Mobile Delivery of Mindfulness-Based Smoking Cessation Treatment Among Low-Income Adults During the COVID-19 Pandemic: Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Smoking is the leading cause of premature death, and low-income adults experience disproportionate burden from tobacco. Mindfulness interventions show promise for improving smoking cessation. A text messaging program "iQuit Mindfully" was developed to deliver just-in-time support for quitting smoking among low-income adults. A pilot study of iQuit Mindfully was conducted in spring 2020, during the COVID-19 pandemic, among low-income and predominantly African American smokers. OBJECTIVE: This pilot study examined the acceptability and feasibility of delivering Mindfulness-Based Addiction Treatment via mHealth during the COVID-19 pandemic. METHODS: Participants were adult cigarette smokers (n=23), of whom 8 (34.8%) were female, 19 (82.6%) were African American, and 18 (78.3%) had an annual income of <US $24,000. They were randomly assigned to either 8 weeks of iQuit Mindfully as a fully automated standalone intervention or iQuit Mindfully in combination with therapist-led in-person group treatment. For participant safety, in-person mindfulness groups were transitioned to the internet and assessments also took place over the internet. Survey questions asked participants about changes in their stress, smoking habits and quit attempts, and their perceptions of the mindfulness and text messaging intervention in the context of the pandemic. RESULTS: Most participants (n=15 of 21, 71.4%) indicated a change in stress due to the pandemic, of whom 14 (93.3%) indicated higher stress. Participants shared concerns about finances, homelessness, health, and social isolation. Most (n=17 of 21, 80.9%) believed that smoking increases the risk of contracting COVID-19, and although that was motivating for some, others expressed lower motivation to quit smoking because of higher stress. Most (n=18 of 21, 85.7%) stated that practicing mindfulness was helpful during the pandemic. Mean ratings of the helpfulness of text messages and the extent to which they would recommend the program to others were 7.1 (median 8 on a 10-point scale, SD 2.9) and 8.2 (median 9, SD 2.5), respectively. Through open-ended program evaluations, participants shared details about how mindfulness practices and the text messages helped them manage stress and feel a sense of social support during the pandemic. Moreover, 10 of 19 (52.6%) of participants achieved 7-day abstinence from smoking, with no differences between conditions. CONCLUSIONS: This study supports the promise of text messaging and the use of teleconferencing to provide mindfulness and smoking cessation services to underserved populations during a pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".