Engaging Teachers and School Leaders in Participatory Data Analysis for the Development of a School-Based Mental Health Intervention

The success of school-based mental health interventions is often inconsistent, in part due to lack of input from teachers and students in the programme design. Therefore, the involvement and engagement of teachers in the co-production of an intervention, especially within data analysis, can create more innovative and effective solutions. This paper presents a teacher-led qualitative data analysis using a new approach within the field, participation theme elicitation. This approach will be used to gather information relevant to the initial development of a school-based mental health intervention. Teachers identified the following themes: (1) physical activity as a stress reliever, (2) programme facilitation, (3) exam pressure and (4) solutions to improve negative mental health. Results from the teacher-led analysis are broadly similar to previous research in the field. Our findings demonstrate that teachers can have a valuable input into research findings which should help address the development of a school-based mental health intervention. In summary, the findings suggest that the use of participatory theme elicitation is a valid and effective method to address the gaps and limitations of participatory qualitative data analysis.

A multi-method exploration into the social networks of young teenagers and their physical activity behavior

Background

There is a need for novel interventions to target inadequate levels of adolescent physical activity behavior. Previous research indicates that better understanding of the processes by which social networks influence physical activity behavior in adolescents may be useful to enhance intervention design.

Methods

This study used a multi-methods approach to aid our understanding about the role of social networks for adolescent physical activity behavior. The quantitative phase of data collection was analyzed using a three-step linear regression model using cross-sectional data from the WiSe study (n = 529 participants, 48.6% female, mean age 14.38 years (SD 0.32)). A demographically reflective sub-sample of schools were invited to take part in the qualitative phase, which involved focus group discussions. Thematic analysis was used to explore findings from the quantitative phase in greater depth, and identify other themes pertaining to the association between social networks and physical activity behavior.

Results

Males’ physical activity behavior was predicted by their friend group (0.46, p = 0.007) whereas females’ physical activity was predicted by their best friend (0.21, p = 0.03). The three main findings that were uncovered by the regression analysis were explored during the qualitative phase: 1) friends have similar physical activity behaviors; 2) friendship social networks may influence differently early adolescent male and female physical activity behavior; 3) popularity and sociability were not associated with physical activity behavior. Two additional themes emerged from the analysis of focus group data: 4) social norms and 5) external factors that may impact the relationship between adolescent physical activity behavior and social networks.

Conclusions

The investigation of the interplay between the findings from each phase of the inquiry indicated that social networks influence in different ways and to different degrees the physical activity of adolescent males and females. In turn, these insights point to the need for a systematic tailoring process for the development and implementation of physical activity behavior interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-10081-0.

Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.

An exercise intervention for people with serious mental illness: Findings from a qualitative data analysis using participatory theme elicitation

Background

People with severe mental illness (SMI) often have poorer physical health than the general population. A coproduced physical activity intervention to improve physical activity for people with SMI in Northern Ireland was evaluated by co‐researchers (researchers with lived experience of SMI) and academic researchers using a new approach to participatory data analysis called participatory theme elicitation (PTE).

Objective

Co‐researchers and academic researchers analysed the data from the pilot study using PTE. This paper aimed to compare these analyses to validate the findings of the study and explore the validity of the PTE method in the context of the evaluation of a physical activity intervention for individuals with SMI.

Results

There was alignment and congruence of some themes across groups. Important differences in the analyses across groups included the use of language, with the co‐researchers employing less academic and clinical language, and structure of themes generated, with the academic researchers including subthemes under some umbrella themes.

Conclusions

The comparison of analyses supports the validity of the PTE approach, which is a meaningful way of involving people with lived experience in research. PTE addresses the power imbalances that are often present in the analysis process and was found to be acceptable by co‐researchers and academic researchers alike.

Group based video-conferencing for adults with depression: findings from a user-led qualitative data analysis using participatory theme elicitation

BACKGROUND

Accessing support services for depression has been historically difficult given the societal stigma that exists regarding the condition. Recent advances in digital technologies continue to be postulated as a potential panacea yet the results from research trials have been mixed with a range of effect sizes.

METHODS

This article offers a different perspective by presenting a panel of end users (co-researchers) with qualitative interview data (n = 8) taken from a feasibility RCT of a group based video-conferencing service for depressed adults. The co-researcher panel were introduced to a new method of participatory data analysis known as Participatory Theme Elicitation (PTE). This method involves using network analysis techniques to create groupings and visual diagrams in order to support the generation of themes and minimise scientific researcher input/influence.

RESULTS

Co-researchers reported that while VC based interventions appeared convenient, accessible and relatively low cost - additional training and support should be offered to improve uptake and retention. In addition, co-researchers suggested that further exploration is needed regarding the level of self-awareness one feels in a group based VC environment and whether this facilitates disclosure (through disinhibition) or increases anxiety.

CONCLUSION

The findings presented here appear to support existing (researcher and academic-led) literature in the field as well as suggest new areas for investigation. By presenting data generated solely by co-researchers, this article also adds to the evidence surrounding participatory analysis methods - particularly the growing need for robust approaches that are accessible and less time-consuming than those currently available.

TRIAL REGISTRATION NUMBER

NCT03288506 (Clinicaltrials.gov) 20th Sept 2017 https://clinicaltrials.gov/ct2/show/NCT03288506.

The importance of social environment in preventing smoking: an analysis of the Dead Cool intervention

Background

An adolescent’s perceptions of their family’s and friends’ smoking attitudes and behaviour can influence their own uptake of smoking. There are two broad sources of such social influence: observing the behaviour directly, and assimilating attitudes.

Methods

We analysed data collected for the evaluation of Dead Cool, a school based smoking prevention intervention in Northern Ireland (n=480 in 20 clusters). The main analysis fits three nested logistic regression models predicting pre-intervention susceptibility to taking up smoking, as reflected in responses to three attitudinal questions. Model 1 includes only personal characteristics as explanatory factors. Model 2 adds the behaviour of friends and family that would provide an opportunity for social influence through observational learning. Model 3 adds the susceptibility of friends.

Results

Each additional group of variables improved the model fit (with reduced AIC and BIC). However, in the final model, only three variables were found to be statistically significant (p<0.05) in predicting susceptibility to smoking initiation: rebelliousness (OR [1.1,1.3]) from the personal characteristics group; and, in the observational learning group, being friends with a smoker (OR [1.0,2.9]) and frequency of being in the same room or car with someone smoking (OR [2.0,9.0] for most frequent). Adding the two measures of diffusion of susceptibility through the friendship network improved the model fit, but neither was found to be statistically significant.

Conclusions

The analysis provides additional evidence to support policies that could reduce children’s exposure to smoking behaviour, and potential subsequent smoking initiation. No conclusions could be drawn about the diffusion of smoking attitudes through the school friendship networks of children.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7485-7) contains supplementary material, which is available to authorized users.

Developing agent-based models of complex health behaviour

Managing non-communicable diseases requires policy makers to adopt a whole systems perspective that adequately represents the complex causal architecture of human behaviour. Agent-based modelling is a computational method to understand the behaviour of complex systems by simulating the actions of entities within the system, including the way these individuals influence and are influenced by their physical and social environment. The potential benefits of this method have led to several calls for greater use in public health research. We discuss three challenges facing potential modellers: model specification, obtaining required data, and developing good practices. We also present steps to assist researchers to meet these challenges and implement their agent-based model.

Network methods to support user involvement in qualitative data analyses: an introduction to Participatory Theme Elicitation

BACKGROUND

While Patient and Public Involvement (PPI) is encouraged throughout the research process, engagement is typically limited to intervention design and post-analysis stages. There are few approaches to participatory data analyses within complex health interventions.

METHODS

Using qualitative data from a feasibility randomised controlled trial (RCT), this proof-of-concept study tests the value of a new approach to participatory data analysis called Participatory Theme Elicitation (PTE). Forty excerpts were given to eight members of a youth advisory PPI panel to sort into piles based on their perception of related thematic content. Using algorithms to detect communities in networks, excerpts were then assigned to a thematic cluster that combined the panel members' perspectives. Network analysis techniques were also used to identify key excerpts in each grouping that were then further explored qualitatively.

RESULTS

While PTE analysis was, for the most part, consistent with the researcher-led analysis, young people also identified new emerging thematic content.

CONCLUSIONS

PTE appears promising for encouraging user led identification of themes arising from qualitative data collected during complex interventions. Further work is required to validate and extend this method.

TRIAL REGISTRATION

ClinicalTrials.gov, ID: NCT02455986 . Retrospectively Registered on 21 May 2015.

Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

Relationship of household food insecurity to anaemia in children aged 6-59 months among families in rural Indonesia

BACKGROUND

Anaemia is a significant global public health problem in developing countries with adverse health effects on young children. Household food insecurity, which reflects a household's access, availability and utilisation of food, has not been well characterised in relation to anaemia in children.

OBJECTIVE

To examine the relationship of household food insecurity with anaemia (Hb <11 g/dl) in children.

METHODS

In a cross-sectional study of 4940 rural households participating in the Indonesian Nutrition Surveillance System, household food insecurity was measured using a modified 9-item food security questionnaire and related to anaemia in children aged 6-59 months.

RESULTS

The proportion of households with an anaemic child was 56·6%. In households with and without anaemic children, the mean (SD) food insecurity score was 1·82 (1·72) vs 1·55 (1·54) (p<0·0001), respectively. In a multivariate logistic regression model, food insecurity score was related to anaemia in children (odds ratio 0·77, 95% confidence interval 0·63-0·95, p=0·01) when the highest quintile of food insecurity score was compared with the lowest quintile, adjusting for potential confounders.

CONCLUSION

A higher household food insecurity score is associated with greater prevalence of anaemia in children in rural families in Indonesia.

The impact of network clustering and assortativity on epidemic behaviour

Epidemic models have successfully included many aspects of the complex contact structure apparent in real-world populations. However, it is difficult to accommodate variations in the number of contacts, clustering coefficient and assortativity. Investigations of the relationship between these properties and epidemic behaviour have led to inconsistent conclusions and have not accounted for their interrelationship. In this study, simulation is used to estimate the impact of social network structure on the probability of an SIR (susceptible-infective-removed) epidemic occurring and, if it does, the final size. Increases in assortativity and clustering coefficient are associated with smaller epidemics and the impact is cumulative. Derived values of the basic reproduction ratio (R(0)) over networks with the highest property values are more than 20% lower than those derived from simulations with zero values of these network properties.

Parameterization of Keeling's network generation algorithm

Simulation is increasingly being used to examine epidemic behaviour and assess potential management options. The utility of the simulations rely on the ability to replicate those aspects of the social structure that are relevant to epidemic transmission. One approach is to generate networks with desired social properties. Recent research by Keeling and his colleagues has generated simulated networks with a range of properties, and examined the impact of these properties on epidemic processes occurring over the network. However, published work has included only limited analysis of the algorithm itself and the way in which the network properties are related to the algorithm parameters. This paper identifies some relationships between the algorithm parameters and selected network properties (mean degree, degree variation, clustering coefficient and assortativity). Our approach enables users of the algorithm to efficiently generate a network with given properties, thereby allowing realistic social networks to be used as the basis of epidemic simulations. Alternatively, the algorithm could be used to generate social networks with a range of property values, enabling analysis of the impact of these properties on epidemic behaviour.

Length of stay comparisons for private and public hospitals

This analysis uses average length of stay as a proxy for efficiency, to compare the Australian private and public hospital sectors. We conclude that private hospitals are more efficient than public hospitals in providing the range of care provided by private hospitals. However, public hospitals are more efficient in handling the casemix of the public hospital sector. The picture is more complicated when particular types of care (such as obstetric and psychiatric) are excluded.

Future financial impact of the current health financing system

Major political parties remain publicly committed to Medicare and community-rated voluntary health insurance. It is important to understand the future financial consequences of this policy in order to assist community debate about whether such a commitment is appropriate or some other policy should be developed. This paper describes development of, and results from, the APHA health financing model. It suggests that health expenditure would represent 12.9% of gross domestic product by 2021, compared to 8.5% in 1995. Increasing per capita expenditure is the major contributor to the growth, with demographic changes responsible for only 14.3%.

Preoperative skin traction for fractures of the proximal femur. A randomised prospective trial

We report the results of a randomised trial to determine the effects of skin traction on 252 patients awaiting surgery for fractures of the proximal femur. They were allocated randomly to be nursed free in bed or to receive Hamilton-Russell skin traction. No differences were found between the groups in terms of pain suffered, analgesia required, frequency of pressure sores or ease of operation. The application of skin traction to patients with fractures of the upper femur is time-consuming and we recommend therefore that its routine use should be discontinued.