Violence among adolescents is a significant public health issue. The focus was on school-going adolescents because of the life-long negative impact at an individual level both for the perpetrator and victim. Besides, it increases the costs to provide health, welfare, and criminal justice as well as decreases general productivity at the community level. The study aims to determine the prevalence of violence-related behavior, characteristics of both victims and perpetrators, in addition to inter and intrapersonal factors associated with violence-related behaviors. A study was carried out in 2013, which involved all upper secondary school students (aged 16 to 17 years). It was a part of the Malaysian Adolescent Health Risk Behavior (MyAHRB) study, which was conducted in 11 states in Peninsular Malaysia. Standardized, validated questionnaires were used for data collection. The prevalence of violence-related behaviors was 22.4%, and this was higher among male students as compared to females (29.1% vs. 16.3%). Multivariable analysis revealed that the odds of violence-related behaviour increased among males, Malay race, drug use, smoking, had exposure to sex, which sometimes and always felt lonely and had attempted suicide. Agreeable to ensure that their lifestyles do not transgress religious limit and belief was significantly protective. This study provides evidence for a targeted approach to combat violence-related behaviors among adolescents.

Introduction: The Family Doctor Concept (FDC) programme was introduced to public primary care clinics in late 2013 as part of the reform agenda in the primary healthcare delivery system. The study aimed to develop a validated and reliable instrument to evaluate the FDC implementation fidelity in primary care clinics. Methods: The instrument, which adapted the concept of patient-centred care (PCC), resulted from a series of expert discussions, a literature search, an FDC guideline, and a review of meeting minutes. A 2-step process was conducted with experts to achieve content and face validity. Consequently, the instrument was piloted in 5 public primary care clinics in Selangor involving 8 trained raters. Inter-rater reliability was estimated using intraclass correlation (ICC), while internal consistency was measured using Kuder–Richardson Formula 20 (KR-20). Results: The final instrument comprises 3 sections (instructions, clinic’s characteristics and assessment items), with Section 3 containing 15 items divided into four components – population registration, formation of a primary care team, integrated treatment, and monitoring and evaluation. The ICC for total score was excellent, 0.981, while the ICCs of the individual component scores were good to excellent (population registration: 0.937, formation of primary care team: 0.742, integrated treatment: 0.996, and monitoring and evaluation: 0.996). The value of KR-20 was 0.615, which was considered adequate. Conclusion The instrument developed was found to be valid in terms of face and content validity and reliable in measuring the fidelity of FDC implementation with excellent inter-rater reliability.
Primary Health Care ; Primary Care Nursing

The application of artificial intelligence (AI) is on the rise in the healthcare industry. However, the study on the physicians’ perspectives is still lacking. The study aimed to examine physicians’ attitudes, expectations, and concerns regarding the application of AI in medicine. A cross-sectional study was conducted in October 2019 among physicians in a tertiary teaching hospital in Malaysia. The survey used a validated questionnaire from the literature, which covered: (1) socio-demographic profile; (2) attitude towards the application of AI; (3) expected application in medicine; and (4) possible risks of using AI. Comparison of the mean score between the groups using a t-test or one-way analysis of variance (ANOVA). A total of 112 physicians participated in the study: 64.3% from the clinical departments; 35.7% from the non-clinical specialties. The physicians from non-clinical departments had significantly higher mean attitude score (mean = 14.94 ± 3.12) compared to the clinical (person-oriented) departments (mean = 14.13 ± 3.10) and clinical (technique-oriented) departments (mean = 13.06 ± 2.88) (p = 0.033). The tech-savvy participants had a significantly higher mean attitude score (mean = 14.72 ± 3.55) than the non–tech-savvy participants (mean = 13.21 ± 2.46) (p = 0.01). There are differences in the expectations among the respondents and some concerns exist especially on the legal aspect of AI application in medicine. Proper training and orientation should precede its implementation and must be appropriate to the physicians’ needs for its utilization and sustainability.