Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivity.

Pain variability can be partially attributed to psycho-cognitive features involved in its processing. However, accumulating research suggests that simple linear correlation between situational and dispositional factors may not be sufficiently explanatory, with some positing a role for mediating influences. In addition, acute pain processing studies generally focus on a post-operative model with less attention provided to post-traumatic injury. As such, this study aimed to investigate a more comprehensive pain processing model that included direct and indirect associations between acute pain intensity in the head and neck, pain catastrophizing (using pain catastrophizing scale (PCS)), and pain sensitivity (using the pain sensitivity questionnaire (PSQ)), among 239 patients with post-motor vehicle collision pain. The effect of personality traits (using Ten Items Personality Inventory (TIPI)) and emotional status (using Hospital Anxiety and Depression Scale (HADS) and Perceived Stress Scale (PSS)) on that model was examined as well. To this end, three Structural Equation Modeling (SEM) analyses were conducted. Overall, the data had good fit to all the models, with only PSQ found to have a direct correlation with acute pain intensity. The SEM analyses conversely revealed several mediations. Specifically, that: first, PSQ fully mediated the relationship between PCS and pain intensity; second, PCS and PSQ together fully mediated the relationship between conscientiousness (personality trait) and pain intensity; and finally, emotional status had direct and indirect links with PSQ and pain intensity. In conclusion, these models suggest that during the acute post-collision phase, pain sensitivity intermediates between emotional states and personality traits, partially via elevated pain catastrophizing thoughts.

1. Introduction

Nearly half of individuals who suffer acute pain due to injury resultant from motor vehicle collisions will go on to report chronic pain [1, 2]. As such the need to explore potential predictors which affect the transition from acute to chronic pain is obvious. However, while much research addresses the correlation between personal traits and emotional states with the psychology of pain among chronic pain patients, affective processing is less well-understood in the context of acute pain intensity, such as that of post-collision. Given that, enhanced acute pain intensity is the main predictor for chronic pain, addressing the dynamic role of psycho-cognitive features as well as processes that underlie sensory and affective responses to nociceptive input during the early acute pain phase may shed more light on the observed variability in the magnitude of the pain experience [3-6].

A traditionally key element in determining variability in pain intensity is pain catastrophizing (PC), which was conceptualized as the tendency to overestimate the severity and consequence of pain [7]. To quantify PC, the Pain Catastrophizing Scale (PCS) was developed to incorporate feature of rumination, magnification, and helplessness toward pain, assumed to attain either situational or dispositional elements [7, 8]. While the latter is considered as a stable characteristic, the former might be manifested in more flexible manner, such that under particular circumstances, the expression of situational features may be altered after an exposure to a demanding situation in either a short- or long-term manner. Although, the link between PCS and pain can be changed over time—highlighting its situational characteristic, previous studies have proposed a reciprocal relationship between situational and dispositional PC. Namely, dispositional PC can be linked with pain intensity in the case that the nociceptive stimulus or the painful event evokes enhanced situational PC and vice versa [8-10].

Indeed, the PCS is a generally well-accepted predictor of negative pain-related outcomes and enhanced pain experience in both acute and chronic pain conditions [11-13]. Nevertheless, recent studies reported that PCS ratings were not associated with acute pain intensity [14-17]. Interestingly, higher pain sensitivity ratings, as obtained by the Pain Sensitivity Questionnaire (PSQ), which assume to depict perceived or imagined response to various everyday pain situations, were found to be directly associated with augmented intensity of acute pain experience [17]. Thus, PCS and PSQ warrant consideration, as either or both may serve either directly or indirectly as indicators of psycho-cognitive pain processing. In that they reflect the manner in which cognitive representation, memories and imagination toward pain shape its experience.

Two conceptual frameworks may be relevant to attain a broader understanding about the relationships of pain catastrophizing and pain sensitivity as well as personal traits and emotional states. First, the fear-avoidance model [18] indicates that an individual with catastrophic thoughts toward pain following injury will tend to avoid activities due to the manner in which the neuromatrix of nociceptive modulation processing enhances pain sensitivity which then determines pain experience. Accordingly, higher PC will directly augment pain sensitivity as expressed by enhanced pain intensity ratings. Based on this concept we hypothesized that:

Hypothesis 1: Higher pain catastrophizing ratings will be associated with higher pain sensitivity, which in turn will be associated with higher acute pain intensity.

The second theoretical framework is the disposition and adjustment to chronic pain model [19] which suggest that personality traits and emotional states (i.e., mental states) might shape PC based on the individual vulnerability (e.g., stress, anxiety) and resource characteristics available (e.g., extraversion, consciousness) toward pain. While an individual’s vulnerability characteristics shape PC through activation of physiological mechanisms evoked in response to nociceptive stimulus, individual resource characteristics shape adaptive coping mechanism recruited to allow them to manage their response to pain. Thus, each individual is located in a different position on the continuum of pain modulation profiles [20] due to the specific amalgamation of ’stable-dispositional’ and ‘temporary-situational’ personal characteristics [21, 22]. This notion was supported by recent publications highlighting the role of mediation and/or moderation effects [23]. For example, PCS was found as mediator between personality traits and pain intensity [24-26]. Specifically, higher scores on agreeableness, extraversion, open to experiences, and conscientiousness (e.g., resource characteristics) were associated with lower PCS and higher scores on neuroticism (e.g., vulnerability characteristic) were associated with higher PCS [27]. The role of PCS, as an independent variable in Hypothesis 1, might also be mediated through pain sensitivity.

Hypothesis 2a: Higher scores on personality traits considered ‘resources’ according to the disposition and adjustment to chronic pain model will be associated with lower pain catastrophizing ratings, which will in turn be associated with lower pain sensitivity, resulting in lower acute pain intensity.

Hypothesis 2b: Higher scores on personality traits considered ‘vulnerabilities’ according to the disposition and adjustment to chronic pain model will be associated with higher pain catastrophizing ratings, which in turn will be associated with higher pain sensitivity, leading to higher acute pain intensity.

Furthermore, emotional states associated with the post-injury circumstance, such as stress, depression, and anxiety, have been linked with PC [28, 29]. With this, mounting research has failed to find direct correlations between state anxiety and depression, and pain in acute post-operative patients [30-32], and emotional elements have been found to be only mildly related to PSQ [33, 34]. Thus, it is possible that the three are interrelated, where emotional state elements (i.e., emotional status) might be indirectly related to pain intensity through PC, and as suggested in Hypothesis 1, through pain sensitivity.

Hypothesis 3: A heightened post-collision emotional status will be linked to higher PC ratings, followed by higher pain sensitivity and consequently higher acute pain ratings.

To explore these hypotheses, we chose to apply structural equation modeling (SEM), an advanced statistical approach, which allows for the simultaneous examination of direct and indirect relationships among latent dispositional and situational characteristics, and acute post-traumatic pain intensity. Specifically, the current study aimed to test three models (Fig 1). The first aimed to explore the mediating role of pain sensitivity in the link between PC and acute post-traumatic pain intensity; the second aimed to investigate how the first model is affected by personality traits; and finally, the third aimed to examine how the first model is affected by emotional status.

Fig 1

Outline of proposed SEM analyses.

2. Methods

2.1. Study design

Patients are part of a larger prospective non-interventional study where initial data was collected between March 2016 and December 2019. A session was scheduled within 72 hours post-injury for MRI, clinical, psychophysical (i.e., experimentally induced pain assessment), psycho-cognitive and neurophysiological assessment which was completed at the testing site. Additionally, blood was drawn for genetics and patients’ demographic and clinical baseline assessments (i.e., socio-demographic information, self-reported pain levels, areas of post-accident body pain, and use of analgesics) were obtained. For more information on the full study protocol please see our previous work [17, 35, 36].

2.2. Study population

2.2.1. Participants

Patients were recruited when visiting the Rambam HealthCare Campus Emergency Room in Haifa, Israel. Inclusion criteria: road accident up to 24 hours before ER arrival; direct or indirect head and neck injury with reports of pain, Glasgow coma scale (GCS) 13–15 with no subsequent decline; no traumatic findings in computed tomography (CT) if performed; age 18–70, both males and females. Exclusion criteria: lack of ability to communicate in Hebrew; other major bodily injuries from the accident; prior chronic head/neck pain that requires regular treatment; neurological disease that might affect testing ability or interpretation such as neurodegenerative diseases; any head and neck injury in past year; any pain condition that requires daily dose of pain medication. The institutional review board of Rambam Health Care Campus approved the study protocol in accordance with The International Helsinki Declaration (No. 0601–14). Written informed consent was obtained from each participant in the presence of a certified physician prior to any data collection or assessment.

2.3. Measures

2.3.1. Dependent measure

2.3.1.1. Acute pain intensity. Was assessed via a Visual Analog Scale (VAS) scale of 0–100 (0 represents ‘no pain’, 100 represents ‘worst pain imaginable’) for the following parameters as it related to the preceding 24h: mean pain scores in the neck and in the head. Participants provided this rating via a custom made smart-phone application. As the cohort was comprised of post-collision individuals, and the study focused on the trajectory of individuals with initial area-of-injury pain (i.e., head and neck), the mean rating for both were considered primary outcome measures in the current study.

2.3.2. Independent measures

2.3.2.1. The Ten Items Personality Inventory (TIPI). [37, 38], is a questionnaire used to assess the 5 dimensions of the Five Factor Model (FFM) of personality (neuroticism, extraversion, conscientiousness, open to experiences, agreeableness). Each factor is independent and includes pairs of personality trait descriptors rated on a 7-point Likert scale (1 = strongly agree to 7 = strongly disagree). Sample items include the following: “I see myself as anxious or easily upset” and “I see myself as dependable or self-disciplined.” Scores are averaged for each factor, where each personality factor represents a continuum of trait characteristic that ranges between two anchors in which the middle point represents the baseline [39].

2.3.2.2. Emotional status. This latent variable contained two measures that represent emotional status. Higher scores are considered as higher emotional distress (i.e., high stress, anxiety, and depression levels).

2.3.2.3. Perceived Stress Scale (PSS). [40]- a self-report 10-item questionnaire devised to measure the perception of stress. It is a measure of the degree to which situations which occurred within the last month are appraised as stressful. The items are designed to assess how unpredictable (‘how often have you been upset because of something that happened unexpectedly), uncontrollable (‘how often have you felt that you were unable to control the important things in your life?’) and overloaded (‘how often have you felt that you were on top of things?’) the subjects find their lives to be. The items are rated from 0 (‘never’) to 4 (‘very often’), 6 items are worded negative and 4 are positive. The subjects were instructed to relate to the accident as part of their last month. Cronbach alpha in the current study was 0.783.

2.3.2.4. Hospital Anxiety and Depression Scale (HADS). [41]- a self-report 14-item questionnaire devised to be used to measure anxiety and depression in individuals with physical health problems. The questionnaire focuses on non-physical symptoms so that it can be used to diagnose depression in people with significant physical ill health. The items are rated from 0 (negative response) to 3 (very positive response). Seven of the items relate to anxiety, and 7 depression, and as such HADS provides two scores. The range for each subscale is 0–21 points, with higher scores indicating more symptoms of anxiety and depression. Cronbach alpha in the current study was 0.866 for anxiety and 0.727 for depression.

2.3.3. Mediating measures

Patients filled out the following questionnaires, using the Hebrew validated version [11, 42]:

2.3.3.1. Pain Catastrophizing Scale (PCS). [7]—a self-report 13-item questionnaire providing ratings based on painful life situations. Catastrophizing is conceptualized by cognitions related to the inability to tolerate painful situations, thinking pain is unbearable, or ruminating on the worst possible outcomes from the pain which is being experienced. As such, the instrument represents the three components of pain catastrophizing: rumination (e.g., “I can’t seem to keep it out of my mind”); magnification (e.g., “I wonder whether something serious may happen”); and helplessness (e.g., “There is nothing I can do to reduce the intensity of pain”). Participants are asked to rate each statement on a 5-point Likert scale ranging from 0 (‘not at all’) to 4 (‘always’). The PCS provides a total score and three sub-scores. The three sub-scores of PCS were used for analysis. Patients were not directed to focus on any particular pain event they experienced in the past [7]. Cronbach alpha in the current study was 0.896.

2.3.3.2. Pain Sensitivity Questionnaire (PSQ). [43]—a self-report 17-item questionnaire, based on pain intensity ratings of imagined painful daily life situations touching on various somatosensory sub-modalities. The items are rated from 0 (‘not painful at all’) to 10 (‘worst pain imaginable’), and span various thermal, chemical, and mechanical pain modalities, noxious intensities and body sites. 14 items relate to situations that are painful for the majority of persons. For example: "Imagine you trap your finger in a drawer" and "Imagine you pick up a hot pot by inadvertently grabbing its equally hot handles". The remaining 3 items describe normally non-painful situations. For example: "Taking a warm shower". The latter are interspersed in order to serve as non-painful sensory references for the subjects. The PSQ provides a total score and two sub-scores of minor and moderate. The PSQ total score was calculated as the average rating of all but the three non-painful items. A higher PSQ score indicates higher pain sensitivity. Cronbach alpha in the current study was 0.932.

2.3.4 Control variables

As suggested in previous studies [e.g., 44], we collected participants’ age and gender to control for possible effects on pain perception.

2.4. Statistical analysis

First, descriptive statistics (mean and standard deviation, and proportions, as appropriate) and correlations were conducted for all study’s variables. Second, SEM mediation analyses were conducted. The SEM models were based on recent recommendations for mediation examination [45], where the independent variable can be linked to the dependent variable only through the mediator. Following Bowen and Guo’s [46] recommendation, alternative models that are based on the conservative recommendation of Baron and Kenny (1986), where the independent variable must have a direct link with the dependent variable [47], were also conducted. Specifically, six SEM analyses that simultaneously examined the direct and indirect relationships among personality traits, emotional status, PCS, PSQ, and head and neck pain intensity ratings were performed in addition to the inclusion of known control variables (i.e., gender and age). This analysis was comprised of three primary SEM analyses and an alternative model for each one, which examined a direct path between the independent variables and head and neck pain intensity ratings to emphasize best fit.

The fit of the data to the model was assessed, as accepted in the field of SEM [46], using a maximum likelihood estimator and several fit indices: the chi-square test (χ2), the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). The data were assumed to fit the model when the non-significant chi-square test [48]; the obtained CFI and TLI were greater than 0.90; and the obtained RMSEA was lower than 0.06 [49]. In order to determine whether the initial model or the alternative model is the preferred one, the difference in chi-squares and degrees of freedom between the initial model and the alternative model was examined using the chi square distribution table. A non-significant difference between the models indicated that the simpler model (with more degrees of freedom) is the preferred model. However, a significant difference between the models indicates that the less parsimonious model is the preferred one [46]. A minimum sample size of 138 for the first model, 200 for the second model, and 156 for the third model was needed to detect a small effect size with a power of 80% under alpha .05 [50, 51]. Descriptive statistics and bivariate analyses were performed using SPSS software version 25, and models were tested using SEM using IBM SPSS AMOS version 25.0. Significance was set at p < 0.05.

3. Results

3.1. Description of study cohort

A total of 239 acute post-collision patients were included in this study. About half were male (n = 134, 56.1%), aged 37.6 (±12.4) years on average (range 18–67 years old). The mean pain intensity ratings were 47.65 (±27.66) and 52.49 (±28.13) for head and neck pain, respectively. Descriptive statistics of study variables are presented in Table 1.

Table 1

Descriptive statistics of study variables.

Study variables	Mean	St. Deviation
Head pain	47.65	27.66
Neck pain	52.49	28.13
PSQ–pain sensitivity
PSQ- total	4.84	1.74
PSQ-minor	3.88	1.86
PSQ-moderate	5.30	1.79
PCS—Pain catastrophizing
Total score	23.46	11.48
Rumination	8.60	4.35
Magnification	4.79	2.88
Helplessness	10.07	5.88
TIPI–Personality traits
Extraversion	3.47	1.46
Agreeableness	4.98	1.05
Neuroticism	5.91	1.08
Conscientiousness	4.84	1.36
Open to experiences	5.43	1.12
Emotional status
HADS–Anxiety	6.65	4.99
HADS–Depression	3.80	3.24
PSS–Stress	14.54	6.68

3.2. Correlations between study variables

Some preliminary support for our hypotheses were observed in the Pearson correlation matrix (Table 2). First, PCS and PSQ scores were significantly linked (r = .31; p<0.001). Second, only PSQ scores were directly correlated with acute pain intensity for both the head (r = .22, p = 0.001) and neck (r = .22, p<0.001). Moreover, PCS scores were significantly related to conscientiousness (r = -.27; p<0.001), anxiety (r = .19; p<0.001), depression (r = .29; p<0.001), and stress (r = .37; p<0.001).

Table 2

Correlations between study variables.

Study variables	1.	2.	3.	4.	5.	6.	7.	.8	9.	10.	11.	12.
1. PCS total	1
2. PSQ total	.31 * *	1
3. Extraversion	-.06	.00	1
4. Agreeableness	-.04	-.00	-.21 * *	1
5. Neuroticism	-.00	-.01	-.13	.21 * *	1
6. Conscientiousness	-.27 * *	-.20 * *	-.22 * *	.13	.09	1
7. Open to experiences	-.09	-.08	.06	.07	.07	.12	1
8. Anxiety	.19 * *	.13	.16 *	-.11	.04	-.28 * *	-.05	1
9. Depression	.29 * *	.24 * *	-.05	-.08	-.03	-.24 * *	-.19 * *	.32 * *	1
10. Stress	.37 * *	.19 * *	.08	-.14 *	-.15 *	-.38 * *	-.00	.34 * *	.39 * *	1
11. Head Pain Avg	.07	.22 * *	.04	.01	.01	-.02	.01	.05	.07	.02	1
12. Neck Pain Avg	.02	.22 * *	.02	-.04	.02	.00	.04	-.00	-.04	.05	.55 * *	1

3.3. Structural Equation Model (SEM) analyses

The first SEM analysis model simultaneously examined the direct and indirect relationships among the latent independent variable pain catastrophizing (rumination, magnification, and helplessness subscales), the latent mediator pain sensitivity (mild and moderate subscales) and acute head and neck pain, adjusting for age and gender (Fig 2).

Fig 2

SEM analysis of the direct and indirect link between PCS, PSQ and head or neck pain intensity ratings.

Note: Estimates in black represent the model with head pain as an outcome and estimates in grey represent the model with neck pain as an outcome. *p < .05 **p < .001.

The data had a good fit to the models according to the fit indices as presented in Fig 2. Pain catastrophizing was significantly associated with pain sensitivity for head and neck pain models (γ = .36 and γ = .37, respectively; p<0.001). In turn, pain sensitivity was significantly related to acute head and neck pain: β = .21, p<0.05 and β = .24, p<0.001, respectively. Both gender and age were not significantly related to head or neck pain.

Alternative models with a direct path between the independent variable pain catastrophizing and head or neck pain found non-significant relationship (p = .686 and p = .193, respectively). Additionally, the difference in chi square and degrees of freedom between the initial models and the alternative models presented were not significant (p = .290 and p = .187, respectively), thus the initial models are the preferred models since they are more parsimonious.

In summary, the first SEM analysis suggests that higher pain catastrophizing is not directly associated with higher acute head and neck pain intensity ratings. However, higher pain catastrophizing was significantly linked to higher pain sensitivity, which in turn was significantly associated with higher acute head and neck pain intensity ratings. Thus, the relationship between high pain catastrophizing and high acute head and neck pain was fully mediated by high pain sensitivity.

The second SEM analysis model included the five personality traits: extraversion, agreeableness, conscientiousness, neuroticism and open to experiences, as independent variables that are both directly associated with pain catastrophizing and also correlated with each other (Fig 3). Although the chi square p-values of both models were significant (p = .029 and p = .021, respectively), other fit indices indicated that the data had a good fit to the models as presented in Fig 3.

Fig 3

SEM analysis of the direct and indirect link between personality traits, PCS, PSQ and head or neck pain intensity ratings.

Note: Estimates in black represent the model with head pain as an outcome and estimates in grey represent the model with neck pain as an outcome. *p < .05 **p < .001.

Only the personality trait of conscientiousness was significantly negatively related to pain catastrophizing γ = -.32 (p<0.001) in both models. As in the initial model that was presented in Fig 2, pain catastrophizing was significantly associated with the pain sensitivity, which in turn was significantly related to both acute head and neck pain intensity ratings.

Alternative models with two new direct paths were examined. The first path was a direct path between conscientiousness and pain sensitivity and the second path was a direct path between conscientiousness and acute head or neck pain intensity ratings. Both new paths were not significant in both head and neck pain models: for the acute head pain model p = .215 for first path and p = .716 for second path; and for the acute neck pain model p = .207 for first path and p = .560 for second path. Additionally, the difference in chi square and degrees of freedom between the models without these additional paths and the alternative models were not significant (p = .206 and p = .169, respectively), thus the models without these additional direct paths are the preferred models.

In summary, the second SEM analysis suggests that personality traits were not directly associated with higher acute head and neck pain intensity ratings. However, the trait of lower conscientiousness was significantly associated with higher pain catastrophizing, which in turn was significantly linked to higher pain sensitivity, which in turn was significantly associated with higher acute head and neck pain intensity ratings. Thus, the relationship between low conscientiousness and high acute head and neck pain intensity ratings was fully mediated by high pain catastrophizing and high pain sensitivity.

The third SEM analysis model included an independent latent variable of emotional status, as measured by stress (PSS), anxiety, and depression (HADS), which was directly associated with pain catastrophizing (Fig 4). Fit indices indicated that the data had a good fit to the models. However, the chi square p-values of the model with head pain as dependent variable and the model with neck pain as dependent variable were both significant (p<0.001 and p = .001, respectively).

Fig 4

SEM analysis of the direct and indirect link between emotional status, PCS, PSQ and head or neck pain intensity ratings.

Note: Estimates in black represent the model with head pain as an outcome and estimates in grey represent the model with neck pain as an outcome. *p < .05 **p < .001.

Emotional status was significantly related to pain catastrophizing in both models (γ = .53, p<0.001), indicating that higher anxiety, depression and/or stress were significantly associated with high pain catastrophizing. In turn, pain catastrophizing was significantly associated with the pain sensitivity (for the acute head pain model β = .38, p<0.001 and for the acute neck pain model β = .39, p<0.001). Finally, higher pain sensitivity was significantly related to higher head and neck pain intensity ratings (β = .20, p<0.001 and β = .24, p<0.001, respectively).

Two new direct paths were entered into alternative models (Fig 5). The first path was a direct path between emotional status and pain sensitivity and the second path was a direct path between emotional status and acute head or neck pain intensity ratings. While the first path was significant for both models (γ = .22, p<0.05 for head pain model and γ = .23, p<0.05 for neck pain model), the second path was not (p = .730 and p = .161, respectively). The difference in chi square and degrees of freedom between the models without these additional paths and the alternative models were significant for the neck but not the head pain intensity model. In the neck pain model, there was a change in the chi square of 6.24 with 2 degrees of freedom, corresponding to p = .044. Thus, the alternative model with these additional direct paths is the preferred one for neck pain intensity model.

Fig 5

Alternative models of SEM analysis of the direct and indirect link between emotional status, PCS, PSQ and head or neck pain.

Note: Estimates in black represent the model with head pain as an outcome and estimates in grey represent the model with neck pain as an outcome. Strait lines represent original model paths and dashed lines represent additional paths of the alternative model. *p < .05 **p < .001.

In summary, the third SEM analysis suggests just like pain catastrophizing and personality traits, emotional status had no direct association with acute head and neck pain intensity rating. However, unlike conscientiousness, which was not directly linked to pain sensitivity, higher emotional status was significantly associated with higher pain sensitivity. Thus, the relationship between a heightened emotional status and high acute head and neck pain was partially mediated by high levels of pain catastrophizing and fully mediated by high pain sensitivity.

4. Discussion

The main findings of this study revealed that solely testing direct links of either situational or dispositional personality characteristics may not be optimal to fully understand acute post-collision pain variability. Rather, pain intensity can be explained by indirect links, through pain sensitivity, with situational measures of anxiety, depression and stress, and dispositional personality traits, as well as pain catastrophizing.

There is a consensus among scholars in the field of chronic pain that pain catastrophizing is a predictor of pain intensity. However, when we originally explored this factor in our cohort, we found no correlation between pain catastrophizing and the patients’ reported acute pain intensity [17]. To parse these findings with the accumulative available evidence, we then looked to explore whether pain catastrophizing relates to acute pain, via indirect links. Our chosen mediator was pain sensitivity, a relatively new dispositional pain characteristic that has shown correlation with both clinical and experimental pain intensity [34, 43, 52–54]. Unlike other more well-explored pain-related questionnaires, the PSQ is distinct in the task which it requires of the patient. In order to assign a value to the daily-life situations presented within, individual’s need to both recall what was, and sometimes imagine what could be if the situation is unfamiliar to them. Thus, within one task an individual summarizes several cognitive representations of emotional and sensory processes which contributes to the pain experience. Indeed, our findings revealed that the hypothesis of mediation was supported, for pain in both the head and neck suggesting that reported pain intensity may be somewhat more of an expression of inherent pain sensitivity, and not only a representation of direct injury.

Since Ruschewyh [43] introduced the PSQ as a tool for pain-related assessment evidence has accumulated to support its contribution to deciphering the nature of ’pain sensitivity’. However, little has been suggested regarding its conceptualization. The theoretical links described in the current findings however help to start elucidating its role, as one which connects different facets of situational and dispositional pain processing. One possible suggestion as to why it can fill a mediating role would be to consider the PSQ as a tool which represents an individual’s imagination of pain. Imaging works [55-57] showed that pain imagination is associated with increased activity of brain regions involved in the pain-related neural network. Thus, it can be assumed that mediating role of PSQ (which reflects deeper cortical representations of the pain matrix) stems from its ability to depict specific routes of pain modulation that shape the manner in which individuals recall, process, and score a pain experience.

Interestingly, it seems that pain catastrophizing may have a dual role in explaining acute pain intensity. Wherein, PCS, when obtained in circumstances of clinical pain, may represent a more situational parameter and therefore is not directly linked with the pain experience, but rather its influence is mediated by the PSQ. At the same time, the PCS also mediated the effect of other dispositional (personality traits) and situational (emotional status) factors on acute pain intensity. While catastrophizing has often been viewed as a personality trait that remains stable in the absence of intervention [e.g., 58, 59], other findings that catastrophizing decreased following pain relief, suggest dynamic, state-like aspects [60]. Thus, the PCS, may comprise both situational and dispositional elements which are affected, among other reasons, by the instructions provided (whether relate to current or on previous pain experience) [61]. Furthermore, Sullivan et al. [58] proposed that the extent to which one engages in catastrophizing might change over time as a function of stimulus cues and social responses present in the individual’s environment. It is thus possible that certain individuals have a tendency to catastrophize in response to pain but that this tendency is amplified under certain internal conditions (depressed, anxious or stressed). A small number of studies have even begun to examine pain catastrophizing as a mediating factor in the context of acute pain [13, 62], further strengthening this explanation.

In regard to the personality traits themselves, while neuroticism and extraversion have been widely explored in previous pain literature [24, 25], the role of conscientiousness seems to be less investigated. Individuals with high scores of conscientiousness are characterized by high accountability as well as ethical responsibility and trustworthiness [63-65]. Previous work in acute pain settings has explored the role of conscientiousness and health outcomes [66, 67]. Thus, one can assume that individuals who scored higher on conscientiousness also demonstrate “more positive” attitudes when they face pain. A recent study [27] suggest that those with high conscientiousness often engage in more adaptive health management behaviors, which may also reflect increased self-efficacy and control perception. This line of thinking may explain why post-collision participants with low conscientiousness exhibited higher catastrophizing thinking toward pain, because their conscientiousness trait served as a ‘buffer’ which allowed them to construct a more adaptive cognitive representation towards pain which attenuates the negative meaning and consequence of their pain symptoms. Specifically, and in line with our findings, Suso-Ribera et al., [66] noted that conscientiousness tended to be associated with better health outcomes, including physical functioning and mental well-being, and Conrad and Stricker [67] showed that conscientiousness women demonstrated positive labor experience.

Situational factors, such as emotional status (e.g., depression, anxiety, stress), were previously reported to be linked to both pain catastrophizing [28, 29], and pain sensitivity [33, 34]. As was observed in this cohort, previous work reported that those with state anxiety experienced higher levels of acute pain in the presence of higher catastrophizing. Our work expands on this by proposing that pain catastrophizing partially mediates an individual’s overall emotional status, comprised of stress, anxiety and depression, which in turn affects their perception of acute post-injury pain. This perspective of mediating factors is prudent as recent cumulative work has failed to find direct correlations between state anxiety and depression, as reflected by the HADS, and acute post-operative pain [30-32]. Furthermore, it supports very recent findings [23], which are based on the Extended Dynamic Mediation Model that tested an integrative theoretical model of the association between personality traits and trait affect in combination with the dynamic mediation hypothesis [68]. Taken together, it seems that both PC and pain sensitivity mediate the relations between personality traits and emotional states, and pain experience.

Despite the large clinical cohort and the advanced statistical methods employed several limitations should be noted. First, given that a comprehensive amalgamation of features shape the ability to perceive, cope with, and react to pain, the cross-sectional nature of the current study does may not allow for a full exploration of the multidimension and fluctuation in the magnitude of the assessed variables. Second, the results regarding personality traits should be carefully interpreted due to the use of the TIPI, which is a short-form tool, and has been less explored in the literature as compared with the full Big Five Inventory.

5. Conclusion

In conclusion, the wide variability in the manifestation of acute post-traumatic pain can be better understood when addressed not as an isolated concept, but rather as a combination of both dispositional and situational influences. Taking this enriched view, and by use of both direct and indirect pathways, it allows for a more in-depth understanding of factors which may affect the acute to chronic pain transition.

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27 Apr 2021

PONE-D-20-40180

Pain Sensitivity mediates between pain-related personality features and acute mTBI post-collision pain

PLOS ONE

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Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: The study focuses on acute pain in non-post-operative patients following mild traumatic brain injury and attempts to untangle the effects of pain-related psychological measures and personality traits on the acute pain perception. It is an interesting topic, and the sample is quite rich. Nevertheless, I have several concerns regarding the current version of the manuscript.

Introduction:

I would suggest expending introduction to better articulate the aim of the study. Namely, it would be useful to expend on previous findings on the relationship between pain perception and personality traits (currently lines 77-87 just reads that some relatively stable personality characteristics are related to pain). This will enable you to make better hypothesis – i.e. „positive“ and „negative“ personality traits is vague and not very accurate depiction of what you are testing here (my overall impression is that the authors do not come from the field of personality which resulted in errors in this aspect of the paper – see below). Please do not label personality traits as negative/positive – each trait is a continuum and high/low scores are not good or bad (depending on the context, both high and low scores can be beneficial for the person, different societies value different expressions of different traits, often „mid-range“ scores are the most adaptive, and extremes (on either low/high) can be dysfunctional.

Although unusual, I like how the hypothesis are embedded in the introduction. However, I am missing the objective of the paper – Why are we contrasting these models? The first aim is clear to me, but the second aim („to investigate how the first model is affected by personality) and the third aim (how the first model is affected by emotional states) are something I am struggling to understand: What is the rationale for this? Why is this something we should be looking into? (I can use my imagination but it is always better to have it explicitly stated in the paper)

Methods

I think that the headings should be differently ordered, Eg. I don’t see how „Study population“ (second order heading) comprises Participants & Study design. I would recommend 2.1. Study design 2.2. Participants 2.3. Measures 2.4. Statistical analysis. Under 2.3. you can have the „primary outcome“ and „predictor measures“, but please do not label TIPI as „pain-related personality questionnaire“; same goes for HADS and PSS.

As this study is a part of a large ongoing data collection, and you have already published some data in other papers, please explain how data presented in this paper differ form the datasets that have already been published. This is something one should pay a lot of attention to in order to avoid double publishing and/or salami-slicing (this is one of the critical issues for me regarding this paper)

On the similar note, you need to justify the sample size – please include the stopping rule (i.e. since the study is ongoing, how did you decide to take this set of participants – why October 2018?, did the study stop for some reason, or was there something else. 200 is a very round number – did you stop at 200 participants?); also power calculation would be useful here so I would strongly suggest moving it from statistical analysis to sample section, and adding the sample size here as well (it is more reader-friendly to have sample description size and power at the same place rather than pages apart)

It is not clear to me how the primary outcome was calculated. Line 152-153 authors state the mean rating for both (read: head and neck), were considered primary outcome measures. What was averaged? The lines 146-147 state: mean pain in the neck, mean pain in the head, maximum pain in the neck, maximum pain in the head. Was it the mean between “mean” and “maximum”, or was just the mean measure used? Why was this measure selected as primary outcome? If other measures have been collected but not used as outcomes, I think it would be good to add the rationale behind that decision or add the analysis on maximal pain to the results in table 2 for example.

Please avoid using “pain-related personality” - Pain Sensitivity Questionnaire is not assessing personality, and TIPI is not assessing pain.

Pain Catastrophizing Scale – please add the information on which scores have been used, the total or subscales? “Patients were not directed to focus on any particular pain sensation”- please provide the rationale behind this decision.

Five Feature Model (FFM) is actually Five Factor Model – please correct this.

In relation to TIPI, I have to ask, just to be sure – were the reverse coded items recoded before averaging items for each factor?

The sentence “…. with high scores endorsing a stronger affirmation of the personality dimension and each dimension is corelated with the other” is not correct. One cannot say “stronger affirmation of dimension” – high score on extraversions means that the person is extraverted, and low means that he/she is more reserved or quiet, so the “baseline” is the middle, not the lower score. The main thing about these five dimensions (and the whole idea behind FFM) is that they are relatively independent – they can show some correlations, but these correlations are low, but they are meant to be mainly independent.

Please consult the paper on TIPI development Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). A Very Brief Measure of the Big Five Personality Domains. Journal of Research in Personality, 37, 504-528, and also the main works on Big Five / Five Factor Model by Goldberg and Costa & McCrae.

“Anxiety often precedes depression in response to stressors and is often poorly identified by clinicians” – this is a bit of a strong claim, please either support it by empirical evidence or simply omit it.

Please add the reliability measures for all instruments (e.g. internal consistency either at this sample or from the previous studies), this is important for the subsequent analysis.

the “chi-square distribution” should be “chi-square test”

replace “ the χ2 estimated value was low and the p-value was greater than .05” with “non-significant chi-square test”

SEM stands for Structural Equation Modeling – so please adjust the wording in the sentences e.g. replace “SEM analyses were tested” with “models were tested using SEM”.

Results

When language is important for conducting the study, it should be included in the inclusion/exclusion criteria, because when one needs to fill in the questionnaire, he/she did not dop out due to the language barrier, but he/she was not supposed to be included in the study at all.

It is important to comment on the fact that the study is underpowered for testing the second model.

I find SDs for TIPI seem a bit small – could you please check the data once more and make sure that they are correct.

SD should be reported with 2 or even 3 decimal places.

Why correlations with only some of the questionnaires and not all are presented?

What do you mean by “which is in line with the previous findings for this cohort”? Is it the same sample, different sample or partially overlapping sample?

Please avoid using “pain-related personality factors” throughout the manuscript.

“correlator” should be replaced with “corelate” line 275

Please report on chi-squares and respective degrees of freedom for models.

It is important not to alter between Neuroticism and Emotional stability as they are the “opposites”. From the paper it is not clear to me whether higher scores on this dimension reflect stability or neuroticism. Please adjust the text and provide this information explicitly.

Please label personality traits as they are commonly labeled or how they have been labeled in TIPI eg. Openness is not Open to changes

Looking at the model 2 that was tested - I am wondering why all five traits were included in the model (and this is why I suggested to explain the introduction) – it is reasonable to assume that N would be related, also A makes some sense, early work on E would suggest so as well, but I a cannot grasp the expectation regrading O for example. This is why it is important to convince the reader that what you are testing has some grounds in the previous literature, or if that is not the case - explicitly state which hypothesis you are testing and what is the rationale behind it.

I am missing zero order correlations between personality, depression, stress, and pain measures, because they are important for understanding the results.

It is not clear what is the operational definition of higher/lower emotional status, please explain.

Discussion

For a number of reasons, I believe it important not to label depression as “situational measure”, same goes for anxiety, even stress is not something that can be easily labeled as situational measure. Depression is deeply rooted in our neurobiology; it is not situationally driven nor measured as situational variable. It is also very important not to make situation-disposition distinction between for eg. depression-neuroticism (just do the correlation analysis between the two on the data set you have, and you’ll see why such distinction cannot be made)

I don’t see the relevance of discussing imagination and pain matrix in the contest of current study. I am not sure if I am missing something or if this part should be excluded altogether.

The relationship between C and health outcomes is usually attributed to the higher adherence to the recommendations and more orderly lifestyle (but I am not sure that such explanation would fit here). The role of C is not discussed adequately – I believe it is important to provide some explanation on what this finding could mean and why it was obtained.

It is unclear how did you derived the following conclusion “Taken together, it seems that personality states, experienced situation characteristics, and state affect mediate the relations between personality traits and trait affect.” Also, please try to be more consistent with the terminology – what are “personality states” “experienced situation characteristics” “state affect” ?

While I would personally agree that causal inference should be based on experiments i.e. manipulation of the conditions, the analysis you are preforming here is the closes you can get to testing causal effects when all variables are registered rather than manipulated. See for example: https://ftp.cs.ucla.edu/pub/stat_ser/r370.pdf and adjust that part of discussion on limitations (I would not attribute the limitation to the cross-sectional design, I see the sentence that follows it but these two sentences are in collision).

It is difficult to draw conclusions on the “situational influences” as none of the variables in the study was situational.

Overall, I believe this is an interested topic, and you have a good data set. From the prospect of publishing the critical issue is how you extract different papers for the same data set – so it is important to be clear and open here so that the same data is not reported several times. On the same note – I find it essential provide more detail regarding the sample selection and the inclusion criteria (I am just confused – that the study is ongoing and that you decided not to use any data collected in the past two years). On the content side, I believe it is essential to correct how the data on personality, depression, and stress are presented. This would require diving into at least most prominent papers on the personality models, depression measurement and interpretation of those measures and doing some literature research on how all these psychological variables relate to each other. If you see the merit of revising your paper in that direction, I will be happy to review again after resubmission.

Reviewer #2: The paper “Pain Sensitivity mediates between pain-related personality features and acute mTBI post-collision pain” presents interesting findings on the mediation effects of pain sensitivity on the relationship between specific personality features and acute mTBI post-collision pain.

The study has both practical and scientific relevance. However, several issues deserve paying attention to before the paper can be accepted for publication.

Overall, the report needs a lot of polishing and structuring. It contains a lot of valuable information but it is not presented in a user-friendly manner. It requires a lot of repeated reading to grasp the presented information.

Obviously, there is an error in the labels of the figures, as all figures are labeled as Figure 1 – this has to be corrected. Also, please check carefully the text in which figures are mentioned.

In Table 2 authors give correlations between a set of measures, but not for all measures. Personality traits are completely excluded from the Table as if they are not relevant. If so, why personality traits were explored at all in subsequent analyses? Please add correlations between personality traits and pain measures as discuss them. Additionally, tables could be improved – for example, non-significant p-values do not have to be displayed.

The introduction is, in my opinion, rather poor in displaying available evidence and discussing why authors decided to include both traits and states and how they relate to pain sensitivity. I recommend careful revision of the introduction. Also, I would recommend authors to use more precise terminology (e.g., terms “positive” and “negative” personality traits should be more precise, to what traits authors refer to).

Hypothesis 2 – authors introduce terms “positive” and “negative” personality traits without specifying to which traits they refer. Thus, judging the quality of the hypothesis is very difficult. Additionally, as part of the text elaborating on Hypothesis 2, the authors introduce negative affective states, which are not part of the hypothesis. Since affective states are related to personality traits, it has to be justified why personality traits and affective states were analyzed separately. Why did the authors decide to pursue that kind of analytic strategy?

Hypothesis 3 is completely unexplained – it is not clear why the Hypothesis is formulated that way, and what is meant under the term “A heightened post-collision emotional status”.

Did the authors try to explore both personality traits and states in one model)?

I would recommend authors to structure the presentation of the results – fit indices of tested models and comparison of models can be displayed in a table.

In all tested models, age and gender are postulated as relevant factors, but the introduction is not saying much about the relevance of sociodemographic variables on the criterion variable. Please revise the text and explain why we should focus on age and gender differences.

I applaud the authors for making their dataset available, but I recommend them to add labels of the variables, and values for each variable. Also, adding a CSV file would increase the visibility and transparency of the dataset, as the .sav file requires licensed software.

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Reviewer #1: Yes: Jovana Bjekic

Reviewer #2: Yes: Ljiljana B. Lazarevic

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13 Aug 2021

Dear Jovana Bjekic and Ljiljana B. Lazarevic,

We thank you for taking the time to review our manuscript entitled “Pain Sensitivity mediates between pain-related personality features and acute mTBI post-collision pain”. We have taken painstaking measures to address your insightful comments, and hope that the manuscript is now clearer and more understandable. Please find our responses below.

Sincerely yours,

The authors

PONE-D-20-40180

Pain Sensitivity mediates between pain-related personality features and acute mTBI post-collision pain

PLOS ONE

Reviewer #1:

The study focuses on acute pain in non-post-operative patients following mild traumatic brain injury and attempts to untangle the effects of pain-related psychological measures and personality traits on the acute pain perception. It is an interesting topic, and the sample is quite rich. Nevertheless, I have several concerns regarding the current version of the manuscript.

Introduction:

I would suggest expending introduction to better articulate the aim of the study. Namely, it would be useful to expend on previous findings on the relationship between pain perception and personality traits (currently lines 77-87 just reads that some relatively stable personality characteristics are related to pain). This will enable you to make better hypothesis – i.e. „positive“ and „negative“ personality traits is vague and not very accurate depiction of what you are testing here (my overall impression is that the authors do not come from the field of personality which resulted in errors in this aspect of the paper – see below). Please do not label personality traits as negative/positive – each trait is a continuum and high/low scores are not good or bad (depending on the context, both high and low scores can be beneficial for the person, different societies value different expressions of different traits, often „mid-range“ scores are the most adaptive, and extremes (on either low/high) can be dysfunctional.

Our response: the reviewer's comment is very important, and it guided us in the revision of the manuscript in general and the introduction section in particular. We re-wrote the entire introduction section according to this comment. We hope that the new version addresses the expectations of the reviewers and allowed us to improve our manuscript. Please see Pages 4-10.

Although unusual, I like how the hypothesis are embedded in the introduction. However, I am missing the objective of the paper – Why are we contrasting these models? The first aim is clear to me, but the second aim („to investigate how the first model is affected by personality) and the third aim (how the first model is affected by emotional states) are something I am struggling to understand: What is the rationale for this? Why is this something we should be looking into? (I can use my imagination but it is always better to have it explicitly stated in the paper)

Our response: Thank you for this comment. Accordingly, in the revised version, we explained that two theoretical models guided this study. Thus, the introduction section was expended, clarified, and current publications were added to strengthen our claims. Please see pages 7 and 8.

Methods

I think that the headings should be differently ordered, Eg. I don’t see how „Study population“ (second order heading) comprises Participants & Study design. I would recommend 2.1. Study design 2.2. Participants 2.3. Measures 2.4. Statistical analysis. Under 2.3. you can have the „primary outcome“ and „predictor measures“, but please do not label TIPI as „pain-related personality questionnaire“; same goes for HADS and PSS.

Our response: The order of the headings was changed as recommended. We believe that the new order will allow the readers better understanding about the information provided in the Methods section. In addition, we reframed the variable sub-titles such that each variable was defied according of its role in the model: dependent, independent and mediator. Please see pages 11-18.

As this study is a part of a large ongoing data collection, and you have already published some data in other papers, please explain how data presented in this paper differ form the datasets that have already been published. This is something one should pay a lot of attention to in order to avoid double publishing and/or salami-slicing (this is one of the critical issues for me regarding this paper).

Our response: Although 3 papers were published during the past two years based on data obtained in this research project, this manuscript is unquestionably not a duplication of other reports. First and foremost this is the only analysis of the data, to date, which includes both patients classified as post-whiplash and those classified as post-mTBI, all other papers only focused on a subsection of patients who were considered mTBI post-collision. In addition the first paper concerned itself with a general comparison of healthy controls with mTBI post-collision patients, the second looked to the PSQ as an additive tool for understanding acute pain, and the third, recently published only looked at 6-month follow-up data from a very small subsection of the cohort.

On the similar note, you need to justify the sample size – please include the stopping rule (i.e. since the study is ongoing, how did you decide to take this set of participants – why October 2018?, did the study stop for some reason, or was there something else. 200 is a very round number – did you stop at 200 participants?); also power calculation would be useful here so I would strongly suggest moving it from statistical analysis to sample section, and adding the sample size here as well (it is more reader-friendly to have sample description size and power at the same place rather than pages apart).

Our response: We thank the reviewer for raising such important issue. Furthermore, this comment encouraged us to add all patients that enrolled in this study project that was completed in December 2019. Since 2020 we were focused only on the follow-up sessions, which occur at 6 and 12-months post-accident. Accordingly, the revised manuscript is comprised of 239 mTBI patients. This allowed us to re-analyze the 3 models. The information about the time frame in which data was collected has been revised in the Method Section, see Page 11 under Study Design. Indeed, the new analyses further support our initial findings and the revised version showed a better model fit in all analyses. Please see at the end of the statistical analyses section the specific information about the sample size required for each model as appropriated in SEM ( Page 19), as this is where we found the information traditionally to be located.

It is not clear to me how the primary outcome was calculated. Line 152-153 authors state the mean rating for both (read: head and neck), were considered primary outcome measures. What was averaged? The lines 146-147 state: mean pain in the neck, mean pain in the head, maximum pain in the neck, maximum pain in the head. Was it the mean between “mean” and “maximum”, or was just the mean measure used? Why was this measure selected as primary outcome? If other measures have been collected but not used as outcomes, I think it would be good to add the rationale behind that decision or add the analysis on maximal pain to the results in table 2 for example.

Our response: We agree that the description of the outcome measure was not clear. Therefore, we rephrased this point as suggested and state in the revised version that the outcome measures represent the mean pain intensity ratings as assessed by VAS. Please see Page 13.

Please avoid using “pain-related personality” - Pain Sensitivity Questionnaire is not assessing personality, and TIPI is not assessing pain.

Our response: According to this comment, we corrected this phrase along the revised manuscript in the relevant places.

Pain Catastrophizing Scale – please add the information on which scores have been used, the total or subscales?

Our response: The 3 models included the three sub-scales of PCS and not the total PCS scores as appropriated in SEM. This is now noted on Page 16.

“Patients were not directed to focus on any particular pain sensation”- please provide the rationale behind this decision.

Our response: Since we were interested in ascertaining patient’s general potential catastrophizing view of painful events, patients were instructed to refer to any commonly experienced previous painful event when they completed the PCS. This approach is commonly used in the assessment of pain catastrophizing as suggested by Sullivan et al. (1995). We have better explained how patients were instructed and state that this is according to Sullivan's direction. Please see Page 16.

Five Feature Model (FFM) is actually Five Factor Model – please correct this.

In relation to TIPI, I have to ask, just to be sure – were the reverse coded items recoded before averaging items for each factor?

Our response: This typo was corrected. As for the second question, the reverse coded items were recoded as required.

The sentence “…. with high scores endorsing a stronger affirmation of the personality dimension and each dimension is corelated with the other” is not correct. One cannot say “stronger affirmation of dimension” – high score on extraversions means that the person is extraverted, and low means that he/she is more reserved or quiet, so the “baseline” is the middle, not the lower score. The main thing about these five dimensions (and the whole idea behind FFM) is that they are relatively independent – they can show some correlations, but these correlations are low, but they are meant to be mainly independent. Please consult the paper on TIPI development Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). A Very Brief Measure of the Big Five Personality Domains. Journal of Research in Personality, 37, 504-528, and also the main works on Big Five / Five Factor Model by Goldberg and Costa & McCrae.

Our response: Based on this comment, the revised manuscript emphasizes that each dimension is independent. Additionally, we added information regarding that the middle point of each continuum for each trait is considered as the baseline score of this factor. Please see page 14.

“Anxiety often precedes depression in response to stressors and is often poorly identified by clinicians” – this is a bit of a strong claim, please either support it by empirical evidence or simply omit it.

Our response: According to this comment we have now omitted this sentence

Please add the reliability measures for all instruments (e.g. internal consistency either at this sample or from the previous studies), this is important for the subsequent analysis.

Our response: This information was added to the Methods sections for each of the Instruments.

The “chi-square distribution” should be “chi-square test”

replace “ the χ2 estimated value was low and the p-value was greater than .05” with “non-significant chi-square test”

Our response: This has been corrected as suggested by the reviewer

SEM stands for Structural Equation Modeling – so please adjust the wording in the sentences e.g. replace “SEM analyses were tested” with “models were tested using SEM”.

Our response: This has been corrected as suggested by the reviewer

Results

When language is important for conducting the study, it should be included in the inclusion/exclusion criteria, because when one needs to fill in the questionnaire, he/she did not dropout due to the language barrier, but he/she was not supposed to be included in the study at all.

Our response: Thank you for this comment, which is very important. Accordingly, we added information about language to the exclusion criteria on Page 13, in that participants who could not communicate in Hebrew were not enrolled into the study.

It is important to comment on the fact that the study is underpowered for testing the second model.

Our response: According to your previous comments about the sample, we now re-analyzed the full data with all the participants in the entire study. Thus, the revised version fully addressed the power requirement.

I find SDs for TIPI seem a bit small – could you please check the data once more and make sure that they are correct.

Our response: We double checked the raw data from the TIPI and found no typo in it.

SD should be reported with 2 or even 3 decimal places.

Our response: Done. We have added 2 decimal places as suggested in the text and Table 1. Additionally, correlations and p-values are now presented with 3 decimal places.

Why correlations with only some of the questionnaires and not all are presented?

Our response: The revised manuscript now contains the full correlation matrix as suggested, see Table 2.

What do you mean by “which is in line with the previous findings for this cohort”? Is it the same sample, different sample or partially overlapping sample?

Our response: As mentioned previously, in relate to your concern about the potential overlapping, although reports based on part of this cohort were published previously, the current manuscript is focused on a different study question, analyzed in a different statistical approach, in a larger sample and was based on measures that were not published before (for example TIPI).

Please avoid using “pain-related personality factors” throughout the manuscript.

“correlator” should be replaced with “corelate” line 275

Our response: This has been corrected.

Please report on chi-squares and respective degrees of freedom for models.

Our response: This has been done.

It is important not to alter between Neuroticism and Emotional stability as they are the “opposites”. From the paper it is not clear to me whether higher scores on this dimension reflect stability or neuroticism. Please adjust the text and provide this information explicitly.

Please label personality traits as they are commonly labeled or how they have been labeled in TIPI eg. Openness is not Open to changes

Our response: Thank you for this astute comment. We have made changes to the wording concerning the TIPI variables, see for example Table 1.

Looking at the model 2 that was tested - I am wondering why all five traits were included in the model (and this is why I suggested to explain the introduction) – it is reasonable to assume that N would be related, also A makes some sense, early work on E would suggest so as well, but I a cannot grasp the expectation regrading O for example. This is why it is important to convince the reader that what you are testing has some grounds in the previous literature, or if that is not the case - explicitly state which hypothesis you are testing and what is the rationale behind it.

Our response: In line with this comment and previous ones, we revised the background section such that the new version better elaborates the theoretical and empirical rational for our hypotheses.

I am missing zero order correlations between personality, depression, stress, and pain measures, because they are important for understanding the results.

Our response: The revised manuscript now includes a full –correlation table for all assessed variables.

It is not clear what is the operational definition of higher/lower emotional status please explain.

Our response: We have clarified that emotional status is a latent variable that was attained by PSS and HADS and that high scores in these questionnaires represents higher emotional distress. Please see Page 14.

Discussion

For a number of reasons, I believe it important not to label depression as “situational measure”, same goes for anxiety, even stress is not something that can be easily labeled as situational measure. Depression is deeply rooted in our neurobiology; it is not situationally driven nor measured as situational variable.

Our response: This comment is very important and thanks to the reviewer’s comment we addressed the perception of this term even in the introduction section. In line with your example about depression, we clarified that dispositional and situational measures are indeed two distinctive features but as seen in depression, situational measures might be manifested in more flexible manner then dispositional measures, such that under particular circumstances, the expression of situational features may be altered after an exposure to a demanding situation in either short- or long-term manner.

It is also very important not to make situation-disposition distinction between for eg. depression-neuroticism (just do the correlation analysis between the two on the data set you have, and you’ll see why such distinction cannot be made)

Our response: We absolutely agree with that comment. Accordingly, this was omitted from the manuscript.

I don’t see the relevance of discussing imagination and pain matrix in the contest of current study. I am not sure if I am missing something or if this part should be excluded altogether.

Our response: According to this comment, we revised the paragraph that now better explains the mediating role of PSQ, which can be found on Page 29.

The relationship between C and health outcomes is usually attributed to the higher adherence to the recommendations and more orderly lifestyle (but I am not sure that such explanation would fit here). The role of C is not discussed adequately – I believe it is important to provide some explanation on what this finding could mean and why it was obtained.

Our response: Indeed, the role of C in pain processing and experience was less explored and reported in the current literature. We assume that individuals who scored higher on C demonstrate also “more positive” attitudes as well as practices when pacing challenging health condition including pain. This assumption is based on a recent study (Day et al., 2021) who stated that :

“Prior research has also shown that more conscientious individuals have more positive health perceptions and visits to the doctor (Jerram & Coleman, 1999), as well as more positive attitudes toward orthodontic treatment which was related to treatment success (Singh et al., 2017). Hence, highly conscientious individuals may tend to evidence

more adaptive health management behaviors, which may also be reflected by higher levels of self-efficacy and perceived control.”

In line with this, the negative association between C and PCS which leads to enhanced pain can be explained by the “buffered” role of this particular trait which allow individuals to construct more adaptive cognitive representation toward pain which attenuate its negative meaning and consequence. We better elaborate this notion in the revised discussion section, please see Page 30.

It is unclear how did you derived the following conclusion “Taken together, it seems that personality states, experienced situation characteristics, and state affect mediate the relations between personality traits and trait affect.” Also, please try to be more consistent with the terminology – what are “personality states” “experienced situation characteristics” “state affect” ? Our response: This sentence has been changed to read: “Taken together, it seems that both PC and pain sensitivity mediate the relations between personality traits and emotional states, and pain experience.”

While I would personally agree that causal inference should be based on experiments i.e. manipulation of the conditions, the analysis you are preforming here is the closes you can get to testing causal effects when all variables are registered rather than manipulated. See for example: https://ftp.cs.ucla.edu/pub/stat_ser/r370.pdf and adjust that part of discussion on limitations (I would not attribute the limitation to the cross-sectional design, I see the sentence that follows it but these two sentences are in collision).

Our response: Thank you for this valuable comment that allowed us to better address, in the revised manuscript, the limitations associated with our study design. We have now clarified that the cross sectional nature of out study limited the ability to depict multidimension and fluctuation in the magnitude of the assessed variables. Please see Page 31.

It is difficult to draw conclusions on the “situational influences” as none of the variables in the study was situational.

Our response: We believe that the remarkable changes that were performed along the revised manuscript allow the readers to understand the term “situational influences” in a more clarity manner.

Overall, I believe this is an interested topic, and you have a good data set. From the prospect of publishing the critical issue is how you extract different papers for the same data set – so it is important to be clear and open here so that the same data is not reported several times. On the same note – I find it essential provide more detail regarding the sample selection and the inclusion criteria (I am just confused – that the study is ongoing and that you decided not to use any data collected in the past two years).

Our response: We hope that the changes that were made according to this comment and previous ones illuminate this issue.

On the content side, I believe it is essential to correct how the data on personality, depression, and stress are presented. This would require diving into at least most prominent papers on the personality models, depression measurement and interpretation of those measures and doing some literature research on how all these psychological variables relate to each other. If you see the merit of revising your paper in that direction, I will be happy to review again after resubmission.

Our response: Thank you for your insightful suggestions along with your thorough comments, the revised manuscript expresses the complexity associated with the assessed psychological variables. We hope that the additional literature we added as well as the clarifications will address your expectations. Please note the extensive addition of new references.

Reviewer #2: The paper “Pain Sensitivity mediates between pain-related personality features and acute mTBI post-collision pain” presents interesting findings on the mediation effects of pain sensitivity on the relationship between specific personality features and acute mTBI post-collision pain.

The study has both practical and scientific relevance. However, several issues deserve paying attention to before the paper can be accepted for publication.

Overall, the report needs a lot of polishing and structuring. It contains a lot of valuable information but it is not presented in a user-friendly manner. It requires a lot of repeated reading to grasp the presented information.

Our response: Thank you for this valuable comment. We have revised the entire manuscript to now better emphasize the theoretical framework for this research as well as rephrased the definitions of the assessed concepts . We hope that the new version is clearer and user-friendly.

Obviously, there is an error in the labels of the figures, as all figures are labeled as Figure 1 – this has to be corrected. Also, please check carefully the text in which figures are mentioned.

Our response: This has been corrected

In Table 2 authors give correlations between a set of measures, but not for all measures. Personality traits are completely excluded from the Table as if they are not relevant. If so, why personality traits were explored at all in subsequent analyses? Please add correlations between personality traits and pain measures as discuss them. Additionally, tables could be improved – for example, non-significant p-values do not have to be displayed.

Our response: In line with this comment and reviewer’s #1 comment we have added all study variables to the correlation table.

The introduction is, in my opinion, rather poor in displaying available evidence and discussing why authors decided to include both traits and states and how they relate to pain sensitivity. I recommend careful revision of the introduction. Also, I would recommend authors to use more precise terminology (e.g., terms “positive” and “negative” personality traits should be more precise, to what traits authors refer to).

We agree that the previous introduction section necessitated remarkable revision. Thus, we re-wrote the introduction and emphasized the conceptualization of the main assessed variables as well as the rationale for the study hypotheses.

Hypothesis 2 – authors introduce terms “positive” and “negative” personality traits without specifying to which traits they refer. Thus, judging the quality of the hypothesis is very difficult. Additionally, as part of the text elaborating on Hypothesis 2, the authors introduce negative affective states, which are not part of the hypothesis.

Our response: This has been corrected as suggested.

Since affective states are related to personality traits, it has to be justified why personality traits and affective states were analyzed separately. Why did the authors decide to pursue that kind of analytic strategy?

Our response: We agree with the reviewer about this concern, and we believe that this issue can be addressed from several perspectives, each represent different theoretical approach. The debate among scholars regarding this issue, is also present in reviewer #1 comment that states the minimal to no link between traits and states. Additionally, due to power consideration, we avoid additional analysis that comprised both elements. Nevertheless, we revised the introduction section in the new manuscript such that the rational to pursue that kind of analytic strategy was clarified.

Hypothesis 3 is completely unexplained – it is not clear why the Hypothesis is formulated that way, and what is meant under the term “A heightened post-collision emotional status”.

Did the authors try to explore both personality traits and states in one model)?

Our response: We apology that the terms personality traits and emotional states were presented in confusing manner. Given that each represent different facet of pain perception and modulation, we aimed to explore each demotion as well as to investigate their composition using the mediation analyses models. We believe that the new version addresses your valuable comment.

I would recommend authors to structure the presentation of the results – fit indices of tested models and comparison of models can be displayed in a table.

Our response: In line with this comment, we omitted information about the fit indices from the text and added it to the figures, which we hope clarifies the information.

In all tested models, age and gender are postulated as relevant factors, but the introduction is not saying much about the relevance of sociodemographic variables on the criterion variable. Please revise the text and explain why we should focus on age and gender differences.

Our response: According to this comment we have added an explanation of using those variables as control variables in the methods section, Please see Page 17.

I applaud the authors for making their dataset available, but I recommend them to add labels of the variables, and values for each variable. Also, adding a CSV file would increase the visibility and transparency of the dataset, as the .sav file requires licensed software.

Our response: Thank you for your positive comment. Accordingly we have arranged the variables’ labels in the dataset.

Submitted filename: PLOS ONE Response to Reviewer.docx

Click here for additional data file.

15 Sep 2021

PONE-D-20-40180R1Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivityPLOS ONE

Dear Dr. Granot,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================Althought all the reviewers' remarks have been addressed, Reviewer 2 has detected small inaccuracies in the text that must be corrected prior to the publication.

==============================

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PLOS ONE

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Reviewer #2: All comments have been addressed

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Reviewer #1: I believe authors have addressed all the major concerns in a reasonable manner; I like that they reanalyzed the data and added new participants. The intro and discussion are much better written now.

Reviewer #2: Thank you for making changes in the manuscript. I identified some minor issues that should be fixed:

1. Check reference mentioned in line 58 – reference number 6 is missing.

2. Openness to changes should be openness to experiences – please revise it in whole manuscript

3. Encore – wrong spelling, it should anchors

4. Correlations should be presented with 2 decimals.

**********

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Reviewer #1: Yes: Jovana Bjekic

Reviewer #2: Yes: Ljiljana B. Lazarevic, University of Belgrade, Serbia

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24 Sep 2021

PONE-D-20-40180R1

Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivity

PLOS ONE

Dear Jovana Bjekic and Ljiljana B. Lazarevic,

We would like to thank you for taking the time to review our manuscript entitled “Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivity”. We have made the minor changes that were requested and hope that the editor and reviewers will be satisfied with this version of the manuscript. Please find our responses below.

Sincerely yours,

The authors

Editorial comments:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Our response: Thank you for pointing this out. We have updated many recent citations and removed some of the older ones during the previous revision. This process resulted in an error in the reference list. Based on this comment, we double-checked all citations and references and made sure they were correct and complete.

Reviewer #1

I believe authors have addressed all the major concerns in a reasonable manner; I like that they reanalyzed the data and added new participants. The intro and discussion are much better written now.

Our response: We appreciate your positive feedback. We have indeed made a major revision of the manuscript, and we are pleased that you are satisfied with it.

Reviewer #2

Thank you for making changes in the manuscript. I identified some minor issues that should be fixed:

1. Check reference mentioned in line 58 – reference number 6 is missing.

Our response: Thank you for pointing this out. During the revision process, reference #6 was accidentally omitted from the text. It has now been added as reference #2. The text and reference list have been corrected accordingly.

2. Openness to changes should be openness to experiences – please revise it in whole manuscript

Our response: Thank you for this comment. We used the term open to experiences rather than Open to changes throughout the manuscript, including tables and figures.

3. Encore – wrong spelling, it should anchors.

Our response: In line with this comment, the typo was corrected.

4. Correlations should be presented with 2 decimals.

Our response: We have corrected both the correlation table and the correlation information in the text to show 2 decimals.

Submitted filename: PLOS ONE Response to Reviewer 23.9.21.docx

Click here for additional data file.

17 Dec 2021

Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivity

PONE-D-20-40180R2

Dear Dr. Granot,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Inmaculada Riquelme

Academic Editor

PLOS ONE

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Reviewers' comments:

31 Dec 2021

PONE-D-20-40180R2

Dispositional and situational personal features and acute post-collision head and neck pain: Double mediation of pain catastrophizing and pain sensitivity

Dear Dr. Granot:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

Dr. Inmaculada Riquelme

Academic Editor

PLOS ONE