Indirect observation is a recent concept in systematic observation. It largely involves analyzing textual material generated either indirectly from transcriptions of audio recordings of verbal behavior in natural settings (e.g., conversation, group discussions) or directly from narratives (e.g., letters of complaint, tweets, forum posts). It may also feature seemingly unobtrusive objects that can provide relevant insights into daily routines. All these materials constitute an extremely rich source of information for studying everyday life, and they are continuously growing with the burgeoning of new technologies for data recording, dissemination, and storage. Narratives are an excellent vehicle for studying everyday life, and quantitization is proposed as a means of integrating qualitative and quantitative elements. However, this analysis requires a structured system that enables researchers to analyze varying forms and sources of information objectively. In this paper, we present a methodological framework detailing the steps and decisions required to quantitatively analyze a set of data that was originally qualitative. We provide guidelines on study dimensions, text segmentation criteria, ad hoc observation instruments, data quality controls, and coding and preparation of text for quantitative analysis. The quality control stage is essential to ensure that the code matrices generated from the qualitative data are reliable. We provide examples of how an indirect observation study can produce data for quantitative analysis and also describe the different software tools available for the various stages of the process. The proposed method is framed within a specific mixed methods approach that involves collecting qualitative data and subsequently transforming these into matrices of codes (not frequencies) for quantitative analysis to detect underlying structures and behavioral patterns. The data collection and quality control procedures fully meet the requirement of flexibility and provide new perspectives on data integration in the study of biopsychosocial aspects in everyday contexts.

Observational methodology is one of the most suitable research designs for evaluating fidelity of implementation, especially in complex interventions. However, the conduct and reporting of observational studies is hampered by the absence of specific guidelines, such as those that exist for other evaluation designs. This lack of specific guidance poses a threat to the quality and transparency of these studies and also constitutes a considerable publication hurdle. The aim of this study thus was to draw up a set of proposed guidelines for reporting evaluations based on observational methodology. The guidelines were developed by triangulating three sources of information: observational studies performed in different fields by experts in observational methodology, reporting guidelines for general studies and studies with similar designs to observational studies, and proposals from experts in observational methodology at scientific meetings. We produced a list of guidelines grouped into three domains: intervention and expected outcomes, methods, and results. The result is a useful, carefully crafted set of simple guidelines for conducting and reporting observational studies in the field of program evaluation.

To contribute new evidence to the controversy about the factor structure of the Eating Disorder Examination Questionnaire (EDE-Q) and to provide, for the first time, norms based on a large adolescent Mexican community sample, regarding sex and area of residence (urban/rural). A total of 2928 schoolchildren (1544 females and 1384 males) aged 11-18 were assessed with the EDE-Q and other disordered eating questionnaire measures. Confirmatory factor analysis of the attitudinal items of the EDE-Q did not support the four theorized subscales, and a two-factor solution, Restraint and Eating-Shape-Weight concern, showed better fit than the other models examined (RMSEA = .054); measurement invariance for this two-factor model across sex and area of residence was found. Satisfactory internal consistency (ω ≥ .80) and two-week test-retest reliability (ICCa ≥ .84; κ ≥ .56), and evidence for convergent validity with external measures was obtained. The highest attitudinal EDE-Q scores were found for urban females and the lowest scores were found for rural males, whereas the occurrence of key eating disorder behavioural features and compensatory behaviours was similar in both areas of residence. This study reveals satisfactory psychometric properties and provides population norms of the EDE-Q, which may help clinicians and researchers to interpret the EDE-Q scores of adolescents from urban and rural areas in Mexico.

Although research has documented the importance of emotion in risk perception, little is known about it in the context of everyday life. Using the Experience Sampling Method (ESM), 94 part‐time students were prompted at random—via cellular telephones—to report on mood state and three emotions and to assess risk on thirty occasions during their working hours. The emotions—valence, arousal, and dominance—were measured using self‐assessment manikins (SAMs) (Bradley & Lang, 1994). Hierarchical linear models (HLM) revealed that mood state and emotions explained significant variance in risk perception. In addition, valence and arousal accounted for variance over and above “reason” (measured by severity and possibility of risks). Six risks were re‐assessed in a post‐experimental session and found to be lower than their real‐time counterparts. The study demonstrates the feasibility and value of collecting representative samples of data with simple technology. Evidence is also provided to demonstrate the statistical consistency of the HLM estimates. Copyright © 2010 John Wiley & Sons, Ltd.

Contextual factors are crucial for evaluative research in psychology, as they provide insights into what works, for whom, in what circumstances, in what respects, and why. Studying behavior in context, however, poses numerous methodological challenges. Although a comprehensive framework for classifying methods seeking to quantify biopsychosocial aspects in everyday contexts was recently proposed, this framework does not contemplate contributions from observational methodology. The aim of this paper is to justify and propose a more general framework that includes observational methodology approaches. Our analysis is rooted in two general concepts: ecological validity and methodological complementarity. We performed a narrative review of the literature on research methods and techniques for studying daily life and describe their shared properties and requirements (collection of data in real time, on repeated occasions, and in natural settings) and classification criteria (eg, variables of interest and level of participant involvement in the data collection process). We provide several examples that illustrate why, despite their higher costs, studies of behavior and experience in everyday contexts offer insights that complement findings provided by other methodological approaches. We urge that observational methodology be included in classifications of research methods and techniques for studying everyday behavior and advocate a renewed commitment to prioritizing ecological validity in behavioral research seeking to quantify biopsychosocial aspects.