METHODS: Stiffness index (SI) was measured and T-scores generated against an Asian database were recorded for 598,757 women and 173,326 men aged over 21 years old using Lunar Achilles (GE Healthcare) heel scanners. The scanners were made available in public centres in Singapore, Vietnam, Malaysia, Taiwan, Thailand, Indonesia and the Philippines.
RESULTS: The mean SI was higher for men than women. In women SI as well as T-scores declined slowly until approximately 45 years of age, then declined rapidly to reach a mean T-score of 80 years.
CONCLUSIONS: The heel scan data shows a high degree of poor bone health in both men and women in Asian countries, raising concern about the possible increase in fractures with ageing and the expected burden on the public health system.
DESIGN AND METHODS: The activity of DPD was measured using 5-[2- (14)C]Fluorouracil (5-[2-(14)C]FUra) followed by separation of substrate and product 5-[2-(14)C]FUraH(2) with a 15 x 4.6 mm I.D., 5 microm particle size (d(p)) porous graphitic carbon (PGC) column (Hypercarb(R)) and HPLC with online detection of the radioactivity. This was standardized using the protein concentration of the cytosol (NanoOrange(R) Protein Quantitation).
RESULTS: Complete baseline separation of 5-[2-(14)C]Fluorouracil (5-[2-(14)C]FUra) and 5-[2-(14)C]Fluoro-5,6-dihydrouracil (5-[2-(14)C]FUraH(2)) was achieved using a porous graphitic carbon (PGC) column. The detection limit for 5-[2-(14)C]FUraH(2) was 0.4 pmol.
CONCLUSIONS: By using linear gradient separation (0.1% Trifluoroacetic acid [TFA] in water to 100% Methanol) protocols in concert with PGC columns (Hypercarb(R)), we have demonstrated that a PGC column has a distinct advantage over C-18 reverse phase columns in terms of column stability (pH 1-14). This method provides an improvement on the specific assay for DPD enzyme activity. It is rapid, reproducible and sensitive and can be used for routine screening for healthy and cancer patients for partial and profound DPD deficiency before treatment with 5- FUra.
OBJECTIVE: This study aimed to evaluate the utility and usability of ScreenMen.
METHODS: This study used both qualitative and quantitative methods. Healthy men working in a banking institution were recruited to participate in this study. They were purposively sampled according to job position, age, education level, and screening status. Men were asked to use ScreenMen independently while the screen activities were being recorded. Once completed, retrospective think aloud with playback was conducted with men to obtain their feedback. They were asked to answer the System Usability Scale (SUS). Intention to undergo screening pre- and postintervention was also measured. Qualitative data were analyzed using a framework approach followed by thematic analysis. For quantitative data, the mean SUS score was calculated and change in intention to screening was analyzed using McNemar test.
RESULTS: In total, 24 men participated in this study. On the basis of the qualitative data, men found ScreenMen useful as they could learn more about their health risks and screening. They found ScreenMen convenient to use, which might trigger men to undergo screening. In terms of usability, men thought that ScreenMen was user-friendly and easy to understand. The key revision done on utility was the addition of a reminder function, whereas for usability, the revisions done were in terms of attracting and gaining users' trust, improving learnability, and making ScreenMen usable to all types of users. To attract men to use it, ScreenMen was introduced to users in terms of improving health instead of going for screening. Another important revision made was emphasizing the screening tests the users do not need, instead of just informing them about the screening tests they need. A Quick Assessment Mode was also added for users with limited attention span. The quantitative data showed that 8 out of 23 men (35%) planned to attend screening earlier than intended after using the ScreenMen. Furthermore, 4 out of 12 (33%) men who were in the precontemplation stage changed to either contemplation or preparation stage after using ScreenMen with P=.13. In terms of usability, the mean SUS score of 76.4 (SD 7.72) indicated that ScreenMen had good usability.
CONCLUSIONS: This study showed that ScreenMen was acceptable to men in terms of its utility and usability. The preliminary data suggested that ScreenMen might increase men's intention to undergo screening. This paper also presented key lessons learned from the beta testing, which is useful for public health experts and researchers when developing a user-centered mobile Web app.
OBJECTIVE: This systematic review presents current evidence on the barriers and facilitators to engaging men in health screening.
METHODS: We included qualitative, quantitative and mixed-method studies identified through five electronic databases, contact with experts and reference mining. Two researchers selected and appraised the studies independently. Data extraction and synthesis were conducted using the 'best fit' framework synthesis method.
RESULTS: 53 qualitative, 44 quantitative and 6 mixed-method studies were included. Factors influencing health screening uptake in men can be categorized into five domains: individual, social, health system, healthcare professional and screening procedure. The most commonly reported barriers are fear of getting the disease and low risk perception; for facilitators, they are perceived risk and benefits of screening. Male-dominant barriers include heterosexual -self-presentation, avoidance of femininity and lack of time. The partner's role is the most common male-dominant facilitator to screening.
CONCLUSIONS: This systematic review provides a comprehensive overview of barriers and facilitators to health screening in men including the male-dominant factors. The findings are particularly useful for clinicians, researchers and policy makers who are developing interventions and policies to increase screening uptake in men.
METHODS: This nested case-control study was performed by collecting data from 1 January 2015 to 30 June 2017. Univariable and multivariable logistic regressions were used to identify potential risk factors. The regression coefficients were converted into item scores by dividing each regression coefficient with the minimum coefficient in the model and rounding to the nearest integer. This value was then summed to the total score. The prediction power of the model was determined by the area under the receiver operating characteristic curve (AuROC).
RESULTS AND DISCUSSION: Six clinical risk factors, namely age ≥65 years, benzodiazepine use, history of a cerebrovascular accident, dose of hydrochlorothiazide ≥25 mg, female sex and statin use, were included in our ABCDF-S score. The model showed good power of prediction (AuROC 81.53%, 95% confidence interval [CI]: 78%-84%) and good calibration (Hosmer-Lemeshow X2 = 23.20; P = .39). The positive likelihood ratios of hyponatremia in patients with low risk (score ≤ 6) and high risk (score ≥ 8) were 0.26 (95% CI: 0.21-0.32) and 3.89 (95% CI: 3.11-4.86), respectively.
WHAT IS NEW AND CONCLUSION: The screening tool with six risk predictors provided a useful prediction index for thiazide-associated hyponatremia. However, further validation of the tool is warranted prior to its utilization in routine clinical practice.
METHODS: We conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy.
RESULTS: 16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (-0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).
CONCLUSIONS: PHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
METHODS: 11 key informant interviews were conducted with policy makers and health care providers from the Ministry of Health in Malaysia from October 2009 to May 2010. Interviewees' perceptions were explored on current and organized cervical screening program based on their expertise and experience.
RESULTS: The results highlighted that the existing cervical screening program in Malaysia faced flaws at all levels that failed to reduce cervical cancer morbidity and mortality. The identified weaknesses were poor acceptance by women, lack of commitment by health care providers, nature of the program, an improper follow-up system, limited resources and other competing needs. Complementarily, all interviewees perceived an organized cervical screening program as an alternative approach both feasible and acceptable by women and government to practice in Malaysia.
CONCLUSION: Better screening coverage depends on an effective screening program that incorporates a behaviour-based strategy. A new program should be focused in the policy-making context to improve screening coverage and to effectively combat cervical cancer.
METHODS: The following electronic resources were searched: Medline @EBSCOHOST(Medline), Embase, PubMed, and CINAHL databases. Manual searches were also conducted. The main outcome of interest was the acceptability of HPV DNA testing by self-sampling in comparison with clinician-collected sampling.
RESULTS: In total, 23 articles were included in this systematic review. The majority (19 studies) were quantitative intervention studies and 4 studies were qualitative observational studies. Eleven studies reported a preference for self-sampling by women compared with clinician-collected sampling (64.7%-93%). The remaining studies found that women preferred clinician-collected sampling because mainly of respondents' lack of confidence in their ability to complete self-sampling correctly. In most articles reviewed, the studied associated factors, such as demographic factors (age, marital status, and ethnicity), socioeconomic factors (income, education level), reproductive factors (condom use, number of children, current use of contraception, and number of partners), and habits (smoking status) were not found to be significantly associated with preference.
CONCLUSIONS: Both methods of sampling were found to be acceptable to women. Self-sampling is cost-effective and could increase the screening coverage among underscreened populations. However, more information about the quality, reliability, and accuracy of self-sampling is needed to increase women's confidence about using to this method.
AIM: This study aimed to evaluate the effectiveness of care-seeking behavior interventions on cervical cancer screening participation.
METHOD: A pragmatic multiphase mixed methods design was adopted for this study, and three phases of the human-centered design process were used for data collection. Deductive thematic analysis was used for qualitative data, while SPSS was used for quantitative data analysis.
RESULTS: The findings show a significant relationship between participants' tribes p values (0.03) 0.05 and screening participation. Before the intervention, most (77.4%) were afraid of exposing their private parts; 75.9% were afraid of being diagnosed with cervical cancer; and the majority felt the procedure was embarrassing and painful. Free screening, awareness, and knowledge, offering transport, the use of influencers, and sample collection by a female care provider are among other facilitators to screening. Screening participation improved from 11.2% preintervention to 29.7% postintervention (average mean screening score from 1.890.316 to 1.70000.458). All participants who were screened postintervention said the procedure was not embarrassing or painful and that they were not afraid of the procedure or the screening environment.
CONCLUSION: In conclusion, screening habits in the community were low before intervention, as this may have resulted from women's feelings and past experiences with screening services. Sociodemographic variables may not directly predict screening participation. Care-seeking behavior interventions have significantly increased screening participation postintervention.
METHODS: This cross-sectional study was conducted at Hospital Tuanku Fauziah, Perlis, Malaysia from August 2015 to April 2016. FEV1/FEV6 and FEV1/FVC results of 117 subjects were analysed. Demographic data and spirometric variables were tabulated. A scatter plot graph with Spearman's correlation was constructed for the correlation between FEV1/FEV6 and FEV1/FVC. The sensitivity, specificity, positive and negative predictive values of FEV1/FEV6 were determined with reference to the gold standard of FEV1/FVC ratio <0.70. Receiver-operator characteristic (ROC) curve analysis and Kappa statistics were used to determine the FEV1/FEV6 ratio in predicting an FEV1/FVC ratio <0.70.
RESULTS: Spearman's correlation with r = 0.636 (P<0.001) was demonstrated. The area under the ROC curve was 0.862 (95% confidence interval [CI]: 0.779 - 0.944, P<0.001). The FEV1/FEV6 cut-off with the greatest sum of sensitivity and specificity was 0.75. FEV1/FEV6 sensitivity, specificity, positive and negative predictive values were 93.02%, 67.74%, 88.89% and 77.78% respectively. There was substantial agreement between the two diagnostic cut-offs (κ = 0.634; 95% CI: 0.471 - 0.797, P<0.001) CONCLUSIONS: The FEV1/FEV6 ratio can be considered to be a good alternative to the FEV1/FVC ratio for screening of COPD. Larger multicentre study and better education on spirometric techniques can validate similar study outcome and establish reference values appropriate to the population being studied.
METHODS: Secondary analysis of data extracted from the British Household Panel Survey, a national longitudinal survey (n=5547). Analysis to ascertain whether patterns of attendance for dental check-ups for a period of 10 years (1991-2001) were associated with risk factors for oral cancer such as age, sex, education, social class, smoking status and smoking intensity.
RESULTS: Males, aged over 40 years, less educated manual workers and smokers were significantly less likely to attend for dental check-ups compared with females and younger, higher educated, higher socio-economic class non-smokers (p < 0.05). Throughout the 10-year period, young people, more than older people, had progressively lower odds ratios of attending. Those with more education used dental services more. Heavy smokers were infrequent attendees.
CONCLUSIONS: This study suggests that opportunistic oral cancer screening by dentists is not feasible to include high-risk groups as they are not regular attendees over 10 years. Those who would be screened would be the low-risk groups. However, dentists should continue screening all patients as oral precancers are also found in regular attendees. More should be done to encourage the high-risk groups to visit their dentists.