Comparing the effects of sun exposure and vitamin D supplementation on vitamin D insufficiency, and immune and cardio-metabolic function: the Sun Exposure and Vitamin D Supplementation (SEDS) Study

BACKGROUND Adults living in the sunny Australian climate are at high risk of skin cancer, but vitamin D deficiency (defined here as a serum 25-hydroxyvitamin D (25(OH)D) concentration of less than 50 nmol/L) is also common. Vitamin D deficiency may be a risk factor for a range of diseases. However, the optimal strategies to achieve and maintain vitamin D adequacy (sun exposure, vitamin D supplementation or both), and whether sun exposure itself has benefits over and above initiating synthesis of vitamin D, remain unclear. The Sun Exposure and Vitamin D Supplementation (SEDS) Study aims to compare the effectiveness of sun exposure and vitamin D supplementation for the management of vitamin D insufficiency, and to test whether these management strategies differentially affect markers of immune and cardio-metabolic function. METHODS/DESIGN The SEDS Study is a multi-centre, randomised controlled trial of two different daily doses of vitamin D supplementation, and placebo, in conjunction with guidance on two different patterns of sun exposure. Participants recruited from across Australia are aged 18-64 years and have a recent vitamin D test result showing a serum 25(OH)D level of 40-60 nmol/L. DISCUSSION This paper discusses the rationale behind the study design, and considers the challenges but necessity of data collection within a non-institutionalised adult population, in order to address the study aims. We also discuss the challenges of participant recruitment and retention, ongoing engagement of referring medical practitioners and address issues of compliance and participant retention. TRIAL REGISTRATION Australia New Zealand Clinical Trials Registry: ACTRN12613000290796 Registered 14 March 2013

Comparing the effects of sun exposure and vitamin D supplementation on vitamin D insufficiency, and immune and cardio-metabolic function: The Sun Exposure and Vitamin D Supplementation (SEDS) Study

Background: Adults living in the sunny Australian climate are at high risk of skin cancer, but vitamin D deficiency (defined here as a serum 25-hydroxyvitamin D (25(OH)D) concentration of less than 50 nmol/L) is also common. Vitamin D deficiency may be a risk factor for a range of diseases. However, the optimal strategies to achieve and maintain vitamin D adequacy (sun exposure, vitamin D supplementation or both), and whether sun exposure itself has benefits over and above initiating synthesis of vitamin D, remain unclear. The Sun Exposure and Vitamin D Supplementation (SEDS) Study aims to compare the effectiveness of sun exposure and vitamin D supplementation for the management of vitamin D insufficiency, and to test whether these management strategies differentially affect markers of immune and cardio-metabolic function. Methods/Design: The SEDS Study is a multi-centre, randomised controlled trial of two different daily doses of vitamin D supplementation, and placebo, in conjunction with guidance on two different patterns of sun exposure. Participants recruited from across Australia are aged 18-64 years and have a recent vitamin D test result showing a serum 25(OH)D level of 40-60 nmol/L. Discussion: This paper discusses the rationale behind the study design, and considers the challenges but necessity of data collection within a non-institutionalised adult population, in order to address the study aims. We also discuss the challenges of participant recruitment and retention, ongoing engagement of referring medical practitioners and address issues of compliance and participant retention. Trial registration: Australia New Zealand Clinical Trials Registry: ACTRN12613000290796 Registered 14 March 2013

Pharmacotherapies for cannabis dependence (Review)

BACKGROUND: Cannabis is the most prevalent illicit drug in the world. Demand for treatment of cannabis use disorders is increasing. There are currently no pharmacotherapies approved for treatment of cannabis use disorders. OBJECTIVES: To assess the effectiveness and safety of pharmacotherapies as compared with each other, placebo or supportive care for reducing symptoms of cannabis withdrawal and promoting cessation or reduction of cannabis use. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (to 4 March 2014), MEDLINE (to week 3 February 2014), EMBASE (to 3 March 2014) and PsycINFO (to week 4 February 2014). We also searched reference lists of articles, electronic sources of ongoing trials and conference proceedings, and contacted selected researchers active in the area. SELECTION CRITERIA: Randomised and quasi-randomised controlled trials involving the use of medications to reduce the symptoms and signs of cannabis withdrawal or to promote cessation or reduction of cannabis use, or both, in comparison with other medications, placebo or no medication (supportive care) in participants diagnosed as cannabis dependent or who were likely to be dependent. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by The Cochrane Collaboration. Two review authors assessed studies for inclusion and extracted data. All review authors confirmed the inclusion decisions and the overall process. MAIN RESULTS: We included 14 randomised controlled trials involving 958 participants. For 10 studies the average age was 33 years; two studies targeted young people; and age data were not available for two studies. Approximately 80% of study participants were male. The studies were at low risk of selection, performance, detection and selective outcome reporting bias. Three studies were at risk of attrition bias. All studies involved comparison of active medication and placebo. The medications included preparations containing tetrahydrocannabinol (THC) (two studies), selective serotonin reuptake inhibitor (SSRI) antidepressants (two studies), mixed action antidepressants (three studies), anticonvulsants and mood stabilisers (three studies), an atypical antidepressant (two studies), an anxiolytic (one study), a norepinephrine reuptake inhibitor (one study) and a glutamatergic modulator (one study). One study examined more than one medication. Diversity in the medications and the outcomes reported limited the extent that analysis was possible. Insufficient data were available to assess the utility of most of the medications to promote cannabis abstinence at the end of treatment. There was moderate quality evidence that completion of treatment was more likely with preparations containing THC compared to placebo (RR 1.29, 95% CI 1.08 to 1.55; 2 studies, 207 participants, P = 0.006). There was some evidence that treatment with preparations containing THC was associated with reduced cannabis withdrawal symptoms and craving, but this latter outcome could not be quantified. For mixed action antidepressants compared with placebo (2 studies, 179 participants) there was very low quality evidence on the likelihood of abstinence from cannabis at the end of follow-up (RR 0.82, 95% CI 0.12 to 5.41), and moderate quality evidence on the likelihood of treatment completion (RR 0.93, 95% CI 0.71 to 1.21). For this same outcome there was very low quality evidence for the effects of SSRI antidepressants (RR 0.82, 95% CI 0.44 to 1.53; 2 studies, 122 participants), anticonvulsants and mood stabilisers (RR 0.78, 95% CI 0.42 to 1.46; 2 studies, 75 participants), and the atypical antidepressant, bupropion (RR 1.06, 95% CI 0.67 to 1.67; 2 studies, 92 participants). Available evidence on gabapentin (anticonvulsant) and N-acetylcysteine (glutamatergic modulator) was insufficient for quantitative estimates of their effectiveness, but these medications may be worth further investigation. AUTHORS’ CONCLUSIONS: There is incomplete evidence for all of the pharmacotherapies investigated, and for many of the outcomes the quality was downgraded due to small sample sizes, inconsistency and risk of attrition bias. The quantitative analyses that were possible, combined with general findings of the studies reviewed, indicate that SSRI antidepressants, mixed action antidepressants, atypical antidepressants (bupropion), anxiolytics (buspirone) and norepinephrine reuptake inhibitors (atomoxetine) are probably of little value in the treatment of cannabis dependence. Preparations containing THC are of potential value but, given the limited evidence, this application of THC preparations should be considered still experimental. Further studies should compare different preparations of THC, dose and duration of treatment, adjunct medications and therapies. The evidence base for the anticonvulsant gabapentin and the glutamatergic modulator N-acetylcysteine is weak, but these medications are also worth further investigation

No improvement in AUDIT-C screening and brief intervention rates among wait-list controls following support of Aboriginal Community Controlled Health Services: Evidence from a cluster randomised trial

Background While Aboriginal and Torres Strait Islander Australians are less likely to drink any alcohol than other Australians, those who drink are more likely to experience adverse alcohol-related health consequences. In a previous study, providing Aboriginal Community Controlled Health Services (ACCHSs) with training and support increased the odds of clients receiving AUDIT-C alcohol screening. A follow-up study found that these results were maintained for at least two years, but there was large variability in the effectiveness of the intervention between services. In this study, we use services that previously received support as a comparison group to test whether training and support can improve alcohol screening and brief intervention rates among wait-list control ACCHSs. Methods Design: Cluster randomised trial using routinely collected health data. Setting: Australia. Cases: Twenty-two ACCHSs that see at least 1000 clients a year and use Communicare as their practice management software. Intervention and comparator: After initiating support, we compare changes in screening and brief intervention between wait-list control services and services that had previously received support. Measurement: Records of AUDIT-C screening and brief intervention activity in routinely collected data. Results During the reference period we observed 357,257 instances where one of 74,568 clients attended services at least once during a two-monthly data extraction period. Following the start of support, the odds of screening (OR = 0.94 [95% CI 0.67, 1.32], p = 0.74, BF10 role= presentation style= margin: 0px; box-sizing: inherit; display: inline-block; line-height: normal; word-spacing: normal; overflow-wrap: normal; text-wrap: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; position: relative; \u3e10≈ role= presentation style= margin: 0px; box-sizing: inherit; display: inline-block; line-height: normal; word-spacing: normal; overflow-wrap: normal; text-wrap: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; position: relative; \u3e≈ 0.002) and brief intervention (OR = 1.43 [95% CI 0.69, 2.95], p = 0.34, BF10 role= presentation style= margin: 0px; box-sizing: inherit; display: inline-block; line-height: normal; word-spacing: normal; overflow-wrap: normal; text-wrap: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; position: relative; \u3e10≈ role= presentation style= margin: 0px; box-sizing: inherit; display: inline-block; line-height: normal; word-spacing: normal; overflow-wrap: normal; text-wrap: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; position: relative; \u3e≈ 0.002) did not improve for the wait-list control group, relative to comparison services. Conclusions We did not replicate the finding that support and training improves AUDIT-C screening rates with wait-list control data. The benefits of support are likely context dependent. Coincidental policy changes may have sensitised services to the effects of support in the earlier phase of the study. Then the COVID-19 pandemic may have made services less open to change in this latest phase. Future efforts could include practice software prompts to alcohol screening and brief intervention, which are less reliant on individual staff time or resources. Trial registration Retrospectively registered on 2018-11-21: ACTRN12618001892202

No improvement in AUDIT-C screening and brief intervention rates among wait-list controls following support of Aboriginal Community Controlled Health Services: evidence from a cluster randomised trial

Background: While Aboriginal and Torres Strait Islander Australians are less likely to drink any alcohol than other Australians, those who drink are more likely to experience adverse alcohol-related health consequences. In a previous study, providing Aboriginal Community Controlled Health Services (ACCHSs) with training and support increased the odds of clients receiving AUDIT-C alcohol screening. A follow-up study found that these results were maintained for at least two years, but there was large variability in the effectiveness of the intervention between services. In this study, we use services that previously received support as a comparison group to test whether training and support can improve alcohol screening and brief intervention rates among wait-list control ACCHSs. Methods: Design: Cluster randomised trial using routinely collected health data. Setting: Australia. Cases: Twenty-two ACCHSs that see at least 1000 clients a year and use Communicare as their practice management software. Intervention and comparator: After initiating support, we compare changes in screening and brief intervention between wait-list control services and services that had previously received support. Measurement: Records of AUDIT-C screening and brief intervention activity in routinely collected data. Results: During the reference period we observed 357,257 instances where one of 74,568 clients attended services at least once during a two-monthly data extraction period. Following the start of support, the odds of screening (OR = 0.94 [95% CI 0.67, 1.32], p = 0.74, 0.002) and brief intervention (OR = 1.43 [95% CI 0.69, 2.95], p = 0.34, 0.002) did not improve for the wait-list control group, relative to comparison services. Conclusions: We did not replicate the finding that support and training improves AUDIT-C screening rates with wait-list control data. The benefits of support are likely context dependent. Coincidental policy changes may have sensitised services to the effects of support in the earlier phase of the study. Then the COVID-19 pandemic may have made services less open to change in this latest phase. Future efforts could include practice software prompts to alcohol screening and brief intervention, which are less reliant on individual staff time or resources. Trial registration: Retrospectively registered on 2018-11-21: ACTRN12618001892202