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The purpose of this paper is to show the importance of secondary analysis to social sciences and to futures studies, both for research and teaching purposes.

An illustration of the main characteristics of secondary analysis, presenting it as a theory-driven activity where the definition of the research design plays a fundamental role.

This paper extends the secondary analysis approach to the study of the future. The utility of secondary analysis for futures studies is illustrated by means of the presentation of two examples developed in the field of the sociology of religion.

The results are useful for those who want to develop sound and robust approaches to the study of social change, taking into consideration the simulation of possible future scenarios.

The purpose of this paper is to explore why autistic people and their caregivers choose interventions other than applied behavior analysis (ABA), and how their decision impacts them over their lifespan. The focus group was divided into those who pursued augmentative and alternative communication (AAC)-based supports, received ABA, selected other interventions or received no intervention at all. The reported posttraumatic stress symptoms (PTSS) of ABA recipients were compared to non-ABA recipients in order to evaluate the long-term impacts of all intervention types. Using a mixed-method thematic analysis, optional comments submitted alongside a quantitative online survey were reviewed for emergent themes. These comments augmented the survey Likert scores with a qualitative impression of the diverse intervention-related attitudes among participants. Investigating the lived experiences of autism intervention recipients illuminated the scope of the long-term impacts of each intervention that was chosen. Overall, autistics who received no intervention fared best, based on the lowest reported PTSS. These findings may inform the potential redesign of autism interventions based on the firsthand reported experiences and opinions of autistics.

The aim of this study was to conduct research that is both question-driven and data-driven to aid in the analysis of existing data (Van Helden, 2013). In the research question-driven approach, the independent variables were the intervention type and duration of exposure relative to lifespan; the dependent variables were the PTSS severity score and binary indicator of meeting PTSS criteria. The analyses that were conducted included linear regression analyses of severity score on intervention type and duration, and χ² tests for independence of the probabilities of PTSS criterion satisfaction and intervention type. This experiment was designed to test the data-driven hypothesis that the prevalence and severity of PTSS are dependent on the type of autism intervention and duration of exposure. After reviewing the primary data set, the data-driven inquiry determined that the sample for secondary analysis should be categorized by communication-based vs non-communication-based intervention type in order to best complement the limitations and strengths of the published findings from the primary analysis.

Autistics who received no intervention had a 59 percent lower likelihood of meeting the PTSS criteria when compared to their ABA peers, and they remained 99.6 percent stable in their reported symptoms throughout their lifespan (R²=0.004). ABA recipients were 1.74 times more likely to meet the PTSS criteria when compared to their AAC peers. Within the 23 percent who selected an intervention other than ABA, consisting of psychotherapy, mental health, son-rise and other varying interventions, 63 percent were asymptomatic. This suggests that the combined benefits of communication-based interventions over behaviorism-influenced ABA practices may contribute to enhanced quality of life. Although not generalizable beyond the scope of this study, it is indicated from the data that autistics who received no intervention at all fared best over their lifetimes.

The obvious advantage of a secondary analysis is to uncover key findings that may have been overlooked in the preliminary study. Omitted variables in the preliminary data leave the researcher naive to crucially significant findings, which may be mitigated by subsequent testing in follow-up studies (Cheng and Phillips, 2014, p. 374). Frequency tables and cross-tabulations of all variables included in the primary analysis were reproduced. The secondary analysis of existing data was conducted from the design variables used in the original study and applied in the secondary analyses to generate less biased estimates (Lohr, 2010; Graubard and Korn, 1996). Inclusion criteria for each intervention group, PTSS scores and exposure duration, were inherited from the primary analysis, to allow for strategic judgment about the coding of the core variables pertaining to AAC and PTSS. The data sample from 460 respondents was reduced to a non-ABA group of n=330. An external statistician scored each respondent, and interrater reliability was assessed using Cohen’s κ coefficient (κ=1).

Including the autistic voice in the long-term planning of childhood interventions is essential to those attempting to meet the needs of the individuals, their families and communities. Both parents and autistic participant quotes were obtained directly from the optional comments to reveal why parents quit or persisted with an autism intervention.

Practitioners and intervention service providers must consider this feedback from those who are directly impacted by the intervention style, frequency or intensity. The need for such work is confirmed in the recent literature as well, such as community-based participatory research (Raymaker, 2016). Autistics should be recognized as experts in their own experience (Milton, 2014). Community–academic partnerships are necessary to investigate the needs of the autistic population (Meza et al., 2016).

Most autistic people do not consider autism to be a mental illness nor a behavior disorder. It is imperative to recognize that when injurious behavior persists, and disturbance in mood, cognition, sleep pattern and focus are exacerbated, the symptoms are unrelated to autism and closely align to the diagnostic criteria for posttraumatic stress disorder (PTSD). When PTSD is underdiagnosed and untreated, the autistic individual may experience hyperarousal and become triggered by otherwise agreeable stimuli. Since autism interventions are typically structured around high contact, prolonged hours and 1:1 engagement, the nature of the intervention must be re-evaluated as a potentially traumatic event for an autistic person in the hyperarousal state. Any interventions which trigger more than it helps should be avoided and discontinued when PTSS emerge.

Dual diagnosis is a term that describes the co-occurrence of mental health disorders or illness and substance use or abuse disorders. Because this co-occurrence results in multiple diseases, layers of treatment are often needed to successfully create positive change in the individual. The purpose of this study is to explore factors of treatment that could facilitate improvements in functionality and quality of life for those with a dual diagnosis.

A secondary data analysis, using both quantitative and qualitative data, was completed. Secondary analysis is an empirical exercise that applies the same basic research principles as studies using primary data and has steps to be followed, including the evaluative and procedural steps commonly associated with secondary data analysis. Documentation data from the intensive mobile psychosocial assertive community treatment program was gathered for this analysis; this program was used because of the intensive and community-based services provided to patients with a dual diagnosis.

The major findings from this secondary analysis suggested that significant barriers included “denial” (e.g. evasion, suspension or avoidance of internal awareness) of diagnoses, complicated treatment and other barriers related to housing. Ultimately, these findings provided greater insight into potential effective treatment interventions for people living with a dual diagnosis.

This study adds to the growing body of literature showing that patient-centered care allows for more effective treatment and ultimately, improved health outcomes.

Access to unbiased self-reported (primary) data for a normative concept like social sustainability has been a challenge for construction project management (CPM) scholars, and this difficulty has been further amplified by the ongoing COVID-19 pandemic. This paper aims to address this issue by asserting the suitability of secondary data as a methodologically sound but underutilized alternative and providing directions for secondary data-based research on social sustainability in a project setting.

By drawing on a framework for social sustainability and using “project-as-practice” approach as its point of departure, this conceptual paper identifies possibilities for utilizing multiple secondary sources in CPM research.

The paper provides a roadmap for identification of secondary sources, access to data, potential research designs and methods, limitations of and cautions in using secondary sources, and points to many novel lines of empirical enquiries to stimulate secondary data-based research on social sustainability in CPM.

Indicated secondary sources and empirical opportunities can support research efforts that aim to promote societal welfare through construction projects.

The presented guidance will assist researchers in identifying, accessing and utilizing naturalistic, secondary data for designing and conducting empirical research that cuts across social sustainability and CPM. This, in turn, will facilitate methodological pluralism and “practice turn” in such research endeavors.

This chapter describes methodologies used in the project ‘Out-of-school activities and the education gap’. The project explored how the out-of-school environment affects children, whether it impacts on primary school attainment and whether it reinforces existing socioeconomic differences. A mixed-methods approach combined three areas of research: statistical analysis of the Millennium Cohort Study (MCS) linked to the National Pupil Database (NPD); a qualitative study through interviews with key stakeholders in 10 schools in London and the North East and the articulation of theories of change for how out-of-school activities may affect attainment. Patterns in how children spend their time, and whether and how this affects attainment, were investigated by analysis of the MCS linked to the NPD. Qualitative research with parents, teachers, pupils and activity providers from schools in London and the North-East afforded an in-depth understanding of drivers and barriers influencing how children spend their time and pathways by which activities may affect children's learning and development. The qualitative research also provided a narrative intersectional analysis of responses in terms of class, gender, ethnicity, religion and disability. Mixing quantitative and qualitative research was made difficult by the volume of data and the time needed to analyse and report each area separately, the different nature of data in the three areas of research and the timing of each phase of data collection. However, meaningful combining of methods occurred at the level of research questions and contributed to a more critical analysis of children's out-of-school activities than had been possible before.

This study aims to help resolve some of the inconsistencies of the relationships between franchisor growth and its drivers in prior literature.

First, this study provides a meta-analysis with bivariate correlation analysis and moderation analysis. It then offers an additional analysis of secondary data to shed further light on the relationship between franchisor growth and its drivers.

This study confirms the diverse nature of the relationship between the various measures of growth and drivers. It finds that proportion of outlets franchised and brand reputation have the strongest relationships with geographic dispersion; age and proportion of outlets franchised have the strongest relationships with outlet growth rate; and size has the strongest relationship with the number of new outlets. In addition, these multiple relationships are moderated by all three research characteristics that this study investigates, including data source, time frame and industry context.

This meta-analysis merely offers an examination of the most commonly studied drivers and not a complete review of all potentially important variables. It calls for further research that examines the factors that lead to franchisor growth and performance in general.

Managers of young franchisors do not need to rush to expand their business across a wide range of geographic regions. Young franchisors instead should focus initially on gaining maturity, developing their business concept, building an attractive track record and improving their brand reputation. Beyond a strong brand and well-developed business concept, franchisors can attract potential franchisees by reassuring them and making them feel secure about their investment.

This study includes a bivariate analysis that was used to conduct a meta-analysis and also an empirical analysis of secondary data. By conducting the secondary data analysis, we were able to examine the extent to which the meta-analysis results of this study could be extended beyond the time period for papers included in the meta-analysis.

In this chapter, I explore traditional notions of secondary data in qualitative research and consider the ways in which these are continually being reimagined in the digital age. I situate this discussion in respect to data typologies and, more reflexively, in relation to our need as researchers to make data real. I consider contemporary understandings of reuse in relation to secondary data, focusing particularly on qualitative interview data. Recognizing those who are already forging a path, I then suggest how we might move beyond notions of reuse and reimagine secondary data in the digital age. To illustrate these points, I highlight relevant studies drawing data from a range of online spaces, and finally summarize key considerations and challenges.

Dynamic planning and scheduling forms a widely adopted smart strategy for solving real-world problems in diverse business systems. This paper uses deductive content analysis to explore secondary data from previous studies in dynamic planning and scheduling to draw conclusions on its current status, forward action and research needs in construction management.

The authors searched academic databases using planning and scheduling keywords without a periodic setting. This research collected secondary data from the database to draw an objective comparison of categories and conclusions about how the data relates to planning and scheduling to avoid the subjective responses from questionnaires and interviews. Then, applying inclusion and exclusion criteria, we selected one hundred and four articles. Finally, the study used a seven-step deductive content analysis to develop the categorisation matrix and sub-themes for describing the dynamic planning and scheduling categories. The authors used deductive analysis because of the secondary data and categories comparison. Using the event types represented in a quadrant mapping, authors delve into where, when, application and benefits of the classes.

The content analysis showed that all the accounts and descriptions of dynamic planning and scheduling are identifiable in an extensive research database. The content analysis reveals the need for multi-hybrid (4D BIM-Agent based-discrete event-discrete rate-system dynamics) simulation modelling and optimisation method for proffering solutions to scheduling and planning problems, its current status, tools and obstacles.

This research reveals the deductive content analysis talent in construction research. It also draws direction, focuses and raises a question on dynamic planning and scheduling research concerning the five-integrated model, an opportunity for their integration, models combined attributes and insight into its solution viability in construction.