BACKGROUND: The number of mobile apps that support smoking cessation is growing, indicating the potential of the mobile phone as a means to support cessation. Knowledge about the potential end users for cessation apps results in suggestions to target potential user groups in a dissemination strategy, leading to a possible increase in the satisfaction and adherence of cessation apps.OBJECTIVE: This study aimed to characterize potential end users for a specific mobile health (mHealth) smoking cessation app.METHODS: A quantitative study was conducted among 955 Dutch smokers and ex-smokers. The respondents were primarily recruited from addiction care facilities and hospitals through Web-based media via websites and forums. The respondents were surveyed on their demographics, smoking behavior, and personal innovativeness. The intention to use and the attitude toward a cessation app were determined on a 5-point Likert scale. To study the association between the characteristics and intention to use and attitude, univariate and multivariate ordinal logistic regression analyses were performed.RESULTS: The multivariate ordinal logistic regression showed that the number of previous quit attempts (odds ratio [OR] 4.1, 95% CI 2.4-7.0, and OR 3.5, 95% CI 2.0-5.9) and the score on the Fagerstrom Test of Nicotine Dependence (OR 0.8, 95% CI 0.8-0.9, and OR 0.8, 95% CI 0.8-0.9) positively correlates with the intention to use a cessation app and the attitude toward cessation apps, respectively. Personal innovativeness also positively correlates with the intention to use (OR 0.3, 95% CI 0.2-0.4) and the attitude towards (OR 0.2, 95% CI 0.1-0.4) a cessation app. No associations between demographics and the intention to use or the attitude toward using a cessation app were observed.CONCLUSIONS: This study is among the first to show that demographic characteristics such as age and level of education are not associated with the intention to use and the attitude toward using a cessation app when characteristics related specifically to the app, such as nicotine dependency and the number of quit attempts, are present in a multivariate regression model. This study shows that the use of mHealth apps depends on characteristics related to the content of the app rather than general user characteristics.
Fingerprints are widely used in forensic science for individualization purposes. However, not every fingermark found at a crime scene is suitable for comparison, for instance due to distortion of ridge detail, or when the reference fingerprint is not in the database. To still retrieve information from these fingermarks, several studies have been initiated into the chemical composition of fingermarks, which is believed to be influenced by several donor traits. Yet, it is still unclear what donor information can be retrieved from the composition of one's fingerprint, mainly because of limited sample sizes and the focus on analytical method development. It this paper, we analyzed the chemical composition of 1852 fingerprints, donated by 463 donors during the Dutch music festival Lowlands in 2016. In a targeted approach we compared amino acid and lipid profiles obtained from different types of fingerprints. We found a large inter-variability in both amino acid and lipid content, and significant differences in L-(iso)leucine, L-phenylalanine and palmitoleic acid levels between male and female donors. In an untargeted approach we used full-scan MS data to generate classification models to predict gender (77.9% accuracy) and smoking habit (90.4% accuracy) of fingerprint donors. In the latter, putatively, nicotine and cotinine are used as predictors.
MULTIFILE
Background: There is still limited evidence on the effectiveness and implementation of smoking cessation interventions for people with severe mental illness (SMI) in Dutch outpatient psychiatric settings. The present study aimed to establish expert consensus on the core components and strategies to optimise practical implementation of a smoking cessation intervention for people treated by Flexible Assertive Community Treatment (FACT) teams in the Netherlands. Design: A modified Delphi method was applied to reach consensus on three core components (behavioural counselling, pharmacological treatment and peer support) of the intervention. The Delphi panel comprised five experts with different professional backgrounds. We proposed a first intervention concept. The panel critically examined the evolving concept in three iterative rounds of 90 min each. Responses were recorded, transcribed verbatim and thematically analysed. Results: Overall, results yielded that behavioural counselling should focus on preparation for smoking cessation, guidance, relapse prevention and normalisation. Pharmacological treatment consisting of nicotine replacement therapy (NRT), Varenicline or Bupropion, under supervision of a psychiatrist, was recommended. The panel agreed on integrating peer support as a regular part of the intervention, thus fostering emotional and practical support among patients. Treatment of a co-morbid cannabis use disorder needs to be integrated into the intervention if indicated. Regarding implementation, staff’s motivation to support smoking cessation was considered essential. For each ambulatory team, two mental health care professionals will have a central role in delivering the intervention. Conclusions: This study provides insight into expert consensus on the core components of a smoking cessation intervention for people with SMI. The results of this study were used for the development of a comprehensive smoking cessation program.
In het forensisch werkveld staan drie vragen centraal. Het gaat dan om “wie is het”, “wat is er gebeurd” en “wanneer is het gebeurd”. Alle informatie die bijdraagt aan het beantwoorden van deze vragen is waardevol in zaakonderzoeken. Vaak wordt er wel een biologisch spoor gevonden, maar is er geen “match” met de databank. In dit geval kan profileringsinformatie helpen bij het zoeken naar de juiste persoon. Met profilering wordt hier bedoeld een serie stoffen, ook markers genoemd, die informatie geven over de levensstijl van mensen. De levensstijl kan bestaan uit kenmerken, voeding, gewoonten en activiteiten. Een recent voorbeeld van een profileringsmethode is het analyseren van de buitenzijde van mobiele telefoons. Door het hanteren van de telefoon laten mensen zweet en stoffen achter die gekarakteriseerd kunnen worden. Het profiel van deze stoffen geeft een beschrijving van de levensstijl van de eigenaar. In veel zaken zijn er echter geen mobiele telefoon aanwezig, maar wel andere sporen zoals haar. Daarom is er behoefte aan een methode om haar te gebruiken voor profilering. Bovendien geeft haar een indicatie van tijd en gebeurtenissen uit het verleden omdat het langzaam groeit. In principe kan er dan informatie over de drie vragen (wie, wat, wanneer) verzameld worden. Haren worden op dit moment vooral gebruikt voor het meten van drugs, alcohol gebruik, cortisol en nicotine. Er is echter behoefte aan een breder palet van stoffen dat in één keer in haar kan worden gemeten. Het doel van dit onderzoek is daarom het ontwikkelen van een methode waarmee in één analysegang een profiel van circa 15 uiteenlopende markers kan worden gemeten.
