Toward Tailoring Just-in-Time Adaptive Intervention Systems for Workplace Stress Reduction: Exploratory Analysis of Intervention Implementation.

Suh J ，Howe E ，Lewis R ，Hernandez J ，Saha K ，Althoff T ，Czerwinski M ... -  《JMIR Mental Health》

Impact of summer programmes on the outcomes of disadvantaged or 'at risk' young people: A systematic review.

Many intervention studies of summer programmes examine their impact on employment and education outcomes, however there is growing interest in their effect on young people's offending outcomes. Evidence on summer employment programmes shows promise on this but has not yet been synthesised. This report fills this evidence gap through a systematic review and meta-analysis, covering summer education and summer employment programmes as their contexts and mechanisms are often similar. The objective is to provide evidence on the extent to which summer programmes impact the outcomes of disadvantaged or 'at risk' young people. The review employs mixed methods: we synthesise quantitative information estimating the impact of summer programme allocation/participation across the outcome domains through meta-analysis using the random-effects model; and we synthesise qualitative information relating to contexts, features, mechanisms and implementation issues through thematic synthesis. Literature searches were largely conducted in January 2023. Databases searched include: Scopus; PsychInfo; ERIC; the YFF-EGM; EEF's and TASO's toolkits; RAND's summer programmes evidence review; key academic journals; and Google Scholar. The review employed PICOSS eligibility criteria: the population was disadvantaged or 'at risk' young people aged 10-25; interventions were either summer education or employment programmes; a valid comparison group that did not experience a summer programme was required; studies had to estimate the summer programme's impact on violence and offending, education, employment, socio-emotional and/or health outcomes; eligible study designs were experimental and quasi-experimental; eligible settings were high-income countries. Other eligibility criteria included publication in English, between 2012 and 2022. Process/qualitative evaluations associated with eligible impact studies or of UK-based interventions were also included; the latter given the interests of the sponsors. We used standard methodological procedures expected by The Campbell Collaboration. The search identified 68 eligible studies; with 41 eligible for meta-analysis. Forty-nine studies evaluated 36 summer education programmes, and 19 studies evaluated six summer employment programmes. The number of participants within these studies ranged from less than 100 to nearly 300,000. The PICOSS criteria affects the external applicability of the body of evidence - allowances made regarding study design to prioritise evidence on UK-based interventions limits our ability to assess impact for some interventions. The risk of bias assessment categorised approximately 75% of the impact evaluations as low quality, due to attrition, losses to follow up, interventions having low take-up rates, or where allocation might introduce selection bias. As such, intention-to-treat analyses are prioritised. The quality assessment rated 93% of qualitative studies as low quality often due to not employing rigorous qualitative methodologies. These results highlight the need to improve the evidence. Quantitative synthesis The quantitative synthesis examined impact estimates across 34 outcomes, through meta-analysis (22) or in narrative form (12). We summarise below the findings where meta-analysis was possible, along with the researchers' judgement of the security of the findings (high, moderate or low). This was based on the number and study-design quality of studies evaluating the outcome; the consistency of findings; the similarity in specific outcome measures used; and any other specific issues which might affect our confidence in the summary findings.Below we summarise the findings from the meta-analyses conducted to assess the impact of allocation to/participation in summer education and employment programmes (findings in relation to other outcomes are also discussed in the main body, but due to the low number of studies evaluating these, meta-analysis was not performed). We only cover the pooled results for the two programme types where there are not clear differences in findings between summer education and summer employment programmes, so as to avoid potentially attributing any impact to both summer programme types when this is not the case. We list the outcome measure, the average effect size type (i.e., whether a standardised mean difference (SMD) or log odds ratio), which programme type the finding is in relation to and then the average effect size along with its 95% confidence interval and the interpretation of the finding, that is, whether there appears to be a significant impact and in which direction (positive or negative, clarifying instances where a negative impact is beneficial). In some instances there may be a discrepancy between the 95% confidence interval and whether we determine there to be a significant impact, which will be due to the specifics of the process for constructing the effect sizes used in the meta-analysis. We then list the I 2 statistic and the p-value from the homogeneity test as indications of the presence of heterogeneity. As the sample size used in the analysis are often small and the homogeneity test is known to be under-powered with small sample sizes, it may not detect statistically significant heterogeneity when it is in fact present. As such, a 90% confidence level threshold should generally be used when interpreting this with regard to the meta-analyses below. The presence of effect size heterogeneity affects the extent to which the average effects size is applicable to all interventions of that summer programme type. We also provide an assessment of the relative confidence we have in the generalisability of the overall finding (low, moderate or high) - some of the overall findings are based on a small sample of studies, the studies evaluating the outcome may be of low quality, there may be wide variation in findings among the studies evaluating the outcome, or there may be specific aspects of the impact estimates included or the effect sizes constructed that affect the generalisability of the headline finding. These issues are detailed in full in the main body of the review. -Engagement with/participation in/enjoyment of education (SMD):∘Summer education programmes: +0.12 (+0.03, +0.20); positive impact; I 2 = 48.76%, p = 0.10; moderate confidence.-Secondary education attendance (SMD):∘Summer education programmes: +0.26 (+0.08, +0.44); positive impact; I 2 = N/A; p = N/A; low confidence.∘Summer employment programmes: +0.02 (-0.03, +0.07); no impact; I 2 = 69.98%; p = 0.03; low confidence.-Passing tests (log OR):∘Summer education programmes: +0.41 (-0.13, +0.96); no impact; I 2 = 95.05%; p = 0.00; low confidence.∘Summer employment programmes: +0.02 (+0.00, +0.04); positive impact; I 2 = 0.01%; p = 0.33; low confidence.-Reading test scores (SMD):∘Summer education programmes: +0.01 (-0.04, +0.05); no impact; I 2 = 0.40%; p = 0.48; high confidence.-English test scores (SMD):∘Summer education programmes: +0.07 (+0.00, +0.13); positive impact; I 2 = 27.17%; p = 0.33; moderate confidence.∘Summer employment programmes: -0.03 (-0.05, -0.01); negative impact; I 2 = 0.00%; p = 0.76; low confidence.-Mathematics test scores (SMD):∘All summer programmes: +0.09 (-0.06, +0.25); no impact; I 2 = 94.53%; p = 0.00; high confidence.∘Summer education programmes: +0.14 (-0.09, +0.36); no impact; I 2 = 94.15%; p = 0.00; moderate confidence.∘Summer employment programmes: +0.00 (-0.04, +0.05); no impact; I 2 = 0.04%; p = 0.92; moderate confidence.-Overall test scores (SMD):∘Summer employment programmes: -0.01 (-0.08, +0.05); no impact; I 2 = 32.39%; p = 0.20; high confidence.-All test scores (SMD):∘Summer education programmes: +0.14 (+0.00, +0.27); positive impact; I 2 = 91.07%; p = 0.00; moderate confidence.∘Summer employment programmes: -0.01 (-0.04, +0.01); no impact; I 2 = 0.06%; p = 0.73; high confidence.-Negative behavioural outcomes (log OR):∘Summer education programmes: -1.55 (-3.14, +0.03); negative impact; I 2 = N/A; p = N/A; low confidence.∘Summer employment programmes: -0.07 (-0.33, +0.18); no impact; I 2 = 88.17%; p = 0.00; moderate confidence.-Progression to HE (log OR):∘All summer programmes: +0.24 (-0.04, +0.52); no impact; I 2 = 97.37%; p = 0.00; low confidence.∘Summer education programmes: +0.32 (-0.12, +0.76); no impact; I 2 = 96.58%; p = 0.00; low confidence.∘Summer employment programmes: +0.10 (-0.07, +0.26); no impact; I 2 = 76.61%; p = 0.02; moderate confidence.-Complete HE (log OR):∘Summer education programmes: +0.38 (+0.15, +0.62); positive impact; I 2 = 52.52%; p = 0.06; high confidence.∘Summer employment programmes: +0.07 (-0.19, +0.33); no impact; I 2 = 70.54%; p = 0.07; moderate confidence.-Entry to employment, short-term (log OR):∘Summer employment programmes: -0.19 (-0.45, +0.08); no impact; I 2 = 87.81%; p = 0.00; low confidence.∘Entry to employment, full period (log OR)∘Summer employment programmes: -0.15 (-0.35, +0.05); no impact; I 2 = 78.88%; p = 0.00; low confidence.-Likelihood of having a criminal justice outcome (log OR):∘Summer employment programmes: -0.05 (-0.15, +0.05); no impact; I 2 = 0.00%; p = 0.76; low confidence.-Likelihood of having a drug-related criminal justice outcome (log OR):∘Summer employment programmes: +0.16 (-0.57, +0.89); no impact; I 2 = 65.97%; p = 0.09; low confidence.-Likelihood of having a violence-related criminal justice outcome (log OR):∘Summer employment programmes: +0.03 (-0.02, +0.08); no impact; I 2 = 0.00%; p = 0.22; moderate confidence.-Likelihood of having a property-related criminal justice outcome (log OR):∘Summer employment programmes: +0.09 (-0.17, +0.34); no impact; I 2 = 45.01%; p = 0.18; low confidence.-Number of criminal justice outcomes, during programme (SMD):∘Summer employment programmes: -0.01 (-0.03, +0.00); no impact; I 2 = 2.17%; p = 0.31; low confidence.-Number of criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.01 (-0.03, +0.00); no impact; I 2 = 23.57%; p = 0.37; low confidence.-Number of drug-related criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.01 (-0.06, +0.06); no impact; I 2 = 55.19%; p = 0.14; moderate confidence.-Number of violence-related criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.02 (-0.08, +0.03); no impact; I 2 = 44.48%; p = 0.18; low confidence.-Number of property-related criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.02 (-0.10, +0.05); no impact; I 2 = 64.93%; p = 0.09; low confidence. We re-express instances of significant impact by programme type where we have moderate or high confidence in the security of findings by translating this to a form used by one of the studies, to aid understanding of the findings. Allocation to a summer education programme results in approximately 60% of individuals moving from never reading for fun to doing so once or twice a month (engagement in/participation in/enjoyment of education), and an increase in the English Grade Point Average of 0.08. Participation in a summer education programme results in an increase in overall Grade Point Average of 0.14 and increases the likelihood of completing higher education by 1.5 times. Signs are positive for the effectiveness of summer education programmes in achieving some of the education outcomes considered (particularly on test scores (when pooled across types), completion of higher education and STEM-related higher education outcomes), but the evidence on which overall findings are based is often weak. Summer employment programmes appear to have a limited impact on employment outcomes, if anything, a negative impact on the likelihood of entering employment outside of employment related to the programme. The evidence base for impacts of summer employment programmes on young people's violence and offending type outcomes is currently limited - where impact is detected this largely results in substantial reductions in criminal justice outcomes, but the variation in findings across and within studies affects our ability to make any overarching assertions with confidence. In understanding the effectiveness of summer programmes, the order of outcomes also requires consideration - entries into education from a summer employment programme might be beneficial if this leads towards better quality employment in the future and a reduced propensity of criminal justice outcomes. Various shared features among different summer education programmes emerged from the review, allowing us to cluster specific types of these interventions which then aided the structuring of the thematic synthesis. The three distinct clusters for summer education programmes were: catch-up programmes addressing attainment gaps, raising aspirations programmes inspiring young people to pursue the next stage of their education or career, and transition support programmes facilitating smooth transitions between educational levels. Depending on their aim, summer education programme tend to provide a combination of: additional instruction on core subjects (e.g., English, mathematics); academic classes including to enhance specialist subject knowledge (e.g., STEM-related); homework help; coaching and mentoring; arts and recreation electives; and social and enrichment activities. Summer employment programmes provide paid work placements or subsidised jobs typically in entry-level roles mostly in the third and public sectors, with some summer employment programmes also providing placements in the private sector. They usually include components of pre-work training and employability skills, coaching and mentoring. There are a number of mechanisms which act as facilitators or barriers to engagement in summer programmes. These include tailoring the summer programme to each young person and individualised attention; the presence of well-prepared staff who provide effective academic/workplace and socio-emotional support; incentives of a monetary (e.g., stipends and wages) or non-monetary (e.g., free transport and meals) nature; recruitment strategies, which are effective at identifying, targeting and engaging participants who can most benefit from the intervention; partnerships, with key actors who can help facilitate referrals and recruitment, such as schools, community action and workforce development agencies; format, including providing social activities and opportunities to support the formation of connections with peers; integration into the workplace, through pre-placement engagement, such as through orientation days, pre-work skills training, job fairs, and interactions with employers ahead of the beginning of the summer programme; and skill acquisition, such as improvements in social skills. In terms of the causal processes which lead from engagement in a summer programme to outcomes, these include: skill acquisition, including academic, social, emotional, and life skills; positive relationships with peers, including with older students as mentors in summer education programmes; personalised and positive relationships with staff; location, including accessibility and creating familiar environments; creating connections between the summer education programme and the students' learning at home to maintain continuity and reinforce learning; and providing purposeful and meaningful work through summer employment programmes (potentially facilitated through the provision of financial and/or non-financial incentives), which makes participants more likely to see the importance of education in achieving their life goals and this leads to raised aspirations. It is important to note that no single element of a summer programme can be identified as generating the causal process for impact, and impact results rather from a combination of elements. Finally, we investigated strengths and weaknesses in summer programmes at both the design and implementation stages. In summer education programmes, design strengths include interactive and alternative learning modes; iterative and progressive content building; incorporating confidence building activities; careful lesson planning; and teacher support which is tailored to each student. Design weaknesses include insufficient funding or poor funding governance (e.g., delays to funding); limited reach of the target population; and inadequate allocation of teacher and pupil groups (i.e., misalignment between the education stage of the pupils and the content taught by staff). Implementation strengths include clear programme delivery guidance and good governance; high quality academic instruction; mentoring support; and strong partnerships. Implementation weaknesses include insufficient planning and lead in time; recruitment challenges; and variability in teaching quality. In summer employment programmes, design strengths include use of employer orientation materials and supervisor handbooks; careful consideration of programme staff roles; a wide range of job opportunities; and building a network of engaged employers. Design weaknesses are uncertainty over funding and budget agreements; variation in delivery and quality of training between providers; challenges in recruitment of employers; and caseload size and management. Implementation strengths include effective job matching; supportive relationships with supervisors; pre-work training; and mitigating attrition (e.g., striving to increase take up of the intervention among the treatment group). Implementation weaknesses are insufficient monitors for the number of participants, and challenges around employer availability.

Muir D ，Orlando C ，Newton B 《-》

The effectiveness of mindfulness based programs in reducing stress experienced by nurses in adult hospital settings: a systematic review of quantitative evidence protocol.

Botha E ，Gwin T ，Purpora C 《-》

Improving Employee Well-Being and Effectiveness: Systematic Review and Meta-Analysis of Web-Based Psychological Interventions Delivered in the Workplace.

Stress, depression, and anxiety among working populations can result in reduced work performance and increased absenteeism. Although there is evidence that these common mental health problems are preventable and treatable in the workplace, uptake of psychological treatments among the working population is low. One way to address this may be the delivery of occupational digital mental health interventions. While there is convincing evidence for delivering digital psychological interventions within a health and community context, there is no systematic review or meta-analysis of these interventions in an occupational setting. The aim of this study was to identify the effectiveness of occupational digital mental health interventions in enhancing employee psychological well-being and increasing work effectiveness and to identify intervention features associated with the highest rates of engagement and adherence. A systematic review of the literature was conducted using Cochrane guidelines. Papers published from January 2000 to May 2016 were searched in the PsychINFO, MEDLINE, PubMed, Science Direct, and the Cochrane databases, as well as the databases of the researchers and relevant websites. Unpublished data was sought using the Conference Proceedings Citation Index and the Clinical Trials and International Standard Randomized Controlled Trial Number (ISRCTN) research registers. A meta-analysis was conducted by applying a random-effects model to assess the pooled effect size for psychological well-being and the work effectiveness outcomes. A positive deviance approach was used to identify those intervention features associated with the highest rates of engagement and adherence. In total, 21 randomized controlled trials (RCTs) met the search criteria. Occupational digital mental health interventions had a statistically significant effect post intervention on both psychological well-being (g=0.37, 95% CI 0.23-0.50) and work effectiveness (g=0.25, 95% CI 0.09-0.41) compared with the control condition. No statistically significant differences were found on either outcome between studies using cognitive behavioral therapy (CBT) approaches (as defined by the authors) compared with other psychological approaches, offering guidance compared with self-guidance, or recruiting from a targeted workplace population compared with a universal workplace population. In-depth analysis of the interventions identified by the positive deviance approach suggests that interventions that offer guidance are delivered over a shorter time frame (6 to 7 weeks), utilize secondary modalities for delivering the interventions and engaging users (ie, emails and text messages [short message service, SMS]), and use elements of persuasive technology (ie, self-monitoring and tailoring), which may achieve greater engagement and adherence. This review provides evidence that occupational digital mental health interventions can improve workers' psychological well-being and increase work effectiveness. It identifies intervention characteristics that may increase engagement. Recommendations are made for future research, practice, and intervention development.

Carolan S ，Harris PR ，Cavanagh K 《JOURNAL OF MEDICAL INTERNET RESEARCH》

Smartphone App Delivery of a Just-In-Time Adaptive Intervention for Adult Gamblers (Gambling Habit Hacker): Protocol for a Microrandomized Trial.

People with gambling problems frequently report repeated unsuccessful attempts to change their behavior. Although many behavior change techniques are available to individuals to reduce gambling harm, they can be challenging to implement or maintain. The provision of implementation support tailored for immediate, real-time, individualized circumstances may improve attempts at behavior change. We aimed to develop and evaluate a Just-In-Time Adaptive Intervention (JITAI) for individuals who require support to adhere to their gambling limits. JITAI development is based on the principles of the Health Action Process Approach with delivery, in alignment with the principles of self-determination theory. The primary objective was to determine the effect of action- and coping planning compared with no intervention on the goal of subsequently adhering to gambling expenditure limits. Gambling Habit Hacker is delivered as a JITAI providing in-the-moment support for adhering to gambling expenditure limits (primary proximal outcome). Delivered via a smartphone app, this JITAI delivers tailored behavior change techniques related to goal setting, action planning, coping planning, and self-monitoring. The Gambling Habit Hacker app will be evaluated using a 28-day microrandomized trial. Up to 200 individuals seeking support for their own gambling from Australia and New Zealand will set a gambling expenditure limit (ie, goal). They will then be asked to complete 3 time-based ecological momentary assessments (EMAs) per day over a 28-day period. EMAs will assess real-time adherence to gambling limits, strength of intention to adhere to goals, goal self-efficacy, urge self-efficacy, and being in high-risk situations. On the basis of the responses to each EMA, participants will be randomized to the control (a set of 25 self-enactable strategies containing names only and no implementation information) or intervention (self-enactable strategy implementation information with facilitated action- and coping planning) conditions. This microrandomized trial will be supplemented with a 6-month within-group follow-up that explores the long-term impact of the app on gambling expenditure (primary distal outcome) and a range of secondary outcomes, as well as an evaluation of the acceptability of the JITAI via postintervention surveys, app use and engagement indices, and semistructured interviews. This trial has been approved by the Deakin University Human Research Ethics Committee (2020-304). The intervention has been subject to expert user testing, with high acceptability scores. The results will inform a more nuanced version of the Gambling Habit Hacker app for wider use. Gambling Habit Hacker is part of a suite of interventions for addictive behaviors that deliver implementation support grounded in lived experience. This study may inform the usefulness of delivering implementation intentions in real time and in real-world settings. It potentially offers people with gambling problems new support to set their gambling intentions and adhere to their limits. Australian New Zealand Clinical Trials Registry ACTRN12622000497707; www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383568. DERR1-10.2196/38919.

Rodda SN ，Bagot KL ，Merkouris SS ，Youssef G ，Lubman DI ，Thomas AC ，Dowling NA ... -  《JMIR Research Protocols》