Search results

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 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.

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.

This article presents a secondary analysis of previously published data in order to drive discussion of the library profession’s current state of preparedness in working with patrons with disabilities.

This article used a secondary analysis of survey data that have been previously published to determine what the continuum of data said about the current state of preparedness in the profession when working with people with disabilities.

A comparison of the data from both surveys reveals that there are not only gaps in library graduate school education related to disability and accessibility but also that those gaps are not being addressed through professional development and staff training after students enter the workforce.

This was a secondary analysis of data, so no new data could be added. There was also no representation from library graduate school administration.

An awareness is built that there needs to be more instruction for library graduate students and library employees on topics related to disability, accessibility and assistive technologies.

The topic has never been studied before in this kind of continuum of data, and the use of the secondary analysis of data with the library and information science profession is exceedingly rare.

The purpose of this paper is to identify the dividend policy determinants of Sri Lankan firms and why they pay dividends.

The study uses several quantitative approaches to investigate dividend determinants using market (secondary) data of 190 Sri Lankan firms and 1,330 firm-year observations. Dividend determinants are also identified using survey (primary) data from 141 of the 190 firms. Triangulation is then used to facilitate validation of the data through cross-verification from two data sources.

Analysis of the market data reveals that firm size, industry impact, corporate governance, free cash flow, earnings, past dividends, profitability, investment opportunities, net working capital, concentrated ownership structure and investor preference represent the most important dividend determinants. Survey data confirm these findings. The evidence supports the pecking order, signaling, free cash flow, catering and outcome theories using both secondary and primary data and the bird-in-the-hand theory using survey data.

The findings are useful not only for corporate decision makers in establishing an appropriate dividend policy but also for shareholders in making investment decisions. Because the current study is limited to Sri Lanka, future researchers should study the same phenomenon in other countries using the triangulation approach.

This study provides a hybrid approach to dividend policy research by using both primary and secondary data in a single study. It is the first dividend study in Sri Lanka to use a triangulation approach.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

This study aims to explore the impact of school leadership, particularly that of the principal (head teacher), on school improvement in England.

The study adopts a mixed‐methods (MM), longitudinal design to investigate the leadership of a sample of academically effective and improving schools identified from analyses of national assessment and examination data sets. In addition, questionnaire surveys of principals and key staff and 20 qualitative school case studies were conducted. The paper reports results from the questionnaire analyses and changes in measures of school performance over three school years using data from 378 primary and 362 secondary schools. Confirmatory factor analysis and structural equation models (SEM) test direct and indirect effects of school leadership and school and classroom processes in predicting changes in schools' academic results.

The analyses identified robust underlying dimensions of leadership and school and classroom processes and highlighted strategies and actions that school principals and staff had adopted to raise pupil attainment. The SEM models reveal both direct and indirect effects of leadership on a range of school and classroom processes that in turn predicted changes (improvements) in schools' academic performance.

This original empirical study presents new results on the leadership of a large sample of effective and improving primary and secondary schools in England. A dynamic model is presented predicting changes in schools' academic performance over three years and identifying direct effects of leadership on school and classroom processes and indirect effects on improvements in schools' academic results.