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Several models of leadership outline theories on successful intervention such as “Observe, Interpret, and Intervene” within the Adaptive Leadership model (Heifetz, Grashow, & Linsky, 2009) or the “Five Practices” within Kouzes & Posner’s (2012) work. However, during stressful moments of leadership practice, many models for leadership intervention are difficult for students to implement. The authors suggest the pVASE framework as an additional component to other intervention models of leadership in order to better support cognitive load and leadership problem-solving during real-time, emergent leadership moments within and beyond the classroom.

The purpose of this paper is to estimate the impact of the 2008 and 2020 economic crises on employment in Spain.

The authors perform a counterfactual analysis, combining intervention (interrupted time series) analysis and conditional forecasting to estimate a “crisis-free” scenario. These counterfactual estimates are used as a synthetic control, to be compared with the observed values of the main variables of the Spanish Labor Force Survey (EPA).

The authors measure the effect on Spanish employment of the 2008 recession and the ongoing COVID/Ukraine crisis and the speed of recovery, which yields a rigorous dating for the beginning and end of the crises studied. Finally, the authors provide estimates about which part of the employed and unemployed people was in furlough (ERTE) based on microdata provided by the Spanish Institute of Statistics.

To the best of the authors’ knowledge, there are no counterfactual studies covering all the basic variables in EPA and no estimates for the effect of ERTEs on the basic employment variables. Finally, the authors combine well-known intervention and forecasting techniques into an integrated framework to assess the effects of both, past and ongoing crises.

In previous studies, outcomes of leadership training have varied, with some studies suggesting large effects and others small. Although the transfer of training literature suggests a number of factors that influence training outcomes, this knowledge has seldom been used when evaluating the outcomes of leadership training. The purpose of the present study is therefore to examine how factors related to transfer of training influence outcomes of leadership training.

In the present research, follower-rated outcomes of a leadership training program in Denmark (N = 298) was examined from a transfer of training perspective.

Using Baldwin and Ford's transfer of training model as a framework, analyses revealed that leaders' utility reactions (i.e. perception of usefulness) and learning were linked to transfer of training. In addition, leaders' perceptions of transfer were associated with post-intervention follower-rated transformational leadership and collective self-efficacy.

Making sure that leaders find the training useful for their everyday activities (i.e. positive utility reactions) and that they have time to learn the training content is important to enable transfer and for leaders to use trained skills back at work.

The findings indicate the importance of understanding how leaders' perception of training content influences leadership training outcomes and that these perceptions need to be a part of the evaluation of leadership training. In addition, the findings suggest that factors predicting transfer of leadership training differ from other types of training.

The purpose of this review was to examine Indian research on help-seeking for mental health problems in adults.

Original Indian research studies on help-seeking for mental health, published from the year 2001−2019 were searched on PubMed, EBSCO, ProQuest and OVID using a set of relevant keywords. After applying exclusion criteria, 52 relevant research studies were identified.

The reviewed studies spanned a variety of themes such as barriers and facilitators to help-seeking, sources of help-seeking, causal attributions as well as other correlates of help-seeking, process of help-seeking and interventions to increase help-seeking. The majority of these studies were carried out in general community samples or treatment-seeking samples. Very few studies incorporated non-treatment seeking distressed samples. There is a severe dearth of studies on interventions to improve help-seeking. Studies indicate multiple barriers to seeking professional help and highlight that mere knowledge about illness and availability of professional services may be insufficient to minimize delays in professional help-seeking.

Help-seeking in the Indian context is often a family-based decision-making process. Multi-pronged help-seeking interventions that include components aimed at reducing barriers experienced by non-treatment seeking distressed persons and empowering informal support providers with knowledge and skills for encouraging professional help-seeking in their significant others may be useful.

This study aims to elucidate the health care organization, management and policy barriers and facilitators associated with implementation of an evidence-based health promotion intervention in primary care centers in the Basque Country, Spain.

Seven focus groups were conducted with 49 health professionals from six primary care centers participating in the Prescribing Healthy Life program. Text was analyzed using the Consolidated Framework for Implementation Research (CFIR) focusing on those constructs related to health care organization, management and policy.

The health promotion intervention was found to be compatible with the values of primary care professionals. However, professionals at all centers reported barriers to implementation related to: (1) external policy and incentives, (2) compatibility with existing workflow and (3) available resources to carry out the program. Specific barriers in these areas related to lack of financial and political support, consultation time constraints and difficulty managing competing day-to-day demands. Other barriers and facilitators were related to the constructs networks and communication, culture, relative priority and leadership engagement. A set of six specific barrier-facilitator pairs emerged.

Implementation science and, specifically, the CFIR constructs were used as a guide. Barriers and facilitators related to the implementation of a health promotion program in primary care were identified. Healthcare managers and policy makers can modify these factors to foster a more propitious implementation environment. These factors should be appropriately monitored, both in pre-implementation phases and during the implementation process, in order to ensure effective integration of health promotion into the primary care setting.

Young incarcerated male offenders are at risk of poorer sexual health, adolescent parenthood and lack opportunities for formative relationship and sexuality education (RSE) as well as positive male role models. The purpose of this paper is to report the process of co-production and feasibility testing of a novel, gender-transformative RSE programme with young male offenders to encourage positive healthy relationships, gender equality, and future positive fatherhood.

Using a rights-based participatory approach, the authors co-produced an RSE programme with young offenders and service providers at two UK prison sites using a sequential research design of: needs analysis, co-production and a feasibility pilot. Core components of the programme are grounded in evidence-based RSE, gender-transformative and behaviour change theory.

A needs analysis highlighted the men’s interest in RSE along with the appeal of film drama and peer-group-based activities. In the co-production stage, scripts were developed with the young men to generate tailored film dramas and associated activities. This co-production led to “If I Were a Dad”, an eight-week programme comprising short films and activities addressing masculinities, relationships, sexual health and future fatherhood. A feasibility pilot of the programme demonstrated acceptability and feasibility of delivery in two prison sites. The programme warrants further implementation and evaluation studies.

The contribution of this paper is the generation of an evidence-based, user-informed, gender-transformative programme designed to promote SRHR of young male offenders to foster positive sexual and reproductive health and well-being in their own lives and that of their partners and (future) children.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

The primary objective of this study is to investigate whether the inclusion of convertible bond prices as important inputs into artificial neural networks can lead to improved accuracy in predicting Chinese stock prices. This novel approach aims to uncover the latent potential inherent in convertible bond dynamics, ultimately resulting in enhanced precision when forecasting stock prices.

The authors employed two machine learning models, namely the backpropagation neural network (BPNN) model and the extreme learning machine neural networks (ELMNN) model, on empirical Chinese financial time series data.

The results showed that the convertible bond price had a strong predictive power for low-market-value stocks but not for high-market-value stocks. The BPNN algorithm performed better than the ELMNN algorithm in predicting stock prices using the convertible bond price as an input indicator for low-market-value stocks. In contrast, ELMNN showed a significant decrease in prediction accuracy when the convertible bond price was added.

This study represents the initial endeavor to integrate convertible bond data into both the BPNN model and the ELMNN model for the purpose of predicting Chinese stock prices.

The Chulalongkorn-Hasanuddin Rifampicin-Resistant Tuberculosis Screening Tool (CUHAS-ROBUST) is an artificial intelligence–based (AI–based) application for rifampicin-resistant tuberculosis (RR-TB) screening. This study aims to elaborate on the drug-resistant TB (DR-TB) problem and the impact of CUHAS-ROBUST implementation on RR-TB screening.

A qualitative approach with content analysis was performed from September 2020 to October 2020. Medical staff from the primary care center were invited online for application trials and in-depth video call interviews. Transcripts were derived as a data source. An inductive thematic data saturation technique was conducted. Descriptive data of participants, user experience and the impact on the health service were summarized

A total of 33 participants were selected from eight major islands in Indonesia. The findings show that DR-TB is a new threat, and its diagnosis faces obstacles particularly prolonged waiting time and inevitable delayed treatment. Despite overcoming the RR-TB screening problems with fast prediction, the dubious screening performance, and the reliability of data collection for input parameters were the main concerns of CUHAS-ROBUST. Nevertheless, this application increases the confidence in decision-making, promotes medical procedure compliance, active surveillance and enhancing a low-cost screening approach.

The CUHAS-ROBUST achieved its purpose as a tool for clinical decision-making in RR-TB screening. Moreover, this study demonstrates AI roles in enhancing health-care quality and boost public health efforts against tuberculosis.

This article theoretically analyzes how response to intervention (RTI) can be used as a tool in lesson study (LS) to enhance student learning and how RTI can be made more user-friendly by teachers in LS. The focus is on how RTI can be adapted to teachers' daily work by including it in the LS model and how LS can benefit by introducing a scientific approach in analyzing student learning outcomes through RTI. The article also highlights how this approach can contribute to learning for children with special educational needs (SEN).

This theoretical paper describes and compares the characteristics of the LS model with the RTI framework. The comparison highlights the design of models related to teachers’ development and learning outcomes. The benefits and challenges with the models are described. A previous research study related to the models is also briefly reviewed.

There are benefits and challenges with both the RTI and LS models but parts of the models appear to complement one another to some extent. Teachers' professional development and a better control of learning outcomes could be gained by combining the models. This could also lead to educational improvement.

There has been almost no research about a combined LS and RTI model.