How a concerned family member, friend or member of the public can help someone with gambling problems: a Delphi consensus study

BackgroundGambling is an enjoyable recreational pursuit for many people. However, for some it can lead to significant harms. The Delphi expert consensus method was used to develop guidelines for how a concerned family member, friend or member of the public can recognise the signs of gambling problems and support a person to change their gambling.MethodsA systematic review of websites, books and journal articles was conducted to develop a questionnaire containing items about the knowledge, skills and actions needed for supporting a person with gambling problems. These items were rated over three rounds by two international expert panels comprising people with a lived experience of gambling problems and professionals who treat people with gambling problems or research gambling problems.ResultsA total of 66 experts (34 with lived experience and 32 professionals) rated 412 helping statements according to whether they thought the statements should be included in these guidelines. There were 234 helping statements that were endorsed by at least 80 % of members of both of the expert panels. These endorsed statements were used to develop the guidelines.ConclusionTwo groups of experts were able to reach substantial consensus on how someone can recognise the signs of gambling problems and support a person to change.<br /

Problematic Facebook use and problematic video gaming as mediators of relationship between impulsivity and life satisfaction among female and male gamers

Over the past few decades, many new technologies have emerged, such as portable computers, the internet and smartphones, which have contributed to improving the lives of individuals. While the benefits of these new technologies are overwhelmingly positive, negative consequences are experienced by a minority of individuals. One possible negative aspect of new technologies is their problematic use due to impulsive use which may lead to lower life satisfaction. The present study investigated the mediating role of problematic video gaming (PVG) and problematic Facebook use (PFU) in the relationship between impulsivity dimensions and life satisfaction as well as the relationship between impulsivity dimensions and problematic behaviors. Additionally, the potential impact of gender differences was also examined. The study comprised 673 gamers (391 females) aged 17–38 years (M = 21.25 years, SD = 2.67) selected from 1365 individuals who completed an offline survey. PFU was assessed using the Facebook Intrusion Scale, and PVG was assessed using the nine-item Internet Gaming Disorder Scale–Short-Form (IGDS9-SF). Impulsivity dimensions such as attention, cognitive instability, motor, perseverance, self-control, and cognitive complexity were assessed using the Barratt Impulsiveness Scale (BIS-11), and life satisfaction was assessed using the Satisfaction With Life Scale (SWLS). Depending on the specific impulsivity dimension, findings showed both positive and negative relationships between impulsivity and life satisfaction. Attention and perseverance subtypes of impulsivity were primarily associated with problematic behaviors. Additionally, cognitive complexity was associated with PFU among female gamers, whereas cognitive instability was associated with PVG among male gamers. Additionally, PVG was primarily associated with lower life satisfaction. However, there was no mediation effects between impulsivity dimensions and life satisfaction via PFU or PVG. These findings provide a better understanding of the relationship between problematic behaviors, life satisfaction, and impulsivity among gamers and the differences between male and female gamers

Affected other interventions: a systematic review and meta-analysis across addictions.

BACKGROUND AND AIMS: Individuals impacted by someone else's alcohol, illicit drug, gambling and gaming problems (affected others) experience extensive harms. To our knowledge, this is the first systematic review and meta-analysis to determine the effectiveness of psychosocial interventions delivered to affected others across addictions. METHODS: This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. An electronic database search (PsycInfo, Medline, Cinahl and EMBASE) of randomized controlled trials (RCTs) published until August 2021 was conducted. RCTs with passive control groups, evaluating psychosocial tertiary interventions delivered to affected others of people with addictions (problematic alcohol use, substance use, gambling or gaming) that did not require the involvement of the addicted person, were included. RESULTS: Twenty included studies, published in 22 articles, mainly evaluated interventions for alcohol use, followed by gambling and illicit drugs, with none investigating gaming interventions. The interventions mainly targeted partners/spouses and focused upon improving affected other outcomes, addicted person outcomes or both. Meta-analyses revealed beneficial intervention effects over control groups on some affected other (depressive symptomatology, life satisfaction and coping style, addicted person [treatment entry] and relationship functioning outcomes (marital discord) at post-intervention. No beneficial intervention effects were identified at short-term follow-up (4-11 months post-treatment). The beneficial intervention effects identified at post-treatment remained when limiting to studies of alcohol use and therapist-delivered interventions. CONCLUSIONS: Psychosocial interventions delivered to affected others of people with addictions (problematic alcohol use, substance use, gambling or gaming) may be effective in improving some, but not all, affected other (depression, life satisfaction, coping), addicted person (treatment) and relationship functioning (marital discord) outcomes for affected others across the addictions, but the conclusion remains tentative due to limited studies and methodological limitations

ChatGPT for Automated Qualitative Research: Content Analysis

BackgroundData analysis approaches such as qualitative content analysis are notoriously time and labor intensive because of the time to detect, assess, and code a large amount of data. Tools such as ChatGPT may have tremendous potential in automating at least some of the analysis. ObjectiveThe aim of this study was to explore the utility of ChatGPT in conducting qualitative content analysis through the analysis of forum posts from people sharing their experiences on reducing their sugar consumption. MethodsInductive and deductive content analysis were performed on 537 forum posts to detect mechanisms of behavior change. Thorough prompt engineering provided appropriate instructions for ChatGPT to execute data analysis tasks. Data identification involved extracting change mechanisms from a subset of forum posts. The precision of the extracted data was assessed through comparison with human coding. On the basis of the identified change mechanisms, coding schemes were developed with ChatGPT using data-driven (inductive) and theory-driven (deductive) content analysis approaches. The deductive approach was informed by the Theoretical Domains Framework using both an unconstrained coding scheme and a structured coding matrix. In total, 10 coding schemes were created from a subset of data and then applied to the full data set in 10 new conversations, resulting in 100 conversations each for inductive and unconstrained deductive analysis. A total of 10 further conversations coded the full data set into the structured coding matrix. Intercoder agreement was evaluated across and within coding schemes. ChatGPT output was also evaluated by the researchers to assess whether it reflected prompt instructions. ResultsThe precision of detecting change mechanisms in the data subset ranged from 66% to 88%. Overall κ scores for intercoder agreement ranged from 0.72 to 0.82 across inductive coding schemes and from 0.58 to 0.73 across unconstrained coding schemes and structured coding matrix. Coding into the best-performing coding scheme resulted in category-specific κ scores ranging from 0.67 to 0.95 for the inductive approach and from 0.13 to 0.87 for the deductive approaches. ChatGPT largely followed prompt instructions in producing a description of each coding scheme, although the wording for the inductively developed coding schemes was lengthier than specified. ConclusionsChatGPT appears fairly reliable in assisting with qualitative analysis. ChatGPT performed better in developing an inductive coding scheme that emerged from the data than adapting an existing framework into an unconstrained coding scheme or coding directly into a structured matrix. The potential for ChatGPT to act as a second coder also appears promising, with almost perfect agreement in at least 1 coding scheme. The findings suggest that ChatGPT could prove useful as a tool to assist in each phase of qualitative content analysis, but multiple iterations are required to determine the reliability of each stage of analysis