Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations

This is the protocol for a review and there is no abstract. The objectives are as follows: The main objective is to assess the effectiveness and cost effectiveness of digital interventions for reducing hazardous and harmful alcohol consumption and/or alcohol-related problems in community-dwelling populations. We envisage two comparator groups: (1) no intervention (or minimal input) controls; and (2) another active intervention for delivering preventive advice or counselling to reduce hazardous or harmful alcohol consumption. Specifically, we will address two questions: (1) Are digital interventions superior to no intervention (or minimal input) controls? This question is important for individuals accessing interventions through their own motivation or interest. These individuals will be unlikely to experience active practitioner input and it is important to understand whether digital interventions are better than general material they might seek out on the internet or via mobile phone-based apps etc. (2) Are digital interventions at least equally effective as face-to-face brief alcohol interventions? Practitioner delivered brief interventions are generally accepted to be the best alternative in secondary preventive care in health, workplace, educational or community settings. However, time constraints can impede face-to-face delivery of such interventions and it is important to know whether digitally provided input can yield comparable effects to interventions delivered by trained practitioners. We will also identify the most effective component behaviour change techniques of such interventions and their mechanisms of action. Secondary objectives are as follows: 1.To assess whether outcomes differ between trials where the digital intervention targets participants attending health, social care, education or other community-based settings and those where it is offered remotely via the internet or mobile phone platforms; 2.To develop a taxonomy of interventions according to their mode of delivery (e.g. functionality features) and assess their impact on outcomes; 3.To identify theories or models that have been used in the development and/or evaluation of the intervention – this will inform intervention development work

Reported theory use by digital alcohol interventions and association with effectiveness: meta-regression

Background: Applying theory to the design and evaluation of interventions is likely to increase effectiveness and improve the evidence base from which future interventions are developed, though few interventions report this. Objective: The aim of this paper was to assess how digital interventions to reduce hazardous and harmful alcohol consumption report the use of theory in their development and evaluation, and whether reporting of theory use is associated with intervention effectiveness. Methods: Randomized controlled trials were extracted from a Cochrane review on digital interventions for reducing hazardous and harmful alcohol consumption. Reporting of theory use within these digital interventions was investigated using the theory coding scheme (TCS). Reported theory use was analyzed by frequency counts and descriptive statistics. Associations were analyzed with meta-regression models. Results: Of 41 trials involving 42 comparisons, half did not mention theory (50% [21/42]), and only 38% (16/42) used theory to select or develop the intervention techniques. Significant heterogeneity existed between studies in the effect of interventions on alcohol reduction (I2=77.6%, P<.001). No significant associations were detected between reporting of theory use and intervention effectiveness in unadjusted models, though the meta-regression was underpowered to detect modest associations. Conclusions: Digital interventions offer a unique opportunity to refine and develop new dynamic, temporally sensitive theories, yet none of the studies reported refining or developing theory. Clearer selection, application, and reporting of theory use is needed to accurately assess how useful theory is in this field and to advance the field of behavior change theories

Behaviour change techniques used in digital behaviour change interventions to reduce excessive alcohol consumption: a meta-regression

Background: Digital behavior change interventions (DBCIs) appear to reduce alcohol consumption, but greater understanding is needed of their mechanisms of action. // Purpose: To describe the behavior change techniques (BCTs) used in DBCIs and examine whether individual BCTs, the inclusion of more BCTs or more Control Theory congruent BCTs is associated with increased effectiveness. // Methods: Forty-one randomized control trials were extracted from a Cochrane review of alcohol reduction DBCIs and coded for up to 93 BCTs using an established and reliable method. Random effects unadjusted and adjusted meta-regression models were performed to assess associations between BCTs and intervention effectiveness. // Results: Interventions used a mean of 9.1 BCTs (range 1–22), 23 different BCTs were used in four or more trials. Trials that used “Behavior substitution” (−95.112 grams per week [gpw], 95% CI: −162.90, −27.34), “Problem solving” (−45.92 gpw, 95% CI: −90.97, −0.87) and “Credible source” (−32.09 gpw, 95% CI: −60.64, −3.55) were significantly associated with greater alcohol reduction than trials without these BCTs. The “Behavior substitution” result should be treated as preliminary because it was reported in only four trials, three of which were conducted by the same research group. “Feedback” was used in 98% of trials (n = 41); other Control Theory congruent BCTs were used less frequently: for example, “Goal setting” 43% (n = 18) and “Self-monitoring” 29%, (n = 12). // Conclusions: “Behavior substitution,” “Problem solving,” and “Credible source” were associated with greater alcohol reduction. Many BCTs were used infrequently in DBCIs, including BCTs with evidence of effectiveness in other domains, such as “Self-monitoring” and “Goal setting.

The cost-effectiveness of procalcitonin for guiding antibiotic prescribing in individuals hospitalized with COVID-19: part of the PEACH study

Background Many hospitals introduced procalcitonin (PCT) testing to help diagnose bacterial coinfection in individuals with COVID-19, and guide antibiotic decision-making during the COVID-19 pandemic in the UK. Objectives Evaluating cost-effectiveness of using PCT to guide antibiotic decisions in individuals hospitalized with COVID-19, as part of a wider research programme. Methods Retrospective individual-level data on patients hospitalized with COVID-19 were collected from 11 NHS acute hospital Trusts and Health Boards from England and Wales, which varied in their use of baseline PCT testing during the first COVID-19 pandemic wave. A matched analysis (part of a wider analysis reported elsewhere) created groups of patients whose PCT was/was not tested at baseline. A model was created with combined decision tree/Markov phases, parameterized with quality-of-life/unit cost estimates from the literature, and used to estimate costs and quality-adjusted life years (QALYs). Cost-effectiveness was judged at a £20 000/QALY threshold. Uncertainty was characterized using bootstrapping. Results People who had baseline PCT testing had shorter general ward/ICU stays and spent less time on antibiotics, though with overlap between the groups’ 95% CIs. Those with baseline PCT testing accrued more QALYs (8.76 versus 8.62) and lower costs (£9830 versus £10 700). The point estimate was baseline PCT testing being dominant over no baseline testing, though with uncertainty: the probability of cost-effectiveness was 0.579 with a 1 year horizon and 0.872 with a lifetime horizon. Conclusions Using PCT to guide antibiotic therapy in individuals hospitalized with COVID-19 is more likely to be cost-effective than not, albeit with uncertainty