Biofield Therapies: Helpful or Full of Hype? A Best Evidence Synthesis

Biofield therapies (such as Reiki, therapeutic touch, and healing touch) are complementary medicine modalities that remain controversial and are utilized by a significant number of patients, with little information regarding their efficacy. This systematic review examines 66 clinical studies with a variety of biofield therapies in different patient populations. We conducted a quality assessment as well as a best evidence synthesis approach to examine evidence for biofield therapies in relevant outcomes for different clinical populations. Studies overall are of medium quality, and generally meet minimum standards for validity of inferences. Biofield therapies show strong evidence for reducing pain intensity in pain populations, and moderate evidence for reducing pain intensity hospitalized and cancer populations. There is moderate evidence for decreasing negative behavioral symptoms in dementia and moderate evidence for decreasing anxiety for hospitalized populations. There is equivocal evidence for biofield therapies' effects on fatigue and quality of life for cancer patients, as well as for comprehensive pain outcomes and affect in pain patients, and for decreasing anxiety in cardiovascular patients. There is a need for further high-quality studies in this area. Implications and future research directions are discussed

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

for the ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS)BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. RESULTS The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag ₄₀ and 35% had autocorrelation through to lag ₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. CONCLUSIONS The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.John L Moran, Patricia J Solomo

Valuing Insect Pollination Services with Cost of Replacement

Value estimates of ecosystem goods and services are useful to justify the allocation of resources towards conservation, but inconclusive estimates risk unsustainable resource allocations. Here we present replacement costs as a more accurate value estimate of insect pollination as an ecosystem service, although this method could also be applied to other services. The importance of insect pollination to agriculture is unequivocal. However, whether this service is largely provided by wild pollinators (genuine ecosystem service) or managed pollinators (commercial service), and which of these requires immediate action amidst reports of pollinator decline, remains contested. If crop pollination is used to argue for biodiversity conservation, clear distinction should be made between values of managed- and wild pollination services. Current methods either under-estimate or over-estimate the pollination service value, and make use of criticised general insect and managed pollinator dependence factors. We apply the theoretical concept of ascribing a value to a service by calculating the cost to replace it, as a novel way of valuing wild and managed pollination services. Adjusted insect and managed pollinator dependence factors were used to estimate the cost of replacing insect- and managed pollination services for the Western Cape deciduous fruit industry of South Africa. Using pollen dusting and hand pollination as suitable replacements, we value pollination services significantly higher than current market prices for commercial pollination, although lower than traditional proportional estimates. The complexity associated with inclusive value estimation of pollination services required several defendable assumptions, but made estimates more inclusive than previous attempts. Consequently this study provides the basis for continued improvement in context specific pollination service value estimates