5 results on '"Sarah Wordsworth"'
Search Results
2. Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear-based messages about antimicrobial resistance
- Author
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Laurence S. J. Roope, Sarah Tonkin-Crine, Natalie Herd, Susan Michie, Koen B. Pouwels, Enrique Castro-Sanchez, Anna Sallis, Susan Hopkins, Julie V. Robotham, Derrick W. Crook, Tim Peto, Michele Peters, Christopher C. Butler, A. Sarah Walker, and Sarah Wordsworth
- Subjects
Inappropriate antibiotic use ,Fear messages about antimicrobial resistance ,Public campaigns ,Medicine - Abstract
Abstract Background To reduce inappropriate antibiotic use, public health campaigns often provide fear-based information about antimicrobial resistance (AMR). Meta-analyses have found that fear-based campaigns in other contexts are likely to be ineffective unless respondents feel confident they can carry out the recommended behaviour (‘self-efficacy’). This study aimed to test the likely impact of fear-based messages, with and without empowering self-efficacy elements, on patient consultations/antibiotic requests for influenza-like illnesses, using a randomised design. Methods We hypothesised that fear-based messages containing empowering information about self-management without antibiotics would be more effective than fear alone, particularly in a pre-specified subgroup with low AMR awareness. Four thousand respondents from an online panel, representative of UK adults, were randomised to receive three different messages about antibiotic use and AMR, designed to induce fear about AMR to varying degrees. Two messages (one ‘strong-fear’, one ‘mild-fear’) also contained empowering information regarding influenza-like symptoms being easily self-managed without antibiotics. The main outcome measures were self-reported effect of information on likelihood of visiting a doctor and requesting antibiotics, for influenza-like illness, analysed separately according to whether or not the AMR information was ‘very/somewhat new’ to respondents, pre-specified based on a previous (non-randomised) survey. Results The ‘fear-only’ message was ‘very/somewhat new’ to 285/1000 (28.5%) respondents, ‘mild-fear-plus-empowerment’ to 336/1500 (22.4%), and ‘strong-fear-plus-empowerment’ to 388/1500 (25.9%) (p = 0.002). Of those for whom the respective information was ‘very/somewhat new’, only those given the ‘strong-fear-plus-empowerment’ message said they would be less likely to request antibiotics if they visited a doctor for an influenza-like illness (p
- Published
- 2020
- Full Text
- View/download PDF
3. Optimising trial designs to identify appropriate antibiotic treatment durations
- Author
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Koen B. Pouwels, Mo Yin, Christopher C. Butler, Ben S. Cooper, Sarah Wordsworth, A. Sarah Walker, and Julie V. Robotham
- Subjects
Antimicrobial resistance ,Design ,Randomised trial ,Duration of therapy ,Antibiotics ,Bayesian ,Medicine - Abstract
Abstract Background For many infectious conditions, the optimal antibiotic course length remains unclear. The estimation of course length must consider the important trade-off between maximising short- and long-term efficacy and minimising antibiotic resistance and toxicity. Main body Evidence on optimal treatment durations should come from randomised controlled trials. However, most antibiotic randomised controlled trials compare two arbitrarily chosen durations. We argue that alternative trial designs, which allow allocation of patients to multiple different treatment durations, are needed to better identify optimal antibiotic durations. There are important considerations when deciding which design is most useful in identifying optimal treatment durations, including the ability to model the duration–response relationship (or duration–response ‘curve’), the risk of allocation concealment bias, statistical efficiency, the possibility to rapidly drop arms that are clearly inferior, and the possibility of modelling the trade-off between multiple competing outcomes. Conclusion Multi-arm designs modelling duration–response curves with the possibility to drop inferior arms during the trial could provide more information about the optimal duration of antibiotic therapies than traditional head-to-head comparisons of limited numbers of durations, while minimising the probability of assigning trial participants to an ineffective treatment regimen.
- Published
- 2019
- Full Text
- View/download PDF
4. Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear-based messages about antimicrobial resistance
- Author
-
Susan Hopkins, Christopher C Butler, Laurence Roope, Natalie Herd, Michele Peters, Julie V. Robotham, Derrick W. Crook, Enrique Castro-Sánchez, Sarah Wordsworth, A. Sarah Walker, Anna Sallis, Sarah Tonkin-Crine, Koen B. Pouwels, Susan Michie, Tim E. A. Peto, and National Institute for Health Research
- Subjects
Adult ,Male ,0301 basic medicine ,RM ,medicine.medical_specialty ,Public campaigns ,medicine.drug_class ,030106 microbiology ,Antibiotics ,lcsh:Medicine ,Primary care ,RT ,03 medical and health sciences ,Medicine, General & Internal ,0302 clinical medicine ,Antibiotic resistance ,General & Internal Medicine ,Surveys and Questionnaires ,Drug Resistance, Bacterial ,Humans ,Medicine ,030212 general & internal medicine ,Antibiotic use ,Inappropriate antibiotic use ,METAANALYSIS ,11 Medical and Health Sciences ,Public Health Informatics ,Science & Technology ,Primary Health Care ,business.industry ,Public health ,lcsh:R ,Outcome measures ,Fear ,General Medicine ,Anti-Bacterial Agents ,QR ,Test (assessment) ,Fear messages about antimicrobial resistance ,Family medicine ,Female ,business ,Life Sciences & Biomedicine - Abstract
Background To reduce inappropriate antibiotic use, public health campaigns often provide fear-based information about antimicrobial resistance (AMR). Meta-analyses have found that fear-based campaigns in other contexts are likely to be ineffective unless respondents feel confident they can carry out the recommended behaviour (‘self-efficacy’). This study aimed to test the likely impact of fear-based messages, with and without empowering self-efficacy elements, on patient consultations/antibiotic requests for influenza-like illnesses, using a randomised design. Methods We hypothesised that fear-based messages containing empowering information about self-management without antibiotics would be more effective than fear alone, particularly in a pre-specified subgroup with low AMR awareness. Four thousand respondents from an online panel, representative of UK adults, were randomised to receive three different messages about antibiotic use and AMR, designed to induce fear about AMR to varying degrees. Two messages (one ‘strong-fear’, one ‘mild-fear’) also contained empowering information regarding influenza-like symptoms being easily self-managed without antibiotics. The main outcome measures were self-reported effect of information on likelihood of visiting a doctor and requesting antibiotics, for influenza-like illness, analysed separately according to whether or not the AMR information was ‘very/somewhat new’ to respondents, pre-specified based on a previous (non-randomised) survey. Results The ‘fear-only’ message was ‘very/somewhat new’ to 285/1000 (28.5%) respondents, ‘mild-fear-plus-empowerment’ to 336/1500 (22.4%), and ‘strong-fear-plus-empowerment’ to 388/1500 (25.9%) (p = 0.002). Of those for whom the respective information was ‘very/somewhat new’, only those given the ‘strong-fear-plus-empowerment’ message said they would be less likely to request antibiotics if they visited a doctor for an influenza-like illness (p p p Conclusions Fear could be effective in public campaigns to reduce inappropriate antibiotic use, but should be combined with messages empowering patients to self-manage symptoms effectively without antibiotics.
- Published
- 2020
- Full Text
- View/download PDF
5. Optimising trial designs to identify appropriate antibiotic treatment durations
- Author
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Ben S. Cooper, Christopher C Butler, Julie V. Robotham, Mo Yin, Koen B. Pouwels, Sarah Wordsworth, and A. Sarah Walker
- Subjects
Opinion ,medicine.medical_specialty ,Randomised trial ,Design ,medicine.drug_class ,Antibiotics ,lcsh:Medicine ,Duration of therapy ,Antimicrobial resistance ,TUBERCULOSIS ,Bayesian ,03 medical and health sciences ,0302 clinical medicine ,Humans ,Medicine ,030212 general & internal medicine ,Intensive care medicine ,Frequentist ,Treatment regimen ,business.industry ,Optimal treatment ,lcsh:R ,ADAPTIVE TRIAL ,Drug Resistance, Microbial ,General Medicine ,TRENDS ,Anti-Bacterial Agents ,3. Good health ,Clinical trial ,business ,030217 neurology & neurosurgery ,CLINICAL-TRIALS - Abstract
Background For many infectious conditions, the optimal antibiotic course length remains unclear. The estimation of course length must consider the important trade-off between maximising short- and long-term efficacy and minimising antibiotic resistance and toxicity. Main body Evidence on optimal treatment durations should come from randomised controlled trials. However, most antibiotic randomised controlled trials compare two arbitrarily chosen durations. We argue that alternative trial designs, which allow allocation of patients to multiple different treatment durations, are needed to better identify optimal antibiotic durations. There are important considerations when deciding which design is most useful in identifying optimal treatment durations, including the ability to model the duration–response relationship (or duration–response ‘curve’), the risk of allocation concealment bias, statistical efficiency, the possibility to rapidly drop arms that are clearly inferior, and the possibility of modelling the trade-off between multiple competing outcomes. Conclusion Multi-arm designs modelling duration–response curves with the possibility to drop inferior arms during the trial could provide more information about the optimal duration of antibiotic therapies than traditional head-to-head comparisons of limited numbers of durations, while minimising the probability of assigning trial participants to an ineffective treatment regimen.
- Published
- 2019
- Full Text
- View/download PDF
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