An application of the stress-diathesis model: A review about the association between smoking tobacco, smoking cessation, and mental health

Taylor, Gemma; Treur, Jorien L.

doi:10.1016/j.ijchp.2022.100335

“…Some studies have looked into relationship between smoking and psychological diseases. Taylor et al [10] investigated the relationship between smoking, quitting smoking, and mental health. Schmidt et al [16] examined the relationship between average patterns of psychological health and average patterns of smoking using longitudinal data.…”

Section: Physical Illnessesmentioning

confidence: 99%

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Alswedani¹,

Mehmood²,

Katib³

et al. 2023

Preprint

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Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

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“…Some studies have looked into relationship between smoking and psychological diseases. Taylor et al [10] investigated the relationship between smoking, quitting smoking, and mental health. Schmidt et al [17] examined the relationship between average patterns of psychological health and average patterns of smoking using longitudinal data.…”

Section: Physical Illnessesmentioning

confidence: 99%

“…There is a significant body of research on the relationship between physical and psychological health. Studies have explored the connection between mental stress and physical diseases such as cancer, lung disease, and kidney disease [5]- [7], as well as the impact of physical conditions such as obesity and smoking on psychological health [8]- [10]. There is also research on specific psychological disorders, including depression, anxiety, stress, and post-traumatic stress disorder (PTSD) [11].…”

Section: Introductionmentioning

confidence: 99%

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Alswedani¹,

Mehmood²,

Katib³

et al. 2023

Preprint

View full text Add to dashboard Cite

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

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“…The misattribution hypothesis suggests that smokers misattribute nicotine withdrawal symptoms of stress or anxiety/depression and believe that smoking alleviates symptoms of mental health difficulties. 18 , 19 …”

Section: Introductionmentioning

confidence: 99%

“…In this qualitative investigation, we aimed to use evidence‐based models of behaviour change and behavioural intervention development 16 , 17 , 18 , 19 to explore participants' subjective experience of mechanisms of change in smoking cessation.…”

Section: Introductionmentioning

confidence: 99%

Service‐user experiences of an integrated psychological intervention for depression or anxiety and tobacco smoking in improving access to psychological therapies services: A qualitative investigation into mechanisms of change in quitting smoking

Stein

¹

,

Sawyer

²

,

Daryan

³

et al. 2022

Health Expectations

Self Cite

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Introduction High smoking prevalence leads to increased morbidity and mortality in individuals with depression/anxiety. Integrated interventions targeting both smoking and mood have been found to be more effective than those targeting smoking alone, but the mechanisms of change of these interventions have not been investigated. This qualitative study aimed to understand participants' experiences of the mechanisms underlying change in smoking behaviour following an integrated cognitive behavioural technique‐based intervention for smoking cessation and depression/anxiety. Methods This study was embedded within an ongoing randomized‐controlled acceptability and feasibility trial ( http://www.isrctn.com/ISRCTN99531779 ). Semistructured interviews were conducted with 15 IAPT service users. Data were analysed using thematic analysis. During the interviews, participants were asked open‐ended questions about their quitting experience and perception of how the intervention aided their behaviour change. Results Five themes were identified. Acquiring an increased awareness of smoking patterns : participants described an increased understanding of how smoking was contributing towards their mental health difficulty. Developing individualized strategies : participants described acquiring ‘a couple of tricks up your sleeve’ that were helpful in making smoking cessation feel more ‘manageable’. Practitioner style as ‘supportive but not lecture‐y ’: participants expressed how important the therapeutic alliance was in helping change their smoking behaviour. Importance of regular sessions : participants expressed the importance of ‘having someone that's checking in on you’. Having the opportunity to access the intervention at ‘the right time ’: participants described the intervention as the ‘push’ that they ‘needed’. Conclusions Participants identified key factors towards smoking behaviour change. Perceived increased awareness of how smoking negatively impacted participants' mental health, and the opportunity to be offered smoking cessation treatment in a ‘non‐judgemental’, ‘supportive’ environment, with regular sessions and individualized strategies contributed to successful smoking cessation outcomes. If similar results are found in more diverse samples, these aspects should be embedded within integrated interventions for smoking cessation and depression/anxiety. Patient or Public Contribution Persons with lived experience of depression, anxiety and tobacco addiction contributed towards the design of the interview schedule, participant information sheets and the debriefing process. This was to ensure that interview questions were relevant, nonjudgemental and acceptable for those who did not manage to quit smoking.

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An application of the stress-diathesis model: A review about the association between smoking tobacco, smoking cessation, and mental health

Cited by 28 publications

References 55 publications

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Service‐user experiences of an integrated psychological intervention for depression or anxiety and tobacco smoking in improving access to psychological therapies services: A qualitative investigation into mechanisms of change in quitting smoking

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