The Development of a Holistic and Quantitative Tool for the Assessment and Improvement of Survey Quality.

There are a variety of guidelines and methods available to measure and assess survey quality. Most of these are based on qualitative descriptions. In practice, they are not easy to implement and it is very difficult to make comparisons between surveys. Hence there is a theoretical and pragmatic demand to develop a mainly quantitative based survey assessment tool. This research aimed to meet this need and make contributions to the evaluation and improvement of survey quality. Acknowledging the critical importance of measurement issues in survey research, this thesis starts with a comprehensive introduction to measurement theory and identifies the types of measurement errors associated with measurement procedures through three experiments. Then it moves on to describe concepts, guidelines and methods available for measuring and assessing survey quality. Combining these with measurement principles leads to the development of a quantitative based statistical holistic tool to measure and assess survey quality. The criteria, weights and subweights for the assessment tool are determined using Multi-Criteria Decision-Making (MCDM) and a survey questionnaire based on the Delphi method. Finally the model is applied to a database of surveys which was constructed to develop methods of classification, assessment and improvement of survey quality. The model developed in this thesis enables survey researchers and/or commissioners to make a holistic assessment of the value of the particular survey(s). This model is an Excel based audit which takes a holistic approach, following all stages of the survey from inception, to design, construction, execution, analysis and dissemination. At each stage a set of criteria are applied to assess quality. Scores attained against these assessments are weighted by the importance of the criteria and summed to give an overall assessment of the stage. The total score for a survey can be obtained by a combination of the scores for every stage weighted again by the importance of each stage. The advantage of this is to construct a means of survey assessment which can be used in a diagnostic manner to assess and improve survey quality.

Interactive support effects on career agency and occupational engagement among young adults.

The PIC model by Gati and Asher describes three career decision making stages: pre-screening, in-depth exploration, and choice of career options. We consider the role that three different forms of support (general career support by parents, emotional/instrumental support, and informational support) may play for young adults in each of these three decision-making stages. The authors further propose that different forms of support may predict career agency and occupational engagement, which are important career decision precedents. In addition, we consider the role of personality traits and perceptions (decision-making window) on these two outcomes. Using an online survey sample (N = 281), we found that general career support was important for career agency and occupational engagement. However, it was the combination of higher general career support with either emotional/instrumental support or informational support that was found to lead to both greater career agency and higher occupational engagement. Personality also played a role: Greater proactivity also led to greater occupational engagement, even when there was little urgency for participants to make decisions (window of decision-making was wide open and not restricted). In practical terms, the findings suggest that the learning required in each of the three PIC processes (pre-screening, in-depth exploration, choice of career options may benefit when the learner has access to the three support measures.