A longitudinal evaluation of the acceptability and impact of a diet diary app for older adults with age-related macular degeneration

Ongoing advances in technology are increasing the scope for enhancing and supporting older adults’ daily living. The digital divide between older and younger adults raises concerns, however, about the suitability of technological solutions for older adults, especially for those with impairments. Taking older adults with Age-Related Macular Degeneration (AMD) as a case study, we used user-centred and participatory design approaches to develop an assistive mobile app for self-monitoring their intake of food [12,13]. In this paper we report on findings of a longitudinal field evaluation of our app that was conducted to investigate how it was received and adopted by older adults with AMD and its impact on their lives. Demonstrating the benefit of applying inclusive design methods for technology for older adults, our findings reveal how the use of the app raises participants’ awareness and facilitates self-monitoring of diet, encourages positive (diet) behaviour change, and encourages learning.

Clinical evaluation of the Grand Seiko Auto Ref/Keratometer WAM-5500

Purpose: A clinical evaluation of the Grand Seiko Auto Ref/Keratometer WAM-5500 (Japan) was performed to evaluate validity and repeatability compared with non-cycloplegic subjective refraction and Javal–Schiotz keratometry. An investigation into the dynamic recording capabilities of the instrument was also conducted. Methods: Refractive error measurements were obtained from 150 eyes of 75 subjects (aged 25.12 ± 9.03 years), subjectively by a masked optometrist, and objectively with the WAM-5500 at a second session. Keratometry measurements from the WAM-5500 were compared to Javal–Schiotz readings. Intratest variability was examined on all subjects, whilst intertest variability was assessed on a subgroup of 44 eyes 7–14 days after the initial objective measures. The accuracy of the dynamic recording mode of the instrument and its tolerance to longitudinal movement was evaluated using a model eye. An additional evaluation of the dynamic mode was performed using a human eye in relaxed and accommodated states. Results: Refractive error determined by the WAM-5500 was found to be very similar (p = 0.77) to subjective refraction (difference, -0.01 ± 0.38 D). The instrument was accurate and reliable over a wide range of refractive errors (-6.38 to +4.88 D). WAM-5500 keratometry values were steeper by approximately 0.05 mm in both the vertical and horizontal meridians. High intertest repeatability was demonstrated for all parameters measured: for sphere, cylinder power and MSE, over 90% of retest values fell within ±0.50 D of initial testing. In dynamic (high-speed) mode, the root-mean-square of the fluctuations was 0.005 ± 0.0005 D and a high level of recording accuracy was maintained when the measurement ring was significantly blurred by longitudinal movement of the instrument head. Conclusion: The WAM-5500 Auto Ref/Keratometer represents a reliable and valid objective refraction tool for general optometric practice, with important additional features allowing pupil size determination and easy conversion into high-speed mode, increasing its usefulness post-surgically following accommodating intra-ocular lens implantation, and as a research tool in the study of accommodation.

Assessing an experimental approach to industrial policy evaluation:Applying RCT+ to the case of Creative Credits

Experimental methods of policy evaluation are well-established in social policy and development eco-nomics but are rare in industrial and innovation policy. In this paper, we consider the arguments forapplying experimental methods to industrial policy measures, and propose an experimental policy eval-uation approach (which we call RCT+). This approach combines the randomised assignment of firmsto treatment and control groups with a longitudinal data collection strategy incorporating quantitativeand qualitative data (so-called mixed methods). The RCT+ approach is designed to provide a causativerather than purely summative evaluation, i.e. to assess both ‘whether’ and ‘how’ programme outcomesare achieved. In this paper, we assess the RCT+ approach through an evaluation of Creative Credits – aUK business-to-business innovation voucher initiative intended to promote new innovation partnershipsbetween SMEs and creative service providers. The results suggest the potential value of the RCT+ approachto industrial policy evaluation, and the benefits of mixed methods and longitudinal data collection.

The Long-Term impact of Business Support? - Exploring the Role of Evaluation Timing using Micro Data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

The long-term impact of business support? - Exploring the role of evaluation timing using micro data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.