Valuation of Multi-Dimensional Health States With a Bolt-On: Is There a Shortcut?

OBJECTIVES: To use the EQ-5D questionnaire with bolt-on dimensions in economic evaluation studies, new value sets are needed. In this study, we explored the feasibility of a new approach called the scaling factor model, which estimates bolt-on value sets using estimated EQ-5D dimensional weights. METHODS: We designed a 2-arm study, inviting university students to value health states with and without bolt-on items using the composite time trade-off method. We selected 25 health states from an orthogonal array and added the 5 mildest EQ-5D states in the design. In arm 1, EQ-5D without self-care and standard EQ-5D states were valued, and in arm 2, standard EQ-5D states and EQ-5D with vision were valued. By arm, we compared the mean observed values of health states with and without bolt-on item. Next, by arm, we estimated value sets for the EQ-5D with bolt-on states using both standard model and scaling factor model. Model performances were compared in terms of prediction accuracy and correlation with likelihood-based mean values. RESULTS: Adding a five-level bolt-on to EQ-5D resulted in statistically lower values. This effect was consistent across 2 arms and bolt-on items. The scaling factor models outperformed the standard models in all statistics. CONCLUSIONS: The scaling factor model offers a methodologically viable and low-cost option for producing value sets for EQ-5D supplemented with bolt-on items. Future studies should further test this method using other bolt-on items and more relevant study populations.

Testing the Psychometric Properties of 9 Bolt-Ons for the EQ-5D-5L in a General Population Sample.

OBJECTIVES: We aimed to assess the psychometric performance and added value of 9 existing bolt-ons (breathing problems, cognition, hearing, self-confidence, skin irritation, sleep, social relationships, tiredness, and vision) for the EQ-5D-5L in a general population sample. METHODS: The EQ-5D-5L, 9 bolt-ons, SF-6Dv1, Patient-Reported Outcomes Measurement Information System (PROMIS)-29+2, PROMIS Global Health, and Satisfaction with Life Scale were completed in an online cross-sectional survey among a general adult population sample in Hungary (n = 1587). The following psychometric properties were tested for the EQ-5D-5L + bolt-on(s): ceiling, divergent and convergent validity, structural validity, known-group validity, and explanatory power. RESULTS: Adding sleep (30%), tiredness (24%), or vision (21%) substantially reduced the ceiling of the EQ-5D-5L (41%). Cognition, sleep, social relationships, and tiredness correlated with corresponding PROMIS and SF-6D items (rs = ǀ0.32ǀ - ǀ0.73ǀ). All bolt-ons, except cognition and self-confidence, loaded on a different factor from the EQ-5D-5L dimensions. Breathing, hearing, skin irritation, and vision significantly improved known-group validity in relevant health condition groups. The sleep bolt-on improved known-group validity in 9 of 13 chronic health conditions. Tiredness had the largest impact on explaining EQ VAS score variance in 8 of 13 conditions. Hearing and vision improved the ability of the EQ-5D-5L to capture declining health with age, whereas self-confidence and social relationships were valuable for mental health assessment. CONCLUSIONS: This study established the validity of multiple bolt-ons for the EQ-5D-5L and highlights the usefulness of including relevant bolt-ons in population-based and patient surveys. Our findings inform the further development of these bolt-ons and the bolt-on item selection for clinical studies.

Exploring potential EQ-5D bolt-on dimensions with a qualitative approach: an interview study in Hong Kong SAR, China.

PURPOSE: The introduction of bolt-on dimensions in EQ-5D instruments is growing common, but most bolt-on studies have targeted the diseased population and obtained bolt-on from other existing Health-related Quality of Life (HRQoL) instruments. As the qualitative approach offers important evidence to support the consistency and design of the potential bolt-on items, this paper studies the Hong Kong SAR community's perception of the current EQ-5D-5 L instrument and identifies potential bolt-on via a qualitative approach. METHODS: A representative sample mix was recruited based on the age group, gender, and education level composition of the Hong Kong SAR community by quota sampling. Semi-structured interviews were conducted and the interviews were transcribed and coded to identify emergent and recurrent themes. RESULTS: Thirty interviews were conducted and the majority of the interviewees considered the EQ-5D-5 L insufficiently comprehensive to illustrate their HRQoL. While some key HRQoL aspects included in the EQ-5D matched with the community's HRQoL perception, respondents showed concern about the potential overlap of the existing HRQoL dimension, the optimal number or attributes, and the appropriateness of the EQ-VAS. Among the potential bolt-on dimensions that emerged, 'Sleep', 'Interpersonal Relationship', and 'Satisfaction' were the key potential bolt-on dimensions identified and emphasized in the interviews. CONCLUSIONS: The qualitative findings of the study illustrate the possible gap between EQ-5D-5 L measurements and community HRQoL perception, while the findings support the development of EQ-5D bolt-on dimensions in the target community with content and face validity.

Content validity of the EQ-5D-5L with skin irritation and self-confidence bolt-ons in patients with atopic dermatitis: a qualitative think-aloud study.

OBJECTIVES: Two bolt-on dimensions (skin irritation, self-confidence) have been developed for the EQ-5D-5L to improve its content validity and responsiveness in psoriasis. However, the two bolt-ons are not strictly psoriasis-specific and are potentially relevant in other skin conditions. This study aims to explore the content validity of the EQ-5D-5L with two bolt-ons in patients with atopic dermatitis (AD). METHODS: In 2021-2022, qualitative, semi-structured interviews were conducted with 20 adult AD patients at a university dermatology clinic in Hungary. We aimed for a heterogeneous sample in terms of age, gender, education and disease severity. Patients completed the EQ-5D-5L with two bolt-ons using a think-aloud protocol. Probing questions were posed to investigate item relevance, potential conceptual overlaps, missing concepts and the appropriateness of the recall period. Interview transcripts were subjected to thematic analysis. RESULTS: The EQ-5D-5L with the two bolt-ons covered the most important aspects of health-related quality of life in AD patients. Most patients found both the skin irritation and self-confidence bolt-ons relevant. Fifteen potential missing concepts were identified, but only two (social relationships, judgement by others) were identified by more than one patient. A smaller conceptual overlap was found between the skin irritation and pain/discomfort dimensions in 7 patients (35%). Half the patients expressed a preference for a recall period of 1 week rather than of 'today'. CONCLUSIONS: The EQ-5D-5L with skin irritation and self-confidence bolt-ons showed good relevance, comprehensiveness and comprehensibility in patients with AD. However, in terms of comprehensiveness, social relationships and judgement by others (stigma) may be missing from the questionnaire.

Boltless nylon-suture technique for stereotactic electroencephalography as a safe, effective alternative when the anchor bolt is inappropriate.

BACKGROUND: The use of anchor bolts to secure electrodes to the skull can be difficult in some clinical situations. Herein, we present the boltless technique to secure electrodes to the scalp using nylon sutures to overcome the problems associated with anchor bolts. We investigated the safety, accuracy errors, and patient-related and operative factors affecting errors in the boltless technique. METHODS: This single-institution retrospective series analyzed 103 electrodes placed in 12 patients. The target-point localization error (TPLE), entry-point localization error (EPLE), radial error (RE), and depth error (DE) of the electrodes were calculated. RESULTS: The median of the mean operative time per electrode was 9.3 min. The median TPLE, EPLE, RE, and absolute DE value were 4.1 mm, 1.6 mm, 2.7 mm, and 1.9 mm, respectively. Positive correlations were observed between the preoperative scalp thickness, mean operative time per electrode, EPLE, RE, and the absolute value of DE versus TPLE (r = .228, p = .02; r = .678, p = .015; r = .228, p = .02; r = .445, p < .01; r = .630, p < .01, respectively), and electrode approach angle versus EPLE (r = .213, p = .031). Multivariate analysis revealed that the absolute value of DE had the strongest influence on the TPLE, followed by RE and preoperative scalp thickness, respectively (ß = .938, .544, .060, respectively, p < .001). No complications related to SEEG insertion and monitoring were encountered. CONCLUSION: The boltless technique using our unique planning and technical method is a safe, effective, and low-cost alternative in cases where anchor bolts are contraindicated.

Image-Based Bolt-Loosening Detection Using a Checkerboard Perspective Correction Method.

In this paper, a new image-correction method for flange joint bolts is proposed. A checkerboard is arranged on the side of a flange node bolt, and the homography matrix can be estimated using more than four feature points, which include the checkerboard corner points. Then, the perspective distortion of the captured image and the deviation of the camera position angle are corrected using the estimated homography matrix. Due to the use of more feature points, the stability of homography matrix identification is effectively improved. Simultaneously, the influence of the number of feature points, camera lens distance, and light intensities are analyzed. Finally, based on a bolt image taken using an iPhone 12, the prototype structure of the flange joint in the laboratory is verified. The results show that the proposed method can effectively correct image distortion and camera position angle deviation. The use of more than four correction points not only effectively improves the stability of bolt image correction but also improves the stability and accuracy of bolt-loosening detection. The analysis of influencing factors shows that the proposed method is still effective when the number of checkerboard correction points is reduced to nine, and the average error of the bolt-loosening detection result is less than 1.5 degrees. Moreover, the recommended camera shooting distance range is 20 cm to 60 cm, and the method exhibits low sensitivity to light intensity.

Prediction of Pre-Loading Relaxation of Bolt Structure of Complex Equipment under Tangential Cyclic Load.

Bolts have the advantages of simple installation and easy removal. They are widely applied in aerospace and high-speed railway traffic. However, the loosening of bolts under mixed loads can lead to nonlinear decreases in pre-loading. This affects the safety performance of the structure and may lead to catastrophic consequences. Existing techniques cannot be used to monitor the bolt performance status in time. This has caused significant problems with the safety and reliability of equipment. In order to study the relaxation law of bolt pre-loading, this paper carries out an experimental analysis for 8.8-grade hexagonal bolts and calibrates the torque coefficient. We also studied different loading waveforms, nickel steel plate surface roughnesses, tangential displacement frequencies, four different strengths and bolt head contact areas of the bolt, the initial pre-loading, and the effects of tangential cyclic displacement on pre-loading relaxation. This was done in order to accurately predict the degree of bolt pre-loading loosening under external loads. The laws are described using the allometric model function and the nine-stage polynomial function. The least squares method is used to identify the parameters in the function. The results show that bolts with a smooth surface of the connected structure nickel steel flat plate, high-frequency working conditions, half-sine wave, and a high-strength have better anti-loosening properties. Taking 5-10 cycles of cyclic loading as a boundary, the pre-loading relaxation is divided into two stages. The first stage is a stage of rapid decrease in bolt pre-loading, and the second stage is the slow decrease process. The performance prediction study shows that the allometric model function is the worst fitted, at 71.7% for the small displacement condition. Other than that, the allometric model function and the nine-stage polynomial function can predict more than 85.5% and 90.4%, which require the use of least squares to identify two and ten unknown parameters, respectively. The complexity of the two is different, but both can by better indicators than the pre-loading relaxation law under specific conditions. It helps to improve the monitoring of bolt loosening and the system use cycle, and it can provide theoretical support for complex equipment working for a long time.

Early Bolt Loosening Detection Method Based on Digital Image Correlation.

Bolt loosening can significantly impact the accuracy, stability, and safety of equipment. The detection of bolt loosening in a timely manner is crucial for ensuring the safety, reliability, performance, and service life of equipment, structures, and systems. Various methods exist for detecting bolt loosening, such as strain gauges and ultrasonic waves. However, these technologies have some limitations that impede their widespread application. In this paper, for the high-pressure pipe manifolds that may experience leakage accidents due to the loosening of bolts, an early bolt loosening detection method based on digital image correlation is proposed. Initially, a model is established through tensile tests to relate the average strain on the side of the bolt head to the axial force. Subsequently, an industrial camera captures images of bolts with random speckles under operational conditions. Using digital image correlation technology, the average strain in a specific region on the side of the bolt head is calculated. By integrating the average strain into the established relationship model between the average strain and axial force, the axial force of the bolt under operational conditions can be predicted, enabling the early assessment of bolt loosening. The findings show that the average strain on the side of the bolt head increases proportionally with the axial force, indicating a strong linear relationship. This method enables accurate prediction of the bolt's axial force, offering a new approach for identifying the early loosening of bolts in high-pressure manifolds and monitoring structural health.

PMUT-Based System for Continuous Monitoring of Bolted Joints Preload.

In this paper, we present a bolt preload monitoring system, including the system architecture and algorithms. We show how Finite Element Method (FEM) simulations aided the design and how we processed signals to achieve experimental validation. The preload is measured using a Piezoelectric Micromachined Ultrasonic Transducer (PMUT) in pulse-echo mode, by detecting the Change in Time-of-Flight (CTOF) of the acoustic wave generated by the PMUT, between no-load and load conditions. We performed FEM simulations to analyze the wave propagation inside the bolt and understand the effect of different configurations and parameters, such as transducer bandwidth, transducer position (head/tip), presence or absence of threads, as well as the frequency of the acoustic waves. In order to couple the PMUT to the bolt, a novel assembly process involving the deposition of an elastomeric acoustic impedance matching layer was developed. We achieved, for the first time with PMUTs, an experimental measure of bolt preload from the CTOF, with a good signal-to-noise ratio. Due to its low cost and small size, this system has great potential for use in the field for continuous monitoring throughout the operative life of the bolt.

Signal Processing Using a Circular Sensor Array to Measure the Torsional Angle of a Bolted Joint.

This study presents a new approach to determining the preload force of bolted joints. The concept involves measuring the torsional angle without contact. For this purpose, we present a circular magnetic sensor array integrated into the torque wrench. The torsional angle in bolted joints depends on the dimensions of the screw and the materials used and is typically less than four degrees. For this reason, one requirement is a high angular resolution so that a continuous recording of the torsion angle is feasible during the assembly process. This can be achieved using the circular sensor array and adapted signal processing methods. Two signal processing approaches are utilized. First, the direct method uses the discrete Fourier transformation to calculate the rotation angle from the signal phase. This approach is robust to signal distortion and does not depend on signal amplitude. Second, the method with a learning phase employs Gaussian process regression to minimize the angle error. In an experiment, both approaches were applied within a test bench and showed promising results. The direct method demonstrated a very good angular resolution without training and calibration. For mobile and less-complex applications where a reference system is unavailable, the direct method is preferable. However, in complex measurement systems where reference systems can be utilized initially, significant enhancements to an excellent resolution can be achieved through prior training.

Crossbow Injuries: Predictors of Mortality.

INTRODUCTION: Crossbow injuries are rare but carry significant morbidity and mortality, and there is limited evidence in the medical literature to guide care. This paper reviews the case reports and case series of crossbow injuries and looks for trends regarding morbidity and mortality based on the type of arrow, anatomic location of injury, and intent of injury. METHODS: Multiple databases were searched for cases of crossbow injuries and data were abstracted into a spreadsheet. Statistics were done in SPSS. RESULTS: 358 manuscripts were returned in the search. After deduplication and removal of nonclinical articles, 101 manuscripts remained. Seventy-one articles describing 90 incidents met the inclusion criteria. The mean age was 36.5 years. There were 10 female and 79 male victims. Fatality was 36% for injuries by field tip arrows and 71% for broadhead arrows, p = .024. Assaults were fatal in 84% of cases, suicides in 29%, and accidental injuries in 17%, p < .001. Mortality was similar for wounds to the head and neck (41%), chest (42%), abdomen (33%), extremities (50%), and multiple regions, p = .618. CONCLUSIONS: Crossbows are potentially lethal weapons sold with fewer restrictions than firearms. Injuries caused by broadhead arrows are more likely to be fatal than injuries from field tip arrows. The anatomic location of injury does not correlate with fatality. More than half of crossbow injuries are due to attempted suicide, with a high case-fatality rate.

Extending the EQ-5D: the case for a complementary set of 4 psycho-social dimensions.

OBJECTIVES: The EQ-5D is the most widely applied preference-based health-related quality of life measure. However, concerns have been raised that the existing dimensional structure lacks sufficient components of mental and social aspects of health. This study empirically explored the performance of a coherent set of four psycho-social bolt-ons: Vitality; Sleep; Personal relationships; and Social isolation. METHODS: Cross-sectional surveys were conducted with online panel members from five countries (Australia, Canada, Norway, UK, US) (total N = 4786). Four bolt-ons were described using terms aligned with EQ nomenclature. Latent structures among all nine dimensions are studied using an exploratory factor analysis (EFA). The Shorrocks-Shapely decomposition analyses are conducted to illustrate the relative importance of the nine dimensions in explaining two outcome measures for health (EQ-VAS, satisfaction with health) and two for subjective well-being (the hedonic approach of global life satisfaction and an eudemonic item on meaningfulness). Sub-group analyses are performed on older adults (65 +) and socially disadvantaged groups. RESULTS: Strength of correlations among four bolt-ons ranges from 0.34 to 0.49. As for their correlations with the EQ-5D dimensions, they are generally much less correlated with four physical health dimensions than with mental health dimensions (ranged from 0.21 to 0.50). The EFA identifies two latent factors. When explaining health, Vitality is the most important. When explaining subjective well-being, Social isolation is second most important, after Anxiety/depression. CONCLUSION: We provide evidence that further complementing the current EQ-5D-5L health state classification system with a coherent set of four bolt-on dimensions that will fill its psycho-social gap.

Trajectory of bolt and length of plate in femoral neck system determine the stability of femur neck fracture and risk of subsequent subtrochanteric fracture : a finite element analysis.

BACKGROUND: This study aimed to analyze the differences in the stability of fractures, stress distribution around the distal-most screw according to the length of the plate and the trajectory of the bolt in Pauwels type III femoral neck fracture using the femoral neck system (FNS). METHODS: Finite element models of Pauwels type III femoral neck fractures were established with surgical variations in the trajectory of the bolt (central, inferior, valgus, and varus) and length of the lateral plate (1- and 2-hole plate). The models were subsequently subjected to normal walking and stair-climbing loads. RESULTS: The screw-holding cortical bone in subtrochanter in the model with a 2-hole plate and the bolt in the inferior trajectory and the models with 1-hole or 2-hole plate and the bolt in valgus trajectory had shown greater maximum principal strain than the models with central or varus trajectories. The gap and sliding distance on the fracture surface were larger with inferior or varus trajectories of the bolt and smaller with the valgus trajectory of the bolt under both loads, compared to those of the central trajectory. CONCLUSION: For the fixation of Pauwels type III femoral neck fracture, the trajectory of the FNS bolt and the length of the plate affect the mechanical stability of the fracture and the strain of cortical bone around the distal-most screw. The surgical target should stay on the central trajectory of the bolt and the 2-hole plate's mechanical benefits did not exceed the risk.

Scattered Train Bolt Point Cloud Segmentation Based on Hierarchical Multi-Scale Feature Learning.

In view of the difficulty of using raw 3D point clouds for component detection in the railway field, this paper designs a point cloud segmentation model based on deep learning together with a point cloud preprocessing mechanism. First, a special preprocessing algorithm is designed to resolve the problems of noise points, acquisition errors, and large data volume in the actual point cloud model of the bolt. The algorithm uses the point cloud adaptive weighted guided filtering for noise smoothing according to the noise characteristics. Then retaining the key points of the point cloud, this algorithm uses the octree to partition the point cloud and carries out iterative farthest point sampling in each partition for obtaining the standard point cloud model. The standard point cloud model is then subjected to hierarchical multi-scale feature extraction to obtain global features, which are combined with local features through a self-attention mechanism, while linear interpolation is used to further expand the perceptual field of local features of the model as a basis for segmentation, and finally the segmentation is completed. Experiments show that the proposed algorithm could deal with the scattered bolt point cloud well, realize the segmentation of train bolt and background, and could achieve high segmentation accuracy, which has important practical significance for train safety detection.

Bolt Installation Defect Detection Based on a Multi-Sensor Method.

With the development of industrial automation, articulated robots have gradually replaced labor in the field of bolt installation. Although the installation efficiency has been improved, installation defects may still occur. Bolt installation defects can considerably affect the mechanical properties of structures and even lead to safety accidents. Therefore, in order to ensure the success rate of bolt assembly, an efficient and timely detection method of incorrect or missing assembly is needed. At present, the automatic detection of bolt installation defects mainly depends on a single type of sensor, which is prone to mis-inspection. Visual sensors can identify the incorrect or missing installation of bolts, but it cannot detect torque defects. Torque sensors can only be judged according to the torque and angel information, but cannot accurately identify the incorrect or missing installation of bolts. To solve this problem, a detection method of bolt installation defects based on multiple sensors is proposed. The trained YOLO (You Only Look Once) v3 network is used to judge the images collected by the visual sensor, and the recognition rate of visual detection is up to 99.75%, and the average confidence of the output is 0.947. The detection speed is 48 FPS, which meets the real-time requirement. At the same time, torque and angle sensors are used to judge the torque defects and whether bolts have slipped. Combined with the multi-sensor judgment results, this method can effectively identify defects such as missing bolts and sliding teeth. Finally, this paper carried out experiments to identify bolt installation defects such as incorrect, missing torque defects, and bolt slips. At this time, the traditional detection method based on a single type of sensor cannot be effectively identified, and the detection method based on multiple sensors can be accurately identified.

Axial Load Measurement of Bolts with Different Clamping Lengths Based on High-Frequency Ultrasonic ZnO Film Sensor.

The ultrasonic testing method has been widely used for measuring the axial load of bolts. However, systematic calibrations are prerequisite if specific bolts have different clamping length configurations, which leads to low efficiency and measurement errors. The focus of this work was to measure the axial load of bolts with different clamping lengths by proposing a method of clamping length correction based on piezoelectric films in order to avoid the complicated calibration steps. Firstly, the relationship between longitudinal wave time-of-flight (TOF) and axial load under different clamping lengths was studied to correct the difference between the effective stress length and the actual clamping length. Secondly, the high-frequency ZnO piezoelectric film sensor was fabricated on the bolts to improve the accuracy of longitudinal wave TOF measurement. The results showed that the center frequency of the fabricated ultrasonic sensor reached 25 MHz, which could realize the high precision measurement of TOF. The proposed correction model proved to be effective for decreasing the measurement error below 2.7% in this experiment. In conclusion, the proposed method simplified the calibration procedure for different application configurations of the same bolt and realized the efficient measurement of bolt axial load.

A Support Vector Machine-Based Approach for Bolt Loosening Monitoring in Industrial Customized Vehicles.

Machine learning techniques have progressively emerged as important and reliable tools that, when combined with machine condition monitoring, can diagnose faults with even superior performance than other condition-based monitoring approaches. Furthermore, statistical or model-based approaches are often not applicable in industrial environments with a high degree of customization of equipment and machines. Structures such as bolted joints are a key part of the industry; therefore, monitoring their health is critical to maintaining structural integrity. Despite this, there has been little research on the detection of bolt loosening in rotating joints. In this study, vibration-based detection of bolt loosening in a rotating joint of a custom sewer cleaning vehicle transmission was performed using support vector machines (SVM). Different failures were analyzed for various vehicle operating conditions. Several classifiers were trained to evaluate the influence of the number and location of accelerometers used and to determine the best approach between specific models for each operating condition or a single model for all cases. The results showed that using a single SVM model with data from four accelerometers mounted both upstream and downstream of the bolted joint resulted in more reliable fault detection, with an overall accuracy of 92.4%.

Detection of Missing Bolts for Engineering Structures in Natural Environment Using Machine Vision and Deep Learning.

The development of an accurate and efficient method for detecting missing bolts in engineering structures is crucial. To this end, a missing bolt detection method that leveraged machine vision and deep learning was developed. First, a comprehensive dataset of bolt images captured under natural conditions was constructed, which improved the generality and recognition accuracy of the trained bolt target detection model. Second, three deep learning network models, namely, YOLOv4, YOLOv5s, and YOLOXs, were compared, and YOLOv5s was selected as the bolt target detection model. With YOLOv5s as the target recognition model, the bolt head and bolt nut had average precisions of 0.93 and 0.903, respectively. Third, a missing bolt detection method based on perspective transformation and IoU was presented and validated under laboratory conditions. Finally, the proposed method was applied to an actual footbridge structure to test its feasibility and effectiveness in real engineering scenarios. The experimental results showed that the proposed method could accurately identify bolt targets with a confidence level of over 80% and detect missing bolts under different image distances, perspective angles, light intensities, and image resolutions. Moreover, the experimental results on a footbridge demonstrated that the proposed method could reliably detect the missing bolt even at a shooting distance of 1 m. The proposed method provided a low-cost, efficient, and automated technical solution for the safety management of bolted connection components in engineering structures.

Criteria for developing, assessing and selecting candidate EQ-5D bolt-ons.

PURPOSE: 'Bolt-on' dimensions are additional items added to multi-attribute utility instruments (MAUIs) such as EQ-5D that measure constructs not included in the core descriptive system. The use of bolt-ons has been proposed to improve the content validity and responsiveness of the descriptive system in certain settings and health conditions. EQ-5D bolt-ons serve a particular purpose and thus satisfy a certain set of criteria. The aim of this paper is to propose a set of criteria to guide the development, assessment and selection of candidate bolt-on descriptors. METHODS: Criteria were developed using an iterative approach. First, existing criteria were identified from the literature including those used to guide the development of MAUIs, the COSMIN checklist and reviews of existing bolt-ons. Second, processes used to develop bolt-ons based on qualitative and quantitative approaches were considered. The information from these two stages was formalised into draft development and selection criteria. These were reviewed by the project team and iteratively refined. RESULTS: Overall, 23 criteria for the development, assessment and selection of candidate bolt-ons were formulated. Development criteria focused on issues relating to i) structure, ii) language, and iii) consistency with the existing EQ-5D dimension structure. Assessment and selection criteria focused on face and content validity and classical psychometric indicators. CONCLUSION: The criteria generated can be used to guide the development of bolt-ons across different health areas. They can also be used to assess existing bolt-ons, and inform their inclusion in studies and patient groups where the EQ-5D may lack content validity.

A qualitative investigation of the relevance of skin irritation and self-confidence bolt-ons and their conceptual overlap with the EQ-5D in patients with psoriasis.

OBJECTIVES: A number of bolt-ons have been proposed for the EQ-5D, including two psoriasis-specific bolt-ons, skin irritation and self-confidence. The study investigates and compares the relevance and comprehensiveness of these psoriasis-specific bolt-ons and the EQ-5D-5L and explores the potential conceptual overlaps between the existing five dimensions and the two bolt-ons. METHODS: Psoriasis patients were purposively sampled according to age and gender. Semi-structured interviews, where participants were asked to complete the EQ-5D-5L and the bolt-ons while thinking aloud, were conducted. Probes were used to investigate the thought processes of patients regarding the dimensions, wording, recall period and relevant concepts not captured by the EQ-5D-5L and bolt-ons. Data were analysed thematically. A focus group was used to confirm the findings. RESULTS: Overall, 16 patients completed the interviews. Sixteen and fifteen patients considered skin irritation and self-confidence relevant areas to describe psoriasis problems. Three patients considered itching a form of discomfort, and thus, pointed out a potential overlap between pain/discomfort and skin irritation. Twelve patients reported overall 10 general health- or psoriasis-related concepts that are not captured by the EQ-5D-5L, including itching, social relationships and sex life. Eleven patients reported that the recall period of the EQ-5D-5L might be subject to bias because of the daily or within-day fluctuations of their symptoms. CONCLUSIONS: The skin irritation and self-confidence bolt-ons contribute to improve content validity of the EQ-5D-5L in patients with psoriasis. The qualitative approach taken in this study expands the existing methodological framework for the development and testing validity of bolt-ons for the EQ-5D.