Children's physical activity behavior following a supervised physical activity program in pediatric oncology

The effects of physical activity interventions on self-esteem during and after cancer treatment: a systematic review and meta-analysis

To investigate the effect of physical activity (PA) (both general and its type) on self-esteem during and after cancer treatment. A systematic search was conducted across PubMed, Web of Science, Scopus, SPORTDiscuss, and PsycINFO from their inception to February 2024. The systematic review included 32 studies, with 15 studies (13 RCT and 2 quasi-experimental) and 3604 participants (66.7% female) included in the meta-analysis involving controlled trials using a control group and at least one PA intervention group. The study was registered in PROSPERO (CRD42022309771). Risk of bias for RCTs was assessed using the Cochrane Collaboration's tool for assessing risk of bias (RoB2), and quasi-experimental studies with the Joanna Briggs Institute critical appraisal tool. PA significantly improved self-esteem during and after cancer treatment (pooled SMD = 0.32, p < 0.01). Specifically, aerobic PA (pooled SMD = 0.33, p = 0.04) and mind-body exercise (pooled SMD = 0.70, p = 0.03) had positive effects on self-esteem. Overall, PA interventions improved self-esteem during cancer treatment (pooled SMD = 0.50, p = 0.01) and in PA interventions lasting more than 12 weeks (pooled SMD = 0.44, p = 0.02). In conclusion, PA (specifically, aerobic and mind-body exercises) may have a positive effect on self-esteem during and after cancer treatment, with cancer status and the duration of the intervention being key factors.

Implementing a behavioral physical activity program in children and adolescent survivors of childhood cancer: a pilot randomized controlled trial

Purpose We aimed to document the acceptability (enrollment rate) and feasibility (phone call delivery rate) of implementing a behavioral PA intervention over 12 weeks, in addition to documenting its effects on patient-reported outcomes and physical functioning. This study also describes the costs of carrying out a behavioral PA intervention. A total of 40 participants were randomized in a 1:1 ratio. The tailored behavioral PA intervention was developed based on the most recent PA guidelines in pediatric oncology and on the COM-B framework to enact PA behavior changes. The prescription (frequency, intensity, time and type (FITT)) was adjusted each week during the weekly support calls. The control group did not receive the intervention. 26 males and 14 females (13.6 years old on average and 2.9 years post-cancer treatment on average) participated in our study. The acceptability rate was 90.9% and the feasibility rate was > 85%. We found that 85% improved PA frequency, 80% improved PA intensity, 100% improved PA time, and 50.0% achieved the recommended PA guidelines. No adverse events were reported over the duration of the intervention. Physical function improved with longer 6-minute walk distances in the intervention group (465.8 ± 74.5 m) than in the control group (398.7 ± 92.9 m) (p = 0.016). PROs scores for all participants were within the limits of the normal range. The estimated cost per participant of carrying out this intervention was USD $126.57. Our 12-week behavioral PA intervention, based on the COM-B framework, was found to be acceptable, feasible and safe in childhood cancer survivors. This study is an important step in the right direction to make exercise standard practice in pediatric oncology.

Chronic pain in children and adolescents diagnosed with cancer: the challenge of mitigating the pain and the potential of integrating exercise into pain management

BACKGROUND

Pain is one of the most common and distressing symptoms experienced by children and adolescents diagnosed with cancer. It is vital that children and adolescents receive adequate pain management early on in their cancer treatments to mitigate pain and cancer-related symptoms. Exercise training shows particular promise in the management of acute and chronic pain among children and adolescents diagnosed with cancer.

METHODS

This position paper comes to outline the challenge of mitigating pain in children and adolescents diagnosed with cancer, and the potential benefits of integrating exercise training to the management of chronic pain in this population in need.

RESULTS

Integrating exercise training into the care and pain management of children and adolescents diagnosed with cancer who have chronic pain would have the advantage of addressing several shortcomings of pain medication. Pain medication aims to temporarily manage or reduce pain; it does not have the potential to directly improve a patient's physical condition in the way that exercise training can. The current paucity of data available on the use of exercise training as a complementary treatment to pain medications to reduce chronic pain in children and adolescents diagnosed with cancer allows only for hypotheses on the effectiveness of this pain management modality.

CONCLUSION

More research on this important topic is necessary and mitigating pain effectively while also reducing the use of opioid pain medication is an important goal shared by patients, their families, clinicians, and researchers alike. Future research in this area has great potential to inform clinical care, clinical care guidelines, and policy-making decisions for pain management in children and adolescents diagnosed with cancer who experience chronic pain.

Prediction Model of Immunosuppressive Medication Non-adherence for Renal Transplant Patients Based on Machine Learning Technology

Objectives

Predicting adherence to immunosuppressive medication (IM) is important to improve and design future prospective, personalized interventions in Chinese renal transplant patients (RTPs).

Methods

A retrospective, multicenter, cross-sectional study was performed in 1,191 RTPs from October 2020 to February 2021 in China. The BAASIS was used as the standard to determine the adherence of the patients. Variables of the combined theory, including the general data, the HBM, the TPB, the BMQ, the PSSS and the GSES, were used to build the models. The machine learning (ML) models included LR, RF, MLP, SVM, and XG Boost. The SHAP method was used to evaluate the contribution of predictors to predicting the risk of IM non-adherence in RTPs.

Results

The IM non-adherence rate in the derivation cohort was 38.5%. Ten predictors were screened to build the model based on the database. The SVM model performed better among the five models, with sensitivity of 0.59, specificity of 0.73, and average AUC of 0.75. The SHAP analysis showed that age, marital status, HBM-perceived barriers, use pill box after transplantation, and PSSS-family support were the most important predictors in the prediction model. All of the models had good performance validated by external data.

Conclusions

The IM non-adherence rate of RTPs was high, and it is important to improve IM adherence. The model developed by ML technology could identify high-risk patients and provide a basis for the development of relevant improvement measures.

Identification of Immunosuppressive Medication Nonadherence Factors Through a Combined Theory Model in Renal Transplant Recipients: 6-12

Background: Immunosuppressive medication (IM) nonadherence is associated with poor transplant outcomes. Therefore, it is of great importance to identify predictive factors with IM nonadherence. We aimed to improve the predicted capacity of the theory of planned behavior (TPB) by adding health belief model's (HBM) variables in renal transplant patients (RTPs). Methods: This cross-sectional study distributed questionnaires to patients who had undergone renal transplant and follow-up regularly in the transplant center of Third Xiangya Hospital in China. The self-developed questionnaire collected data in three aspects: general data questionnaire, TPB, HBM-specific questionnaire, and Basel Assessment of Adherence to Immunosuppressive Medications scale. Results: A total of 1,357 of 1,480 patients completed the survey, with a participation rate of 91.69% and IM nonadherence rate of 33.53%. The marital status, household income, preoperative drinking history, the time after transplantation, and religion showed independent predictive factors with IM nonadherence (p < 0.05). Strikingly, adding HBM variables to the TPB theory model significantly increased its prediction ability to IM nonadherence (52%). Also, HBM manifested the highest coefficient of effect (-0.620). Particularly, perceived barriers and perceived seriousness, the variables of the HBM model, played a vital influence on medication nonadherence (-0.284 and 0.256). Conclusion: Our study here reveals the first investigation of the combined effects of the TPB and HBM model on IM nonadherence in Chinese RTPs, which could significantly improve the predictive ability of any single model. Meanwhile, future interventions should be conducted to both increase perceived seriousness and reduce perceived barriers for taking IM, which will effectively decrease IM nonadherence rates and improve transplant outcomes.