u0026rdquo;, and \u003cem\u003ereceived emotional support\u003c/em\u003e with the item \u0026ldquo;The person comforted me or hugged me\u0026rdquo; (71), both on a scale from 1 (\u003cem\u003eI completely disagree\u003c/em\u003e) to 6 (\u003cem\u003eI completely agree\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAffect, Perceived Stress and Self-Control.\u0026nbsp;\u003c/strong\u003eAt the beginning of each measurement, we assess positive and negative affect by asking \u0026ldquo;How \u0026hellip; do you feel at the moment?\u0026rdquo;, presenting five single positive affect items (\u003cem\u003einspired, alert, excited, enthusiastic, determined\u003c/em\u003e) and six negative affect items (\u003cem\u003eafraid, upset, nervous, distressed, jittery, annoyed\u003c/em\u003e). The affect items are rated on a scale of 1 (\u003cem\u003every slightly or not at all\u003c/em\u003e), 2 (\u003cem\u003ea little\u003c/em\u003e), 3 (\u003cem\u003emoderately\u003c/em\u003e), 4 (\u003cem\u003equite a bit\u003c/em\u003e), and 5 (\u003cem\u003every much\u003c/em\u003e). The items are derived from the short form of the PANAS (61, 63) (translation of one item adapted). Using the same item format and response scale, we additionally ask participants to rate their perceived stress. Next, we measure self-control using one positively and one negatively framed item adapted from the State Self-Control Capacity Scale (SMS-5, (72)): \u0026ldquo;At the moment, I feel like I have no willpower left\u0026rdquo; and \u0026ldquo;At the moment, I feel balanced\u0026rdquo;. Both items are rated on a scale from 1 (\u003cem\u003efully disagree\u003c/em\u003e) to 7 (\u003cem\u003efully agree\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneralizability\u003c/strong\u003e. At 9 pm, participants report whether they worked that day and, if so, the exact hours they worked. Participants then report how typical their day was using the item \u0026ldquo;Now think about your usual activities on a typical weekday or weekend day like today. Was today typical for your everyday life?\u0026rdquo;, with a 5-point Likert scale of 1 (\u003cem\u003enot at all or very little\u003c/em\u003e), 2 (\u003cem\u003ea little\u003c/em\u003e), 3 (\u003cem\u003eto some extent\u003c/em\u003e), 4 (\u003cem\u003ea lot\u003c/em\u003e), and 5 (\u003cem\u003eextremely\u003c/em\u003e). If the answer is \u0026ldquo;to some extent\u0026rdquo; or lower, participants are asked to provide additional information on that day. First, with the multiple-choice item \u0026ldquo;What made today less typical than usual?\u0026rdquo;, with the response format 1 (\u003cem\u003eless low back pain than usual\u003c/em\u003e), 2 (\u003cem\u003emore low back pain than usual\u003c/em\u003e), 3 (\u003cem\u003eless physical activity than usual\u003c/em\u003e), 4 (\u003cem\u003emore physical activity than usual\u003c/em\u003e), 5 (\u003cem\u003eother peculiarities\u003c/em\u003e). Second, with the open-ended question \u0026ldquo;What was different than usual?\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePower Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo test the micro-longitudinal hypotheses, an a priori power calculation for the LTPA outcome indicated that over \u003cem\u003en\u003c/em\u003e=2000 individuals (i.e., number of individuals required) and at least \u003cem\u003en\u003c/em\u003e=14 (i.e., number of repeated measures) would be required to detect small-sized population effects (given the unknown size of the cross-level interaction which is typically smaller than a main effect, (73)) with a power of \u0026gt;=.95. We aim to achieve this, but more realistically, assuming a power of \u0026gt;=.80, a sample size of at least \u003cem\u003en\u003c/em\u003e=200 (accounting for 30% attrition) is required to detect small-sized population effects (74).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses will be carried out both throughout the data collection process for monitoring purposes and at the end of the data collection. Descriptive statistics will be calculated for all variables (see Tables 1 and 2), together with plausibility checks, assessment of distribution characteristics, identification of outliers and analysis of missing data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBetween-Person Hypotheses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationship between physical activity and behavior-related health outcomes will be evaluated through regression models. Additionally, path analyses will be employed to test our hypotheses regarding longitudinal direct and indirect associations between theory-based psychological variables and LTPA (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWithin-Person Hypotheses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntra-class correlations (ICC), Pearson correlations, as well as repeated measures correlations (75) will be calculated. To account for the nested structure of the micro-longitudinal data, multilevel models will be calculated with the primary outcome (i.e., LTPA) and the secondary outcomes (e.g., LBP intensity, back health) as dependent variables. Based on the BHBM (Figure 1), psychosocial variables will be included as level-1 predictors. LBP chronicity status (i.e., participants with and without cLBP) will be considered a person-level predictor, moderating associations between within-person predictors and outcomes. We will specify multilevel models with fixed and random effects. Hypothesis testing for the fixed effects will provide insights into the relationships between LBP intensity, back health, LTPA, and its within-person and between-person predictors. To test the theoretical assumptions (Figure 1), we will specify within-person mediation models and estimate indirect effects. In collaboration with the research consortium, we will also investigate whether the association between LTPA and its predictors is of different size depending on, for example, sex, spinal morphology and mechanics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDissemination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study registration and this protocol are the first publications of the PRIA study. The results of this research will be reported to the funding agency (DFG), published in peer-reviewed international journals and presented at national and international conferences. In addition, wider dissemination to the public is planned through events such as the Long Night of Sciences (a public science fair) in Berlin and various media channels.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs part of a larger interdisciplinary research consortium, the PRIA study investigates diagnostic, preventive and therapeutic aspects of cLBP. It complements the current clinical diagnostic approach to cLBP by examining LBP intensity and back health in participants with and without cLBP in their everyday lives. In doing so, the study implements methods that go beyond cross-sectional analyses of data collected at a single point in time. The results of this study are expected to contribute to the development of improved diagnostics, for example by looking more closely at how physical activity and LBP intensity unfold in the daily lives of people with cLBP (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e), and effective, personalized interventions by addressing risk factors and resources for cLBP and back health in daily life. One promising avenue of prevention research is just-in-time adaptive interventions using mobile technology (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). Research that improves our understanding of the subtle connections between pain and physical activity can help shape psychotherapeutic and behavioral recommendations, potentially improving the health, longevity, and quality of life for people with chronic pain.\u003c/p\u003e \u003cp\u003eFor the prevention of cLBP, individuals are expected to be able to actively minimize psychosocial risk factors and build on resources, such as engaging in physical activity. In the context of cLBP, the latter may encompass both LTPA (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and adjustment and modification of back posture (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Currently, there is no consistent evidence on which types of physical activity (e.g., in terms of intensity, duration, and frequency of LTPA (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)) are most beneficial for people with cLBP to reduce pain intensity and promote back health, and evidence as to how the associations between pain and physical activity unfold at the momentary level (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). A deeper understanding of the associations between cLBP, different aspects of physical activity, and their theory-based psychological predictors is needed to guide future recommendations and interventions. With its comprehensive approach combining theory, evidence and assessment methods from health and pain psychology, but also drawing on insights from behavioral medicine, biomechanics and movement sciences, the PRIA intensive longitudinal study aims to advance the field of cLBP prevention and treatment.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eStrengths, Limitations, and Challenges\u003c/h2\u003e \u003cp\u003eA notable advance of the PRIA study, in line with previous studies in primary prevention of chronic pain (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), is its shift from a pathological perspective to a more resource-oriented approach to understanding cLBP (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). While previous research has focused primarily on examining modifiable risk factors such as health risk behaviors (e.g., heavy lifting, prolonged sitting) and negative health-related cognitions (e.g., fear of movement), the PRIA study broadens this scope. It examines these risk factors alongside theory-based, modifiable resources, including physical activity and self-efficacy, providing a more balanced view of cLBP prevention and management. A unique value of the PRIA study is that it examines psychosocial risk factors and resources in a cohort of individuals with and without cLBP. This will allow us to examine not only the role of resources and risk factors in the presence of pain (i.e., cohort of people with cLBP), but also the role of resources and risk factors in promoting back health (i.e., cohort of asymptomatic individuals). This approach will provide valuable insights for the development of effective behavioral interventions aimed at both the prevention of LBP and the promotion of back health.\u003c/p\u003e \u003cp\u003eIn addition to a traditional macro-longitudinal approach, the PRIA study utilizes an intensive longitudinal design that involves multiple sampling of participants' momentary experiences and behaviors in their everyday environments, rather than relying on isolated laboratory-based assessments. This allows for high temporal data resolution at the intra-individual level, providing new theoretical insights into the within-person dynamics of psychosocial and behavioral risks and resources associated with LBP over time in everyday life (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e). However, this approach also presents challenges, such as the potential for higher dropout rates and increased participant burden. To mitigate these risks, the study includes financial incentives and individualized feedback to improve participant retention and engagement. Another challenge may be the potential adverse effect of repeated pain assessments, which could increase the perception of pain by focusing the participant\u0026rsquo;s attention on adverse bodily experiences. However, recent research supports the usability and feasibility of EMA on a smartphone to collect real-time data on cLBP (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Importantly, the assessment of pain using smartphones does not appear to have a negative impact on pain intensity trajectories (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA key strength of the PRIA study is its multi-method approach to assessing physical activity, including both objective measures and self-reports. By using objective data on physical activity, the study helps to mitigate problems commonly associated with method variance, such as inflated correlations between self-reported predictors and self-reported outcomes. In addition, the use of accelerometry reduces the potential for over- or underestimation of physical activity. However, the use of accelerometers has limitations, including the potential for missing or unusable data, participant noncompliance with wearing the device, and technical malfunction. A major disadvantage of accelerometers is their inability to capture detailed information about the specific type of physical activity (e.g., yoga, walking). To address this, the PRIA study combines accelerometer data with self-reported measures of physical activity.\u003c/p\u003e \u003cp\u003eDespite the potential risks and limitations, the theoretical insights gained from our observational study are expected to improve the understanding of risk factors and protective resources related to cLBP. In particular, findings on the temporal dynamics of pain and modifiable resources and risk factors are expected to inform the development of mobile technology-based interventions (e.g., just-in-time-adaptive interventions, (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e)) that support behavioral approaches to both LBP treatment and back health promotion.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAE-FS \u0026ndash; Avoidance-Endurance Fast-Screen\u003c/p\u003e\n\u003cp\u003eBHBM \u0026ndash; Back Health Behavior Model\u003c/p\u003e\n\u003cp\u003eBMI \u0026ndash; Body mass index\u003c/p\u003e\n\u003cp\u003eB-PMM \u0026ndash; Back Posture, Movement and Mobility\u003c/p\u003e\n\u003cp\u003ecLBP \u0026ndash; chronic low back pain\u003c/p\u003e\n\u003cp\u003eCPGQ \u0026ndash; Chronic Pain Grade Questionnaire\u003c/p\u003e\n\u003cp\u003eDFG \u0026ndash; Deutsche Forschungsgemeinschaft (German Research Foundation)\u003c/p\u003e\n\u003cp\u003eDRKS \u0026ndash; Deutsches Register Klinischer Studien (German Clinical Trials Register)\u003c/p\u003e\n\u003cp\u003eEMA \u0026ndash; Ecological momentary assessment\u003c/p\u003e\n\u003cp\u003eEU \u0026ndash; European Union\u003c/p\u003e\n\u003cp\u003eFESS \u0026ndash; Fragebogen zur Erfassung der schmerzspezifischen Selbstwirksamkeit\u003c/p\u003e\n\u003cp\u003eFOR 5177 \u0026ndash; Forschungsgruppe 5177\u003c/p\u003e\n\u003cp\u003eGDPR \u0026ndash; General Data Protection Regulation\u003c/p\u003e\n\u003cp\u003eHAPA \u0026ndash; Health Action Process Approach\u003c/p\u003e\n\u003cp\u003eIPAQ \u0026ndash; International Physical Activity Questionnaire\u003c/p\u003e\n\u003cp\u003eLBP \u0026ndash; Low back pain\u003c/p\u003e\n\u003cp\u003eLTPA \u0026ndash; Leisure-time physical activity\u003c/p\u003e\n\u003cp\u003eMPI-D \u0026ndash; Multidimensional Pain Inventory, deutsche Version\u003c/p\u003e\n\u003cp\u003eMRI \u0026ndash; Magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eMSB \u0026ndash; Medical School Berlin\u003c/p\u003e\n\u003cp\u003eMQS \u0026ndash; Medication Quantification Scale\u003c/p\u003e\n\u003cp\u003eMVPA \u0026ndash; Moderate-to-vigorous physical activity\u003c/p\u003e\n\u003cp\u003ePAAM \u0026ndash; Physical Activity Adoption and Maintenance\u003c/p\u003e\n\u003cp\u003ePANAS \u0026ndash; Positive and Negative Affect Schedule\u003c/p\u003e\n\u003cp\u003ePAS \u0026ndash; Postural Awareness Scale\u003c/p\u003e\n\u003cp\u003ePCS \u0026ndash; Pain Catastrophizing Scale\u003c/p\u003e\n\u003cp\u003ePRIA \u0026ndash;\u0026nbsp;Psychologie und R\u0026uuml;ckengesundheit im Alltag\u003c/p\u003e\n\u003cp\u003ePSEQ \u0026ndash; Pain Self-Efficacy Questionnaire\u003c/p\u003e\n\u003cp\u003ePSS-10 \u0026ndash; 10-item Perceived Stress Scale\u003c/p\u003e\n\u003cp\u003eSCS-K-D \u0026ndash; German version of the Self-Control Scale\u003c/p\u003e\n\u003cp\u003eSF-12 \u0026ndash; 12-item Short-Form-Health-Survey\u003c/p\u003e\n\u003cp\u003eSMS-5 \u0026ndash; State Self-Control Capacity Scale\u003c/p\u003e\n\u003cp\u003eSTROBE \u0026ndash; Strengthening the Reporting of Observational studies in Epidemiology\u003c/p\u003e\n\u003cp\u003eT0 \u0026ndash; Time 0 (baseline assessment)\u003c/p\u003e\n\u003cp\u003eT1 \u0026ndash; Time 1 (first follow-up assessment)\u003c/p\u003e\n\u003cp\u003eT2 \u0026ndash; Time 2 (second follow-up assessment)\u003c/p\u003e\n\u003cp\u003eTSK \u0026ndash; Tampa Scale for Kinesiophobia\u003c/p\u003e\n\u003cp\u003eWHYMPI/MPI \u0026ndash; West Haven-Yale Multidimensional Pain Inventory\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe university\u0026rsquo;s ethics committee at the MSB Medical School Berlin approved the study on 03/08/2021 (approval number MSB-2021/59, amendment approved on 11/10/2023, amendment number MSB-2023/145). Ethical approval for the FOR 5177 initial screening was granted by Charit\u0026eacute; \u0026ndash; Universit\u0026auml;tsmedizin Berlin (EA1/058/21). Written informed consent is obtained from each participant before enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the research context of a chronic health issue, strict personal data protection is required. Study materials and anonymized data may be accessed upon request after the data collection is completed. Inquiries can be directed to Lena Fleig ([email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests: YES\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKarolina Kolodziejczak-Krupp\u0026rsquo;s position as Research Associate at MSB Medical School Berlin, Berlin, Germany is funded from Lena Fleig\u0026rsquo;s grant obtained by the German Research Foundation (DFG) to conduct the study (grant number: FL 879/2-1). Lena Fleig, Hendrik Schmidt, Matthias Pumberger, and Christoph Stein received funding from the German Research Foundation to conduct research within the FOR 5177.\u003cbr\u003eAll the other authors do not have any further conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for the PRIA study is provided by the German Research Foundation (project number 439742772) through grants FL 879/2-1 and STE 477/22-1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKKK and LF drafted the initial version of the protocol. LOW, LT, CS, TS, MP, and HS contributed valuable feedback for the revised manuscript. LF, CS, and MP serve as principal investigators for the study and secured its funding. HS, as spokesperson of the FOR 5177, is the lead principal investigator responsible for funding acquisition and research consortium oversight. LF, CS, TS, MP, and HS formulated the original research questions and designed the study methodology. KKK, VZ, and LF coordinate the study and collect the data. All authors have approved the final manuscript version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the entire FOR 5177 team, especially the study coordinators responsible for recruitment. Special thanks go to the study physicians who conduct the initial screening and to the student assistants involved in data collection and cleaning. The authors would like to acknowledge the time and effort that study participants put into data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerreira ML, de Luca K, Haile LM, Steinmetz JD, Culbreth GT, Cross M, et al. 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Comput Inf Nurs. 2019;37(5):276\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/cin.0000000000000478\u003c/span\u003e\u003cspan address=\"10.1097/cin.0000000000000478\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ecological Momentary Assessment, ambulatory assessment, accelerometry, back health, physical activity, back posture, Health Action Process Approach, fear avoidance model of pain, Back Health Behavior Model, prevention of low back pain","lastPublishedDoi":"10.21203/rs.3.rs-5965211/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5965211/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDespite the high prevalence of chronic low back pain (cLBP), its underlying mechanisms remain poorly understood. Addressing modifiable psychosocial resources and health behaviors such as physical activity offers a promising avenue for reducing the impact of cLBP. Furthermore, although the relationship between physical activity and pain is theorized as a within-person process, previous research has primarily focused on between-person differences. In this article, we present the protocol for the prospective observational study PRIA (Psychologie und Rückengesundheit im Alltag), which is part of a larger interdisciplinary research consortium investigating preventive, diagnostic and therapeutic aspects of cLBP. Drawing on theories from health and pain psychology, the outlined study examines the interplay between different dimensions of cLBP and back health, physical activity and their psychosocial determinants within individuals in their everyday lives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This prospective longitudinal study combines online questionnaires with Ecological Momentary Assessment (EMA) of health behaviors, cognitions, affect, social support, and pain using a smartphone-based app (movisensXS) and continuous measurement of physical activity by accelerometry (movisens Move 4). Parameters will be recorded at baseline (T0), daily for the following 14 days, 3 and 6 months later (T1 and T2). A total of 230 participants (115 individuals with cLBP and 115 without cLBP) aged 18 to 64 years will be enrolled. The associations between cLBP and the measured parameters will be examined using multilevel models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion:\u003c/strong\u003e The use of ambulatory assessment to examine physical activity, psychosocial factors, back health and pain in individuals’ daily lives addresses the limitations of previous research based on cross-sectional designs. This approach is expected to provide novel insights into the intraindividual and temporal dynamics of pain, back health, physical activity and psychosocial risk factors and resources. These findings are expected to contribute to the development of improved diagnostics, recommendations and interventions that leverage advances in mobile technology for more personalized and effective prevention and healthcare solutions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e This trial is registered in the German Clinical Trials Register, DRKS-ID DRKS00032978. Date of registration: 22 December 2022.\u003c/p\u003e","manuscriptTitle":"Physical activity and psychosocial characteristics of individuals with and without chronic low back pain in daily life: A study protocol for the PRIA intensive longitudinal study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-03 07:07:45","doi":"10.21203/rs.3.rs-5965211/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5c454f0a-1996-47e9-96b9-87ec195298cd","owner":[],"postedDate":"April 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-01T13:38:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-03 07:07:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5965211","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5965211","identity":"rs-5965211","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}