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Older adults who are or have been incarcerated constitute a growing population in the USA. The complex health needs of this group are often inadequately addressed during incarceration and equally so when transitioning back to the community. The purpose of this paper is to discuss the literature on challenges older adults (age 50 and over) face in maintaining health and accessing social services to support health after an incarceration and to outline recommendations to address the most urgent of these needs.

This study conducted a narrative literature review to identify the complex health conditions and health services needs of incarcerated older adults in the USA and outline three primary barriers they face in accessing health care and social services during reentry.

Challenges to healthy reentry of older adults include continuity of health care; housing availability; and access to health insurance, disability and other support. The authors recommend policy changes to improve uniformity of care, development of support networks and increased funding to ensure that older adults reentering communities have access to resources necessary to safeguard their health and safety.

This review presents a broad perspective of the current literature on barriers to healthy reentry for older adults in the USA and offers valuable system, program and policy recommendations to address those barriers.

This article surveys the literature dealing with theory and applications of life cycle costing (LCC). It deals with the literature published in the last 25 years and provides 667 references.

The purpose of this paper is to examine both the Latino/Hispanic entrepreneurs’ social media adoption (SMA) for business purposes and the influence of culture on personal versus business social network platform (SNP) selection.

The Technology Acceptance Model’s (TAM) factors of perceived usefulness (PU) and perceived ease of use (PEU) as drivers of Latino/Hispanic entrepreneurs’ social network platform selection are examined as well as the effect of SMA on revenue. Data was collected from 633 small business owners across the United States via an online survey administered in English and Spanish.

Results indicate that Latino/Hispanic business owners use personal SNP more than business SNP for business purposes. PU and PEU were not found to predict personal SNP for Latino/Hispanic entrepreneurs. However, for Non-Latino/Hispanics, PU was significant while PEU was marginally significant. Findings for PU and PEU as predictors of business SNP indicate similar results for both Latino/Hispanic and non-Latino/Hispanic entrepreneurs, where only PEU was significant. Finally, there was no relationship between either business or personal SNP and revenue for either Latino/Hispanic or non-Latino/Hispanic entrepreneurs.

This research provides more insight into Latino/Hispanic entrepreneurs’ self-directed engagement in personal SNP (Facebook) and business SNP (LinkedIn) for business purposes and invites future research in this population to further examine cultural influence and business performance. The findings support the need for Latino/Hispanic entrepreneurs’ strengthening their competency in social media usage to remain competitive, as doing so will enhance their capability for building customer relationships, brand development, and equity financing.

This investigation 1) examines SMA’s role in Latino/Hispanic small and medium enterprises (SMEs); 2) distinguishes between personal and business social network platforms; 3) investigates TAM’s relevance for Latino/Hispanic entrepreneurs’ use of social media for business; and 4) explores SME social media usage as a predictor of revenue. We seek to provide practitioners with a greater understanding of how they may influence business success and sustainability through better competency development and usage of social media platforms.

A new research domain known as the Quantified Self has recently emerged and is described as gaining self-knowledge through using wearable technology to acquire information on self-monitoring activities and physical health related problems. However, very little is known about the impact of time window models on discovering self-quantified patterns that can yield new self-knowledge insights. This paper aims to discover the self-quantified patterns using multi-time window models.

This paper proposes a multi-time window analytical workflow developed to support the streaming k-means clustering algorithm, based on an online/offline approach that combines both sliding and damped time window models. An intervention experiment with 15 participants is used to gather Fitbit data logs and implement the proposed analytical workflow.

The clustering results reveal the impact of a time window model has on exploring the evolution of micro-clusters and the labelling of macro-clusters to accurately explain regular and irregular individual physical behaviour.

The preliminary results demonstrate the impact they have on finding meaningful patterns.

We have conducted a study of academic faculty use of databases for research, their need for evaluative guides to databases, and the appropriateness of currently‐available guides. Although the response rate was low (19%), the follow‐up survey suggested only a minimal non‐response bias. Our findings suggest that academic faculty are typically unaware of the range of databases available and few recognize the need for databases in research. Of those faculty who do use databases, most delegate the searching to a librarian or an assistant, rather than performing the searches themselves. We identified thirty‐nine database guides; these tend to be descriptive rather than evaluative.