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家庭及社区健康

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家庭及社区健康

Family1

    本研究组致力促进健康,我们关注有健康风险的社群,以社会生态学模式为基础,考虑个人,人际/伴侣/家长/家庭之间的关係,学校和工作环境,社区和社会健康等因素,探讨疾病预防。

Family2
此外,识别不同社群,如︰儿童、青少年、家长和伴侣的健康风险,及早制定预防的干预措施,从家庭、学校、职场和社区层面促进全民健康。
设计及推行各式计划,从家庭、学校和社区层面,促进儿童和青少年的身心健康和健康行为,并建立健康生活模式,使儿童和青少年健康成长。
关注为人父母者之健康,亲职过渡期和亲职经验,并探讨家庭作为社会支持的来源,伴侣的支持和家庭的凝聚力。制订计划以加强家庭成员的归属感,相互支持,亲职和应付疾病的能力。
善用全球、本地、国家和地区层面的知识和资讯,宣传危害社区健康的因素,如:灾害风险,感染控制,工作场地的危险等等。此外,开展研究并评估可提升个人和社区抗逆能力的策略。

研究范畴主任

成员

智慧健康研究中心

智慧健康研究中心运用科技创新医护服务,促进医护实践及提升护理质素。我们善用科技专长 (如虚拟实境和人工智慧),开展跨专业应用研究,并把研究成果应用于实践,以促进医护教育,诊断和治疗。

世界卫生组织社区健康服务合作中心

世界卫生组织(世卫组织)在2007年12月委任香港理工大学护理学院为「世界卫生组织社区健康服务合作中心」。膺受重任,本院一直履行世卫组织所予职责,积极推动循证社区健康服务,促进香港、区域及全球民众健康。

雪肌兰国际感染控制中心

雪肌兰国际感染控制中心是香港理工大学护理学院的专科中心,旨在领导业界,并推动感染预防和控制的卓越实践。理大各学系参与其中,与我们一起提供多专业,科技,教育和谘询服务。

研究的影响

即将推出。

在学研究生

黄修禹

博士生

林美娟

博士生

谭汉麟

博士生

张雪林

博士生

肖霄

博士生

邹静

博士生

林静宜

博士生 (Part-time)

校外资助计划

The effect of a father-involvement breastfeeding telephone support intervention on exclusive and sustained breastfeeding: A randomized controlled trial

Investigators Name:
PI: Dr Fei Wan NGAI
Co-I: Ms Pui Sze CHAN, Ms Chi Oi Christine LAM

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK$1,235,540

Commencement Date: 29-Jan-22

Objectives: To examine the effect of a father-involvement breastfeeding telephone support intervention on prevalence and duration of exclusive breastfeeding, postnatal depression and parent-infant boding.

Methods: This is a randomized controlled trial. A sample of 738 postpartum mothers and fathers will be recuited at the postnatal units of public hospitals and randomly assigned to either the experimental or the control groups. The intervention consists of four weekly telephone-administered counselling sessions on breastfeeding, delivered individually in the first month postpartum for mothers and fathers. Outcomes include the prevalence and duration of exclusive breastfeeding, which will be collected at 1, 2, 4 and 6 months postpartum, postnatal depression and parent-infant boding, which will be assessed by the Edinburgh Postnatal Depression Scale and Postpartum Bonding Questionnaire, respectively, at 2 and 6 months postpartum. Generalized linear mixed models and survival analysis will be conducted to compare differences between two groups on the outcomes.

Significance: The World Health Organization advocates for breastfeeding as the best source of food for optimal infant development, which can reduce the risk of infant mortality and morbidity. The findings can provide a direction for the development of flexible, accessible and culturally sensitive interventions to promote breastfeeding and mental health in Chinese society.

Virtual/Augmented Reality Based Planning and Intraoperative Guidance for Precise Laparoscopic Cystectomy via Advanced Human-in-the-loop Image Segmentation, Visualization, and Registration Techniques

Investigators Name:
PI: Dr Jing QIN
Co-I: Prof. Kup Sze CHOI, Prof. Jeremy Yuen Chun TEOH

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK$838,393

Commencement Date: 1-Jan-22

Bladder cancer is one of the most common malignant tumors in the urinary system. While cystectomy is the gold standard treatment for invasive and recurred superficial high-grade bladder tumors, traditional open cystectomy remains one of the most invasive surgical procedures in urology. Clinical evidence has shown that laparoscopic cystectomy (LC) and robotic-assisted laparoscopic cystectomy (RALC) are feasible and reliable minimally invasive alternatives to open cystectomy. However, it is still a challenging task for surgeons to perform a successful LC/RALC mainly due to (1) the complicated (and patient-specific) surgical anatomy and (2) a loss of direct vision caused by the limited view of laparoscopic scenes.

While some LC/RALC planning and intraoperative guidance systems have been developed, they are still incapable of sufficiently fulfilling the demanding clinical requirements. The main shortcomings include inaccurate segmentation under limited training data, imperfect visualization for comprehensive planning, and imprecise intraoperative and preoperative image registration under large deformations. More importantly, existing systems failed to seamlessly and naturally integrate human interactions into planning and intraoperative guidance procedures, resulting in that surgeons’ knowledge and experience cannot be efficiently combined with machine wisdom to enhance the preciseness and efficiency of computer-assisted LC/RALC.

In this project, we shall develop a set of innovative yet efficient human-in-the-loop image segmentation, visualization, and registration algorithms to sufficiently leverage human-computer collaboration to tackle the aforementioned shortcomings. First, we shall propose a novel interactive deep learning architecture equipped with an unsupervised model to precisely segment bladder, tumor, prostate, and other relevant organs from CT volumes without using any pixel-level annotations. We shall further propose a new human-in-the-loop model tailored for vessel segmentation considering their unique yet complicated topological characteristics. Second, we shall propose a novel human-in-the-loop volume rendering algorithm via a generative adversarial network (GAN), allowing surgeons to conveniently select viewpoints and modify transfer functions to extract more useful visual information for precise planning. Third, we shall propose a new real-time registration algorithm to register preoperative models and intraoperative laparoscopic scenes for interactive intraoperative guidance. Finally, we shall integrate these techniques into a system and extensively evaluate it with our clinical collaborators.

In summary, this is a joint project with a strong interdisciplinary team including experts in medical image computing, virtual/augmented reality, and LC/RALC. The proposed innovative techniques can not only strengthen LC/RALC planning and intraoperative guidance but provide insights on how to integrate human interactions into a computer-assisted surgery system to improve its preciseness and efficiency.

Patient-Specific Abdominal Aortic Aneurysm Rupture Risk Assessment via Advanced Deep Learning and Computational Fluid Dynamics

Investigators Name:
PI: Dr Jing QIN

Funding Scheme/ Source of Funding: Innovation and Technology Fund - Mainland-Hong Kong Joint Funding Scheme (ITF-MHKJFS)

Total Grant: HK$1,998,600

Commencement Date: 1-Dec-21

Abdominal Aortic Aneurysm (AAA) is a common cardiovascular disease, referring to the local or diffuse expansion and bulging of the abdominal aorta, which belongs to a kind of lesion or injury of the abdominal aortic wall. Once an AAA ruptures, only about 3% of patients can survive. Therefore, accurately predicting the risk of AAA rupture is extremely important for saving lives. Unfortunately, the current clinical guidelines still use the largest AAA diameter as the risk prediction indicator, which has been proposed for more than 30 years, and mounting evidence shows that its accuracy is obviously insufficient in clinical practice. Another approach is, based on the patient-specific blood vascular models, to leverage computational fluid dynamics (CFD) to analyze the hemodynamic characteristics of AAA and calculate the corresponding rupture risk assessment indexes. However, nowadays, it is a challenging task to develop a robust and efficient AAA rupture risk prediction system based on CFD models. In this project, we shall propose a series of new deep learning and computational fluid dynamics models to meet these challenges, and develop a new AAA rupture risk prediction system in order to improve the accuracy of prediction and provide more solid evidence for clinical decision-making. This project will deal with various challenging tasks, including clinical data collection, medical image processing, mathematical and physical model construction, algorithm acceleration, clinical verification and analysis, etc., by harnessing deep learning, fluid-structure coupling model, turbulence calculation, high-performance computing, and other advanced technologies. We shall investigate accurate biomechanical models suitable for AAA hemodynamic analysis and corresponding efficient solvers. Through extensive clinical verification, we aim to ensure the correspondence between the obtained indicators and clinical symptoms/rupture. The proposed system has great commercial potential, and the proposed techniques can also promote many relevant industries, such as intelligent diagnosis and treatment, deep learning, and computational fluid dynamics.

An Automated Urine Cytopathology Reporting System via Advanced Deep Learning Models Driven by Both Data and Human Knowledge

Investigators Name:
PI: Dr Jing QIN
Co-I: Prof. Yuen-Chun TEOH, Dr Cheong-Kin CHAN

Funding Scheme/ Source of Funding: Innovation and Technology Fund - Innovation and Technology Support Programme (ITF-ITSP)

Total Grant: HK$2,425,760

Commencement Date: 1-Sep-21

Bladder cancer is a common cancer worldwide. While urine cytology is a simple and effective way to detect and diagnose bladder cancer, screening urine cytology specimens has long been regarded as a labor-intensive, time-consuming and costly task in clinical practice. Automated urine cytopathology reporting system is thus highly demanded. However, development such a system is a challenging task due to (1) the complicated context of digitized urine cytology slides, including sampling errors, urothelial cell degradation, and obscuring inflammation and/or blood, (2) the difficulties in distinguishing atypical and suspicious cells, and (3) more importantly, the insufficient capability of existing deep learning models, which are often only driven by data and is difficult to take advantage of human knowledge to make to diagnosis more precise and efficient. In this project, we shall develop a set of novel deep learning models to comprehensively address these challenges. We shall first develop deep learning models for cell-level analysis by segmenting cytoplasm and nuclei of each cell, measuring its cytoplasm-to nuclei area ratio, and classifying the cells by integrating clinical and morphometric knowledge. Then, based on the cell-level knowledge and whole-slide information, we shall further infer the diagnosis results to assist clinical decision-making. We shall integrate these algorithms into an automated and user-friendly urine cytopathology reporting system. The proposed system cannot only greatly reduce the workload of pathologists but also has great commercial potential considering extensive urine tests are conducted in clinical routine.

Time to Change Hong Kong: Reducing Stigma Around Mental Health in Hong Kong – A Service Evaluation

Investigators Name:
PI: Dr Wing Ka Grace HO
Co-I: Mr Man Hon CHUNG, Prof. Daniel Thomas BRESSINGTON, Ms Odile THIANG

Funding Scheme/ Source of Funding: Mind Mental Health Hong Kong Limited

Total Grant: HK$73,238

Commencement Date: 1-Jun-21

Background
It is estimated that one in six Hong Kong adults suffer from a diagnosable mental illness and the number of people requiring treatment have been rising over the last 5 years. However, negative stigmatized attitudes towards mental illness and its treatment are still commonplace locally, leading to discriminatory behaviour and isolation. This creates stigma, dissuades those suffering from a mental illness to seek help, and prevents their re-integration into the community. Improving the public’s attitudes towards mental illness and its treatment is therefore crucial.
Previous studies have shown that a variety of educational interventions can have positive effects, but it is still very unclear how best to reduce stigmatized attitudes of Hong Kong citizens. The Time to Change Hong Kong programme is offered by Mind HK. This is a new campaign that involves training ambassadors with personal experience of mental health challenges to facilitate face-to-face educational events with the public.

Study aims

  • Explore the ambassadors’ experiences and views of the programme in focus groups before starting their training and 3-months later.  
  • Measure changes in the attendees’ attitudes and understanding towards mental illness, and their attitudes towards people with mental health problems both currently, and in their intended behaviour at three time points (before attending the story telling events, immediately following the events, and three months after attending).
  • Evaluate the achievement of Mind HK’s defined key performance indicators over a 6-month period.

Design and methods
This service evaluation will adopt a prospective cohort mixed-methods study design. All attendees from September 2020 to March 2021 will be invited to take part. Participants will complete a set of questionnaires measuring their attitudes towards mental illness and treatment using paper based questionnaires or the online system. They will be asked to re-complete these questionnaires immediately after their visit and at 3-months follow-up. Focus group interviews will be also be conducted with the ambassadors before their training and at 3-months follow up to explore their experiences of attending the training and delivering the workshop events.

Relevance
The findings are expected to provide essential information about the effectiveness of Time to Change Hong Kong programme in reducing stigma and increasing public understanding, and highlight experiences of the ambassadors in participating in the programme.


Cardiac-Flow: A Precise yet Super-Efficient Diagnosis System for Coronary Artery Disease Based on Deep Learning and Computational Fluid Dynamics

Investigators Name:
PI: Dr Jing QIN
Co-I: Prof. Jing CAI, Prof. Qiang XU, Dr Ming Yen NG, Dr Qi DOU, Prof. Ruqiong NIE, Prof. Xiaopei LIU, Prof. Xiao KE

Funding Scheme/ Source of Funding: Innovation and Technology Fund - Midstream Research Programme for Universities (ITF-MRP)

Total Grant: HK$5,655,100

Commencement Date: 1-Jun-21

Cardiovascular disease is the major cause of death globally, and around half of these deaths are relevant to coronary artery disease (CAD). However, in clinical practice, it remains a very challenge task to precisely and efficiently diagnose CAD and make an appropriate treatment for it. The current gold standard of diagnosis is measuring the functional severity of coronary stenosis in an invasive way, which may put patients at risk. While some systems for non-invasive diagnosis have been developed, they have some obvious shortcomings in terms of preciseness and efficiency. In this project, we propose a novel precise yet super-efficient diagnosis system for CAD by developing a set of advanced deep learning and computational fluid dynamics models in order to, as comprehensively as we can, address these shortcomings. First, we will propose an interactive segmentation framework equipped with an unsupervised model, which allows physicians to precisely segment the coronary arteries from computed tomography angiography (CTA) images without expensive voxel-wise annotations. Second, we shall propose a data-driven approach to refine the anatomical model reconstructed from the segmentation results by removing the artifacts and recovering its high-quality geometrical characteristics. Third, we shall propose a novel computational fluid dynamics (CFD) solver to accelerate blood flow simulation based on kinetic mechanism with Lattice Boltzmann Method (LBM). Fourth, we shall further propose a novel deep learning model equipped with an active learning strategy, taking 3D vascular models and coarse-grained LBM results as inputs and inferring accurate fine-grained LBM results, to further accelerate the diagnosis procedure. We shall integrate these techniques into a system and conduct extensive experiments to validate it with our clinical collaborators. Our aim is to, compared with existing systems, help physicians diagnose CAD with more precise models and a much faster speed, reducing the current computational time from several days to several minutes. In this project, we aim at developing a novel and efficient system for rapid and noninvasive diagnosis of CAD. First, we shall propose a novel interactive image segmentation approach equipped with a weakly-supervised deep learning model to accurately segmenting patient-specific anatomic model of coronary arteries from CTA images. We shall then propose a data-driven approach to refine the reconstructed anatomic model by removing the artifacts and outliers and recovering its high-quality geometric structures, which is critical for the following fluid computation. Third, we shall propose a novel CFD solver based on lattice Boltzmann method, which is capable of figuring out the fluid properties under complex boundary conditions in a highly parallel way, making rapid and accurate diagnosis of CAD possible. Fourth, in order to further accelerate the diagnosis speed with limited computational resources in clinical settings, we shall develop dedicated learning models to predict high-resolution results from a set of low-resolutions results and inference the hemodynamics directly from the coronary anatomies. Fifth, we shall validate the accuracy and performance of the above algorithms and integrate them into a unified system for the diagnosis of CAD. The proposed system shall provide a valuable strategy for clinical decision-making and patient management, while reducing the ratio of unnecessary invasive testing and improving the patient outcomes with reduced healthcare cost.

Intelligent Recognition of Movement Intention with Brain-Computer Interface for Lower-limb Rehabilitation

Investigators Name:
PI: Prof. Kup Sze CHOI
Co-I: Dr Zhaohong DENG, Dr Nai Kuen FONG, Dr Shuang LIANG

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK$528,999

Commencement Date: 1-Jan-20

Neuromuscular signals of people with neurological disorders cannot be effectively transmitted from the brain to the extremities, leading to movement impairment that causes difficulty with activities of daily living. To promote brain plasticity, brain-computer interface (BCI) is proposed to develop neuro-rehabilitation approaches that can produce external feedback based on movement intentions directly identified with the electroencephalogram (EEG) signals acquired non-invasively from the brain. The approaches have been largely applied for upper-limb rehabilitation.

For the lower limbs, since the signals are generated from deeper brain regions, they are less distinctive for accurate classification, making it more challenging to develop BCI for lower-limb rehabilitation. To meet this challenge, this project focuses on neuro-rehabilitation of lower limbs. Advanced machine learning technologies will be developed to process the EEG signals from deeper brain regions and detect the movement intention accurately. Takagi-Sugeno-Kang (TSK) fuzzy system (FS) will be exploited due to its superior interpretability and classification performance. First, multi-view algorithms will be developed to obtain effective features from the EEG signals by synergizing various feature extraction methods. Next, multi-task algorithms will be developed to accurately perform the tasks of classifying the intention to move the left or right hip, and left or right knee, respectively. The classification is achieved by considering collectively the individual tasks and their correlation, where deep learning will be used to further increase the accuracy. Analogous to mirror therapy, virtual environment will be created to display interactive visual cues and guidance driven by EEG signals via BCI. Haptic feedback will also be provided through exoskeleton robot and vibrotactile stimulation. Experiments will be conducted to study be performance of the proposed approaches.

Patient-specific Planning and Intraoperative Guidance System for Precise Left Atrial Appendage Occlusion via Weakly-supervised Deep Learning, Perception-aware Visualization, and Context-driven Touchless Interaction

Investigators Name:
PI: Dr Jing QIN
Co-I: Prof. Kup Sze CHOI, Prof. Chi Wing FU, Prof. Pui Wai LEE, Prof. Tien Tsin WONG

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK$528,999

Commencement Date: 1-Jan-20

Atrial fibrillation (AF) is a common and clinically significant arrhythmic disorder that results in increased risk of morbidity and mortality. Compelling evidence has demonstrated that the left atrial appendage (LAA), a finger-like structure originating from the left atrium, is the most common site for thrombus formation in association with AF. In recent years, many studies have suggested that occluding LAA and isolating it from the left atrium is an effective treatment for preventing patients with AF from stroke. However, it is challenging for surgeons to perform a successful LAA occlusion procedure due to (1) the large variations in the anatomical characteristics of LAA among patients, (2) the complicated surgical anatomy and environment, and (3) the inconveniences of current intraoperative guidance settings, where x-ray fluoroscopy and transesophageal echocardiography (TEE) are applied to display the device position and the surgical anatomy separately. In this project, we aim at developing a novel system with a set of new and enabling technologies to meet these challenges to facilitate patient-specific planning and intraoperative guidance of LAA occlusion and improve its outcome and prognosis.

The proposed system is composed of two modules: a planning software and a toolkit for intraoperative guidance. To construct the planning software, we shall first propose a novel weakly-supervised deep learning model to automatically segment the LAA and relevant tissues from 3D TEE images, which aims at obtaining accurate segmentation results with limited manual annotations. We shall then propose a perception-aware visualization approach to clearly exhibit the surgical environment with lucid morphological information of LAA for precise planning. To construct the toolkit for intraoperative guidance, we shall first propose a new 2D X-ray and 3D TEE registration algorithm based on domain adaptation and adversarial learning. Then, a novel occlusion-manageable and lightness-consistent visualization algorithm will be developed to clearly display the fused data obtained based on the registration, which is neglected by most of existing intraoperative guidance systems. Furthermore, we shall propose a novel context-driven touchless interaction framework for natural, intuitive and effective interaction between the surgeons and the fused guidance image. We shall extensively evaluate these proposal algorithms and the system based on widely used metrics and clinical requirements.

This is a joint project with a strong interdisciplinary team including experts in medical image processing, visualization, human-computer interaction, echocardiography, and LAA occlusion procedure. The proposed system, as far as we know, is the first one to comprehensively address the challenges in LAA occlusion procedures with the aid of advanced techniques and hence has great potential to improve its outcome and efficiency. We believe the proposed novel techniques can also to be used to construct planning and intraoperative guidance systems for other complicated structure heart interventions, especially the ones taking TEE as guidance.

A couple-based interpersonal psychotherapy on postnatal depression and family sense of coherence: a randomized controlled trial

Investigators Name:
PI: Dr Fei Wan NGAI
Co-I: Dr Kwok-yin LEUNG, Prof. Ling Ling GAO, Prof. Jean Tak Alice LOKE YUEN

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $1,104,700

Commencement Date: 1-Jan-19

Background: Postnatal depression is a common public health problem which has long-term sequelae on the family and the infant’s psychosocial development. Interpersonal psychotherapy has demonstrated its value as one of the most effective interventions for postnatal depression. Enhancement of family sense of coherence may be helpful for women who are at risk for postnatal depression. However, few studies in the context of Chinese parenthood have evaluated the effect of interpersonal psychotherapy on postnatal depression and the underlying mechanisms.

Aims: This study seeks to examine the effect of a couple-based intervention using an interpersonal psychotherapy approach in preventing postnatal depression and promoting family sense of coherence and marital relationship among first-time Chinese mothers and fathers; and to explore the possible mediation effects of family sense of coherence on depression reduction in interpersonal therapy.

Methods: This will be a randomised controlled trial. A convenience sample of 472 couples will be recruited at antenatal clinics and randomly assigned to either experimental or control group. The experimental group will receive the intervention in addition to the standard perinatal care, while the control group will only receive the standard perinatal care. The intervention consists of three weekly 2-hour antenatal sessions using an interpersonal psychotherapy approach that focused on enhancement of family sense of coherence and two telephone follow-ups within the first four weeks after delivery. The primary outcome measure of postnatal depression will be assessed by the Edinburgh Postnatal Depression Scale. Secondary outcome measures of family sense of coherence and the marital relationship, will be assessed by the Family Sense of Coherence Scale and Dyadic Adjustment, respectively, at baseline, immediately post- intervention, 6 weeks and 6 months postpartum.

Data analysis: Linear mixed models will be used to test for significant differences between the groups on outcome variables. The classical 3-step algorithm will be used to test if family sense of coherence has a mediating effect between the intervention and postnatal depression. Significance: This study will contribute to both the theoretical development and the clinical applications of interpersonal psychotherapy and family sense of coherence for the prevention of postnatal depression in the context of Chinese parenthood. The results may help to improve perinatal services and reduce healthcare costs for the treatment of postnatal depression in the light of fiscal limitations in the contemporary healthcare system.

A longitudinal investigation of migraine features and cardiovascular risk profile: initiatives for establishing a cohort of general Hong Kong Chinese women

Investigators Name:
PI: Dr Yaojie XIE

Funding Scheme/ Source of Funding: RGC Early Career Scheme

Total Grant: HK $913,705

Commencement Date: 1-Jan-19

Epidemiologic studies have shown that migraine, particularly migraine with aura, was significantly associated with various cardiovascular diseases (CVDs). The migraine features (subtype, duration, frequency, and intensity), however, have not been well examined in those previous studies due to the difficulty in recording the episodic headache attacks. These migraine features are relevant for locating the subgroup of migraineurs who have the highest CVD risk, which may enable treatment to be targeted at those most likely to benefit. A few studies have found an unfavorable cardiovascular risk profile among migraineurs. Understanding the CVD risk factors associated with migraine features may not only help to further substantiate the link between migraine and CVD but also aid in the identification of high-risk individuals for early intervention.

We plan to establish a cohort of women living in Hong Kong for longitudinal evaluation of migraine features in relation to cardiovascular risk profile. Our primary objectives are: 1) To characterize the migraine features and cardiovascular risk profile in a cohort of Hong Kong Chinese women; 2) To determine whether migraineurs have unfavorable cardiovascular risk profile; 3) To investigate which CVD risk factors predict certain migraine features; 4) To examine the relationship between migraine and predicted risk of developing CVD; and 5) To test whether migraine features make any difference to the progression of cardiovascular risk.

Four thousand Chinese women aged ≥30 years and are free of existing CVD will be enrolled at the collaborating clinics that provide medical services to a large number of women. Data will be collected through face-to-face interview, physical examinations and laboratory tests, and medical record review and data extraction. At baseline, participants will be screened by the ID MigraineTM embedded in the questionnaire, and probable migraineurs will be confirmed using clinical diagnostic criteria. Confirmed migraineurs are asked to document their migraine features in a migraine diary. Two years follow-up will be carried out. The primary outcome is the estimated risk of developing CVD, which is evaluated by the calibrated Framingham 10-Year General Cardiovascular Risk Score. Secondary outcomes are the distribution of modifiable CVD risk factors from baseline to the end of the follow-up period, including body mass index, waist circumference, blood pressure, blood lipids, smoking, alcohol consumption, physical activity, diabetes mellitus, and dyslipidemia; as well as the stress and health related quality of life. Multiple linear mix model will be used to examine the associations between migraine features and cardiovascular risk profile.

Intelligent Dementia Risk Prediction System with Community Health Profile of Elderly

Investigators Name:
PI: Dr Kup Sze CHOI
Co-I: Dr Yiu Cho KWAN, Dr Jing QIN, Dr Guanjin WANG

Funding Scheme/ Source of Funding: ITF-MRP

Total Grant: HK$3,607,120

Commencement Date: 1-Jan-19

The demand of primary healthcare for community-dwelling elderly is on the rise as population ages. In this regard, comprehensive electronic records of elder's community health profile can facilitate health care services and management. Furthermore, the community health data can be used for big data analytics, providing predictive intelligence for early intervention of health issues or decision support in care planning. In this project, we propose the community-oriented intelligent Dementia Risk Prediction System (iDRPS) based on elderly community health profile. The system consists of two components. First, a community-oriented intelligent information system called c-IntelleHIS will be developed, catering for the management of elderly-care-specific health assessment data collected in the community by non-governmental organizations (NGOs) offering elderly care services. More importantly, we target at a challenging issue of population ageing – dementia, where the big data in the c-IntelleHIS will be used to predict the risk of dementia by using artificial intelligence (AI). A battery of intelligent algorithms called Learn2Health will be developed using novel machine learning and transfer learning technologies to construct the risk prediction model. The innovative iDRPS can significantly enhance the productivity and quality of community elderly care services, enabling timely intervention of dementia whilst reducing medical burden.

Effectiveness of a Novel Self-disinfecting Coating for Inactivation of Healthcare-associated Pathogens and Environmental Decontamination in the Healthcare Setting

Investigators Name:
PI: Dr Margaret May O'DONOGHUE
Co-I: Dr. Christopher LAI, Dr Kit Hang SIU, Dr Kwai Ping Lorna SUEN, Dr. Dominic NC TSANG

Funding Scheme/ Source of Funding: Ecolab Healthcare ANZ

Total Grant: HK $177,608

Commencement Date: 14-Aug-18

Background: Environmental contamination in the healthcare setting plays a key role in continuing the cycle of healthcare-associated infections (HA Is). Many pathogens can survive on hospital surfaces for days to >1 year and spores of Clostridium difficile can survive for > 5 months. We are currently experiencing a global antimicrobial resistance crisis. This has led to increased focus on novel technologies to improve infection control for prevention of HAI and relieve the pressure on antibiotics for treatment of such infections. Cleaning and disinfection of hospital environmental surfaces is often inadequate for many reasons including poor training of cleaning staff, rapid turnover of staff and overcrowding of hospitals. One novel solution is to use a self-disinfecting surface with prolonged antimicrobial activity. We aim to evaluate the effectiveness of one such product, AA 24/7, which contains a quaternary ammonium compound and alcohol as antimicrobial agents and claims to have antimicrobial activity for 24 hours in high- touch sites and up to seven days in areas with low traffic when coated on environmental surfaces. Methods: The study will consist of two parts: Stage I laboratory in vitro studies will investigate the antimicrobial activity of AA 24/7 against a range of pathogens (gram positive and gram negative), and C. difficile spores on different surfaces (Formica, stainless steel, glass). Preliminary studies will investigate inhibition of S. aureus on Formica in the absence of organic material (a); and in its presence (5% fetal calf serum) (b); over a seven-day period with and without additional re-challenge of organisms (107). The process will be repeated for other pathogens. The potential for residues of the product to induce biocide resistance in 5. aureus strains positive for biocide resistance genes and multidrug resistant strains of Pseudomonas aeruginosa and Acinetobacter baumanii will be investigated over an 18-day period by determining MICs for chlorhexidine and benzalkonium chloride. Total bacterial counts (TBC) will be determined for all investigations and compared over time as well as with control surfaces. Stage II will be a field trial to evaluate effectiveness of AA 24/7 for continual decontamination of high-touch sites in six hospital isolation rooms in a local district hospital over a four-week period. Changes in TBCs and M ICs will be determined and statistically analyzed. A P value of <0.05 will be considered as statistically significant. Significance: An effective self-disinfecting surface could significantly reduce the microbial load on environmental surfaces and potentially decrease the incidence of healthcare-associated infections towards zero. This will be a preliminary study and if the results are promising could lead to larger clinical studies to determine the effect if any on incidence of HAIs.0.05

SurViTK: Development of a Software Toolkit for Automated Surgical Video Analysis via Advanced Recurrent Neural Networks

Investigators Name:
PI: Dr Jing QIN
Co-I: Dr Kup Sze CHOI, Dr. Jingjing HU, Dr. Liping LIU, Prof. Jeremy Yuen-Chun TEOH

Funding Scheme/ Source of Funding: ITF - ITSP - Tier 3

Total Grant: HK $1,854,956

Commencement Date: 1-Jul-18

Surgical video analysis is an essential tool for surgical skill evaluation and education, surgical workflow optimization and complication awareness, and the development of surgical robotics. Traditional manual analysis is tedious, time-consuming and error-prone. Automated analysis approaches are highly demanded with the progress and popularity of minimal invasive surgery and the unprecedented growth in the volume of surgical videos nowadays. Unfortunately, existing algorithms and tools for natural video analysis are incapable of fulfilling the requirements of surgical video analysis due to many distinctive characteristics and challenges of surgical videos. In this project, we aim at developing a series of novel deep learning techniques tailored for automated surgical video analysis tasks, including workflow recognition, indexing, surgical tool detection, key frame summarization and editing, and critical events detection and recognition. The main novel models include a deep recurrent convolutional network for surgical workflow recognition and indexing, a two-layer deep recurrent model of visual attention for surgical tool detection, a deep bi-directional adversarial recurrent neural network for surgical summarization and a semantical spatial-temporal pooling scheme for error and “near miss” event detection. We shall also systematically integrate these models into a modularized software toolkit to facilitate users to flexibly harness these models to carry out various analysis tasks. We believe, not only can the toolkit help surgeons to enhance their surgical skills and improve the postoperative outcomes, but it also has great potential to promote many strategic and/or emerging industries in Hong Kong, including computer-assisted surgery, surgical robotics and intelligent operation room.

Computer-Assisted Precise Partial Nephrectomy Using Advanced Deep Learning, Visualization, and Physically-Based Modeling Techniques

Investigators Name:
PI: Dr Jing QIN
Co-I: Dr Kup Sze CHOI, Mr Hon-Ming WONG, Prof. Pheng-Ann HENG, Prof. Yuen Chun Jeremy TEOH

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $550,000

Commencement Date: 1-Jan-18

Recent advances in medical imaging and surgery technology have made minimally invasive partial nephrectomy (PN) an attractive alternative to radical nephrectomy (RN) for a large number of patients. Evidence has demonstrated that PN can significantly decrease chronic kidney diseases and cardiovascular events compared with RN, especially for patients with small renal tumors. However, nowadays it is still quite difficult for surgeons to precisely excise the tumor with a thin negative margin and meanwhile avoid warm ischemia in the complicated surgical environment, which are two critical factors for the success of a PN. In this project, we aim at developing a set of innovative technologies that facilitate the precise planning and intraoperative guidance of minimally invasive PN in order to greatly improve both oncological and functional outcomes of PN.

Although several PN planning systems have been developed, they are incapable of making the precise planning of many advanced yet challenging PN strategies, such as selective clamping of segmental arteries, super-selective clamping of tumor-specific artery branches, and zero-ischemia PN without clamping. These techniques require surgeons to thoroughly grasp the complex surgical anatomy, identify the location and vascularity of the tumor, and recognize the optimal surgical path, which are all laborious and painful tasks using existing tools. To meet these challenges, we shall first propose a novel deep convolutional neural network (DCNN) equipped with probabilistic graphics models and skip connections to precisely delineate the kidney parenchyma and the tumor, which facilitates to exactly identify the tumor-parenchyma interface for precise excision. Then, we shall propose a new multi-level and fine-grained recurrent neural network (RNN) to segment renal vasculature from bi- or tri-phasic 3D CT Images. Based on the segmented results, we shall build a 3D surgical anatomy environment by developing depth- and shape-aware visualization models to clearly exhibit the complicated surgical anatomy for precise planning of advanced PN strategies. We shall also develop a novel interactive physically-based model for the alignment of preoperative data with intraoperative data for accurate and interactive intraoperative guidance, and hence help surgeons exactly track the kidney, the margin of the tumor and the critical anatomical landmarks during the surgery. In summary, this is a joint project with a strong interdisciplinary team including experts in medical image processing, virtual reality, visualization, urological oncology and minimally invasive kidney surgery. The proposed techniques are anticipated to strengthen PN planning and operation, as well as advance the research on computerassisted minimally invasive surgery.

Development of an Interactive Planning and Prediction System for Patient-Specific Precise Shock Wave Lithotripsy via Advanced Deep Learning and Physically-based Modeling Techniques

Investigators Name:
PI: Dr Jing QIN
Co-I: Dr Kup Sze CHOI, Dr Tin Cheung YING, Prof. Chi-Fai NG, Prof. Yuen-Chun Jeremy TEOH

Funding Scheme/ Source of Funding: ITF - ITSP - Tier 3

Total Grant: HK $1,718,198

Commencement Date: 1-Jan-18

While extracorporeal shock wave lithotripsy (SWL) has been widely used in the treatment of kidney stones, its success (or stone-free) rate is still not satisfactory in clinical practice. In addition, if the treatment is not well planned, it may severely damage surrounding normal kidney tissues. However, patient-specific precise planning and prediction of SWL is still quite challenging as the shock wave passes through various body tissues with different biomechanical properties to reach and fragment the stones. In this project, we aim at developing a novel and interactive planning and prediction system for patient-specific precise shock wave lithotripsy by leveraging a set of advanced deep learning and physically-based modeling techniques. First, we shall develop a deep convolutional neural network (ConvNet) with multi-scale short connections and contour supervision mechanism to automatically segment the kidney for 3D CT scans and a deep recurrent neural network (RNN) to automatically segment the muscle and skin layers from 3D CT scans. We shall then integrate the patient-specific biomechanical parameters acquired from elastography into the segmented results to construct the biomechanical models. Second, we shall develop a finite element model to simulate cavitation phenomenon and pressure field of shock waves. Third, we shall combine these patient-specific biomechanical models and shock wave model to developed an interactive system for precise planning and prediction of SWL. The techniques developed in this project are general enough to be used in planning and prediction of other medical procedures involving ultrasonic waves.

Healthy Families Healthy Minds

Investigators Name:
PI: Dr Chung Lim Vico CHIANG
Co-I: Dr Wing Ka Grace HO, Dr Yim Wah MAK, Mr Kwok Kai Benson CHAN, Ms Sin Yee Petsy CHOW, Ms Siu Ling Ivy LEUNG, Prof. Jean Tak Alice LOKE YUEN

Funding Scheme/ Source of Funding: Health Care and Promotion Fund

Total Grant: HK $267,000

Commencement Date: 1-May-17

Parents need to have knowledge and awareness of the mental health of their children in addition to their learning at school. The need for mental health promotion in the family with children is clear and it is essential to take actions at early childhood. This project is to promote family mental health through workshops that enhance mental health knowledge/awareness of parents, and a family mental health promotion video competition for parents with their children as a team among the participating primary schools. The goal is to promote family mental health by strategically targeting parents’ mental health knowledge/awareness and self-efficacy, and activities with children in the family. Evaluation of the participating families will be conducted by comparing indicators at baseline (T0) and half a month after the workshop (T1), two months after entry to the videos competition (T2), and two months (T3) after the awards presentation ceremony is completed.

High-fidelity and Real-time 3D/4D Ultrasound Visualization System via Advanced Image Denoising and Volume Rendering

 

Investigators Name:
PI: Dr Jing QIN
Co-I: Dr Alex P. W. LEE, Dr Kup Sze CHOI

Funding Scheme/ Source of Funding: ITF - ITSP - Tier 3

Total Grant: HK $1,917,782

Commencement Date: 1-Mar-17

Last decade has witnessed significant advances in 3D/4D Ultrasound imaging technology. Compared with 2D ultrasound, 3D/4D Ultrasound can provide more anatomical and pathological information for more precise diagnosis and treatment. However, nowadays, it is still quite challenging to visualize 3D/4D ultrasound data offering high-fidelity anatomical information in a real-time manner due to speckle noise, low signal-to-noise ratio and the complicated anatomical relationship among tissues. Existing visualization systems are incompetent at anatomical feature-aware visualization for precise diagnosis and treatment. We propose to develop a novel 3D/4D ultrasound visualization system by leveraging a set of advanced image denoising algorithms and volume rendering techniques. First, we shall develop a new 3D denoising algorithm exploiting both the non-local self-similarity and phase information to effectively remove the speckle noise while preserving anatomical features in ultrasound data. Second, we shall propose a novel automated transfer function (TF) design scheme based on the affinity propagation (AP) clustering algorithm to differentiate the voxels belonging to different tissues so that the generated TF can assign different optical properties to them. Third, we shall propose a perception enhanced global illumination model for detail enhancement visualization based on volumetric photon mapping. We shall integrate these techniques as a modularized visualization system and develop two showcases for high-dimensional fetal and cardiac ultrasound data. The proposed system can greatly enhance the international competitiveness of current ultrasound devices produced in Hong Kong, mainland and southeast Asia, and hence has great commercial potential.

Virtual BCI-Based Rehabilitation Leveraging Haptics and Harnessing Insights from Healthy People Using Transfer Learning

 

Investigators Name:
PI: Dr Kup Sze CHOI
Co-I: Dr Zhaohong DENG, Mr King Hung LO

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $321,737

Commencement Date: 1-Jan-17

Brain computer interface (BCI) provides an opportunity for paralyzed people to interact with the world. Through BCI, control of external objects, e.g. speller or wheelchair, can be achieved using electrical brainwave signals by electroencephalography (EEG). Despite major progress in recent years, practical use of BCI remains a challenge. While most BCI systems rely on visual and audio feedbacks, the sense of touch that patients may still preserve is not fully exploited. On the other hand, the performance of BCI depends on the accuracy of EEG signal classification algorithms. It requires a large amount of data which are not readily available from disabled patients due to the lengthy acquisition process and ethical concerns. The project aims to tackle these two issues. First, the role of the sense of touch, i.e. haptic feedback, in BCI will be investigated. In the regard, the brain connectivity corresponding to haptic tasks and the psychophysics will be analysed. The features of haptic-associated EEG signals will be studied using time-frequency analysis to reduce the dimensionality and complexity of machine learning. Next, novel transfer learning algorithms will be developed to recognise the intentions of disabled subjects – even few EEG data can only be acquired from them – by harnessing the knowledge from the data of the healthy subjects. Advanced algorithms based on support vector machines and fuzzy logic systems are thus proposed. These novel algorithms will be implemented and evaluated in virtual reality based rehabilitation environments specifically designed for wheelchair control and handwriting training, where multi-sensory feedback involving haptic, audio and visual feedback are provided interactively. The BCI performance and the effectiveness of the virtual training of the system will be studied.

Effects of Indoor Environmental Factors on Influenza Like Illness in the Older Population of Hong Kong

Investigators Name:
PI: Dr Lin YANG

Funding Scheme/ Source of Funding: RGC Early Career Scheme

Total Grant: HK $814,662

Commencement Date: 1-Oct-16

Background: Influenza virus shows a clear winter peak in temperate regions, but its seasonality is less clear in subtropical/tropical regions where viruses can be isolated throughout the year. This seasonal pattern could not be fully explained by the findings of experimental studies that cold temperature and low relative humidity facilitate the survival and transmission of influenza viruses in environment. Based on the previous studies by others and our recent studies, we hypothesize that indoor environmental factors (temperature and relative/absolute humidity), together with outdoor environmental factors, could affect the risk of influenza infections in the older population. Objectives: 1) To estimate the independent effects of indoor environment factors on selfreport influenza-like symptoms, outpatient visits and hospitalizations of acute respiratory diseases in the community dwelling elderly in Hong Kong; 2) To investigate the seasonal pattern of exposed indoor environment (including temperature and humidity) in older people and assess the relationship of indoor and outdoor environmental factors; 3) To develop a simulation model for influenza virus activity during 2004-2015, by incorporating observed outdoor meteorological data and extrapolated indoor environment factors. Methodology: A cohort of elderly participants who are 65 years or over and dwelling in the community will be recruited from four districts of Hong Kong Island (HKI). Digital data loggers will be installed in the residential homes of recruited participants and the elderly centers they often visit, to continuously collect daily data of indoor temperature and relative humidity. Self-report episodes of acute respiratory symptoms and average daily hours staying indoors and outdoors will be recorded. The case-crossover design with conditional logistic regression models will be applied to estimate the effects of different indoor environmental parameters on the risk of self-report influenza like symptoms, outpatient visits and hospitalization of acute respiratory diseases, respectively.

The susceptible-infected-recovered (SIR) model will be adopted to simulate the daily incidence data of laboratory confirmed cases in the elderly population of HKI during 2004-2015, by incorporating outdoor meteorological data and indoor environment factors extrapolated from this proposed study. Implications: Our study will be the first to comprehensively assess the impacts of indoor environments on influenza like illness in a subtropical city. The findings will provide key evidence to elucidate the mechanism of influenza transmission, which will help refine the control measures in warm climates. The relationship between outdoor and indoor environmental factors could also be used to extrapolate the individual indoor exposure data in future environmental studies.

A Longitudinal Cohort Study On Physical And Mental Health Of Hidden Youths And Adults Living With Hikikomori (Hermetic) Lifestyle

Investigators Name:
PI: Dr Wai Man YUEN
Co-I: Dr Wai San Wilson TAM, Ms Ka Wing SO, Prof. Wai Tong CHIEN, Prof. Cheong Wing Victor WONG

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $950,834

Commencement Date: 15-Aug-16

Purpose: To investigate the changes of physical and mental well-being of youths and adults experiencing distorted lifestyle and social behaviours of hikikomori.

Hypothesis: 1)Hikikomoris’ physical and mental health will be significantly associated with their lifestyle patterns, social well-being, and socio-demographic characteristics. 2) Hikikomoris’ social and lifestyle distortions can predict their physical and mental health conditions over 12 months follow-up, mediated by their socio-demographic characteristics.

Design: A longitudinal cohort study design with three measurements at recruitment (baseline), 6 months and 12 months follow-up. Participants: A total of 287 hikikomori cases (18-34 year-old) will be interviewed face-to-face by using a structured questionnaire and physical assessment.

Measures: After screening for elibility (particularly hikikomori status and SCID assessment), a set of questionnaires will be administered to the participants, consisting of three sections: 1) socio-demographic data, 2) Dependent variables to measure perceived stress, depression, anxiety, and physical functioning, and 3) Independent variables to measure sleep habits, dietary habits, physical exercise, social support, and family relationships. Another dependent variable, physical health, will be assessed in terms of vital signs and body size.

Data analysis: All dependent and independent variables are compared between subgroups in terms of socio-demographic variables (e.g. age) by using independent t-test or analysis of variance. Generalized Estimating Equation and Structural Modelling technique will be used to examine the longitudinal changes of variables and their relationships, respectively.

Raising Awareness Of Disaster Risk And Personal Protection Among Teenagers In Hong Kong

Investigators Name:
PI: Dr Wai Man Olivia FUNG
Co-I: Ms Lai King YIP, Prof. Jean Tak Alice LOKE YUEN

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $99,399

Commencement Date: 1-Jun-16

Purpose: To evaluate the effectiveness of raising awareness of disaster risk and personal protection among teenagers by implementation of an ‘Increasing Disaster Awareness’ (IDA) program. Design: A mixed-method design is adopted to measure and compare the changes in teenagers’ awareness of disasters risks, the knowledge and skills of personal protection in potential hazards. Participants and Setting: The participants are students in two co-educational secondary schools. In order to reduce differences due to age, only first-year secondary students will be selected as samples in this pilot study. Interventions: The IDA program will be conducted before the school summer holiday when students have completed the syllabus and examinations for the school year. This program includes board games and education talks to raise students’ awareness of disaster risks such as stampede, fire and infectious disease outbreak which are regarded as potential risks in Hong Kong. A simulation-based session provides a chance for student to practice the important survival skills followed by a debriefing to consolidate the safety actions. The control group will recieve a list of websites for disasters knowledge and protection actions. Outcomes measures: Participating student’s awareness of disasters risks, their knowledge, skills and attitude towards personal protection will be measured by questionnaire before, three days after and three months after the program. Focus group interview to collect students’ feedback will be conducted. Results: Students’ disaster awareness, personal protection knowledge and attitude will be increased significantly after attending the program than the control group.

Evaluation of the Efficacy of a Simplified 5-Step Hand Washing Intervention Program Versus the Conventional Hand Washing (7-Step) Program for Students with Mild Grade Intellectual Disability: A Clustered Randomized Controlled Non-inferior Trial

Investigators Name:
PI: Dr Regina Lai Tong LEE
Co-I: Prof. Man Cynthia LEUNG, Dr Ka Yeung CHENG, Dr Hong CHEN, Dr Hong LEE

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $668,688

Commencement Date: 1-Jan-16

Background: Hand washing has been proven effective in reducing the spread of infectious diseases (1,2). However, evidence of the effectiveness of hand hygiene interventions in preventing infectious diseases among schoolchildren in Hong Kong is limited, especially with regard to schoolchildren with intellectual disability (ID). This is due to sensory impairment, mental retardation, social and emotional disturbance, and environmental influences (e.g. cultural differences or insufficient / inappropriate instruction) (3). Accompanying weaknesses may be identified in areas of speed of processing, working memory, phonological recoding, fine-grained auditory and/or visual processing, sequencing, organization, and motor coordination (4). All of these symptoms can make it difficult to teach simple hygiene lessons like hand washing. Schoolchildren who have developmental disabilities cannot follow complicated steps for life skills such as hand washing, but they should be given opportunities to develop skills that will prepare them to be productive community members (5). Thus, the current standardized 7-step hand washing procedure used for the general population may not be appropriate for schoolchildren with ID, as they require extra guidance and more detailed instructions for picking up basic life skills such as brushing their teeth and complicated hand washing procedure. The findings on a simplified 5-step hand hygiene program piloted in 2013 among this target group showed it to be acceptable, suitable and sustainable (6,7).

Aim: To evaluate whether the efficacy, acceptability and sustainability of a simplified hand washing program is non-inferior to the conventional 7-step hand hygiene program for students with mild intellectual disability (MID).

Design and subjects: The study will be a clustered randomized controlled non-inferior trial using repeated measures design with pre- and post-tests and follow-up measures. We will recruit 480 students aged 6-15 with MID (IQ score 50-69) from 6 MID special schools in Kowloon and the New Territories (There are only 14 MID special schools in these two areas). An equal proportion of students from each school (n=80) will be randomized to two parallel intervention arms clustered by class level. The first intervention arm will receive an 8-week simplified 5-step hand washing program, including elements of demonstration and return demonstration, a song and a video, posters, a reward system and checklists. The second intervention arm, as the active control, will receive a similar 8-week conventional 7-step hand washing program using standard education materials from the Centre for Health Protection, HKSAR. The study will be conducted in four phases: program preparation, implementation, evaluation, and long-term impact assessment after 2 years.

Main outcome measures: Hand cleaning efficacy will be evaluated by the change in fluorescent stain rating before and after the hand washing, at pre-and post-intervention time points among the intervention and control groups. Absenteeism rates will be analyzed to evaluate the effect of hand washing programs in reducing sickness-related school absenteeism. Program sustainability will be evaluated 6 months after the intervention by the level of taught hand washing procedures recalled by the subjects, and by a fluorescent stain rating test. A focus group analysis will be conducted to compare and evaluate the acceptability and logistics involved in implementing the two different hand washing programs.

Potential implications: The results will provide evidence for formulating a standardized hand hygiene program that is suitable for schoolchildren with mild intellectual disability. It will also provide evidence to optimize the resources and procedures for implementing hand hygiene programs in special school settings. The results will encourage the development of further public health intervention programs for other vulnerable groups, especially for schoolchildren with special needs.

Experience of post-discharge community life of patients with mental illness from the Integrated Community Centre for Mental Wellness (ICCMW): A qualitative exploration

Investigators Name:
PI: Dr Chung Lim Vico CHIANG
Co-I: Prof. Wai Tong CHIEN, Mr Siu Ling Ivy LEUNG, Mr Ming Chi WAN, Ms Yuen Ha Sally CHEUNG

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $79,920

Commencement Date: 18-May-15

Objective: To explore, from the perspectives of patients and staff, patient’s experience in quality of community life within three months after discharge from the Integrated Community Centre for Mental Wellness (ICCMW); and to study patient’s perceptions about the care and service they received from ICCMW.

Design: Qualitative approach by interpretive description using individual open-ended and semi-structured interviews for data collection.

Setting: Community (interviews to be conducted in an ICCMW). Participants: Estimated 25 adult mental health patients discharged from an ICCMW and all 10 staff members of the related ICCMW.

Results and Significance: This qualitative study can contribute to better and deeper understanding of the life of patients in community after ICCMW. In addition to the current outcome-based and empirical studies, the findings will also generate new and more comprehensive knowledge, and provide better insights and clearer directions of service improvement and patient-centered care from the patient’s and staff’s perspectives.

Individual, Acceptance and Commitment Therapy in smoking cessation for people with schizophrenia: A randomized control trial

Investigators Name:
PI: Dr Yim Wah MAK
Co-I: Prof. Jean Tak Alice LOKE YUEN

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $1,095,000

Commencement Date: 1-Jan-15

Background: Amongst people with mental disorders, the prevalence of smoking has been reported to be the highest among people with schizophrenia, ranging from 54%-90%. It is more than two to three times (20%-30%) of the general population. The cooccurrence of schizophrenia and smoking will lead to a higher chance of smokingrelated diseases such as cardiovascular disease, liver diseases and reduced life expectancy. Currently, there is a large gap in knowledge regarding smoking cessation in people with schizophrenia; there has been few studies examining non-pharmacological interventions in smoking cessation on people with schizophrenia. Acceptance and commitment therapy (ACT) for mental health disorders has found that it has in general positive outcomes for the clients; improvements were consistently found in a number of studies. ACT is more encouraging compared to traditional methods of smoking cessation, where the individual is seen to be at fault for the habit. To date, no randomized trial has been conducted to compare the effects of ACT in smoking cessation among people with schizophrenia. Objective: To evaluate the efficacy of Acceptance and Commitment Therapy (ACT) in enhancing smoking cessation among people with schizophrenia living in the community.

Design: This is a randomised controlled trial. Individual, face to face, assessor-blinded with assessments will be conducted before intervention, after intervention, and at the 6th and 12th month after the initial session of ACT intervention. Participants and setting: 156 individuals aged 18 years or older, currently smoking but not undergoing any smoking cessation or similar programme, who were diagnosed with schizophrenia and were referred to 4 community-based mental health rehabilitation settings by medical doctors will be included in this trial. Interventions: Social chats on encouraging medication adherence for 5-10 mins per session, 10 sessions, will be given to subjects allocated to control group (CG), on weekly basis.

Subjects of Intervention Group (IG): will additionally be provided 30-45 mins, individual, face to face ACT by trained ACT interventionists per each session.

Main outcome measures and data analysis: The primary outcome will be the selfreported not smoking for at least 7 days preceding to the assessment at the 6th and 12th month after the pre-intervention assessment. A comparative analysis of the proportion of smokers who quit smoking in either intervention or control groups at the 6 and 12-month follow-up will be performed according to intention-to-treat principles. Subjects: who do not adhere to the study programme (‘lost-to-follow-up’) will be presumed smoking.

Using orthotopic MB49/C57 mice model to delineate the prophylactic activity of Ganoderma lucidum in bladder transitional cell carcinoma

Investigators Name:
PI: Dr Wai Man YUEN
Co-I: Dr Eddie Shu Yin CHAN, Dr Ka Wai Helen LAW, Prof. Mayur Danny Indulal GOHEL, Prof. Chi-fai Anthony NG

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $641,413

Commencement Date: 22-Dec-14

A powerful and toxicity-free chemopreventive agent is demanded and long overdue for treating transitional cell carcinoma of the urinary bladder. In-vitro studies of Ganoderma lucidum, known as Lingzhi in Chinese have demonstrated the growth inhibitory effects on urothelial carcinoma cells, in addition to the cytokines stimulation, neutrophilic cell migration, and telomerase inhibition. The cytotoxic effects of Lingzhi were also shown to be synergistic with the conventional BCG immunotherapy, besides its activities in regulating BCG-mediated cytokines which suggested the potentials in reducing BCGassociated toxicity. Yet, intravesical bladder instillation of Lingzhi has never been testified at animal level, which is a critical step prior to human trials. In this study, an orthotopic mice model will be adopted in order to implant stable luciferase-transfected mouse bladder-49 (MB49Luc) cells into C57BL/6J by electrocautery method. This model mimics the closet clinical conditions for TCC post surgical tumor resection that 1) point disruptive damage caused by electrocautery on urothelial layer imitate trauma caused by surgery, and 2) implanted MB49 cells in the lamina propria and muscle layer represent residual tumor cells. Such properties allow the evaluation of intravesical therapy, Lingzhi in this case, at the early phase of orthotopic tumorigenesis, i.e. before the tumor establishment. Outcome measures include the assessment of tumor incidence, tumor size and characteristics, apoptosis, localized immune status and inflammatory response, urothelial toxicity, together with selected molecular markers such as nuclear matrix protein BLCA-4. Analysis of such parameters enables to assess the effectiveness and safety and to possibly explore the mechanism of action for using Lingzhi as a prophylactic regimen to treat TCC. Additionally, its drug-drug interactions with BCG strains will also be determined using isobologram analysis and combination index. The proposed project addresses the problem of high recurrence and progression of TCC, provides critical scientific evidence to support the prophylactic roles of Lingzi, with the particular consideration on BCG’s drawbacks.

Effectiveness of school-based weight management program for overweight and obese students with mild intellectual disability in a special school: A randomized controlled trial

Investigators Name:
PI: Dr Regina Lai Tong LEE
Co-I: Dr Jyu-Lin CHEN, Dr Hung-tak Lobo LOUIE, Dr Hong LEE, Mr Gordon Chi Leung CHEUNG, Prof. Man Cynthia LEUNG, Prof. Michael BROWN

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $446,870

Commencement Date: 16-Dec-14

Background: There is a high prevalence of obesity among children with disability and special needs, which is increasingly recognized as an international phenomenon and one that requires active intervention to address. Obesity is a significant health concern for children and adults with disabilities, and many children with disability will grow into obese adults with all the associated chronic health problems, such as diabetes, hypertension and cardiovascular disease. There are as a result significant health and social-related issues for the individual, their family and care services. Interventions to promote physical activity, improve dietary habits and reduce sedentary behaviors have been recommended for weight reduction. While childhood overweight has been the focus of considerable research in recent years, longer-term follow up is needed to confirm the maintenance of treatment effects for all types of interventions. There is clear evidence of the efficacy of interventions to establish health-enhancing behaviors at the individual level to reduce health-risk behaviors such as obesity and the wider associated health complications. Yet these behavior changes are frequently difficult to maintain, especially for children with intellectual disability, which poses an important challenge in the planning of a weight loss maintenance program in this population. The limited maintenance of behavioral change seen in initial intervention efforts may be due to the failure to take account of how social contextual factors such as collective efficacy that may influence the relationships between self-efficacy and behavior through interaction and observation learning (modeling) at the group level. Collective efficacy is a group’s shared belief in its conjoint capabilities to organize and execute the course of action required to produce. Aim: The aim is to implement and evaluate the effectiveness of a school-based weight management program integrated with social factors in collective efficacy of social learning theory in reducing body weight, through changes in the physical activity and nutrition behaviors of overweight and obese students (8-16 years old) with mild intellectual disability in special schools. Management in weight, body fat and wrist-hip ratio should be targeted as the primary outcome measures, and secondary outcome measures: improvement in quality of life, self-esteem, body shape and figure, self-efficacy in peer interactions, exercise and nutrition. Methods: A randomized controlled trial with a repeated measures control design with pre- and post-interventions and follow-up measures at three time points. The two-by-two Solomon Four Group Design will be adopted as it contains two extra control groups. Four special schools will be randomized into an intervention school and three control schools. Thirty-five overweight or obese P.3-F.4 students with intellectual disability who meet the inclusion criteria will be recruited from each special school (140 overweight/obese students). The 8-month school-based weight management program is based on the constructs in the social learning theory through theoretically informed factors: instruction and observation to modify behaviors. The 16-session intervention program involving students and parents consists of a mix of individual, group, and environmental strategies and social factor components. The constructs of social learning theory will be used for outcome measures at the three time points: pre- and post-intervention and follow-up measures of an 8-month school-based weight management program.

Implications: It is hoped that the results will support the hypothesis that an 8-month school-based weight management program involving parents based on collective efficacy of social learning theory is superior to conventional interventions for overweight and obese students with intellectual disability in terms of primary and secondary outcome changes. It is anticipated that students in the intervention school will experience reductions in BMI, body fat percentage, and wrist-hip ratio as primary outcome changes; and improvements in quality of life, self-esteem, perceived body shape and figure rating scale, self-efficacy in peer interactions, physical activity and nutrition as the secondary outcome changes.

Impact of Increased Influenza and Pneumococcal Vaccine Coverage on the Burden of Influenza in the Elderly: A Comparison between Hong Kong and Brisbane

Investigators Name:
PI: Dr Lin YANG
Co-I: Dr Shui-seng Susan CHIU, Dr Hak Kan LAI, Dr Ricardo J. Soares MAGALHAES, Dr Quoc Thuan THACH, Dr Chit Ming WONG, Prof. Archie C. A. CLEMENTS, Prof. Joseph Syrial Malik PEIRIS

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $158,824

Commencement Date: 1-Mar-14

Objectives: Influenza vaccination rates in the Hong Kong elderly dramatically increased after the outbreak of Severe Acute Respiratory Syndrome in 2003. The pneumococcal vaccination rate also greatly increased after the implementation of the Elderly Vaccination Subsidy Scheme in Hong Kong in 2009. By contrast, during the same period, the influenza and pneumococcal vaccination rates constantly remained at a relatively high level among the elderly in Brisbane, Australia.Here we propose a study to compare the long term trends in influenza associated disease burden between Hong Kong and Brisbane from 2001 to 2012, in order to assess the impacts of increased vaccination on the old population of Hong Kong with adjustment for virulence of influenza strains and other confounding factors. Hypothesis to be tested: Hong Kong showed a greater extent of reduction in influenza associated disease burden in the elderly than did Brisbane.

Design and subjects: an ecological study in the old population

Main outcome measures: influenza associated hospitalization and mortality Data analysis: Poisson models will be separately fitted to hospitalization and mortality data of Hong Kong and Brisbane to estimate the mortality or hospitalization risks associated with influenza in the elders during the pre-SARS, post-SARS and post-pandemic period. The magnitude of temporal change in disease burden within and between the cities will be meausred by the risk ratio (RR).

Expected results: A greater decrease in influenza disease burden of Hong Kong elders than that of Brisbane elders would suggest that influenza vaccination could effectively reduce the influenza disease burden.

An Evaluation of a Simplified 5-step Hand Hygiene Intervention Program for Students with Mild Grade Intellectual Disability in a Special School

Investigators Name:
PI: Dr Regina Lai Tong LEE
Co-I: Dr Hong CHEN, Dr Wah Kun TONG, Prof. Man Cynthia LEUNG

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $80,000

Commencement Date: 2-Jan-14

Objective: To develop and evaluate a simplified hand washing program for mild grade intellectually disabled students.

Design: A quasi-experimental study pre and post-tests, nonequivalent-comparison group design with an interventon school and a comparison school.

Setting: Two special schools enrol mildly grade intellectually disabled students located in Mongkok and Kwan Tong Districts in Hong Kong. Participants: Students aged 6-15 with mild grade intellectual disability on a standardized intelligence test (IQ score of 50-69) who are studying in P.1-F.2 in the special schools.

Methods: There are three phases in this study: 1) Program development: a simplified 5-step hand hygiene program with song lyrics and pictures; 2) Program validation; 3) Feasibility testing: implement a simplified hand washing program with pre and post-tests in intervention group. Interventions: A simplified hand hygiene intervention program with song lyrics and pictures using video modeling.

Data analysis: Wilcoxon Signed Rank Tests will be used to examine the difference in the amount of fluorescent stains (rated on a 4-point ordinal scale) in the intervention and comparison groups.

Outcome measure: Comparing the a composite rating of 4-point scale (0,1,2,3) fluorescent stain on both hands of each student in both groups in pre- and post-tests.

Conclusion: It is very important in the public health agenda to standardize a simplified 5-step hand washing program for students with mild grade intellectual disability in order to promote the hand hygiene care in the Hona Kana community.

Evaluation of a Multidimensional Programme for Reducing Work-related Musculoskeletal Disorders among Nursing Assistants in Nursing Homes: A Cluster Randomized Control Trial

Investigators Name:
PI: Dr Kin CHEUNG
Co-I: Dr Siu Yin CHING, Dr Pui Yuk Grace SZETO, Mr Kin Bun Godfrey LAI, Ms Linda LAI

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $930,700

Commencement Date: 1-Jan-14

Background: It is well known that nursing personnel, particularly nursing assistants (NAs), are at risk of workrelated musculoskeletal disorders (WMSDs). Risk factors for WMSDs include physical, psychosocial, personal and organizational, which are consistent with the conceptual framework of contributors to WMSDs developed by the National Research Council (1999). Several systematic reviews have concluded that multidimensional intervention strategies are necessary to address all aspects in the work of nursing personnel that may have contributed to WMSDs. But limited studies have been conducted to develop and evaluate multidimensional training programmes to reduce WMSDs in this vulnerable group. Aims and objectives: (1) to develop and evaluate a multidimensional programme for reducing WMSDs among NAs working in nursing homes; and (2) to test the hypothesis that there are differences between the intervention group and control group in reducing musculoskeletal symptoms (primary outcome) and work stress, and improving perceived rate of exertion, function of different body regions, ergonomics and manual handling knowledge (secondary outcomes). The proposed programme will be developed based on a locally designed programme that has been pilot-tested among community nurses.

Design and methods: A non-blinded cluster randomized control trial will be employed to evaluate the effectiveness of the multidimensional programme in reducing WMSDs. Nursing homes with same risk level for patient handling will be randomly selected into an intervention and a control group. The intervention group will receive the multidimensional programme, which will last for eight weeks and consist of six elements: (1) group training of ergonomics principles, (2) onsite training, (3) exercise training, (4) stress management, (5) use of assistive devices, and (6) improvement of work organization. The control group will practice as usual without receiving the multidimensional programme. Based on the effect size of 0.23 obtained from the pilot study with the coefficient of intracluster correlation of 0.10, the estimated sample size will be 690 in 30 clusters to provide 80% power with α=0.05. The effectiveness of the programme on primary and secondary outcomes will be evaluated by questionnaires after 3 months, 6 months, and one year. The effect of the intervention on outcome measures will be evaluated using mixed effect models with intervention as fixed effect and taking account random variation between NAs in the same cluster and between clusters, after adjusting for cluster and age.

Implications: The effectiveness of the programme improves not only NAs’ WMSDs, but also their occupational health and safety. This multidimensional training can be gradually integrated into all nursing homes’ on-the-job training programmes.

The Effect of A Father Inclusive Psychoeducation Program On Postnatal Depression: A Randomized Controlled trial

Investigators Name:
PI: Dr Fei Wan NGAI

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $547,834

Commencement Date: 1-Jan-14

Background: Having a first child is a key marker of the transition into parenthood that requires substantial adjustment of couples’ life. A recent meta-analysis published in the Journal of American Medical Association reports that both women (23.8%) and men (10.4%) suffer from perinatal depression [1]. The father’s involvement during pregnancy can positively influence health outcomes not only for the man, but his partner, and their children [1,2]. However, the effectiveness of father’s involvement in prenatal care in preventing paternal and maternal depression, is still unknown.

Aims: This study seeks to: (1) evaluate the effect of a father inclusive psychoeducation program for first-time Chinese mothers and fathers on depressive symptoms (primary outcome), marital relationships and quality of life at 6 weeks, 6 months and one year postpartum; and (2) explore fathers’ involvement, their perceived benefits of participating in the program and factors influencing the effectiveness of the program.

Methods: This study employs a longitudinal, randomized, pre and post-test design. A convenience sample of 576 couples will be recruited at antenatal clinics and randomly assigned to one of three groups: (1) the experimental group with both couples receives the intervention on top of usual perinatal care; (2) the comparison group with only the women receives the intervention on top of usual perinatal care; and (3) the control group receives usual perinatal care only. The intervention consists of a single 3-hour session during pregnancy and two telephone follow-up at postpartum week one and week two. Primary outcome on postnatal depression will be assessed by Edinburgh Postnatal Depression Scale. Secondary outcomes on marital relationship and quality of life will be assessed by Dyadic Adjustment Scale and Medical Outcomes Study Short Form 12-item Health Survey, respectively, at baseline, 6 weeks, 6 months and one year postpartum. Process evaluation will be conducted at 6 weeks postpartum using individual telephone interview on 20 couples randomly selected from the experimental group.

Data analysis: A repeated-measures multivariate analysis of variance will be used to test for significant differences among three groups on outcome variables. Interview data will be analyzed by content analysis. Significance: The knowledge gained from this study can provide the direction for developing flexible, accessible and culturally sensitive care to enhance both maternal and paternal well-being in Chinese society. The results may be utilized to improve perinatal services and reduce healthcare costs on the treatment of postnatal depression in light of fiscal limitations in contemporary healthcare system.

The Experience and Coping of Co-occurrence of Schizophrenia and/or Depression with Smoking: a Qualitative Study

Investigators Name:
PI: Dr Yim Wah MAK
Co-I: Dr Chung Lim Vico CHIANG, Prof. Jean Tak Alice LOKE YUEN

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $80,000

Commencement Date: 1-Apr-13

Purposes: To explore the experience and coping of co-occurrence of mental health disorders and substance use among adolescents.The specific objectives are (1) to describe the experiences of the co-occurrence of mental health disorders and substance use; (2) to explore the impacts of those co-occurring disorders; and (3) to explore and describe how the adolescents cope with the disorders. Setting: Half-way house, hostel and integrated vocational rehabilitation centres of Christian Family Services Center at Chai Wan, Kwun Tong or Tseng Kwan 0, Hong Kong.

Design and subjects: This proposal is a qualitative descriptive study with face-to-face, individual and semi-structured interviews. Purposive sampling will be adopted in this study. The inclusion criteria of the respondents are, 1) in the age of 12-24 years, 2) with diagnosis of mental illness who are referred to the centres by medical doctors (such as diagnosis of schizophrenia, schizoaffective disorder or other diagnosis of psychosis), 3) currently or previously using tobacco, alcohol and/or drug, and 4) express interests in taking part in an individual interview. Exclusion criteria include disorientation, developmental disabilities, organic conditions.

Main outcome measures: Respondents' experiences in managing co-occurrence of mental health disorders and substance use.

Nurse's Participation on Smoking Cessation: A National Survey

Investigators Name:
PI: Dr Yim Wah MAK
Co-I: Ms Susie LUM, Prof. Jean Tak Alice LOKE YUEN, Prof. Alexandros MOLASIOTIS, Prof. Kam Yuet WONG

Funding Scheme/ Source of Funding: The Provisional Hong Kong Academy of Nursing Limited

Total Grant: HK $245,170

Commencement Date: 1-Apr-13

Previous studies have shown that nursing interventions are effective in helping people to stop smoking, but that the participation of nurses in tobacco control activities has been far from satisfactory. The primary objective of this study is to identify factors that encourage or discourage nurses from participating in providing smoking cessation interventions to their clients, based on the 5 A’s (ask, advise, assess, assist, arrange) framework . A cross-sectional survey was conducted among 4,413 nurses in Hong Kong from different clinical specialties. A logistics regression analysis found that predictors for the practicing of all of the 5 A’s are nurses who want to receive training in smoking cessation interventions, those who have received such training, and those who are primarily working in a medical unit or in ambulatory/outpatient settings. The regression model also showed that attitude towards smoking cessation was positively associated with all of the 5 A’s. The results indicate a need to encourage and provide nurses with opportunities to receive training on smoking cessation interventions. Strategies to persuade nurses to provide smoking cessation interventions are also important, since nurses are motivated to perform smoking cessation interventions when they feel a stronger sense of mission to control tobacco use.

Validation of the Chinese Version of the Chronic Illness Resources Survey for Patients with Type 2 Diabetes Mellitus

Investigators Name:
PI: Dr Chum Ming Meyrick CHOW
Co-I: Prof. Wai Tong CHIEN

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $79,830

Commencement Date: 15-Jan-13

Purpose: to examine the reliability and validity of a Chinese version of the Chronic Illness Resources Survey (CIRS-C). Objectives: (1) to assess the content validity 01 the CIRS-C and semantic equivalence between the English and translated Chinese version of the CIRS; (2) to examine the internal consistency, test-retest reliability, criteria-related validity, divergent validity, and factor structure of the CIRS-C; and (3) to conduct a preliminary assessment of the multilevel support and resources in patients with type 2 diabetes mellitus by using the CIRS-C.

Design and Subjects: This study is designed to test the reliability and validity olthe CIRS-C. The CIRS-C will be developed following the translation procedures described by Bracken and Barona. A convenience sample of 110 Chinese-speaking adults with type 2 diabetes will be recruited. They will complete the questionnaires listed below. The CIRS-C will be administered to 30 participants again after a 2-week interval for evaluating its test-retest reliability. Instruments: CIRS-C, SDSCA-C, GHQ-12-C, and demographic questionnaire. Data Analysis: Descriptive statistics will be used to summarize the values of the various study measures. The internal consistency of the CIRS-C will be examined by computing Cronbach's alpha, the stability of the CIRS-C will be established by measuring test-retest reliability using intraclass correlation coefficient. To assess the criterion-related and divergent validities of the CIRS-C, Pearson's product-moment correlation coefficients will be computed to determine its correlations with SDSCA-C and with GHQ-12-C respectively. Confirmatory factor analysis will be conducted to examine the construct validity and confirm the factor structure of CIRS-C.

The Characteristics of Students who Influence their School Peers' Health Risk Behaviors

Investigators Name:
PI: Prof. Jean Tak Alice LOKE YUEN
Co-I: Dr Yim Wah MAK, Dr Sau Ting Cynthia WU

Funding Scheme/ Source of Funding: Health and Medical Research Fund (HMRF)

Total Grant: HK $79,934

Commencement Date: 1-Jan-13

Purpose: This study aims to identify the characteristics of influential peers from their own perspectives and those of their peers. Interviews will solicit an in-depth understanding of the characteristics of influential students and how and why they influence their peers. This information will be useful for developing plans for recruiting students in peer-led health promotion programs in the future.

The specific objectives of this study are to: 1. identify influential students by anonymous ballot among peers, and elicit the reasons for their nomination, 2. identify peers' perceptions of the characteristics of these influential students, 3. explore the peer crowd affiliat+H25:H54ion and health risk behaviors of secondary students, 4. identify the self-reported characteristics of these influential students, and 5. identify the influential students' perceptions of their impact on their peers. Design and subjects: This study will be divided into two phases. The first consists of an anonymous ballot and a cross-sectional questionnaire to be completed by all Form 3 students. The second involves in-depth interviews of nominated influential students. Study instruments: An anonymous ballot of influential peers, with reasons for nomination. A questionnaire will be developed to solicit the students' perceptions of the characteristics of their nominees. Items in the questionnaire will include the Peer Crown Questionnaire (PCQ) and their health risk behaviors. A semi-structured interview guide will also be developed for interviewing the influential students.

Main outcome measures and analysis: Chi-squared tests and t-tests will be performed to identify the characteristics of the influential students, the peer crowd affiliation, and the health risk behaviors of all secondary students. Content analysis will be used to analyse qualitative data from the in-depth interviews regarding the students' characteristics and their impacts.

Flight Simulator in Modern Nursing Education: An Intelligent Training System for Nasogastric Tube Placement

Investigators Name:
PI: Dr Kup Sze CHOI
Co-I: Dr Chung Lim Vico CHIANG, Dr Zhaohong DENG

Funding Scheme/ Source of Funding: General Research Fund

Total Grant: HK $725,000

Commencement Date: 1-Jan-13

Nasogastric tube (NGT) placement is an essential clinical procedure for feeding, drainage or emptying. It involves the insertion of a plastic tube from the nose through the throat to the stomach. Being a non-trivial blind process, NGT insertion has unfortunately resulted in many serious complications and fatal accidents. The techniques are conventionally acquired by practising on humans or mannequins. The former causes discomfort and could be harmful whilst the latter is unrealistic. To improve the procedural techniques and clinical education, an interactive and intelligent training system is proposed for learning NGT insertion in a risk-free and realistic computersimulated environment. Real human anatomy, interactions between NGT and the nasogastric passage, tactile feeling and obstruction during intubation, as well as patient’s response will all be simulated to guarantee high level of realism. The system will also simulate difficult cases. Trainees can then practise in virtual environments as if they were performing intubation on real patients. Furthermore, quantitative metrics will be provided for automated performance evaluation and assessment. An intelligent scoring module will be developed by benchmarking against expert performance to grade the proficiency level of the trainees. The system will be built using lowcost hardware to make it affordable for wider adoption in clinical nursing education. The computerized NGT placement training system has the potential to improve the manual skills and the learning curve by offering more experiential learning opportunities, where trainees are free to self-practise safely as often as needed.

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