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Objectives The belief in medical care entitlement has recently resulted in major changes in the medical system in the United States. The objectives of this study were the following: to compare endorsement of three medical entitlement beliefs (I deserve the best medical care no matter what the cost [BMC], I am entitled to all of the medical care I want at no charge [NC], I shouldn't have to wait to see my doctors [W]) in community nonpatients without pain (CNPWP), acute pain patients (APPs), and chronic pain patients (CPPs) and to develop predictor models for these beliefs in APPs and CPPs. Design CNPWP, APPs, and CPPs were compared statistically for frequency of endorsement of each belief. All available variables were utilized in logistic regression models to predict each belief in APPs and CPPs. Those affirming/nonaffirming each belief were compared by t-test for affirmation of narcissism, dependency, and antisocial practices on three scales from established inventories. Results CPPs were significantly more likely than APPs to endorse BMC. No other comparisons were significant. The logistic regression models identified variables that related to narcissism, anger, doctor dissatisfaction, depression, and anxiety, which entered the models for both APPs and CPPs for some beliefs. Those APPs and CPPs who affirmed the beliefs of NC and W were more likely than their counterparts to affirm antisocial practices, but not narcissism or dependency. Conclusions Patient medical entitlement beliefs may be related to some psychiatric/psychological issues.

OBJECTIVES: To further explore the controversy as to whether childhood molestation is associated with chronic pain in adulthood. DESIGN: Community nonpatients without pain (CNPWP), community patients with pain (CPWP), acute pain patients (APPs), and chronic pain patients (CPPs) were compared for endorsement of affirmation of childhood molestation by chi-square. Logistic regression was utilized to predict affirmation in male and female CPPs. RESULTS: A significantly higher percentage of male APPs affirmed molestation versus CNPWP and CPWP. No other comparisons were statistically significant for males. For females, no comparisons were significant. For male CPPs, the behavior health inventory-2 (BHI-2) survivor of violence scale and 1 item from this scale predicted affirmation. The following BHI-2 scales and items predicted affirmation for female CPPs: muscular bracing and survivor of violence scales; the item "I have been a victim of many sexual attacks"; and the item "My father was kind and loving to me when I was growing up" (scored opposite direction). CONCLUSIONS: In female PWCP, the prevalence of childhood molestation is not greater than in a number of unique comparison groups. Unique predictors of childhood molestation are yet to be identified. Language: en

Objectives: One indirect line of evidence for opioid-induced hyperalgesia (OIH) in humans is decreased pain thresholds (PTREs) and tolerances (PTOLs) in opioid addicts on opioids. There are a number of such studies in opioid maintained addicts, but no such studies in chronic pain patients (CPPs) with current opioid addiction. The objective of this study was to determine if this group demonstrates hyperalgesia. Methods: CPPs were subdivided into those with psychoactive substance (opioid dependence) (PSOD) (n = 38) (addicted) and those taking opioids but without PSOD (n = 198) (not addicted). A group of opioid-free non-CPPs served as a control group (n = 36). PTREs/PTOLs were determined in each group by pressure pain stimulation in both the right and left index fingers. PTREs/PTOLs were compared by analysis of variance among the three groups controlling for sex/age and by analysis of covariance between the PSOD CPPs and non-PSOD CPPs controlling for duration of pain and visual analog scale pain level over the last 24 hours. Results: The PSOD and non-PSOD CPPs had significantly lower PTREs and PTOLs vs. the control group, ie, were hyperalgesic. However, they were not significantly different from each other. Conclusions: This study contributes to the human OIH literature. However, because of the potential confounders in this study, the issue of OIH in humans remains unresolved.

Objectives: (1) Determine and compare prevalence of forms of anger (FOA; anger, hostility, aggression, anger-in, anger-out, chronic anger) in community nonpatients (n = 478), community patients (n = 158), acute pain patients (APPs; n = 326), chronic pain patients (CPPs; n = 341); and (2) develop FOA predictor models in APPs and CPPs. Design: A large set of items containing the FOA items was administered to the above groups, who were compared statistically for FOA endorsement. APPs and CPPs affirming the anger and chronic anger items were compared with those not affirming on all available variables including the Battery for Health Improvement (BHI-2) with significant variables (P ≤ 0.001) utilized in predictor models for anger and chronic anger in APPs and CPPs. Setting community plus rehabilitation facilities. Results: FOA affirmation ranged from 8.28% for chronic anger in nonpatients to 37.54% for anger in CPPs. Only CPPs were more likely to affirm anger (P ≤ 0.04) and chronic anger (P ≤ 0.01) at a significantly higher rate than community patients. In both APPs and CPPs, all FOA items except anger management-in were significantly correlated with other FOA items. For anger and chronic anger for CPPs and APPs, hostility was the strongest predictor. All models predicted anger and chronic anger significantly better than the base rate prediction. Conclusion: According to the results of this study anger and chronic anger are more frequently found in CPPs vs. community patients supporting the clinical perception that many CPPs are angry. As such,clinicians should actively screen CPPs for the presence of anger in order to engage these CPPs in anger management treatment.

Objectives: The objectives of this article were the following: (1) determine risk for self-predicted future psychopharmacological nonadherence in rehabilitation acute pain patients (APPs) and rehabilitation chronic pain patients (CPPs) vs. pain-free community controls and community patients, and (2) determine which variables predict nonadherence. Design: The Battery for Health Improvement 2 was developed utilizing a healthy (pain-free) community sample (N = 1,478), a community patient sample (N = 158), and a rehabilitation patient sample (N = 777) of which 326 were APPs, 341 were CPPs, and 110 were patients without pain. These groups predicted their future psychopharmacological treatment adherence. Risk for nonadherence was calculated for each group utilizing the healthy community sample as the reference group. Nonadherent and adherent APPs and CPPs were compared statistically on variables of interest. Significant variables (P ≤ 0.01) were utilized in APPs' and CPPs' logistic regression models to predict nonadherence. Setting: The participants in this article were from a variety of settings. Results: Of APPs and CPPs, 10.74% and 10.85%, respectively, predicted that they would be nonadherent. Risk for nonadherence was greater in both groups vs. healthy nonpain community subjects and nonhealthy community patients. The predictors for APPs' nonadherence were general resistance to using medications and a tendency to forget physicians' suggestions. For CPPs, the predictors were general resistance to using medications, fear of dependence on prescription medications, and fighting with loved ones. The models classified 90% and 89% of APPs and CPPs (respectively) correctly. However, these were no better than the base rate. Conclusions: APPs and CPPs are at greater risk for self-predicted psychopharmacological nonadherence than healthy community subjects and community patients. We cannot as yet predict self-predicted psychopharmacological nonadherence at greater than the base rate. However, the identified variables could be clinically useful.

Study Design: This is an evidence-based structured review. Objectives: The objectives of this review were to answer the following questions: (1) Are somatization/hypochondriasis associated with chronic pain? (2) Is the degree of somatization/hypochondriasis related to pain levels? (3) Does pain treatment improve somatization/hypochondriasis? (4) Are some pain diagnoses differentially associated with somatization/hypochondriasis? Methods: Fifty-seven studies which fulfilled inclusion criteria and had high quality scores were sorted by the above-mentioned objectives. Agency for health care policy and research guidelines were utilized to type and characterize the strength/consistency of the study evidence within each objective. Results: Somatization and hypochondriasis were both consistently associated with chronic pain (consistency ratings B and A, respectively). Study evidence indicated a correlation between pain intensity and presence of somatization and hypochondriasis (consistency rating A and B, respectively). Pain treatment improved somatization and hypochondriasis (consistency rating B and A, respectively). Some chronic pain diagnostic groups somatized more (consistency rating B). Conclusions: Somatization is commonly associated with chronic pain and may relate to pain levels.