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Turk, Dennis C.; Dworkin, Robert H.

doi:10.1186/ar1196

Cited by 71 publications

(21 citation statements)

References 5 publications

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“…58;228–230 Given the synergy between pain and negative affect, this makes good logical sense: efficacious analgesic treatments that reduce the frequency and intensity of pain should have a beneficial effect on patients’ affective states and appropriate treatment of emotional distress should have a positive influence on the experience of pain 9;12;128;137 . Indeed, several randomized controlled trials in primary care settings have shown that antidepressant treatment in patients with comorbid chronic pain and mood disorders produces fairly rapid analgesic benefits that are anticipated by, and robustly correlated with, improvements in indices of psychosocial distress 127;193 .…”

Section: The Biopsychosocial Model Of Painmentioning

confidence: 99%

The Role of Psychosocial Processes in the Development and Maintenance of Chronic Pain

Edwards

Dworkin

Sullivan

et al. 2016

The Journal of Pain

627

544

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The recently-proposed ACTTION-APS Pain Taxonomy provides an evidence-based, multidimensional, chronic pain classification system. Psychosocial factors play a crucial role within several dimensions of the Taxonomy. In this paper, we discuss the evaluation of psychosocial factors that influence the diagnosis and trajectory of chronic pain disorders. We review studies in individuals with a variety of persistent pain conditions, and describe evidence that psychosocial variables play key roles in conferring risk for the development of pain, in shaping long-term pain-related adjustment, and in modulating pain treatment outcomes. We consider both “general” psychosocial variables such as negative affect, childhood trauma, and social support, as well as “pain-specific” psychosocial variables that include pain-related catastrophizing, self-efficacy for managing pain, and pain-related coping. Collectively, the complexity and profound variability in chronic pain highlights the need to better understand the multidimensional array of interacting forces that determine the trajectory of chronic pain conditions.

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Section: The Biopsychosocial Model Of Painmentioning

confidence: 99%

The Role of Psychosocial Processes in the Development and Maintenance of Chronic Pain

Edwards

Dworkin

Sullivan

et al. 2016

The Journal of Pain

627

544

View full text Add to dashboard Cite

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“…Collectively, while instruments assessing depression, anxiety, and distress have most often appeared as outcome measures in the pain RCT literature [75;228–230], emerging evidence suggests that pre-treatment phenotyping of these patient symptoms can have important predictive effects [82]. On the basis of a review of the literature of measures of emotional functioning used in phenotyping participants in analgesic trials, the Hospital Anxiety and Depression Scale (HADS) can be recommended as a core phenotyping measure for assessing general negative affect (see the background materials for IMMPACT-XVI at http://www.immpact.org/index.html).…”

Section: Phenotypic Domainsmentioning

confidence: 99%

Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations

Edwards

Dworkin

Turk

et al. 2016

Pain

298

261

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There is tremendous inter-patient variability in the response to analgesic therapy (even for efficacious treatments), which can be the source of great frustration in clinical practice. This has led to calls for “precision medicine”, or personalized pain therapeutics (i.e., empirically-based algorithms that determine the optimal treatments, or treatment combinations, for individual patients) that would presumably improve both the clinical care of patients with pain, and the success rates for putative analgesic drugs in Phase 2 and 3 clinical trials. However, before implementing this approach, the characteristics of individual patients or subgroups of patients that increase or decrease the response to a specific treatment need to be identified. The challenge is to identify the measurable phenotypic characteristics of patients that are most predictive of individual variation in analgesic treatment outcomes, and the measurement tools that are best suited to evaluate these characteristics. In this article, we present evidence on the most promising of these phenotypic characteristics for use in future research, including psychosocial factors, symptom characteristics, sleep patterns, responses to noxious stimulation, endogenous pain-modulatory processes, and response to pharmacologic challenge. We provide evidence-based recommendations for core phenotyping domains and recommend measures of each domain.

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“…It has been estimated that there might be more than 30 million people in USA with chronic or recurrent pain [35]. Also nearly half of Americans seeking treatment from a physician report pain as their primary symptom.…”

Section: Introductionmentioning

confidence: 99%

“…Also nearly half of Americans seeking treatment from a physician report pain as their primary symptom. The United States Bureau of the Census estimated the total cost for chronic pain to exceed $150 billion annually in year 1995–96 [35, 10]. Thus there has been a significant research effort in improving pain management over the years.…”

Section: Introductionmentioning

confidence: 99%

Classification and weakly supervised pain localization using multiple segment representation

Sikka

Dhall

Bartlett

2014

Image and Vision Computing

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Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through ‘concept frames’ to ‘concept segments’ and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our algorithm and relates them to Action Units that have been associated with pain expression. We conclude the paper by demonstrating that MS-MIL yields a significant improvement on another spontaneous facial expression dataset, the FEEDTUM dataset.

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Untitled

Cited by 71 publications

References 5 publications

The Role of Psychosocial Processes in the Development and Maintenance of Chronic Pain

The Role of Psychosocial Processes in the Development and Maintenance of Chronic Pain

Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations

Classification and weakly supervised pain localization using multiple segment representation

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