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1.
Adicciones (Palma de Mallorca) ; 35(4): 387-396, 2023. tab, graf
Article in English, Spanish | IBECS | ID: ibc-229122

ABSTRACT

Debido a la expansión de los juegos de azar, los trastornos asociados al juego se convierten en un gran problema social con una alta relevancia para la Salud Pública, afectando tanto a adultos como a adolescentes. Los principales objetivos de este estudio fueron conocer la prevalencia de gallegos que gastaron dinero en juegos de azar en el último año y de jugadores con un trastorno de juego o de riesgo. Los datos se obtuvieron del estudio transversal realizado en 2017 por el Sistema de Información sobre Conductas de Riesgo (SICRI). El SICRI se basa en la realización anual de encuestas telefónicas a la población gallega residente que tiene al menos 16 años de edad con la muestra equidistribuida en 12 meses. Un total de 7.841 participantes fueron seleccionados mediante un muestreo aleatorio estratificado. Con el objetivo de estimar la prevalencia de trastorno de juego o de riesgo se utilizó el cuestionario South Oaks Gambling Screen (SOGS) de Lesieur y Blume. Se estimó la prevalencia de juego y jugadores con un trastorno de juego o juego de riesgo y se ajustaron modelos de regresión para identificar las variables asociadas al trastorno de juego o juego de riesgo. De la población gallega de 16 años en adelante, el 58,1% (IC 95%: 57,0-59,2) gastó dinero en juegos de azar en los 12 meses previos a la realización del estudio, siendo la prevalencia de jugadores más alta en los hombres (64,6% vs. 52,2%) en todos los grupos de edad. La prevalencia de trastorno de juego o juego de riesgo en la población es del 1,6% (IC 95%: 1,3-1,9), siendo más alta entre los hombres y en los jugadores más jóvenes. Las prevalencias obtenidas señalan al juego como un importante problema de Salud Pública, siendo los varones jóvenes los que tienen un mayor riesgo de desarrollar un problema asociado al juego. (AU)


Due to the increase in gambling, gambling disorders have become a major social problem of importance for public health, affecting both adults and adolescents. The main objectives of this study were to assess the prevalence of the Galician population who spent money on gambling in the last year and the prevalence of people with, or at risk of, gambling disorder. Data was obtained from a cross-sectional survey carried out in 2017 by the Galician Information System on Risk Behaviors (SICRI). The SICRI conducts annual telephone surveys of Galician residents who were at least 16 years of age, with the sample equidistributed over a 12-month period. A total of 7,841 participants were selected using stratified random sampling. In order to estimate the prevalence of gambling disorder or at-risk gambling, The South Oaks Gambling Screen (SOGS) questionnaire by Lesieur and Blume was applied. The prevalence of gambling and having or being at risk of gambling disorder was estimated and regression models were adjusted to identify variables associated with gambling disorder or being at risk. Of the Galician population aged 16 years and older, 58.1% (95% CI: 57.0-59.2) spent money on gambling in the 12 months previous to this study, with the highest prevalence of gambling found in men (64.6% vs. 52.2%) in all age groups. The prevalence of gambling disorder or at-risk gambling at the population level is 1.6% (95% CI 1.3-1.9), and is higher among men and younger gamblers. The prevalence obtained signals to gambling as a major public health concern, with young males being at greater risk of developing a gambling problem. (AU)


Subject(s)
Humans , Male , Female , Adolescent , Young Adult , Adult , Middle Aged , Aged , Aged, 80 and over , Gambling/prevention & control , Gambling/psychology , Public Health , Addiction Medicine/statistics & numerical data , Spain , Cross-Sectional Studies , Prevalence , Surveys and Questionnaires
2.
Acad Med ; 95(9S A Snapshot of Medical Student Education in the United States and Canada: Reports From 145 Schools): S5-S14, 2020 09.
Article in English | MEDLINE | ID: mdl-33626633

ABSTRACT

Medical school curricula have evolved from 2010 to 2020. Numerous pressures and influences affect medical school curricula, including those from external sources, academic medical institutions, clinical teaching faculty, and undergraduate medical students. Using data from the AAMC Curriculum Inventory and the LCME Annual Medical School Questionnaire Part II, the nature of curriculum change is illuminated. Most medical schools are undertaking curriculum change, both in small cycles of continuous quality improvement and through significant change to curricular structure and content. Four topic areas are explored: cost consciousness, guns and firearms, nutrition, and opioids and addiction medicine. The authors examine how these topic areas are taught and assessed, where in the curriculum they are located, and how much time is dedicated to them in relation to the curriculum as a whole. When examining instructional methods overall, notable findings include (1) the decrease of lecture, although lecture remains the most used instructional method, (2) the increase of collaborative instructional methods, (3) the decrease of laboratory, and (4) the prevalence of clinical instructional methods in academic levels 3 and 4. Regarding assessment methods overall, notable findings include (1) the recent change of the USMLE Step 1 examination to a pass/fail reporting system, (2) a modest increase in narrative assessment, (3) the decline of practical labs, and (4) the predominance of institutionally developed written/computer-based examinations and participation. Among instructional and assessment methods, the most used methods tend to cluster by academic level. It is critical that faculty development evolves alongside curricula. Continued diversity in the use of instructional and assessment methods is necessary to adequately prepare tomorrow's physicians. Future research into the life cycle of a curriculum, as well optional curriculum content, is warranted.


Subject(s)
Curriculum/trends , Education, Medical, Undergraduate/methods , Faculty, Medical/standards , Schools, Medical/history , Academic Medical Centers/organization & administration , Addiction Medicine/education , Addiction Medicine/statistics & numerical data , Analgesics, Opioid , Canada/epidemiology , Costs and Cost Analysis/economics , Education, Medical, Undergraduate/trends , Educational Measurement/methods , Firearms , History, 21st Century , Humans , Nutritional Sciences/education , Nutritional Sciences/statistics & numerical data , Schools, Medical/trends , Students, Medical/statistics & numerical data , Surveys and Questionnaires , United States/epidemiology
3.
JMIR Mhealth Uhealth ; 7(6): e13301, 2019 06 07.
Article in English | MEDLINE | ID: mdl-31237841

ABSTRACT

BACKGROUND: Most evidence-based practices (EBPs) do not find their way into clinical use, including evidence-based mobile health (mHealth) technologies. The literature offers implementers little practical guidance for successfully integrating mHealth into health care systems. OBJECTIVE: The goal of this research was to describe a novel decision-framing model that gives implementers a method of eliciting the considerations of different stakeholder groups when they decide whether to implement an EBP. METHODS: The decision-framing model can be generally applied to EBPs, but was applied in this case to an mHealth system (Seva) for patients with addiction. The model builds from key insights in behavioral economics and game theory. The model systematically identifies, using an inductive process, the perceived gains and losses of different stakeholder groups when they consider adopting a new intervention. The model was constructed retrospectively in a parent implementation research trial that introduced Seva to 268 patients in 3 US primary care clinics. Individual and group interviews were conducted to elicit stakeholder considerations from 6 clinic managers, 17 clinicians, and 6 patients who were involved in implementing Seva. Considerations were used to construct decision frames that trade off the perceived value of adopting Seva versus maintaining the status quo from each stakeholder group's perspective. The face validity of the decision-framing model was assessed by soliciting feedback from the stakeholders whose input was used to build it. RESULTS: Primary considerations related to implementing Seva were identified for each stakeholder group. Clinic managers perceived the greatest potential gain to be better care for patients and the greatest potential loss to be cost (ie, staff time, sustainability, and opportunity cost to implement Seva). All clinical staff considered time their foremost consideration-primarily in negative terms (eg, cognitive burden associated with learning a new system) but potentially in positive terms (eg, if Seva could automate functions done manually). Patients considered safety (anonymity, privacy, and coming from a trusted source) to be paramount. Though payers were not interviewed directly, clinic managers judged cost to be most important to payers-whether Seva could reduce total care costs or had reimbursement mechanisms available. This model will be tested prospectively in a forthcoming mHealth implementation trial for its ability to predict mHealth adoption. Overall, the results suggest that implementers proactively address the cost and burden of implementation and seek to promote long-term sustainability. CONCLUSIONS: This paper presents a model implementers may use to elicit stakeholders' considerations when deciding to adopt a new technology, considerations that may then be used to adapt the intervention and tailor implementation, potentially increasing the likelihood of implementation success. TRIAL REGISTRATION: ClinicalTrials.gov NCT01963234; https://clinicaltrials.gov/ct2/show/NCT01963234 (Archived by WebCite at http://www.webcitation.org/78qXQJvVI).


Subject(s)
Addiction Medicine/methods , Addiction Medicine/standards , Addiction Medicine/statistics & numerical data , Evidence-Based Practice/methods , Evidence-Based Practice/standards , Evidence-Based Practice/statistics & numerical data , Female , Health Promotion/methods , Health Promotion/standards , Health Promotion/statistics & numerical data , Humans , Male , Middle Aged , Primary Health Care/methods , Primary Health Care/standards , Primary Health Care/statistics & numerical data , Retrospective Studies , Telemedicine/methods , Telemedicine/standards , Telemedicine/statistics & numerical data
4.
Addict Sci Clin Pract ; 14(1): 18, 2019 05 01.
Article in English | MEDLINE | ID: mdl-31039821

ABSTRACT

BACKGROUND: Ontario patients on opioid agonist treatment (OAT) are often prescribed methadone instead of buprenorphine, despite the latter's superior safety profile. Ontario OAT providers were surveyed to better understand their attitudes towards buprenorphine and potential barriers to its use, including the induction process. METHODS: We used a convenience sample from an annual provincial conference to which Ontario physicians who are involved with OAT are invited. RESULTS: Based on 85 survey respondents (out of 215 attendees), only 4% of Ontario addiction physicians involved in OAT routinely used unobserved "home" buprenorphine induction: 59% of physicians felt that unobserved induction was risky because it was against "the guidelines" and 66% and 61% respectively believed that unobserved "home" induction increased the risk of diversion and of precipitated withdrawal. CONCLUSIONS: Ontario addiction physicians largely report following the traditional method of bringing in patients for observed in-office buprenorphine induction: they expressed fear of precipitated withdrawal, diversion, and going against clinical guidelines. The hesitance in using unobserved induction may explain, in part, Ontario's reliance on methadone.


Subject(s)
Buprenorphine/therapeutic use , Narcotics/therapeutic use , Opiate Substitution Treatment/methods , Opioid-Related Disorders/drug therapy , Practice Patterns, Physicians'/statistics & numerical data , Addiction Medicine/standards , Addiction Medicine/statistics & numerical data , Attitude of Health Personnel , Buprenorphine/administration & dosage , Cross-Sectional Studies , Female , Health Knowledge, Attitudes, Practice , Humans , Male , Methadone/therapeutic use , Narcotics/administration & dosage , Ontario , Practice Guidelines as Topic
5.
Fam Med ; 49(7): 537-543, 2017 Jul.
Article in English | MEDLINE | ID: mdl-28724151

ABSTRACT

BACKGROUND AND OBJECTIVES: Substance use disorder (SUD) is a widespread problem but physicians may feel inadequately prepared to provide addiction care. We sought to assess current addiction medicine curricula in US family medicine residencies (FMRs) and evaluate barriers to improving or implementing addiction medicine curricula. METHODS: Questions regarding addiction medicine training were added to the December 2015 Council of Academic Family Medicine Educational Research Alliance (CERA) survey to US FMR program directors to evaluate each FMR's curriculum, potential workforce production, perceived barriers to improving or implementing curricula and faculty training in addiction medicine. RESULTS: Of 461 FMR directors, 227 (49.2%) responded; 28.6% reported a required addiction medicine curricula. Regional variations of having a required curriculum ranged from 41.3% in the Northeast to 20.0% in the South (P=0.07). Of residencies, 31.2% had at least one graduate obtain a buprenorphine prescription waiver in the past year and 8.6% had at least one graduate pursue an addiction medicine fellowship in the past 5 years. Lack of faculty expertise was the most commonly cited barrier to having a curriculum, with only 36.2% of programs having at least one buprenorphine waivered faculty member, 9.4% an addiction medicine board certified faculty, and 5.5% a fellowship trained faculty. CONCLUSIONS: Few FMRs have addiction medicine curricula and most graduates do not seek additional training. Multifaceted efforts, including developing model national curricula, training existing faculty, and recruiting addiction trained faculty, may improve addiction medicine training in family medicine residencies to better address the growing SUD epidemic.


Subject(s)
Addiction Medicine/statistics & numerical data , Curriculum , Family Practice/education , Internship and Residency , Addiction Medicine/education , Education, Medical, Graduate , Humans , Retrospective Studies , Surveys and Questionnaires
6.
J Rural Health ; 33(1): 102-109, 2017 01.
Article in English | MEDLINE | ID: mdl-26987797

ABSTRACT

BACKGROUND: Opioid misuse is a large public health problem in the United States. Residents of rural areas and American Indian (AI) reservation/trust lands represent traditionally underserved populations with regard to substance-use disorder therapy. PURPOSE: Assess differences in the number of opioid agonist therapy (OAT) facilities and physicians with Drug Addiction Treatment Act (DATA) waivers for rural versus urban, and AI reservation/trust land versus non-AI reservation/trust land areas in Washington State. METHODS: The unit of analysis was the ZIP code. The dependent variables were the number of OAT facilities and DATA-waivered physicians in a region per 10,000 residents aged 18-64 in a ZIP code. A region was defined as a ZIP code and its contiguous ZIP codes. The independent variables were binary measures of whether a ZIP code was classified as rural versus urban, or AI reservation/trust land versus non-AI reservation/trust land. Zero-inflated negative binomial regressions with robust standard errors were estimated. RESULTS: The number of OAT clinics in a region per 10,000 ZIP-code residents was significantly lower in rural versus urban areas (P = .002). This did not differ significantly between AI reservation/trust land and non-AI reservation/trust land areas (P = .79). DATA-waivered physicians in a region per 10,000 ZIP-code residents was not significantly different between rural and urban (P = .08), or AI reservation/trust land versus non-AI reservation/trust land areas (P = .21). CONCLUSIONS: It appears that the potential for Washington State residents of rural and AI reservation areas to receive OAT is similar to that of residents outside of those areas; however, difficulties in accessing therapy may remain, highlighting the importance of expanding health care insurance and providing support for DATA-waivered physicians.


Subject(s)
Geographic Mapping , Health Services Accessibility/standards , Indians, North American/statistics & numerical data , Substance Abuse Treatment Centers/statistics & numerical data , Substance-Related Disorders/therapy , Addiction Medicine/statistics & numerical data , Addiction Medicine/trends , Adolescent , Adult , Female , Humans , Male , Middle Aged , Opioid-Related Disorders , Poisson Distribution , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , Washington
7.
Addiction ; 111(12): 2230-2247, 2016 12.
Article in English | MEDLINE | ID: mdl-27347846

ABSTRACT

BACKGROUND AND AIMS: It has been proposed that more use should be made of Bayes factors in hypothesis testing in addiction research. Bayes factors are the ratios of the likelihood of a specified hypothesis (e.g. an intervention effect within a given range) to another hypothesis (e.g. no effect). They are particularly important for differentiating lack of strong evidence for an effect and evidence for lack of an effect. This paper reviewed randomized trials reported in Addiction between January and June 2013 to assess how far Bayes factors might improve the interpretation of the data. METHODS: Seventy-five effect sizes and their standard errors were extracted from 12 trials. Seventy-three per cent (n = 55) of these were non-significant (i.e. P > 0.05). For each non-significant finding a Bayes factor was calculated using a population effect derived from previous research. In sensitivity analyses, a further two Bayes factors were calculated assuming clinically meaningful and plausible ranges around this population effect. RESULTS: Twenty per cent (n = 11) of the non-significant Bayes factors were < â…“ and 3.6% (n = 2) were > 3. The other 76.4% (n = 42) of Bayes factors were between ⅓ and 3. Of these, 26 were in the direction of there being an effect (Bayes factor > 1 and < 3); 12 tended to favour the hypothesis of no effect (Bayes factor < 1 and > â…“); and for four there was no evidence either way (Bayes factor = 1). In sensitivity analyses, 13.3% of Bayes Factors were < â…“ (n = 20), 62.7% (n = 94) were between ⅓ and 3 and 24.0% (n = 36) were > 3, showing good concordance with the main results. CONCLUSIONS: Use of Bayes factors when analysing data from randomized trials of interventions in addiction research can provide important information that would lead to more precise conclusions than are obtained typically using currently prevailing methods.


Subject(s)
Addiction Medicine/statistics & numerical data , Bayes Theorem , Biomedical Research/statistics & numerical data , Randomized Controlled Trials as Topic/statistics & numerical data , Humans , Mathematics
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