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A search was performed to identify literature on implementation fidelity, i.e ., empirical research, reviews, or theoretical pieces. The following databases were searched with the terms "implementation fidelity" or "fidelity" within five words of "implement", "implementation", "implemented", etc.: Applied Social Sciences Index and Abstracts, Cumulative Index of Nursing and Allied Health Literature (CINAHL), International Bibliography of the Social Sciences, MEDLINE, and the Social Science Citation Index. The relevant studies identified by this search were also then scanned for additional literature. Conference abstracts and presentations provided another source of literature in this field. This multi-method search identified a number of reviews discussing the conceptualisation of implementation fidelity, and a body of empirical research measuring the fidelity with which various interventions had been implemented. This article focuses principally on research published from 2002 to 2007, because of the presence of major reviews of the implementation fidelity literature from 2003 and before [ Cafè Noir LDE925010380 016 Grigio 41 MICROPHIBE Tape bNiOS4bz
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, 5 ]. The arguments, limitations, and findings of all of this literature contributed to the development of the novel framework presented here and provided examples of how to evaluate individual elements of the framework.

The concept of implementation fidelity is currently described and defined in the literature in terms of five elements that need to be measured [ 1 , 2 , Bogner Women’s Oslo 18f Platform Sandals Beige Beige reWz9mnl
]. These are: adherence to an intervention; exposure or dose; quality of delivery; participant responsiveness; and programme differentiation. There are certain overlaps here with the concept of process evaluation [ 15 ]. Within this conceptualisation of implementation fidelity, adherence is defined as whether "a program service or intervention is being delivered as it was designed or written" [ 4 ]. Dosage or exposure refers to the amount of an intervention received by participants; in other words, whether the frequency and duration of the intervention is as full as prescribed by its designers [ 1 , 4 ]. For example, it may be that not all elements of the intervention are delivered, or are delivered less often than required. Coverage may also be included under this element, i.e ., whether all the people who should be participating in or receiving the benefits of an intervention actually do so.

Quality of delivery is defined as "the manner in which a teacher, volunteer, or staff member delivers a program" [ 4 ]. However, it is perhaps a more ambiguous element than this suggests. An evaluation of this may require using a benchmark, either within or beyond that stipulated by an intervention's designers; this element of fidelity could involve either delivering the intervention using "techniques . . . prescribed by the program" [ 4 ], or applying a benchmark from outside the programme, i.e ., "the extent to which a provider approaches a theoretical ideal in terms of delivering program content" [ 1 ]. If such a clear benchmark exists then quality of delivery may be treated, along with adherence and dosage, as one of three discrete aspects required to assess the fidelity of an intervention. However, it may potentially also be viewed as a moderator of the relationship between an intervention and the fidelity with which it is implemented. This is a role that is simply not explored in the literature to date. For example, an intervention could be delivered but delivered badly; in turn, the degree of fidelity achieved by the implemented intervention could be adversely affected.

Changing the Hierarchy Axis

Changing Measures Measures are predetermined values in Power BI. Only pre-selected measures within a visual are seen at the report level when a report is shared. The solution tricks Power BI so that if you select a text value for a measure (such as total sales), you can switch it to the actual total sales measure in that dataset. Or, if you’re looking at month-to-month sales but want to look at product growth month-over-month, you can switch the measure dynamically from sales to order quantity. The solution presents a slicer of all the measures you might want to be able to dynamically switch and solves the problem of how to change the measure on the fly.

Changing Measures

Changing Visualizations Power BI has numerous ways to present data visually in a report, but it’s rare that a particular visualization type in a shared report will solve for all user needs in an organization. To prevent users from having to manipulate the dataset to suit their own needs, this solution presents a slicer for users to select from a set of visualizations. For example, one click changes the view from a Bar Chart to an Area Chart. This solution was created in much the same way as the measures solution.

Changing Visualizations

The Solutions in Action These solutions provide considerable impact and compelling new uses for Power BI in the enterprise. They save time and frustration at the end-user level from not needing to manually edit every shared report they receive. Also, they can potentially reduce the level of training required for Power BI users as they do not necessarily need to know how to edit a report they receive. These solutions also enable more productivity for users who don’t have edit rights at all as they can change the report on the fly without having to go into powerbi.com to edit the report.

The Solutions in Action

As a Power BI report creator, if you share a report with 200 people in your organization, you certainly don’t want 200 people to alter the original report. With these solutions, all 200 users can change how data is displayed in the report to meet their own needs, enabling a multitude of new routes to data viewing and interpretation within an organization, without having to devote the time and resources to create 200 different reports.

Here’s a look at all of the solutions together in action:

These solutions are available from AIM Consulting and can be tailored to clients’ specific needs to increase the productivity level of Power BI end-users and of your entire organization. They provide compelling new avenues for end-users to view and manage enterprise data in Power BI.

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JJ has over 7 years of experience in Data Analytics and Business Intelligence with experience in data modeling, data visualization, and web analytics. He is passionate about analyzing large volumes of data to identify criticalgapsand evaluating trends and current conditions.

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