Explore the vast range of titles available.

Choose to Move (CTM), an effective health-promoting intervention for older adults, was scaled-up across British Columbia, Canada. Adaptations that enable implementation at scale may lead to 'voltage drop'-diminished positive effects of the intervention. For CTM Phase 3 we assessed: i. implementation; ii. impact on physical activity, mobility, social isolation, loneliness and health-related quality of life (impact outcomes); iii. whether intervention effects were maintained; iv) voltage drop, compared with previous CTM phases. We conducted a type 2 hybrid effectiveness-implementation pre-post study of CTM; older adult participants (n = 1012; mean age 72.9, SD = 6.3 years; 80.6% female) were recruited by community delivery partners. We assessed CTM implementation indicators and impact outcomes via survey at 0 (baseline), 3 (mid-intervention), 6 (end-intervention) and 18 (12-month follow-up) months. We fitted mixed-effects models to describe change in impact outcomes in younger (60-74 years) and older (≥ 75 years) participants. We quantified voltage drop as percent of effect size (change from baseline to 3- and 6-months) retained in Phase 3 compared with Phases 1-2. Adaptation did not compromise fidelity of CTM Phase 3 as program components were delivered as intended. PA increased during the first 3 months in younger (+1 days/week) and older (+0.9 days/week) participants (p<0.001), and was maintained at 6- and 18-months. In all participants, social isolation and loneliness decreased during the intervention, but increased during follow-up. Mobility improved during the intervention in younger participants only. Health-related quality of life according to EQ-5D-5L score did not change significantly in younger or older participants. However, EQ-5D-5L visual analog scale score increased during the intervention in younger participants (p<0.001), and this increase was maintained during follow-up. Across all outcomes, the median difference in effect size, or voltage drop, between Phase 3 and Phases 1-2 was 52.6%. However, declines in social isolation were almost two times greater in Phase 3, compared with Phases 1-2. Benefits of health-promoting interventions-like CTM-can be retained when implemented at broad scale. Diminished social isolation in Phase 3 reflects how CTM was adapted to enhance opportunities for older adults to socially connect. Thus, although intervention effects may be reduced at scale-up, voltage drop is not inevitable.

Jack's grandfather is always grumpy, and a bit scary, too, but during a visit to the country house where \"Grumpy Grandpa\" lives with the brave Aunt Ellie and Uncle Wilbur, Jack learns that his grandfather was once very different.

Funding agencies and research journals are increasingly demanding that researchers share their data in public repositories. Despite these requirements, researchers still withhold data, refuse to share, and deposit data that lacks annotation. We conducted a meta-synthesis to examine the views, perspectives, and experiences of academic researchers on data sharing and reuse of research data. We searched the published and unpublished literature for studies on data sharing by researchers in academic institutions. Two independent reviewers screened citations and abstracts, then full-text articles. Data abstraction was performed independently by two investigators. The abstracted data was read and reread in order to generate codes. Key concepts were identified and thematic analysis was used for data synthesis. We reviewed 2005 records and included 45 studies along with 3 companion reports. The studies were published between 2003 and 2018 and most were conducted in North America (60%) or Europe (17%). The four major themes that emerged were data integrity, responsible conduct of research, feasibility of sharing data, and value of sharing data. Researchers lack time, resources, and skills to effectively share their data in public repositories. Data quality is affected by this, along with subjective decisions around what is considered to be worth sharing. Deficits in infrastructure also impede the availability of research data. Incentives for sharing data are lacking. Researchers lack skills to share data in a manner that is efficient and effective. Improved infrastructure support would allow them to make data available quickly and seamlessly. The lack of incentives for sharing research data with regards to academic appointment, promotion, recognition, and rewards need to be addressed.

Correction: Int J Behav Nutr Phys Act 21, 140 (2024) https://doi.org/10.1186/s12966-024-01649-9 After publication of the original article [1], we identified an error that impacted the analysis of one secondary outcome (social isolation). [...]for comparison with previous CTM phases (e.g., to estimate voltage drop with scale-up), we believe it is more appropriate to create a single combined response from the two items asking about participation in meetings and programs and use the combined response to calculate the social isolation score. Adjusted means (95% confidence interval) for impact outcome measures by time point and age group Months Full sample (n = 1126) < 75 years (n = 783) ≥ 75 years (n = 319) p-value Full sample 0–3 mos p-value < 75 yrs 0–3 mos p-value ≥ 75 yrs 0–3 mos Physical activity (# days/week > 30 min) 0 2.1 (2.0, 2.2) 2.0 (1.8, 2.1) 2.3 (2.1, 2.6) 3 3.4 (3.3, 3.5) 3.4 (3.3, 3.6) 3.3 (3.1, 3.6) < 0.001 < 0.001 < 0.001 Mobility (n (%) reporting any limitation) 0 454 (40.6%) 290 (37.2%) 159 (50.3%) 3 324 (34.6%) 199 (30.8%) 121 (44.8%) 0.005 0.010 0.184 Mobility (MAT-sf score, 30–80) 0 51.4 (50.8, 52.0) 52.7 (52.0, 53.4) 47.9 (46.8, 49.1) 3 52.3 (51.7, 52.9) 53.4 (52.9, 54.3) 49.0 (47.9, 50.2) < 0.001 < 0.001 0.002 Social Isolation (score, 0–15) 0 11.1 (10.9, 11.3) 10.8 (10.6, 11.0) 11.8 (11.4, 12.1) 3 11.7 (11.5, 11.9) 11.5 (11.3, 11.7) 12.1 (11.7, 12.4) < 0.001 < 0.001 0.048 Loneliness (score, 3–9) 0 5.21 (5.09, 5.31) 5.35 (5.22, 5.48) 4.83 (4.62, 5.04) 3 5.04 (4.92, 5.15) 5.12 (4.98, 5.25) 4.86 (4.64, 5.07) < 0.001 < 0.001 0.775 Some text has also been corrected Incorrect Abstract Post-intervention, PA (+ 1.4 days/week; 95% CI 1.3, 1.6), mobility limitations (-6.4%), and scores for mobility (+ 0.7; 95% CI: 0.4, 1.3), social isolation (+ 0.9; 95% CI: 0.67, 1.17), and loneliness (-0.23; 95% CI: -0.34, -0.13) were improved in those < 75 years. [...]to facilitate comparison with previous phases (i.e., maintain a score range of 0–15) we created a single summary response for online and in-person programs before summing to create a final social isolation score.

Background Few studies have examined costs of implementing evidence-based interventions (EBIs) as scale-up proceeds. Across four phases, we co-adapted and scaled up an effective EBI designed to promote older adults’ health (Choose to Move; CTM). Following formative evaluation (2015), Phases 1–2 (2016-17) comprised the CTM pilot and early scale-up. For Phase 3 (2018-20), we adapted CTM to establish “best fit” and support broad scale-up. In response to COVID-19 (2020), we adapted CTM for virtual delivery. For Phase 4 (2020-22), we adapted CTM to reduce resource use. We aimed to (1) identify, measure, and value costs of implementing CTM across four phases (7 years) of scale-up; and (2) analyze change in implementation costs alongside changes in intervention effect sizes to assess cost-consequence trends from Phases 1–2 through Phase 4. Methods We conducted a trial-based cost and cost-consequence analysis of CTM Phases 1–2 through Phase 4 from a program provider perspective. Program costs were identified, measured, and valued using micro-costing techniques; variation in program cost was explored using scenario analyses. We compared Phase 4 intervention effects against those of Phases 1–2 and Phase 3 to examine how changes in implementation costs corresponded with changes in effect size. Results For Phases 1–2, total cost ($CDN, 2024) of CTM implementation was $863,559 for 55 programs (534 participants; $1,617/participant). Phase 3 costs were $1,564,446 for 165 programs (1668 participants; $938/participant). Phase 4 costs were $760,983 for 135 programs (1278 participants; $595/participant), a reduction of 63% and 37% compared with Phases 1–2 and Phase 3, respectively. Compared with Phases 1–2, Phase 4 had a greater positive effect on social isolation but effect sizes for physical activity, mobility and loneliness were reduced. Phase 4 had a greater positive effect on physical activity and mobility in all participants, and loneliness among those < 75 years, compared with Phase 3. Conclusions Costs associated with broad scale-up of EBIs are rarely investigated. We sought innovative ways to maximize impact of a health-promoting EBI, while minimizing costs. Our analysis highlights how strategic adaptations can enhance cost efficiency while improving intervention outcomes; this represents an emergent application of economic analysis within scale-up science. Trial registration Retrospectively registered at ClinicalTrials.gov, NCT05678985 (CTM Phase 4) and NCT05497648 (CTM Phase 3).

Using a policy-capturing approach with a broad student sample we examine how individuals' economic, social and environmental values influence their propensity to engage in a broad range of sustainability-related corporate actions. We employ a multi-dimensional sustainability framework of corporate actions and account for both the positive and negative impacts associated with corporate activity—termed strength and concern actions, respectively. Strong economic values were found to increase the propensity for concern actions and the willingness to work in controversial industries. Individuals with balanced values were as likely as those with strong economic values to pursue positive economic outcomes, but without the same downside potential for concern actions. We also found significant gender effects, with females being less likely to engage in concern actions and more supportive of social and environmental strength actions.

Background Investment in scale-up and sustainment of effective health-promoting programs is often hampered by competing demands on scarce health dollars. Thus, optimizing programs to reduce resource use (e.g., delivery costs) while maintaining effectiveness is necessary to promote health at scale. Using a phased approach (2015–2024), we adapted and scaled-up an evidence-based, health-promoting program for older adults (Choose to Move; CTM). For CTM Phase 4 we undertook a systematic, data-driven adaptation process to reduce resource use. In this paper we: 1) describe the CTM Phase 4 program (‘CTM Phase 4’) and assess its 2) implementation and 3) effectiveness. Methods For CTM Phase 4 (30-min one-on-one consultation and 8, 60-min group meetings with an activity coach), we reduced activity coach hours by 40% compared to Phase 3. To evaluate effectiveness of CTM Phase 4 we conducted a type 2 hybrid effectiveness-implementation study involving 137 programs (1126 older adults; 59–74 years, 75 + years) delivered by 29 activity coaches. We assessed implementation indicators (e.g., dose, fidelity, adaptation, participant responsiveness, self-efficacy) via survey in activity coaches and older adults. We assessed older adults’ physical activity (PA), mobility, social isolation, and loneliness before and after (0, 3 months) the program. Results Implementation indicators demonstrated that CTM Phase 4 was delivered successfully. Post-intervention, PA (+ 1.5 days/week; 95% CI 1.3, 1.6), mobility limitations (-6.4%), and scores for mobility (+ 0.7; 95% CI: 0.4, 1.3), social isolation (+ 0.69; 95% CI: 0.50, 0.89), and loneliness (-0.24; 95% CI: -0.34, -0.13) were improved in those < 75 years. Among those ≥ 75 years, PA (+ 1.0 days/week; 95% CI, 0.7, 1.2), mobility score (+ 1.1; 95% CI: 0.4, 1.8), and social isolation score (+ 0.31; 95% CI: 0.002, 0.61) were improved post-intervention. Overall, participant-level benefits were comparable to those observed in Phase 3. Conclusions CTM was co-designed as a flexible program, adapted over time based on user group needs and preferences. This flexibility enabled us to reduce activity coach delivery hours without compromising implementation or benefits to older adults’ health. Optimizing effective health-promoting programs to enhance their scalability and sustainability provides an important pathway to improved population health. Trial Registration ClinicalTrials.gov, NCT05678985. Registered 10 January 2023 – Retrospectively registered, https://clinicaltrials.gov/study/NCT05678985 .

Background A key challenge to implementing and scaling up evidence-based interventions (EBIs) into practice is organisational readiness; described as an organisation’s motivation, general capacities, and capabilities specific to the EBI. Building organisational readiness has been investigated in some health disciplines (e.g., mental health). However, the importance of building organisational readiness to effectively implement public health EBIs for adults and older adults in the community setting remains largely unexplored. Our aim was to examine how readiness was defined and measured, what strategies were used to build readiness, and the relationship between readiness-building strategies and implementation, service-level, and person-level outcomes. Methods In this scoping review, we searched seven databases and conducted forward and backward citation tracking. From a pool of eight reviewers, combinations of two reviewers independently screened references for eligibility. A single reviewer extracted data, and a second reviewer checked data. Results for each implementation, service-level and person-level outcome in each study were extracted and categorised as favourable, nonsignificant, or unfavourable. Results Twelve studies were included, which implemented a mix of different public health EBIs to almost 40,000 participants ( n  = 37,883; 54% women) across varied community settings. Only four studies defined readiness; all used different definitions. Five studies used five different instruments to assess readiness, all with poor psychometric properties. All studies used multiple strategies to build readiness (range 4–20 strategies per study), with all using strategies to assess, plan and monitor implementation of the EBI (i.e., ‘evaluative and iterative strategies’) and strategies to support collaboration between organisations delivering the EBI (i.e., ‘develop interest-holder interrelationships’). Three-quarters of the strategies focused on building the organisation’s capability to deliver the specific EBI (e.g., assessing readiness, conducting educational meetings) and were delivered by external support teams. Exploring the relationship between readiness-building strategies and study outcomes indicated more favourable than unfavourable outcomes, particularly for implementation and service-level outcomes (38/48; 79% favourable). Conclusions Within this limited sample, the use of readiness-building strategies improved the implementation of public health EBIs in community organisations. However, consistency of definitions and terminology and more sophisticated testing of readiness-building strategies will help confirm how best to do this. Trial registration Open Science Framework, May 5, 2024.

Background Pregnant women with epilepsy frequently experience seizures related to pregnancy complications and are often prescribed anti-epileptic drugs (AEDs) to manage their symptoms. However, less is known about the comparative safety of AED exposure in utero. We aimed to compare the risk of congenital malformations (CMs) and prenatal outcomes of AEDs in infants/children who were exposed to AEDs in utero through a systematic review and Bayesian random-effects network meta-analysis. Methods MEDLINE, EMBASE, and Cochrane CENTRAL were searched from inception to December 15, 2015. Two reviewers independently screened titles/abstracts and full-text papers for experimental and observational studies comparing mono- or poly-therapy AEDs versus control (no AED exposure) or other AEDs, then abstracted data and appraised the risk of bias. The primary outcome was incidence of major CMs, overall and by specific type (cardiac malformations, hypospadias, cleft lip and/or palate, club foot, inguinal hernia, and undescended testes). Results After screening 5305 titles and abstracts, 642 potentially relevant full-text articles, and 17 studies from scanning reference lists, 96 studies were eligible (n = 58,461 patients). Across all major CMs, many AEDs were associated with higher risk compared to control. For major CMs, ethosuximide (OR, 3.04; 95% CrI, 1.23–7.07), valproate (OR, 2.93; 95% CrI, 2.36–3.69), topiramate (OR, 1.90; 95% CrI, 1.17–2.97), phenobarbital (OR, 1.83; 95% CrI, 1.35–2.47), phenytoin (OR, 1.67; 95% CrI, 1.30–2.17), carbamazepine (OR, 1.37; 95% CrI, 1.10–1.71), and 11 polytherapies were significantly more harmful than control, but lamotrigine (OR, 0.96; 95% CrI, 0.72–1.25) and levetiracetam (OR, 0.72; 95% CrI, 0.43–1.16) were not. Conclusion The newer generation AEDs, lamotrigine and levetiracetam, were not associated with significant increased risks of CMs compared to control, and were significantly less likely to be associated with children experiencing cardiac malformations than control. However, this does not mean that these agents are not harmful to infants/children exposed in utero. Counselling is advised concerning teratogenic risks when the prescription is written for a woman of childbearing age and before women continue with these agents when considering pregnancy, such as switching from polytherapy to monotherapy with evidence of lower risk and avoiding AEDs, such as valproate, that are consistently associated with CMs. These decisions must be balanced against the need for seizure control. Systematic Review Registration PROSPERO CRD42014008925