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      Impact of the ENSP eLearning platform on improving knowledge, attitudes and self-efficacy for treating tobacco dependence: An assessment across 15 European countries

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      Tobacco Induced Diseases
      European Publishing on behalf of the International Society for the Prevention of Tobacco Induced Diseases (ISPTID)
      evidence-based strategies, healthcare professionals, eLearning, smoking cessation

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          Abstract

          INTRODUCTION

          In 2018, the European Network for Smoking Cessation and Prevention (ENSP) released an update to its Tobacco Treatment Guidelines for healthcare professionals, which was the scientific base for the development of an accredited eLearning curriculum to train healthcare professionals, available in 14 languages. The aim of this study was to evaluate the effectiveness of ENSP eLearning curriculum in increasing healthcare professionals’ knowledge, attitudes, self-efficacy (perceived behavioral control) and intentions in delivering tobacco treatment interventions in their daily clinical routines.

          METHODS

          We conducted a quasi-experimental pre-post design study with 444 healthcare professionals, invited by 20 collaborating institutions from 15 countries (Albania, Armenia, Belgium, Italy, France, Georgia, Greece, Kosovo, Romania, North Macedonia, Russia, Serbia, Slovenia, Spain, Ukraine), which completed the eLearning course between December 2018 and July 2019.

          RESULTS

          Healthcare professionals’ self-reported knowledge improved after the completion of each module of the eLearning program. Increases in healthcare professionals’ self-efficacy in delivering tobacco treatment interventions (p<0.001) were also documented. Significant improvements were documented in intentions to address tobacco use as a priority, document tobacco use, offer support, provide brief counselling, give written material, discuss available medication, prescribe medication, schedule dedicated appointment to develop a quit plan, and be persistent in addressing tobacco use with the patients (all p<0.001).

          CONCLUSIONS

          An evidence-based digital intervention can be effective in improving knowledge, attitudes, self-efficacy and intentions on future delivery of tobacco-treatment interventions.

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          Most cited references22

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          The theory of planned behavior

          Icek Ajzen (1991)
          Organizational Behavior and Human Decision Processes, 50(2), 179-211
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            Internet-based interventions for smoking cessation

            Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking. To determine the effectiveness of Internet‐based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults. We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016. We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no‐intervention control, a different Internet intervention, or a non‐Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer. Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six‐month follow‐up or more, reporting short‐term outcomes narratively where longer‐term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI). We grouped studies according to whether they (1) compared an Internet intervention with a non‐active control arm (e.g. printed self‐help guides), (2) compared an Internet intervention with an active control arm (e.g. face‐to‐face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age. We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants. There were only four RCTs conducted in adolescence or young adults that were eligible for meta‐analysis. Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non‐active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I 2 = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I 2 = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non‐active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I 2 = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I 2 = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I 2 = 0%); GRADE rating was moderate. Three studies compared tailored with non‐tailored Internet‐based messages, compared to non‐tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I 2 = 57%); GRADE rating was low. Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias. The evidence from trials in adults suggests that interactive and tailored Internet‐based interventions with or without additional behavioural support are moderately more effective than non‐active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown. Can Internet‐based interventions help people to stop smoking?  Background Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide. The Internet is an attractive platform to help people quit smoking because of low costs per user, and it has potential to reach smokers who might not access support because of limited health care availability or stigmatisation. Internet‐based interventions could also be used to target young people who smoke, or others who may not seek traditional methods of smoking treatment. Study Characteristics Up to August 2016, this review found 67 trials, including data from over 110,000 participants. Smoking cessation data after six months or more were available for 35,969 participants. We examined a range of Internet interventions, from a low intensity intervention, for example providing participants with a list of websites for smoking cessation, to intensive interventions consisting of Internet‐, email‐ and mobile phone‐delivered components. We classed interventions as tailored or interactive, or both. Tailored Internet interventions differed in the amount of tailoring, from multimedia components to personalised message sources. Some interventions also included Internet‐based counselling or support from nurses, peer coaches or tobacco treatment specialists. Recent trials incorporated online social networks, such as Facebook, Twitter, and other online forums. Key results In combined results, Internet programmes that were interactive and tailored to individual responses led to higher quit rates than usual care or written self‐help at six months or longer. Quality of evidence There were not many trials conducted in younger people. More trials are needed to determine the effect on Internet‐based methods to aid quitting in youth and young adults. Results should be interpreted with caution, as we rated some of the included studies at high risk of bias, and for most outcomes the quality of evidence was moderate or low.
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              E-learning in medical education in resource constrained low- and middle-income countries

              Background In the face of severe faculty shortages in resource-constrained countries, medical schools look to e-learning for improved access to medical education. This paper summarizes the literature on e-learning in low- and middle-income countries (LMIC), and presents the spectrum of tools and strategies used. Methods Researchers reviewed literature using terms related to e-learning and pre-service education of health professionals in LMIC. Search terms were connected using the Boolean Operators “AND” and “OR” to capture all relevant article suggestions. Using standard decision criteria, reviewers narrowed the article suggestions to a final 124 relevant articles. Results Of the relevant articles found, most referred to e-learning in Brazil (14 articles), India (14), Egypt (10) and South Africa (10). While e-learning has been used by a variety of health workers in LMICs, the majority (58%) reported on physician training, while 24% focused on nursing, pharmacy and dentistry training. Although reasons for investing in e-learning varied, expanded access to education was at the core of e-learning implementation which included providing supplementary tools to support faculty in their teaching, expanding the pool of faculty by connecting to partner and/or community teaching sites, and sharing of digital resources for use by students. E-learning in medical education takes many forms. Blended learning approaches were the most common methodology presented (49 articles) of which computer-assisted learning (CAL) comprised the majority (45 articles). Other approaches included simulations and the use of multimedia software (20 articles), web-based learning (14 articles), and eTutor/eMentor programs (3 articles). Of the 69 articles that evaluated the effectiveness of e-learning tools, 35 studies compared outcomes between e-learning and other approaches, while 34 studies qualitatively analyzed student and faculty attitudes toward e-learning modalities. Conclusions E-learning in medical education is a means to an end, rather than the end in itself. Utilizing e-learning can result in greater educational opportunities for students while simultaneously enhancing faculty effectiveness and efficiency. However, this potential of e-learning assumes a certain level of institutional readiness in human and infrastructural resources that is not always present in LMICs. Institutional readiness for e-learning adoption ensures the alignment of new tools to the educational and economic context.
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                Author and article information

                Journal
                Tob Induc Dis
                Tob Induc Dis
                TID
                Tobacco Induced Diseases
                European Publishing on behalf of the International Society for the Prevention of Tobacco Induced Diseases (ISPTID)
                2070-7266
                1617-9625
                07 May 2020
                2020
                : 18
                : 40
                Affiliations
                [1 ]European Network for Smoking and Tobacco Prevention, Brussels, Belgium
                [2 ]Medical School, University of Crete, Heraklion, Greece
                [3 ]Division of Prevention and Rehabilitation, University of Ottawa Heart Institute, Ottawa, Canada
                [4 ]Faculty of Medicine, University of Ottawa, Ottawa, Canada
                [5 ]Department of Health Care, Faculty of Public Health, University ‘Ismail Qemali’ Vlore, Vlora, Albania
                [6 ]Institute of Leadership and Healthcare Management, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
                [7 ]University of Medicine and Pharmacy ‘Grigore T. Popa’ Iasi, Iasi, Romania
                [8 ]AER PUR Romania, Bucharest, Romania
                [9 ]Kosovo Advocacy and Development Center, Pristina, Kosovo
                [10 ]Turpanjian School of Public Health, American University of Armenia, Yerevan, Armenia
                [11 ]Macedonian Respiratory Society, Skopje, North Macedonia
                [12 ]Comité Nacional de Prevención del Tabaquismo, Madrid, Spain
                [13 ]Tobacco Control Alliance of Georgia, Tbilisi, Georgia
                [14 ]University of Cantabria, Santander, Spain
                [15 ]Foundation ‘Smart Health – Health in 3D’, Warsaw, Poland
                [16 ]Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
                [17 ]Department of Public Health and Infectious Diseases, Sapienza University, Rome, Italy
                [18 ]Società Italiana di Tabaccologia (SITAB), Rome, Italy
                [19 ]Slovenian Coalition for Public Health, Environment and Tobacco Control, Maribor, Slovenia
                [20 ]Institute of Public Health of Serbia ‘Dr Milan Jovanović Batut’, Belgrade, Serbia
                [21 ]Kyiv Health Center, Kyiv, Ukraine
                [22 ]George D. Behrakis Research Laboratory, Athens, Greece
                [23 ]Hellenic Cancer Society, Athens, Greece
                [24 ]Wallionie Tabac Prevention, Brussels, Belgium
                Author notes
                CORRESPONDENCE TO Charis Girvalaki. European Network for Smoking and Tobacco Prevention, Chaussée d’Ixelles 144, 1050 Brussels, Belgium. E-mail: charis@ 123456tobcontrol.eu ORCID ID: https://orcid.org/0000-0001-6849-0972
                Article
                40
                10.18332/tid/120188
                7233524
                e8deb416-8281-4bdd-b498-b2785af3f32d
                © 2020 Girvalaki C. et al.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License.

                History
                : 13 January 2020
                : 06 April 2020
                : 07 April 2020
                Categories
                Research Paper

                Respiratory medicine
                evidence-based strategies,healthcare professionals,elearning,smoking cessation

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