Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.

Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.

Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.

Discussion 1: Methods of Measuring




The center point of research studies is the body of data collected to answer the research question. These data must be measured, which is the act of taking an abstract concept (e.g., depression, anger, etc.), sorting them out and quantifying them in some cohesive way in order to construct meaning—but how can you measure something that is not easily quantifiable? Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.

Choosing an appropriate measurement tool requires consideration of a number of different issues including reliability, validity, appropriateness for use with a specific group or culture, availability, and potential cost. Sometimes, social workers will attempt to create their own set of questions to tap into or measure a concept. This may appear to be an easy thing to do; however, writing questions to measure a phenomenon is more challenging than it would seem. For example, how do we know it measures what we want it to measure?  In the first discussion this week, you will have the opportunity to create your own questions to measure a phenomenon of your interest. In the second discussion, you will compare the measure you created with an existing instrument that measures the same phenomenon.

To prepare: Choose one phenomenon or issue that a client may be dealing with (for example, depression, anxiety, or family conflict). Consider how you would evaluate the client’s progress in this area. Create questions with response options that would capture this phenomenon or client issue.


By Day 3

· Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.

· Provide at least 3 questions you would use to measure this phenomenon and explain how these questions operationalize the phenomenon.

· Define reliability in 2-3 sentences and give one example of how you would establish reliability for the questions you created.

· Define validity in 2-3 sentences and give one example of how you would establish validity for the questions you created.

· Create a measurement plan to assess the phenomenon.

· Describe the methodology you would use to collect data using your measurement tool (your method for acquiring this research data).

· Explain the advantages and disadvantages of your choices. Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.





Discussion 2: Evaluating Existing Measures



In discussion 1, you considered how you might create an instrument for measuring a phenomenon or client issue. For this week’s Discussion 2, choose and evaluate an existing instrument to measure the concept you identified in Discussion 1. Consider how you would compare your original measurement to the existing measurement.

To Prepare: Review the following at the Walden Library on how to find existing instruments:


By Day 5

Post a brief explanation of the existing measurement instrument that you identified. Then, compare your original measurement approach to the existing instrument. Next, explain how you would revise or replace your original measurement plan. Finally explain the advantages and/or disadvantages of using existing instruments for measurement. Please use the Learning Resources to support your answer.



















Yegidis, B. L., Weinbach, R. W., & Myers, L. L. (2018). Research methods for social workers (8th ed.). New York, NY: Pearson.

· Chapter 10, “Measurements Concepts and Issues” (pp. 223-245)

· Chapter 11,” Methods for Acquiring Research Data” (pp. 246-275)

· Chapter 12, “Data Collection Instruments” (pp. 277-294)



A methodological review of resilience measurement scales.


Windle, Gill1 Bennett, Kate M.Noyes, Jane3


Health & Quality of Life Outcomes. 2011, Vol. 9 Issue 1, p8-25. 18p.























A methodological review of resilience measurement scales Gill Windle1*, Kate M Bennett2 , Jane Noyes3 Abstract Background: The evaluation of interventions and policies designed to promote resilience, and research to understand the determinants and associations, require reliable and valid measures to ensure data quality. This paper systematically reviews the psychometric rigour of resilience measurement scales developed for use in general and clinical populations. Methods: Eight electronic abstract databases and the internet were searched and reference lists of all identified papers were hand searched. The focus was to identify peer reviewed journal articles where resilience was a key focus and/or is assessed. Two authors independently extracted data and performed a quality assessment of the scale psychometric properties. Results: Nineteen resilience measures were reviewed; four of these were refinements of the original measure. All the measures had some missing information regarding the psychometric properties. Overall, the Connor-Davidson Resilience Scale, the Resilience Scale for Adults and the Brief Resilience Scale received the best psychometric ratings. The conceptual and theoretical adequacy of a number of the scales was questionable. Conclusion: We found no current ‘gold standard’ amongst 15 measures of resilience. A number of the scales are in the early stages of development, and all require further validation work. Given increasing interest in resilience from major international funders, key policy makers and practice, researchers are urged to report relevant validation statistics when using the measures. Background International research on resilience has increased substantially over the past two decades [1], following dissatisfaction with ‘deficit’ models of illness and psychopathology [2]. Resilience is now also receiving increasing interest from policy and practice [3,4] in relation to its potential influence on health, well-being and quality of life and how people respond to the various challenges of the ageing process. Major international funders, such as the Medical Research Council and the Economic and Social Research Council in the UK [5] have identified resilience as an important factor for lifelong health and well-being. Resilience could be the key to explaining resistance to risk across the lifespan and how people ‘bounce back’ and deal with various challenges presented from childhood to older age, such as ill-health. Evaluation of interventions and policies designed to promote resilience require reliable and valid measures. Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.

However the complexity of defining the construct of resilience has been widely recognised [6-8] which has created considerable challenges when developing an operational definition of resilience. Different approaches to measuring resilience across studies have lead to inconsistencies relating to the nature of potential risk factors and protective processes, and in estimates of prevalence ([1,6]. VanderbiltAdriance and Shaw’s review [9] notes that the proportions found to be resilient varied from 25% to 84%. This creates difficulties in comparing prevalence across studies, even if study populations experience similar adversities. This diversity also raises questions about the extent to which resilience researchers are measuring resilience, or an entirely different experience. * Correspondence: 1 Dementia Services Development Centre, Institute of Medical and Social Care Research, Bangor University, Ardudwy, Holyhead Road, Bangor, LL56 2PX Gwynedd, UK Full list of author information is available at the end of the article Windle et al. Health and Quality of Life Outcomes 2011, 9:8 © 2011 Windle et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. One of the main tasks of the Resilience and Healthy Ageing Network, funded by the UK Cross-Council programme for Life Long Health and Wellbeing (of which the authors are members), was to contribute to the debate regarding definition and measurement. As part of the work programme, the Network examined how resilience could best be defined and measured in order to better inform research, policy and practice. An extensive review of the literature and concept analysis of resilience research adopts the following definition. Resilience is the process of negotiating, managing and adapting to significant sources of stress or trauma. Assets and resources within the individual, their life and environment facilitate this capacity for adaptation and ‘bouncing back’ in the face of adversity. Across the life course, the experience of resilience will vary [10]. This definition, derived from a synthesis of over 270 research articles, provides a useful benchmark for understanding the operationalisation of resilience for measurement. This parallel paper reports a methodological review focussing on the measurement of resilience. One way of ensuring data quality is to only use resilience measures which have been validated. This requires the measure to undergo a validation procedure, demonstrating that it accurately measures what it aims to do, regardless of who responds (if for all the population), when they respond, and to whom they respond. The validation procedure should establish the range of and reasons for inaccuracies and potential sources of bias. It should also demonstrate that it is well accepted by responders and that items accurately reflect the underlying concepts and theory. Ideally, an independent ‘gold standard’ should be available when developing the questionnaire [11,12]. Other research has clearly demonstrated the need for reliable and valid measures. For example Marshall et al. [13] found that clinical trials evaluating interventions for people with schizophrenia were almost 40% more likely to report that treatment was effective when they used unpublished scales as opposed to validated measures. Thus there is a strong case for the development, evaluation and utilisation of valid measures. Although a number of scales have been developed for measuring resilience, they are not widely adopted and no one scale is preferable over the others [14]. Consequently, researchers and clinicians have little robust evidence to inform their choice of a resilience measure and may make an arbitrary and inappropriate selection for the population and context. Methodological reviews aim to identify, compare and critically assess the validity and psychometric properties of conceptually similar scales, and make recommendations about the most appropriate use for a specific population, intervention and outcome. Fundamental to the robustness of a methodological review are the quality criteria used to distinguish the measurement properties of a scale to enable a meaningful comparison [15]. An earlier review of instruments measuring resilience compared the psychometric properties and appropriateness of six scales for the study of resilience in adolescents [16]. Although their search strategy was thorough, their quality assessment criteria were found to have weaknesses. The authors reported the psychometric properties of the measures (e.g. reliability, validity, internal consistency). However they did not use explicit quality assessment criteria to demonstrate what constitutes good measurement properties which in turn would distinguish what an acceptable internal consistency co-efficient might be, or what proportion of the lowest and highest scores might indicate floor or ceiling effects. On that basis, the review fails to identify where any of the scales might lack specific psychometric evidence, as that judgement is left to the reader. The lack of a robust evaluation framework in the work of Ahern et al. [16] creates difficulties for interpreting overall scores awarded by the authors to each of the measures. Each measure was rated on a scale of one to three according to the psychometric properties presented, with a score of one reflecting a measure that is not acceptable, two indicating that the measure may be acceptable in other populations, but further work is needed with adolescents, and three indicating that the measure is acceptable for the adolescent population on the basis of the psychometric properties. Under this criteria only one measurement scale, the Resilience Scale [17] satisfied this score fully. Although the Resilience Scale has been applied to younger populations, it was developed using qualitative data from older women. More rigorous approaches to content validity advocate that the target group should be involved with the item selection when measures are being developed[11,15]. Thus applying a more rigorous criterion for content validity could lead to different conclusions. In order to address known methodological weaknesses in the current evidence informing practice, this paper reports a methodological systematic review of resilience measurement scales, using published quality assessment criteria to evaluate psychometric properties[15]. The comprehensive set of quality criteria was developed for the purpose of evaluating psychometric properties of health status measures and address content validity, internal consistency, criterion validity, construct validity, reproducibility, responsiveness, floor and ceiling effects and interpretability (see Table 1). In addition to strengthening the previous review, it updates it to the current, and by identifying scales that have been applied to all populations (not just adolescents) it contributes an important addition to the current evidence ba