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1.
Psychosom Med ; 85(4): 351-357, 2023 05 01.
Article in English | MEDLINE | ID: mdl-36825929

ABSTRACT

OBJECTIVE: Posttraumatic stress disorder (PTSD) and traumatic life events are often coupled to chronic pain, possibly linked by central sensitization. We wanted to assess the prevalence of traumatic events and PTSD in chronic pain patients of a German university hospital outpatient pain clinic. Moreover, we evaluated the extent of indicators and co-occurring traits of central sensitization in comorbid patients. METHODS: We retrospectively divided 914 chronic pain patients into four groups depending on their trauma severity: no trauma, accidental trauma, interpersonal trauma, and PTSD. We collected electronic pain drawings focusing on pain area and widespreadness, as well as information about pain intensity, sleep impairment, disability, stress, anxiety, depression, and somatization. Differences between groups were calculated using Kruskal-Wallis with post-hoc Mann-Whitney tests. RESULTS: Of 914 patients, 231 (25%) had no trauma, 210 (23%) had accidental traumas, 283 (31%) had interpersonal traumas, 99 (11%) had PTSD, and 91 (10%) could not be classified. We observed statistically significant differences between groups in pain area and widespreadness, as well as maximal pain, sleep impairment, disability, stress, anxiety, depression, and somatization. The severity of symptoms increased with trauma severity. CONCLUSIONS: Traumatic life events and PTSD are frequent in chronic pain patients. The increased pain area and widespreadness, as well as the increased negative impact on co-occurring traits of sensory sensitivity (anxiety, depression, somatization), are compatible with central sensitization in comorbid patients. Therefore, a heightened awareness of the comorbidity between traumatic experiences and chronic pain is recommended.


Subject(s)
Chronic Pain , Stress Disorders, Post-Traumatic , Humans , Stress Disorders, Post-Traumatic/epidemiology , Stress Disorders, Post-Traumatic/diagnosis , Chronic Pain/epidemiology , Central Nervous System Sensitization , Outpatients , Pain Clinics , Retrospective Studies , Comorbidity
3.
JMIR Mhealth Uhealth ; 7(9): e14569, 2019 09 05.
Article in English | MEDLINE | ID: mdl-31489841

ABSTRACT

BACKGROUND: In a pain drawing (PD), the patient shades or marks painful areas on an illustration of the human body. This simple yet powerful tool captures essential aspects of the subjective pain experience, such as localization, intensity, and distribution of pain, and enables the extraction of meaningful information, such as pain area, widespreadness, and segmental pattern. Starting as a simple pen-on-paper tool, PDs are now sophisticated digital health applications paving the way for many new and exciting basic translational and clinical applications. OBJECTIVE: Grasping the full potential of digital PDs and laying the groundwork for future medical PD apps requires an understanding of the methodological developments that have shaped our current understanding of uses and design. This review presents methodological milestones in the development of both pen-on-paper and digital PDs, thereby offering insight into future possibilities created by the transition from paper to digital. METHODS: We conducted a systematic literature search covering PD acquisition, conception of PDs, PD analysis, and PD visualization. RESULTS: The literature search yielded 435 potentially relevant papers, from which 53 methodological milestones were identified. These milestones include, for example, the grid method to quantify pain area, the pain-frequency maps, and the use of artificial neural networks to facilitate diagnosis. CONCLUSIONS: Digital technologies have had a significant influence on the evolution of PDs, whereas their versatility is leading to ever new applications in the field of medical apps and beyond. In this process, however, there is a clear need for better standardization and a re-evaluation of methodological and technical limitations that no longer apply today.


Subject(s)
Human Body , Mobile Applications/standards , Pain Measurement/instrumentation , Pain/classification , Humans , Mobile Applications/trends , Pain/diagnosis , Pain Measurement/methods
4.
JMIR Mhealth Uhealth ; 7(1): e11412, 2019 01 10.
Article in English | MEDLINE | ID: mdl-30632970

ABSTRACT

BACKGROUND: Pain drawings (PDs) are an important tool to evaluate, communicate, and objectify pain. In the past few years, there has been a shift toward tablet-based acquisition of PDs, and several studies have been conducted to test the usefulness, reliability, and repeatability of electronic PDs. However, to our knowledge, no study has investigated the potential role of electronic PDs in the clinical assessment and treatment of inpatients in acute pain situations. OBJECTIVE: The aim of this study was to evaluate whether knowledge of the patients' electronic PD has the potential to improve the doctors' understanding of their patients and to influence their clinical decision making. Furthermore, we sought to identify differences between electronic PDs of patients and their treating pain specialists in an acute pain situation and to find those specific characteristics derived from the PDs that had the largest impact on doctors' understanding. METHODS: We obtained electronic PDs from 47 inpatients in acute pain situations before their consultation with a pain specialist on a tablet personal computer with a stylus. Before looking at their patients' drawings, these specialists drew their own conception of the patients' pain after anamnesis and physical examination. Patients' drawings were then revealed to the doctors, and they were asked to evaluate how much the additional information improved their understanding of the case and how much it influenced their clinical decision on an 11-point Likert scale (0="not at all" and 10="very much"). Similarities and differences of patients' and doctors' PDs were assessed by visual inspection and by calculating Jaccard index and intraclass correlation coefficient (ICC) of the pain area and the number of pain clusters. Exploratory analyses were conducted by means of correlation tables to identify specific factors that influenced doctors' understanding. RESULTS: Patients' PDs significantly improved the doctors' understanding (mean score 4.81, SD 2.60, P<.001) and to a lesser extent their clinical decision (mean 2.68, SD 1.18, P<.001). Electronic PDs of patients and doctors showed fair to good similarity for pain extent (r=.454, P=.001) and widespreadness (P=.447, r=.002) were important factors helping doctors to understand their patients. CONCLUSIONS: In a clinical setting, electronic PDs can improve doctors' understanding of patients in acute pain situations. The ability of electronic PDs to visualize differences between doctors' and patients' conception of pain has the potential to improve doctor-patient communication.


Subject(s)
Art , Pain Measurement/instrumentation , Physician-Patient Relations , Physicians/psychology , Acute Pain/psychology , Acute Pain/therapy , Adolescent , Adult , Aged , Aged, 80 and over , Computers, Handheld/trends , Female , Humans , Male , Middle Aged , Pain Measurement/methods , Pain Measurement/standards , Physicians/standards , Surveys and Questionnaires
5.
JMIR Mhealth Uhealth ; 6(5): e127, 2018 May 30.
Article in English | MEDLINE | ID: mdl-29848470

ABSTRACT

BACKGROUND: Symptom drawings are widely used as a qualitative and quantitative method of assessing pain symptoms for both clinical and research purposes. As electronic drawings offer many advantages over classical pen-and-paper drawings, the last years have seen a shift toward tablet-based acquisition of symptom drawings. However, software that is used in clinical care requires special attention to usability aspects and design to provide easy access for physically impaired or elderly patients. OBJECTIVE: The aims of this project were to develop a new tablet-based software app specifically designed to collect patients' and doctors' drawings of pain and related bodily symptoms and test it for usability in 2 samples of chronic pain patients (Aim 1) and their treating doctors (Aim 2) as well as for test-retest reliability (Aim 3). METHODS: In 2 separate studies, symptom drawings from 103 chronic pain patients and their treating doctors were collected using 2 different versions of the app. Both patients and doctors evaluated usability aspects of the app through questionnaires. Results from study 1 were used to improve certain features of the app, which were then evaluated in study 2. Furthermore, a subgroup of 25 patients in study 2 created 2 consecutive symptom drawings for test-retest reproducibility analysis. Usability of both app versions was compared, and reproducibility was calculated for symptom extent, number of symptom clusters, and the whole symptom pattern. RESULTS: The changes we made to the app and the body outline led to significant improvements in patients' usability evaluation regarding the identification with the body outline (P=.007) and the evaluation of symptom depth (P=.02), and the overall difficultness of the drawing process (P=.003) improved significantly. Doctors' usability evaluation of the final app showed good usability with 75.63 (SD 19.51) points on the System Usability Scale, Attrakdiff 2 scores from 0.93 to 1.41, and ISONORM 9241/10 scores from -0.05 to 1.80. Test-retest analysis showed excellent reproducibility for pain extent (intraclass correlation coefficient, ICC=0.92) and good results for the number of symptom clusters (ICC=0.70) and a mean overlap of 0.47 (Jaccard index). CONCLUSIONS: We developed a tablet-based symptom drawing app and improved it based on usability assessment in a sample of chronic pain patients and their treating doctors. Increases in usability of the improved app comprised identification with the body outline, symptom depth evaluation, and difficultness of the drawing process. Test-retest reliability of symptom drawings by chronic pain patients showed fair to excellent reproducibility. Patients' usability evaluation is an important factor that should not be neglected when designing apps for mobile or eHealth apps.

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