P < 0.05) were found between childhood eczema and the factors of using composite wood floors , living in a villa/townhouse , the presence of mold or damp stains in the child's room , and rarely cleaning the child's room . In addition, watching TV/playing computer games for more than one hour per day was significantly associated with eczema . Notably, we found that eating rice/pasta one to three times per week may elevate the risk of eczema-like symptoms (aOR = 1.343), which warrants further investigation. In addition, ambient air pollution, in the covariates, may also affect childhood eczema. Therefore, avoiding these adverse factors and creating a low-risk environment are crucial to prevent childhood eczema.Eczema, one of the most prevalent inflammatory skin diseases among children, is potentially influenced by genetic, environmental and social factors. However, few studies have investigated the effect of residential environment and lifestyle on childhood eczema. Therefore, this study conducted a cross-sectional study based on 2,781 preschool children in Shenzhen, China, during 2015–2016. Logistic regression models were employed to analyze the associations between residential/household environment, lifestyle, dietary habits and eczema in children. The prevalence of eczema among children in Shenzhen was 24.6%. Significant associations (increased odds >50%,  Eczema, also known as allergic dermatitis, is one of the most prevalent inflammatory skin diseases among children. It usually occurs as pruritus at the back of the knees and the front of the elbow. About 15–30% of children all over the world suffer from eczema . AlthougThe incidence of eczema may be associated with genetic factors, ambient air exposure, and social and economic status –8. HowevHence, this study systemically investigated the associations of dietary habits, residential/household environment, and lifestyle and childhood eczema in Shenzhen, China. To the best of our knowledge, we provided the first comprehensive data on these potential influencing factors of childhood eczema in a typically urbanizing and industrializing region.This study was based on a follow-up to the nationwide “China-Children-Homes-Health (CCHH)” study performed in 2010–2012 in multiple cities . A totalChildren in kindergartens were randomly sampled to represent the general population of preschool children in Shenzhen. Our questionnaire was based on the International Study of Asthma and Allergies in Childhood (ISAAC)  and a SwWe retrieved 4,614 filled questionnaires in total, with a very high response rate of 98.2%. First, 136 invalid samples with a large number of missing data were excluded. We then excluded 1,212 children aged younger than 3 years or older than 6 years. In addition, 485 questionnaires were invalid because of incomplete information about sex, age and eczema outcomes. Finally, a total of 2,781 samples with paired questionnaires were included in this study.The residential/household environment represented the outdoor and indoor living environment. The lifestyles included living and dietary habits in the last 12 months before the survey. Relatively long exposure period was set to reflect the actual scenario of sensitization, because , size, age, and the type of dwelling. The household environment, being the indoor environment formed by individual habits, encompassed mold, damp stains, water damage, window condensation, and house decoration status . Lifestyles were defined as the daily routine and living habits of children and their families, including the frequency of cleaning and ventilating and airing bedclothes, the time spent watching TV/playing with a computer, keeping pets at home, and smoking in the child's room. Children were defined as being “exposed” when their questionnaires answered “Yes” to the corresponding questions.“DDE” was defined by the following question: “Has your child ever been diagnosed with eczema by doctor(s)?”“ELS” was defined by reviewing the children's eczema-like symptoms in the past 12 months. The symptoms were based on the diagnostic criteria, including redness, itching, rash, dryness, desquamation or blisters, and seborrhea.Children were defined as having “DDE” or “ELS” when their questionnaires answered “Yes” to the corresponding questions.According to previous studies , 29–31, 10, SO2, and NO2) were selected to be adjusted for in Model 3. The daily mean concentrations of each air pollutant during 2008–2016 for each participant were obtained from 12 municipal monitoring stations for ambient air pollutants. Personal exposure to outdoor PM10, SO2, and NO2 was calculated by the inverse distance weighted (IDW) method (Ambient air pollution has been reported to be associated with increased odds of childhood eczema . Three m) method .P < 0.05 was considered statistically significant. First, a single-variable model was adopted to evaluate the crude ORs of residential/household environment and lifestyle for childhood eczema (Model 1). Second, parental atopy, breast feeding and the child's age, sex and birth season were adjusted in Model 2. Third, the effects of ambient air pollutants were further adjusted (Model 3). All statistical analyses were performed using SPSS software .We used binary logistic regression models to evaluate the associations of childhood eczema with dietary habits, residential/household environment, and lifestyle by adjusting for potential confounding covariates. Pearson's chi-square test was used to compare the differences in childhood eczema prevalence. Associations in the regression analysis were calculated as the odds ratio (OR) with a 95% confidence interval (95% CI). A P > 0.05), while fast food intake was found correlated with ELS (P < 0.05).This cross-sectional study is the first to systematically investigate the effects of living environment and lifestyle habits on childhood eczema in southern China. The effect of ambient air pollution was adjusted in the regression models. The results showed that diagnosed eczema among children was significantly associated with the residential/household environment, and lifestyles of their family members . HoweverP < 0.001) had the highest prevalence of childhood eczema . An age difference was observed in DDE prevalence among children, with the highest prevalence among children aged 3 years (29.0%). Notably, we did not find an association between childhood eczema and sex or breast feeding. In this study, the prevalence of eczema in children was comparable to those in other Chinese cities including Wuhan (23%), Shanghai (21.1%), Changsha (28.6%), and Beijing (29.7%)  , 19, and (29.7%) –35, suggP ≤ 0.001). Repainting the child's room, house size, building age, house type, airing bedclothes, time spent watching TV/playing with a computer, and keeping pets at home also had a significant impact on the prevalence of childhood eczema (P ≤ 0.01), especially living in a villa/townhouse (47.4%).The associations of eczema prevalence in children and residential/household environment and lifestyle habits obtained by the chi-square test are shown in P < 0.05). In addition, a relatively high prevalence of both DDE and ELS was found among children who never eat fruits or vegetables, have a moderate intake of rice/pasta, and have a high intake of fast food. The prevalence of DDE was lower among children with a moderate intake of fruits (23.1%) or vegetables (22.1%). In addition, a moderate intake of vegetables had a significantly protective effect on DDE, which is consistent with previous studies  had a significant positive association with increased odds of childhood eczema .10 and SO2 were added to the confounders, living near a highway was found to be a risk factor for childhood eczema, and the larger the house, the higher the risk of DDE in children. Living in a multistory building of more than seven floors or in a villa/townhouse was significantly associated with an increased risk of childhood eczema, which is consistent with previous studies  of a family indirectly and determine the type and degree of outdoor pollutants, which are closely related to childhood diseases , 37, 38. studies , 36, 39. reports , 39. How reports , 41. FurIn terms of household factors, compared with stone/tile, use of composite wood and cement as floor materials was significantly associated with increasing odds of childhood eczema , 3. RepaThe household environment can also produce indoor pollution, which can affect childhood diseases . Our repLifestyle factors were also found to associated with DDE and ELS , 3. RareWe found that childhood eczema has significant associations with lifestyle, including frequency of cleaning the child's room and airing bedclothes, keeping pets at home, and the child's time spent watching TV/playing with a computer. These results are consistent with those reported from Shanghai and Japan; not cleaning children's rooms or airing bedclothes frequently increased the risk of eczema in children , 48. HowThe environmental pathogenic mechanisms of eczema in children may be multifaceted and have not been fully understood, which may be related to the dysregulation of cytokines and inflammatory mediators directly or indirectly induced by chronic exposure to xenobiotics –52. BesiThe present study had some strengths. Above all, this study had a relatively large sample size, representing children in the general population. In addition, the response rate of the questionnaires was high (98%), which ensured the reliability and consistency of the results. Furthermore, the questions on atopic eczema in our study were taken from the ISAAC study , which w10/SO2/NO2 values. Floor materials, repainting, house size and type, living near a highway, the frequency of cleaning the child's room and airing bedclothes, mold or damp stains in the child's room, pet-keeping at home, time spent watching TV/playing with a computer, and a moderate intake of rice/pasta were found to be risk factors for childhood eczema. A moderate intake of vegetables and fruits could decrease the risk of childhood eczema. Parents and kindergarten staff should make an attempt to avoid giving their children too many electronics-based tasks and create a low risk living environment for children during their growth stage.Our study indicated significant associations between childhood eczema and both living environment and lifestyle habits after adjusting for covariates including the child's sex, age, and birth season, parental atopy, breast feeding, and ambient air pollution, with lifetime outdoor PMThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of Shenzhen Institute of Information Technology. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.YL: investigation, data analysis, and writing. SS: investigation and writing—reviewing and editing. DZ: writing—reviewing and editing. WL: data analysis. ZD and SL: supervision. All authors contributed to the article and approved the submitted version.This work was supported by the Shenzhen Science and Technology Project (JCYJ20180307160045548 and JSGG20180504165551779), Research platform and projects of the education department of Guangdong province (2018GKTSCX063), and with the subject of Shenzhen Institute of Information Technology (HX-227 and SZIIT2020KJ004).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Women in low to middle-income countries (LMICs), such as in Malaysia, face complex barriers to healthcare because of social, economic, geographic, and other interrelated factors, which can limit their access to timely, affordable, and effective breast cancer care. Patient Navigation has emerged as a cost-effective and impactful approach to enable women to access care.We have established a hospital-based partnership model between a non-profit organization and national healthcare service to address the barriers faced by low-income women to improve the timeliness of diagnosis and treatment and reduce poor adherence to treatment. The navigation team provides resources required to overcome financial and logistic barriers, counseling to address knowledge and emotional needs and to ensure treatment adherence.P < .05) and that for initiation of primary treatment increased from 36.5% to 49.5% (P < .05). The overall treatment default rates reduced from 8.6% to 2.6% (P < .05).To determine the effectiveness of the program, timeliness of diagnosis and treatment, and rates of treatment adherence were compared with a historical cohort from the same hospital. The proportion of patients who met the healthcare system's targets for timeliness to cancer diagnosis increased from 50.4% to 67.3% (In summary, Patient Navigation is feasible and potentially effective for addressing barriers to cancer care and could be a key element of cancer control in LMICs.


Schizophrenia research has significantly grown in the past years. However, there is no comprehensive evaluation of schizophrenia research publications from Southeast Asia (SEA). Thus, this study determined the characteristics and trends of published articles about schizophrenia in SEA through a bibliometric analysis.A database search on schizophrenia research in SEA countries was performed using the Scopus databases from 1973 to 2021. Bibliometric information was obtained from Scopus, and network visualization was conducted using VOSviewer software.There were 1068 articles on schizophrenia from SEA from 1973 until 2021. Schizophrenia research outputs from SEA started to increase from 2000 onwards. Singapore, Malaysia, and Thailand were the most productive countries in schizophrenia research and had the most collaborations. Most schizophrenia research in SEA was published in Asia- or SEA-based journals. The research hotspots for schizophrenia in SEA included treatment, pathophysiology, symptomatology, and psychological and social aspects of schizophrenia. Lastly, correlation analysis showed that gross domestic product per capita, research and development (R&D) expenditures, number of researchers in R&D, number of physicians, and international research collaborations were significantly correlated with higher research productivity and scientific impact in schizophrenia research.In conclusion, this study showed the trends and gaps for research in SEA and the socioeconomic factors correlated with research productivity for schizophrenia in SEA. This study emphasized increasing financial support and collaborations for schizophrenia research to improve research productivity in schizophrenia in the SEA region. •There were 1068 articles on schizophrenia from Southeast Asia from 1973 until 2021.•Southeast Asian countries only contributed 1.09% of the global research outputs on schizophrenia.•Singapore, Malaysia, and Thailand were the most productive countries in schizophrenia research.•Most schizophrenia research in Southeast Asia was published in regional or local journals.•Research funding, number of researchers and physicians, and collaboration increased research productivity in schizophrenia. One of these conditions is schizophrenia, a severe psychiatric disorder with the hallmark symptom of psychosis characterized by hallucinations and delusions . It is cThe prevalence of schizophrenia is estimated to be approximately 1 in 300 people globally . PatientSchizophrenia research has significantly grown in the past years. Previous bibliometric analysis showed an increasing trend in schizophrenia research publications worldwide . However22.1A database search was performed using the Scopus database. We used the search term “schizophreni*” and it was only searched for in the article title field. We limited the search to Southeast Asian countries, particularly Brunei, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam. All electronic searches were performed on December 12, 2021.2.2A total of 1068 articles were obtained from our search in the Scopus database. The following information was obtained for each article: authors, year of publication, title, journal, institution, country, title, keywords, and citation frequency. These were used to investigate the knowledge domain and development trends of schizophrenia research worldwide.2.3The correlation analysis was conducted in GraphPad Prism version 7 . The visualization of collaboration networks of countries and keywords related to schizophrenia was conducted using VOSviewer version 1.6.16  .33.1There were 1068 articles on schizophrenia from SEA from 1973 until 2021. Schizophrenia research outputs from SEA increased from 2000 onwards . Despite3.2The total publications, total citation (TC), citation per publication (CPP), and h-index of SEA countries for schizophrenia research outputs were presented in 3.3Regarding the number of schizophrenia total publications, the top institutions were from Singapore, Malaysia, and Thailand . The Sin3.4Interestingly, half of the top journals that published schizophrenia research from SEA were Asia- or SEA-based journals . The oth3.5Keyword co-occurrence was performed to determine general trends in schizophrenia research in SEA . The red3.6p = 0.004), researchers in R&D (p = 0.005), physicians per 1000 population (p = 0.013), and the number of international research collaborations (p = 0.0004) were significantly correlated with the total number of publications in schizophrenia in SEA countries. Moreover, GDP per capita , R&D expenditure , researchers in R&D , physicians per 1000 population , and the number of international research collaborations  were also correlated with the total citations and h-index of SEA countries for their schizophrenia research outputs.Correlation analysis was done to determine the country-specific characteristics  that wer4This bibliometric study of schizophrenia in Southeast Asia showed the following findings: 1) studies on schizophrenia in SEA were low and lagged behind the global research output; 2) Singapore, Malaysia, and Thailand were the most productive countries in schizophrenia research and had the most number of collaborations, and the institutions from these respective countries also contributed the most in terms of research outputs; 3) most of the papers were published within Asia or SEA-based journals; 4) prominent research keywords in schizophrenia included topics about treatment, pathophysiology, and symptomatology, and psychological and social aspects of schizophrenia; and 5) GDP per capita, R&D expenditures, number of researchers in R&D, number of physicians, and international research collaborations were significantly correlated with higher research productivity and scientific impact in schizophrenia research.To our knowledge, this was the first bibliometric analysis done on schizophrenia in SEA. Publication of studies about schizophrenia lagged globally as it only started during the 1970s, while other countries began publishing as early as 1911. This is not surprising since Asian psychiatry only came into focus during the 1950s , unlike The majority of the schizophrenia research in SEA was from Singapore, Malaysia, and Thailand. These countries have higher research funding and more physicians and researchers. The results of this study agree with previous bibliometric studies in SEA and showed that these socioeconomic indicators promote research productivity in a country .These countries also have the most significant number of collaborations in the field. This is expected as it has been previously established that countries that are more open to collaboration tend to produce more scientific articles than less open countries ,19. WithSchizophrenia Research published the most significant number of schizophrenia papers in SEA. This journal targets basic researchers and clinicians and is the most prominent specialist journal in the field. Although this is an international publishing journal, most schizophrenia research in SEA is still published in Asian-based journals such as the Journal of the Medical Association of Thailand, Asian Journal of Psychiatry, Singapore Medical Journal, and the Annals of the Academy of Medicine Singapore. Whether international or local, all the top journals that published schizophrenia research from SEA are written in English. This indicates a broader readership of the published papers, hence the higher h-index. This coincides with a previous finding that articles in English are more likely to be cited than those published in other languages [anguages .General trends in schizophrenia research can be gleaned through the common keyword co-occurrence associated with schizophrenia. Three clusters are dominant in the keyword visualization - those related to treatments, the disease pathophysiology and symptomatology, and those related to psychological and social aspects of schizophrenia. With this, we can surmise that the research landscape in schizophrenia encompasses a lot of bases - from the micro-level where molecular etiology of the disease is examined as in the keywords clustered under pathophysiology, to the macro level where its societal impact is reviewed as in the cluster related to the psychosocial aspects of schizophrenia. These can be the basis for setting the research agenda of the region for schizophrenia.There are some limitations to this bibliometric analysis. First, our study was limited to Scopus databases and may have missed other journals from other databases. Our study is also limited to articles published in English. This analysis may have missed research articles published in native languages in SEA countries. Despite these limitations, this study still provides a comprehensive picture of research productivity in Southeast Asia regarding schizophrenia. It has identified research trends and gaps in this field of research.5In summary, this study showed low schizophrenia research productivity in SEA, but its current trend was increasing. Researchers and institutions from Singapore, Thailand, and Malaysia contributed the most and had the most significant impact on schizophrenia research in SEA. Research productivity in schizophrenia research in SEA was correlated with GDP per capita, R&D expenditure, the number of researchers and physicians, and international research collaborations. The government in SEA countries should consider increasing the funding and support to schizophrenia researchers to improve productivity in this field. Researchers should also foster collaboration with other countries within and outside SEA. Lastly, research trends in schizophrenia are wide range, as shown by the keyword co-occurrence results from this study. This study emphasized increasing financial support and collaborations for schizophrenia research to improve research productivity in schizophrenia in the SEA region.The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.Not commissioned, externally peer reviewed.Not applicable.This study did not receive any funding.Not applicable.OAGT and MNARU conceived the review, contributed to analysis and interpretation of available literature, and prepared the manuscript. All authors contributed to the article and approved the submitted version.1.Name of the registry: N/A2.Unique Identifying number or registration ID: N/A3.Hyperlink to your specific registration (must be publicly accessible and will be checked): N/AOurlad Alzeus G. Tantengco.The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential competing interest.


Fall risk in the elderly is a major public health issue due to the injury-related consequences and the risk of associated long-term disability. However, delivering preventive interventions in usual clinical practice still represents a challenge.To evaluate the efficacy of a multiple-component combined with a multifactorial personalized intervention in reducing fall rates in a mixed population of community-dwelling elderly compared to usual care.clinicalTrials.gov).Randomized Controlled Trial . The control group (n = 200) received usual care and recommendations to minimize fall risk factors. In addition, each participant received a fall diary, followed by 12 monthly phone calls. The primary endpoint was the total number of falls in each group over 12 months, while the secondary endpoints were other fall-related indicators recorded at one year. In addition, participants' functioning was assessed at baseline (T1) and 3-month (T3).After the randomization, the described interventions were administered to the intervention group (p = 0.004) and the Fullerton Advanced Balance Scale (p = 0.006) for the intervention group, with a small effect size , at T1 and T3 evaluations.690 falls were reported at 12 months, 48.8% in the intervention and 51.2% in the control group, with 1.66 (± 3.5) and 1.77 (± 3.2) mean falls per subject, respectively. Subjects with ≥ 1 fall and ≥2 falls were, respectively, 236 (58.6%) and 148 (36.7%). No statistically significant differences were observed between groups regarding the number of falls, the falling probability, and the time to the first fall. According to the subgroup analysis, no significant differences were reported. However, a statistically significant difference was found for the Mini-BESTest (The intervention was ineffective in reducing the number of falls, the falling probability, and the time to the first fall at 12 months in a mixed population of community-dwelling elderly. A significant improvement for two balance indicators was recorded in the intervention group. Future studies are needed to explore different effects of the proposed interventions to reduce falls and consequences. Furthermore, we also hypothesized that the synergy between group exercise and personalized home exercise proposed in the trial would increase compliance and the routinary integration of home exercise in the older adults' long-term active and healthy lifestyle.Thus, the current study aimed to evaluate the efficacy of a multiple-component intervention associated with a personalized multifactorial intervention to reduce fall rates in community-dwelling older adults who can walk but are at risk of falling, including those with PD and stroke, compared to usual care.This study was a multicenter randomized controlled trial where individuals randomized to the intervention group (IG) received an 11-week multiple-component and personalized multifactorial intervention to reduce fall risk. In contrast, the control group (CG) participants received only usual care. Pre-test and post-test assessments were conducted, respectively, before randomization and 12 weeks after the commencement of the intervention. Primary and secondary endpoints were assessed at a twelve-month follow-up. The study design is presented in The study was conducted in two Italian Public Hospitals  between 2015 and 2016. It was registered on clinicaltrials.gov (unique identifier NCT03592420) and approved by the local Ethical Committee . Furthermore, all participants gave written informed consent to participate in the study, whose conduction adhered strictly to the Helsinki Declaration's ethical principles .Inclusion criteria were: age ≥65 years, moderate-to-high fall risk associated with age and/or neurological conditions , ability to walk for at least 10 meters without assistance , and the agreement to give written informed consent to the study. The inclusion criteria “moderate-to-high fall risk” and “ability to walk for at least 10 meters without assistance” were assessed during the Anamnestic and the Objective Assessments of Eligibility for the enrolment through the administration of validated tests as described below.Exclusion criteria were: general health conditions likely to interfere with or to pose a contraindication to physical exercise , cognitive impairment , severe deafness, severe vision impairment, severe aphasia or visual-spatial disorders, subjective and objective vertigo in the last 3 months, ongoing physiotherapy likely to influence the target variables (at the time of enrolment).ad hoc case report any subjects over 65 years old, with or without a diagnosis of PD or stroke, considered to be “at fall risk”. The subject's compliance with the inclusion and exclusion criteria was declared in this form. Also, subjects considering themselves at risk of falling could self-report themselves through a dedicated email address.Health professionals  could signal to an enrolment office shared between the two centers  through an After the initial report, potentially eligible participants were screened for inclusion and exclusion criteria in more detail. In particular, eligible subjects underwent further assessments by these subsequential steps:Anamnestic Assessment of Eligibility (AAE):This assessment was the PRE.C.I.S.A.'s first selection step. It was administered by a PUA's trained nurse, through a telephone call, to older adults who had been signaled as “at fall risk”;The aim was to confirm the inclusion/exclusion criteria for the study recruitment and evaluate the most influential fall risk factors. In particular, the PUA's nurse verified the subjects' adherence to inclusion and exclusion criteria. Furthermore, the subjects were submitted to the Fall Risk Assessment Tool  and werLater, each subject was classified as “not eligible and/or at low risk”, “moderate”, or “high” fall risk according to the defined algorithm indicated in post-hoc validation of the screening algorithm.Those who resulted at “low fall risk” or “not satisfying study criteria” were excluded. However, the study protocol allowed the PUA's nurse to contact these subjects after 1 year to record any eventual fall, thus providing helpful quantitative information for the After combining the assessment results, people classified as being at “moderate-to-high fall risk” accessed the successive selection step (Objective Assessment of Eligibility - OAE).The estimated time to perform this step was 5–10 min.Objective Assessment of Eligibility (OAE):This assessment constituted the PRE.C.I.S.A.'s. second selection step, and it was administered during an outpatient visit by a trained physiotherapist to individuals selected at “moderate-to-high fall risk” during the previous selection step (AAE);The aim was to evaluate in detail all fall risk factors described in the literature and, hence, to confirm the eligibility for the study . In particular, the prospective participant was submitted to the Falls Risk for Older People in the Community Screen (FROP-Com Screen) , to the Those who obtained an “eligible coefficient” ≥1, calculated from the FROP-Com Screen and the FRAT  total scAny individual re-classified at “low risk” following this second assessment step was excluded from the enrolment and contacted 1 year later by the PUA's trained nurse to collect the number of any eventual falls that occurred.The estimated time to perform this step was 20–30 min.After the enrolment, subjects judged as “eligible” participants underwent the pre-test assessments, which were conducted by a Physiatrist (P), a Physiotherapist (PT), a Geriatrician (G), and a Neurologist (N), as described in the following outcome measures section. These assessments helped determine in detail the individual fall risk profile.ad hoc for this study, and computer-based randomization was implemented to guarantee the allocation concealment. The randomization sequence was created using random block sizes of 4 and stratified according to risk classes, which distinguish subjects based on the different fall risks attributed in the literature depending on age and the presence of associated neurological diseases . ParticAfter the randomization, all enrolled subjects were informed about the allocation arm and received a ‘usual care' intervention  based ona report on their personalized risk factor profile;an illustrated brochure on fall prevention;personalized suggestions to minimize the fall risk addressed to their General Practitioner (GP).Furthermore, all participants were provided with a one-year fall report diary, integrated with a physical activity monitoring diary, and several copies of a “fall report” that had to be filled by the participant, in case of a fall, with more detailed information about the event.Participants in the IG were taken in charge by an interdisciplinary team, including the four professionals mentioned above, who administered synergically the following five interventions  for 60 min. Each session was composed of the three following parts:Warming-up (5 min): head, neck, trunk, and ankle movements, back and knee extensions, walking on the spot;Three-station circuit training (35 min): muscular strength exercises, balance exercises, and recovery techniques from falling ;Dynamic balance and walking exercises specific for the risk class (10 min).The remaining 10 min were used to check the physical activity report diary.In the first session, the PT delivered a weight vest to each IG participant and verified the initial level for each of the three circuit training stations cited above. The personalization of the exercise intervention regarded the three-station circuit training , which were adapted individually. On the other hand, activities within the last part  were not personalized but were adapted for the subject's risk class . Further details are available in At each group session, the participants needed to have their weight vest, their fall-physical activity report diary of the current month, and their manual for the home exercise program (see next point 4). During rest periods from exercises, the participants delivered their fall-physical activity report diary and the completed 'fall report' in case of at least one fall during the week. At the end of the session, the PT updated the manual of the home exercise program with the week-level progression of the exercises .The IG participants received a thirty-minute educational session after each weekly group exercise session, focusing on different modifiable fall risk factors and avoidable risky behavior. The sessions were provided using appropriate language for lay elderly people and audio-visual material. The rationale of this intervention was to allow participants and their caregivers to identify everyday experiences and attitudes about the specific topic and to plan strategies to implement suggested prevention strategies for fall risk factors. Similar educational sessions had already been proposed in the study protocol of a Brazilian RCT (Prevquedas Brazil) on the effectiveness of a multifactorial fall prevention program in community-dwelling older people .Each educational session was divided into two parts:A 10 min frontal lecture on a specific theme held by a component of the interdisciplinary team;A 20 min group discussion on the lecture content . A handbook summarizing these topics was provided to each participant at the beginning of the first education session.ad hoc questionnaire and the subsequent suggestions for their reduction given by a physiotherapist within four home visits. The rationale for a personalized plan for reducing domestic fall risk factors is that this intervention proved effective in reducing the rate of falls and the risk of falling in community-dwelling older adults, especially those at higher risk of falling, e.g., elderly with severe visual impairment ;During the subsequent three home visits related to the personalized home exercise program, the PT checked the implementation of the recommended interventions proposed during the first home access and filled the “Check-list of correction of environmental risk factors at home”.This intervention was coordinated with the group exercise program aimed at improving strength, and static and dynamic balance, with the specific aim of enabling the participants to develop a long-term daily habit of exercising and performing physical activity in the context of a progressive and permanent adoption of a healthy and active lifestyle. The rationale for a home-based personalized exercise program is that the latter is known to be effective at reducing the rate of falls and the risk of falling in this population . FurtherThe personalized home exercise program was realized according to the following steps:The PT devised this program in the context of an initial home visit (on the second week) and subsequently monitored within two further home visits (on the fourth and sixth weeks).During the initial home visit, an illustrated manual containing strength and balance exercises was provided and explained to each participant based on the first group exercise session. These exercises were chosen between those the subject performed with greater safety in the group session.Besides, the PT gave indications about recommended training frequency, as well as regarding time and registration of the performed physical activity in the fall-physical activity report diary of the current month.During the subsequent two visits, the PT verified: a) the setting adequacy, b) the modality in which the participant performed the suggested exercises, and c) the update of the fall-physical activity report diary.Finally, in all three home accesses linked to the home exercise program, the PT checked the implementation/maintenance of the recommendations on risk factors correction given in the first-week home visit.The rationale for this intervention is that a personalized multifactorial intervention is a well-known effective strategy to reduce both the fall rates and the risk of falling in elderly persons, as suggested by the already mentioned 2012 Cochrane systematic review . This inReview of medications, including psychotropic medications (N and G), antiparkinsonian drugs (N), and cardiovascular medications (G);Management of unaddressed visual impairments (G): ophthalmologist referral, lens prescription, suggestions regarding the limitation of bifocal lenses;Management of unaddressed cardiovascular issues (G), such as postural hypotension, covert cardiac failure, and abnormalities of cardiac rhythm; eventual cardiology referral;Vitamin D prescription (G);Improvement of nutritional state (G), with prescription of caloric-proteic integration and/or nutritional referral;Management of muscle-skeletal issues, including spasticity (P and PT);Education about foot self-care, including podologist referral if appropriate (P);Assessment, prescription, and final testing of orthosis and mobility aids, including proper shoes (P and PT).Interventions one to four were administered to all IG participants (multiple-component intervention). In contrast, the multifactorial intervention (intervention number five) was personalized based on the individual fall risk profile devised on the pre-test assessment. Furthermore, interventions one, two, and five were conducted within an outpatient setting, while interventions three and four were home-based.Participants allocated to the CG received only the usual care, as described in the randomization section. The fall risk management of each individual enrolled in the CG was delegated to the participant's GP.Participants' demographic and clinical characteristics were collected during the baseline pre-test visit, including age, sex, fall risk according to epidemiological criteria, and Falls Risk for Older People in the Community (FROP-Com) criteria.Furthermore, several indicators were used by the interdisciplinary team to assess functioning at pre-test (T1) and three-month follow-up (T3). In addition, even instruments administered at the OAE assessment were recollected at the three-month follow-up (T3). We have reported all the scales and questionnaires administered at the various assessment steps  in The primary endpoint was the total number of falls in each group over 12 months. A fall was defined as an “unexpected event where a person inadvertently comes to rest on the ground, floor, or lower level” , 36. TheAll participants were provided with their fall diary and were followed up for 12 months with monthly telephone contacts to record the primary and secondary endpoints. During these monthly calls, each participant was inquired about any incurred falls at each contact, with date, circumstances, underlying cause, and related injuries. The primary endpoint was further verified at the end of the study by returning the fall diary.The blindness of the assessments was guaranteed with various strategies:For both pre-test and post-test evaluations, as the former was performed before randomization, whereas the latter was undertaken by the other center's assessors, unaware of the allocation arms of the participants' within the enrolling center;Furthermore, subjects in both groups were instructed not to discuss their allocation with other participants and assessors during the post-test assessments;Finally, the assessor was unaware of the allocation arms at the monthly follow-up calls.The sample size was determined based on the assumptions that the fall risk in the control group was equal to 50% and that the experimental intervention was able to reduce this risk by 30% , 37, thaFinally, it should be noted that the sample size calculation was made by considering the expected risk of falling in the enrolled population. However, the primary endpoint was represented by the rate of falls. Considering that the rate of falls is usually 15–20% higher than the risk of falling due to multiple fallers . Therefore, the date of randomization for each subject was considered the start date for the follow-up. The follow-up end date was calculated differently for participants with at least one fall and those without falls. For the former, we considered the least recent date among the dates of telephone interviews in which at least one fall was reported. For the latter, the most recent date among telephone interviews was considered. Thus, the follow-up time in months was equal to the difference in days between the start and end follow-up dates, divided by 30.4 (mean duration of a month).We performed multivariate analyses on the whole sample to statistically control for additional variables , which could have influenced the predictive ability of the models for the primary and secondary endpoints for the whole sample. We used the following models and statistics:‘Number of falls' (primary endpoint): negative binomial regression model, Incidence Rate Ratio (IRR) with a 95% confidence interval (95CI%) and a p-value;‘Fall probability for one fall, two or more falls, and three or more falls  within 12 months' (secondary endpoints): logistic regression model, Odds Ratio (OR) with a 95%CI and a p-value;p-value.‘Time to the first fall' (secondary endpoint): Cox regression model, Hazard Ratio (HR) with a 95%CI and a p-value, comparing the experimental and control groups.Concerning the study's primary endpoint, the comparison of observed fall incidences in the two groups was performed using statistical regression methodologies for counting data. A model assumes a negative binomial distribution for the response variable . The results were expressed as the Incidence Rate Ratio (IRR) with a 95% confidence interval (95 CI%) and a p-value, referring to the comparison between IG and CG. This fall probability was calculated for one fall, two or more falls, and three or more falls  within 12 months.Concerning the secondary endpoint “fall probability”, the results were expressed as Relative Risk (RR) with a 95%CI and a p-value, comparing the two groups. In addition, the cumulative probabilities of occurrence of at least one fall were graphically represented as Kaplan-Meier survival curves, reporting the survival point estimate from falls at three, six, and 12 months, with 95%CI.A Cox regression model was employed to perform the analyses of the secondary endpoint “time to the first fall”. The results were expressed as Hazard Ratio (HR) with a 95%CI and a We also explored the impact of risk classes and gender  on comparing primary and secondary endpoints between the two groups. For doing so, we performed a multivariate analysis where we statistically controlled for the additional variables employing the same models and statistics indicated in the previous section on the multivariate analysis to predict the final endpoint on the whole sample.The analysis of the differences between randomization arms (IG and CG) were also performed for each of the subgroups identified by the four etiological risk class categories considered in the study , and by gender.Preliminary to comparing the two groups on post-test with ANCOVA, we performed a Rasch analysis of the scales and questionnaires involved in the comparison. Rasch analysis was conducted because ANCOVA is a parametric statistical analysis requiring continuous variables, whereas the total scores of scales and questionnaires deliver ordinal data. Indeed, within Rasch analysis, it may be possible to transform the ordinal total score of a scale or a questionnaire into interval-level person estimates of ability, should the data fit the fundamental measurement requirements of the Rasch model  . In partFROP-Com ;Berg Balance Scale BBS , 41];;41)];Performance-Oriented Mobility Assessment POMA , 42];;42)];Fullerton Advanced Balance Scale FABS , 43];;43)];Mini-BESTest .The FROP-Com is a global fall risk indicator, while the other four indicators all quantify balance, although with differences related to the measurement range. Therefore, two Rasch analyses were carried out separately: the first for the FROP-Com and the second for the four balance indicators. Given their conceptual equivalence , the latp-value confidence interval. The effect size was calculated as Cohen's d by comparing pre-post differences between groups.The values of the above five indicators, calculated before and after the intervention, were compared between the two groups using parametric statistical techniques. In particular, we reported the mean values of these parameters at the pre-test and post-test levels. The post-intervention values were compared between the groups through a linear regression model that uses the treatment and the pre-intervention value as independent variables (ANCOVA model). This analysis was reported as mean differences (MD) with 95% and Whenever possible, the reasons for any cases lost to follow-up were recorded. Concerning logistic regression, we initially conducted an analysis that considered all randomized subjects without considering any follow-up loss according to the principle of the intention to treat. In case of loss to follow-up due to death or other causes, we considered the information collected up to that time. Whether a subject was lost to follow-up, independent from experiencing a fall or not (primary outcome), their data were considered for the analysis. Thus, it was possible to conduct sensitivity analyses that hypothesized various scenarios of the outcomes considered for loss to follow-up.Regarding the analysis of survival curves, any loss to follow-up data was treated as censored since the last available information for these subjects. However, it was possible to conduct further sensitivity analyses even in this context.www.rummlab.com).Statistical analyses were performed using the Stata 14 software  and R 3.4.3  by the Medical Statistics Unit of the University of Modena e Reggio Emilia, using a 95% confidence level (p 0.05). In addition, Rasch analyses were carried out using the software RUMM 2030  or the IG (n = 203)  . Seventyn = 203) ; among tn = 203) . The twoThe mean age of enrolled participants was 76.2 years (SD: 6.3), and about two-thirds (65.5%) were females. The mean level of education was 9.0 years of schooling (SD: 4.6), corresponding approximately to the completion of lower secondary school. About two-thirds of the enrolled patients (65.2%) were elderly with an estimated fall risk at 1 year comprised between 33 and 50%, as 43.7 and 21.6% were classified within the 65 to 80 and >80 risk classes, respectively. The remaining 34.7% were elderly patients with an associated neurological condition. Their estimated fall risk at 1 year was between 60 and 70%, as 19.4 and 15.4% had a diagnosis of Parkinson's Disease or stroke, respectively.Regarding the level of impairment of older adults with an associated neurological disease, those with PD showed a median value of the modified Hoehn and Yahr scale (H&Y) of 3 (Interquartile range IQR: 1), thus suggesting that almost 50% of them were physically independent. Subjects with stroke had a median value of the National Institutes of Health Stroke Scale (NIHSS) of 2 (IQR: 4), highlighting that almost 50% of these elderly suffered from a minor stroke's sequelae . In partConsidering the estimated fall risk of the enrollment patients, only 7.9% could be considered at ‘low risk' according to the FROP-Com. In contrast, the enrollment algorithm classified the remaining 92.1% of patients correctly as being at moderate (36.2%) or high fall risk (55.8%) according to the FROP-Com. All subjects' characteristics at baseline for each group (IG and CG) were reported in Amongst the participants, the majority (58.6%) experienced at least one or more falls. In particular, 21.8% and 14.6% experienced one or two falls, respectively, whereas the percentage of multiple fallers  was 22.1% . The ratMost falls (67.4%) led to no injury, whereas 32.6% were associated with various injuries. In particular, 6.4% of them led to serious injury requiring hospitalization, whereas 10.9 and 15.4% of falls were associated with minor injury either requiring or not a medical consultation, respectively.The median time of occurrence of the first fall was 11.1 months. A probability of absence of falls of 77.6% , 65.0%  and 47.3%  were recorded, respectively, at three, six, and twelve months. All these endpoints . On the other hand, people with stroke seemed to have a lower risk of falling one or more times (borderline significance) in comparison to those aged 65–80   in comparison to younger subjects aged 65-80  .Concerning the “gender” effect on the whole sample, after statistically controlling for the additional variables “experimental groups” and “risk classes”, males reported a significantly higher risk for “the number of falls” and the “fall probability” for three or more falls than females. They had a “number of falls” 1.74 higher, and they were 1.73 times more likely (borderline significance) to have three or more falls than females .In the CG and the IG, most participants  fell at least once or more. In particular, 20.0% and 23.6% experienced one fall, 13.0 and 16.3% two falls, whereas the percentage of multiple fallers  was 25.5 and 18.7%, respectively . The perMost falls (67.4%) led to no injury for both groups, whereas the remaining one-third was associated with various degrees of injury. In particular, 16.2% in the CG and 14.5% in the IG of falls led to minor injuries not requiring medical consultation, whereas 9.6% and 12.2% of falls were associated with minor injuries requiring medical consultation. Finally, 6.8% of falls in the CG and 5.9% in the IG led to serious injury requiring hospitalization .p = 0.693), and the fall probability for one fall, and two or more falls . Regarding the falling probability for three or more falls , this was in favor of the IG, although slightly above the chosen level of statistical significance   and 78.8%  in the first 3 months were recorded, respectively, for CG and IG. No statistically significant differences were observed between groups regarding the number of falls  .p = 0.398)  in the CG and 11.2 months (95%CI 9.7–NA) in the CG. No statistically significant differences were observed between groups regarding the time to the first fall  .p = 0.676), and the “fall probability” for one fall, and two or more falls . However, regarding the falling probability for three or more falls , the probability was in favor of the IG even in this analysis, although slightly above the chosen level of statistical significance  (p = 0.370)  . Besides= 0.370) .Regarding the number of falls , the comConcerning the falling probability for one fall, elderly aged 65–80 and with PD in the IG had a lower  probability of falling than those randomized in the CG . On the other hand, elderly aged >80 and elderly with stroke had a higher  probability of falling if randomized in the IG . Furthermore, the falling probability appeared lower  for the ‘female' gender subgroup within the IG , as shown in Concerning the falling probability for two or more falls, elderly aged 65–80 and aged >80 in the IG had a lower  probability of falling than those randomized in the CG . Even elderly with PD in the IG had a lower  probability of falling than those randomized in the CG, with a RR closer to the chosen level of statistical significance . Differently, the elderly with stroke had a higher  probability of falling if randomized in the IG . The multi-falling probability for two or more falls appeared lower  again for the ‘female' gender subgroup within the IG  .Regarding the falling probability for three or more falls  , similarConsidering the endpoint ‘time to the first fall' , elderlyThe final solutions for the FROP-Com and the balance scales showed adequate fitness to the Rasch Model . Hence, The ANCOVA analysis  showed np = 0.035; effect size 0.26, 95%CI ) and FABS  between the two groups after controlling for the pre-test measures.However, there were statistically significant differences for the post-test MBT measures , with a fall incidence of 58.6% and a mean of 1.7 (SD: 3.4) falls accounted for each included subject. These data are in contrast with those reported in the literature, where the overall fall incidence in older adults over 65 years is around 28 to 35% and about 32 to 42% in those over 75 years , with 0.The statistical analyses revealed no significant differences in fall rates and related parameters between IG and CG, i.e., fall severity, fall probability for one, two or more, and three or more falls within 12 months, and time to the first fall. These results align with Lamb's and Cattaneo's works , 48. HowThe subgroup analyses yielded similar results, with the absence of significant differences between the CG and IG regarding the number of falls, the falling probability, or the time to the first fall  across all the considered subgroups . As per the general group, there was a general trend of better outcomes for the IG group, although not significant. In particular, it is interesting that the falling probability for two or more falls in the elderly with PD was very close to the level of statistical significance, considering that this was the subgroup showing a significantly higher risk for all the considered endpoints in the multivariate analysis. The stroke subgroup made an exception, as the risk of falling was apparently higher  for patients enrolled in the IG. The fall risk for persons with stroke is notoriously high, being reported to be around 43 to 70% in the previous trials . UndoubtLiterature data about gender influence on the risk of falling suggests that females may be at a higher risk of falling than men. In particular, Stevens and Sogolow  showed tRegarding gender influence, our data showed a general trend for better outcomes within the IG group for females, although non-statistically significant. In particular, the falling probability for three or more falls in females was slightly below the statistical significance. Furthermore, the possible protective effect of the female gender emerged from the multivariate analysis performed on the whole sample for three of the considered endpoints  after controlling for experimental groups and risk class. Thus, the intervention may have further reduced female subjects' risk-taking behaviors and occupational hazards, which are known to be less prevalent in women than men . HoweverThe analysis of the differences between baseline (T1) and 3-month follow-up (T3) across CG and IG was preceded by a Rasch Analysis. The latter was performed because scales' total scores are ordinal and, as such, should not be used with parametric statistical techniques such as ANCOVA , 69, as In a previous study evaluating the effects of a home-based exercise program in reducing falls in the elderly population, Vogler et al. observed an improvement in reducing fall risk and balance indicators at the end of the 12-week treatment and a subsequent return to baseline values after 24 weeks . Indeed,per se, might be a fall risk factor  at moderate-to-high fall risk.Unfortunately, other recent RCTs have reached similar conclusions for other interventions , 48, 85.We believe that future studies exploring different effects of combined multiple-component and personalized multifactorial interventions to reduce falls and subsequent consequences should be undertaken with a clear plan for overcoming the limitations highlighted in the PRE.C.I.S.A. study.Ospedale Civile di Baggiovara ;Rehabilitation Medicine: Fabio La Porta, Serena Caselli, Pierina Viviana Clerici, Stefano Cavazza, Valeria Serraglio, Maria Cristina Vannini, Federica Bovolenta, Giada Lullini, Silvia Puglisi, Angela Gallo;Elderly Medicine: Chiara Mussi, Marco Bertolotti, Roberto Scotto, Giulia Lancellotti;Neurology: Franco Valzania, Francesca Falzone;Primary Care Department: Monica Montanari, Maria Luisa De Luca, Emanuela Malagoli, Elisa Franchini;Research and Innovation Unit: Luisa Palmisano, Franca Serafini.Arcispedale Santa Maria Nuova ;Rehabilitation Medicine: Claudio Tedeschi, Gioacchino Anselmi, Valentina D'Alleva, Mariangela Di Matteo, Rosalinda Ferrari, Stefania Costi, Filomena Simeone, Giulia D'Apote, Alessandra Rizzica, Maria Beatrice Galavotti, Marta Ghirelli;Elderly Medicine: Giulio Pioli, Chiara Bendini, Giulia Lancellotti;Neurology: Massimo Bondavalli, Eleni GeorgopoulosUniversity of Modena and Reggio Emilia, Unit of statistical and methodological support for clinical research;Roberto D'Amico, Sara Balduzzi, Roberto Vicini, Federico BanchelliUniversity of Bologna, Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” (DEI);Lorenzo Chiari, Sabato Mellone, Alice Coni.Zenodo.org  from the following link: https://doi.org/10.5281/zenodo.6954088.The raw data supporting the conclusions of this article are available for download at The studies involving human participants were reviewed and approved by Provincial Ethics Committees of Modena and Reggio Emilia, Italy. The patients/participants provided their written informed consent to participate in this study.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This study was financed by the Agenzia Socio-Sanitaria Regionale della Regione Emilia-Romagna  in the context of the Programma di Ricerca Regione-Università 2013 (PRUA2-2013-00002056).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the Publisher.


PSA is currently the most commonly used screening indicator for prostate cancer. However, it has limited specificity for the diagnosis of prostate cancer. We aim to construct machine learning-based models and enhance the prediction of prostate cancer.The data of 551 patients who underwent prostate biopsy were retrospectively retrieved and divided into training and test datasets in a 3:1 ratio. We constructed five PCa prediction models with four supervised machine learning algorithms, including tPSA univariate logistic regression (LR), multivariate LR, decision tree (DT), random forest (RF), and support vector machine (SVM). The five prediction models were compared based on model performance metrics, such as the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, calibration curve, and clinical decision curve analysis (DCA).All five models had good calibration in the training dataset. In the training dataset, the RF, DT, and multivariate LR models showed better discrimination, with AUCs of 1.0, 0.922 and 0.91, respectively, than the tPSA univariate LR and SVM models. In the test dataset, the multivariate LR model exhibited the best discrimination (AUC=0.918). The multivariate LR model and SVM model had better extrapolation and generalizability, with little change in performance between the training and test datasets. Compared with the DCA curves of the tPSA LR model, the other four models exhibited better net clinical benefits.The results of the current retrospective study suggest that machine learning techniques can predict prostate cancer with significantly better AUC, accuracy, and net clinical benefits. Prostate cancer (PCa) is the second leading malignancy in men and the fifth leading cause of cancer mortality in men worldwide . AlthougMachine learning is a branch of artificial intelligence (AI) in which machines are programmed to learn patterns from data, and the learning itself is based on a set of mathematical rules and statistical assumptions. It is widely used in biology because of its enormous advantages in dealing with large datasets , 8. It hIn this study, we constructed generalizable machine learning predictive models to improve the accuracy of PCa risk assessment by using objective parameters present in electronic medical records and then evaluated their performance.A total of 789 male patients in the First Hospital of Jilin University who underwent transrectal ultrasound-guided prostate biopsy from January 2013 to January 2021 were included. Indications for prostate biopsy included serum tPSA >4 ng/ml, abnormal digital rectal exam (DRE), or imaging findings suggestive of suspected prostate cancer. All patients underwent systematic biopsy with 10-12 cores. Patients with one of the following criteria were excluded from the study: taking medications that could affect serum PSA levels, unclear results of the prostate biopsy, and significant abnormal values or missing data. A final total of 551 patients were included in the study. All patient data were collected through electronic medical records, including age, BMI, hypertension, diabetes, total PSA (tPSA), free PSA (fPSA), the ratio of serum fPSA to tPSA (f/tPSA), prostate volume (PV), PSA density (PSAD), neutrophil-to-lymphocyte ratio (NLR), and pathology reports of prostate biopsy. All examinations were completed within one week before prostate biopsy. PSAD is the ratio of tPSA to PV. The calculation of PV was calculated by the following formula: maximal transverse diameter × maximal anterior-posterior diameter × maximal superior-inferior diameter × 0.52.https://www.rproject.org/) was used to develop machine learning models. A total of five prediction models were constructed by dividing the data into a training dataset and a test dataset at a ratio of 3:1. The pathologic type of PCa or other benign disease was used as the dichotomous variable, and other variables were all used as continuous variables. For logistic regression (LR) model construction, the best predictive variables were first screened in the training dataset using stepwise regression, association plots between the variables were made to understand the magnitude of the association between the variables, and the presence or absence of collinearity between variables was judged according to the variance inflation factor (VIF). Then, LR models were constructed using the “lrm” function in the “rms” package. For the decision tree (DT) model, we used the “rpart” package for training, using two hyperparameters, the complexity parameters cp and spilt. The initial cp value was set to 0.001, and then the best cp value was found and pruned based on the best cp value. The input variables were obtained through the selection of important features, and the best DT model was then output. The random forest (RF) model screened the optimal input variables by significant feature selection. The RF model was trained using the “randomForest” package in R software, using two hyperparameters, ntree and mtry, which were set at 500 and 6, respectively. The support vector machine (SVM) model was filtered by the “caret” package for important features. Training was performed using the “e1071” package, using a Gaussian kernel function and setting the two hyperparameters, cost and gamma, to 1 and 0.1, respectively.R software  curve and its corresponding area under the curve (AUC) and the accuracy, sensitivity, and specificity. The calibration curve was used to evaluate the calibration of the model, the Brier score was used to assess the calibration, the Hosmer–Lemeshow goodness-of-fit test was used to judge whether there was a significant difference between the observed and predicted values, and clinical decision curve analysis (DCA) was used to assess the net benefit of the model.For comparative analysis between two samples, Student’s t test was used for normally distributed continuous variables, and the Mann–Whitney U test was used for categorical variables with nonnormal continuous variables. Continuous variables in the data were expressed as medians and IQRs or means and SDs, categorical variables were expressed as frequencies and percentages, and the bilateral significance level for the left-right test was set at 5% (p<0.05).First, the tPSA univariate LR model was constructed in the training dataset by including only one single factor, tPSA. This model showed that tPSA was positively correlated with the diagnosis of PCa (coefficient=0.034). Then, a multivariate LR model was constructed by including all variables through a stepwise regression method. When the VIC value reached the minimum value, a total of seven best predictive variables were selected, including age, tPSA, fPSA, PV, NLR, peripheral blood neutrophil count and lymphocyte count. The two LR models are shown in The optimal cp value for the DT model was 0.008. Based on the corresponding ranking of important features, the final input variables for the DT model were age, tPSA, fPSA, PV, PSAD, NLR, f/tPSA, and biopsy results .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To examine the changes in body composition, water compartment, and bioimpedance in mild cognitive impairment (MCI) individuals.We obtained seven whole-body composition variables and seven pairs of segmental body composition, water compartment, and impedance variables for the upper and lower extremities from the segmental multi-frequency bioelectrical impedance analysis (BIA) of 939 elderly participants, including 673 cognitively normal (CN) people and 266 individuals with MCI. Participants’ characteristics, anthropometric information, and the selected BIA variables were described and statistically compared between the CN participants and those with MCI. The correlations between the selected BIA variables and neuropsychological tests such as the Korean version of the Mini-Mental State Examination and Seoul Neuropsychological Screening Battery – Second Edition were also examined before and after controlling for age and sex. Univariate and multivariate logistic regression analyses with estimated odds ratios (ORs) were conducted to investigate the associations between these BIA variables and MCI prevalence for different sexes.Participants with MCI were slightly older, more depressive, and had significantly poorer cognitive abilities when compared with the CN individuals. The partial correlations between the selected BIA variables and neuropsychological tests upon controlling for age and sex were not greatly significant. However, after accounting for age, sex, and the significant comorbidities, segmental lean mass, water volume, resistance, and reactance in the lower extremities were positively associated with MCI, with ORs [95% confidence interval (CI)] of 1.33 (1.02–1.71), 1.33 (1.03–1.72), 0.76 (0.62–0.92), and 0.79 (0.67–0.93), respectively; with presumably a shift of water from the intracellular area to extracellular space. After stratifying by sex, resistance and reactance in lower extremities remained significant only in the women group.An increase in segmental water along with segmental lean mass and a decrease in body cell strength due to an abnormal cellular water distribution demonstrated by reductions in resistance and reactance are associated with MCI prevalence, which are more pronounced in the lower extremities and in women. These characteristic changes in BIA variables may be considered as an early sign of cognitive impairment in the elderly population. Changes in body composition commonly occur with aging in healthy individuals and in those with protein–energy malnutrition, poor physical conditions, or cognitive impairments such as Alzheimer’s disease (AD). Body composition changes over the aging process are characterized by increasing body fat mass, particularly by the reformation of the body’s fat distribution from appendicular fat to trunk fat, with decreasing lean mass and bone mineral density, especially in older adults –3. In miMild cognitive impairment (MCI) is an age-related disorder which describes the symptomatic transitional phase between normal cognition and dementia. Clinically, MCI is defined as a set of criteria, including evidence of a change in cognition and lower performance in one or more cognitive domains despite the preservation of independent daily functioning [diagnostic guidelines from National Institute on Aging and the Alzheimer’s Association ]. Aside Recognizing and monitoring changes in body composition can reveal early signs of the body’s vital status, thereby allowing the application of appropriate therapies or lifestyle changes to help reverse the risk of MCI and progression to dementia. Anthropometrical measurements such as weight, height, body mass index (BMI), body circumference, and waist to hip ratio (WHR) have been commonly used in clinical practice to indirectly estimate fat or muscle mass –19. HoweMost previous studies employed specific bioelectrical impedance vector analysis in the later stage of AD rather than during early cognitive impairment. They reported a lower body cell mass, indicated by a lower reactance and phase angle or a shifting to the lower right half of the ellipse, in the AD or dementia group than in individuals with normal cognition , 23. TheSex is another aspect to be considered for the evaluation and comparison of body composition in individuals with cognitive decline. Sex has a strong relationship with body composition, where women present with a relatively higher fat mass and lower FFM than men , 30. BufRegarding segmental body analysis, few studies have reported changes in the composition of different body segments in individuals with cognitive decline. Mereu et al. demonstrated that bioimpedance results obtained for only the right arm would be similar to whole-body composition in patients with AD . ReductiSubsequently, there is a lack of information about the relationship between body composition, and bioimpedance for each body segment and cognitive decline. Differences by sex in these components between the upper and lower extremities are not well established, especially for individuals with MCI. Therefore, using a segmental multi-frequency BIA technique, we aimed to examine how whole-body composition changes, segmental body fluids, and bioimpedance variables distinctly for the upper and lower extremities differed between cognitively normal (CN) people and those with MCI among both women and men. We hypothesized that lower extremity variables are more strongly linked to the incidence of MCI than upper extremity variables and that this pattern is more noticeable in women than in men. To test our hypotheses, linear logistic regression methods were conducted to examine odds ratios (ORs) before and after controlling for potential covariates, which was then repeated for the different sexes.In total, 1,153 individuals participated in the study. MCI patients were recruited at Chonnam University Hospital  alongside their family members or caregivers, who were recruited as participants with normal cognition. Written informed consent was obtained from each participant or their legal guardian prior to the study. Individuals were excluded from the study if they met one of the following criteria: obtained less than 3 years of education; had a medical history or ongoing acute or chronic illness that interfered with the intended study design, such as neurological diseases, infections, or mental health instability; excessive alcohol consumption; as a CN individual, had a baseline magnetic resonance imaging showing an abnormal pattern or atrophy; and showing clinical signs of hydration imbalance.z-score no less than −1.5 in at least one of the domains. In contrast, to be considered as CN, participants must have had no history or current symptoms of cognitive decline, a Clinical Dementia Rating of zero, and a SNSB-II z-score no less than −1.5 for all tests. All participants aged between 55 and 90 years had adequate hearing and vision on neuropsychological examination. The included participants then underwent a more precise clinical assessment to obtain demographic information and a medical history alongside a general medical examination, neuropsychological tests, and neurophysiological tests. In the data preprocessing, participants who had non-random missing data (n = 4), extreme results for any parameters  (n = 61), and were diagnosed with dementia or other causes of cognitive decline (n = 61) were excluded from the analysis. According to the principle of multi-frequency BIA, correct impedance measurements should have lower values for higher frequencies ; therefore, observations that did not follow this pattern were excluded (n = 88). There was a total of 939 participants included in the final analysis, including 673 CN and 266 MCI individuals, as illustrated in Mild cognitive impairment patients were defined as those who were not yet demented, had a Clinical Dementia Rating scale of 0.5, had a Seoul Neuropsychological Screening Battery – Second Edition (SNSB-II) The Korean version of the Mini-Mental State Examination (K-MMSE) and SNSB-II were used as neuropsychological assessments in this study.Seoul Neuropsychological Screening Battery – Second Edition is a comprehensive neuropsychological test that is widely used in Korea for evaluating cognitive performance in people with brain injuries and neurological disorders such as dementia , 39. It The K-MMSE is a commonly used screening test for dementia. It tests the five cognitive domains of time and spatial orientation, memory, attention and calculation, language, and visuospatial configuration with a maximum of 30 points.2). Body composition parameters including WHR, FFM, percent body fat (PBF), percent body cell mass (PBCM), total body water per fat free mass (TBW_FFM), and basal metabolic rate (BMR) were estimated from impedance variables obtained from the same device. This device uses a tetrapolar 8-point tactile electrode to measure impedance at six electrical frequencies: 1, 5, 50, 250, 500, and 1,000 kHz and reactance and phase angle at three frequencies: 5, 50, and 250 kHz. Notably, the tetrapolar BIA method was validated as it gives similar results to reference methods such as dual energy X-ray absorptiometry or magnetic resonance imaging techniques (Anthropometric parameters such as height (cm) and weight (kg) were automatically measured from the multi-frequency BIA segmental analyzer Inbody S10 Korea  to the nchniques , 43. Thechniques  instructt-test or Mann–Whitney–Wilcoxon rank sum test was used after confirming distribution normality by the Shapiro–Wilk test. Cohen’s d was applied to test the effect size of the difference. To check the independence of each categorical variable with cognitive status, Pearson’s Chi-squared test or Fisher’s exact test was used. Pearson correlation coefficients were employed to examine the bivariate correlations between age, BMI, and neuropsychological test (SNSB-II and K-MMSE) scores with body composition, segmental water, and impedance-related variables. Pearson correlation coefficients were also used to inspect the partial correlations between those variables with conditioning on age and sex, the two factors that are known to be associated with cognition and body composition  was used for all statistical analyses.The characteristics of the two groups of participants (CN and MCI) were compared. Demographic information, neuropsychological test results, and body composition characteristics were summarized as means and SDs for continuous variables and as frequencies and proportions for categorical variables. Regarding hypothesizing differences by continuous variables, a univariate independent two-sample position , 45. UniConsidering the role of age in the relationship between MCI and changes in body composition and water compartment, we used age as one of the potential confounders in the multivariate regression analysis models in the Considering that all participants appeared to have a symmetrical body structure upon the in-person screening phase, their left-side was strongly positively correlated with the corresponding variable on the right side of the body for most of the segmental BIA variables . The aveThe demographic information, neuropsychological test scores, and comorbidities for the CN and MCI groups are described in Anthropometric information and the whole-body composition results were described in r = 0.46) and cellular water ratio  variables in the lower extremity tended to increase. The reactance and phase angle variables in the lower extremity tended to decrease with aging . Whole-body water hydration status indicated by the ratio of TBW_FFM was positively correlated with age (r = 0.39), whereas other parameters such as PBF, PBCM, and BMR did not show significant correlations.Age displayed positive correlations with the water-related variables but negative correlations with the impedance-related variables. Age demonstrated relatively stronger correlations with the lower extremity variables such as Water_Lean_lower, ECW_ICW_lower, Xc_lower, and PA_lower than the corresponding upper extremity variables. With aging, relative water volume . K-MMSE had the highest positive correlation with PA_lower, with a coefficient of 0.21. Overall, the correlations were more observable with lower extremity variables than with those of the upper extremity.r = 0.14 and TBW_FFM with r = −0.16 and r = −0.17, respectively. These results determined the role of these covariates in the association between BIA variables and cognitive tests.After adjusting for age and sex, most of the significant correlations between the BIA variables and the neuropsychological test scores were diminished. The highest coefficients were obtained between the SNSB-II visuospatial and frontal domains and PA_lower with Before controlling for the covariates, several BIA variables showed significant associations with MCI, such as the whole-body composition variables PBF, WHR, and TBW_FFM or the segmental variables Water_Lean_lower, ECW_ICW_upper, ECW_ICW_lower, R_lower, Xc_upper, Xc_lower, and PA_lower, with significant ORs and their 95% confidence intervals (CIs) away from 1. Regarding whole-body composition, PBF and WHR exhibited negative associations with MCI, whereas TBW_FFM had a positive association with MCI with ORs (95% CI) of 0.86 (0.75–0.99), 0.86 (0.74–0.99), and 1.17 (1.02–1.35), respectively. With respect to segmental variables, there was a positive association between the water-related variables and MCI, and a negative association between the impedance-related variables and MCI. A unit increase in Water_Lean_lower, ECW_ICW_upper, or ECW_ICW_lower was associated with a nearly 22–26% increase in the odds of having MCI, whereas one unit decrease in R_lower, Xc_upper, Xc_lower, or PA_lower was associated with an approximate 17–27% increase in the odds of having MCI.p-values. R_lower and Xc_lower remained associated with MCI prevalence, with ORs and 95% CIs of 0.76 (0.62–0.92) and 0.79 (0.67–0.93), respectively; decreasing one unit in one of these variables was associated with increasing the odds of MCI by 21–24%. Noticeably, SW_lower and SL_lower which did not associate with MCI in the crude model became significantly associated with MCI after adjusting for the covariates, with the OR (95% CIs) of 1.32 (1.02–1.71) and 1.33 (1.03–1.72), respectively. Cellular water distribution between extra- and intra-spaces indicated by ECW_ICW_upper and ECW_ICW_lower variables exhibited a tendency of negatively associated with MCI which was demonstrated by an adjoining statistical significance threshold of the ORs . Relative water volume in both upper and lower extremities  did not show significant associations with the incidence of MCI.After adjusting for age, sex, GDS score, and the comorbidities, PBF, WHR, and TBW_FFM were no longer associated with MCI according to their In this study, we aimed to examine the association between the BIA variables with the incidence of MCI, including seven whole-body composition variables and seven pairs of segmental BIA variables. The MCI group was shown to be slightly older, more depressive, and had significantly poorer cognitive abilities than CN group. The CN and MCI groups had approximately equivalent body anthropometric indices such as height, weight, and BMI. However, individuals with MCI had a slightly lower fat mass as indicated by lower WHR and PBF and higher PBCM and TBW_FFM than the CN participants .Segmental analysis revealed that MCI individuals had a higher amount of relative water volumes and extra- to intracellular water ratios, but lower resistance, reactance, and phase angle in the upper and/or lower extremities when compared with CN individuals . After aFirst of all, the segmental water and segmental lean mass in the lower extremities were proportionally associated with MCI, but their ratio indicated by the Water_Lean_lower variable was not significantly associated with MCI . This reSecondly, the reduction in lower extremity reactance was found to be associated with the higher prevalence of MCI, independent of age, sex, and the other covariates. Lower reactance indicates a lower cell membrane capacitance due to a reduction in body cell mass or a decrease in cell strength due to malnutrition , 46. CovFurthermore, resistance in lower extremity was also found to be linked with the higher prevalence of MCI, regardless of age and the other covariates. Resistance is a measure of resistivity and is inversely proportional to the relative amount of total body water, decrease in resistance indicates a higher proportion of water volume , 49. SarIn this study, those with MCI were in the early stage of cognitive decline, with a mean (SD) K-MMSE score of 26.2 (2.5) that is somewhat closer to the mean (SD) of 27.6 1.9) seen in the CN group than those in the aforementioned studies. Similarly, our MCI participants had better cognitive test scores than the cognitively impaired individuals in the previous studies , 25. The seen in After stratifying by sex, we found that women with MCI showed a significant reduction in terms of reactance and resistance of the lower extremity, whereas this pattern did not emerge in men . The bodIn this study, whole-body composition measurements, such as FFM or PBCM, were investigated as indicators of muscle volume in relation to MCI. Although individuals with MCI showed slightly more muscle volume due to larger FFM and PBCM compared with CN individuals , these vIn terms of muscle quality, phase angle and ECW/ICW have been recommended as indicators of muscle quality , 61. PhaIn the correlation analysis, age was the primary factor in the correlations between cognitive tests (SNSB-II and K-MMSE) and the BIA variables . After aDaily activities involve physical strengths in both arms and both legs. In this study, bioimpedance changes in the lower extremity were observed and were more significantly associated with MCI than those in the upper extremity. A reduction in physical function in the lower extremity is likely to be related to a higher risk of cognitive decline , 33; it In this study, among multiple frequencies of 5, 50, and 250 kHz, the frequency of 50 kHz was selected to simplify the data analysis and be representative of the impedance variables. Indeed, the bioimpedance variables at other frequencies, such as 5 and 250 kHz, behave similarly as those at 50 kHz; lower extremity resistance and reactance variables at those frequencies were associated with MCI prevalence as well .Compared to precedent publications –27, 36, There are some limitations in this study. First, confounding factors, such as daily activity hours and nutritional states, may affect body composition and bioimpedance characteristics , 73. SecThe selected BIA variables, which reflect the changes in body composition, water compartment and bioimpedance for upper and lower extremities, have weak correlations with the K-MMSE score as well as with the SNSB-II domains, especially when taking age and sex into consideration. Nevertheless, multiple logistic regression analysis reveals significant associations between the lower extremity BIA variables with MCI. Specifically, we found an increase in segmental lean mass and a decrease in body cell volume due to an abnormal cellular water distribution in the lower extremities with MCI, which were demonstrated by the reductions in both resistance and reactance. These characteristic changes of BIA variables may be considered as an early sign accompanied by cognitive impairment in the older population.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Institutional Review Board of the Chonnam National University Hospital. The patients/participants provided their written informed consent to participate in this study.DD analyzed the data and wrote the manuscript. BK assisted in the data analysis. KK handled the Institutional Review Board approval and managed the data. MJ participated in writing the manuscript. KC and KL took care of the data collection and curation. JK designed the study and wrote the manuscript. All authors revised and approved the contents of the manuscript, contributed to the article, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Online or hybrid exercise programs incorporating interactive methods  could enhance RNL and quality of life of children with CP. Thus, well-designed online or hybrid exercise programs should be developed and provided for children with CP to enhance overall quality of life during the pandemic.Due to the ongoing COVID-19 pandemic, many online programs for social meetings, education, leisure, and physical activities have been developed and provided; however, children with cerebral palsy (CP) cannot enjoy online programs in the same way that those without disabilities can. The aim of this study was to investigate the differences in reintegration to normal living (RNL), social interaction, and quality of life among school-age children with CP after participation in a game-based online–offline hybrid group exercise program. The current study was conducted on 26 children with CP who participated in a hybrid exercise program. The RNL, social interaction, and quality of life were measured before and after the six-week program. The scores of RNL and quality of life were improved ( The ongoing COVID-19 pandemic has affected people’s lives and led to changes in the daily lives of the worldwide population. People with disabilities who have pre-existing barriers are more vulnerable to unexpected pandemics than people without disabilities. Specifically, children with disabilities and their caregivers have struggled more with changes and adapting to unanticipated pandemic situations than the general population has . Social-In addition, the lack of physical activity and regular rehabilitation treatment due to COVID-19 negatively affect physical development and the attenuation of physical strength, such as muscle loss and muscle atrophy among children with CP, which may cause other problems such as lethargy and social isolation , which hPhysical activity is also a significant predictor of satisfaction with the performance of the daily activities of people with disabilities. The Reintegration to Normal Living (RNL) Index has been used to assess personal satisfaction with social, physical, and psychological functions in the everyday activities of people with disabilities. The RNL is particularly important to understanding the daily life of people with disabilities since it shows how one can actively participate in some domains of human life, such as mobility, self-care, daily activity, and recreational activity . McVeighDespite the known benefits of participation in physical activities, the physical activity levels of people with or without disabilities have dropped due to the COVID-19 pandemic ,23. As aTherefore, the purpose of this study was to explore the effectiveness of the program and investigate the differences in RNL, social interaction levels, and quality of life among school-age children with CP after participation in a game-based online–offline hybrid group exercise program. The hypotheses were as follows.Hypothesis 1.There will be differences in RNL among children with CP before and after participation in a blended (online and offline) group exercise program.Hypothesis 2.There will be differences in social interaction levels among children with CP before and after participation in the blended group exercise program.Hypothesis 3.There will be differences in the quality of life of children with CP before and after participation in the blended group exercise program.The pre–post research design was employed to observe the association between a six- week game-based online–offline hybrid group exercise program for children with CP to explore the effects of the program on children’s RNL, social interaction levels, and quality of life.Participants were recruited from children with CP who were provided wheelchairs from a mobility-improvement project of a welfare foundation. Among them, only children whose parents or caregivers could support online–offline exercise participation were able to participate in this program due to its requirement of both online and offline participation. Thirty-three children voluntarily participated in a group exercise program for CP organized by a G fitness center for children with disabilities in Seoul, South Korea, but only 26 children participated in all six-week sessions and completed both pre- and post-program surveys. Participants were allowed to continue any rehabilitation treatments that they had undergone before participating the program.Throughout the program, there were unpredictable changing schedules due to the government’s COVID-19 policy, making it difficult for the children’s parents and caregivers to follow the changed schedules to support their child’s participation. Additionally, some parents experienced challenges in providing support for their child’s online participation due to a lack of technical knowledge, which also caused an increase in the dropout rate. Moreover, children with disabilities or chronic conditions, including children with CP, are often considered vulnerable during such pandemics by their parents or caregivers ,33; thusParticipants’ ages ranged from 6 to 15 years , with 57.7% identifying as male. The degree of brain lesion disability was reported by parents or caregivers based on the Korean disability rating system, which was assessed by the Modified Barthel Index . The paThe purpose of the study was explained to the parents and caregivers, and informed consent was obtained from them. Parents/caregivers completed questionnaires assessing children’s RNL, social interaction levels, and quality of life before starting the program. Parents/caregivers of children with CP who participated in the exercise program were asked to complete the self-administered questionnaires via email or Google online survey.The game-based online–offline hybrid group exercise program was conducted for 6 weeks every Sunday between September 2020 to October 2020. The program consisted of four online sessions  and two offline sessions (4th week and 5th week), which lasted for 50 min each. The online sessions were conducted using video conferencing platforms, and the offline sessions were held at a gym in Seoul, South Korea. Participants were divided into five classes (5 to 7 children) which eventually became five teams for competition prior to beginning the program. The exercise program focused on a different set of physical activities using metal cage-shaped exercise equipment allowing height and weight adjustments to fix the resistance bands according to the physical characteristics of individual users. The equipment was developed by a team of medical doctors with national funding to support the exercise participation of people with disabilities and was used for exercise programs by wheelchair users . Each grEach online session included (1) a warm-up exercise (stretching), (2) five movements of muscle-strengthening exercises focused on the upper body using resistance bands fixed on a metal cage-shaped exercise instrument, and (3) a cool-down exercise. Strengthening exercises included shoulder-press, pull-down, and trunk exercises  that werThe participants’ level of community reintegration was measured with the Reintegration to Normal Living Index (RNLI), which consists of 11 items in eight domains . The RNLAlthough RNLI includes an item indirectly asking the sociality of the respondents, we used four additional items to identify changes in participants’ ability to interact with various social contexts. The items measuring the social interaction levels of the participants were modified from the socialization part of the Children’s Assessment of Participation and Enjoyment (CAPE)  used in For assessing the quality of life, the work of Charlifue et al.  for peopThe pre- and post-survey questionnaire for this study consisted of a total of 18 questions  and general characteristic questions. Demographic information  was also asked in the pre-survey .W(26) = 0.982, p = 0.913) and quality of life (W(26) = 0.970, p = 0.620). However, the social interaction levels did not meet the criteria for the normality assumption; thus, the Wilcoxon signed-rank test was used to identify the differences between pre- and post-program scores. A paired t-test analysis comparing pre- and post-program scores was conducted to identify changes in the RNL and quality of life of children with CP before and after participating in the exercise program. We adopted a statistical significance level at p≤ 0.05. The differences between pre- and post-program tests were presented using means, standard deviations, t-values for the paired t-test, z-values for the Wilcoxon signed-rank test, and p-values.The data collected in this study were analyzed using IBM SPSS Statistics for Windows, version 25.0  Frequency analysis and technical statistics were conducted to identify demographic information, participation in exercise programs, RNL, social interaction levels, and quality of life of the participants. Before statistical analysis, the Shapiro–Wilk test was performed to assess the normality of continuous data. The results did not show evidence of non-normality of RNL (SD = 0.46), and that of the post-test was 3.40 (SD = 0.51), which were significantly different (t(25) = −2.210, p < 0.05). The average values were compared to see the differences in the detailed items of the RNLI before and after participation in exercise programs for children with CP. In detail, only one item, the ability to deal with life events, showed a significant positive difference before and after participating exercise program (t(25) = 2.379, p < 0.05). However, the scores of nine RNLI items improved after participating in the program, while those of two items remained same  and the post-test  were not significantly different, z = −1.051, p = 0.293 , and the mean of the post-test, 7.50 (SD = 1.39), were significantly different (t(25) = −3.765, p < 0.01; t(25) = −3434, p < 0.01), satisfaction with physical health (t(25) = −2.929, p ≤ 0.01), and satisfaction with psychological health, emotions and mood (t(25) = −3.353, p < 0.01).The paired t-test was conducted to determine the difference in the quality of life before and after participation in exercise programs for children with CP. The mean of the pre-test, 6.20  have been emerging; however, the research shows conflicting results of the satisfaction and effectiveness of the services ,52. ThusIn conclusion, this study focused on exploring the positive changes in participation related to daily living in the social context and quality of life through the hybrid exercise program rather than the enhancement of physical functions of children with CP, which seems small but meaningful; the results of the study could open doors for future research. More studies should be conducted to enhance the quality of online or digital-related exercise programs for children with disabilities and to explore the statistical effectiveness of the programs, which will eventually enable children with disabilities to enjoy the benefits of exercise.