Background Invitation letters can be the first point of contact between research staff and potential participants and a number of modifiable variables have been studied to improve their effectiveness. The aim of this analysis was to determine if lower reading levels and "gain-framed" messages improved recruitment for a RCT that mailed nicotine replacement therapy (NRT) patches for smoking cessation. Methods Invitation letters were created which varied in a two-by-two design by reading level and message framing. The letters were randomly mailed to all households in a community selected to receive targeted distribution of NRT patches. Results There were no significant differences found in the number of participants enrolled. Conclusion Future research investigating factors to improve invitation letters is merited despite current project limitations. Trial registration ClinicalTrials.gov NCT04534231.

Participation in online gambling is growing and the risk of experiencing harms is also increasing. Brief personalised feedback interventions have been shown to prevent, reduce and address gambling harm and this randomised controlled trial tested the effectiveness of a version customised for the UK. A sample of 1586 online gambling participants with moderate or problem gambling were rapidly recruited from an existing Internet panel of UK residents. Participants were randomised to a no intervention control group or received the self-directed, online intervention which included normative feedback and personalised information explaining the consequences of gambling above lower-risk guidelines. One- and three-month follow-ups assessed the short-term impact on frequency and harm. Feedback and recommendations were collected to guide improvements and increase future utility. All gambling outcomes showed improvement between the initial survey and both follow-ups, however, there were no differences between the intervention and control groups. Most participants displayed normative misperceptions when estimating how much others the same age and gender gambled. The majority of the sample had never previously sought treatment despite over a third of these reporting moderate or problematic levels of gambling. There is need for a publicly available, low-cost alternative to traditional treatment in order to help the large proportion of people with gambling concerns who would not otherwise seek formal support. Although an intervention effect was not detected in this sample, Internet-based alternatives remain a promising opportunity meriting further research.

INTRODUCTION Rural regions generally report higher smoking rates than urban centers, which increases the risk of tobacco related harms and consequences, and makes promoting smoking cessation in these areas a priority. Mass distribution of nicotine replacement therapy (NRT) by postal mail has been found to increase the odds of successful cessation attempts. Understanding factors that contribute to the use of NRT could help maximize this intervention's effectiveness. METHODS People who smoke cigarettes and live in rural areas of Canada were recruited from December 2020 to February 2022 using random digit telephone dialing. Participants were either randomized to be mailed a free, 5-week supply of NRT patches (experimental condition; n=252) or not (control condition; n=246). This secondary analysis used data from this randomized controlled trial to conduct an ordinal regression to determine if any variables measured at baseline predicted which participants in the experimental condition used none, some, or all of the RESULTS Greater confidence in ability to quit (AOR=1.07; 95% CI: 1.00-1.15) independently predicted more patch use, while living in more remote places (AOR=0.25; 95% CI: 0.07-0.90) and past substance use (compared to having no CONCLUSIONS Understanding what contributes to NRT use in rural mass distribution programs could help maximize the odds of successful cessation attempts, personalize treatment recommendations, and target limited rural resources. Future research focused on rural NRT use and smoking cessation is merited.

OBJECTIVE:Alexithymia is characterized by difficulty identifying and/or describing emotions, reduced imaginal processes, and externally oriented thinking. High levels of alexithymia may increase the challenge of supporting individuals with co-occurring depression and hazardous alcohol use. This secondary analysis sought to investigate whether or not alexithymia moderated the outcomes of an online intervention for depression and alcohol use. METHOD:As part of a randomized controlled trial, 988 participants were randomly assigned to receive an intervention dually focused on depression and alcohol use, or an intervention only focused on depression. The pre-specified mediation hypothesis was that changes in drinking at 3 months follow-up would effect the association between the intervention and change in depression at 6 months. This secondary analysis extends the investigation by adding alexithymia as a moderator. RESULTS:The current analysis demonstrated that including alexithymia as a moderator resulted in a conditional direct effect. Specifically, there was an intervention effect where participants who received the combined depression and alcohol intervention had larger improvements in their depression scores at 6 months, but this was only when their alexithymia score at baseline was also high (60.5 or higher). CONCLUSION:These results suggest that treatment planning and intervention effectiveness could be informed and optimized by taking alexithymia severity into consideration. This is especially merited as alexithymia can contribute to the weaker therapeutic alliance, more distress and dysphoria, shorter periods of abstinence, and more severe depression, compounding the complexity of supporting individuals with comorbid conditions. More research is needed to systematically investigate these possible modifying effects. PLAIN LANGUAGE TITLE:Does difficulty identifying/describing emotions or externally-oriented thinking influence the effectiveness of an intervention among people with both depression and hazardous alcohol use?

Background Previous studies have demonstrated that excluding individuals at risk of suicide from online depression interventions can impact recruited sample characteristics. Aim To determine if a small change in suicide risk exclusion criterion led to differences in the usage and effectiveness of an Internet depression intervention at 6 months of follow-up. Method A partial sample of a recently completed online depression intervention trial was divided into two groups: those with no risk of suicide versus those with some risk. The two groups were compared for baseline demographic and clinical measures, as well as intervention uptake and treatment success across 6 months. Results Overall, individuals with less risk of suicide at baseline reported significantly less severe clinical symptoms. Both groups interacted with the intervention at the same rate, but specific use of modules was different. Finally, the impact of intervention usage on outcomes over time did not vary by group. Limitations While different suicide risk exclusion criteria can change recruited sample characteristics, it remains unclear how these differences impact intervention uptake and success. Conclusion Overall, the findings suggest that researchers should exercise caution when excluding individuals at risk of suicide, as they greatly benefit from web-based interventions.

Primary, secondary, and tertiary reinforcement contribute to the maintenance of smoking behaviour and may influence the efficacy of different cessation treatments. This analysis examined these relationships in a large general population sample and investigated how previous experiences of the different reinforcement mechanisms impacted future quit attempts. Random digit telephone dialing was used to recruit a sample of Canadian adults who smoked and were interested in being part of a hypothetical program that would provide nicotine replacement therapy (NRT) patches free by mail and half of the eligible participants were randomized to actually receive a five-week supply of NRT patches. During the interviews, reasons for relapse to smoking during previous quit attempts were collected and coded by two reviewers (disagreements were settled by a third reviewer). Binary logistic regression was used to determine if type of reinforcer moderated the intervention effect of the patches. Participants who made cessation attempts in the past year were more likely to report negative (p = .039), secondary (p = .041), and tertiary (p = .010) reinforcers and less likely to report positive reinforcers (p = .016) compared to those who did not attempt to quit. Logistic regressions revealed no significant conditional effects of the intervention on the relationship between reinforcer type and quit attempts or 30-day smoking abstinence. Analysis including all three reinforcers showed negative reinforcers decreased but tertiary reinforcers increased the odds participants reported a cessation attempt before the baseline interview and between baseline and 8-weeks. Understanding the different ways nicotine reinforces smoking behaviour could help guide individuals to more effective treatment options.

Background and aims: Unhealthy alcohol use is common and causes tremendous harm. Most people with unhealthy alcohol use will never seek formal alcohol treatment. As an alternative, smartphone apps have been developed as one means to provide help to people concerned about their alcohol use. The aim of this study was to test the efficacy of a smartphone app targeting unhealthy alcohol consumption in a general population sample. Methods: Participants were recruited from across Canada using online advertisements. Eligible participants who consented to the trial were asked to download a research-specific version of the app and were provided with a code that unlocked it (a different code for each participant to prevent sharing). Those who entered the code were randomized to one of two different versions of the app: 1) the Full app containing all intervention modules; or 2) the Educational only app, containing only the educational content of the app. Participants were followed-up at 6 months. The primary outcome variable was number of standard drinks in a typical week. Secondary outcome variables were frequency of heavy drinking days and experience of alcohol-related problems. Results: A total of 761 participants were randomized to a condition. The follow-up rate was 81 %. A generalized linear mixed model revealed that participants receiving the full app reduced their typical weekly alcohol consumption to a greater extent than participants receiving the educational only app (incidence rate ratio 0.89; 95 % confidence interval 0.80 to 0.98). No significant differences were observed in the secondary outcome variables (p > .05). Discussion and conclusion: The results of this trial provide some supportive evidence that smartphone apps can reduce unhealthy alcohol consumption. As this is the second randomized controlled trial demonstrating an impact of this same app (the first one targeted unhealthy alcohol use in university students), increased confidence is placed on the potential effectiveness of the smartphone app employed in the current trial. ClinicalTrials.org number: NCT04745325

Background Previous research has demonstrated that remissions from alcohol use disorders can occur without accessing treatment. The current study explored the prevalence of such untreated remissions in the UK and further, examined the extent to which people who resolved an alcohol use disorder regarded themselves as ever, or currently, being in recovery. Methods Participants were recruited using the Prolific online platform. Participants who met criteria for lifetime alcohol dependence (ICD-10) were asked about their drinking at its heaviest, use of treatment services, whether they identified as being in recovery, and their current alcohol consumption (to identify those who were abstinent or drinking in a moderate fashion). Results A total of 3,994 participants completed surveys to identify 166 participants with lifetime alcohol dependence who were currently abstinent (n = 67) or drinking in a moderate fashion (n = 99). Participants who were currently abstinent were more likely to have accessed treatment than those who were currently moderate drinkers (44.4% versus 16.0%; Fischer’s exact test = 0.001). Further, those who were abstinent were heavier drinkers prior to remission [Mean (SD) drinks per week = 53.6 (31.7) versus 29.1 (21.7); t-test = 5.6, 118.7 df, p < .001] and were more likely to have ever identified themselves as ‘in recovery’ (51.5% versus 18.9%; Fischer’s exact test = 0.001) than current moderate drinkers. Conclusions While participants with an abstinent remission were more likely than those currently drinking in a moderate fashion to have accessed treatment and to identify as being ‘in recovery,’ the majority of participants reduced their drinking without treatment (and did not regard themselves as in recovery).

BackgroundQuality of life (QOL) summarizes an individual's perceived satisfaction across multiple life domains. Many factors can impact this measure, but research has demonstrated that individuals with addictions, physical, and mental health concerns tend to score lower than general population samples. While QOL is often important to individuals, it is rarely used by researchers as an outcome measure when evaluating treatment efficacy.MethodsThis secondary analysis used data collected during three separate randomized controlled trials testing the efficacy of different online interventions to explore change in QOL over time between treatment conditions. The first project was concerned with only alcohol interventions. The other two combined either a gambling or mental health intervention with a brief alcohol intervention. Males and females were analyzed separately.ResultsThis analysis found treatment effects among female participants in two projects. In the project only concerning alcohol, female quality of life improved more among those who received an extensive intervention for hazardous alcohol use compared to a brief intervention (p = .029). QOL among females who received only the mental health intervention improved more than those who also received a brief alcohol intervention (p = .049).ConclusionPoor QOL is often cited as a reason individuals decide to make behavior changes, yet treatment evaluations do not typically consider this patient-important outcome. This analysis found some support for different treatment effects on QOL scores in studies involving at least one intervention for hazardous alcohol use.

Introduction:This study examines normative misperceptions in a sample of participants recruited for a brief intervention trial targeting risky cannabis use. Methods:Participants who were concerned about their own risky cannabis use were recruited to help develop and evaluate intervention materials. At baseline, participants reported on their own cannabis use and provided estimates of how often others their gender and age used cannabis in the past 3 months. Comparisons were made between participants estimates of others cannabis use with reports of cannabis use obtained from a general population survey conducted during a similar time period. Results:Participants (N = 744, mean age = 35.8, 56.2% identified as female) largely reported daily or almost daily cannabis use (82.4%). Roughly half (55.3%) of participants estimated that others their age and gender used cannabis weekly or more often in the past 3 months, whereas the majority of people in the general population reported not using cannabis at all. Conclusions:Normative misperceptions about cannabis use were common in this sample of people with risky cannabis use. Limitations and possible future directions of this research are discussed, as well as the potential for targeting these misperceptions in interventions designed to motivate reductions in cannabis use. ClinicalTrials.org number:NCT04060602

This randomized clinical trial assesses the efficacy of mailed nicotine patches on cessation of tobacco smoking among adults in rural Canada.

Aim: A number of important health disparities associated with place of residence have been reported in the literature. The Remoteness Index (RI) was developed to account for community size, population density, and proximity to larger population centres. This exploratory analysis uses the RI to examine community level associations related to cannabis use.Design: This secondary analysis uses data collected as part of a randomized controlled trial of a brief cannabis intervention. Participants' place of residence was matched to a corresponding value on the RI. Univariate regressions of RI and cannabis related outcomes were modeled with age and gender as moderating variables. Three outcomes were analyzed separately: 1) total number of days of cannabis use in the past 30 days; 2) risk of experiencing cannabis related problems; and 3) number of self-reported consequences related to cannabis.Findings: Participants living in more remote areas were significantly more likely to drive within an hour of using cannabis, but also reported fewer consequences and less risky cannabis use. Although the overall regression models tested in the moderation analyses were significant, there were no interaction effects between RI and age or gender.Conclusion: While this analysis did not find significant conditional effects of age or gender on the relationship between cannabis use and place of residence, further research is needed to investigate other factors which may contribute to health disparities related to substance use between individuals living in different geographic regions.

Free AccessWidening the CracksUnintended Harms of Excluding Individuals at Risk of Suicide From Broader Mental Health ResearchAlexandra Godinho, Christina Schell, and John A. CunninghamAlexandra Godinhohttps://orcid.org/0000-0003-3430-1947Institute of Mental Health and Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada, Christina SchellInstitute of Mental Health and Policy Research, Centre for Addiction and Mental Health, Toronto, ON, CanadaDalla Lana School of Public Health, University of Toronto, ON, Canada, and John A. CunninghamJohn A. Cunningham, National Addiction Centre, 4 Windsor Walk, Denmark Hill, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8BB, UK, john.cunningham@kcl.ac.ukInstitute of Mental Health and Policy Research, Centre for Addiction and Mental Health, Toronto, ON, CanadaNational Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UKDepartment of Psychiatry, University of Toronto, ON, CanadaPublished Online:August 02, 2022https://doi.org/10.1027/0227-5910/a000872PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit SectionsMoreThe inclusion of participants at risk of suicide in general mental health intervention research can make balancing participant safety and recruiting a representative sample challenging. On the one hand, excluding these individuals can preclude researchers from evaluating interventions for those who are most in need (Fisher et al., 2002; Hom et al., 2017). On the other hand, managing suicide risk and providing support to these participants can be resource intensive and time consuming, requires specialized training for staff, and necessitates ongoing monitoring, which may seem unfeasible for low-cost and/or brief intervention research (Stevens et al., 2021; Ward & Wilks, 2020). More importantly, the inclusion of these individuals in broader mental health research, rather than in specialized suicide prevention research, often faces greater resistance from ethics committees, leaving researchers hesitant to include these individuals in their studies (Bailey et al., 2020). This problem is even further complicated for digitally delivered mental health interventions, as some of the strategies for suicide risk reduction used in research specific to suicide prevention can interfere with the evaluation of an intervention. For example, in the case of self-guided online environments for depression, where interaction with research staff and/or clinicians is minimal or nonexistent, providing direct clinical support could significantly change the intervention and impact the generalizability of results. In light of these challenges, many online researchers opt to exclude individuals at risk of suicide in order to satisfy ethics board requirements to mitigate risk. Using this management strategy, exclusion rates as high as 70% have been reported (Godinho et al. 2021; Sander et al., 2020).Although excluding individuals at risk of suicide in broader mental health research may feel like a necessary compromise for researchers, it is important to consider the ethical implications of these decisions for the excluded individuals themselves, as well as the data quality threats it may pose to study results. This editorial discusses these issues in light of the recent literature, and focuses on the specific harms to these individuals, as well as the potential for biases in recruited samples; it concludes with how some of these issues can be mitigated. Moreover, we provide some lessons learned from our own experiences conducting a study of a brief online intervention for depression that excluded individuals at risk of suicide.Unintended Harms to the IndividualThe literature has seen a recent proliferation in the number of surveys that investigate the attitudes and concerns both of researchers and ethics committees around the inclusion of individuals at risk of suicide in research. Despite some of the tension that is often observed between these two groups, both do see the value of including these individuals in mental health research (Andriessen et al., 2019; Bailey et al., 2020). However, the most common concerns expressed by researchers and ethics committees alike can be categorized into: (1) competency to consent due to the severity of the individuals' mental distress; (2) the provision of adequate suicide risk management and ongoing monitoring (e.g., research staff training, resources for participants); and (3) ascertaining the overall safety and well-being of participants (i.e., minimizing adverse events; Andriessen et al., 2019; Bailey et al., 2020; Barnard et al., 2021).Although these concerns are paramount to conducting ethically sound research, the potential unintended harms of excluding individuals at risk of suicide from general mental health research has received far less attention. Indeed, to our knowledge, no study has examined the short- or long-term mental health effects of excluding these individuals from intervention research, despite the highly co-occurring nature of suicide risk and mental health disorders. A recent US study found that 51.3% of individuals who die by suicide have a recorded mental health diagnosis (Yeh et al., 2019), while nearly 25% of depressed individuals report suicidal ideation (American Association of Suicidology, 2014). Moreover, some research evidence has suggested that higher severity of depression and/or anxiety disorders, including the presence of suicidal ideation, may be a significant predictor of the likelihood of seeking treatment and can have a protective effect against the risk of a suicide attempt (Hoertel et al., 2018; Magaard et al., 2017). However, qualitative research has suggested that treatment seeking might be delayed among those with more severe symptomology, since getting help is seen as a last-ditch effort that may threaten one's identity (Doblyte & Jiménez-Mejías, 2016).Altogether, these findings suggest that when suicide risk is used as an exclusion criterion, researchers may be excluding individuals most at need, and importantly excluding a significant proportion of the very group the intervention is intended to target, since suicide risk and ideation are common symptoms among people with mental health concerns. This denies these individuals the opportunity to participate in a mental health intervention study, which may improve their symptoms, and prevents them from providing meaningful feedback to researchers. This has the potential to lead to feelings of rejection and loss of trust in the health-care system, and potentially leave them with no alternative forms of help, particularly as public mistrust in research is commonplace (Holzer et al., 2014). This is especially important in the case of online mental health interventions, where access to alternative in-person treatment may be unavailable or inaccessible (e.g., in rural areas), expensive, or undesirable for individuals who prefer to remain anonymous in order to avoid the stigma associated with mental health disorders (Graham et al., 2021; Gulliver et al., 2010).Our recent experience in recruiting individuals for an online depression intervention provided us with a glimpse of how some of these excluded individuals feel, via the comments posted on our Facebook page and direct emails. As part of the screening process, all potential participants were screened for suicide risk using the final item of the Patient Health Questionnaire-9 (PHQ-9). Individuals were excluded if any risk was present (reporting any thoughts of being better off dead or of hurting themselves), regardless of the severity of their depression scores. Despite being given access to the intervention free-of-charge, excluded participants who were at risk of suicide expressed extreme frustration in not being eligible for the study. Most notable were feelings of being "too sick" to participate, and once again being "let down by the system." In addition, many expressed confusion over being ineligible as they had a formal diagnosis of depression, and anger over feeling that the study was designed for those who merely have low mood and not depression. These participants did not recognize their suicide risk as being the barrier to their participation, and instead made assumptions about the targeted sample of the study. Lastly, some expressed concern over where they were going to get help as they felt no other forms of help were available to them. In light of recent evidence suggesting that feelings of rejection and ostracism can increase risky decision-making (Buelow & Wirth, 2017), it is not known what long-term effects this exclusion may have on individuals who are at a higher risk of suicide.It is important to understand that the ethical conduct of clinical research demands more than managing potential participant harm. Emanuel et al. (2000) outline a total of seven requirements for conducting ethical clinical research. Among these are fair participant selection and a favorable risk–benefit ratio. Excluding individuals at risk of suicide from broader mental health research without a valid scientific rationale can violate fair participant selection since individuals are excluded solely as a result of their vulnerability. As individuals at risk of suicide are expected to comprise a large majority of the future users of a mental health intervention, excluding these individuals does not appear to align with the scientific goals of research. Moreover, recent evidence suggests that asking about suicide does not necessarily change risk levels, while mental health interventions have been shown to similarly improve the symptoms of those on both the higher and lower end of the symptomology spectrum (Bower et al., 2013; Crawford et al., 2011). Therefore, excluding individuals at any risk of suicide from mental health interventions may violate the favorable risk–benefit ratio requirement, especially when nuanced attention is not given to the individual degree of suicide risk (e.g., ideation vs. active intent). We encourage researchers and ethics committees to engage in more meaningful discussions about the ethical responsibilities toward potential participants, when considering harms, benefits, and the scientific merit of conducting the study. In particular, discussions should consider both the benefits and harms to excluded individuals at risk of suicide, including the potential to: (1) deny the only form of possible help available to the individual, (2) discourage future treatment seeking, (3) lead to poorer mental health outcomes in the long term, and (4) result in short- and long-term risks associated with rejection and emotional pain.Data Quality ConcernsIn addition to ethical concerns, it is also important that researchers consider the data quality threats that may result from excluding potential participants who are at risk of suicide. The reported rates of exclusion due to suicide risk have been reported to be as high as 70% (Godinho et al., 2021; Sander et al., 2020), and this can have important implications for the external validity of intervention research; especially when common suicide risk screening tools in mental health research consist of 1-item questions that measure very short-term risk (e.g., the PHQ-9 only considers the past 2 weeks). Excluding such a large group can artificially inflate or – more probably – mute the intervention's efficacy. This is because those at risk of suicide may be more likely to benefit the most from the intervention. Since individuals who are most in need of treatment may be the least likely to seek it, it is important that individuals who attempt to participate in mental health intervention research be included in the development of such interventions. This is particularly important for online mental health research, as recent evidence suggests even the most severely depressed individuals are reluctant to attend face-to-face psychotherapy, but they report benefits from and favorable attitudes toward self-guided interventions (Moritz et al., 2013).Moreover, recent findings that inclusion thresholds have been increasing within depression research further complicate the matter (Zimmerman et al., 2005; 2019). That is, if researchers are selecting participants for research with greater severity of symptoms, but excluding those at risk of suicide, the resulting recruited sample becomes highly selective and biased. Consequently, any outcome data from biased samples could significantly alter the design of future interventions, leaving individuals who have milder forms of depression as well as those who have severe symptoms, and suicide risk, with potentially ineffective interventions. It is imperative that future research examine these issues in greater depth.Balancing Risk of Suicide in Mental Health ResearchHow do researchers balance the unintended harms to participants, data quality concerns, and ensure ethical research is being conducted? One strategy is to use validated forms of determining suicide risk. While the use of single-item measures to determine suicide risk is one of the most popular exclusion criterion methods (Sander et al., 2020), recent evidence suggests that single-item assessments of suicide risk often lead to misclassifications and are insufficient measures of risk (Millner et al., 2015; Na et al., 2018). Moreover, suicide risk assessment scales have largely been shown to not be good predictors of fatal suicide attempts when administered once, but instead that risk assessment involves repeated measures over time and clinical inference (Runeson et al., 2017). Therefore, the inclusion of these individuals in mental health intervention research, and ongoing monitoring of suicide risk, can minimize unintended harms to the individual and diminish data quality threats.In addition to having better measures of suicide risk, researchers should build suicide management strategies into the interventions they are testing. Since a large proportion of individuals with mental health disorders also are at risk of suicide, and given the dynamic nature of suicidality and suicidal behavior, incorporating suicide prevention strategies into broader mental health interventions would have the capacity to both minimize the risk of harm to individuals and improve the overall efficacy of the intervention. For some interventions it may be sufficient to provide additional resources (e.g., suicide hotlines, referrals to clinicians), or in the context of digital interventions the provision of efficacious self-guided interventions for suicide prevention may suffice (Torok et al., 2019). Researchers are encouraged to familiarize themselves with efficacious suicide prevention strategies that may be simple to implement and improve the overall effectiveness of the intervention, as well as to collaborate with others who are specialists in suicide risk, prevention, and management.ConclusionGiven the complex nature of measuring suicide risk, and the potential harms of excluding individuals at risk of suicide from broader mental health research, it is important that these individuals be included in research when ethically possible. Researchers must strive to inform their ethics committees about the existing evidence on how excluding individuals at risk of suicide can potentially harm these individuals and may compromise study outcomes and the development of interventions. It is also recommended that suicide prevention strategies be built into existing mental health interventions since suicide and mental health disorders are highly correlated, and such additions have the potential to greatly improve intervention efficacies.Author BiographiesAlexandra Godinho, MScCH, is a research coordinator at the Centre for Addiction and Mental Health, University of Toronto, Canada. She has supported numerous online intervention research projects, and her main research interests are recruitment methodology, online data collection, and ensuring data quality.Christina Schell, BSc, is a research analyst at the Centre for Addiction and Mental Health, University of Toronto, Canada. Her recent research work has investigated social desirability responding, invalid responding, and rurality in addictions research.John Cunningham, PhD, works in the intersection between clinical and population health. He currently holds the Nat and Loretta Rothschild Chair in Addictions Treatment and Recovery Studies at King's College London, UK. His research is driven by the question, "How do people change from addictive behaviors?"ReferencesAmerican Association of Suicidology. (2014). Depression and suicide risk. http://suicidology.org/Portals/14/docs/Resources/FactSheets/2011/DepressionSuicide2014.pdf First citation in articleGoogle ScholarAndriessen, K., Reifels, L., Krysinska, K., Robinson, J., Dempster, G., & Pirkis, J. (2019). Ethical concerns in suicide research: Results of an international researcher survey. Journal of Empirical Research on Human Research Ethics, 14(4), 383–394. 10.1177/1556264619859734 First citation in articleCrossref Medline, Google ScholarBailey, E., Muhlmann, C., Rice, S., Nedelijkovic, M., Alvarez-Jimenez, M., Sander, L., Calear, A. L., & Robinson, J. (2020). Ethical issues and practical barriers in internet-based suicide prevention research: A review and investigator survey. BMC Medical Ethics, 21(1), 37. 10.1186/s12910-020-00479-1 First citation in articleCrossref Medline, Google ScholarBarnard, E., Dempster, G., Krysinska, K., Reifels, L., Robinson, J., Pirkis, J., & Andriessen, K. (2021). Ethical concerns in suicide research: Thematic analysis of the views of human research ethics committees in Australia. BMC Medical Ethics, 22(1), Article 41. 10.1186/s12910-021-00609-3 First citation in articleCrossref Medline, Google ScholarBower, P., Kontopantelis, E., Sutton, A., Kendrick, T., Richards, D. A., Gilbody, S., Knowles, S., Cuijpers, P., Andersson, G., Christensen, H., Meyer, B., Huibers, M., Smit, F., van Straten, A., Warmerdam, L., Barkham, M., Bilich, L., Lovell, K., & Liu, E. T.-H. (2013). Influence of initial severity of depression on effectiveness of low intensity interventions: Meta-analysis of individual patient data. BMJ, 346, Article f540. 10.1136/bmj.f540 First citation in articleCrossref Medline, Google ScholarBuelow, M. T., & Wirth, J. H. (2017). Decisions in the face of known risks: Ostracism increases risky decision-making. Journal of Experimental Social Psychology, 69, 210–217. 10.1016/j.jesp.2016.07.006 First citation in articleCrossref, Google ScholarCrawford, M. J., Thana, L., Methuen, C., Ghosh, P., Stanley, S. V., Ross, J., Gordon, F. Blair, G, & Bajaj P. (2011). Impact of screening for risk of suicide: Randomised controlled trial. The British Journal of Psychiatry, 198(5), 379–384. 10.1192/bjp.bp.110.083592 First citation in articleCrossref Medline, Google ScholarDoblyte, S., & Jiménez-Mejías, E. (2016). Understanding help-seeking behavior in depression. Qualitative Health Research, 27(1), 100–113. 10.1177/1049732316681282 First citation in articleCrossref, Google ScholarEmanuel, E. J., Wendler, D., & Grady, C. (2000). What makes clinical research ethical? JAMA, 283(20), 2701–2711. 10.1001/jama.283.20.2701 First citation in articleCrossref Medline, Google ScholarFisher, C. B., Pearson, J. L., Kim, S., & Reynolds, C. F. (2002). Ethical issues in including suicidal individuals in clinical research. IRB: Ethics and Human Research, 24(5), 9–14. 10.2307/3563804 First citation in articleCrossref Medline, Google ScholarGodinho, A., Schell, C., & Cunningham, J. A. (2021). Falling between the cracks: The effect of using different levels of suicide risk exclusion criteria on sample characteristics when recruiting for an online intervention for depression. Suicide and Life‐Threatening Behavior, 51(4), 736–740. 10.1111/sltb.12761 First citation in articleCrossref Medline, Google ScholarGraham, A. K., Weissman, R. S., & Mohr, D. C. (2021). Resolving key barriers to advancing mental health equity in rural communities using digital mental health interventions. JAMA Health Forum, 2(6), e211149. 10.1001/jamahealthforum.2021.1149 First citation in articleCrossref Medline, Google ScholarGulliver, A., Griffiths, K. M., & Christensen, H. (2010). Perceived barriers and facilitators to mental health help-seeking in young people: A systematic review. BMC Psychiatry, 10, Article 113. 10.1186/1471-244x-10-113 First citation in articleCrossref Medline, Google ScholarHoertel, N., Blanco, C., Olfson, M., Oquendo, M. A., Wall, M. M., Franco, S., Leleu, H., Lemogne, C., Falissard, B., & Limosin, F. (2018). A comprehensive model of predictors of suicide attempt in depressed individuals and effect of treatment-seeking behavior. The Journal of Clinical Psychiatry, 79(5), Article 17m11704. 10.4088/JCP.17m11704 First citation in articleCrossref Medline, Google ScholarHolzer, J. K., Ellis, L., & Merritt, M. W. (2014). Why we need community engagement in medical research. Journal of Investigative Medicine, 62(6), 851–855. 10.1097/jim.0000000000000097 First citation in articleCrossref Medline, Google ScholarHom, M. A., Podlogar, M. C., Stanley, I. H., & Joiner, T. E., Jr. (2017). Ethical issues and practical challenges in suicide research. Crisis, 38(2), 107–114. 10.1027/0227-5910/a000415 First citation in articleLink, Google ScholarMagaard, J. L., Seeralan, T., Schulz, H., & Brütt, A. L. (2017). Factors associated with help-seeking behaviour among individuals with major depression: A systematic review. PLoS One, 12(5), Article e0176730. 10.1371/journal.pone.0176730 First citation in articleCrossref, Google ScholarMillner, A. J., Lee, M. D., & Nock, M. K. (2015). Single-item measurement of suicidal behaviors: Validity and consequences of misclassification. PLoS One, 10(10), Article e0141606. 10.1371/journal.pone.0141606 First citation in articleCrossref Medline, Google ScholarMoritz, S., Schröder, J., Meyer, B., & Hauschildt, M. (2013). The more it is needed, the less it is wanted: Attitudes towards face-to-face interventions among depresssed patients undergoing online treatment. Depression and Anxiety, 30(2), 157–167. 10.1002/da.21988 First citation in articleCrossref Medline, Google ScholarNa, P. J., Yaramala, S. R., Kim, J. A., Kim, H., Goes, F. S., Zandi, P. P., Vande Voort, J. L., Sutor, B., Croarkin, P., & Bobo, W. V. (2018). The PHQ-9 item 9 based screening for suicide risk: A validation study of the Patient Health Questionnaire (PHQ)−9 item 9 with the columbia suicide severity rating scale (C-SSRS). Journal of Affective Disorders, 232, 34–40. 10.1016/j.jad.2018.02.045 First citation in articleCrossref Medline, Google ScholarRuneson, B., Odeberg, J., Pettersson, A., Edbom, T., Jildevik Adamsson, I., & Waern, M. (2017). Instruments for the assessment of suicide risk: A systematic review evaluating the certainty of the evidence. PLoS One, 12(7), Article e0180292. 10.1371/journal.pone.0180292 First citation in articleCrossref Medline, Google ScholarSander, L., Gerhardinger, K., Bailey, E., Robinson, J., Lin, J., Cuijpers, P., & Mühlmann, C. (2020). Suicide risk management in research on internet-based interventions for depression: A synthesis of the current state and recommendations for future research. Journal of Affective Disorders, 263, 676–683. 10.1016/j.jad.2019.11.045. First citation in articleCrossref Medline, Google ScholarStevens, K., Thambinathan, V., Hollenberg, E., Inglis, F., Johnson, A., Levinson, A., Salman, S., Cardinale, L., Lo, B., Shi, J., Wiljer, D., Korczak, D. J., & Cleverley, K. (2021). Core components and strategies for suicide and risk management protocols in mental health research: A scoping review. BMC Psychiatry, 21(1), Article 13. 10.1186/s12888-020-03005-0 First citation in articleCrossref Medline, Google ScholarTorok, M., Han, J., Baker, S., Werner-Seidler, A., Wong, I., Larsen, M. E., & Christensen, H. (2019). Suicide prevention using self-guided digital interventions: A systematic review and meta-analysis of randomised controlled trials. Lancet Digital Health, 2(1), E25–E36. 10.1016/S2589-7500(19)30199-2 First citation in articleCrossref Medline, Google ScholarWard, C. H., & Wilks, C. R. (2020). Conducting research with individuals at risk for suicide: Protocol for assessment and risk management. Suicide and Life-Threatening Behavior, 50(2), 461–471. 10.1111/sltb.12602. First citation in articleCrossref Medline, Google ScholarYeh, H.-H., Westphal, J., Hu, Y., Peterson, E. L., Williams, L. K., Prabhakar, D., Frank, C., Autio, K., Elsiss, F., Simon, G. E., Beck, A., Lynch, F. L., Rossom, R. C., Lu, C. Y., Owen-Smith, A. A., Waitzfelder, B. E., & Ahmedani, B. K. (2019). Diagnosed mental health conditions and risk of suicide mortality. Psychiatric Services, 70(9), 750–757. 10.1176/appi.ps.201800346 First citation in articleCrossref Medline, Google ScholarZimmerman, M., Balling, C., Chelminski, I., & Dalrymple, K. (2019). Have treatment studies of depression become even less generalizable? Applying the inclusion and exclusion criteria in placebo-controlled antidepressant efficacy trials published over 20 years to a clinical sample. Psychotherapy and Psychosomatics, 88(13), 165–170. 10.1159/000499917 First citation in articleCrossref Medline, Google ScholarZimmerman, M., Chelminski, I., & Posternak, M. A. (2005). Generalizability of antidepressant efficacy trials: Differences between depressed psychiatric outpatients who would or would not qualify for an efficacy trial. American Journal of Psychiatry, 162(7), 1370–1372. 10.1176/appi.ajp.162.7.1370 First citation in articleCrossref Medline, Google ScholarFiguresReferencesRelatedDetails Volume 43Issue 6December 2022ISSN: 0227-5910eISSN: 2151-2396 Published onlineAugust 2, 2022 InformationCrisis (2022), 43, pp. 455-459 https://doi.org/10.1027/0227-5910/a000872.© 2022Hogrefe PublishingPDF download

Background In 2018, Canada legalized the use and sale of non-medical cannabis, with most provinces also permitting home cultivation. To advance the knowledge of home cultivation patterns in Canada within the context of legalization, this study examines (1) the demographics and use patterns of cannabis home growers before and after legalization and (2) the relationship between home cultivation and cannabis-related risks, including workplace use and driving after cannabis use (DACU).Data and methods The study is based on seven waves of the National Cannabis Survey, dating from 2018 to 2019. Descriptive statistics were used to analyze home cultivation across several individual and sociodemographic characteristics pre-and post-legalization. Logistic regression was used to examine whether home cultivation is correlated to selected cannabis-related risks.Results The rate and demographics of home cultivation remained relatively unchanged post-legalization. Those most likely to cultivate cannabis post-legalization were male; 35 years and older; not single; married, common law, divorced, separated or widowed; lived in the Atlantic provinces; consumed cannabis medically or medically and non-medically on a daily or almost daily basis; had more than a high school diploma; and reported "smoking" as their primary consumption method. Home cultivation was correlated to workplace use but not to DACU.Interpretation The research provides early insights into home cultivation within a legalized framework. It also shows a relationship between home cultivation and certain cannabis-related risks (e.g., workplace use), suggesting a need for future research to determine whether tailored education and policy interventions are needed to target cannabis home growers.

Background Inconsistent responding is a type of invalid responding, which occurs on self-report surveys and threatens the reliability and validity of study results. This secondary analysis evaluated the utility of identifying inconsistent responses as a real-time, direct method to improve quality during data collection for an Internet-based RCT. Methods The cannabis subscale of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) was administered as part of eligibility screening for the RCT. Following the consent procedure, the cannabis subscale was repeated during the baseline interview. Responses were automatically compared and individuals with inconsistent responses were screened out. Results Nearly half of those initially eligible for the RCT were subsequently screened out for data quality issues (n = 626, 45.3%). Between-group bivariate analysis found that those screened out (OUT) were significantly older (OUT = 39.5 years (SD = 13.9), IN = 35.7 years (SD = 12.9), p < .001), more had annual incomes less than $20,000CND (OUT = 58.3%, IN = 53.0%, p = .047), used cannabis less often in the past 30 days (OUT = 23.3 days (SD = 9.7), IN = 24.8 days (SD = 11.3), p < .006), and had lower total ASSIST scores at screener (OUT = 19.3 (SD = 8.0), IN = 23.8 (SD = 10.4), p < .001) and baseline (OUT = 17.5 (SD = 7.9), IN = 23.3 (SD = 10.3), p < .001) compared to participants who were screened in to the RCT. Conclusion Inconsistent responding may occur at high rates in Internet research and direct methods to identify invalid responses are needed. Comparing responses for consistency can be programmed in Internet surveys to automatically screen participants during recruitment and reduce the need for post-hoc data cleaning.

BACKGROUND AND AIMS:Given the widespread use of cannabis, and the concomitant risks associated with the drug, there is a need to increase the availability of interventions designed to reduce risky cannabis use. One promising intervention in the addictions employs personalized normative feedback to motivate change. METHODS:A two-arm randomized controlled trial (RCT) was conducted in which participants who used cannabis in a risky fashion were randomly assigned to one of two groups - those who received an online personalized feedback report in addition to educational materials about risky cannabis use and those who just received the online educational materials. Follow-up assessment occurred at three- and six-months post-randomization. Outcome variables included: number of days cannabis was used in the past 30, risky cannabis use (ASSIST score of four or more), and participant estimates of the proportion of cannabis users among those of the same age and gender. RESULTS:A total of 744 participants with risky cannabis use were recruited for the trial using online advertisements. There were no significant differences between intervention and educational materials only groups at three- and six-month follow-ups for the outcome variables, number of days used cannabis in the last 30 (p = 0.927) and proportion of participants engaging in risky cannabis use (p = 0.557). At three and six month follow-ups, participants who received the feedback intervention were more likely than those in the educational materials group to estimate that a larger proportion of people their age and gender did not use cannabis in the last year (p = 0.028). DISCUSSION AND CONCLUSION:While there was some evidence that the personalized feedback intervention modified normative perceptions about cannabis use, there did not appear to be support for the prediction that the intervention reduced cannabis consumption.

BACKGROUND:Despite a strong link between suicide risk and depression, a recent literature review found that many effectiveness studies for online depression interventions exclude individuals at risk of suicide. This study scrutinizes how different suicide risk exclusion criteria impact recruitment rates and final sample characteristics.MATERIALS AND METHODS:Two recruitment periods for an online depression intervention trial utilized different suicide risk cutoff exclusion criteria, a one-point difference on the last item of the Personal Health Questionnaire (i.e., more than 0 (Not at all) vs. more than 1 (Several Days)). Bivariate statistics were used to assess differences in recruitment rates and sample characteristics between these two recruitment periods, while all other eligibility criteria and recruitment strategies remained consistent.RESULTS:The recruitment period using the least restrictive suicide risk exclusion criteria yielded twice as many participants; however, recruited sample characteristics did not significantly differ among demographic or clinical characteristics, despite observable trends.DISCUSSION:Researchers should carefully select suicide risk exclusion criteria that balance recruitment rates, study budgets, and sample selection biases, while minimizing participant harm. Moreover, researchers are urged to report suicide risk exclusion rates and consider these exclusions when interpreting results. Limitations of the results are also discussed.

INTRODUCTION:Using data from an extended follow-up of a randomized trial of mailed nicotine patches, the current secondary analysis explores the continued level of interest in nicotine replacement therapy (NRT) as a means to promote tobacco cessation and whether the purchase of additional NRT was related to tobacco cessation. METHODS:Attempts were made to re-contact participants (N = 999) from a randomized trial of mailed nicotine patches to take part in a five-year follow-up. Those contacted were asked about their current smoking status, interest in free-of-charge NRT, and purchase of other NRT in the time since the 6-month follow-up. RESULTS:A total of 518 participants were successfully interviewed at the five-year time point. While 43.6% of these participants purchased additional NRT, this purchase was unrelated to success at tobacco cessation or to initial group randomization (received/did not received nicotine patches at baseline). Current smokers reported continued interest in receiving free-of charge NRT (77.2% were interested). Participants in the intervention group who reported using all of the nicotine patches they received at baseline (31.8%) were more likely to report purchasing additional NRT (54.9% versus 39.1%; p = .02) and to report not currently smoking at the five-year follow-up (46.2% versus 27.2%; p = .006) compared to those who used some or none of the nicotine patches mailed to them. CONCLUSIONS:The present study found no consistent evidence that NRT is related to long-term success at tobacco cessation. Smokers remain interested in NRT as a means to help them quit smoking.