Abstract
Background
Early mobilization (EM) mitigates Post-Intensive Care Syndrome (PICS). However, kinesiophobia (fear of movement) driven by severe acute pain is often overlooked. This study aimed to identify acute pain trajectory phenotypes, evaluate their association with kinesiophobia, and explore outcomes under a PERMA-informed exploratory framework.
Methods
A single-center retrospective cohort study was conducted including surgical/trauma ICU patients (January 2021–December 2025). Group-based trajectory modeling (GBTM) identified latent classes of pain over the first 5 ICU days. Kinesiophobia and PERMA-related proxy variables (Relationships, Accomplishment) were extracted. Multivariable logistic regression, restricted cubic splines (RCS), and Cox proportional hazards models assessed outcomes.
Results
Among 586 eligible patients, four pain trajectories were identified: “Rapid Relief” (38.4%), “Persistent Moderate” (29.5%), “Delayed Onset/Flare-up” (21.3%), and “Persistent Severe” (10.8%). After adjusting for confounding factors, Delayed Onset (Adjusted OR 3.85, 95% CI 2.15–6.84) and Persistent Severe (Adjusted OR 6.12, 95% CI 3.25–11.56) trajectories were independently associated with kinesiophobia. RCS demonstrated a significant plateauing association between cumulative opioid doses and kinesiophobia. Patients with kinesiophobia exhibited significant delays in first out-of-bed mobilization, prolonged ICU lengths of stay, and a reduced likelihood of direct discharge to home. In adjusted outcome models, kinesiophobia was associated with delayed first target mobilization (HR 0.42, 95% CI 0.33–0.54, P<0.001) and lower odds of direct-to-home discharge (OR 0.21, 95% CI 0.14–0.32, P<0.001).
Conclusion
Acute pain in surgical/trauma ICU patients is highly heterogeneous. Higher-risk pain trajectory phenotypes were associated with kinesiophobia, which may represent a psychological barrier to functional recovery. Prospectively testing PERMA-informed strategies—particularly family support, meaning-oriented reframing, and goal-based achievement—may help clarify whether this approach can disrupt the pain-fear-immobility cycle.
Keywords: pain trajectory, kinesiophobia, early mobilization, intensive care unit, PERMA-informed framework, post-intensive care syndrome
Graphical Abstract
Introduction
The landscape of critical care survivorship has profoundly shifted over the past decade. While advancements in life-sustaining technologies have drastically reduced intensive care unit (ICU) mortality rates, an unprecedented number of survivors now face profound physical, cognitive, and psychological impairments collectively known as Post-Intensive Care Syndrome (PICS).1,2 Among the manifestations of PICS, ICU-acquired weakness (ICU-AW) is particularly devastating, affecting up to 50% of mechanically ventilated patients and leading to long-term functional disability, reduced quality of life, and increased 5-year mortality.3 Within this context, Early Mobilization (EM)—defined as structured physical activity initiated within 48 to 72 hours of ICU admission—has been universally endorsed as the gold standard intervention to mitigate ICU-AW and expedite recovery.4 However, translating this evidence into clinical practice within surgical and trauma ICUs remains a formidable challenge. Despite rigorous protocolization, compliance with EM in multidisciplinary surgical and trauma cohorts is alarmingly low, frequently falling below 30% globally.5,6 Traditional paradigms have predominantly attributed these low adherence rates to physiological instability, the presence of multiple invasive devices, or sheer illness severity.7 Consequently, the profound psychological barriers impeding patient participation have been systematically marginalized, with kinesiophobia—an excessive, irrational, and debilitating fear of physical movement resulting from a feeling of vulnerability to pain or reinjury—emerging as a critical blind spot in critical care nursing.8
For surgical and trauma patients (eg, those with massive pelvic fractures, severe blunt trauma, or major abdominal surgeries), acute tissue injury invariably triggers severe nociceptive stimuli, which remains a significant challenge in critical care pain management.9 According to the Fear-Avoidance Model of pain, catastrophic misinterpretations of pain signals lead to kinesiophobia, trapping patients in a vicious cycle of pain, fear, physical deconditioning, and prolonged immobility.10–12 In the ICU environment, kinesiophobia is often masqueraded as “non-compliance” or “delirium-related agitation”, a phenomenon that can significantly hinder post-ICU rehabilitation outcomes.11 Currently, the assessment of ICU pain is predominantly cross-sectional, relying on single-point scores such as the Numeric Rating Scale (NRS) or the Critical-Care Pain Observation Tool (CPOT).13,14 This static approach operates under the flawed assumption that pain is a uniform experience, blatantly ignoring the temporal dynamics and heterogeneity of pain resolution. Pain is an evolving physiological and psychological phenomenon; therefore, examining longitudinal pain trajectories (eg, rapid resolution, persistent severe pain, or delayed flare-ups) provides a vastly superior prognostic window into central sensitization and subsequent maladaptive psychological responses compared to isolated mean scores.15,16 Despite its robust application in chronic pain management and post-operative orthopedic settings, the utilization of Group-Based Trajectory Modeling (GBTM) to characterize acute pain evolution during the initial, highly vulnerable ICU days remains exceptionally scarce.
Furthermore, the conventional ICU response to severe acute pain relies heavily on an escalating pharmacological cascade—primarily intravenous opioids and sedatives.17 While essential for controlling physiological nociception, this unimodal “disease-elimination” approach fails to address the cognitive and psychological catastrophe underlying kinesiophobia, a condition characterized by a debilitating fear of movement.18 Excessive sedation further strips patients of their autonomy, exacerbating their sense of helplessness and contributing to physical decline post-ICU transfer.19 To effectively dismantle kinesiophobia, critical care nursing must transcend the mere suppression of agony and embrace positive psychological reconstruction. In this study, we innovatively introduce a PERMA-informed exploratory framework—a cornerstone of positive psychology comprising Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment—into the critical care rehabilitation continuum.20,21 Originating from Martin Seligman’s well-being theory, the PERMA model postulates that human flourishing is not merely the absence of suffering but the active cultivation of positive psychological assets.22 In the context of early ICU mobilization, kinesiophobia represents a total collapse of a patient’s bodily autonomy and meaning. We hypothesize that kinesiophobia cannot be reversed by analgesia alone; instead, it requires the establishment of secure inter-personal support (Relationships, facilitated by family presence),23 cognitive reframing of the rehabilitation process (Meaning), and the attainment of micro-rehabilitation goals (Accomplishment).24
Given these substantial literature gaps, there is an urgent need to dynamically phenotype acute pain and systematically unearth its interaction with psychological barriers during EM. Therefore, the objectives of this 5-year retrospective cohort study (2021–2025) are threefold: (1) to identify the latent trajectory phenotypes of acute pain over the first 5 days of admission in surgical/trauma ICU patients using GBTM; (2) to investigate the independent association between higher-risk pain trajectory phenotypes and the incidence of kinesiophobia during early rehabilitation, integrating proxy variables of the PERMA framework; and (3) to evaluate the associations of kinesiophobia with clinically relevant outcomes, including the time to achieve targeted mobilization, ICU length of stay, and discharge destination. We hypothesize that patients exhibiting persistent high or delayed-onset pain trajectories are at a significantly heightened risk of developing kinesiophobia, which may be associated with delayed functional recovery, and that integrating elements of the PERMA framework may offer novel pathways to mitigate this psychological paralysis.
Methods
Study Design and Setting
This single-center, retrospective, observational cohort study was conducted at a 3000-bed tertiary academic medical center equipped with a Level I trauma center. Clinical data were retrospectively queried from the hospital’s Electronic Medical Record (EMR) and Nursing Information System (NIS) for the period between January 1, 2021, and December 31, 2025. This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of The First Hospital of Hebei Medical University (S00057). Given the retrospective nature of the study, the requirement for informed written consent was waived. This manuscript was prepared strictly adhering to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, as recommended by the EQUATOR Network for high-quality observational research.25
Participants
The source population comprised all adult patients admitted to the surgical or trauma intensive care units during the 5-year study window. Inclusion criteria were defined as follows: (1) age ≥ 18 years; (2) primary ICU admission diagnosis of severe trauma (eg, multiple rib fractures, pelvic fractures) or post-operative monitoring following major elective/emergency surgery (eg, major abdominal surgery, spine reconstruction); (3) length of ICU stay ≥ 72 hours; and (4) ability to communicate and follow basic commands during the early rehabilitation window (defined as achieving a Richmond Agitation-Sedation Scale [RASS] score between −1 and +1). Patients were excluded if they met any of the following criteria: (1) pre-existing severe psychiatric illnesses (eg, schizophrenia) or cognitive impairments (eg, advanced dementia) documented prior to admission; (2) pre-existing neuromuscular disorders limiting mobility (eg, amyotrophic lateral sclerosis, severe stroke sequelae); (3) palliative care status or death within the first 72 hours; or (4) >10% missing values in core variables such as pain scores or nursing notes.
Data Extraction and Variable Definitions
Construction of Acute Pain Trajectories
Pain assessment was routinely performed by ICU nurses using the Numeric Rating Scale (NRS, 0–10) for self-reporting patients, or the Critical-Care Pain Observation Tool (CPOT, 0–8) for those unable to self-report. To harmonize the observational CPOT scale with the self-reported NRS scale for longitudinal modeling, CPOT scores were multiplied by a conversion factor of 1.25 to approximate a 0–10 scale. Because CPOT and NRS are not psychometrically interchangeable, this conversion was used only to place both measures on a common 0–10 modeling scale; findings were therefore checked in an NRS-only sensitivity analysis. Furthermore, to address potential discrepancies between observational and self-reported pain measures, an additional sensitivity analysis was conducted utilizing only patients who were assessed via the NRS scale. We extracted the highest pain score recorded during each 8-hour nursing shift over the first 5 days (120 hours) following ICU admission. The daily average of these peak scores was calculated to represent the daily acute pain burden. Day 1 to Day 5 were chosen as they represent the most acute inflammatory phase and the critical window for initiating EM.
Operational Definition of Kinesiophobia (Proxy)
Unlike prospective studies utilizing standardized questionnaires (eg, TSK-11), kinesiophobia in this retrospective cohort was identified via systematic textual analysis of the NIS and physical therapy logs. Two senior critical care nurses independently reviewed daily progress notes using a standardized coding guide based on the theoretical constructs of the Fear-Avoidance Model. The coding guide, including inclusion phrases, exclusion criteria, and representative examples, is provided in Supplementary Table 3. Reviewers were not fully blinded to the clinical context visible in contemporaneous notes; this limitation was mitigated by independent dual review, standardized coding rules, and third-reviewer adjudication. A positive manifestation of kinesiophobia was defined when documentation included explicit descriptions such as “patient expressed intense fear of wound rupture”, “patient exhibited extreme resistance/crying during turning”, or “refused out-of-bed mobilization strictly due to fear/anxiety”. To be classified as kinesiophobia, such events had to be documented ≥ 2 times during the EM sessions, after strictly excluding physiological intolerance (eg, hemodynamic instability, desaturation, or severe orthostatic hypotension). The inter-rater reliability between the two independent reviewers was high, yielding a Cohen’s Kappa statistic of 0.85. Discrepancies between the two reviewers were resolved through consensus with a third senior researcher.
PERMA Framework Proxies
To evaluate the impact of positive psychological variables under the exploratory PERMA framework, we established two robust proxy variables from the EMR. First, to represent “Relationships (R)” (interpersonal support), we quantified the frequency of family visits or bedside companion hours recorded in the ICU access logs, dichotomizing them into “High Family Support” (>3 visits/week) versus “Low Family Support”. Second, to represent “Accomplishment (A)”, we screened rehabilitation notes for terms indicating the patient’s active participation, such as “patient proactively requested to stand” or “patient celebrated completing the daily step goal”.
Clinical Outcomes
The primary outcomes of this study were functional recovery metrics: (1) time to achieve the first target mobilization level (defined as sitting independently on the edge of the bed or active standing, measured in days from ICU admission), and (2) total ICU length of stay (LOS). The secondary outcome was the discharge destination, categorized as a favorable discharge (direct discharge to home) versus an unfavorable discharge (transfer to a long-term acute care hospital [LTACH], skilled nursing facility, or discharged with extensive home health devices).
Statistical Analysis
Statistical analyses were performed using R software (version 4.3.0, R Foundation for Statistical Computing, Vienna, Austria). Continuous variables were expressed as mean ± standard deviation (SD) or median with interquartile range (IQR), while categorical variables were presented as frequencies and percentages. To identify latent phenotypes of acute pain over the first 5 days, we utilized Group-Based Trajectory Modeling (GBTM) via the lcmm package. The optimal number of latent classes (tested from 2 to 5 classes) was determined based on the lowest Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC), an average posterior probability >0.70 for each group, and clinical interpretability. Model fit statistics were compiled to thoroughly detail the model selection process.
After classifying patients into trajectory phenotypes, multivariable logistic regression models were employed to identify independent predictors of kinesiophobia. Adjustments were made for a priori confounders including age, sex, APACHE II score, surgery type (trauma vs general surgery), and cumulative opioid dose (converted to Morphine Milligram Equivalents, MME). Results are presented as Odds Ratios (OR) with 95% Confidence Intervals (CI).
Furthermore, to examine the non-linear association between cumulative pharmacological analgesia and kinesiophobia, we applied Restricted Cubic Splines (RCS) integrated into the logistic regression model, with four knots at 80, 150, 210, and 300 MME, corresponding to the 5th, 35th, 65th, and 95th percentiles of the observed cumulative MME distribution. Adjusted odds ratios were plotted using 80 MME as the reference value. Finally, a Cox proportional hazards model was constructed to evaluate the “time-to-event” impact of pain trajectories and kinesiophobia on achieving the first targeted mobilization, illustrated via forest plots. Given that kinesiophobia was identified during the early mobilization window, it was entered into the model as a time-varying covariate strictly evaluated prior to the achievement of the mobilization outcome to prevent immortal time bias. Patients were censored at 28 days, upon successful discharge, or death. The proportional hazards assumption was verified via Schoenfeld residuals testing. A two-tailed P-value < 0.05 was considered statistically significant.
Results
Baseline Characteristics
A total of 4,325 patients were initially screened from the ICU admission logs between January 2021 and December 2025. After applying the rigorous inclusion and exclusion criteria, a final analytical cohort of 586 eligible patients was included. The detailed stepwise selection and exclusion process is depicted in Figure 1. The cohort had a median age of 58.4 years (IQR: 45.2–69.1), and 61.2% were male. The primary admission diagnoses comprised severe trauma (55.1%, n=323) and major general surgery (44.9%, n=263). The median APACHE II score at admission was 18.5 (IQR: 14–22). Detailed baseline demographics, clinical severity, and cumulative analgesic use across the different identified trajectory subgroups are systematically summarized in Table 1.
Figure 1.
Study Flowchart of Patient Selection. The flowchart outlines the rigorous screening process according to STROBE guidelines. From an initial pool of 4,325 ICU admissions, sequential exclusions were made based on ICU length of stay, sedation/delirium status preventing interaction, missing data, and predefined clinical criteria, resulting in a final analytical cohort of 586 patients.
Table 1.
Baseline Demographic and Clinical Characteristics Stratified by Acute Pain Trajectory Phenotypes
| Characteristics | Overall (n = 586) |
Rapid Relief (n = 225) |
Persistent Moderate (n = 173) |
Delayed Onset (n = 125) |
Persistent Severe (n = 63) |
P-value |
|---|---|---|---|---|---|---|
| Demographics | ||||||
| Age (years), median (IQR) | 58.4 (45.2–69.1) | 57.2 (44.5–68.4) | 59.1 (46.0–69.5) | 58.8 (44.8–69.8) | 60.5 (48.1–70.2) | 0.412 |
| Male gender, n (%) | 359 (61.2) | 135 (60.0) | 108 (62.4) | 77 (61.6) | 39 (61.9) | 0.945 |
| Clinical Variables | ||||||
| APACHE II score, median (IQR) | 18.5 (14–22) | 16.5 (13–20) | 18.0 (14–22) | 20.5 (16–24) | 22.0 (17–26) | < 0.001 |
| Admission diagnosis, n (%) | 0.038 | |||||
| Severe Trauma | 323 (55.1) | 112 (49.8) | 98 (56.6) | 71 (56.8) | 42 (66.7) | |
| Major General Surgery | 263 (44.9) | 113 (50.2) | 75 (43.4) | 54 (43.2) | 21 (33.3) | |
| Mechanical ventilation days, median (IQR) | 4.2 (2.1–7.5) | 3.1 (1.8–5.4) | 4.5 (2.5–7.8) | 5.6 (3.0–8.5) | 6.8 (3.5–10.2) | < 0.001 |
| Cumulative MME (Day 1–5), mean ± SD | 185.4 ± 65.2 | 120.5 ± 35.4 | 175.2 ± 42.1 | 235.8 ± 55.6 | 310.4 ± 78.5 | < 0.001 |
| High Family Support (>3 visits/week), n (%) | 252 (43.0) | 105 (46.7) | 78 (45.1) | 48 (38.4) | 21 (33.3) | 0.124 |
| Primary Outcome | ||||||
| Incidence of Kinesiophobia, n (%) | 157 (26.8) | 20 (8.9) | 32 (18.5) | 57 (45.6) | 48 (76.2) | < 0.001 |
Notes: High family support serves as a proxy for the “Relationships” component within the PERMA-informed framework.
Abbreviations: APACHE II, Acute Physiology and Chronic Health Evaluation II; MME, Morphine Milligram Equivalents; IQR, Interquartile Range; SD, Standard Deviation.
Identification of Acute Pain Trajectories
Based on the daily average of shift-level peak pain scores across the first 5 ICU days, Group-Based Trajectory Modeling (GBTM) successfully identified four distinct latent pain trajectory phenotypes. The temporal evolution of pain scores for these four trajectories is visually depicted in Figure 2A. The 4-class model yielded the optimal fit parameters (lowest BIC=2845.3, highest entropy=0.88). A detailed summary of the model fit statistics, including AIC, BIC, entropy, and posterior probabilities for the 2- to 5-class models, is provided in Supplementary Table 1, validating the selection of the 4-class solution. Additionally, the sensitivity analysis restricted to patients evaluated exclusively via the NRS self-reported tool confirmed stable group proportions and risk profiles (Supplementary Table 2). As illustrated in the population distribution in Figure 2B, the classes were characterized as follows: Class 1 (“Rapid Relief”, 38.4%) showed initial moderate pain that quickly subsided; Class 2 (“Persistent Moderate”, 29.5%) maintained a baseline level of moderate discomfort throughout; Class 3 (“Delayed Onset/Flare-up”, 21.3%) presented an alarming pattern where initial control was followed by a sharp surge in pain around Day 3; and Class 4 (“Persistent Severe”, 10.8%) comprised patients sustaining critically high pain levels across all 5 days.
Figure 2.
Latent Class Trajectories of Acute Pain Evolution. (A) Overall trajectory plot derived from Group-Based Trajectory Modeling (GBTM) over the first 5 ICU days. The Y-axis represents the daily average of shift-level peak pain scores on a harmonized 0–10 scale. Four distinct phenotypes are displayed with 95% Confidence Intervals: Rapid Relief (green), Persistent Moderate (blue), Delayed Onset/Flare-up (Orange), and Persistent Severe (red). (B) Pie chart illustrating the proportion of the 586 patients assigned to each latent pain trajectory phenotype.
Predictors of Kinesiophobia and the Analgesic Dose-Response Relationship
The overall incidence of clinically defined kinesiophobia during early mobilization was 26.8% (157/586). Multivariable logistic regression analysis revealed that, after adjusting for APACHE II severity, surgical subtype, and mechanical ventilation duration, the Delayed Onset/Flare-up and Persistent Severe trajectories were independently associated with higher odds of kinesiophobia compared with the Rapid Relief trajectory (Delayed Onset/Flare-up: adjusted OR 3.85, 95% CI 2.15–6.84; Persistent Severe: adjusted OR 6.12, 95% CI 3.25–11.56), as detailed in Table 2. Notably, the PERMA framework proxy variable for Relationships—represented by high family visitation—was associated with lower odds of kinesiophobia (adjusted OR 0.45, 95% CI 0.28–0.72, P=0.001).
Table 2.
Multivariable Logistic Regression Analysis of Predictors for Kinesiophobia During Early Mobilization
| Predictors | Unadjusted OR (95% CI) |
P-value | Adjusted OR (95% CI) |
P-value |
|---|---|---|---|---|
| Pain Trajectory Phenotypes | ||||
| Rapid Relief (Class 1) | Reference | - | Reference | - |
| Persistent Moderate (Class 2) | 1.65 (0.85–3.21) | 0.142 | 1.42 (0.75–2.85) | 0.265 |
| Delayed Onset/Flare-up (Class 3) | 4.55 (2.56–8.12) | < 0.001 | 3.85 (2.15–6.84) | < 0.001 |
| Persistent Severe (Class 4) | 8.24 (4.65–14.62) | < 0.001 | 6.12 (3.25–11.56) | < 0.001 |
| PERMA-Informed Framework Proxy | ||||
| High Family Support (Yes vs No) | 0.40 (0.26–0.62) | < 0.001 | 0.45 (0.28–0.72) | 0.001 |
| Clinical Confounders | ||||
| APACHE II Score (per 1 point increase) | 1.12 (1.05–1.18) | 0.002 | 1.06 (1.01–1.12) | 0.045 |
| Admission Type (Trauma vs Gen Surgery) | 1.45 (1.08–1.95) | 0.015 | 1.25 (0.88–1.78) | 0.210 |
| Cumulative MME (per 50 units increase) | 1.38 (1.20–1.58) | < 0.001 | 1.18 (1.02–1.36) | 0.032 |
Notes: The model was adjusted for age, gender, admission diagnosis, APACHE II score, mechanical ventilation duration, and cumulative MME. Bolded values indicate statistical significance (P < 0.05).
Abbreviations: OR, Odds Ratio; CI, Confidence Interval; APACHE II, Acute Physiology and Chronic Health Evaluation II; MME, Morphine Milligram Equivalents.
To further examine whether escalating pharmacological analgesia was associated with kinesiophobia across the observed dose range, we utilized Restricted Cubic Splines (RCS). The analysis demonstrated a significant non-linear association between cumulative opioid dosage and kinesiophobia (P for non-linearity = 0.012), with the adjusted odds ratio curve tending to plateau at higher MME levels (Figure 3A). This pattern should be interpreted as an observational plateauing association rather than evidence of a causal pharmacological threshold. When stratified by admission diagnosis, the point-estimate curves suggested similar plateauing patterns across both the trauma subgroup and the major general surgery subgroup (Figure 3B).
Figure 3.
Restricted Cubic Splines (RCS) Revealing the Analgesic Dose-Response Relationship. (A) Overall adjusted odds ratios for kinesiophobia across cumulative opioid dose (MME), with shaded bands representing 95% confidence intervals and 80 MME as the reference. (B) Diagnosis-stratified adjusted point-estimate curves for trauma and general surgery; confidence bands are omitted for visual clarity. The curves suggest a plateauing association at higher MME levels; this should not be interpreted as proof of a causal pharmacological threshold.
Impact of Kinesiophobia on Functional Recovery and Clinical Outcomes
Kinesiophobia was associated with slower achievement of first targeted out-of-bed mobilization. In the Cox model, kinesiophobia was associated with a lower daily hazard of achieving target mobilization (HR 0.42, 95% CI 0.33–0.54, P<0.001), with no evidence of violation of the proportional hazards assumption (Schoenfeld global P=0.42) (Figure 4A). In the discharge model, kinesiophobia was also associated with lower odds of direct-to-home discharge (OR 0.21, 95% CI 0.14–0.32, P<0.001) (Figure 4B). These findings should be interpreted as adjusted observational associations rather than causal effects.
Figure 4.
Forest Plots Demonstrating the Impact of Kinesiophobia on Clinical Outcomes. (A) Cox proportional hazards model for the time to achieve the first target out-of-bed mobilization. The presence of kinesiophobia significantly reduces the probability of timely mobilization. (B) Multivariable logistic regression for discharge destination, showing the adjusted association between kinesiophobia and lower odds of favorable direct-to-home discharge.
Discussion
Summary of Principal Findings
This 5-year retrospective cohort study conceptualized acute pain in the surgical and trauma ICU as a dynamic trajectory and examined its association with kinesiophobia under a PERMA-informed positive psychology framework. We found that Delayed Onset/Flare-up and Persistent Severe pain phenotypes were strongly associated with movement-related fear. The RCS analysis suggested a plateauing association between cumulative opioid exposure and kinesiophobia at higher dose levels. In contrast, PERMA-related proxies—particularly strong family relationships and goal achievement—were associated with lower kinesiophobia risk and more favorable recovery indicators.
Contrasting Pain Heterogeneity with Static Paradigms
Historically, ICU pain management has been dictated by single-point, cross-sectional assessments. Foundational studies, such as those by Payen et al (2007) on sedation and analgesia practices, generally presumed a static view of pain assessment in critically ill patients.26 Our application of GBTM critically challenges this static paradigm by exposing a much more complex reality—most notably, the “Delayed Onset/Flare-up” phenotype. This delayed surge mirrors the “rebound pain” trajectories previously observed in post-operative orthopedic cohorts by Chapman et al.16 In our ICU setting, we hypothesize that this phenomenon is heavily influenced by critical care transitions, such as the protocolized management of analgesia and sedation during awakening, as described by Skrobik et al.27 Furthermore, from a neurobiological perspective, initial trauma can trigger secondary hyperalgesia and central sensitization, which are considered manifestations of central nervous system plasticity.28 When a patient awakens expecting recovery but is instead confronted by a secondary pain surge, it induces a severe psychological mismatch. This mismatch is significant because psychological factors, such as pain beliefs and catastrophizing, are strongly associated with pain intensity and disability outcomes in chronic pain conditions.29,30
The Analgesic Paradox and the Fear-Avoidance Model
Baseline nociceptive control remains essential before physical therapy. However, our restricted cubic spline analysis showed a non-linear association between opioid exposure and kinesiophobia, with a plateauing pattern at higher opioid doses. This finding is compatible with the Fear-Avoidance Model established by Vlaeyen and Linton,10 although causal inference is limited by the retrospective observational design. Kinesiophobia is not merely the sensation of pain; it reflects catastrophic misinterpretation of mechanical stress as impending bodily rupture. As such, it may not be eliminated simply by escalating opioid exposure. Our results are also consistent with reports that high opioid exposure in trauma patients can be accompanied by delirium, cognitive clouding, and loss of control,31,32 factors that may reinforce refusal to mobilize.
PERMA-Informed Interpretation and Clinical Implications
Conventional responses to ICU patients who are “uncooperative” during mobilization often default to physical restraints or reinstitution of sedation.33 In contrast, our study provides real-world proxy data suggesting the potential relevance of a PERMA-informed approach (Positive Emotion, Engagement, Relationships, Meaning, Accomplishment).21 Although only Relationships and Accomplishment could be operationalized retrospectively, these proxies map onto clinically meaningful bedside strategies. Active family support (Relationships) was associated with lower odds of kinesiophobia and is consistent with family-centered ICU care championed by Davidson et al34 and others.35 Families may act as emotional anchors that regulate sympathetic hyperarousal. Goal-oriented mobilization milestones may support Accomplishment and restore a sense of control. Prospective interventions should directly measure the other PERMA domains, especially Positive Emotion, Engagement, and Meaning, before claims of framework-level validation are made. While our study retrospectively analyzed Accomplishment through goal-oriented nursing logs, implementing prospective cognitive reframing (Meaning) to restructure the patient’s catastrophic beliefs into an understanding of tissue healing could proactively dismantle movement-related fear. This hypothesis-generating interpretation is consistent with prior positive psychology and psychologically informed rehabilitation studies,36 supporting the need to prospectively test PERMA-informed or psychologically informed rehabilitation strategies in ICU populations.37
Strengths and Limitations
Compared to existing cross-sectional surveys, the primary strength of this study is the utilization of advanced trajectory modeling on a large longitudinal sample, allowing for a dynamic understanding of pain. Additionally, it represents an exploratory effort to examine PERMA-related proxy variables using clinical data. However, inherent limitations of retrospective designs must be acknowledged. Extracting psychological variables from nursing text logs, rather than utilizing validated psychometric tools (eg, Tampa Scale of Kinesiophobia), introduces reporting bias, and reviewers were not fully blinded to the clinical context contained in the notes. Similarly, harmonizing CPOT and NRS scores may have introduced measurement error because observational and self-reported pain scores capture related but non-identical constructs. The NRS-only sensitivity analysis should therefore be interpreted as supportive rather than definitive. Furthermore, a major limitation is our inability to comprehensively evaluate the entire PERMA framework. Because data were mined retrospectively, we could only construct proxy variables for Relationships and Accomplishment, lacking direct measures for Positive Emotion, Engagement, and Meaning. Thus, our results represent a PERMA-informed exploratory analysis rather than a holistic test of the psychological model. Unmeasured confounders, such as pre-hospital chronic pain history or baseline opioid tolerance, may have also influenced trajectory assignments.
Future Directions
To inform clinical guidelines, future research should shift from retrospective observation to prospective, multicenter randomized or pragmatic implementation studies. These studies should test structured, PERMA-informed nursing protocols—integrating family members as active rehabilitation coaches and employing daily interactive goal-attainment strategies while utilizing validated psychometric surveys across all five PERMA domains—against standard pharmacological care, aiming to reduce kinesiophobia and optimize early mobilization.
Conclusion
Acute pain in surgical and trauma ICU patients was heterogeneous, with Delayed Onset/Flare-up and Persistent Severe trajectories showing strong associations with kinesiophobia. Kinesiophobia was associated with delayed functional recovery and lower odds of direct-to-home discharge. Opioid escalation showed a plateauing association with kinesiophobia at higher cumulative doses, suggesting that pharmacological analgesia alone may not fully address movement-related fear. PERMA-informed strategies, particularly family support and goal-based rehabilitation milestones, warrant prospective evaluation as adjunctive approaches to early mobilization.
Funding Statement
This work was supported by the Medical Science Research Project of Hebei (Grant Nos. 20241935, 20270149, and 20270186).
Abbreviations
ICU, Intensive Care Unit; PERMA, Positive Emotion, Engagement, Relationships, Meaning, Accomplishment; PICS, Post-Intensive Care Syndrome; ICU-AW, Intensive Care Unit-Acquired Weakness; GBTM, Group-Based Trajectory Modeling; EM, Early Mobilization; NRS, Numeric Rating Scale; CPOT, Critical-Care Pain Observation Tool; OR, Odds Ratio; HR, Hazard Ratio; CI, Confidence Interval.
Data Sharing Statement
The datasets generated and/or analysed during the current study are not publicly available due to the protection of patient privacy and institutional data security policies, but are available from the corresponding author, Xiaoqiu Liu, upon reasonable request.
Ethics Approval and Consent to Participate
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of The First Hospital of Hebei Medical University (S00057). Given the retrospective observational nature of the study, the requirement for written informed consent was waived by the Ethics Committee of The First Hospital of Hebei Medical University. Patient data confidentiality was strictly maintained throughout the study.
Author Contributions
Jie Ma and Xiaoqiu Liu are co-corresponding authors. Xiaoqiu Liu is the lead corresponding author. All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
Yun Li and Hao Wang are co-first authors for this study. The authors declare that they have no competing interests in this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analysed during the current study are not publicly available due to the protection of patient privacy and institutional data security policies, but are available from the corresponding author, Xiaoqiu Liu, upon reasonable request.