Pain Squad+ smartphone app to support real-time pain treatment for adolescents with cancer: protocol for a randomised controlled trial

Real-time analgesic efficacy and factors determining drug requirements of combined spinal-epidural analgesia for labor: a prospective cohort study

PURPOSE

Combined spinal-epidural analgesia (CSEA) is effective but not sufficient for labor pain. This study was conducted to assess the real-time analgesic efficacy, side effects of anesthetic drug dosage, and maternal satisfaction in labor to provide reference for the optimization of labor analgesia.

METHODS

This was a prospective, cohort, single-center study that included 3020 women who received CSEA for labor analgesia. The visual analogue scale (VAS) for labor pain, real-time anesthetic drug dosage, side effects, adverse labor outcomes, factors influencing average drug dosage, and maternal satisfaction with CSEA were assessed.

RESULTS

Overall, the VAS labor pain score was lowest at the first hour after the anesthesia was given. After 4 h for primiparas and 3 h for multiparas, the VAS score was greater than 3 but the anesthetic drug dosage did not reach the maximum allowed dosage at the same time. The average anesthetic drug dosage was positively correlated with fever, urinary retention, uterine atony, prolonged active phase, prolonged second stage, assisted vaginal delivery, and postpartum hemorrhage. The average anesthetic drug dosage was the highest in women ≤ 20 years old, those with a body mass index (BMI) ≥ 24.9 kg/m2, and those with a primary or secondary education level.

CONCLUSION

Appropriate age guidance and emphasis on education of labor analgesia, weight management during pregnancy, and real-time anesthetic dosage adjustment during labor based on VAS pain score may have positive effects on the satisfaction of labor analgesia.

CLINICAL TRIAL NUMBER AND REGISTRY

Clinicaltrials.gov (ChiCTR2100051809).

Assessing digital health knowledge, attitudes and practices among nurses in Naples: a survey study protocol

INTRODUCTION

Digital competencies are essential for nurses to actively participate in the digitisation of healthcare systems. Therefore, it is important to assess their skill levels to identify strengths and areas for improvement.

METHOD AND ANALYSIS

This study aims to investigate nurses' knowledge, attitudes, behaviours, subjective norms and behavioural control regarding digital health. A knowledge-attitude-practice model guided the development of a structured questionnaire divided into six sections. A sample of 480 registered nurses of Naples will be involved in the study. After conducting a pretest, an invitation will be publicised through the institutional communication channels of Nurses Provincial Order of Naples. Nurses will respond via a unique link or quick response code sent through a PEC email system (a legally valid email system, which guarantees delivery and receipt). They will have 30 days to complete the survey, scheduled between May and July 2024.

ETHICS AND DISSEMINATION

No ethics committee approval was required, as the study does not involve minors, direct or indirect physical or physiological harm to participants, or clinical trials. Anonymity will be guaranteed at all data collection and processing levels. The results will be broadly distributed through conference presentations and peer-reviewed publications. The effective use of digital technologies by healthcare professionals can bring significant improvements to healthcare services and help improve the health of individuals and community health. The study's findings will serve as a foundation for developing and implementing educational programmes related to eHealth and telemedicine, promoting the harmonisation of such programmes.

Psychometric evaluation of the electronic faces thermometer scale for pain assessment in children 8-17 years old: A study protocol

It is often a challenge for a child to communicate their pain, and their possibilities to do so should be strengthened in healthcare settings. Digital self-assessment provides a potential solution for person-centered care in pain management and promotes child participation when a child is ill. A child's perception of pain assessment differs when it is assessed using digital or analog formats. As we move into the digital era, there is an urgent need to validate digital pain assessment tools, including the newly developed electronic Faces Thermometer Scale (eFTS). This study protocol describes three studies with the overall aim to evaluate psychometric properties of the eFTS for assessing pain in children 8-17 years of age. A multi-site project design combining quantitative and qualitative methods will be used for three observational studies. Study 1: 100 Swedish-speaking children will report the level of anticipated pain from vignettes describing painful situations in four levels of pain and a think-aloud method will be used for data collection. Data will be analyzed with phenomenography as well as descriptive and comparative statistics. Study 2: 600 children aged 8-17 years at pediatric and dental settings in Sweden, Denmark, Iceland, and USA will be included. Children will assess their pain intensity due to medical or dental procedures, surgery, or acute pain using three different pain Scales for each time point; the eFTS, the Faces Pain Scale Revised, and the Coloured Analogue Scale. Descriptive and comparative statistics will be used, with subanalysis taking cultural context into consideration. Study 3: A subgroup of 20 children out of these 600 children will be purposely included in an interview to describe experiences of grading their own pain using the eFTS. Qualitative data will be analyzed with content analysis. Our pilot studies showed high level of adherence to the study procedure and rendered only a small revision of background questionnaires. Preliminary analysis indicated that the instruments are adequate to be used by children and that the analysis plan is feasible. A digital pain assessment tool contributes to an increase in pain assessment in pediatric care. The Medical Research Council framework for complex interventions in healthcare supports a thorough development of a new scale. By evaluating psychometric properties in several settings by both qualitative and quantitative methods, the eFTS will become a well-validated tool to strengthen the child's voice within healthcare.

Multi-level Pain Quantification using a Smartphone and Electrodermal Activity

Appropriate prescription of pain medication is challenging because pain is difficult to quantify due to the subjectiveness of pain assessment. Currently, clinicians must entirely rely on pain scales based on patients' assessments. This has been alleged to be one of the causes of drug overdose and addiction, and a contributor to the opioid crisis. Therefore, there is an urgent unmet need for objective pain assessment. Furthermore, as pain can occur anytime and anywhere, ambulatory pain monitoring would be welcomed in practice. In our previous study, we developed electrodermal activity (EDA)-derived indices and implemented them in a smartphone application that can communicate via Bluetooth to an EDA wearable device. While we previously showed high accuracy for high-level pain detection, multi-level pain detection has not been demonstrated. In this paper, we tested our smartphone application with a multi-level pain-induced dataset. The dataset was collected from fifteen subjects who underwent four levels of pain-inducing electrical pulse (EP) stimuli. We then performed statistical analyses and machine-learning techniques to classify multiple pain levels. Significant differences were observed in our EDA-derived indices among no-pain, low-pain, and high-pain segments. A random forest classifier showed 62.6% for the balanced accuracy, and a random forest regressor exhibited 0.441 for the coefficient of determination. Clinical Relevance - This is one of the first studies to present a smartphone application for detecting multiple levels of pain in real time using an EDA wearable device. This work shows the feasibility of ambulatory pain monitoring which can potentially be useful for chronic pain management.

Reducing pain in children with cancer at home: a feasibility study of the KLIK pain monitor app

PURPOSE

This study assessed adherence to, feasibility of, and barriers and facilitators of implementation of an app developed to monitor and follow-up with pain in children with cancer at home.

METHODS

Children (8-18 years) receiving cancer treatment (all diagnoses) or their parents (of children aged 0-7 years) used the KLIK Pain Monitor app for 3 weeks. Pain was assessed twice daily using an 11-point numeric rating scale (NRS-11) (ranging from 0 to 10). Healthcare professionals (HCP's) from the hospital's Pediatric Pain Service were instructed to follow-up with clinically significant pain scores (≥ 4) within 120 min (scores 4-6) or 30 min (scores 7-10). Adherence, feasibility, and implementation outcomes were assessed using questionnaires, app log data, and interviews.

RESULTS

Twenty-seven children (M age = 7.3 years, 51.8% male) and six HCP's participated. Sixty-three percent (N = 17) of families used the app on a daily basis during three weeks, and 18.5% (N = 5) reported pain scores twice daily during that time (family adherence). Twelve out of 27 children (44.4%) reported a clinically significant pain score at least once. In 70% (14/20) of clinically significant pain scores, HCP's followed-up with families within the set timeframe (HCP adherence). Outcomes reveal feasibility for the majority of app functions (i.e., positive evaluation by ≥ 70% families/HCP's), and non-feasible aspects could be resolved. Identified barriers and facilitators were used to improve future implementation efforts.

CONCLUSION

Use of the KLIK Pain Monitor app seems feasible. Future research will determine its effectiveness in reducing pain in children with cancer at home.

A Person-Centered Approach to Symptom Assessment and Management for Children and Adolescents Receiving Cancer Treatment

OBJECTIVES

Discuss the clinical assessment and management of symptoms for children and adolescents receiving treatment for cancer with attention to a person-centered approach to care.

DATA SOURCES

Review of currently published literature and guidelines pertaining to symptom assessment and management for children and adolescents receiving treatment for cancer.

CONCLUSION

Symptoms such as pain, nausea, and fatigue are commonly reported by children and adolescents receiving cancer treatment and are associated with greater symptom burden. Symptom assessment should be tailored to the child or adolescent and include the child's or adolescent's preference for reporting symptoms and attention to the symptoms that are of greatest priority. Evidence-based guidelines for the management of symptoms, including pain and nausea, are available to guide symptom management interventions and should be tailored to provide person-centered care.

IMPLICATIONS FOR NURSING PRACTICE

Nurses can lead efforts through clinical practice and research initiatives to advance person-centered symptom care for children and adolescents with cancer on a global level. Priorities for future work to advance person-centered symptom assessment and management include (1) identification of best practices for symptom assessment, (2) attention to social determinants of health and their subsequent influence on symptom outcomes, (3) compilation of evidence for management of less commonly reported symptoms, and (4) implementation of published clinical guidelines for symptom management in practice settings.

Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor

The subjectiveness of pain can lead to inaccurate prescribing of pain medication, which can exacerbate drug addiction and overdose. Given that pain is often experienced in patients' homes, there is an urgent need for ambulatory devices that can quantify pain in real-time. We implemented three time- and frequency-domain electrodermal activity (EDA) indices in our smartphone application that collects EDA signals using a wrist-worn device. We then evaluated our computational algorithms using thermal grill data from ten subjects. The thermal grill delivered a level of pain that was calibrated for each subject to be 8 out of 10 on a visual analog scale (VAS). Furthermore, we simulated the real-time processing of the smartphone application using a dataset pre-collected from another group of fifteen subjects who underwent pain stimulation using electrical pulses, which elicited a VAS pain score level 7 out of 10. All EDA features showed significant difference between painless and pain segments, termed for the 5-s segments before and after each pain stimulus. Random forest showed the highest accuracy in detecting pain, 81.5%, with 78.9% sensitivity and 84.2% specificity with leave-one-subject-out cross-validation approach. Our results show the potential of a smartphone application to provide near real-time objective pain detection.