Does computer interaction negatively affect teenagers socially? What effect does Facebook have on the academic achievement of the school goers?
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Abstract Technology-based interventions to promote health are expanding rapidly. Assessing the preliminary efficacy of these interventions can be achieved by employing single-case experiments sometimes referred to as n-of-1 studies. Although single-case experiments are often misunderstood, they offer excellent solutions to address the challenges associated with testing new technology-based interventions.
This paper provides an introduction to single-case techniques and highlights advances in developing and evaluating single-case experiments, which help ensure that treatment outcomes are reliable, replicable, and generalizable.
These advances include quality control standards, heuristics to guide visual analysis of time-series data, effect size calculations, and statistical analyses. They also include experimental designs to isolate the active elements in a treatment package and to assess the mechanisms of behavior change.
The paper concludes with a discussion of issues related to the generality of findings derived from single-case research and how generality can be established through replication and through analysis of behavioral mechanisms.
Research design, technology, mHealth, single-case design, preliminary efficacy Introduction Case study design of experiments field of technology-based behavioral health interventions is expanding rapidly.
New technologies are enabling access to, and assessment of, individuals and their health-related behavior [ 1 - 3 ]. The fields of eHealth, mHealth, and the promise of emerging technologies have the potential to transform many systems of health care and improve public health by increasing access to cost-effective interventions.
With these opportunities comes the need to evaluate rigorously the potential efficacy of new treatments. In this paper, we describe some challenges and methodological solutions associated with testing preliminary efficacy.
In particular, we focus on the solutions offered by single-case experiments, which fill a unique and vital niche in the ecology of research designs.
We also highlight advances in developing and evaluating single-case experiments, which help ensure that treatment outcomes are reliable, replicable, and generalizable.
Finally, we describe experimental designs that allow researchers to isolate the active elements in a treatment package and to assess the mechanisms of behavior change.
Our goal is to introduce a range of techniques that will be relevant to behavioral scientists that are unfamiliar with single-case research and that are particularly well suited for the research and development of new technology-based interventions. We hope to supply enough detail to achieve a basic understanding of the mechanics, utility, and versatility of single-case research and enough resources to propel further inquiry.
Broadly, single-case designs include a family of methods in which each participant serves as his or her own control. In a typical study, some behavior or self-reported symptom is measured repeatedly during all conditions for all participants.
The experimenter systematically introduces and withdraws control and intervention conditions and then assesses effects of the intervention on behavior across replications of these conditions within and across participants.
Thus, the telltale traits of these studies include repeated and frequent assessment of behavior, experimental manipulation of the independent variable, and replication of effects within and across participants. Although some forms of replication are readily apparent, such as replications of effects within and between subjects, other forms may be more subtle.
For example, replication within subjects also occurs by simply measuring behavior repeatedly within a condition. Assuming some degree of stability of the dependent variable within a condition, there will be many replications of the effects of a treatment on behavior.
A recent study illustrates the efficiency and rigor of a single-case design to assess a novel technology-based treatment [ 8 ]. Raiff and Dallery assessed whether an Internet-based incentive program could increase adherence to blood glucose testing for 4 teenagers diagnosed with Type 1 diabetes.
Teens monitored glucose levels with a glucose meter during a 5-day baseline control condition. During a 5-day treatment condition, participants earned vouchers statements of earnings exchangeable for goods and services for adhering to blood glucose testing recommendations ie, 4 tests per day.
After the treatment condition, participants monitored blood glucose just as they did during the first baseline condition for 5 days, without the possibility of earning incentives.
Participants submitted a mean of 1. Because adherence increased only when the treatment was implemented for all 4 participants and because behavior within each condition was stable ie, five replications of treatment effects per participant and ten replications of control levels per participantthis experiment suggested that an Internet-based incentive program can reliably increase adherence to self-monitoring of blood glucose.
Single-case designs can capitalize on the ability of technology to easily, unobtrusively, and repeatedly assess health-related behavior [ 79 ].
|Comprehensive guide on conducting Design of Experiments (case study)||Added to Your Shopping Cart Add to cart Description "This is an engaging and informative book on the modern practice of experimental design.|
|Introduction||Events Study Designs This short article gives a brief guide to the different study types and a comparison of the advantages and disadvantages. A defined population P from which groups of subjects are studied Outcomes O that are measured And for experimental and analytic observational studies:|
|Design and Analysis of Experiments||A detailed analysis of a person or group, especially as a model of medical, psychiatric, psychological, or social phenomena.|
For example, researchers have used technology-based measures of activity in the form of daily step counts [ 10 ], twice-daily measurements of exhaled carbon monoxide as an indicator of smoking status [ 11 ], and medication adherence on a daily basis [ 12 ]. Such repeated assessment, whether through existing or new technology, provides excellent opportunities to analyze the effects of treatment variables using single-case experiments.
In addition, many technology-delivered behavioral health interventions permit automated treatment delivery [ 15 ]. This means that treatment can be delivered with high fidelity, which can minimize between-subject variability in treatment dose and quality.
Because detecting treatment effects in single-case designs requires replications across subjects, ensuring equivalent treatment fidelity and quality across participants enhances the internal validity of the study.
There are two additional advantages of single-case research, and these advantages exist whether patient improvement is measured with technology-based or alternative methods.
Single-case research requires a fine-grained view of health-related behavior over time, and technology-based data capture can enable this view.
Patient improvement can be revealed by changes in health-related behavior from baseline to treatment, and the cause of these changes can be verified via replications within and across participants.The purpose that study is to collect information about DoE in healthcare and try to apply the philosophy of DoE in that field.
For that aim three theoretical case studies are explained. case-control study (‘retrospective study’ based on recall of the exposure) Advantages and Disadvantages of the Designs.
Randomised Controlled Trial.
An experimental comparison study in which participants are allocated to treatment/intervention or control/placebo groups using a .
Gasoline Case Study Design of Experiment Open Script This example shows how to design an experiment for the gasoline case study problem using the command-line interface to Model-Based Calibration Toolbox™. The case study is a separate research method that has its own research design.
A research design is a logical plan for getting from here to there, where here may be defined as the initial set of questions to be answered and there is some set of conclusions (answers) about these questions. The case study research design have evolved over the past few years as a useful tool for investigating trends and specific situations in many scientific disciplines.
Research Methods & Experimental Design Human Supervisory Control The Experimental Design Process Research Question (Hypothesis) Design Experiment Collect Data Analyze Data Draw Conclusions. Example Experiment Are web-based case studies better than print versions.