Development of a data collection tool to profile osteopathic practice: Use of a nominal group technique to enhance clinician involvement

Low-cost and precise traditional Chinese medicinal tree pest and disease monitoring using UAV RGB image only

Accurate and timely pest and disease monitoring during the cultivation process of traditional Chinese medicinal materials is crucial for ensuring optimal growth, increased yield, and enhanced content of effective components. This paper focuses on the essential requirements for pest and disease monitoring in a planting base of Cinnamomum Camphora var. Borneol (CCB) and presents a solution using unmanned aerial vehicle (UAV) images to address the limitations of real-time and on-site inspections. In contrast to existing solutions that rely on advanced sensors like multispectral or hyperspectral sensors mounted on UAVs, this paper utilizes visible light sensors directly. It introduces an ensemble learning approach for pest and disease monitoring of CCB trees based on RGB-derived vegetation indices and a combination of various machine learning algorithms. By leveraging the feature extraction capabilities of multiple algorithms such as RF, SVM, KNN, GBDT, XGBoost, GNB, and ELM, and incorporating morphological filtering post-processing and genetic algorithms to assign weights to each classifier for optimal weight combination, a novel ensemble learning strategy is proposed to significantly enhance the accuracy of pest and disease monitoring of CCB trees. Experimental results validate that the proposed method can achieve precise pest and disease monitoring with reduced training samples, exhibiting high generalization ability. It enables large-scale pest and disease monitoring at a low cost and high precision, thereby contributing to improved precision in the cultivation management of traditional Chinese medicinal materials.

Responsiveness, Reliability, and Minimally Important and Minimal Detectable Changes of 3 Electronic Patient-Reported Outcome Measures for Low Back Pain: Validation Study

Background

The Roland Morris Disability Questionnaire (RMDQ), visual analog scale (VAS) of pain intensity, and numerical rating scale (NRS) are among the most commonly used outcome measures in trials of interventions for low back pain. Their use in paper form is well established. Few data are available on the metric properties of electronic counterparts.

Objective

The goal of our research was to establish responsiveness, minimally important change (MIC) thresholds, reliability, and minimal detectable change at a 95% level (MDC₉₅) for electronic versions of the RMDQ, VAS, and NRS as delivered via iOS and Android apps and Web browser.

Methods

We recruited adults with low back pain who visited osteopaths. We invited participants to complete the eRMDQ, eVAS, and eNRS at baseline, 1 week, and 6 weeks along with a health transition question at 1 and 6 weeks. Data from participants reporting recovery were used in MIC and responsiveness analyses using receiver operator characteristic (ROC) curves and areas under the ROC curves (AUCs). Data from participants reporting stability were used for analyses of reliability (intraclass correlation coefficient [ICC] agreement) and MDC₉₅.

Results

We included 442 participants. At 1 and 6 weeks, ROC AUCs were 0.69 (95% CI 0.59 to 0.80) and 0.67 (95% CI 0.46 to 0.87) for the eRMDQ, 0.69 (95% CI 0.58 to 0.80) and 0.74 (95% CI 0.53 to 0.95) for the eVAS, and 0.73 (95% CI 0.66 to 0.80) and 0.81 (95% CI 0.69 to 0.92) for the eNRS, respectively. Associated MIC thresholds were estimated as 1 (0 to 2) and 2 (–1 to 5), 13 (9 to 17) and 7 (–12 to 26), and 2 (1 to 3) and 1 (0 to 2) points, respectively. Over a 1-week period in participants categorized as “stable” and “about the same” using the transition question, ICCs were 0.87 (95% CI 0.66 to 0.95) and 0.84 (95% CI 0.73 to 0.91) for the eRMDQ with MDC₉₅ of 4 and 5, 0.31 (95% CI –0.25 to 0.71) and 0.61 (95% CI 0.36 to 0.77) for the eVAS with MDC₉₅ of 39 and 34, and 0.52 (95% CI 0.14 to 0.77) to 0.67 (95% CI 0.51 to 0.78) with MDC₉₅ of 4 and 3 for the eNRS.

Conclusions

The eRMDQ was reliable with borderline adequate responsiveness. The eNRS was responsive with borderline reliability. While the eVAS had adequate responsiveness, it did not have an attractive reliability profile. Thus, the eNRS might be preferred over the eVAS for measuring pain intensity. The observed electronic outcome measures’ metric properties are within the ranges of values reported in the literature for their paper counterparts and are adequate for measuring changes in a low back pain population.

"Teaches People That I'm More Than a Disability": Using Nominal Group Technique in Patient-Oriented Research for People With Intellectual and Developmental Disabilities

Individuals with intellectual and developmental disabilities (IDD) have complex healthcare needs, which are often unmet. Nominal group technique (NGT) uses a mixed-methods approach, which may engage the IDD population in the research process in a person-centered manner and address the shortcomings of traditional research methods with this population. NGT was used with a group of 10 self-advocates to evaluate a series of healthcare tools created by and for individuals with IDD. Participants provided helpful input about the strengths of these tools and suggestions to improve them. NGT was found to be an effective way to engage all participants in the research process.

Primary reasons for osteopathic consultation: a prospective survey in Quebec

BACKGROUND

Osteopathy is an increasingly popular health care modality to address pain and function in the musculoskeletal system, organs and the head region, as well as functional somatic syndromes. Although osteopathy is recommended principally in guidelines for management of back pain, osteopaths' scope of practice is wide, albeit poorly defined. In order to understand better the practice of osteopathy, this study aimed to investigate the most common reasons for osteopathic consultations in clinical settings in Quebec.

METHODS

A prospective survey of members of the Registre des ostéopathes du Québec was conducted to examine demographics in osteopathic practices, as well as patients' primary reasons for consultations over a two-week period. The questionnaire was devised following a literature review and refined and verified with two stages of expert input.

RESULTS

277 osteopaths (60[corrected]% response rate) responded to the survey notice. 14,002 patients' primary reasons for consultations were reported in completed questionnaires and returned by practicing osteopaths. Musculoskeletal pain located in the spine, thorax, pelvis and limbs was the most common reason for consultations (61.9%), with females consulting most commonly for cervical pain and males for lumbar pain. Perinatal and paediatric (11.8%), head (9.1%), visceral (5.0%) and general concerns (4.8%) were the other most common reasons for consultations. Preventive care represented the remaining 0.3%.

INTERPRETATION

The nature of primary reasons for osteopathic consultations, coupled with documented satisfaction of patients with this approach, suggest a future for multidisciplinary collaborative health care including osteopathy. Results of this survey may contribute to informing physicians and others pending regulation of Quebec osteopaths, and also provide direction for future clinical research and guidelines development.

A profile of osteopathic care in private practices in the United Kingdom: a national pilot using standardised data collection

Increasing interest is being shown in osteopathy on a national and international basis. Since little prospective data had been available concerning the day-to-day practice of the profession, a standardised data collection tool was developed to try and address this issue. The tool development process has been described in an earlier paper. The standardised data collection (SDC) tool underwent national piloting between April and July 2009 in United Kingdom private practices. Osteopaths volunteered to participate and collected data on consecutive new patients or patients presenting with a new symptom episode for a period of one month; follow-up data were collected for a further two months. A total of 1630 completed datasets from the SDC pilot were analysed by the project team. Data generated from the national pilot showed that lumbar symptoms were the most commonly presented in patients (36%), followed by cervical spine (15%), sacroiliac/pelvic/groin (7.9%), head/facial area (7%), shoulder (6.8%), and thoracic spine (6%). A total of 48.8% of patients reported comorbidities, the most common being hypertension (11.7%), followed by asthma (6.6%), and arthritis (5.7%). Outcome data were collected looking at the patients' response to treatment, and any form of treatment reactions. The profiling information collected using the SDC tool provides a contemporary picture of osteopathic practice in the United Kingdom.