Journal of Psychosomatic Research 61 (2006) 213 – 219
Resilience as a moderator of pain and stress Oddgeir Friborga,4, Odin Hjemdalb, Jan H. Rosenvingea, Monica Martinussena, Per M. Aslaksena, Magne A. Flatena a
Department of Psychology, University of Tromsb, Tromsb, Norway Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
b
Received 9 June 2005; received in revised form 28 November 2005; accepted 22 December 2005
Abstract Objective: To study the predictive validity of the Resilience Scale for Adults (RSA) experimentally in relation to pain and stress. Method: The submaximum tourniquet method was used to induce ischemic pain and stress. Eighty-four subjects were randomized to a low- or a high stress group, and selected to a low- or a high resilience group according to their scores on the RSA. Measures of pain and stress were taken every 5 min. Results: Perceived pain and stress increased significantly throughout the experimental session,
but individuals scoring high on the RSA reported less pain and stress. This protection was more pronounced for the high stress group, thus supporting a protective effect of resilience as measured by the RSA. Conclusions: The predictive validity of the RSA was confirmed. Due to the positive role of these factors in pain and stress perception, it may also be a promising measure for studies on pain patients. D 2006 Elsevier Inc. All rights reserved.
Keywords: Resilience; Predictive validity; Tourniquet; Subjective pain; Subjective stress
One of the first conceptualizations of resilience originated from clinical psychology [1] as a need to understand wellbeing vs. dysfunction. Today, resilience is a well-established construct for describing and explaining unexpected positive outcomes despite a high risk for maladjustment when exposed to psychosocial adversities [2 – 4]. After three decades of longitudinal research on resilience factors and mechanisms, three broad categories stand out as protective [5,6]: (a) positive characteristics and resources of the individual; (b) a coherent, stable, and supportive family environment; and (c) a social network that supports and reinforces adaptive coping. The present authors developed the b Resilience Scale for Adults Q (RSA) to meet the need for a tool to measure these aspects in the adult population [7]. The RSA comprises five factors named Personal strength, Social competence, Structured style, Family cohesion, and Social resources. The reliability and validity of the scale
4 Corresponding author. Department of Psychology, University of Tromsb, N-9037 Tromsb, Norway. Fax: +47 776 45 610. E-mail address:
[email protected] (O. Friborg). 0022-3999/06/$ – see front matter D 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jpsychores.2005.12.007
were found to be promising [8 –10]. In the present study, the predictive validity of the RSA was investigated experimentally against measures of pain and stress. Feelings of pain and pain-related dysfunctions are often augmented by psychopathology [11], negative and stressful life events [12], and personality traits like neuroticism [13] and, to a lesser extent, introversion [14]. In previous validation studies of the RSA, it has discriminated significantly between healthy controls and psychiatric patients [8], and protected significantly against negative life events by increasing adaptability to life stresses [15]. The RSA has shown strong negative correlations with neuroticism and introversion, as well [10]. Although resilience may play a role in predicting well-being irrespective of stress factors (i.e., a compensatory effect) [16], it is presumed to play a considerably stronger role for adaptation under high stress conditions (i.e., a protective effect) [17,18]. Accordingly, an instrument measuring resilience should be significantly strongly associated with indices of adaptation or well-being under high than low stress conditions. As the relationship between stress and pain is well documented [19], a procedure from pain research [20] may
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be used to induce pain and stress. The pain produced by this procedure mimics pathological pain well and is quite stressful. By experimentally manipulating levels of stress in the experimental situation, it can be tested whether a high score on the RSA imply a compensatory or a protective effect against subjective feelings of pain and stress. As the protective model is theoretically more in line with the resilience construct [4,17,18], scores from the RSA were expected to fit this model by predicting larger differences in pain and stress responses in a group experiencing more stress than in a group experiencing less stress.
Method Subjects Eighty-four subjects (mean= 24.8, S.D. = 3.7), 47 women and 37 men, were recruited at the University of Tromsb and through advertisement in the local newspaper. Four subjects were removed due to missing data (three) and uniform questionnaire scores (one). All subjects received verbal and written description of the experiment, before deciding to participate or not. Subjects suffering from serious somatic illnesses (e.g., diabetes, cardiac diseases, hypertension, asthma), using prescribed drugs, as well as women in the menstrual period, were not eligible as these factors affect pain sensitivity [21]. The study was approved by the Regional Committee for Medical Research Ethics in Northern Norway. Procedure The experiment was conducted at the Department of Clinical Research at the University Hospital of Northern Norway, Tromsb. All subjects underwent a screening procedure before reading and signing an informed consent form. Everyone was instructed to be abstinent from intoxicating substances, nicotine, and caffeine, for a minimum of 12 h prior to the experiment. They completed the questionnaire materials at home, before returning to the lab. The experimental procedure was run from 8 a.m. to 1 p.m. The standardized submaximum tourniquet method [20] was used to induce ischemic pain. Blood was forced out from the forearm using an Esmarch bandage. A pneumatic compression device (sphygmomanometer) was attached to the nondominant arm and inflated to 200 mm Hg to occlude blood flow. Before putting the arm to rest, the subject pressed a hand trainer 12 times every 2 s to increase ischemic pain due to the accumulation of metabolites [22]. Pain induction lasted for a maximum of 45 min. To reduce the opportunity for the subjects to use compensatory strategies to withstand pain and stress better, they were not informed about the duration of the experiment. Subjects were randomized to two stress conditions. For the low stress group receiving support and information
assuring the safety of the tourniquet method, the following information was given after applying the tourniquet: b This method for inducing pain is a frequently used technique by surgeons to allow for surgical bloodless interventions in the arm or hand. It is not uncommon to use a tourniquet for up till two hours. No damage following the use of the tourniquet has been reported. In a couple of minutes your arm will start feeling numb and relaxed, it will turn pale, cold, and some specks may become visible. This is quite normal. In forcing most of the blood out of the arm, the color of the arm will disappear and the temperature will fall. After releasing the tourniquet, blood will return and the arm will feel completely normal and regain its color and temperature within a few minutes. Even though this feels unpleasant, it is completely safeQ. Throughout the experiment, the experimenter expressed care and sympathy for the unpleasantness of the pain, probed regularly for the subject’s well being and repeated the safety of this procedure. In the high stress group, the experimenter gave no further information regarding the procedure and was instructed to relate formally to the subject. In case of questions, the experimenter only referred to previously given information and that she was not allowed to disclose anything more beyond this. The experiment ended if the subject expressed a desire to do so, gave a maximum pain intensity score (= 10), or if the maximum 45 min had passed since the tourniquet was applied. Materials Measures of perceived pain and stress Subjective feelings of pain and stress were measured by three visual analog scales (VASs) going from 0 (no pain/ stress) to 10 cm (maximum pain/stress). To examine whether resilience was generally protective or only at certain times, subjects rated themselves on these scales prior to fitting the tourniquet (pre), every 5 min during the experiment (5, 10, 15, 20, 25 30, 35, 40, and 45 min), and 5 min after removal of the tourniquet (post). The 11 repeated measures represented a within time factor. In measuring negative stress, arousal ratings have proved more discriminative of negative emotions than valence ratings [23]. To indicate stress, an adapted version of the VAS [24] using two items (each having two pairs of adjectives, relaxed– tensed and calm–nervous) was combined into a composite mean score to indicate stress. The Resilience Scale for Adults The RSA consists of 33 items and was developed to measure intrapersonal and interpersonal protective resources that may facilitate adaptation and tolerance to stress and adverse negative life events [8,10]. It comprises six factors: (1) Personal strength, containing two subfactors: (1a) Positive perception of self (6 items) and (1b) Positive perception of the future (4 items); (2) Social competence
O. Friborg et al. / Journal of Psychosomatic Research 61 (2006) 213 – 219 Table 1 Number of subjects under study across the four groups in the experiment Minutes at which pain and stress were measured Groups
5
10
15
20
25
30
35
40
45
Low RSA, low stress Low RSA, high stress High RSA, low stress High RSA, high stress Subjects terminating
18 20 23 19 0
18 19 23 19 1
18 19 23 18 2
17 17 22 18 6
15 15 21 16 13
12 14 19 16 19
10 12 17 15 26
9 7 12 12 40
8 4 9 8 51
There were no missing data at pre- and post-test.
(6 items); (3) Structured style (4 items); (4) Family cohesion (6 items); and (5) Social resources (7 items). Items were scored along a seven-point semantic differential scale, with the positive differentials to the right for half of the items to reduce problems of acquiescence bias [25]. The total score ranged from 33 to 231. A confirmatory factor analysis allowing all factors to correlate indicated a satisfactory fit [10]. Internal consistency and test–retest correlations (4 months) ranged from .76 to .86 [10] and .69 to .84 [8], respectively. In the present study, the Cronbach alphas were .75, .68, .72, .87, .81, and .70, for the factors, respectively, and .88 for the total RSA score. In the present analyses, the total RSA score was used in preference to the individual RSA factors for three reasons. Firstly, the intercorrelations between the RSA’s subscales have been found positive and of moderate to strong effect sizes (mean r =.41) [10]. In using a data set from a study [10] (N = 411), a second ordered factor model was compared against a correlated factor model. The difference in model fit was minor [Satorra-Bentler rescaled v 2 (S-B v 2) statistics (489) =751, P b.01; root mean square error of approximation (RMSEA) = .036; Akaike’s information criterion (AIC) = 895 vs. S-B v 2 (480) = 717, P b.01; RMSEA=.034; AIC = 879, respectively]. The factor loadings on the general factor ranged from .54 to .86 (mean k = .68). Hence, the subscales measure common aspects of resilience, thus supporting the use of the total RSA score without significantly changing the meaning of lowvs. high resilience scores. Secondly, the internal consistency for some of the individual factors was lower than expected in this study, which, among other things, reduced statistical power. By employing the total RSA score, which was more reliable, statistical sensitivity was increased. Thirdly, keeping in mind the main objective of the study, i.e., to study the predictive validity of test scores, the more parsimonious total RSA score was considered sufficient to test whether the scale converged with a protective model of resilience. Confirmatory factor analyses The confirmatory factor analyses in the previous section were run on LISREL version 8.53 [26]. As the main purpose was to compare rather than indicate absolute fit of models, fit statistics was judged in terms of relative differences. Due
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to non-normal item distributions, an asymptotic covariance matrix was estimated using PRELIS and added as a weight matrix to adjust standard errors, allowing the computation of S-B v 2. Better model fit was indicated by smaller values in S-B v 2 statistics, RMSEA, and AIC [27]. Data analyses All descriptive and inferential statistics were performed with SPSS version 13. As pain increased, a growing number of subjects terminated the experiment (see Table 1). This made a repeated analysis of variance inappropriate as it excludes all cases with missing data. Mixed linear effect models were therefore chosen to allow for estimation of the variance –covariance matrices on all the data available, increasing the degrees of freedom considerably [28]. Moreover, unbalanced designs and violations of compound symmetry and sphericity were all present, and mixed models handle such conditions better. In addition, mixed modeling offers the important opportunity to specify the covariances between the residuals of the repeated measures to account for variation in stress and pain simply predicted by past levels of stress and pain. As the covariances decreased over time, the matrices were specified as first-order autoregressive and estimated using restricted maximum likelihood. All three factors (stress, resilience, and time) were treated asfixed effects as none of them was presumed associated with the sampling procedure. Since the pain induction and the stress intervention were not present during pre- and posttests, these time points were not part of the mixed models to avoid inflating the interaction terms due to equal mean scores at pre- and post-tests but not during the experiment. As the scores from the RSA were significantly negatively skewed (z-value 3.08), the normality assumption was violated. Accordingly, the RSA scores were dichotomized into a low- (0) and a high (1) resilience group using the median as a split point. The study then corresponded to a mixed factorial design containing three independent factors: 2 RSA (low/ high resilience)2 stress (low/high)9 time (repeated measures of pain and stress). Since the design was quasiexperimental, the subjects were not randomly assigned to the resilience factor but selected on the basis of their scores to the RSA questionnaire. The experimental data from this study are published here [32]. As the number of subjects terminating the experiment increased with the passage of time, a differential rate of dropouts across the four groups would violate the assumption of missing cases occurring at random. However, a survival analysis using a Cox proportional-hazards regression model, entering RSA and stress as independent factors, and time to termination and termination status (0/1) to define censored cases, indicated no significant effects. Selective dropout was therefore not associated with the fixed factors, and the mixed models should therefore be reliable. Post hoc tests were run using conventional Student’s t-tests with a significance level of Pb.01. Hedge’s g was used as effect size statistic ( g), where
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Fig. 1. Mean differences in perceived pain between subjects scoring high and low on the RSA by levels of stress (high/low) and time (nine repeated measures). Ninety-five percent error bars depicted.
.20, .50, and .80 represent a weak, moderate, and strong effect, respectively [29]. Results Test and effect size statistics were computed to confirm distinctively different resilience groups. The mean resilience scores in the low RSA group (N =38, mean = 4.61, S.D.=.77) vs. the high RSA group (N = 42, mean =6.02, S.D. = .45) was strongly different [t(78) = 10.58, P b.001, Hegde’s g = 2.44]. Resilience as a moderator of pain intensity The main effect of the time factor was significant [ F(8,442) = 50.42, P b.001], indicating that pain scores increased significantly throughout the experiment. The main effect of the stress factor was not significant. Pain scores at pretest and posttest were not statistically different between the RSA (low/high) and the stress (low/high) groups. The main effect of the total RSA score was marginally significant [ F(1,77) = 3.75, P = .06], indicating slightly less pain in the high resilience group (mean difference = 6.7 mm, g = .28). A significant three-way interaction with stress and time also appeared [ F(8,441)=2.45, Pb.01]. As illustrated in Fig. 1, a high RSA score protected significantly against perceived pain during the beginning and middle phase, but not at the end. This difference was present in the high stress group only. Post hoc t-tests on the mean differences in the high stress group indicated significant differences at 15 min [mean difference = 19.1 mm, t(35) = 2.57, P = .01, g =.85] and marginally significant differences at 25 min (mean difference =16.1 mm, P = .04, g =.76) and 30 min (mean difference =19.1 mm, P = .02, g = .89). None of the differences in the low stress group was significant, thus partly supporting a protective effect. No other significant effects appeared.
Resilience as a moderator of perceived stress The main effect of the time factor was again significant [ F(8, 441) = 22.99, P b.001], confirming that perceived stress increased throughout the experiment. Unexpectedly, the main effect of the stress manipulation was not significant. The total RSA score predicted subjective stress both at pretest [t(673) = 4.34, P b.001, g =.33] and as a main effect during the experiment [ F(1,77) = 4.10, P b.05], which indicated significantly less stress/negative arousal in the high RSA group. The two-way interaction of RSA by levels of stress came out significant [ F(1,77) =3.81, P =.05]. Post hoc t-tests confirmed that a high vs. a low RSA score did not affect self-reported stress in the low stress group, but protected significantly in the high stress group by implying less perceived stress [mean difference=13.0 mm, t(266) = 5.37, P b.001, g = .66]. As the three-way interaction was not significant, these results supported a protective effect throughout the experiment (Fig. 2). At post-test, perceived stress was equal across the RSA and stress groups. Discussion The results supported the predictive validity of the Resilience Scale for Adults (RSA) as responses given to this measure a few days before entering the laboratory could be used to reliably predict individual differences in selfreported pain and stress. The beneficial effect of scoring high on the RSA was more pronounced for subjective stress than for subjective pain. This was evident as a high RSA score was associated with less stress scores independently of points in time, while reductions in pain due to a high RSA score was only present at certain time points. As the main effects were significant, it supported the notion that high resilience may be generally helpful for
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Fig. 2. Mean differences in perceived stress/negative arousal between subjects scoring high and low on the RSA by level of stress and time. Ninety-five percent error bars depicted.
dealing with unpleasantness and stressors in life. However, the concept of resilience is inextricably linked to the stress concept, e.g., it is assumed that exposure to some kind of stressors is a prerequisite for resilience to develop [2]. According to this conceptualization, resilience is an attribute that should provide an extra protection when individuals encounter stressful situations demanding more resources to overcome and adapt successfully to these challenges [17,18]. An instrument measuring resilience should fit this conceptualization, and indeed, the results supported the presence of such a protective effect when situational stress was higher. The present results contribute to the increasing evidence for the usefulness of the RSA. Previously, the RSA has correlated as expected with conceptually related and unrelated measures [9], differentiated significantly between psychiatric patients and healthy controls [8], and between personality profiles of well-adjusted and poorly adjusted individuals [10]. Our results also converged well with recent findings from a study on the RSA in which a high total RSA score was found to moderate significantly the negative effects of stressful life events in a prospective study [15]. A critique that has been raised against many longitudinal studies, like the one from Werner [4], has been that the observed good outcome may not have been related to higher resilience, but rather to different kinds of and perhaps less levels of psychosocial stress. The advantage of using an experiment in validating an instrument for resilience is the opportunity to control for this potential confound by exposing all individuals to the same stressor and intervention. If the scale still predicts individual differences, it may be more reliably related to individual differences in resilience as measured by the RSA. A disturbing factor in the study was the lack of a significant main effect of the stress intervention. Despite being
weaker than expected, it did not invalidate the results due to a significant interaction with the resilience factor, thereby indicating that it had an effect but more so among subjects rating themselves as more resilient. In future studies then, a stronger manipulation of the stress factor could be introduced, such as the Trier Social Stress Test [30]. This test involves a speech and an arithmetic task in front of an audience and should provoke more stress due to the risk of social embarrassment. It is also found to affect stress hormones. If a more effective stress intervention had been applied, larger positive effects of scoring high on the RSA would be expected rather than the opposite. How clinically relevant was the pain-reducing effect of scoring high on the RSA? In a previous study [31], a difference of 13 mm on the pain VAS was identified as a clinically significant change in pain severity, and that a smaller difference might be clinically irrelevant although it is statistically significant. In the present study, the main effect of scoring high vs. low on the RSA represented a mean difference of 6.7 mm. Although it was statistically marginally significant, it probably is of less clinical relevance. The situation was, however, different for the three-way interaction with stress and time. At three points in time, the mean differences were 19, 16, and 19 mm, thus indicating that a high RSA had a clinically relevant effect when situational stress was higher, and during the beginning and middle phase, when pain severity still had not grown intensely high. Although the resilience factors are moderately to strongly correlated and thus indicate common aspects of resilience, each subscale also measures some unique aspects of resilience [8]. While the factors bPersonal strength Q, bSocial competence,Q and b Structured styleQ indicate intrapersonal resources such as self-efficacy, self-esteem, positive social skills, and an organized manner in dealing with stressors, the interpersonal factors bFamily cohesion Q and bSocial
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resources Q indicate the availability of family members and close friends that may support coping and adjustment. Interestingly though, b Social resources Q was found to load moderately strongly on the personality trait agreeableness [10], whereas bFamily cohesionQ was less related to personality. The expected positive effects of scoring high on the different individual factors were not reported in this study. Nevertheless, they were analyzed. With some caution due to a lower statistical power of these tests (caused by lower reliability and many simultaneous statistical tests; six pain, six stress), the results indicated a stronger positive effect of the intrapersonal than the interpersonal factors. Given a valid result, this differential effect would be expected. In an experimental context, dispositional attributes and skills of the person would be expected as more important to withstand pain and unpleasantness, whereas interpersonal factors would be more relevant for situations involving real-life problems stretching over a longer time period. Implications In assessing resilience to pain and stress, the present experimental study gave support for the RSA as a valid and useful instrument. As it has shown protective effects against stressful life events in real-life contexts, as well as a laboratory setting, it seems to offer versatile applications. Applying these findings to patients with chronic pain problems, one could expect that, in times of increased stress or negative emotions, the RSA may detect individual differences in pain experiences, general level of functioning, and possibly in the use of pain medication, as well. Moreover, the present findings point to the importance of integrating these resilience factors in the psychological treatment of pain conditions. In particular, treatment effects may even be predicted by pretreatment RSA scores, thus possibly increasing the probability of treatment success.
Acknowledgments Funding for the present experiment was provided by the Bial Foundation of Portugal (Project 28/02) and the Norwegian Science Foundation’s Mental Health Program.
References [1] Garmezy N. Vulnerability research and the issue of primary prevention. Am J Orthopsychiatry 1971;41:101 – 16. [2] Rutter M. Psychosocial resilience and protective mechanisms. In: Rolf AS, Masten AS, editors. Risk and protective factors in the development of psychopathology. New York7 Cambridge Univ. Press, 1990. pp. 181 – 214. [3] Luthar SL, Cicchetti D, Becker B. The construct of resilience: a critical evaluation and guidelines for future work. Child Dev 2000; 71:543 – 62.
[4] Werner EE. Journeys from childhood to midlife: risk, resilience and recovery. Ithaca (NY)7 Cornell Univ. Press, 2001. [5] Garmezy N. Children in poverty: resilience despite risk. Psychiatry 1993;56:127 – 36. [6] Werner EE. High-risk children in young adulthood: a longitudinal study from birth to 32 years. Am J Orthopsychiatry 1989;59:72 – 81. [7] Hjemdal O, Friborg O, Martinussen M, Rosenvinge JH. Preliminary results from the development and validation of a Norwegian scale for measuring adult resilience. J Norw Psychol Assoc 2001; 38:310 – 7. [8] Friborg O, Hjemdal O, Rosenvinge JH, Martinussen M. A new rating scale for adult resilience: what are the central protective resources behind healthy adjustment? Int J Methods Psychiatr Res 2003; 12:65 – 76. [9] Friborg O, Hjemdal O. Resilience as a measure of adjustment. J Norw Psychol Assoc 2004;41:206 – 8. [10] Friborg O, Barlaug D, Martinussen M, Rosenvinge JH, Hjemdal O. Resilience in relation to personality and intelligence. Int J Methods Psychiatr Res 2005;14:29 – 42. [11] Dersh J, Polatin PB, Gatchel RJ. Chronic pain and psychopathology: research findings and theoretical considerations. Psychosom Med 2002;64:773 – 86. [12] Lampe A, Doering S, Rumpold G, Solder E, Krismer M, KantnerRumplmair W, Schubert C, Sollner W. Chronic pain syndromes and their relation to childhood abuse and stressful life events. J Psychosom Res 2003;54:361 – 7. [13] Goubert L, Crombez G, Van Damme S. The role of neuroticism, pain catastrophizing and pain-related fear in vigilance to pain: a structural equations approach. Pain 2004;107:234 – 41. [14] Eysenck HJ. The biological basis of personality. Springfield (Ill)7 CC Thomas, 1967. [15] Hjemdal O, Friborg O, Stiles TC, Rosenvinge JH, Martinussen M. Resilience predicting psychiatric symptoms: a prospective study of protective factors and their role in adjustment to negative life events. Clin Psychol Psychother 2005 [in press]. [16] Masten AS, Powell JL. A resilience framework for research, policy, and practice. In: Luthar SS, editor. Resilience and vulnerability: adaptation in the context of childhood adversities. New York7 Cambridge Univ. Press, 2003. pp. 1 – 25. [17] Rutter M. Psychosocial resilience and protective mechanisms. Am J Ortopsychiatry 1987;57:316 – 31. [18] Masten AS, Morison P, Pellegrini D, Tellegen A. Competence under stress: risk and protective factors. In: Masten AS, et al., editors. Risk and protective factors in the development of psychopathology. New York7 Cambridge Univ. Press, 1990. pp. 236 – 56. [19] Gil KM, Carson JW, Porter LS, Ready J, Valrie C, Redding-Lallinger R, Daeschner C. Daily stress and mood and their association with pain, health-care use, and school activity in adolescents with sickle cell disease. J Pediatr Psychol 2003;28:363 – 73. [20] Smith GM, Egbert LD, Markowitz RA, Mosteller F, Beecher HK. An experimental pain method sensitive to morphine in man: the submaximum torniquet technique. J Pharmacol Exp Ther 1966;154: 324 – 32. [21] DePascalis V, Chiaradia C, Carotenuto E. The contribution of suggestibility and expectation to placebo analgesia phenomenon in an experimental setting. Pain 2002;96:393 – 402. [22] Pertovaara A, Nurmikko T, Pfntinen PJ. Two separate components of pain produced by the submaximal effort tourniquet test. Pain 1984;20: 53 – 8. [23] Cuthbert BN, Schupp HT, Bradley MM, Birbaumer N, Lang PJ. Brain potentials in affective picture processing: covariation with autonomic arousal and affective report. Biol Psychol 2000;52: 95 – 111. [24] O’Neill ST, Parrot AC. Stress and arousal in sedative and stimulant cigarette smokers. Psychopharmacology 1992;107:442 – 6. [25] Friborg O, Martinussen M, Rosenvinge J. Likert-based versus semantic differential-based scorings of positive psychological
O. Friborg et al. / Journal of Psychosomatic Research 61 (2006) 213 – 219 constructs: a psychometric comparison of two versions of a scale measuring resilience. Pers Individ Differ 2006;40:873 – 84. [26] Jfreskog KG, Sfrbom D. LISREL 8: users’ reference guide. Mooresville (Ind)7 Scientific Software Inc, 1996. [27] Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling 1999;6:1 – 55. [28] Bagiella E, Sloan RP, Heitjan DF. Mixed-effects models in psychophysiology. Psychophysiology 2000;37:13 – 20.
219
[29] Cohen J. Statistical power analysis for the behavioural sciences. New York7 Academic Press, 1988. [30] Kirschbaum C, Pirke KM, Hellhammer DH. The b Trier Social Stress TestQ: a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology 1993;28:76 – 81. [31] Todd KH, Funk KG, Funk JP. Clinical significance of reported changes in pain severity. Ann Emerg Med 1996;27:485 – 9. [32] Flaten MA, Aslaksen PM, Finset A, Simonsen T. Cognitive and emotional factors in placebo analgesia. J Psychosom Res [in press].