The success of Australia’s ‘No Jab,No Pay’ policy at a local level; retrospective clinical audit of a single medical practice assessing incidence of catch-up vaccinations

Vaccination is a vital health care initiative to prevent individual and population infection. To increase vaccination rates the federal government implemented the ‘No Jab, No Pay’ policy, where eligibility for several government benefits required children to be fully vaccinated by removing ‘conscientious objections’ and expanding the age range of children whose families receive benefits. This study assesses the impact of this policy at a local area within a single medical practice community in NSW, Australia. A retrospective clinical audit was performed between 2012 and 2017 on a single general practice's vaccination records for children ≤19 years. Catch-up vaccinations were assessed based on age at vaccination. Incidence of catch-up vaccinations was assessed for each of four years before and two years after the implementation of the ‘No Jab, No Pay’ policy in January 2016, along with the age of children and vaccination(s) given. Catch-up vaccinations were assessed temporally either side of implementation of ‘No Jab, No Pay’. Comparing the average annual vaccination catch-up incidence rate of 6.2% pre-implementation (2012–2015), there was an increase to 9.2% in 2016 (p < .001) and 7.8% in 2017 (p = .027). Secondary outcome measurement of catch-up vaccination incidence rates before (2012–2015) and after (2016–2017) ‘No Jab, No Pay’ implementation showed statistically significant increases for children aged 8–11 years (3.2%–5.6%, p = .038), 12–15 years (7.5%–14.7%, p < .001) and 16–19 years (3.3%–10.2%, p < .001) along with a statistically significant reduction in children aged 1–3 years (11.4%–6.2%, p = .015). Also, catch-up rates for DTPa significantly increased after program implementation. This study demonstrates that the Australian federal government vaccination policy ‘No Jab, No Pay’ was coincident with an increase in catch-up vaccinations within a rural NSW community served by one medical practice, especially for older children.     

Neuroticism,Trait Fear of Missing Out,and Phubbing: The Mediating Role of State Fear of Missing Out and Problematic Instagram Use

International Journal of Mental Health and Addiction - One of the relatively new negative consequences of smartphone use is “phubbing” (snubbing someone while an individual checks their...     

Outcomes after neoadjuvant or adjuvant chemotherapy for cT2-4N0-1 non–small cell lung cancer: A propensity-matched analysis

Objective

Comparative survival between neoadjuvant chemotherapy and adjuvant chemotherapy for patients with cT2-4N0-1M0 non–small cell lung cancer has not been extensively studied.

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.