Smoking Cessation in Hospitalized Patients Using an App

NCT ID: NCT04502004

Last Updated: 2020-08-06

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: NA
• Total Enrollment: 116 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2019-11-14
• Study Completion Date: 2021-07-31

Brief Summary

This study generates a new proposal for intensive intervention following the recommendations to quit smoking in hospitalized patients, providing intensive, accessible and individualized treatment, as well as long-term follow-up, thanks to new technologies. The main advantage that mhealth can bring to public health is cost-effectiveness, scalability and wide reach compared to traditional treatments. Rapid diffusion and remote outreach can impact traditional treatment programs, reduce waiting lists for tobacco visits, and increase quit rates, as well as reduce barriers to accessing smoking cessation programs, by location or time conflicts. Since the possibility of continuous face-to-face support is very limited, health interventions carried out through a smartphone can help avoid this situation. The study by Finkelstein and Me Cha (2016) justifies this line of intervention and solves the doubt about the feasibility of using the mobile phone to quit smoking in hospitalized patients, highlighting its usefulness for all patients regadless their age, gender, computer skills, income and educational level.

-Can an App apply an intensive intervention to stop smoking in the hospitalized patient?

Detailed Description

Tobacco use is the leading cause of preventable disease and death in our country. In the world it is still one of the most serious public health problems due to its morbidity and mortality. Smoking causes approximately one in ten deaths and it is expected that in 2030 that figure will increase to one in six, which will mean around 7-8 million deaths each year.

Furthermore, quitting smoking is the most effective factor in reducing these deaths. Patients with heart disease reduce sudden death and its mortality by 36% when they stop smoking. Likewise, the relative risk of stroke is reduced by 50% when quitting. For all these reasons, quitting smoking is the most cost-effective treatment compared to other interventions.

The National Health Survey indicates that the reductions in tobacco consumption due to "natural tendency" are very slow. As an example, if 24% of the population over 15 years of age smoked daily in 2012, five years later 22% smoked. To control this "epidemic", the World Health Organization requires several actions: Prevent young people from starting to smoke, protect non-smokers from air polluted by tobacco smoke and help smokers to quit. smoking habit.

The Clinical Practice Guidelines (CPG) indicate a variety of treatments that have been shown to be effective in quitting smoking. The CPG "National Institute for Health and Care Excellence (NICE) Public Health Guideline" -PH10- (2008), updated in 2013, names the following treatments in the out-of-hospital setting: offer brief advice (min. 10 minutes); group or individual behavioral therapies (such as Cognitive-Behavioral Therapy (CBT)), alone or combined with drugs (at least 4 weeks before the date participants are going to quit); pharmacotherapy (varenicline, bupropion, or nicotine replacement therapy), alone or in combination with psychological therapy; self-help material (written or in electronic format); advice hotline or TV or radio programs.

Smokers are forced to abruptly quit on the day they enter a hospital, given that Law 42/2010 prohibits tobacco consumption not only in the in-hospital physical space, but also in the external environment. And, although there are unreliable data, it has been estimated that between 15% and 27% of patients admitted to a hospital in Spain are smokers.

With the goal of helping smokers to quit, hospitalization is a good time to do so, since the patient is in a smoke-free place and admission can increase the perception of threat to their health. For this reason, the investigator may find that there is a greater receptiveness to messages to quit smoking, the so-called "learning moment", and health professionals must take advantage of this opportunity and make use of the possibilities available to us.

Following these recommendations, the Spanish Society of Pneumology and Thoracic Surgery (SEPAR) has recently published the regulations on the treatment of smoking in hospitalized patients, which offer clear guidelines for considering the process of cessation in hospitalized smokers. In it they indicate the general guidelines of brief intervention during the care practice towards the smoker known as 5 "As" (Ask, Advise, Assess, Assist, Arrange) that is (ask, advise, evaluate, help and plan). In addition to highlighting that the intervention on smoking in hospitalized patients is more effective when done in a complementary and shared way among the different professionals who care for the subject. At the same time, a drug treatment of the type Nicotine replacement therapy (NRT) is always recommended, combined with behavioral therapy with intensive support (greater than or equal to 4 sessions lasting more than or equal to 15 minutes each) during admission. Highlighting the importance of continuity of treatment for at least one month after hospital discharge and with follow-ups at one, three and six months.

In summary, asking patients if they are willing to quit, providing medications that help along with psychological support, and counseling everyone who says they are willing to quit smoking has been shown to be effective, especially if there is follow-up at discharge. Finding statistically significant differences if the follow-up is followed at 6 months and a year after discharge hospital; as well as the greater the intensity of the advice given.

Despite this evidence and the support of clinical practice guidelines, the level of application in the hospital is low; interventions that have been shown to be effective in clinical trials have not been implemented in routine clinical practice in the hospital.

Different ways are proposed to prolong health intervention beyond hospitalization, such as emails, SMS messages or proactive telephone contact. All these forms increase the effectiveness of the interventions offered and the effectiveness of these treatments is related to the duration of the call or the number of messages received, the more contact the more effective.

New Information and Communication Technologies (TICs) allow smoking cessation therapies to be applied through applications on mobile devices (Apps), some of which alone have proven to be effective in addiction therapy.

Aim

-The overall aim of this study is to determine the efficacy of an intensive intervention based on CBT applied through a App, for smoking cessation during hospitalization compared to patients receiving conventional clinical practice.

Hypothesis:

-Patients who receive an intensive CBT intervention thanks to the support of a mobile application "Application" during admission, are more successful in quitting smoking compared to those who receive conventional treatment.

Design

This is a randomized controlled trial (RCT), a study design that randomly assigns participants into an Experimental Group (EG) or a Control Group (CG).

two-branch clinical trial in which the group will be randomly assigned using a computer program, in balanced blocks of 4 patients (2 patients from each group in each block).

The CG will follow routine clinical practice. Currently, at the Public Hospital Son LLatzer(HSLL) there is no established protocol in the cardiology, pulmonology and Intensive Care Unit, even so, the CG will at least receive the recommendations of the Clinical Practice Guidelines which consist of: advice on smoking cessation smoking, leaflet with information (tobacco components, treatments to reduce withdrawal syndrome) and follow-up after discharge by the hospital tabacco unit: at one month, at three months, at six months and at one year.

The EG will receive codes to download the App "NoFumo+" that offer a CBT program. Follow-up after discharge by the hospital tabacco unit: at one month, at six months and at one year.

Participants Study subjects-hospitalized: patients of both sexes smokers, over 18 years, hospitalized, the investigators define hospitalized as; admission of a patient to the hospital for a minimum stay of one night. The study will be carried out in the cardiology, pulmonology and intensive care units of the HSLL.

Sample size determination

Accepting an alpha risk of 0.05 and a beta risk of 0.2 in a bilateral contrast, 116 subjects is required (to be splitted between the two group conditions) to detect statistical significant differences between both groups, considering that 20% of the control group will quit smoking compared to 40% of the intervention group. A follow-up loss rate of 30% has been estimated.

The assignment of the patient will be carried out by the Main Investigator (MI), once the patient's consent has been obtained, through a specific program available online. This program has been designed so that randomization so that the patient's identification data is entered first and the assigned group is subsequently displayed. Once the patient's identification data has been entered, it will not be possible to change any data or change the group to which it has been assigned, and the patient's data and the assigned group will be recorded.

Study development

The BIT Foundation will develop an App for the study whose main objective will be to have the treatment available at all times, strengthen adherence and provide follow-up to patients in the program. The app will have the name "NoFumo+", it can be downloaded through a username and password only for patients participating in the study. NoFumo+, in addition to having information about the contents of the guide in digital format, will allow access to the contents sequentially, once they have passed the previous session. That is, the application will support and facilitate the patient a continuous monitoring of their treatment for smoking cessation. NoFumo+ will have:

• Alerts remember to start daily work.
• Daily assessment of changes in craving.
• Participants can consult additional information, through links, to expand information.
• It will inform of the health benefits of staying abstinent. NoFumo+ will calculate from the day of the discharge (days that it has been abstinent), as well as the monetary savings and will report the health benefits.
• Participants can consult via email or via chat. The App will have direct mail with the health-research team or via chat.
• Social support: participants will have a chat to be able to be in contact with other people who are using the App in the same situation as them, hospitalized or after discharge with a follow-up of up to one year.
• The participants will receive motivational messages. The App will send the messages in text format and / or in animated image format of type GIFT, acronym in English for (Graphics Interchande Format).

The NoFumo+ application will consist of a client app, which resides on the patient's mobile phone, and a server, which resides on a central computer. NoFumo+ will in no case keep information about the identity of the patients.

The user App will store a user code, generated randomly, and the password associated with said user code. The monitoring information of each patient's program will be saved on the server and will be linked to the patient's user code. The relationship between the user code and the patient to which it belongs cannot be established by any means based on the data present in the application. Said relationship will only be in the hands of the main investigator, registered outside the application (for example, within the patient's medical history) and in the manner he deems appropriate, following the confidentiality rules established in these cases.

At the time of the creation of the user account, the patient will be informed in relation to their rights regarding the treatment and confidentiality of their data. The data will be processed in accordance with the General Data Protection Regulation of the European Commission, which is mandatory.

Study variables

Main variables

The dependent variable will be the objective measure of tobacco abstinence from the carbon monoxide level, abstinent if CO≤6 at 6 and 12 months of follow-up. Carried out using a co-oximeter (Mini Smokerlyzer, Bedfont instruments, Sittingbourne, Kent, UK).

The independent variable will be membership in the EG or CG group.

Independent secondary variables

• Sociodemographic variables (factors related to the patient): age, sex, marital status, educational level, employment situation.
• Alcohol consumption (UBE)
• Current pharmacological treatment.
• Smoking history: Age of onset of tobacco use, type of tobacco, use (pack / year), presence of smokers at home. Previous attempts to quit tobacco: (number of attempts, method and duration of withdrawal period).
• Clinical diagnosis.
• Reason for admission
• Level of motivation to quit smoking, measured by the "Richmond Motivation Test".
• Nicotine dependence level, measured using the "Fagerstrom Questionnaire".
• Trait anxiety and state anxiety measured by the "State or Trait Anxiety Inventory" (STAI-E/R).
• Symptoms of depression measured by Beck Depression Inventory II (BDI-I).
• Measure of Anger Trait / State, measured by Anger Inventory (STAXI).
• Identification of disorders related to Alcohol Use measured by the AUDIT questionnaire.
• Short personality questionnaire (TIPY).
• Comorbidities / survival predictor: Charlson index.
• Adherence to the intervention through the use of the App: frequency: number of times participants connect to the App, duration: the time are connected, completion of the proposed interactive activities and evaluations carried out.

Statistical analysis

Normality tests and graphs will be used to determine if the variables follow a normal distribution.

Variables with normal distribution are expressed as mean, standard deviation, and those without normal distribution are expressed as median and interquartile range.

To evaluate the differences between groups, the student's t test or the Mann-Whitney U test will be used for the quantitative variables; and the chi-square test or Fisher's exact test for qualitative variables.

The correlations will be examined by the Spearman or Pearson rank correlation. To evaluate intra-group differences, paired or related samples tests will be used. A value of p <0.05 will be considered an indicator of a significant difference.

The CART algorithm, acronym for Classification And Regression Trees, will be used to obtain classification models (binary trees) on the adherence of the subjects to the treatment program, as well as the success of the program. In this way we can see if there is a smoking profile that can benefit more from this treatment.

Development of the study: work plan and data collection

The doctor who admits the patient in one of the three units of this study, collects in his medical history that he is an active smoker and will directly ask him if he is interested in treating his nicotine addiction during this admission.

-If the patient wants to take advantage of the income to quit smoking . Participants will be presented with the study and if participants want to participate, participants will initiate the following steps necessary for this investigation:

Inclusion visit (V0)

• Participants will be informed about the different aspects of the study and participants will be given the Patient Information Document.

• The informed consent form will be delivered to both groups.

• The PI that will contact him will be informed

1. st Visit (V1)

The MI:

• Participants will be assigned, with a randomized computer program, to one of the two treatment groups (EG and CG).
• Depending on the EG or CG treatment group, the following intervention will be carried out:

1. - Intervention in EG: The data collection begins, will carry out CO and a dossier with questionnaires will be delivered. The Hospital tobacco unit will start the treatment, a username and password will be provided to download the App and an explanation of how it works.

2. -Intervencion in CG: The Data Collection Notebook begins, will carry out CO and will deliver a dossier with questionnaires. Participants will be given regular treatment without the App.

2. th Visit (V2)

The selected EG patient will receive an App notification every day to work on their addiction. The treatment will last 30 days in total, divided into 5 phases, each consisting of three cells, lasting 1 week.

CG patients will follow the usual treatment, including the advice of places or sessions that they can attend to continue with the help of either Basic Health Units or the hospital tobacco service in the case of HSLL.

Follow-up visits (V3)

• The EG will be summoned by phone at the Hospital Tobacco service to carry out CO and assess treatment (follow-up interview).
• The CG will carry out a telephone intervention; if they remain abstinent, it will be cited by the hopital tobacco service for CO.

Follow-up visits will be carried out in both groups the first month after completing the daily treatment of the App, six months and one year after withdrawal.

Ethical Considerations

Before the start of the study, the project will be presented to the Ethical and Research Committee of the Balearic Islands (CEI). In the case of HSLL, to the Research Commission of the hospital. Health professionals participating in the study will sign a confidentiality document. Before starting any study procedure, the informed consent of each patient must be obtained. The recommendations contained in the Declaration of Helsinki and the Organic Law 15/1999 on Data Protection will be followed.

This study will fully adhere to the standards of good clinical practice that any clinical study must follow. All participating researchers will receive training to standardize criteria and they will insist on the dissemination and understanding of the aforementioned standards. The consent will be kept with the documents of the researcher's study.

During the trial, the investigators must immediately notify the CEI of any Serious Adverse Event allegedly related to the intervention within the time limits established by current regulations. Likewise, the CEI must be notified of deviations from the protocol; new information that may affect the safety of the subjects or the performance of the test and the information of the test follow-up as required by the CEI. For any reason to withdraw from the study, affected patients should continue with the most appropriate treatment, in the judgment of the healthcare staff attending them. If the eligible subject requires a reflection time to confirm participation in the study, they will be granted a period of 24 hours during which they will receive the usual treatment.

Limitations

The investigators found a limitation at the end of the study, due to the difficulty of applying the treatment to all patients admitted to the hospital, the possibility of face-to-face monitoring and co-oximetry due to lack of resources / personnel.

On the other hand, patients admitted to the Intensive Care Unit could be a special group due to the critical episode experienced during admission. Having the critically ill patient undergo intensive treatment at that time, while still in the Intensive CareUnit, could lead to a greater predisposition to quit smoking. The investigators want to reduce this bias by randomizing the patients into different groups, thus there would have a similar number in both groups. Furthermore, the investigators could assess the motivating value of the traumatic experience and its influence on adherence and temporal generalization.

Due to this intervention, it could improve the usual care by the responsible physician, when asked about the participation of the study.

Scientific relevance and applicability

This study aims to provide more data to the scientific community on the importance of performing a combined and intensive treatment to help quit smoking in smoking patients, taking advantage of their hospital admission.

With the help of TICs, in this case the App, the investigators try to improve its applicability to be able to proactively carry out intense treatment (frequency and time spent on smoking cessation)

If this program were to prove effective, it could be applied to all patients hospitalized in other hospital services to be treated for nicotine dependence and the App will be available to all patients free of charge.

Conditions

Hospitalized Smokers; CBT; Smoking Cessation; Mhealth

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: FACTORIAL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

Control Group (CG)

Receive the recommendations of the Clinical Practice Guidelines which consist of: advice on smoking cessation smoking, leaflet with information (tobacco components, treatments to reduce withdrawal syndrome).

Follow-up after discharge by the hospital tabacco service: at one month, at three months, at six months and at one year.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Experimental Group (EG)

Receive codes to download the App "NoFumo+" . Is a mHealth that offer a CBT program. Follow-up after discharge by the hospital tabacco service: at one month, at three months, at six months and at one year.

Group Type: EXPERIMENTAL

App for health=mhealth

Intervention Type: DEVICE

Cognitive-Behavioural Therapy and Clinical Practice Guide that recommends 5 Aes: Ask about tobacco, Advise smoking cessation, Assess tobacco consumption, Assist and Arrange (Fiore et alt., 2008)

Interventions

App for health=mhealth

Cognitive-Behavioural Therapy and Clinical Practice Guide that recommends 5 Aes: Ask about tobacco, Advise smoking cessation, Assess tobacco consumption, Assist and Arrange (Fiore et alt., 2008)

Intervention Type: DEVICE

Other Intervention Names

(NoFumo+)

Eligibility Criteria

Inclusion Criteria

• Patients over 18 years of both sexes, who sign the informed consent to participate in the study.
• Patients who register wanting to quit smoking during admission
• Active smoking patients at the time of hospital admission or ex-smokers with less than 6 months of evolution.
• Autonomous patients with the capacity to understand the treatment.
• Patients who have an Android and Iphone Smartphone, accustomed to their use sith superior operating system 5.0 or 4.0 respectively.

Exclusion Criteria

• Serious medical illness that prevents the patient from participating in the tobacco cessation intervention study.
• Ex-smoking patients of more than 6 months of evolution.
• Active patients in substance abuse.
• Patients with any current condition (medical, psychological or social) that limits the patient's participation in the study.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 70 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Hospital Son Llatzer

OTHER

Sponsor Role: collaborator

University of the Balearic Islands

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Universidad de las Islas Baleares

Palma de Mallorca, Balearic Islands, Spain

Site Status: RECRUITING

Countries

Spain

Facility Contacts

Patricia García-Pazo, Profesora

Role: primary

patricia.garcia@uib.es

609683256

Psicología

Role: backup

References

Baltaci D, Aydin LY, Alasan F, Deler MH, Karacam MS, Turker Y, Gur M, Sariguzel F. Evaluation of smoking cessation practice by physicians for hospitalized patients in a tertiary hospital. J Pak Med Assoc. 2016 Dec;66(12):1547-1553.

Reference Type: BACKGROUND

PMID: 27924963 (View on PubMed)

Becona E, Lopez-Duran A, Fernandez del Rio E, Martinez U. Changes in the profiles of smokers seeking cessation treatment and in its effectiveness in Galicia (Spain) 2001-10. BMC Public Health. 2014 Jun 17;14:613. doi: 10.1186/1471-2458-14-613.

Reference Type: BACKGROUND

PMID: 24938635 (View on PubMed)

Campos ACF, Nani ASF, Fonseca VADS, Silva EN, Castro MCS, Martins WA. Comparison of two smoking cessation interventions for inpatients. J Bras Pneumol. 2018 May-Jun;44(3):195-201. doi: 10.1590/S1806-37562017000000419.

Reference Type: BACKGROUND

PMID: 30043885 (View on PubMed)

Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. doi: 10.1016/0021-9681(87)90171-8.

Reference Type: BACKGROUND

PMID: 3558716 (View on PubMed)

Faseru B, Ellerbeck EF, Catley D, Gajewski BJ, Scheuermann TS, Shireman TI, Mussulman LM, Nazir N, Bush T, Richter KP. Changing the default for tobacco-cessation treatment in an inpatient setting: study protocol of a randomized controlled trial. Trials. 2017 Aug 14;18(1):379. doi: 10.1186/s13063-017-2119-9.

Reference Type: BACKGROUND

PMID: 28806908 (View on PubMed)

Finkelstein J, Cha EM. Using a Mobile App to Promote Smoking Cessation in Hospitalized Patients. JMIR Mhealth Uhealth. 2016 May 6;4(2):e59. doi: 10.2196/mhealth.5149.

Reference Type: BACKGROUND

PMID: 27154792 (View on PubMed)

Gram, I. T., Larbi, D., & Wangberg, S. C. (n.d.). "Papel original."

Reference Type: BACKGROUND

Haskins BL, Lesperance D, Gibbons P, Boudreaux ED. A systematic review of smartphone applications for smoking cessation. Transl Behav Med. 2017 Jun;7(2):292-299. doi: 10.1007/s13142-017-0492-2.

Reference Type: BACKGROUND

PMID: 28527027 (View on PubMed)

Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991 Sep;86(9):1119-27. doi: 10.1111/j.1360-0443.1991.tb01879.x.

Reference Type: BACKGROUND

PMID: 1932883 (View on PubMed)

Heffernan KJ, Chang S, Maclean ST, Callegari ET, Garland SM, Reavley NJ, Varigos GA, Wark JD. Guidelines and Recommendations for Developing Interactive eHealth Apps for Complex Messaging in Health Promotion. JMIR Mhealth Uhealth. 2016 Feb 9;4(1):e14. doi: 10.2196/mhealth.4423.

Reference Type: BACKGROUND

PMID: 26860623 (View on PubMed)

Hopewell S, Clarke M, Moher D, Wager E, Middleton P, Altman DG, Schulz KF; CONSORT Group. CONSORT for reporting randomized controlled trials in journal and conference abstracts: explanation and elaboration. PLoS Med. 2008 Jan 22;5(1):e20. doi: 10.1371/journal.pmed.0050020.

Reference Type: BACKGROUND

PMID: 18215107 (View on PubMed)

Jimenez Ruiz CA, de Granda Orive JI, Solano Reina S, Riesco Miranda JA, de Higes Martinez E, Pascual Lledo JF, Garcia Rueda M, Lorza Blasco JJ, Signes Costa-Minana J, Valencia Azcona B, Villar Laguna C, Cristobal Fernandez M. Guidelines for the Treatment of Smoking in Hospitalized Patients. Arch Bronconeumol. 2017 Jul;53(7):387-394. doi: 10.1016/j.arbres.2016.11.004. Epub 2016 Dec 22. English, Spanish.

Reference Type: BACKGROUND

PMID: 28017455 (View on PubMed)

Keane, L., Anderson, C., Perez, D., & Freeman, B. (2018). The Development and Evaluation of Online Smoking Cessation Services: A Narrative Literature Review. Journal of Smoking Cessation. https://doi.org/10.1017/jsc.2018.8

Reference Type: BACKGROUND

Lee M, Lee H, Kim Y, Kim J, Cho M, Jang J, Jang H. Mobile App-Based Health Promotion Programs: A Systematic Review of the Literature. Int J Environ Res Public Health. 2018 Dec 13;15(12):2838. doi: 10.3390/ijerph15122838.

Reference Type: BACKGROUND

PMID: 30551555 (View on PubMed)

Middleton ET, Morice AH. Breath carbon monoxide as an indication of smoking habit. Chest. 2000 Mar;117(3):758-63. doi: 10.1378/chest.117.3.758.

Reference Type: BACKGROUND

PMID: 10713003 (View on PubMed)

Nieto Garcia MA, Abdel-Kader Martin L, Rosado Martin MM, Carriazo Perez de Guzman A, Arias Jimenez JL. [Smoking of in-patients]. An Med Interna. 2003 Jul;20(7):351-9. Spanish.

Reference Type: BACKGROUND

PMID: 12892552 (View on PubMed)

Perula de Torres LA, Fernandez-Garcia JA, Arias-Vega R, Muriel-Palomino M, Marquez-Rebollo E, Ruiz-Moral R. [Validation of the AUDIT test for identifying risk consumption and alcohol use disorders in women]. Aten Primaria. 2005 Nov 30;36(9):499-506. doi: 10.1016/s0212-6567(05)70552-7. Spanish.

Reference Type: BACKGROUND

PMID: 16324508 (View on PubMed)

Rahmah, S., & Oktamianti, P. (2018). Smoking Cessation Clinic, Hospital's Participation in Supporting a Quit Smoking Program: A Systematic Review. https://doi.org/10.18502/kls.v4i9.3562

Reference Type: BACKGROUND

Reid ZZ, Regan S, Kelley JH, Streck JM, Ylioja T, Tindle HA, Chang Y, Levy DE, Park ER, Singer DE, Carpenter KM, Reyen M, Rigotti NA. Comparative Effectiveness of Post-Discharge Strategies for Hospitalized Smokers: study protocol for the Helping HAND 2 randomized controlled trial. BMC Public Health. 2015 Feb 7;15:109. doi: 10.1186/s12889-015-1484-0.

Reference Type: BACKGROUND

PMID: 25879193 (View on PubMed)

Renau, V., Oberst, U., Gosling, S. D., Rusiñol, J., & Chamarro, A. (2013). Translation and validation of the Ten- Item-Personality Inventory into Spanish and Catalan. Aloma, 31(2), 85-97. https://doi.org/10.1027/1015-5759/a000215

Reference Type: BACKGROUND

Rigotti NA, Clair C, Munafo MR, Stead LF. Interventions for smoking cessation in hospitalised patients. Cochrane Database Syst Rev. 2012 May 16;5(5):CD001837. doi: 10.1002/14651858.CD001837.pub3.

Reference Type: BACKGROUND

PMID: 22592676 (View on PubMed)

Rigotti NA, Regan S, Levy DE, Japuntich S, Chang Y, Park ER, Viana JC, Kelley JH, Reyen M, Singer DE. Sustained care intervention and postdischarge smoking cessation among hospitalized adults: a randomized clinical trial. JAMA. 2014 Aug 20;312(7):719-28. doi: 10.1001/jama.2014.9237.

Reference Type: BACKGROUND

PMID: 25138333 (View on PubMed)

Sanidad, M. De. (2018). Nota Técnica Encuesta Nacional de Salud . España 2017. Sanz, J. (2013). Rendimiento diagnóstico y estructura factorial del Inventario de Depresión de Beck-II ( BDI-II ) Introducción, 29, 66-75.

Reference Type: BACKGROUND

Tembo AC, Parker V. Factors that impact on sleep in intensive care patients. Intensive Crit Care Nurs. 2009 Dec;25(6):314-22. doi: 10.1016/j.iccn.2009.07.002. Epub 2009 Oct 31.

Reference Type: BACKGROUND

PMID: 19880319 (View on PubMed)

Thomas D, Abramson MJ, Bonevski B, Taylor S, Poole SG, Paul E, Weeks GR, Dooley MJ, George J. Integrating smoking cessation into routine care in hospitals--a randomized controlled trial. Addiction. 2016 Apr;111(4):714-23. doi: 10.1111/add.13239. Epub 2016 Jan 13.

Reference Type: BACKGROUND

PMID: 26597421 (View on PubMed)

Tobal, J.J.M. Casado, M.I. Cano, A, & Spielberger, C. D. (2014). STAXI-2 Inventario de Expresión de Ira Estado-Rasgo. U

Reference Type: BACKGROUND

Ubhi HK, Kotz D, Michie S, van Schayck OCP, West R. A comparison of the characteristics of iOS and Android users of a smoking cessation app. Transl Behav Med. 2017 Jun;7(2):166-171. doi: 10.1007/s13142-016-0455-z.

Reference Type: BACKGROUND

PMID: 28168609 (View on PubMed)

Ubhi HK, Michie S, Kotz D, Wong WC, West R. A mobile app to aid smoking cessation: preliminary evaluation of SmokeFree28. J Med Internet Res. 2015 Jan 16;17(1):e17. doi: 10.2196/jmir.3479.

Reference Type: BACKGROUND

PMID: 25596170 (View on PubMed)

Vidrine DJ, Frank-Pearce SG, Vidrine JI, Tahay PD, Marani SK, Chen S, Yuan Y, Cantor SB, Prokhorov AV. Efficacy of Mobile Phone-Delivered Smoking Cessation Interventions for Socioeconomically Disadvantaged Individuals: A Randomized Clinical Trial. JAMA Intern Med. 2019 Feb 1;179(2):167-174. doi: 10.1001/jamainternmed.2018.5713.

Reference Type: BACKGROUND

PMID: 30556832 (View on PubMed)

West R, Raw M, McNeill A, Stead L, Aveyard P, Bitton J, Stapleton J, McRobbie H, Pokhrel S, Lester-George A, Borland R. Health-care interventions to promote and assist tobacco cessation: a review of efficacy, effectiveness and affordability for use in national guideline development. Addiction. 2015 Sep;110(9):1388-403. doi: 10.1111/add.12998.

Reference Type: BACKGROUND

PMID: 26031929 (View on PubMed)

Westmaas JL, Bontemps-Jones J, Hendricks PS, Kim J, Abroms LC. Randomised controlled trial of stand-alone tailored emails for smoking cessation. Tob Control. 2018 Mar;27(2):136-146. doi: 10.1136/tobaccocontrol-2016-053056. Epub 2017 May 18.

Reference Type: BACKGROUND

PMID: 28522745 (View on PubMed)

Whittaker R, McRobbie H, Bullen C, Rodgers A, Gu Y. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev. 2016 Apr 10;4(4):CD006611. doi: 10.1002/14651858.CD006611.pub4.

Reference Type: BACKGROUND

PMID: 27060875 (View on PubMed)

Ylioja T, Cochran G, Chang Y, Tindle HA, Rigotti NA. Postdischarge smoking cessation in subgroups of hospitalized smokers: A latent class analysis. Subst Abus. 2017 Oct-Dec;38(4):493-497. doi: 10.1080/08897077.2017.1355870. Epub 2017 Jul 20.

Reference Type: BACKGROUND

PMID: 28727541 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Informed Consent Form

View Document

Other Identifiers

IB 3835/19 PI

Identifier Type: -

Identifier Source: org_study_id