Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 3 / 3 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 22 Oct 2026 01:26 UTC — 22 Oct 2026 06:26 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 52 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 98 | 3 | 3/3 | 3/3 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 3 / 3 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-22T01:26:31.517605+00:00 — 2026-10-22T06:26:48.955594+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 3 | 3/3 |
| 2018 | All selected publications | 0 | 3 | 3/3 |
| 2019 | All selected publications | 0 | 3 | 3/3 |
| 2020 | All selected publications | 5 | 3 | 3/3 |
| 2021 | All selected publications | 33 | 3 | 3/3 |
| 2022 | All selected publications | 18 | 3 | 3/3 |
| 2023 | All selected publications | 18 | 3 | 3/3 |
| 2024 | All selected publications | 17 | 3 | 3/3 |
| 2025 | All selected publications | 6 | 3 | 3/3 |
| 2026 | All selected publications | 1 | 3 | 3/3 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2020 | 3 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Research in Business and Social Science SSBFNET | 3 | 52 | 98 | 3/3 | 17.33 | 6 | 66.7 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
Experiencing a pandemic and being quarantined have been proven to have debilitating effects in mental health. Some of the existing studies mentioned in this research have been conducted to assess the presence of possible mental health concerns brought about by the pandemic but most of these studies focused on the earlier phase of the pandemic. The present study focuses on the reported distress of the respondents who have been through a strict quarantine since March 2020 and are now experiencing a more relaxed lockdown. The objective of this research is to determine if COVID stress predicts common mental health concerns such as stress, depression and anxiety. A survey was conducted with 421 Filipino respondents ages 15 – 65 utilizing the COVID Stress Scales (CSS) by Taylor et al. (2020) and DASS-21. Correlational analysis was utilized showing the COVID Stress is a predictor of depression, anxiety, and stress symptoms. Then, comparative analyses were conducted to determine if differences of COVID stress across age groups, gender, occupation, and exposure. The results show that students and unemployed respondents are highly vulnerable to COVID stress and its mental health implications. Men and women did not significantly differ in distress. Surprisingly, those who have a COVID positive family member had the lowest COVID stress and DASS scores. There were 40.7% percent who experienced moderate to severe stress, 60.3% had moderate to severe anxiety and 53.1% of the respondents had moderate to severe depression. These findings show that the pandemic stress has debilitating effects on mental health. Common mental health concerns (e.g. depression and anxiety) may be highly prevalent due to the COVID-19 pandemic
The aim of this study is to explore how COVID-19 influences the mental health of old age employees by posing challenges to psychological resilience thus affecting their work engagement. The data was collected from three countries, China, Pakistan, and the UK, through eighteen semi-structured interviews. Three sub-themes emerged under the core theme of “psychological challenges”: “cognitive challenges”, “physical challenges”, and “behavioral challenges”. Similarly, “individual resilience” and “group resilience” emerged under the core theme of “psychological resilience”. The results showed that the mental health of old age employees without having any medical complications was also affected during the pandemic thus resulting in low work engagement. The data was collected from three countries namely China, Pakistan, and the UK. Furthermore, data were collected through telephonic interviews so some aspects of the study might be left unexplored which can only be possible through face to face interaction. This study, in line with the previous literature, indicate that challenges explored related to COVID-19 can significantly influence the mental wellbeing of aging employees. The study also encourages employers to understand the limitations of aging employees and develop flexible policies that can have a positive impact on work engagement. The study presents a novel approach contributing to the knowledge gap of COVID-19 impact on wellbeing and work engagement of healthy but senescent employees.
In this study, 403 participants were asked questions to determine the preventive measures being taken and anxiety levels during COVID-19 Pandemic. Participants were almost equally divided between women (55%) and men (45%). The rate of most worried persons about the pandemic was 62%. The risk of anxiety of women compared to men has been calculated as 2.1 times higher (95% CI 1.20–3.84). The Cramer’s V value of the change in hand-washing habit before and after COVID-19 outbreak is 0.706, indicates the existence of a strong relationship. The data is analysed by using SPSS 24.0. ODDS Ratio values are calculated to determine the impact levels, and Cramer’s V value is calculated to determine the relationship in behavior change in hand-washings habits.
The aim of this study is to explore how COVID-19 influences the mental health of old age employees by posing challenges to psychological resilience thus affecting their work engagement. The data was collected from three countries, China, Pakistan, and the UK, through eighteen semi-structured interviews. Three sub-themes emerged under the core theme of “psychological challenges”: “cognitive challenges”, “physical challenges”, and “behavioral challenges”. Similarly, “individual resilience” and “group resilience” emerged under the core theme of “psychological resilience”. The results showed that the mental health of old age employees without having any medical complications was also affected during the pandemic thus resulting in low work engagement. The data was collected from three countries namely China, Pakistan, and the UK. Furthermore, data were collected through telephonic interviews so some aspects of the study might be left unexplored which can only be possible through face to face interaction. This study, in line with the previous literature, indicate that challenges explored related to COVID-19 can significantly influence the mental wellbeing of aging employees. The study also encourages employers to understand the limitations of aging employees and develop flexible policies that can have a positive impact on work engagement. The study presents a novel approach contributing to the knowledge gap of COVID-19 impact on wellbeing and work engagement of healthy but senescent employees.
Experiencing a pandemic and being quarantined have been proven to have debilitating effects in mental health. Some of the existing studies mentioned in this research have been conducted to assess the presence of possible mental health concerns brought about by the pandemic but most of these studies focused on the earlier phase of the pandemic. The present study focuses on the reported distress of the respondents who have been through a strict quarantine since March 2020 and are now experiencing a more relaxed lockdown. The objective of this research is to determine if COVID stress predicts common mental health concerns such as stress, depression and anxiety. A survey was conducted with 421 Filipino respondents ages 15 – 65 utilizing the COVID Stress Scales (CSS) by Taylor et al. (2020) and DASS-21. Correlational analysis was utilized showing the COVID Stress is a predictor of depression, anxiety, and stress symptoms. Then, comparative analyses were conducted to determine if differences of COVID stress across age groups, gender, occupation, and exposure. The results show that students and unemployed respondents are highly vulnerable to COVID stress and its mental health implications. Men and women did not significantly differ in distress. Surprisingly, those who have a COVID positive family member had the lowest COVID stress and DASS scores. There were 40.7% percent who experienced moderate to severe stress, 60.3% had moderate to severe anxiety and 53.1% of the respondents had moderate to severe depression. These findings show that the pandemic stress has debilitating effects on mental health. Common mental health concerns (e.g. depression and anxiety) may be highly prevalent due to the COVID-19 pandemic
In this study, 403 participants were asked questions to determine the preventive measures being taken and anxiety levels during COVID-19 Pandemic. Participants were almost equally divided between women (55%) and men (45%). The rate of most worried persons about the pandemic was 62%. The risk of anxiety of women compared to men has been calculated as 2.1 times higher (95% CI 1.20–3.84). The Cramer’s V value of the change in hand-washing habit before and after COVID-19 outbreak is 0.706, indicates the existence of a strong relationship. The data is analysed by using SPSS 24.0. ODDS Ratio values are calculated to determine the impact levels, and Cramer’s V value is calculated to determine the relationship in behavior change in hand-washings habits.
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |