Using the Analytic Hierarchy Process (AHP) to understand the most important factors to design and evaluate a telehealth system for Parkinson's disease

Construction and Analysis of the Physical Fitness Evaluation Index System for Elite Male Singles Badminton Players: Based on Delphi and AHP Methods

OBJECTIVE

To construct and validate a physical fitness evaluation index system for elite male singles badminton players.

METHODS

Utilizing the Delphi method to establish a comprehensive evaluation system, the analytic hierarchy process (AHP) was employed to calculate the influence weights of various indicators. The validity of the comprehensive evaluation system was verified using testing methods.

RESULTS

After three rounds of expert selection, the physical fitness evaluation index system for elite male singles badminton players includes three primary indicators, nine secondary indicators, and twenty-one tertiary indicators. Among the primary indicators, specialized physical fitness holds a significant weight in the evaluation with a value of 0.651, whereas body morphology has a smaller weight of 0.077. Among the secondary indicators, specialized agility, strength, and endurance have higher weights of 0.223, 0.217, and 0.210, respectively. Among the tertiary indicators, four-corner ball touch, 400 m × 5 shuttle run, smash-and-rush, and vertical jump height hold higher weights of 0.119, 0.114, 0.104, and 0.096, respectively. The results after randomly selecting ten elite male singles badminton players and applying the evaluation index system demonstrated that this system has high feasibility and validity. It can not only comprehensively assess the physical fitness of athletes but also provide significant practical guidance for enhancing their competitive performance.

CONCLUSIONS

The evaluation system and weight assignments constructed in this study can scientifically and comprehensively reflect the physical fitness status of athletes. It can guide coaches in formulating targeted training plans and optimizing training outcomes.

Multiple prescription pattern recognition model based on Siamese network

Prescription data is an important focus and breakthrough in the study of clinical treatment rules, and the complex multidimensional relationships between Traditional Chinese medicine (TCM) prescription data increase the difficulty of extracting knowledge from clinical data. This paper proposes a complex prescription recognition algorithm (MTCMC) based on the classification and matching of TCM prescriptions with classical prescriptions to identify the classical prescriptions contained in the prescriptions and provide a reference for mining TCM knowledge. The MTCMC algorithm first calculates the importance level of each drug in the complex prescriptions and determines the core prescription combinations of patients through the Analytic Hierarchy Process (AHP) combined with drug dosage. Secondly, a drug attribute tagging strategy was used to quantify the functional features of each drug in the core prescriptions; finally, a Bidirectional Long Short-Term Memory Network (BiLSTM) was used to extract the relational features of the core prescriptions, and a vector representation similarity matrix was constructed in combination with the Siamese network framework to calculate the similarity between the core prescriptions and the classical prescriptions. The experimental results show that the accuracy and F1 score of the prescription matching dataset constructed based on this paper reach 94.45% and 94.34% respectively, which is a significant improvement compared with the models of existing methods.

Need for personalized monitoring of Parkinson's disease: the perspectives of patients and specialized healthcare providers

Background

Digital tools such as wearable sensors may help to monitor Parkinson's disease (PD) in daily life. To optimally achieve the expected benefits, such as personized care and improved self-management, it is essential to understand the perspective of both patients and the healthcare providers.

Objectives

We identified the motivations for and barriers against monitoring PD symptoms among PD patients and healthcare providers. We also investigated which aspects of PD were considered most important to monitor in daily life, and which benefits and limitations of wearable sensors were expected.

Methods

Online questionnaires were completed by 434 PD patients and 166 healthcare providers who were specialized in PD care (86 physiotherapists, 55 nurses, and 25 neurologists). To gain further understanding in the main findings, we subsequently conducted homogeneous focus groups with patients (n = 14), physiotherapists (n = 5), and nurses (n = 6), as well as individual interviews with neurologists (n = 5).

Results

One third of the patients had monitored their PD symptoms in the past year, most commonly using a paper diary. Key motivations were: (1) discuss findings with healthcare providers, (2) obtain insight in the effect of medication and other treatments, and (3) follow the progression of the disease. Key barriers were: (1) not wanting to focus too much on having PD, (2) symptoms being relatively stable, and (3) lacking an easy-to-use tool. Prioritized symptoms of interest differed between patients and healthcare providers; patients gave a higher priority to fatigue, problems with fine motor movements and tremor, whereas professionals more frequently prioritized balance, freezing and hallucinations. Although both patients and healthcare providers were generally positive about the potential of wearable sensors for monitoring PD symptoms, the expected benefits and limitations varied considerably between groups and within the patient group.

Conclusion

This study provides detailed information about the perspectives of patients, physiotherapists, nurses and neurologists on the merits of monitoring PD in daily life. The identified priorities differed considerably between patients and professionals, and this information is critical when defining the development and research agenda for the coming years. We also noted considerable differences in priorities between individual patients, highlighting the need for personalized disease monitoring.

Analytic hierarchy process: An innovative technique for culturally tailoring evidence-based interventions to reduce health disparities

Latinos in the United States represent a disproportionate burden of illness and disease and face barriers to accessing health care and related resources. Culturally tailored, evidence-based interventions hold promise in addressing many of these challenges. Yet, ensuring patient voice is vital in the successful development and implementation of such interventions. Thus, this paper examines the application of analytic hierarchy process (AHP) to inform the augmentation and implementation of an evidence-based chronic disease self-management programme for underserved Latinos living with both minor depression and chronic illness. The process of AHP allows for direct input from the individuals that would utilize such a programme, including afflicted individuals, their family members and the health educators/promotores that would be responsible for implementation. Specifically, 45 participants, including 15 individuals with chronic disease, 15 family members/caregivers and 15 promotores, partook in the Stakeholder Values Questionnaire, which elicited preferences and values regarding major goals, processes and content for the intervention. AHP was employed to analyse pairwise comparison ratings and to determine differences and similarities across stakeholder groups. This analytical technique allowed for the adaptation of the EBI to stakeholders' specific priorities and preferences and facilitated complex decision-making. Findings not only shed light on similarities and differences between stakeholder groups, but also the magnitude of these priorities and preferences and allowed the intervention to be driven by the participants, themselves. Applying AHP was a unique opportunity to optimize the decision-making process to inform cultural adaptation of an EBI while considering multiple viewpoints systematically.

The need scoping and prioritization of the medical team to integrate new technologies for inpatient rehabilitation services

BACKGROUND/PURPOSE

To explore unmet needs for inpatient rehabilitation services and assess the relative preference of new technology versus current practice by a structured decision-making model.

METHODS

The clinical needs for in-patient rehabilitation care were explored by an in-depth interview with the aid of a service blueprint in 2 affiliated hospitals of a university. A questionnaire was constructed according to the analytic hierarchical process (AHP) model to make pairwise comparison between the clinical needs for prioritization. The preference between traditional practice and new technology to fulfill the criteria was compared.

RESULTS

Seven categories of unmet needs were summarized through focus group interviews to construct a questionnaire for the analytic hierarchical process. The results showed that assessment and recording ranked first as important applications, followed by clinical alerts, implementation of rehabilitation, patient/family education, team communication, schedule management and finally, the localization of patients/workers. The subjects from different professional disciplines had different rankings of preference weight, reflecting the individualized needs related to their practice. In addition, the subjects placed a higher preference on new technology than on current practice in all the categories.

CONCLUSION

The preference global weights on the needs to integrate new technologies into rehabilitation services aims to improve efficiency, safety and outcome. Further studies are needed to explore the needs from the perspective of the patients.

An integrated model to evaluate the impact of social support on improving self-management of type 2 diabetes mellitus

BACKGROUND

Type 2 Diabetes Mellitus (T2DM) is a chronic disease closely related to personal life style. Therefore, achieving effective self-management is one of the most important ways to control it. There is evidence that social support can help to improve the self-management ability of patients with T2DM, but which social support is more effective has been rarely explored. The purpose of this study is to construct an integrated model to analyze which social support has more significant impact on self-management of T2DM, and provide reasonable suggestions to health care providers on how to effectively play the role of social support.

METHODS

We established a social support indicator evaluation system and proposed an integrated model that combines ANP (Analytical Network Process) and CRITIC (CRiteria Importance through Intercriteria Correlation) methods to evaluate the impact of social support on T2DM self-management from both subjective and objective perspectives. The weights calculated by the model will serve as the basis for us to judge the importance of different social support indicators.

RESULTS

Informational support (weighting 49.26%) is the most important criteria, followed by tangible support (weighting 39.24%) and emotional support (weighting 11.51%). Among 11 sub-criteria, guidance (weighting 23.05%) and feedback (weighting 14.68%) are two most relevant with T2DM self-management. This result provides ideas and evidence for health care providers on how to offer more effective social support.

CONCLUSION

To our knowledge, this is the first study in which Multi-Criteria Decision Making (MCDM) tools, specifically ANP and CRITIC, are used to evaluate the impact of social support on improving self-management of type 2 diabetes. The study suggests that incorporating two sub-indicators of guidance and feedback into the diabetes care programs may have great potential to improve T2DM self-management and further control patient blood glucose and reduce complications.

Use of the AHP methodology in system dynamics: Modelling and simulation for health technology assessments to determine the correct prosthesis choice for hernia diseases

Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model.

Shaping an Effective Health Information Website on Rare Diseases Using a Group Decision-Making Tool: Inclusion of the Perspectives of Patients, Their Family Members, and Physicians

BACKGROUND

Despite diverging definitions on rare conditions, people suffering from rare diseases share similar difficulties. A lack of experience by health professionals, a long wait from first symptoms to diagnosis, scarce medical and scientific knowledge, and unsatisfactory treatment options all trigger the search for health information by patients, family members, and physicians. Examining and systematically integrating stakeholder needs can help design information platforms that effectively support this search.

OBJECTIVE

The aim of this study was to innovate on the group decision-making process involving patients, family members, and physicians for the establishment of a national rare disease Internet platform. We determined differences in the relevance of health information-especially examining quantifiable preference weights-between these subgroups and elucidated the structure and distribution of these differences in people suffering from rare diseases, their family members, and physicians, thus providing information crucial to their collaboration.

METHODS

The included items were identified using a systematic Internet research and verified through a qualitative interview study. The identified major information needs included medical issues, research, social help offers, and current events. These categories further comprised sublevels of diagnosis, therapy, general disease pattern, current studies, study results, registers, psychosocial counseling, self-help, and sociolegal advice. The analytic hierarchy process was selected as the group decision-making tool. A sensitivity analysis was used to determine the stability and distribution of results. t tests were utilized to examine the results' significance.

RESULTS

A total of 176 questionnaires were collected; we excluded some questionnaires in line with our chosen consistency level of 0.2. Ultimately, 120 patients, 24 family members, and 32 physicians participated in the study (48 men and 128 women, mean age=48 years, age range=17-87 years). Rankings and preference weights were highly heterogeneous. Global ranking positions of patients, family members, and physicians are shown in parentheses, as follows: medical issues (3/4, 4, 4), research (3/4, 2/3, 3), social help offers (1, 2/3, 2), and current events (2, 1, 1); diagnosis (6, 8, 9), therapy (5, 9, 7), general disease pattern (9, 4/5/6, 6), current studies (7, 4/5/6, 3), study results (8, 7, 8), registers (4, 1, 5), psychosocial counseling (1, 2, 4), self-help (3, 3, 2), and sociolegal advice (2, 4/5/6, 1). Differences were verified for patients for 5 information categories (P=.03), physicians for 6 information categories (P=.03), and family members for 4 information categories (P=.04).

CONCLUSIONS

Our results offer a clear-cut information structure that can transparently translate group decisions into practice. Furthermore, we found different preference structures for rare disease information among patients, family members, and physicians. Some websites already address differences in comprehension between those subgroups. Similar to pharmaceutical companies, health information providers on rare diseases should also acknowledge different information needs to improve the accessibility of information.

All that Glitters is not Gold: Six Steps Before Selecting and Prioritizing e-Health Services

Since the market for e-health applications is constantly growing, it is getting an ever more complex endeavor to select and prioritize the right service offering given a particular situation. In examining the extant literature, it was revealed that little emphasis is actually placed on how to analyze contextual or environmental factors prior to the selection and prioritization of e-health services. With this paper, we therefore propose a formative framework consisting of six fundamental yet very pragmatic steps that may support decision makers in identifying the most important contextual pre-requisites that e-health services need to fulfill in order to be considered as effective for their environment to be implemented.

Monitoring of motor and non-motor symptoms of Parkinson's disease through a mHealth platform

Parkinson's disease (PD) is a complex, chronic disease that many patients live with for many years. In this work we propose a mHealth approach based on a set of unobtrusive, simple-in-use, off-the-self, co-operative, mobile devices that will be used for motor and non-motor symptoms monitoring and evaluation, as well as for the detection of fluctuations along with their duration through a waking day. Ideally, a multidisciplinary and integrated care approach involving several professionals working together (neurologists, physiotherapists, psychologists and nutritionists) could provide a holistic management of the disease increasing the patient's independence and Quality of Life (QoL). To address these needs we describe also an ecosystem for the management of both motor and non-motor symptoms on PD facilitating the collaboration of health professionals and empowering the patients to self-manage their condition. This would allow not only a better monitoring of PD patients but also a better understanding of the disease progression.

OB CITY-Definition of a Family-Based Intervention for Childhood Obesity Supported by Information and Communication Technologies

Childhood obesity is becoming one of the 21st century's most important public health problems. Nowadays, the main treatment of childhood obesity is behavior intervention that aims at improve children's lifestyle to arrest the disease. Information and communication technologies (ICTs) have not been widely employed in this intervention, and most of existing ICTs systems are not having a long-term effect. The purpose of this paper is to define a system to support family-based intervention through a state-of-the-art analysis of family-based interventions and related technological solutions first, and then using the analytic hierarchy process to derive a childhood obesity family-based behavior intervention model, and finally to provide a prototype of a system called OB CITY. The system makes use of applied behavior analysis, affective computing technologies, as well as serious game and gamification techniques, to offer long term services in all care dimensions of the family-based behavioral intervention aiming to provide positive effects to the treatment of childhood obesity.

Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting

Background

The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context.

Methods

A systematic literature review was conducted by searching the Pubmed and Web of Science databases for articles with the following keywords in their titles or abstracts: “Analytic Hierarchy Process,” “Analytical Hierarchy Process,” “multi-criteria decision analysis,” “multiple criteria decision,” “stated preference,” and “pairwise comparison.” In addition, we developed reporting criteria to indicate whether the authors reported important aspects and evaluated the resulting studies’ reporting.

Results

The systematic review resulted in 121 articles. The number of studies applying AHP has increased since 2005. Most studies were from Asia (almost 30 %), followed by the US (25.6 %). On average, the studies used 19.64 criteria throughout their hierarchical levels. Furthermore, we restricted a detailed analysis to those articles published within the last 5 years (n = 69). The mean of participants in these studies were 109, whereas we identified major differences in how the surveys were conducted. The evaluation of reporting showed that the mean of reported elements was about 6.75 out of 10. Thus, 12 out of 69 studies reported less than half of the criteria.

Conclusion

The AHP has been applied inconsistently in healthcare research. A minority of studies described all the relevant aspects. Thus, the statements in this review may be biased, as they are restricted to the information available in the papers. Hence, further research is required to discover who should be interviewed and how, how inconsistent answers should be dealt with, and how the outcome and stability of the results should be presented. In addition, we need new insights to determine which target group can best handle the challenges of the AHP.